[ 2019-03-21 16:52:40,876 ] [ DEBUG ] [ main:133 ] Namespace(batch=None, data_type='float', disable_fusing=False, disable_gfusing=False, disable_nhwc_to_nchw=False, disable_resnet_optimization=False, extensions='/home/sweta/intel/computer_vision_sdk_2018.5.455/deployment_tools/model_optimizer/extensions', finegrain_fusing=None, framework='tf', freeze_placeholder_with_value=None, generate_deprecated_IR_V2=False, input='input1,input2', input_checkpoint=None, input_meta_graph=None, input_model='/home/sweta/Desktop/12-3-19/fall_v1.1/frozen_model_1.pb', input_model_is_text=False, input_shape='[1,30,128],[1,30,28]', log_level='DEBUG', mean_values=(), model_name=None, move_to_preprocess=False, offload_unsupported_operations_to_tf=False, output='output', output_dir='/home/sweta/intel/computer_vision_sdk_2018.5.455/deployment_tools/model_optimizer/irmodels', reverse_input_channels=False, saved_model_dir=None, saved_model_tags=None, scale=None, scale_values=(), silent=False, tensorboard_logdir=None, tensorflow_custom_layer_libraries=None, tensorflow_custom_operations_config_update=None, tensorflow_object_detection_api_pipeline_config=None, tensorflow_operation_patterns=None, tensorflow_subgraph_patterns=None, tensorflow_use_custom_operations_config=None, version=False) [ 2019-03-21 16:52:40,876 ] [ DEBUG ] [ main:134 ] Model Optimizer started [ 2019-03-21 16:52:40,876 ] [ DEBUG ] [ main:148 ] Output model name would be frozen_model_1{.xml, .bin} Model Optimizer arguments: Common parameters: - Path to the Input Model: /home/sweta/Desktop/12-3-19/fall_v1.1/frozen_model_1.pb - Path for generated IR: /home/sweta/intel/computer_vision_sdk_2018.5.455/deployment_tools/model_optimizer/irmodels - IR output name: frozen_model_1 - Log level: DEBUG - Batch: Not specified, inherited from the model - Input layers: input1,input2 - Output layers: output - Input shapes: [1,30,128],[1,30,28] - Mean values: Not specified - Scale values: Not specified - Scale factor: Not specified - Precision of IR: FP32 - Enable fusing: True - Enable grouped convolutions fusing: True - Move mean values to preprocess section: False - Reverse input channels: False TensorFlow specific parameters: - Input model in text protobuf format: False - Offload unsupported operations: False - Path to model dump for TensorBoard: None - List of shared libraries with TensorFlow custom layers implementation: None - Update the configuration file with input/output node names: None - Use configuration file used to generate the model with Object Detection API: None - Operations to offload: None - Patterns to offload: None - Use the config file: None Model Optimizer version: 1.5.12.49d067a0 [ 2019-03-21 16:52:42,643 ] [ DEBUG ] [ main:236 ] Placeholder shapes : {'input1': array([ 1, 30, 128]), 'input2': array([ 1, 30, 28])} [ INFO ] Importing extensions from: /home/sweta/intel/computer_vision_sdk_2018.5.455/deployment_tools/model_optimizer/mo [ INFO ] New subclass: [ INFO ] Registered a new subclass with key: Const [ INFO ] New subclass: [ INFO ] Registered a new subclass with key: LSTMCell [ INFO ] New subclass: [ INFO ] Registered a new subclass with key: OpOutput [ INFO ] New subclass: [ INFO ] Registered a new subclass with key: Reshape [ INFO ] New subclass: [ INFO ] Registered a new subclass with key: TensorIteratorInput [ INFO ] New subclass: [ INFO ] Registered a new subclass with key: TensorIteratorOutput [ INFO ] New subclass: [ INFO ] Registered a new subclass with key: TensorIteratorCondition [ INFO ] New subclass: [ INFO ] Registered a new subclass with key: TensorIteratorBackEdge [ INFO ] New subclass: [ INFO ] Registered a new subclass with key: TensorIterator [ INFO ] New subclass: [ INFO ] Registered a new subclass with key: Shape [ WARNING ] Skipped registration because it was already registered or it was disabled. [ INFO ] New subclass: [ INFO ] Registered a new subclass with key: ReLU [ WARNING ] Skipped registration because it was already registered or it was disabled. [ INFO ] New subclass: [ INFO ] Registered a new subclass with key: Activation [ INFO ] New subclass: [ INFO ] Registered a new subclass with key: Clamp [ INFO ] New subclass: [ INFO ] Registered a new subclass with key: Concat [ INFO ] New subclass: [ INFO ] Registered a new subclass with key: Convolution [ INFO ] New subclass: [ INFO ] Registered a new subclass with key: Crop [ INFO ] New subclass: [ INFO ] Registered a new subclass with key: Deconvolution [ INFO ] New subclass: [ INFO ] Registered a new subclass with key: Eltwise [ WARNING ] Skipped registration because it was already registered or it was disabled. [ INFO ] New subclass: [ INFO ] Registered a new subclass with key: EltwiseN [ WARNING ] Skipped registration because it was already registered or it was disabled. [ INFO ] New subclass: [ INFO ] Registered a new subclass with key: Flatten [ INFO ] New subclass: [ INFO ] Registered a new subclass with key: FlattenONNX [ INFO ] New subclass: [ INFO ] Registered a new subclass with key: FullyConnected [ INFO ] New subclass: [ INFO ] Registered a new subclass with key: Input [ WARNING ] Skipped registration because it was already registered or it was disabled. [ INFO ] New subclass: [ INFO ] Registered a new subclass with key: Memory [ INFO ] New subclass: [ INFO ] Registered a new subclass with key: Pad [ INFO ] New subclass: [ INFO ] Registered a new subclass with key: Pooling [ WARNING ] Skipped registration because it was already registered or it was disabled. [ WARNING ] Skipped registration because it was already registered or it was disabled. [ INFO ] New subclass: [ INFO ] Registered a new subclass with key: ScaleShift [ INFO ] New subclass: [ INFO ] Registered a new subclass with key: Slice [ INFO ] New subclass: [ INFO ] Registered a new subclass with key: SoftMax [ INFO ] New subclass: [ INFO ] Registered a new subclass with key: Split [ WARNING ] Skipped registration because it was already registered or it was disabled. [ INFO ] New subclass: [ INFO ] Registered a new subclass with key: Tile [ WARNING ] Skipped registration because it was already registered or it was disabled. [ INFO ] New subclass: [ INFO ] Registered a new subclass with key: Div [ INFO ] New subclass: [ INFO ] New subclass: [ INFO ] New subclass: [ INFO ] Registered a new subclass with key: UnknownOp [ WARNING ] Skipped registration because it was already registered or it was disabled. [ INFO ] New subclass: [ INFO ] New subclass: [ INFO ] New subclass: [ INFO ] New subclass: [ INFO ] New subclass: [ INFO ] New subclass: [ WARNING ] Skipped registration because it was already registered or it was disabled. [ WARNING ] Skipped registration because it was already registered or it was disabled. [ INFO ] New subclass: [ INFO ] New subclass: [ INFO ] New subclass: [ INFO ] New subclass: [ INFO ] New subclass: [ WARNING ] Skipped registration because it was already registered or it was disabled. [ WARNING ] Skipped registration because it was already registered or it was disabled. [ WARNING ] Skipped registration because it was already registered or it was disabled. [ INFO ] New subclass: [ INFO ] New subclass: [ INFO ] New subclass: [ WARNING ] Skipped registration because it was already registered or it was disabled. [ WARNING ] Skipped registration because it was already registered or it was disabled. [ WARNING ] Skipped registration because it was already registered or it was disabled. [ WARNING ] Skipped registration because it was already registered or it was disabled. [ WARNING ] Skipped registration because it was already registered or it was disabled. [ WARNING ] Skipped registration because it was already registered or it was disabled. [ WARNING ] Skipped registration because it was already registered or it was disabled. [ WARNING ] Skipped registration because it was already registered or it was disabled. [ WARNING ] Skipped registration because it was already registered or it was disabled. [ WARNING ] Skipped registration because it was already registered or it was disabled. [ WARNING ] Skipped registration because it was already registered or it was disabled. [ WARNING ] Skipped registration because it was already registered or it was disabled. [ WARNING ] Skipped registration because it was already registered or it was disabled. [ WARNING ] Skipped registration because it was already registered or it was disabled. [ WARNING ] Skipped registration because it was already registered or it was disabled. [ WARNING ] Skipped registration because it was already registered or it was disabled. [ WARNING ] Skipped registration because it was already registered or it was disabled. [ WARNING ] Skipped registration because it was already registered or it was disabled. [ WARNING ] Skipped registration because it was already registered or it was disabled. [ WARNING ] Skipped registration because it was already registered or it was disabled. [ WARNING ] Skipped registration because it was already registered or it was disabled. [ WARNING ] Skipped registration because it was already registered or it was disabled. [ WARNING ] Skipped registration because it was already registered or it was disabled. [ WARNING ] Skipped registration because it was already registered or it was disabled. [ WARNING ] Skipped registration because it was already registered or it was disabled. [ WARNING ] Skipped registration because it was already registered or it was disabled. [ WARNING ] Skipped registration because it was already registered or it was disabled. [ WARNING ] Skipped registration because it was already registered or it was disabled. [ WARNING ] Skipped registration because it was already registered or it was disabled. [ WARNING ] Skipped registration because it was already registered or it was disabled. [ WARNING ] Skipped registration because it was already registered or it was disabled. [ WARNING ] Skipped registration because it was already registered or it was disabled. [ WARNING ] Skipped registration because it was already registered or it was disabled. [ WARNING ] Skipped registration because it was already registered or it was disabled. [ WARNING ] Skipped registration because it was already registered or it was disabled. [ WARNING ] Skipped registration because it was already registered or it was disabled. [ WARNING ] Skipped registration because it was already registered or it was disabled. [ WARNING ] Skipped registration because it was already registered or it was disabled. [ WARNING ] Skipped registration because it was already registered or it was disabled. [ WARNING ] Skipped registration because it was already registered or it was disabled. [ WARNING ] Skipped registration because it was already registered or it was disabled. [ WARNING ] Skipped registration because it was already registered or it was disabled. [ WARNING ] Skipped registration because it was already registered or it was disabled. [ WARNING ] Skipped registration because it was already registered or it was disabled. [ WARNING ] Skipped registration because it was already registered or it was disabled. [ WARNING ] Skipped registration because it was already registered or it was disabled. [ WARNING ] Skipped registration because it was already registered or it was disabled. [ WARNING ] Skipped registration because it was already registered or it was disabled. [ WARNING ] Skipped registration because it was already registered or it was disabled. [ WARNING ] Skipped registration because it was already registered or it was disabled. [ WARNING ] Skipped registration because it was already registered or it was disabled. [ WARNING ] Skipped registration because it was already registered or it was disabled. [ WARNING ] Skipped registration because it was already registered or it was disabled. [ WARNING ] Skipped registration because it was already registered or it was disabled. [ WARNING ] Skipped registration because it was already registered or it was disabled. [ WARNING ] Skipped registration because it was already registered or it was disabled. [ WARNING ] Skipped registration because it was already registered or it was disabled. [ WARNING ] Skipped registration because it was already registered or it was disabled. [ WARNING ] Skipped registration because it was already registered or it was disabled. [ WARNING ] Skipped registration because it was already registered or it was disabled. [ WARNING ] Skipped registration because it was already registered or it was disabled. [ WARNING ] Skipped registration because it was already registered or it was disabled. [ WARNING ] Skipped registration because it was already registered or it was disabled. [ WARNING ] Skipped registration because it was already registered or it was disabled. [ WARNING ] Skipped registration because it was already registered or it was disabled. [ WARNING ] Skipped registration because it was already registered or it was disabled. [ WARNING ] Skipped registration because it was already registered or it was disabled. [ WARNING ] Skipped registration because it was already registered or it was disabled. [ WARNING ] Skipped registration because it was already registered or it was disabled. [ WARNING ] Skipped registration because it was already registered or it was disabled. [ WARNING ] Skipped registration because it was already registered or it was disabled. [ WARNING ] Skipped registration because it was already registered or it was disabled. [ WARNING ] Skipped registration because it was already registered or it was disabled. [ WARNING ] Skipped registration because it was already registered or it was disabled. [ WARNING ] Skipped registration because it was already registered or it was disabled. [ WARNING ] Skipped registration because it was already registered or it was disabled. [ WARNING ] Skipped registration because it was already registered or it was disabled. [ WARNING ] Skipped registration because it was already registered or it was disabled. [ WARNING ] Skipped registration because it was already registered or it was disabled. [ WARNING ] Skipped registration because it was already registered or it was disabled. [ WARNING ] Skipped registration because it was already registered or it was disabled. [ WARNING ] Skipped registration because it was already registered or it was disabled. [ WARNING ] Skipped registration because it was already registered or it was disabled. [ WARNING ] Skipped registration because it was already registered or it was disabled. [ WARNING ] Skipped registration because it was already registered or it was disabled. [ WARNING ] Skipped registration because it was already registered or it was disabled. [ WARNING ] Skipped registration because it was already registered or it was disabled. [ WARNING ] Skipped registration because it was already registered or it was disabled. [ WARNING ] Skipped registration because it was already registered or it was disabled. [ WARNING ] Skipped registration because it was already registered or it was disabled. [ WARNING ] Skipped registration because it was already registered or it was disabled. [ WARNING ] Skipped registration because it was already registered or it was disabled. [ WARNING ] Skipped registration because it was already registered or it was disabled. [ WARNING ] Skipped registration because it was already registered or it was disabled. [ WARNING ] Skipped registration because it was already registered or it was disabled. [ WARNING ] Skipped registration because it was already registered or it was disabled. [ WARNING ] Skipped registration because it was already registered or it was disabled. [ WARNING ] Skipped registration because it was already registered or it was disabled. [ WARNING ] Skipped registration because it was already registered or it was disabled. [ WARNING ] Skipped registration because it was already registered or it was disabled. [ WARNING ] Skipped registration because it was already registered or it was disabled. [ WARNING ] Skipped registration because it was already registered or it was disabled. [ WARNING ] Skipped registration because it was already registered or it was disabled. [ WARNING ] Skipped registration because it was already registered or it was disabled. [ WARNING ] Skipped registration because it was already registered or it was disabled. [ WARNING ] Skipped registration because it was already registered or it was disabled. [ WARNING ] Skipped registration because it was already registered or it was disabled. [ WARNING ] Skipped registration because it was already registered or it was disabled. [ WARNING ] Skipped registration because it was already registered or it was disabled. [ WARNING ] Skipped registration because it was already registered or it was disabled. [ WARNING ] Skipped registration because it was already registered or it was disabled. [ WARNING ] Skipped registration because it was already registered or it was disabled. [ WARNING ] Skipped registration because it was already registered or it was disabled. [ WARNING ] Skipped registration because it was already registered or it was disabled. [ WARNING ] Skipped registration because it was already registered or it was disabled. [ WARNING ] Skipped registration because it was already registered or it was disabled. [ WARNING ] Skipped registration because it was already registered or it was disabled. [ WARNING ] Skipped registration because it was already registered or it was disabled. [ WARNING ] Skipped registration because it was already registered or it was disabled. [ WARNING ] Skipped registration because it was already registered or it was disabled. [ WARNING ] Skipped registration because it was already registered or it was disabled. [ WARNING ] Skipped registration because it was already registered or it was disabled. [ WARNING ] Skipped registration because it was already registered or it was disabled. [ WARNING ] Skipped registration because it was already registered or it was disabled. [ WARNING ] Skipped registration because it was already registered or it was disabled. [ WARNING ] Skipped registration because it was already registered or it was disabled. [ WARNING ] Skipped registration because it was already registered or it was disabled. [ WARNING ] Skipped registration because it was already registered or it was disabled. [ WARNING ] Skipped registration because it was already registered or it was disabled. [ WARNING ] Skipped registration because it was already registered or it was disabled. [ WARNING ] Skipped registration because it was already registered or it was disabled. [ WARNING ] Skipped registration because it was already registered or it was disabled. [ WARNING ] Skipped registration because it was already registered or it was disabled. [ WARNING ] Skipped registration because it was already registered or it was disabled. [ WARNING ] Skipped registration because it was already registered or it was disabled. [ WARNING ] Skipped registration because it was already registered or it was disabled. [ WARNING ] Skipped registration because it was already registered or it was disabled. [ WARNING ] Skipped registration because it was already registered or it was disabled. [ WARNING ] Skipped registration because it was already registered or it was disabled. [ WARNING ] Skipped registration because it was already registered or it was disabled. [ WARNING ] Skipped registration because it was already registered or it was disabled. [ WARNING ] Skipped registration because it was already registered or it was disabled. [ WARNING ] Skipped registration because it was already registered or it was disabled. [ WARNING ] Skipped registration because it was already registered or it was disabled. [ WARNING ] Skipped registration because it was already registered or it was disabled. [ WARNING ] Skipped registration because it was already registered or it was disabled. [ WARNING ] Skipped registration because it was already registered or it was disabled. [ WARNING ] Skipped registration because it was already registered or it was disabled. [ WARNING ] Skipped registration because it was already registered or it was disabled. [ WARNING ] Skipped registration because it was already registered or it was disabled. [ WARNING ] Skipped registration because it was already registered or it was disabled. [ WARNING ] Skipped registration because it was already registered or it was disabled. [ WARNING ] Skipped registration because it was already registered or it was disabled. [ WARNING ] Skipped registration because it was already registered or it was disabled. [ WARNING ] Skipped registration because it was already registered or it was disabled. [ WARNING ] Skipped registration because it was already registered or it was disabled. [ WARNING ] Skipped registration because it was already registered or it was disabled. [ WARNING ] Skipped registration because it was already registered or it was disabled. [ WARNING ] Skipped registration because it was already registered or it was disabled. [ WARNING ] Skipped registration because it was already registered or it was disabled. [ WARNING ] Skipped registration because it was already registered or it was disabled. [ WARNING ] Skipped registration because it was already registered or it was disabled. [ WARNING ] Skipped registration because it was already registered or it was disabled. [ WARNING ] Skipped registration because it was already registered or it was disabled. [ WARNING ] Skipped registration because it was already registered or it was disabled. [ WARNING ] Skipped registration because it was already registered or it was disabled. [ WARNING ] Skipped registration because it was already registered or it was disabled. [ WARNING ] Skipped registration because it was already registered or it was disabled. [ WARNING ] Skipped registration because it was already registered or it was disabled. [ WARNING ] Skipped registration because it was already registered or it was disabled. [ WARNING ] Skipped registration because it was already registered or it was disabled. [ WARNING ] Skipped registration because it was already registered or it was disabled. [ WARNING ] Skipped registration because it was already registered or it was disabled. [ WARNING ] Skipped registration because it was already registered or it was disabled. [ WARNING ] Skipped registration because it was already registered or it was disabled. [ WARNING ] Skipped registration because it was already registered or it was disabled. [ WARNING ] Skipped registration because it was already registered or it was disabled. [ WARNING ] Skipped registration because it was already registered or it was disabled. [ WARNING ] Skipped registration because it was already registered or it was disabled. [ WARNING ] Skipped registration because it was already registered or it was disabled. [ WARNING ] Skipped registration because it was already registered or it was disabled. [ WARNING ] Skipped registration because it was already registered or it was disabled. [ WARNING ] Skipped registration because it was already registered or it was disabled. [ WARNING ] Skipped registration because it was already registered or it was disabled. [ WARNING ] Skipped registration because it was already registered or it was disabled. [ WARNING ] Skipped registration because it was already registered or it was disabled. [ WARNING ] Skipped registration because it was already registered or it was disabled. [ WARNING ] Skipped registration because it was already registered or it was disabled. [ WARNING ] Skipped registration because it was already registered or it was disabled. [ WARNING ] Skipped registration because it was already registered or it was disabled. [ WARNING ] Skipped registration because it was already registered or it was disabled. [ WARNING ] Skipped registration because it was already registered or it was disabled. [ WARNING ] Skipped registration because it was already registered or it was disabled. [ WARNING ] Skipped registration because it was already registered or it was disabled. [ WARNING ] Skipped registration because it was already registered or it was disabled. [ WARNING ] Skipped registration because it was already registered or it was disabled. [ WARNING ] Skipped registration because it was already registered or it was disabled. [ WARNING ] Skipped registration because it was already registered or it was disabled. [ WARNING ] Skipped registration because it was already registered or it was disabled. [ WARNING ] Skipped registration because it was already registered or it was disabled. [ WARNING ] Skipped registration because it was already registered or it was disabled. [ WARNING ] Skipped registration because it was already registered or it was disabled. [ WARNING ] Skipped registration because it was already registered or it was disabled. [ WARNING ] Skipped registration because it was already registered or it was disabled. [ WARNING ] Skipped registration because it was already registered or it was disabled. [ WARNING ] Skipped registration because it was already registered or it was disabled. [ WARNING ] Skipped registration because it was already registered or it was disabled. [ WARNING ] Skipped registration because it was already registered or it was disabled. [ WARNING ] Skipped registration because it was already registered or it was disabled. [ WARNING ] Skipped registration because it was already registered or it was disabled. [ WARNING ] Skipped registration because it was already registered or it was disabled. [ WARNING ] Skipped registration because it was already registered or it was disabled. [ WARNING ] Skipped registration because it was already registered or it was disabled. [ WARNING ] Skipped registration because it was already registered or it was disabled. [ WARNING ] Skipped registration because it was already registered or it was disabled. [ WARNING ] Skipped registration because it was already registered or it was disabled. [ WARNING ] Skipped registration because it was already registered or it was disabled. [ WARNING ] Skipped registration because it was already registered or it was disabled. [ WARNING ] Skipped registration because it was already registered or it was disabled. [ WARNING ] Skipped registration because it was already registered or it was disabled. [ WARNING ] Skipped registration because it was already registered or it was disabled. [ WARNING ] Skipped registration because it was already registered or it was disabled. [ WARNING ] Skipped registration because it was already registered or it was disabled. [ WARNING ] Skipped registration because it was already registered or it was disabled. [ WARNING ] Skipped registration because it was already registered or it was disabled. [ WARNING ] Skipped registration because it was already registered or it was disabled. [ WARNING ] Skipped registration because it was already registered or it was disabled. [ WARNING ] Skipped registration because it was already registered or it was disabled. [ WARNING ] Skipped registration because it was already registered or it was disabled. [ WARNING ] Skipped registration because it was already registered or it was disabled. [ WARNING ] Skipped registration because it was already registered or it was disabled. [ WARNING ] Skipped registration because it was already registered or it was disabled. [ WARNING ] Skipped registration because it was already registered or it was disabled. [ WARNING ] Skipped registration because it was already registered or it was disabled. [ WARNING ] Skipped registration because it was already registered or it was disabled. [ WARNING ] Skipped registration because it was already registered or it was disabled. [ WARNING ] Skipped registration because it was already registered or it was disabled. [ WARNING ] Skipped registration because it was already registered or it was disabled. [ WARNING ] Skipped registration because it was already registered or it was disabled. [ WARNING ] Skipped registration because it was already registered or it was disabled. [ WARNING ] Skipped registration because it was already registered or it was disabled. [ WARNING ] Skipped registration because it was already registered or it was disabled. [ WARNING ] Skipped registration because it was already registered or it was disabled. [ WARNING ] Skipped registration because it was already registered or it was disabled. [ WARNING ] Skipped registration because it was already registered or it was disabled. [ WARNING ] Skipped registration because it was already registered or it was disabled. [ WARNING ] Skipped registration because it was already registered or it was disabled. [ WARNING ] Skipped registration because it was already registered or it was disabled. [ WARNING ] Skipped registration because it was already registered or it was disabled. [ WARNING ] Skipped registration because it was already registered or it was disabled. [ WARNING ] Skipped registration because it was already registered or it was disabled. [ WARNING ] Skipped registration because it was already registered or it was disabled. [ WARNING ] Skipped registration because it was already registered or it was disabled. [ WARNING ] Skipped registration because it was already registered or it was disabled. [ WARNING ] Skipped registration because it was already registered or it was disabled. [ WARNING ] Skipped registration because it was already registered or it was disabled. [ WARNING ] Skipped registration because it was already registered or it was disabled. [ WARNING ] Skipped registration because it was already registered or it was disabled. [ WARNING ] Skipped registration because it was already registered or it was disabled. [ WARNING ] Skipped registration because it was already registered or it was disabled. [ WARNING ] Skipped registration because it was already registered or it was disabled. [ WARNING ] Skipped registration because it was already registered or it was disabled. [ WARNING ] Skipped registration because it was already registered or it was disabled. [ WARNING ] Skipped registration because it was already registered or it was disabled. [ WARNING ] Skipped registration because it was already registered or it was disabled. [ WARNING ] Skipped registration because it was already registered or it was disabled. [ WARNING ] Skipped registration because it was already registered or it was disabled. [ WARNING ] Skipped registration because it was already registered or it was disabled. [ WARNING ] Skipped registration because it was already registered or it was disabled. [ WARNING ] Skipped registration because it was already registered or it was disabled. [ WARNING ] Skipped registration because it was already registered or it was disabled. [ WARNING ] Skipped registration because it was already registered or it was disabled. [ WARNING ] Skipped registration because it was already registered or it was disabled. [ WARNING ] Skipped registration because it was already registered or it was disabled. [ WARNING ] Skipped registration because it was already registered or it was disabled. [ WARNING ] Skipped registration because it was already registered or it was disabled. [ WARNING ] Skipped registration because it was already registered or it was disabled. [ WARNING ] Skipped registration because it was already registered or it was disabled. [ WARNING ] Skipped registration because it was already registered or it was disabled. [ WARNING ] Skipped registration because it was already registered or it was disabled. [ WARNING ] Skipped registration because it was already registered or it was disabled. [ WARNING ] Skipped registration because it was already registered or it was disabled. [ WARNING ] Skipped registration because it was already registered or it was disabled. [ WARNING ] Skipped registration because it was already registered or it was disabled. [ WARNING ] Skipped registration because it was already registered or it was disabled. [ WARNING ] Skipped registration because it was already registered or it was disabled. [ WARNING ] Skipped registration because it was already registered or it was disabled. [ WARNING ] Skipped registration because it was already registered or it was disabled. [ WARNING ] Skipped registration because it was already registered or it was disabled. [ WARNING ] Skipped registration because it was already registered or it was disabled. [ WARNING ] Skipped registration because it was already registered or it was disabled. [ WARNING ] Skipped registration because it was already registered or it was disabled. [ WARNING ] Skipped registration because it was already registered or it was disabled. [ WARNING ] Skipped registration because it was already registered or it was disabled. [ WARNING ] Skipped registration because it was already registered or it was disabled. [ WARNING ] Skipped registration because it was already registered or it was disabled. [ INFO ] New subclass: [ INFO ] Registered a new subclass with key: Elu [ INFO ] New subclass: [ INFO ] Registered a new subclass with key: Sigmoid [ INFO ] New subclass: [ INFO ] Registered a new subclass with key: Tanh [ WARNING ] Skipped registration because it was already registered or it was disabled. [ WARNING ] Skipped registration because it was already registered or it was disabled. [ WARNING ] Skipped registration because it was already registered or it was disabled. [ WARNING ] Skipped registration because it was already registered or it was disabled. [ WARNING ] Skipped registration because it was already registered or it was disabled. [ WARNING ] Skipped registration because it was already registered or it was disabled. [ WARNING ] Skipped registration because it was already registered or it was disabled. [ WARNING ] Skipped registration because it was already registered or it was disabled. [ WARNING ] Skipped registration because it was already registered or it was disabled. [ WARNING ] Skipped registration because it was already registered or it was disabled. [ WARNING ] Skipped registration because it was already registered or it was disabled. [ WARNING ] Skipped registration because it was already registered or it was disabled. [ WARNING ] Skipped registration because it was already registered or it was disabled. [ WARNING ] Skipped registration because it was already registered or it was disabled. [ WARNING ] Skipped registration because it was already registered or it was disabled. [ WARNING ] Skipped registration because it was already registered or it was disabled. [ WARNING ] Skipped registration because it was already registered or it was disabled. [ WARNING ] Skipped registration because it was already registered or it was disabled. [ WARNING ] Skipped registration because it was already registered or it was disabled. [ WARNING ] Skipped registration because it was already registered or it was disabled. [ WARNING ] Skipped registration because it was already registered or it was disabled. [ WARNING ] Skipped registration because it was already registered or it was disabled. [ WARNING ] Skipped registration because it was already registered or it was disabled. [ WARNING ] Skipped registration because it was already registered or it was disabled. [ INFO ] Importing extensions from: /home/sweta/intel/computer_vision_sdk_2018.5.455/deployment_tools/model_optimizer/extensions [ WARNING ] Skipped registration because it was already registered or it was disabled. [ WARNING ] Skipped registration because it was already registered or it was disabled. [ WARNING ] Skipped registration because it was already registered or it was disabled. [ WARNING ] Skipped registration because it was already registered or it was disabled. [ WARNING ] Skipped registration because it was already registered or it was disabled. [ WARNING ] Skipped registration because it was already registered or it was disabled. [ WARNING ] Skipped registration because it was already registered or it was disabled. [ WARNING ] Skipped registration because it was already registered or it was disabled. [ WARNING ] Skipped registration because it was already registered or it was disabled. [ WARNING ] Skipped registration because it was already registered or it was disabled. [ WARNING ] Skipped registration because it was already registered or it was disabled. [ WARNING ] Skipped registration because it was already registered or it was disabled. [ WARNING ] Skipped registration because it was already registered or it was disabled. [ WARNING ] Skipped registration because it was already registered or it was disabled. [ WARNING ] Skipped registration because it was already registered or it was disabled. [ WARNING ] Skipped registration because it was already registered or it was disabled. [ WARNING ] Skipped registration because it was already registered or it was disabled. [ WARNING ] Skipped registration because it was already registered or it was disabled. [ WARNING ] Skipped registration because it was already registered or it was disabled. [ WARNING ] Skipped registration because it was already registered or it was disabled. [ WARNING ] Skipped registration because it was already registered or it was disabled. [ WARNING ] Skipped registration because it was already registered or it was disabled. [ WARNING ] Skipped registration because it was already registered or it was disabled. [ WARNING ] Skipped registration because it was already registered or it was disabled. [ WARNING ] Skipped registration because it was already registered or it was disabled. [ WARNING ] Skipped registration because it was already registered or it was disabled. [ WARNING ] Skipped registration because it was already registered or it was disabled. [ WARNING ] Skipped registration because it was already registered or it was disabled. [ WARNING ] Skipped registration because it was already registered or it was disabled. [ WARNING ] Skipped registration because it was already registered or it was disabled. [ WARNING ] Skipped registration because it was already registered or it was disabled. [ WARNING ] Skipped registration because it was already registered or it was disabled. [ WARNING ] Skipped registration because it was already registered or it was disabled. [ WARNING ] Skipped registration because it was already registered or it was disabled. [ WARNING ] Skipped registration because it was already registered or it was disabled. [ WARNING ] Skipped registration because it was already registered or it was disabled. [ WARNING ] Skipped registration because it was already registered or it was disabled. [ WARNING ] Skipped registration because it was already registered or it was disabled. [ WARNING ] Skipped registration because it was already registered or it was disabled. [ WARNING ] Skipped registration because it was already registered or it was disabled. [ INFO ] New subclass: [ INFO ] Registered a new subclass with key: BlockLSTM [ INFO ] New subclass: [ INFO ] Registered a new subclass with key: DetectionOutput [ INFO ] New subclass: [ INFO ] Registered a new subclass with key: Enter [ INFO ] New subclass: [ INFO ] Registered a new subclass with key: Exit [ INFO ] New subclass: [ INFO ] Registered a new subclass with key: NextIteration [ INFO ] New subclass: [ INFO ] Registered a new subclass with key: SquaredDifference [ INFO ] New subclass: [ INFO ] Registered a new subclass with key: TensorArrayV3 [ INFO ] New subclass: [ INFO ] Registered a new subclass with key: TensorArrayGatherV3 [ INFO ] New subclass: [ INFO ] Registered a new subclass with key: TensorArrayReadV3 [ INFO ] New subclass: [ INFO ] Registered a new subclass with key: TensorArrayScatterV3 [ INFO ] New subclass: [ INFO ] Registered a new subclass with key: TensorArraySizeV3 [ INFO ] New subclass: [ INFO ] Registered a new subclass with key: TensorArrayWriteV3 [ INFO ] New subclass: [ INFO ] Registered a new subclass with key: Accum [ INFO ] New subclass: [ INFO ] Registered a new subclass with key: ArgMax [ INFO ] New subclass: [ INFO ] Registered a new subclass with key: Assert [ INFO ] New subclass: [ INFO ] Registered a new subclass with key: Axpy [ INFO ] New subclass: [ INFO ] Registered a new subclass with key: BN [ INFO ] New subclass: [ INFO ] Registered a new subclass with key: ConstantFill [ INFO ] New subclass: [ INFO ] Registered a new subclass with key: Correlation [ INFO ] New subclass: [ INFO ] Registered a new subclass with key: CTCGreedyDecoder [ INFO ] New subclass: [ INFO ] Registered a new subclass with key: DataAugmentation [ INFO ] New subclass: [ INFO ] Registered a new subclass with key: DepthToSpace [ INFO ] New subclass: [ INFO ] Registered a new subclass with key: Gather [ INFO ] New subclass: [ INFO ] Registered a new subclass with key: GRN [ INFO ] New subclass: [ INFO ] Registered a new subclass with key: Identity [ INFO ] New subclass: [ INFO ] Registered a new subclass with key: InstanceNormalization [ INFO ] New subclass: [ INFO ] Registered a new subclass with key: Interp [ INFO ] New subclass: [ INFO ] Registered a new subclass with key: LSTMSequence [ INFO ] New subclass: [ INFO ] Registered a new subclass with key: Merge [ INFO ] New subclass: [ INFO ] Registered a new subclass with key: MVN [ INFO ] New subclass: [ INFO ] Registered a new subclass with key: Normalize [ INFO ] New subclass: [ INFO ] Registered a new subclass with key: Pack [ INFO ] New subclass: [ INFO ] Registered a new subclass with key: PowerFile [ INFO ] New subclass: [ INFO ] Registered a new subclass with key: PredictionHeatmap [ INFO ] New subclass: [ INFO ] Registered a new subclass with key: PReLU [ INFO ] New subclass: [ INFO ] Registered a new subclass with key: PriorBox [ INFO ] New subclass: [ INFO ] Registered a new subclass with key: PriorBoxClustered [ INFO ] New subclass: [ INFO ] Registered a new subclass with key: Proposal [ INFO ] New subclass: [ INFO ] Registered a new subclass with key: PSROIPooling [ INFO ] New subclass: [ INFO ] Registered a new subclass with key: Rank [ INFO ] New subclass: [ INFO ] Registered a new subclass with key: RegionYolo [ INFO ] New subclass: [ INFO ] Registered a new subclass with key: ReorgYolo [ INFO ] New subclass: [ INFO ] Registered a new subclass with key: Resample [ INFO ] New subclass: [ INFO ] Registered a new subclass with key: ReverseSequence [ INFO ] New subclass: [ INFO ] Registered a new subclass with key: Select [ INFO ] New subclass: [ INFO ] Registered a new subclass with key: ShuffleChannel [ INFO ] New subclass: [ INFO ] Registered a new subclass with key: SimplerNMS [ INFO ] New subclass: [ INFO ] Registered a new subclass with key: SpatialTransformer [ INFO ] New subclass: [ INFO ] Registered a new subclass with key: Splice [ INFO ] New subclass: [ INFO ] Registered a new subclass with key: SplitV [ INFO ] New subclass: [ INFO ] Registered a new subclass with key: StopGradient [ INFO ] New subclass: [ INFO ] Registered a new subclass with key: Switch [ WARNING ] Skipped registration because it was already registered or it was disabled. [ WARNING ] Skipped registration because it was already registered or it was disabled. [ WARNING ] Skipped registration because it was already registered or it was disabled. [ WARNING ] Skipped registration because it was already registered or it was disabled. [ WARNING ] Skipped registration because it was already registered or it was disabled. [ WARNING ] Skipped registration because it was already registered or it was disabled. [ WARNING ] Skipped registration because it was already registered or it was disabled. [ WARNING ] Skipped registration because it was already registered or it was disabled. [ WARNING ] Skipped registration because it was already registered or it was disabled. [ WARNING ] Skipped registration because it was already registered or it was disabled. [ WARNING ] Skipped registration because it was already registered or it was disabled. [ WARNING ] Skipped registration because it was already registered or it was disabled. [ WARNING ] Skipped registration because it was already registered or it was disabled. [ WARNING ] Skipped registration because it was already registered or it was disabled. [ WARNING ] Skipped registration because it was already registered or it was disabled. [ WARNING ] Skipped registration because it was already registered or it was disabled. [ WARNING ] Skipped registration because it was already registered or it was disabled. [ WARNING ] Skipped registration because it was already registered or it was disabled. [ WARNING ] Skipped registration because it was already registered or it was disabled. [ WARNING ] Skipped registration because it was already registered or it was disabled. [ WARNING ] Skipped registration because it was already registered or it was disabled. [ WARNING ] Skipped registration because it was already registered or it was disabled. [ WARNING ] Skipped registration because it was already registered or it was disabled. [ WARNING ] Skipped registration because it was already registered or it was disabled. [ WARNING ] Skipped registration because it was already registered or it was disabled. [ WARNING ] Skipped registration because it was already registered or it was disabled. [ WARNING ] Skipped registration because it was already registered or it was disabled. [ WARNING ] Skipped registration because it was already registered or it was disabled. [ WARNING ] Skipped registration because it was already registered or it was disabled. [ WARNING ] Skipped registration because it was already registered or it was disabled. [ WARNING ] Skipped registration because it was already registered or it was disabled. [ WARNING ] Skipped registration because it was already registered or it was disabled. [ WARNING ] Skipped registration because it was already registered or it was disabled. [ WARNING ] Skipped registration because it was already registered or it was disabled. [ WARNING ] Skipped registration because it was already registered or it was disabled. [ WARNING ] Skipped registration because it was already registered or it was disabled. [ WARNING ] Skipped registration because it was already registered or it was disabled. [ WARNING ] Skipped registration because it was already registered or it was disabled. [ WARNING ] Skipped registration because it was already registered or it was disabled. [ WARNING ] Skipped registration because it was already registered or it was disabled. [ WARNING ] Skipped registration because it was already registered or it was disabled. [ WARNING ] Skipped registration because it was already registered or it was disabled. [ WARNING ] Skipped registration because it was already registered or it was disabled. [ WARNING ] Skipped registration because it was already registered or it was disabled. [ WARNING ] Skipped registration because it was already registered or it was disabled. [ WARNING ] Skipped registration because it was already registered or it was disabled. [ WARNING ] Skipped registration because it was already registered or it was disabled. [ WARNING ] Skipped registration because it was already registered or it was disabled. [ WARNING ] Skipped registration because it was already registered or it was disabled. [ WARNING ] Skipped registration because it was already registered or it was disabled. [ WARNING ] Skipped registration because it was already registered or it was disabled. [ WARNING ] Skipped registration because it was already registered or it was disabled. [ WARNING ] Skipped registration because it was already registered or it was disabled. [ WARNING ] Skipped registration because it was already registered or it was disabled. [ WARNING ] Skipped registration because it was already registered or it was disabled. [ WARNING ] Skipped registration because it was already registered or it was disabled. [ WARNING ] Skipped registration because it was already registered or it was disabled. [ WARNING ] Skipped registration because it was already registered or it was disabled. [ WARNING ] Skipped registration because it was already registered or it was disabled. [ WARNING ] Skipped registration because it was already registered or it was disabled. [ WARNING ] Skipped registration because it was already registered or it was disabled. [ WARNING ] Skipped registration because it was already registered or it was disabled. [ WARNING ] Skipped registration because it was already registered or it was disabled. [ WARNING ] Skipped registration because it was already registered or it was disabled. [ WARNING ] Skipped registration because it was already registered or it was disabled. [ WARNING ] Skipped registration because it was already registered or it was disabled. [ WARNING ] Skipped registration because it was already registered or it was disabled. [ WARNING ] Skipped registration because it was already registered or it was disabled. [ WARNING ] Skipped registration because it was already registered or it was disabled. [ WARNING ] Skipped registration because it was already registered or it was disabled. [ WARNING ] Skipped registration because it was already registered or it was disabled. [ WARNING ] Skipped registration because it was already registered or it was disabled. [ WARNING ] Skipped registration because it was already registered or it was disabled. [ WARNING ] Skipped registration because it was already registered or it was disabled. [ WARNING ] Skipped registration because it was already registered or it was disabled. [ WARNING ] Skipped registration because it was already registered or it was disabled. [ WARNING ] Skipped registration because it was already registered or it was disabled. [ WARNING ] Skipped registration because it was already registered or it was disabled. [ WARNING ] Skipped registration because it was already registered or it was disabled. [ WARNING ] Skipped registration because it was already registered or it was disabled. [ WARNING ] Skipped registration because it was already registered or it was disabled. [ WARNING ] Skipped registration because it was already registered or it was disabled. [ WARNING ] Skipped registration because it was already registered or it was disabled. [ WARNING ] Skipped registration because it was already registered or it was disabled. [ WARNING ] Skipped registration because it was already registered or it was disabled. [ WARNING ] Skipped registration because it was already registered or it was disabled. [ WARNING ] Skipped registration because it was already registered or it was disabled. [ WARNING ] Skipped registration because it was already registered or it was disabled. [ WARNING ] Skipped registration because it was already registered or it was disabled. [ WARNING ] Skipped registration because it was already registered or it was disabled. [ WARNING ] Skipped registration because it was already registered or it was disabled. [ WARNING ] Skipped registration because it was already registered or it was disabled. [ WARNING ] Skipped registration because it was already registered or it was disabled. [ WARNING ] Skipped registration because it was already registered or it was disabled. [ WARNING ] Skipped registration because it was already registered or it was disabled. [ WARNING ] Skipped registration because it was already registered or it was disabled. [ WARNING ] Skipped registration because it was already registered or it was disabled. [ WARNING ] Skipped registration because it was already registered or it was disabled. [ WARNING ] Skipped registration because it was already registered or it was disabled. [ WARNING ] Skipped registration because it was already registered or it was disabled. [ WARNING ] Skipped registration because it was already registered or it was disabled. [ WARNING ] Skipped registration because it was already registered or it was disabled. [ WARNING ] Skipped registration because it was already registered or it was disabled. [ WARNING ] Skipped registration because it was already registered or it was disabled. [ WARNING ] Skipped registration because it was already registered or it was disabled. [ WARNING ] Skipped registration because it was already registered or it was disabled. [ WARNING ] Skipped registration because it was already registered or it was disabled. [ WARNING ] Skipped registration because it was already registered or it was disabled. [ WARNING ] Skipped registration because it was already registered or it was disabled. [ WARNING ] Skipped registration because it was already registered or it was disabled. [ WARNING ] Skipped registration because it was already registered or it was disabled. [ WARNING ] Skipped registration because it was already registered or it was disabled. [ WARNING ] Skipped registration because it was already registered or it was disabled. [ WARNING ] Skipped registration because it was already registered or it was disabled. [ WARNING ] Skipped registration because it was already registered or it was disabled. [ WARNING ] Skipped registration because it was already registered or it was disabled. [ WARNING ] Skipped registration because it was already registered or it was disabled. [ WARNING ] Skipped registration because it was already registered or it was disabled. [ WARNING ] Skipped registration because it was already registered or it was disabled. [ WARNING ] Skipped registration because it was already registered or it was disabled. [ WARNING ] Skipped registration because it was already registered or it was disabled. [ WARNING ] Skipped registration because it was already registered or it was disabled. [ WARNING ] Skipped registration because it was already registered or it was disabled. [ INFO ] New subclass: [ INFO ] Registered a new subclass with key: LRN [ INFO ] New subclass: [ INFO ] Registered a new subclass with key: Pack [ INFO ] New subclass: [ INFO ] Registered a new subclass with key: EltwiseN [ INFO ] New subclass: [ INFO ] Registered a new subclass with key: ImageScaler [ INFO ] New subclass: [ INFO ] Registered a new subclass with key: InstanceNormalization [ INFO ] New subclass: [ INFO ] Registered a new subclass with key: Reciprocal [ INFO ] New subclass: [ INFO ] Registered a new subclass with key: SquaredDifference [ INFO ] New subclass: [ INFO ] Registered a new subclass with key: Sub [ WARNING ] Skipped registration because it was already registered or it was disabled. [ WARNING ] Skipped registration because it was already registered or it was disabled. [ WARNING ] Skipped registration because it was already registered or it was disabled. [ WARNING ] Skipped registration because it was already registered or it was disabled. [ WARNING ] Skipped registration because it was already registered or it was disabled. [ WARNING ] Skipped registration because it was already registered or it was disabled. [ INFO ] New subclass: [ INFO ] New subclass: [ WARNING ] Skipped registration because it was already registered or it was disabled. [ WARNING ] Skipped registration because it was already registered or it was disabled. [ WARNING ] Skipped registration because it was already registered or it was disabled. [ WARNING ] Skipped registration because it was already registered or it was disabled. [ WARNING ] Skipped registration because it was already registered or it was disabled. [ WARNING ] Skipped registration because it was already registered or it was disabled. [ WARNING ] Skipped registration because it was already registered or it was disabled. [ WARNING ] Skipped registration because it was already registered or it was disabled. [ WARNING ] Skipped registration because it was already registered or it was disabled. [ WARNING ] Skipped registration because it was already registered or it was disabled. [ WARNING ] Skipped registration because it was already registered or it was disabled. [ WARNING ] Skipped registration because it was already registered or it was disabled. [ WARNING ] Skipped registration because it was already registered or it was disabled. [ WARNING ] Skipped registration because it was already registered or it was disabled. [ WARNING ] Skipped registration because it was already registered or it was disabled. [ WARNING ] Skipped registration because it was already registered or it was disabled. [ WARNING ] Skipped registration because it was already registered or it was disabled. [ WARNING ] Skipped registration because it was already registered or it was disabled. [ WARNING ] Skipped registration because it was already registered or it was disabled. [ WARNING ] Skipped registration because it was already registered or it was disabled. [ WARNING ] Skipped registration because it was already registered or it was disabled. [ WARNING ] Skipped registration because it was already registered or it was disabled. [ WARNING ] Skipped registration because it was already registered or it was disabled. [ WARNING ] Skipped registration because it was already registered or it was disabled. [ WARNING ] Skipped registration because it was already registered or it was disabled. [ WARNING ] Skipped registration because it was already registered or it was disabled. [ WARNING ] Skipped registration because it was already registered or it was disabled. [ WARNING ] Skipped registration because it was already registered or it was disabled. [ WARNING ] Skipped registration because it was already registered or it was disabled. [ WARNING ] Skipped registration because it was already registered or it was disabled. [ WARNING ] Skipped registration because it was already registered or it was disabled. [ WARNING ] Skipped registration because it was already registered or it was disabled. [ WARNING ] Skipped registration because it was already registered or it was disabled. [ WARNING ] Skipped registration because it was already registered or it was disabled. [ WARNING ] Skipped registration because it was already registered or it was disabled. [ WARNING ] Skipped registration because it was already registered or it was disabled. [ WARNING ] Skipped registration because it was already registered or it was disabled. [ WARNING ] Skipped registration because it was already registered or it was disabled. [ WARNING ] Skipped registration because it was already registered or it was disabled. [ WARNING ] Skipped registration because it was already registered or it was disabled. [ WARNING ] Skipped registration because it was already registered or it was disabled. [ WARNING ] Skipped registration because it was already registered or it was disabled. [ WARNING ] Skipped registration because it was already registered or it was disabled. [ WARNING ] Skipped registration because it was already registered or it was disabled. [ WARNING ] Skipped registration because it was already registered or it was disabled. [ WARNING ] Skipped registration because it was already registered or it was disabled. [ WARNING ] Skipped registration because it was already registered or it was disabled. [ WARNING ] Skipped registration because it was already registered or it was disabled. [ WARNING ] Skipped registration because it was already registered or it was disabled. [ WARNING ] Skipped registration because it was already registered or it was disabled. [ WARNING ] Skipped registration because it was already registered or it was disabled. [ WARNING ] Skipped registration because it was already registered or it was disabled. [ WARNING ] Skipped registration because it was already registered or it was disabled. [ WARNING ] Skipped registration because it was already registered or it was disabled. [ WARNING ] Skipped registration because it was already registered or it was disabled. [ WARNING ] Skipped registration because it was already registered or it was disabled. [ WARNING ] Skipped registration because it was already registered or it was disabled. [ WARNING ] Skipped registration because it was already registered or it was disabled. [ WARNING ] Skipped registration because it was already registered or it was disabled. [ WARNING ] Skipped registration because it was already registered or it was disabled. [ WARNING ] Skipped registration because it was already registered or it was disabled. [ WARNING ] Skipped registration because it was already registered or it was disabled. [ WARNING ] Skipped registration because it was already registered or it was disabled. [ WARNING ] Skipped registration because it was already registered or it was disabled. [ WARNING ] Skipped registration because it was already registered or it was disabled. [ WARNING ] Skipped registration because it was already registered or it was disabled. [ WARNING ] Skipped registration because it was already registered or it was disabled. [ WARNING ] Skipped registration because it was already registered or it was disabled. [ WARNING ] Skipped registration because it was already registered or it was disabled. [ WARNING ] Skipped registration because it was already registered or it was disabled. [ WARNING ] Skipped registration because it was already registered or it was disabled. [ WARNING ] Skipped registration because it was already registered or it was disabled. [ WARNING ] Skipped registration because it was already registered or it was disabled. [ WARNING ] Skipped registration because it was already registered or it was disabled. [ WARNING ] Skipped registration because it was already registered or it was disabled. [ WARNING ] Skipped registration because it was already registered or it was disabled. [ WARNING ] Skipped registration because it was already registered or it was disabled. [ WARNING ] Skipped registration because it was already registered or it was disabled. [ WARNING ] Skipped registration because it was already registered or it was disabled. [ WARNING ] Skipped registration because it was already registered or it was disabled. [ WARNING ] Skipped registration because it was already registered or it was disabled. [ WARNING ] Skipped registration because it was already registered or it was disabled. [ WARNING ] Skipped registration because it was already registered or it was disabled. [ WARNING ] Skipped registration because it was already registered or it was disabled. [ WARNING ] Skipped registration because it was already registered or it was disabled. [ WARNING ] Skipped registration because it was already registered or it was disabled. [ WARNING ] Skipped registration because it was already registered or it was disabled. [ WARNING ] Skipped registration because it was already registered or it was disabled. [ WARNING ] Skipped registration because it was already registered or it was disabled. [ WARNING ] Skipped registration because it was already registered or it was disabled. [ WARNING ] Skipped registration because it was already registered or it was disabled. [ WARNING ] Skipped registration because it was already registered or it was disabled. [ WARNING ] Skipped registration because it was already registered or it was disabled. [ WARNING ] Skipped registration because it was already registered or it was disabled. [ WARNING ] Skipped registration because it was already registered or it was disabled. [ WARNING ] Skipped registration because it was already registered or it was disabled. [ WARNING ] Skipped registration because it was already registered or it was disabled. [ WARNING ] Skipped registration because it was already registered or it was disabled. [ WARNING ] Skipped registration because it was already registered or it was disabled. [ WARNING ] Skipped registration because it was already registered or it was disabled. [ WARNING ] Skipped registration because it was already registered or it was disabled. [ WARNING ] Skipped registration because it was already registered or it was disabled. [ WARNING ] Skipped registration because it was already registered or it was disabled. [ WARNING ] Skipped registration because it was already registered or it was disabled. [ WARNING ] Skipped registration because it was already registered or it was disabled. [ WARNING ] Skipped registration because it was already registered or it was disabled. [ WARNING ] Skipped registration because it was already registered or it was disabled. [ WARNING ] Skipped registration because it was already registered or it was disabled. [ WARNING ] Skipped registration because it was already registered or it was disabled. [ WARNING ] Skipped registration because it was already registered or it was disabled. [ WARNING ] Skipped registration because it was already registered or it was disabled. [ WARNING ] Skipped registration because it was already registered or it was disabled. [ INFO ] New subclass: [ INFO ] Registered a new subclass with key: BlockLSTM [ INFO ] New subclass: [ INFO ] Registered a new subclass with key: CTCGreedyDecoder [ INFO ] New subclass: [ INFO ] Registered a new subclass with key: TensorArrayV3 [ INFO ] New subclass: [ INFO ] Registered a new subclass with key: TensorArrayGatherV3 [ INFO ] New subclass: [ INFO ] Registered a new subclass with key: AddN [ INFO ] New subclass: [ INFO ] Registered a new subclass with key: ArgMax [ INFO ] New subclass: [ INFO ] Registered a new subclass with key: Concat [ INFO ] New subclass: [ INFO ] Registered a new subclass with key: Conv2D [ INFO ] New subclass: [ INFO ] Registered a new subclass with key: DepthwiseConv2dNative [ INFO ] New subclass: [ INFO ] Registered a new subclass with key: Conv3D [ INFO ] New subclass: [ INFO ] Registered a new subclass with key: CropAndResize [ INFO ] New subclass: [ INFO ] Registered a new subclass with key: Conv2DBackpropInput [ INFO ] New subclass: [ INFO ] Registered a new subclass with key: Conv3DBackpropInputV2 [ INFO ] New subclass: [ INFO ] Registered a new subclass with key: DepthToSpace [ INFO ] New subclass: [ INFO ] Registered a new subclass with key: ExtractImagePatches [ INFO ] New subclass: [ INFO ] Registered a new subclass with key: FIFOQueueV2 [ INFO ] New subclass: [ INFO ] Registered a new subclass with key: Gather [ INFO ] New subclass: [ INFO ] Registered a new subclass with key: ResourceGather [ INFO ] New subclass: [ INFO ] Registered a new subclass with key: GatherV2 [ INFO ] New subclass: [ INFO ] Registered a new subclass with key: Max [ INFO ] New subclass: [ INFO ] Registered a new subclass with key: NextIteration [ INFO ] New subclass: [ INFO ] Registered a new subclass with key: Pad [ INFO ] New subclass: [ INFO ] Registered a new subclass with key: PadV2 [ INFO ] New subclass: [ INFO ] Registered a new subclass with key: MirrorPad [ INFO ] New subclass: [ INFO ] Registered a new subclass with key: AvgPool [ INFO ] New subclass: [ INFO ] Registered a new subclass with key: MaxPool [ INFO ] New subclass: [ INFO ] Registered a new subclass with key: MaxPool3D [ INFO ] New subclass: [ INFO ] Registered a new subclass with key: AvgPool3D [ INFO ] New subclass: [ INFO ] Registered a new subclass with key: Rank [ INFO ] New subclass: [ INFO ] Registered a new subclass with key: ResizeBilinear [ INFO ] New subclass: [ INFO ] Registered a new subclass with key: ResizeNearestNeighbor [ INFO ] New subclass: [ INFO ] Registered a new subclass with key: ReverseSequence [ INFO ] New subclass: [ INFO ] Registered a new subclass with key: ReverseV2 [ INFO ] New subclass: [ INFO ] Registered a new subclass with key: Slice [ INFO ] New subclass: [ INFO ] Registered a new subclass with key: Softmax [ INFO ] New subclass: [ INFO ] Registered a new subclass with key: SplitV [ INFO ] New subclass: [ INFO ] Registered a new subclass with key: Sqrt [ INFO ] New subclass: [ INFO ] Registered a new subclass with key: Square [ INFO ] New subclass: [ INFO ] Registered a new subclass with key: StopGradient [ INFO ] New subclass: [ INFO ] Registered a new subclass with key: Tile [ INFO ] New subclass: [ INFO ] Registered a new subclass with key: Variable [ INFO ] New subclass: [ INFO ] Registered a new subclass with key: VariableV2 [ WARNING ] Skipped registration because it was already registered or it was disabled. [ WARNING ] Skipped registration because it was already registered or it was disabled. [ WARNING ] Skipped registration because it was already registered or it was disabled. [ WARNING ] Skipped registration because it was already registered or it was disabled. [ WARNING ] Skipped registration because it was already registered or it was disabled. [ WARNING ] Skipped registration because it was already registered or it was disabled. [ WARNING ] Skipped registration because it was already registered or it was disabled. [ WARNING ] Skipped registration because it was already registered or it was disabled. [ WARNING ] Skipped registration because it was already registered or it was disabled. [ INFO ] New subclass: [ INFO ] Registered a new subclass with key: ArgMax [ INFO ] New subclass: [ INFO ] Registered a new subclass with key: BlockLSTM [ INFO ] New subclass: [ INFO ] Registered a new subclass with key: CropAndResize [ INFO ] New subclass: [ INFO ] Registered a new subclass with key: Unpack [ INFO ] New subclass: [ INFO ] Registered a new subclass with key: Assign [ INFO ] New subclass: [ INFO ] Registered a new subclass with key: AssignSub [ INFO ] New subclass: [ INFO ] Registered a new subclass with key: AssignAdd [ INFO ] New subclass: [ INFO ] Registered a new subclass with key: FakeConst [ WARNING ] Skipped registration because it was already registered or it was disabled. [ WARNING ] Skipped registration because it was already registered or it was disabled. [ WARNING ] Skipped registration because it was already registered or it was disabled. [ WARNING ] Skipped registration because it was already registered or it was disabled. [ WARNING ] Skipped registration because it was already registered or it was disabled. [ WARNING ] Skipped registration because it was already registered or it was disabled. [ WARNING ] Skipped registration because it was already registered or it was disabled. [ WARNING ] Skipped registration because it was already registered or it was disabled. [ INFO ] New subclass: [ INFO ] New subclass: [ INFO ] New subclass: [ INFO ] New subclass: [ INFO ] New subclass: [ INFO ] New subclass: [ INFO ] New subclass: [ INFO ] New subclass: [ INFO ] New subclass: [ WARNING ] Skipped registration because it was already registered or it was disabled. [ INFO ] New subclass: [ INFO ] New subclass: [ INFO ] New subclass: [ INFO ] New subclass: [ INFO ] New subclass: [ INFO ] New subclass: [ INFO ] New subclass: [ INFO ] New subclass: [ WARNING ] Skipped registration because it was already registered or it was disabled. [ WARNING ] Skipped registration because it was already registered or it was disabled. [ WARNING ] Skipped registration because it was already registered or it was disabled. [ WARNING ] Skipped registration because it was already registered or it was disabled. [ WARNING ] Skipped registration because it was already registered or it was disabled. [ WARNING ] Skipped registration because it was already registered or it was disabled. [ WARNING ] Skipped registration because it was already registered or it was disabled. [ WARNING ] Skipped registration because it was already registered or it was disabled. [ WARNING ] Skipped registration because it was already registered or it was disabled. [ WARNING ] Skipped registration because it was already registered or it was disabled. [ WARNING ] Skipped registration because it was already registered or it was disabled. [ WARNING ] Skipped registration because it was already registered or it was disabled. [ WARNING ] Skipped registration because it was already registered or it was disabled. [ WARNING ] Skipped registration because it was already registered or it was disabled. [ WARNING ] Skipped registration because it was already registered or it was disabled. [ WARNING ] Skipped registration because it was already registered or it was disabled. [ INFO ] New subclass: [ INFO ] New subclass: [ INFO ] New subclass: [ INFO ] New subclass: [ WARNING ] Skipped registration because it was already registered or it was disabled. [ WARNING ] Skipped registration because it was already registered or it was disabled. [ WARNING ] Skipped registration because it was already registered or it was disabled. [ WARNING ] Skipped registration because it was already registered or it was disabled. [ WARNING ] Skipped registration because it was already registered or it was disabled. [ WARNING ] Skipped registration because it was already registered or it was disabled. [ WARNING ] Skipped registration because it was already registered or it was disabled. [ WARNING ] Skipped registration because it was already registered or it was disabled. [ WARNING ] Skipped registration because it was already registered or it was disabled. [ WARNING ] Skipped registration because it was already registered or it was disabled. [ WARNING ] Skipped registration because it was already registered or it was disabled. [ WARNING ] Skipped registration because it was already registered or it was disabled. [ WARNING ] Skipped registration because it was already registered or it was disabled. [ WARNING ] Skipped registration because it was already registered or it was disabled. [ WARNING ] Skipped registration because it was already registered or it was disabled. [ WARNING ] Skipped registration because it was already registered or it was disabled. [ WARNING ] Skipped registration because it was already registered or it was disabled. [ WARNING ] Skipped registration because it was already registered or it was disabled. [ WARNING ] Skipped registration because it was already registered or it was disabled. [ WARNING ] Skipped registration because it was already registered or it was disabled. [ WARNING ] Skipped registration because it was already registered or it was disabled. [ WARNING ] Skipped registration because it was already registered or it was disabled. [ WARNING ] Skipped registration because it was already registered or it was disabled. [ WARNING ] Skipped registration because it was already registered or it was disabled. [ WARNING ] Skipped registration because it was already registered or it was disabled. [ WARNING ] Skipped registration because it was already registered or it was disabled. [ WARNING ] Skipped registration because it was already registered or it was disabled. [ WARNING ] Skipped registration because it was already registered or it was disabled. [ WARNING ] Skipped registration because it was already registered or it was disabled. [ WARNING ] Skipped registration because it was already registered or it was disabled. [ WARNING ] Skipped registration because it was already registered or it was disabled. [ WARNING ] Skipped registration because it was already registered or it was disabled. [ WARNING ] Skipped registration because it was already registered or it was disabled. [ WARNING ] Skipped registration because it was already registered or it was disabled. [ WARNING ] Skipped registration because it was already registered or it was disabled. [ WARNING ] Skipped registration because it was already registered or it was disabled. [ WARNING ] Skipped registration because it was already registered or it was disabled. [ WARNING ] Skipped registration because it was already registered or it was disabled. [ WARNING ] Skipped registration because it was already registered or it was disabled. [ WARNING ] Skipped registration because it was already registered or it was disabled. [ WARNING ] Skipped registration because it was already registered or it was disabled. [ WARNING ] Skipped registration because it was already registered or it was disabled. [ WARNING ] Skipped registration because it was already registered or it was disabled. [ WARNING ] Skipped registration because it was already registered or it was disabled. [ WARNING ] Skipped registration because it was already registered or it was disabled. [ WARNING ] Skipped registration because it was already registered or it was disabled. [ WARNING ] Skipped registration because it was already registered or it was disabled. [ WARNING ] Skipped registration because it was already registered or it was disabled. [ WARNING ] Skipped registration because it was already registered or it was disabled. [ WARNING ] Skipped registration because it was already registered or it was disabled. [ WARNING ] Skipped registration because it was already registered or it was disabled. [ WARNING ] Skipped registration because it was already registered or it was disabled. [ WARNING ] Skipped registration because it was already registered or it was disabled. [ WARNING ] Skipped registration because it was already registered or it was disabled. [ WARNING ] Skipped registration because it was already registered or it was disabled. [ WARNING ] Skipped registration because it was already registered or it was disabled. [ WARNING ] Skipped registration because it was already registered or it was disabled. [ WARNING ] Skipped registration because it was already registered or it was disabled. [ WARNING ] Skipped registration because it was already registered or it was disabled. [ WARNING ] Skipped registration because it was already registered or it was disabled. [ WARNING ] Skipped registration because it was already registered or it was disabled. [ WARNING ] Skipped registration because it was already registered or it was disabled. [ WARNING ] Skipped registration because it was already registered or it was disabled. [ WARNING ] Skipped registration because it was already registered or it was disabled. [ WARNING ] Skipped registration because it was already registered or it was disabled. [ WARNING ] Skipped registration because it was already registered or it was disabled. [ WARNING ] Skipped registration because it was already registered or it was disabled. [ WARNING ] Skipped registration because it was already registered or it was disabled. [ WARNING ] Skipped registration because it was already registered or it was disabled. [ WARNING ] Skipped registration because it was already registered or it was disabled. [ WARNING ] Skipped registration because it was already registered or it was disabled. [ WARNING ] Skipped registration because it was already registered or it was disabled. [ WARNING ] Skipped registration because it was already registered or it was disabled. [ WARNING ] Skipped registration because it was already registered or it was disabled. [ WARNING ] Skipped registration because it was already registered or it was disabled. [ WARNING ] Skipped registration because it was already registered or it was disabled. [ WARNING ] Skipped registration because it was already registered or it was disabled. [ WARNING ] Skipped registration because it was already registered or it was disabled. [ WARNING ] Skipped registration because it was already registered or it was disabled. [ WARNING ] Skipped registration because it was already registered or it was disabled. [ WARNING ] Skipped registration because it was already registered or it was disabled. [ WARNING ] Skipped registration because it was already registered or it was disabled. [ WARNING ] Skipped registration because it was already registered or it was disabled. [ WARNING ] Skipped registration because it was already registered or it was disabled. [ WARNING ] Skipped registration because it was already registered or it was disabled. [ WARNING ] Skipped registration because it was already registered or it was disabled. [ WARNING ] Skipped registration because it was already registered or it was disabled. [ WARNING ] Skipped registration because it was already registered or it was disabled. [ WARNING ] Skipped registration because it was already registered or it was disabled. [ WARNING ] Skipped registration because it was already registered or it was disabled. [ WARNING ] Skipped registration because it was already registered or it was disabled. [ WARNING ] Skipped registration because it was already registered or it was disabled. [ WARNING ] Skipped registration because it was already registered or it was disabled. [ WARNING ] Skipped registration because it was already registered or it was disabled. [ WARNING ] Skipped registration because it was already registered or it was disabled. [ WARNING ] Skipped registration because it was already registered or it was disabled. [ WARNING ] Skipped registration because it was already registered or it was disabled. [ WARNING ] Skipped registration because it was already registered or it was disabled. [ WARNING ] Skipped registration because it was already registered or it was disabled. [ WARNING ] Skipped registration because it was already registered or it was disabled. [ WARNING ] Skipped registration because it was already registered or it was disabled. [ WARNING ] Skipped registration because it was already registered or it was disabled. [ WARNING ] Skipped registration because it was already registered or it was disabled. [ WARNING ] Skipped registration because it was already registered or it was disabled. [ WARNING ] Skipped registration because it was already registered or it was disabled. [ WARNING ] Skipped registration because it was already registered or it was disabled. [ WARNING ] Skipped registration because it was already registered or it was disabled. [ WARNING ] Skipped registration because it was already registered or it was disabled. [ WARNING ] Skipped registration because it was already registered or it was disabled. [ WARNING ] Skipped registration because it was already registered or it was disabled. [ WARNING ] Skipped registration because it was already registered or it was disabled. [ WARNING ] Skipped registration because it was already registered or it was disabled. [ WARNING ] Skipped registration because it was already registered or it was disabled. [ WARNING ] Skipped registration because it was already registered or it was disabled. [ WARNING ] Skipped registration because it was already registered or it was disabled. [ WARNING ] Skipped registration because it was already registered or it was disabled. [ WARNING ] Skipped registration because it was already registered or it was disabled. [ WARNING ] Skipped registration because it was already registered or it was disabled. [ WARNING ] Skipped registration because it was already registered or it was disabled. [ WARNING ] Skipped registration because it was already registered or it was disabled. [ WARNING ] Skipped registration because it was already registered or it was disabled. [ WARNING ] Skipped registration because it was already registered or it was disabled. [ WARNING ] Skipped registration because it was already registered or it was disabled. [ WARNING ] Skipped registration because it was already registered or it was disabled. [ WARNING ] Skipped registration because it was already registered or it was disabled. [ WARNING ] Skipped registration because it was already registered or it was disabled. [ WARNING ] Skipped registration because it was already registered or it was disabled. [ WARNING ] Skipped registration because it was already registered or it was disabled. [ WARNING ] Skipped registration because it was already registered or it was disabled. [ WARNING ] Skipped registration because it was already registered or it was disabled. [ WARNING ] Skipped registration because it was already registered or it was disabled. [ WARNING ] Skipped registration because it was already registered or it was disabled. [ WARNING ] Skipped registration because it was already registered or it was disabled. [ WARNING ] Skipped registration because it was already registered or it was disabled. [ WARNING ] Skipped registration because it was already registered or it was disabled. [ WARNING ] Skipped registration because it was already registered or it was disabled. [ WARNING ] Skipped registration because it was already registered or it was disabled. [ WARNING ] Skipped registration because it was already registered or it was disabled. [ WARNING ] Skipped registration because it was already registered or it was disabled. [ WARNING ] Skipped registration because it was already registered or it was disabled. [ WARNING ] Skipped registration because it was already registered or it was disabled. [ WARNING ] Skipped registration because it was already registered or it was disabled. [ WARNING ] Skipped registration because it was already registered or it was disabled. [ WARNING ] Skipped registration because it was already registered or it was disabled. [ WARNING ] Skipped registration because it was already registered or it was disabled. [ WARNING ] Skipped registration because it was already registered or it was disabled. [ WARNING ] Skipped registration because it was already registered or it was disabled. [ WARNING ] Skipped registration because it was already registered or it was disabled. [ WARNING ] Skipped registration because it was already registered or it was disabled. [ WARNING ] Skipped registration because it was already registered or it was disabled. [ WARNING ] Skipped registration because it was already registered or it was disabled. [ WARNING ] Skipped registration because it was already registered or it was disabled. [ WARNING ] Skipped registration because it was already registered or it was disabled. [ WARNING ] Skipped registration because it was already registered or it was disabled. [ WARNING ] Skipped registration because it was already registered or it was disabled. [ WARNING ] Skipped registration because it was already registered or it was disabled. [ WARNING ] Skipped registration because it was already registered or it was disabled. [ WARNING ] Skipped registration because it was already registered or it was disabled. [ WARNING ] Skipped registration because it was already registered or it was disabled. [ WARNING ] Skipped registration because it was already registered or it was disabled. [ WARNING ] Skipped registration because it was already registered or it was disabled. [ WARNING ] Skipped registration because it was already registered or it was disabled. [ WARNING ] Skipped registration because it was already registered or it was disabled. [ WARNING ] Skipped registration because it was already registered or it was disabled. [ WARNING ] Skipped registration because it was already registered or it was disabled. [ WARNING ] Skipped registration because it was already registered or it was disabled. [ WARNING ] Skipped registration because it was already registered or it was disabled. [ WARNING ] Skipped registration because it was already registered or it was disabled. [ WARNING ] Skipped registration because it was already registered or it was disabled. [ WARNING ] Skipped registration because it was already registered or it was disabled. [ WARNING ] Skipped registration because it was already registered or it was disabled. [ WARNING ] Skipped registration because it was already registered or it was disabled. [ WARNING ] Skipped registration because it was already registered or it was disabled. [ WARNING ] Skipped registration because it was already registered or it was disabled. [ WARNING ] Skipped registration because it was already registered or it was disabled. [ WARNING ] Skipped registration because it was already registered or it was disabled. [ WARNING ] Skipped registration because it was already registered or it was disabled. [ WARNING ] Skipped registration because it was already registered or it was disabled. [ WARNING ] Skipped registration because it was already registered or it was disabled. [ WARNING ] Skipped registration because it was already registered or it was disabled. [ WARNING ] Skipped registration because it was already registered or it was disabled. [ WARNING ] Skipped registration because it was already registered or it was disabled. [ WARNING ] Skipped registration because it was already registered or it was disabled. [ WARNING ] Skipped registration because it was already registered or it was disabled. [ WARNING ] Skipped registration because it was already registered or it was disabled. [ WARNING ] Skipped registration because it was already registered or it was disabled. [ WARNING ] Skipped registration because it was already registered or it was disabled. [ WARNING ] Skipped registration because it was already registered or it was disabled. [ WARNING ] Skipped registration because it was already registered or it was disabled. [ WARNING ] Skipped registration because it was already registered or it was disabled. [ WARNING ] Skipped registration because it was already registered or it was disabled. [ WARNING ] Skipped registration because it was already registered or it was disabled. [ WARNING ] Skipped registration because it was already registered or it was disabled. [ WARNING ] Skipped registration because it was already registered or it was disabled. [ WARNING ] Skipped registration because it was already registered or it was disabled. [ WARNING ] Skipped registration because it was already registered or it was disabled. [ INFO ] New subclass: [ INFO ] Registered a new subclass with key: Slice [ INFO ] New subclass: [ INFO ] New subclass: [ INFO ] New subclass: [ INFO ] New subclass: [ INFO ] New subclass: [ INFO ] New subclass: [ INFO ] New subclass: [ INFO ] New subclass: [ INFO ] New subclass: [ INFO ] New subclass: [ INFO ] New subclass: [ INFO ] New subclass: [ INFO ] New subclass: [ INFO ] New subclass: [ INFO ] New subclass: [ INFO ] New subclass: [ INFO ] Registered a new subclass with key: Minimum [ INFO ] New subclass: [ INFO ] New subclass: [ INFO ] New subclass: [ INFO ] New subclass: [ INFO ] New subclass: [ INFO ] Registered a new subclass with key: Reduce [ INFO ] New subclass: [ WARNING ] Skipped registration because it was already registered or it was disabled. [ INFO ] New subclass: [ INFO ] New subclass: [ WARNING ] Skipped registration because it was already registered or it was disabled. [ WARNING ] Skipped registration because it was already registered or it was disabled. [ INFO ] New subclass: [ INFO ] New subclass: [ WARNING ] Skipped registration because it was already registered or it was disabled. [ WARNING ] Skipped registration because it was already registered or it was disabled. [ WARNING ] Skipped registration because it was already registered or it was disabled. [ WARNING ] Skipped registration because it was already registered or it was disabled. [ WARNING ] Skipped registration because it was already registered or it was disabled. [ WARNING ] Skipped registration because it was already registered or it was disabled. [ WARNING ] Skipped registration because it was already registered or it was disabled. [ WARNING ] Skipped registration because it was already registered or it was disabled. [ WARNING ] Skipped registration because it was already registered or it was disabled. [ WARNING ] Skipped registration because it was already registered or it was disabled. [ WARNING ] Skipped registration because it was already registered or it was disabled. [ WARNING ] Skipped registration because it was already registered or it was disabled. [ WARNING ] Skipped registration because it was already registered or it was disabled. [ WARNING ] Skipped registration because it was already registered or it was disabled. [ WARNING ] Skipped registration because it was already registered or it was disabled. [ WARNING ] Skipped registration because it was already registered or it was disabled. [ WARNING ] Skipped registration because it was already registered or it was disabled. [ WARNING ] Skipped registration because it was already registered or it was disabled. [ WARNING ] Skipped registration because it was already registered or it was disabled. [ WARNING ] Skipped registration because it was already registered or it was disabled. [ WARNING ] Skipped registration because it was already registered or it was disabled. [ WARNING ] Skipped registration because it was already registered or it was disabled. [ WARNING ] Skipped registration because it was already registered or it was disabled. [ WARNING ] Skipped registration because it was already registered or it was disabled. [ WARNING ] Skipped registration because it was already registered or it was disabled. [ WARNING ] Skipped registration because it was already registered or it was disabled. [ WARNING ] Skipped registration because it was already registered or it was disabled. [ WARNING ] Skipped registration because it was already registered or it was disabled. [ WARNING ] Skipped registration because it was already registered or it was disabled. [ WARNING ] Skipped registration because it was already registered or it was disabled. [ WARNING ] Skipped registration because it was already registered or it was disabled. [ WARNING ] Skipped registration because it was already registered or it was disabled. [ WARNING ] Skipped registration because it was already registered or it was disabled. [ WARNING ] Skipped registration because it was already registered or it was disabled. [ WARNING ] Skipped registration because it was already registered or it was disabled. [ WARNING ] Skipped registration because it was already registered or it was disabled. [ WARNING ] Skipped registration because it was already registered or it was disabled. [ WARNING ] Skipped registration because it was already registered or it was disabled. [ WARNING ] Skipped registration because it was already registered or it was disabled. [ WARNING ] Skipped registration because it was already registered or it was disabled. [ WARNING ] Skipped registration because it was already registered or it was disabled. [ WARNING ] Skipped registration because it was already registered or it was disabled. [ WARNING ] Skipped registration because it was already registered or it was disabled. [ WARNING ] Skipped registration because it was already registered or it was disabled. [ WARNING ] Skipped registration because it was already registered or it was disabled. [ WARNING ] Skipped registration because it was already registered or it was disabled. [ WARNING ] Skipped registration because it was already registered or it was disabled. [ WARNING ] Skipped registration because it was already registered or it was disabled. [ WARNING ] Skipped registration because it was already registered or it was disabled. [ WARNING ] Skipped registration because it was already registered or it was disabled. [ WARNING ] Skipped registration because it was already registered or it was disabled. [ WARNING ] Skipped registration because it was already registered or it was disabled. [ WARNING ] Skipped registration because it was already registered or it was disabled. [ WARNING ] Skipped registration because it was already registered or it was disabled. [ WARNING ] Skipped registration because it was already registered or it was disabled. [ WARNING ] Skipped registration because it was already registered or it was disabled. [ WARNING ] Skipped registration because it was already registered or it was disabled. [ WARNING ] Skipped registration because it was already registered or it was disabled. [ WARNING ] Skipped registration because it was already registered or it was disabled. [ WARNING ] Skipped registration because it was already registered or it was disabled. [ WARNING ] Skipped registration because it was already registered or it was disabled. [ WARNING ] Skipped registration because it was already registered or it was disabled. [ WARNING ] Skipped registration because it was already registered or it was disabled. [ WARNING ] Skipped registration because it was already registered or it was disabled. [ WARNING ] Skipped registration because it was already registered or it was disabled. [ WARNING ] Skipped registration because it was already registered or it was disabled. [ WARNING ] Skipped registration because it was already registered or it was disabled. [ WARNING ] Skipped registration because it was already registered or it was disabled. [ WARNING ] Skipped registration because it was already registered or it was disabled. [ WARNING ] Skipped registration because it was already registered or it was disabled. [ WARNING ] Skipped registration because it was already registered or it was disabled. [ WARNING ] Skipped registration because it was already registered or it was disabled. [ WARNING ] Skipped registration because it was already registered or it was disabled. [ WARNING ] Skipped registration because it was already registered or it was disabled. [ WARNING ] Skipped registration because it was already registered or it was disabled. [ WARNING ] Skipped registration because it was already registered or it was disabled. [ WARNING ] Skipped registration because it was already registered or it was disabled. [ WARNING ] Skipped registration because it was already registered or it was disabled. [ WARNING ] Skipped registration because it was already registered or it was disabled. [ WARNING ] Skipped registration because it was already registered or it was disabled. [ WARNING ] Skipped registration because it was already registered or it was disabled. [ WARNING ] Skipped registration because it was already registered or it was disabled. [ WARNING ] Skipped registration because it was already registered or it was disabled. [ WARNING ] Skipped registration because it was already registered or it was disabled. [ WARNING ] Skipped registration because it was already registered or it was disabled. [ WARNING ] Skipped registration because it was already registered or it was disabled. [ WARNING ] Skipped registration because it was already registered or it was disabled. [ WARNING ] Skipped registration because it was already registered or it was disabled. [ WARNING ] Skipped registration because it was already registered or it was disabled. [ WARNING ] Skipped registration because it was already registered or it was disabled. [ WARNING ] Skipped registration because it was already registered or it was disabled. [ WARNING ] Skipped registration because it was already registered or it was disabled. [ WARNING ] Skipped registration because it was already registered or it was disabled. [ WARNING ] Skipped registration because it was already registered or it was disabled. [ WARNING ] Skipped registration because it was already registered or it was disabled. [ WARNING ] Skipped registration because it was already registered or it was disabled. [ WARNING ] Skipped registration because it was already registered or it was disabled. [ WARNING ] Skipped registration because it was already registered or it was disabled. [ WARNING ] Skipped registration because it was already registered or it was disabled. [ WARNING ] Skipped registration because it was already registered or it was disabled. [ WARNING ] Skipped registration because it was already registered or it was disabled. [ WARNING ] Skipped registration because it was already registered or it was disabled. [ WARNING ] Skipped registration because it was already registered or it was disabled. [ WARNING ] Skipped registration because it was already registered or it was disabled. [ WARNING ] Skipped registration because it was already registered or it was disabled. [ WARNING ] Skipped registration because it was already registered or it was disabled. [ WARNING ] Skipped registration because it was already registered or it was disabled. [ WARNING ] Skipped registration because it was already registered or it was disabled. [ WARNING ] Skipped registration because it was already registered or it was disabled. [ WARNING ] Skipped registration because it was already registered or it was disabled. [ WARNING ] Skipped registration because it was already registered or it was disabled. [ WARNING ] Skipped registration because it was already registered or it was disabled. [ WARNING ] Skipped registration because it was already registered or it was disabled. [ WARNING ] Skipped registration because it was already registered or it was disabled. [ WARNING ] Skipped registration because it was already registered or it was disabled. [ WARNING ] Skipped registration because it was already registered or it was disabled. [ WARNING ] Skipped registration because it was already registered or it was disabled. [ WARNING ] Skipped registration because it was already registered or it was disabled. [ WARNING ] Skipped registration because it was already registered or it was disabled. [ WARNING ] Skipped registration because it was already registered or it was disabled. [ WARNING ] Skipped registration because it was already registered or it was disabled. [ WARNING ] Skipped registration because it was already registered or it was disabled. [ WARNING ] Skipped registration because it was already registered or it was disabled. [ WARNING ] Skipped registration because it was already registered or it was disabled. [ WARNING ] Skipped registration because it was already registered or it was disabled. [ WARNING ] Skipped registration because it was already registered or it was disabled. [ WARNING ] Skipped registration because it was already registered or it was disabled. [ WARNING ] Skipped registration because it was already registered or it was disabled. [ WARNING ] Skipped registration because it was already registered or it was disabled. [ WARNING ] Skipped registration because it was already registered or it was disabled. [ WARNING ] Skipped registration because it was already registered or it was disabled. [ WARNING ] Skipped registration because it was already registered or it was disabled. [ WARNING ] Skipped registration because it was already registered or it was disabled. [ WARNING ] Skipped registration because it was already registered or it was disabled. [ WARNING ] Skipped registration because it was already registered or it was disabled. [ WARNING ] Skipped registration because it was already registered or it was disabled. [ WARNING ] Skipped registration because it was already registered or it was disabled. [ WARNING ] Skipped registration because it was already registered or it was disabled. [ WARNING ] Skipped registration because it was already registered or it was disabled. [ WARNING ] Skipped registration because it was already registered or it was disabled. [ WARNING ] Skipped registration because it was already registered or it was disabled. [ WARNING ] Skipped registration because it was already registered or it was disabled. [ WARNING ] Skipped registration because it was already registered or it was disabled. [ WARNING ] Skipped registration because it was already registered or it was disabled. [ WARNING ] Skipped registration because it was already registered or it was disabled. [ WARNING ] Skipped registration because it was already registered or it was disabled. [ WARNING ] Skipped registration because it was already registered or it was disabled. [ WARNING ] Skipped registration because it was already registered or it was disabled. [ WARNING ] Skipped registration because it was already registered or it was disabled. [ WARNING ] Skipped registration because it was already registered or it was disabled. [ WARNING ] Skipped registration because it was already registered or it was disabled. [ WARNING ] Skipped registration because it was already registered or it was disabled. [ WARNING ] Skipped registration because it was already registered or it was disabled. [ WARNING ] Skipped registration because it was already registered or it was disabled. [ WARNING ] Skipped registration because it was already registered or it was disabled. [ WARNING ] Skipped registration because it was already registered or it was disabled. [ WARNING ] Skipped registration because it was already registered or it was disabled. [ WARNING ] Skipped registration because it was already registered or it was disabled. [ WARNING ] Skipped registration because it was already registered or it was disabled. [ WARNING ] Skipped registration because it was already registered or it was disabled. [ WARNING ] Skipped registration because it was already registered or it was disabled. [ WARNING ] Skipped registration because it was already registered or it was disabled. [ WARNING ] Skipped registration because it was already registered or it was disabled. [ WARNING ] Skipped registration because it was already registered or it was disabled. [ WARNING ] Skipped registration because it was already registered or it was disabled. [ WARNING ] Skipped registration because it was already registered or it was disabled. [ WARNING ] Skipped registration because it was already registered or it was disabled. [ WARNING ] Skipped registration because it was already registered or it was disabled. [ WARNING ] Skipped registration because it was already registered or it was disabled. [ WARNING ] Skipped registration because it was already registered or it was disabled. [ WARNING ] Skipped registration because it was already registered or it was disabled. [ WARNING ] Skipped registration because it was already registered or it was disabled. [ WARNING ] Skipped registration because it was already registered or it was disabled. [ WARNING ] Skipped registration because it was already registered or it was disabled. [ WARNING ] Skipped registration because it was already registered or it was disabled. [ WARNING ] Skipped registration because it was already registered or it was disabled. [ WARNING ] Skipped registration because it was already registered or it was disabled. [ WARNING ] Skipped registration because it was already registered or it was disabled. [ WARNING ] Skipped registration because it was already registered or it was disabled. [ WARNING ] Skipped registration because it was already registered or it was disabled. [ WARNING ] Skipped registration because it was already registered or it was disabled. [ WARNING ] Skipped registration because it was already registered or it was disabled. [ WARNING ] Skipped registration because it was already registered or it was disabled. [ WARNING ] Skipped registration because it was already registered or it was disabled. [ WARNING ] Skipped registration because it was already registered or it was disabled. [ WARNING ] Skipped registration because it was already registered or it was disabled. [ WARNING ] Skipped registration because it was already registered or it was disabled. [ WARNING ] Skipped registration because it was already registered or it was disabled. [ WARNING ] Skipped registration because it was already registered or it was disabled. [ WARNING ] Skipped registration because it was already registered or it was disabled. [ WARNING ] Skipped registration because it was already registered or it was disabled. [ WARNING ] Skipped registration because it was already registered or it was disabled. [ WARNING ] Skipped registration because it was already registered or it was disabled. [ WARNING ] Skipped registration because it was already registered or it was disabled. [ WARNING ] Skipped registration because it was already registered or it was disabled. [ WARNING ] Skipped registration because it was already registered or it was disabled. [ WARNING ] Skipped registration because it was already registered or it was disabled. [ WARNING ] Skipped registration because it was already registered or it was disabled. [ WARNING ] Skipped registration because it was already registered or it was disabled. [ WARNING ] Skipped registration because it was already registered or it was disabled. [ WARNING ] Skipped registration because it was already registered or it was disabled. [ WARNING ] Skipped registration because it was already registered or it was disabled. [ WARNING ] Skipped registration because it was already registered or it was disabled. [ WARNING ] Skipped registration because it was already registered or it was disabled. [ WARNING ] Skipped registration because it was already registered or it was disabled. [ WARNING ] Skipped registration because it was already registered or it was disabled. [ WARNING ] Skipped registration because it was already registered or it was disabled. [ WARNING ] Skipped registration because it was already registered or it was disabled. [ WARNING ] Skipped registration because it was already registered or it was disabled. [ WARNING ] Skipped registration because it was already registered or it was disabled. [ WARNING ] Skipped registration because it was already registered or it was disabled. [ WARNING ] Skipped registration because it was already registered or it was disabled. [ WARNING ] Skipped registration because it was already registered or it was disabled. [ WARNING ] Skipped registration because it was already registered or it was disabled. [ WARNING ] Skipped registration because it was already registered or it was disabled. [ WARNING ] Skipped registration because it was already registered or it was disabled. [ WARNING ] Skipped registration because it was already registered or it was disabled. [ WARNING ] Skipped registration because it was already registered or it was disabled. [ WARNING ] Skipped registration because it was already registered or it was disabled. [ WARNING ] Skipped registration because it was already registered or it was disabled. [ WARNING ] Skipped registration because it was already registered or it was disabled. [ WARNING ] Skipped registration because it was already registered or it was disabled. [ WARNING ] Skipped registration because it was already registered or it was disabled. [ WARNING ] Skipped registration because it was already registered or it was disabled. [ WARNING ] Skipped registration because it was already registered or it was disabled. [ WARNING ] Skipped registration because it was already registered or it was disabled. [ WARNING ] Skipped registration because it was already registered or it was disabled. [ WARNING ] Skipped registration because it was already registered or it was disabled. [ WARNING ] Skipped registration because it was already registered or it was disabled. [ WARNING ] Skipped registration because it was already registered or it was disabled. [ INFO ] New subclass: [ INFO ] New subclass: [ INFO ] New subclass: [ INFO ] New subclass: [ WARNING ] Skipped registration because it was already registered or it was disabled. [ WARNING ] Skipped registration because it was already registered or it was disabled. [ INFO ] New subclass: [ WARNING ] Skipped registration because it was already registered or it was disabled. [ WARNING ] Skipped registration because it was already registered or it was disabled. [ WARNING ] Skipped registration because it was already registered or it was disabled. [ WARNING ] Skipped registration because it was already registered or it was disabled. [ WARNING ] Skipped registration because it was already registered or it was disabled. [ WARNING ] Skipped registration because it was already registered or it was disabled. [ 2019-03-21 16:52:44,264 ] [ DEBUG ] [ tf:138 ] Number of nodes in graph_def: 410 [ 2019-03-21 16:52:44,264 ] [ DEBUG ] [ register_custom_ops:74 ] Added a new entry Elu to extractors with custom extractor class . [ 2019-03-21 16:52:44,264 ] [ DEBUG ] [ register_custom_ops:74 ] Added a new entry Sigmoid to extractors with custom extractor class . [ 2019-03-21 16:52:44,264 ] [ DEBUG ] [ register_custom_ops:74 ] Added a new entry Tanh to extractors with custom extractor class . [ 2019-03-21 16:52:44,265 ] [ DEBUG ] [ register_custom_ops:74 ] Added a new entry BlockLSTM to extractors with custom extractor class . [ 2019-03-21 16:52:44,265 ] [ DEBUG ] [ register_custom_ops:74 ] Added a new entry CTCGreedyDecoder to extractors with custom extractor class . [ 2019-03-21 16:52:44,265 ] [ DEBUG ] [ register_custom_ops:74 ] Added a new entry TensorArrayV3 to extractors with custom extractor class . [ 2019-03-21 16:52:44,265 ] [ DEBUG ] [ register_custom_ops:74 ] Added a new entry TensorArrayGatherV3 to extractors with custom extractor class . [ 2019-03-21 16:52:44,265 ] [ DEBUG ] [ register_custom_ops:74 ] Added a new entry AddN to extractors with custom extractor class . [ 2019-03-21 16:52:44,265 ] [ DEBUG ] [ register_custom_ops:74 ] Added a new entry ArgMax to extractors with custom extractor class . [ 2019-03-21 16:52:44,265 ] [ DEBUG ] [ register_custom_ops:74 ] Added a new entry Concat to extractors with custom extractor class . [ 2019-03-21 16:52:44,265 ] [ DEBUG ] [ register_custom_ops:74 ] Added a new entry Conv2D to extractors with custom extractor class . [ 2019-03-21 16:52:44,265 ] [ DEBUG ] [ register_custom_ops:74 ] Added a new entry DepthwiseConv2dNative to extractors with custom extractor class . [ 2019-03-21 16:52:44,266 ] [ DEBUG ] [ register_custom_ops:74 ] Added a new entry Conv3D to extractors with custom extractor class . [ 2019-03-21 16:52:44,266 ] [ DEBUG ] [ register_custom_ops:74 ] Added a new entry CropAndResize to extractors with custom extractor class . [ 2019-03-21 16:52:44,266 ] [ DEBUG ] [ register_custom_ops:74 ] Added a new entry Conv2DBackpropInput to extractors with custom extractor class . [ 2019-03-21 16:52:44,266 ] [ DEBUG ] [ register_custom_ops:74 ] Added a new entry Conv3DBackpropInputV2 to extractors with custom extractor class . [ 2019-03-21 16:52:44,266 ] [ DEBUG ] [ register_custom_ops:74 ] Added a new entry DepthToSpace to extractors with custom extractor class . [ 2019-03-21 16:52:44,266 ] [ DEBUG ] [ register_custom_ops:74 ] Added a new entry ExtractImagePatches to extractors with custom extractor class . [ 2019-03-21 16:52:44,266 ] [ DEBUG ] [ register_custom_ops:74 ] Added a new entry FIFOQueueV2 to extractors with custom extractor class . [ 2019-03-21 16:52:44,266 ] [ DEBUG ] [ register_custom_ops:74 ] Added a new entry Gather to extractors with custom extractor class . [ 2019-03-21 16:52:44,267 ] [ DEBUG ] [ register_custom_ops:74 ] Added a new entry ResourceGather to extractors with custom extractor class . [ 2019-03-21 16:52:44,267 ] [ DEBUG ] [ register_custom_ops:74 ] Added a new entry GatherV2 to extractors with custom extractor class . [ 2019-03-21 16:52:44,267 ] [ DEBUG ] [ register_custom_ops:74 ] Added a new entry Max to extractors with custom extractor class . [ 2019-03-21 16:52:44,267 ] [ DEBUG ] [ register_custom_ops:74 ] Added a new entry NextIteration to extractors with custom extractor class . [ 2019-03-21 16:52:44,267 ] [ DEBUG ] [ register_custom_ops:74 ] Added a new entry Pad to extractors with custom extractor class . [ 2019-03-21 16:52:44,267 ] [ DEBUG ] [ register_custom_ops:74 ] Added a new entry PadV2 to extractors with custom extractor class . [ 2019-03-21 16:52:44,267 ] [ DEBUG ] [ register_custom_ops:74 ] Added a new entry MirrorPad to extractors with custom extractor class . [ 2019-03-21 16:52:44,267 ] [ DEBUG ] [ register_custom_ops:74 ] Added a new entry AvgPool to extractors with custom extractor class . [ 2019-03-21 16:52:44,267 ] [ DEBUG ] [ register_custom_ops:74 ] Added a new entry MaxPool to extractors with custom extractor class . [ 2019-03-21 16:52:44,268 ] [ DEBUG ] [ register_custom_ops:74 ] Added a new entry MaxPool3D to extractors with custom extractor class . [ 2019-03-21 16:52:44,268 ] [ DEBUG ] [ register_custom_ops:74 ] Added a new entry AvgPool3D to extractors with custom extractor class . [ 2019-03-21 16:52:44,268 ] [ DEBUG ] [ register_custom_ops:74 ] Added a new entry Rank to extractors with custom extractor class . [ 2019-03-21 16:52:44,268 ] [ DEBUG ] [ register_custom_ops:74 ] Added a new entry ResizeBilinear to extractors with custom extractor class . [ 2019-03-21 16:52:44,268 ] [ DEBUG ] [ register_custom_ops:74 ] Added a new entry ResizeNearestNeighbor to extractors with custom extractor class . [ 2019-03-21 16:52:44,268 ] [ DEBUG ] [ register_custom_ops:74 ] Added a new entry ReverseSequence to extractors with custom extractor class . [ 2019-03-21 16:52:44,268 ] [ DEBUG ] [ register_custom_ops:74 ] Added a new entry ReverseV2 to extractors with custom extractor class . [ 2019-03-21 16:52:44,268 ] [ DEBUG ] [ register_custom_ops:74 ] Added a new entry Slice to extractors with custom extractor class . [ 2019-03-21 16:52:44,269 ] [ DEBUG ] [ register_custom_ops:74 ] Added a new entry Softmax to extractors with custom extractor class . [ 2019-03-21 16:52:44,269 ] [ DEBUG ] [ register_custom_ops:74 ] Added a new entry SplitV to extractors with custom extractor class . [ 2019-03-21 16:52:44,269 ] [ DEBUG ] [ register_custom_ops:74 ] Added a new entry Sqrt to extractors with custom extractor class . [ 2019-03-21 16:52:44,269 ] [ DEBUG ] [ register_custom_ops:70 ] Overridden extractor entry Square by custom extractor class . [ 2019-03-21 16:52:44,269 ] [ DEBUG ] [ register_custom_ops:74 ] Added a new entry StopGradient to extractors with custom extractor class . [ 2019-03-21 16:52:44,269 ] [ DEBUG ] [ register_custom_ops:74 ] Added a new entry Tile to extractors with custom extractor class . [ 2019-03-21 16:52:44,269 ] [ DEBUG ] [ register_custom_ops:74 ] Added a new entry Variable to extractors with custom extractor class . [ 2019-03-21 16:52:44,269 ] [ DEBUG ] [ register_custom_ops:74 ] Added a new entry VariableV2 to extractors with custom extractor class . [ 2019-03-21 16:52:44,269 ] [ DEBUG ] [ register_custom_ops:104 ] Added a new entry LSTMCell to extractors with custom op class . [ 2019-03-21 16:52:44,270 ] [ DEBUG ] [ register_custom_ops:104 ] Added a new entry OpOutput to extractors with custom op class . [ 2019-03-21 16:52:44,270 ] [ DEBUG ] [ register_custom_ops:104 ] Added a new entry TensorIteratorInput to extractors with custom op class . [ 2019-03-21 16:52:44,270 ] [ DEBUG ] [ register_custom_ops:104 ] Added a new entry TensorIteratorOutput to extractors with custom op class . [ 2019-03-21 16:52:44,270 ] [ DEBUG ] [ register_custom_ops:104 ] Added a new entry TensorIteratorCondition to extractors with custom op class . [ 2019-03-21 16:52:44,270 ] [ DEBUG ] [ register_custom_ops:104 ] Added a new entry TensorIteratorBackEdge to extractors with custom op class . [ 2019-03-21 16:52:44,270 ] [ DEBUG ] [ register_custom_ops:104 ] Added a new entry TensorIterator to extractors with custom op class . [ 2019-03-21 16:52:44,270 ] [ DEBUG ] [ register_custom_ops:104 ] Added a new entry Activation to extractors with custom op class . [ 2019-03-21 16:52:44,270 ] [ DEBUG ] [ register_custom_ops:104 ] Added a new entry Clamp to extractors with custom op class . [ 2019-03-21 16:52:44,271 ] [ DEBUG ] [ register_custom_ops:104 ] Added a new entry Convolution to extractors with custom op class . [ 2019-03-21 16:52:44,271 ] [ DEBUG ] [ register_custom_ops:104 ] Added a new entry Crop to extractors with custom op class . [ 2019-03-21 16:52:44,271 ] [ DEBUG ] [ register_custom_ops:104 ] Added a new entry Deconvolution to extractors with custom op class . [ 2019-03-21 16:52:44,271 ] [ DEBUG ] [ register_custom_ops:104 ] Added a new entry Eltwise to extractors with custom op class . [ 2019-03-21 16:52:44,271 ] [ DEBUG ] [ register_custom_ops:104 ] Added a new entry EltwiseN to extractors with custom op class . [ 2019-03-21 16:52:44,271 ] [ DEBUG ] [ register_custom_ops:104 ] Added a new entry Flatten to extractors with custom op class . [ 2019-03-21 16:52:44,271 ] [ DEBUG ] [ register_custom_ops:104 ] Added a new entry FlattenONNX to extractors with custom op class . [ 2019-03-21 16:52:44,271 ] [ DEBUG ] [ register_custom_ops:104 ] Added a new entry FullyConnected to extractors with custom op class . [ 2019-03-21 16:52:44,272 ] [ DEBUG ] [ register_custom_ops:104 ] Added a new entry Input to extractors with custom op class . [ 2019-03-21 16:52:44,272 ] [ DEBUG ] [ register_custom_ops:104 ] Added a new entry Memory to extractors with custom op class . [ 2019-03-21 16:52:44,272 ] [ DEBUG ] [ register_custom_ops:104 ] Added a new entry Pooling to extractors with custom op class . [ 2019-03-21 16:52:44,272 ] [ DEBUG ] [ register_custom_ops:104 ] Added a new entry ScaleShift to extractors with custom op class . [ 2019-03-21 16:52:44,272 ] [ DEBUG ] [ register_custom_ops:104 ] Added a new entry DetectionOutput to extractors with custom op class . [ 2019-03-21 16:52:44,272 ] [ DEBUG ] [ register_custom_ops:104 ] Added a new entry Enter to extractors with custom op class . [ 2019-03-21 16:52:44,272 ] [ DEBUG ] [ register_custom_ops:104 ] Added a new entry Exit to extractors with custom op class . [ 2019-03-21 16:52:44,272 ] [ DEBUG ] [ register_custom_ops:104 ] Added a new entry SquaredDifference to extractors with custom op class . [ 2019-03-21 16:52:44,273 ] [ DEBUG ] [ register_custom_ops:104 ] Added a new entry TensorArrayReadV3 to extractors with custom op class . [ 2019-03-21 16:52:44,273 ] [ DEBUG ] [ register_custom_ops:104 ] Added a new entry TensorArrayScatterV3 to extractors with custom op class . [ 2019-03-21 16:52:44,273 ] [ DEBUG ] [ register_custom_ops:104 ] Added a new entry TensorArraySizeV3 to extractors with custom op class . [ 2019-03-21 16:52:44,273 ] [ DEBUG ] [ register_custom_ops:104 ] Added a new entry TensorArrayWriteV3 to extractors with custom op class . [ 2019-03-21 16:52:44,273 ] [ DEBUG ] [ register_custom_ops:104 ] Added a new entry Accum to extractors with custom op class . [ 2019-03-21 16:52:44,273 ] [ DEBUG ] [ register_custom_ops:104 ] Added a new entry Assert to extractors with custom op class . [ 2019-03-21 16:52:44,273 ] [ DEBUG ] [ register_custom_ops:104 ] Added a new entry Axpy to extractors with custom op class . [ 2019-03-21 16:52:44,273 ] [ DEBUG ] [ register_custom_ops:104 ] Added a new entry BN to extractors with custom op class . [ 2019-03-21 16:52:44,274 ] [ DEBUG ] [ register_custom_ops:104 ] Added a new entry ConstantFill to extractors with custom op class . [ 2019-03-21 16:52:44,274 ] [ DEBUG ] [ register_custom_ops:104 ] Added a new entry Correlation to extractors with custom op class . [ 2019-03-21 16:52:44,274 ] [ DEBUG ] [ register_custom_ops:104 ] Added a new entry DataAugmentation to extractors with custom op class . [ 2019-03-21 16:52:44,274 ] [ DEBUG ] [ register_custom_ops:104 ] Added a new entry GRN to extractors with custom op class . [ 2019-03-21 16:52:44,274 ] [ DEBUG ] [ register_custom_ops:104 ] Added a new entry InstanceNormalization to extractors with custom op class . [ 2019-03-21 16:52:44,274 ] [ DEBUG ] [ register_custom_ops:104 ] Added a new entry Interp to extractors with custom op class . [ 2019-03-21 16:52:44,274 ] [ DEBUG ] [ register_custom_ops:104 ] Added a new entry LSTMSequence to extractors with custom op class . [ 2019-03-21 16:52:44,274 ] [ DEBUG ] [ register_custom_ops:104 ] Added a new entry Merge to extractors with custom op class . [ 2019-03-21 16:52:44,274 ] [ DEBUG ] [ register_custom_ops:104 ] Added a new entry MVN to extractors with custom op class . [ 2019-03-21 16:52:44,275 ] [ DEBUG ] [ register_custom_ops:104 ] Added a new entry Normalize to extractors with custom op class . [ 2019-03-21 16:52:44,275 ] [ DEBUG ] [ register_custom_ops:104 ] Added a new entry PowerFile to extractors with custom op class . [ 2019-03-21 16:52:44,275 ] [ DEBUG ] [ register_custom_ops:104 ] Added a new entry PredictionHeatmap to extractors with custom op class . [ 2019-03-21 16:52:44,275 ] [ DEBUG ] [ register_custom_ops:104 ] Added a new entry PReLU to extractors with custom op class . [ 2019-03-21 16:52:44,275 ] [ DEBUG ] [ register_custom_ops:104 ] Added a new entry PriorBox to extractors with custom op class . [ 2019-03-21 16:52:44,275 ] [ DEBUG ] [ register_custom_ops:104 ] Added a new entry PriorBoxClustered to extractors with custom op class . [ 2019-03-21 16:52:44,275 ] [ DEBUG ] [ register_custom_ops:104 ] Added a new entry Proposal to extractors with custom op class . [ 2019-03-21 16:52:44,275 ] [ DEBUG ] [ register_custom_ops:104 ] Added a new entry PSROIPooling to extractors with custom op class . [ 2019-03-21 16:52:44,276 ] [ DEBUG ] [ register_custom_ops:104 ] Added a new entry RegionYolo to extractors with custom op class . [ 2019-03-21 16:52:44,276 ] [ DEBUG ] [ register_custom_ops:104 ] Added a new entry ReorgYolo to extractors with custom op class . [ 2019-03-21 16:52:44,276 ] [ DEBUG ] [ register_custom_ops:104 ] Added a new entry Resample to extractors with custom op class . [ 2019-03-21 16:52:44,276 ] [ DEBUG ] [ register_custom_ops:104 ] Added a new entry Select to extractors with custom op class . [ 2019-03-21 16:52:44,276 ] [ DEBUG ] [ register_custom_ops:104 ] Added a new entry ShuffleChannel to extractors with custom op class . [ 2019-03-21 16:52:44,276 ] [ DEBUG ] [ register_custom_ops:104 ] Added a new entry SimplerNMS to extractors with custom op class . [ 2019-03-21 16:52:44,276 ] [ DEBUG ] [ register_custom_ops:104 ] Added a new entry SpatialTransformer to extractors with custom op class . [ 2019-03-21 16:52:44,276 ] [ DEBUG ] [ register_custom_ops:104 ] Added a new entry Splice to extractors with custom op class . [ 2019-03-21 16:52:44,276 ] [ DEBUG ] [ register_custom_ops:104 ] Added a new entry Switch to extractors with custom op class . [ 2019-03-21 16:52:44,365 ] [ DEBUG ] [ extractor:830 ] Sink: output/sink_port_0 for node output [ 2019-03-21 16:52:44,365 ] [ DEBUG ] [ extractor:831 ] {'precision': 'FP32', 'kind': 'op', 'type': 'OpOutput', 'op': 'OpOutput', 'is_output': True, 'infer': None, 'value': None, 'data_type': None, 'name': 'output/sink_port_0', 'dim_attrs': ['spatial_dims', 'channel_dims', 'axis', 'batch_dims'], 'shape_attrs': ['output_shape', 'shape', 'pad', 'window', 'stride'], 'IE': [('layer', [('id', . at 0x7fb075d30488>), 'name', 'precision', 'type'], [('data', [], []), '@ports', '@consts'])]} [ 2019-03-21 16:52:44,365 ] [ DEBUG ] [ extractor:832 ] Add edge from output to output/sink_port_0 [ 2019-03-21 16:52:44,385 ] [ DEBUG ] [ eliminate:64 ] The following nodes are seeded as output reachable: output/sink_port_0 [ 2019-03-21 16:52:44,534 ] [ DEBUG ] [ eliminate:130 ] Removing the following dead nodes: [ 2019-03-21 16:52:44,538 ] [ DEBUG ] [ eliminate:64 ] The following nodes are seeded as output reachable: output/sink_port_0 [ 2019-03-21 16:52:44,611 ] [ DEBUG ] [ eliminate:130 ] Removing the following dead nodes: [ 2019-03-21 16:52:45,009 ] [ DEBUG ] [ const:33 ] Constant extractor for node gives shape = [ 3 28 64] and value.shape = (3, 28, 64) [ 2019-03-21 16:52:45,010 ] [ DEBUG ] [ const:33 ] Constant extractor for node gives shape = [64] and value.shape = (64,) [ 2019-03-21 16:52:45,011 ] [ DEBUG ] [ utils:78 ] value = [1], shape = [], res = [1], res.shape = (1,) [ 2019-03-21 16:52:45,012 ] [ DEBUG ] [ const:33 ] Constant extractor for node gives shape = [] and value.shape = () [ 2019-03-21 16:52:45,013 ] [ DEBUG ] [ utils:78 ] value = [0], shape = [], res = [0], res.shape = (1,) [ 2019-03-21 16:52:45,013 ] [ DEBUG ] [ const:33 ] Constant extractor for node gives shape = [] and value.shape = () [ 2019-03-21 16:52:45,017 ] [ DEBUG ] [ const:33 ] Constant extractor for node gives shape = [64] and value.shape = (64,) [ 2019-03-21 16:52:45,018 ] [ DEBUG ] [ const:33 ] Constant extractor for node gives shape = [64] and value.shape = (64,) [ 2019-03-21 16:52:45,020 ] [ DEBUG ] [ const:33 ] Constant extractor for node gives shape = [64] and value.shape = (64,) [ 2019-03-21 16:52:45,021 ] [ DEBUG ] [ const:33 ] Constant extractor for node gives shape = [64] and value.shape = (64,) [ 2019-03-21 16:52:45,022 ] [ DEBUG ] [ utils:78 ] value = [0.0010000000474974513], shape = [], res = [0.001], res.shape = (1,) [ 2019-03-21 16:52:45,023 ] [ DEBUG ] [ const:33 ] Constant extractor for node gives shape = [] and value.shape = () [ 2019-03-21 16:52:45,028 ] [ DEBUG ] [ const:33 ] Constant extractor for node gives shape = [ 3 64 128] and value.shape = (3, 64, 128) [ 2019-03-21 16:52:45,029 ] [ DEBUG ] [ const:33 ] Constant extractor for node gives shape = [128] and value.shape = (128,) [ 2019-03-21 16:52:45,030 ] [ DEBUG ] [ utils:78 ] value = [1], shape = [], res = [1], res.shape = (1,) [ 2019-03-21 16:52:45,030 ] [ DEBUG ] [ const:33 ] Constant extractor for node gives shape = [] and value.shape = () [ 2019-03-21 16:52:45,032 ] [ DEBUG ] [ utils:78 ] value = [0], shape = [], res = [0], res.shape = (1,) [ 2019-03-21 16:52:45,032 ] [ DEBUG ] [ const:33 ] Constant extractor for node gives shape = [] and value.shape = () [ 2019-03-21 16:52:45,035 ] [ DEBUG ] [ const:33 ] Constant extractor for node gives shape = [128] and value.shape = (128,) [ 2019-03-21 16:52:45,037 ] [ DEBUG ] [ const:33 ] Constant extractor for node gives shape = [128] and value.shape = (128,) [ 2019-03-21 16:52:45,038 ] [ DEBUG ] [ const:33 ] Constant extractor for node gives shape = [128] and value.shape = (128,) [ 2019-03-21 16:52:45,040 ] [ DEBUG ] [ const:33 ] Constant extractor for node gives shape = [128] and value.shape = (128,) [ 2019-03-21 16:52:45,044 ] [ DEBUG ] [ utils:78 ] value = [0.0010000000474974513], shape = [], res = [0.001], res.shape = (1,) [ 2019-03-21 16:52:45,044 ] [ DEBUG ] [ const:33 ] Constant extractor for node gives shape = [] and value.shape = () [ 2019-03-21 16:52:45,050 ] [ DEBUG ] [ const:33 ] Constant extractor for node gives shape = [ 3 128 256] and value.shape = (3, 128, 256) [ 2019-03-21 16:52:45,051 ] [ DEBUG ] [ const:33 ] Constant extractor for node gives shape = [256] and value.shape = (256,) [ 2019-03-21 16:52:45,053 ] [ DEBUG ] [ utils:78 ] value = [1], shape = [], res = [1], res.shape = (1,) [ 2019-03-21 16:52:45,053 ] [ DEBUG ] [ const:33 ] Constant extractor for node gives shape = [] and value.shape = () [ 2019-03-21 16:52:45,054 ] [ DEBUG ] [ utils:78 ] value = [0], shape = [], res = [0], res.shape = (1,) [ 2019-03-21 16:52:45,054 ] [ DEBUG ] [ const:33 ] Constant extractor for node gives shape = [] and value.shape = () [ 2019-03-21 16:52:45,057 ] [ DEBUG ] [ const:33 ] Constant extractor for node gives shape = [256] and value.shape = (256,) [ 2019-03-21 16:52:45,059 ] [ DEBUG ] [ const:33 ] Constant extractor for node gives shape = [256] and value.shape = (256,) [ 2019-03-21 16:52:45,060 ] [ DEBUG ] [ const:33 ] Constant extractor for node gives shape = [256] and value.shape = (256,) [ 2019-03-21 16:52:45,062 ] [ DEBUG ] [ const:33 ] Constant extractor for node gives shape = [256] and value.shape = (256,) [ 2019-03-21 16:52:45,064 ] [ DEBUG ] [ utils:78 ] value = [0.0010000000474974513], shape = [], res = [0.001], res.shape = (1,) [ 2019-03-21 16:52:45,064 ] [ DEBUG ] [ const:33 ] Constant extractor for node gives shape = [] and value.shape = () [ 2019-03-21 16:52:45,070 ] [ DEBUG ] [ const:33 ] Constant extractor for node gives shape = [ 3 256 512] and value.shape = (3, 256, 512) [ 2019-03-21 16:52:45,071 ] [ DEBUG ] [ const:33 ] Constant extractor for node gives shape = [512] and value.shape = (512,) [ 2019-03-21 16:52:45,073 ] [ DEBUG ] [ utils:78 ] value = [1], shape = [], res = [1], res.shape = (1,) [ 2019-03-21 16:52:45,073 ] [ DEBUG ] [ const:33 ] Constant extractor for node gives shape = [] and value.shape = () [ 2019-03-21 16:52:45,075 ] [ DEBUG ] [ utils:78 ] value = [0], shape = [], res = [0], res.shape = (1,) [ 2019-03-21 16:52:45,075 ] [ DEBUG ] [ const:33 ] Constant extractor for node gives shape = [] and value.shape = () [ 2019-03-21 16:52:45,078 ] [ DEBUG ] [ const:33 ] Constant extractor for node gives shape = [512] and value.shape = (512,) [ 2019-03-21 16:52:45,080 ] [ DEBUG ] [ const:33 ] Constant extractor for node gives shape = [512] and value.shape = (512,) [ 2019-03-21 16:52:45,081 ] [ DEBUG ] [ const:33 ] Constant extractor for node gives shape = [512] and value.shape = (512,) [ 2019-03-21 16:52:45,083 ] [ DEBUG ] [ const:33 ] Constant extractor for node gives shape = [512] and value.shape = (512,) [ 2019-03-21 16:52:45,084 ] [ DEBUG ] [ utils:78 ] value = [0.0010000000474974513], shape = [], res = [0.001], res.shape = (1,) [ 2019-03-21 16:52:45,084 ] [ DEBUG ] [ const:33 ] Constant extractor for node gives shape = [] and value.shape = () [ 2019-03-21 16:52:45,090 ] [ DEBUG ] [ const:33 ] Constant extractor for node gives shape = [ 3 182 256] and value.shape = (3, 182, 256) [ 2019-03-21 16:52:45,091 ] [ DEBUG ] [ const:33 ] Constant extractor for node gives shape = [256] and value.shape = (256,) [ 2019-03-21 16:52:45,093 ] [ DEBUG ] [ utils:78 ] value = [1], shape = [], res = [1], res.shape = (1,) [ 2019-03-21 16:52:45,093 ] [ DEBUG ] [ const:33 ] Constant extractor for node gives shape = [] and value.shape = () [ 2019-03-21 16:52:45,094 ] [ DEBUG ] [ utils:78 ] value = [0], shape = [], res = [0], res.shape = (1,) [ 2019-03-21 16:52:45,095 ] [ DEBUG ] [ const:33 ] Constant extractor for node gives shape = [] and value.shape = () [ 2019-03-21 16:52:45,098 ] [ DEBUG ] [ const:33 ] Constant extractor for node gives shape = [256] and value.shape = (256,) [ 2019-03-21 16:52:45,100 ] [ DEBUG ] [ const:33 ] Constant extractor for node gives shape = [256] and value.shape = (256,) [ 2019-03-21 16:52:45,101 ] [ DEBUG ] [ const:33 ] Constant extractor for node gives shape = [256] and value.shape = (256,) [ 2019-03-21 16:52:45,102 ] [ DEBUG ] [ const:33 ] Constant extractor for node gives shape = [256] and value.shape = (256,) [ 2019-03-21 16:52:45,104 ] [ DEBUG ] [ utils:78 ] value = [0.0010000000474974513], shape = [], res = [0.001], res.shape = (1,) [ 2019-03-21 16:52:45,104 ] [ DEBUG ] [ const:33 ] Constant extractor for node gives shape = [] and value.shape = () [ 2019-03-21 16:52:45,111 ] [ DEBUG ] [ const:33 ] Constant extractor for node gives shape = [ 3 256 512] and value.shape = (3, 256, 512) [ 2019-03-21 16:52:45,112 ] [ DEBUG ] [ const:33 ] Constant extractor for node gives shape = [512] and value.shape = (512,) [ 2019-03-21 16:52:45,113 ] [ DEBUG ] [ utils:78 ] value = [1], shape = [], res = [1], res.shape = (1,) [ 2019-03-21 16:52:45,114 ] [ DEBUG ] [ const:33 ] Constant extractor for node gives shape = [] and value.shape = () [ 2019-03-21 16:52:45,116 ] [ DEBUG ] [ utils:78 ] value = [0], shape = [], res = [0], res.shape = (1,) [ 2019-03-21 16:52:45,116 ] [ DEBUG ] [ const:33 ] Constant extractor for node gives shape = [] and value.shape = () [ 2019-03-21 16:52:45,119 ] [ DEBUG ] [ const:33 ] Constant extractor for node gives shape = [512] and value.shape = (512,) [ 2019-03-21 16:52:45,120 ] [ DEBUG ] [ const:33 ] Constant extractor for node gives shape = [512] and value.shape = (512,) [ 2019-03-21 16:52:45,122 ] [ DEBUG ] [ const:33 ] Constant extractor for node gives shape = [512] and value.shape = (512,) [ 2019-03-21 16:52:45,123 ] [ DEBUG ] [ const:33 ] Constant extractor for node gives shape = [512] and value.shape = (512,) [ 2019-03-21 16:52:45,125 ] [ DEBUG ] [ utils:78 ] value = [0.0010000000474974513], shape = [], res = [0.001], res.shape = (1,) [ 2019-03-21 16:52:45,125 ] [ DEBUG ] [ const:33 ] Constant extractor for node gives shape = [] and value.shape = () [ 2019-03-21 16:52:45,134 ] [ DEBUG ] [ const:33 ] Constant extractor for node gives shape = [ 3 512 512] and value.shape = (3, 512, 512) [ 2019-03-21 16:52:45,137 ] [ DEBUG ] [ const:33 ] Constant extractor for node gives shape = [512] and value.shape = (512,) [ 2019-03-21 16:52:45,138 ] [ DEBUG ] [ utils:78 ] value = [1], shape = [], res = [1], res.shape = (1,) [ 2019-03-21 16:52:45,138 ] [ DEBUG ] [ const:33 ] Constant extractor for node gives shape = [] and value.shape = () [ 2019-03-21 16:52:45,140 ] [ DEBUG ] [ utils:78 ] value = [0], shape = [], res = [0], res.shape = (1,) [ 2019-03-21 16:52:45,140 ] [ DEBUG ] [ const:33 ] Constant extractor for node gives shape = [] and value.shape = () [ 2019-03-21 16:52:45,143 ] [ DEBUG ] [ const:33 ] Constant extractor for node gives shape = [512] and value.shape = (512,) [ 2019-03-21 16:52:45,144 ] [ DEBUG ] [ const:33 ] Constant extractor for node gives shape = [512] and value.shape = (512,) [ 2019-03-21 16:52:45,146 ] [ DEBUG ] [ const:33 ] Constant extractor for node gives shape = [512] and value.shape = (512,) [ 2019-03-21 16:52:45,147 ] [ DEBUG ] [ const:33 ] Constant extractor for node gives shape = [512] and value.shape = (512,) [ 2019-03-21 16:52:45,149 ] [ DEBUG ] [ utils:78 ] value = [0.0010000000474974513], shape = [], res = [0.001], res.shape = (1,) [ 2019-03-21 16:52:45,149 ] [ DEBUG ] [ const:33 ] Constant extractor for node gives shape = [] and value.shape = () [ 2019-03-21 16:52:45,154 ] [ DEBUG ] [ utils:78 ] value = [3], shape = [], res = [3], res.shape = (1,) [ 2019-03-21 16:52:45,155 ] [ DEBUG ] [ const:33 ] Constant extractor for node gives shape = [] and value.shape = () [ 2019-03-21 16:52:45,156 ] [ DEBUG ] [ utils:78 ] value = [2], shape = [], res = [2], res.shape = (1,) [ 2019-03-21 16:52:45,156 ] [ DEBUG ] [ const:33 ] Constant extractor for node gives shape = [] and value.shape = () [ 2019-03-21 16:52:45,157 ] [ DEBUG ] [ utils:78 ] value = [1], shape = [], res = [1], res.shape = (1,) [ 2019-03-21 16:52:45,157 ] [ DEBUG ] [ const:33 ] Constant extractor for node gives shape = [] and value.shape = () [ 2019-03-21 16:52:45,162 ] [ DEBUG ] [ const:33 ] Constant extractor for node gives shape = [2] and value.shape = (2,) [ 2019-03-21 16:52:45,163 ] [ DEBUG ] [ utils:78 ] value = [0], shape = [], res = [0], res.shape = (1,) [ 2019-03-21 16:52:45,163 ] [ DEBUG ] [ const:33 ] Constant extractor for node gives shape = [] and value.shape = () [ WARNING ] Broadcast of scalar to shape: [1] [ 2019-03-21 16:52:45,165 ] [ DEBUG ] [ const:33 ] Constant extractor for node gives shape = [1] and value.shape = (1,) [ WARNING ] Broadcast of scalar to shape: [1] [ 2019-03-21 16:52:45,167 ] [ DEBUG ] [ const:33 ] Constant extractor for node gives shape = [1] and value.shape = (1,) [ 2019-03-21 16:52:45,167 ] [ DEBUG ] [ utils:78 ] value = [0], shape = [], res = [0], res.shape = (1,) [ 2019-03-21 16:52:45,168 ] [ DEBUG ] [ const:33 ] Constant extractor for node gives shape = [] and value.shape = () [ 2019-03-21 16:52:45,170 ] [ DEBUG ] [ utils:78 ] value = [0.0], shape = [], res = [0.], res.shape = (1,) [ 2019-03-21 16:52:45,170 ] [ DEBUG ] [ const:33 ] Constant extractor for node gives shape = [] and value.shape = () [ WARNING ] Broadcast of scalar to shape: [1] [ 2019-03-21 16:52:45,172 ] [ DEBUG ] [ const:33 ] Constant extractor for node gives shape = [1] and value.shape = (1,) [ WARNING ] Broadcast of scalar to shape: [1] [ 2019-03-21 16:52:45,173 ] [ DEBUG ] [ const:33 ] Constant extractor for node gives shape = [1] and value.shape = (1,) [ 2019-03-21 16:52:45,174 ] [ DEBUG ] [ utils:78 ] value = [0], shape = [], res = [0], res.shape = (1,) [ 2019-03-21 16:52:45,174 ] [ DEBUG ] [ const:33 ] Constant extractor for node gives shape = [] and value.shape = () [ 2019-03-21 16:52:45,176 ] [ DEBUG ] [ utils:78 ] value = [0.0], shape = [], res = [0.], res.shape = (1,) [ 2019-03-21 16:52:45,176 ] [ DEBUG ] [ const:33 ] Constant extractor for node gives shape = [] and value.shape = () [ WARNING ] Broadcast of scalar to shape: [1] [ 2019-03-21 16:52:45,178 ] [ DEBUG ] [ const:33 ] Constant extractor for node gives shape = [1] and value.shape = (1,) [ WARNING ] Broadcast of scalar to shape: [1] [ 2019-03-21 16:52:45,179 ] [ DEBUG ] [ const:33 ] Constant extractor for node gives shape = [1] and value.shape = (1,) [ 2019-03-21 16:52:45,180 ] [ DEBUG ] [ utils:78 ] value = [0], shape = [], res = [0], res.shape = (1,) [ 2019-03-21 16:52:45,180 ] [ DEBUG ] [ const:33 ] Constant extractor for node gives shape = [] and value.shape = () [ 2019-03-21 16:52:45,182 ] [ DEBUG ] [ utils:78 ] value = [0.0], shape = [], res = [0.], res.shape = (1,) [ 2019-03-21 16:52:45,182 ] [ DEBUG ] [ const:33 ] Constant extractor for node gives shape = [] and value.shape = () [ WARNING ] Broadcast of scalar to shape: [1] [ 2019-03-21 16:52:45,184 ] [ DEBUG ] [ const:33 ] Constant extractor for node gives shape = [1] and value.shape = (1,) [ WARNING ] Broadcast of scalar to shape: [1] [ 2019-03-21 16:52:45,185 ] [ DEBUG ] [ const:33 ] Constant extractor for node gives shape = [1] and value.shape = (1,) [ 2019-03-21 16:52:45,186 ] [ DEBUG ] [ utils:78 ] value = [0], shape = [], res = [0], res.shape = (1,) [ 2019-03-21 16:52:45,186 ] [ DEBUG ] [ const:33 ] Constant extractor for node gives shape = [] and value.shape = () [ 2019-03-21 16:52:45,188 ] [ DEBUG ] [ utils:78 ] value = [0.0], shape = [], res = [0.], res.shape = (1,) [ 2019-03-21 16:52:45,188 ] [ DEBUG ] [ const:33 ] Constant extractor for node gives shape = [] and value.shape = () [ WARNING ] Broadcast of scalar to shape: [1] [ 2019-03-21 16:52:45,189 ] [ DEBUG ] [ const:33 ] Constant extractor for node gives shape = [1] and value.shape = (1,) [ WARNING ] Broadcast of scalar to shape: [1] [ 2019-03-21 16:52:45,195 ] [ DEBUG ] [ const:33 ] Constant extractor for node gives shape = [1] and value.shape = (1,) [ 2019-03-21 16:52:45,196 ] [ DEBUG ] [ utils:78 ] value = [0], shape = [], res = [0], res.shape = (1,) [ 2019-03-21 16:52:45,196 ] [ DEBUG ] [ const:33 ] Constant extractor for node gives shape = [] and value.shape = () [ 2019-03-21 16:52:45,197 ] [ DEBUG ] [ utils:78 ] value = [0.0], shape = [], res = [0.], res.shape = (1,) [ 2019-03-21 16:52:45,197 ] [ DEBUG ] [ const:33 ] Constant extractor for node gives shape = [] and value.shape = () [ WARNING ] Broadcast of scalar to shape: [1] [ 2019-03-21 16:52:45,199 ] [ DEBUG ] [ const:33 ] Constant extractor for node gives shape = [1] and value.shape = (1,) [ WARNING ] Broadcast of scalar to shape: [1] [ 2019-03-21 16:52:45,200 ] [ DEBUG ] [ const:33 ] Constant extractor for node gives shape = [1] and value.shape = (1,) [ 2019-03-21 16:52:45,201 ] [ DEBUG ] [ utils:78 ] value = [0], shape = [], res = [0], res.shape = (1,) [ 2019-03-21 16:52:45,201 ] [ DEBUG ] [ const:33 ] Constant extractor for node gives shape = [] and value.shape = () [ 2019-03-21 16:52:45,203 ] [ DEBUG ] [ utils:78 ] value = [0.0], shape = [], res = [0.], res.shape = (1,) [ 2019-03-21 16:52:45,203 ] [ DEBUG ] [ const:33 ] Constant extractor for node gives shape = [] and value.shape = () [ 2019-03-21 16:52:45,204 ] [ DEBUG ] [ const:33 ] Constant extractor for node gives shape = [3] and value.shape = (3,) [ WARNING ] Broadcast of scalar to shape: [1] [ 2019-03-21 16:52:45,206 ] [ DEBUG ] [ const:33 ] Constant extractor for node gives shape = [1] and value.shape = (1,) [ WARNING ] Broadcast of scalar to shape: [1] [ 2019-03-21 16:52:45,207 ] [ DEBUG ] [ const:33 ] Constant extractor for node gives shape = [1] and value.shape = (1,) [ WARNING ] Broadcast of scalar to shape: [1] [ 2019-03-21 16:52:45,209 ] [ DEBUG ] [ const:33 ] Constant extractor for node gives shape = [1] and value.shape = (1,) [ 2019-03-21 16:52:45,211 ] [ DEBUG ] [ utils:78 ] value = [0], shape = [], res = [0], res.shape = (1,) [ 2019-03-21 16:52:45,211 ] [ DEBUG ] [ const:33 ] Constant extractor for node gives shape = [] and value.shape = () [ 2019-03-21 16:52:45,213 ] [ DEBUG ] [ const:33 ] Constant extractor for node gives shape = [3] and value.shape = (3,) [ WARNING ] Broadcast of scalar to shape: [1] [ 2019-03-21 16:52:45,214 ] [ DEBUG ] [ const:33 ] Constant extractor for node gives shape = [1] and value.shape = (1,) [ WARNING ] Broadcast of scalar to shape: [1] [ 2019-03-21 16:52:45,215 ] [ DEBUG ] [ const:33 ] Constant extractor for node gives shape = [1] and value.shape = (1,) [ WARNING ] Broadcast of scalar to shape: [1] [ 2019-03-21 16:52:45,216 ] [ DEBUG ] [ const:33 ] Constant extractor for node gives shape = [1] and value.shape = (1,) [ 2019-03-21 16:52:45,218 ] [ DEBUG ] [ utils:78 ] value = [0], shape = [], res = [0], res.shape = (1,) [ 2019-03-21 16:52:45,218 ] [ DEBUG ] [ const:33 ] Constant extractor for node gives shape = [] and value.shape = () [ 2019-03-21 16:52:45,219 ] [ DEBUG ] [ utils:78 ] value = [1], shape = [], res = [1], res.shape = (1,) [ 2019-03-21 16:52:45,219 ] [ DEBUG ] [ const:33 ] Constant extractor for node gives shape = [] and value.shape = () [ 2019-03-21 16:52:45,221 ] [ DEBUG ] [ utils:78 ] value = [1], shape = [], res = [1], res.shape = (1,) [ 2019-03-21 16:52:45,221 ] [ DEBUG ] [ const:33 ] Constant extractor for node gives shape = [] and value.shape = () [ 2019-03-21 16:52:45,224 ] [ DEBUG ] [ utils:78 ] value = [0], shape = [], res = [0], res.shape = (1,) [ 2019-03-21 16:52:45,224 ] [ DEBUG ] [ const:33 ] Constant extractor for node gives shape = [] and value.shape = () [ 2019-03-21 16:52:45,246 ] [ DEBUG ] [ utils:78 ] value = [1], shape = [], res = [1], res.shape = (1,) [ 2019-03-21 16:52:45,247 ] [ DEBUG ] [ const:33 ] Constant extractor for node gives shape = [] and value.shape = () [ 2019-03-21 16:52:45,256 ] [ DEBUG ] [ const:33 ] Constant extractor for node gives shape = [1024 2048] and value.shape = (1024, 2048) [ 2019-03-21 16:52:45,257 ] [ DEBUG ] [ const:33 ] Constant extractor for node gives shape = [2048] and value.shape = (2048,) [ 2019-03-21 16:52:45,259 ] [ DEBUG ] [ utils:78 ] value = [1], shape = [], res = [1], res.shape = (1,) [ 2019-03-21 16:52:45,259 ] [ DEBUG ] [ const:33 ] Constant extractor for node gives shape = [] and value.shape = () [ 2019-03-21 16:52:45,262 ] [ DEBUG ] [ utils:78 ] value = [1], shape = [], res = [1], res.shape = (1,) [ 2019-03-21 16:52:45,263 ] [ DEBUG ] [ const:33 ] Constant extractor for node gives shape = [] and value.shape = () [ 2019-03-21 16:52:45,264 ] [ DEBUG ] [ utils:78 ] value = [1.0], shape = [], res = [1.], res.shape = (1,) [ 2019-03-21 16:52:45,265 ] [ DEBUG ] [ const:33 ] Constant extractor for node gives shape = [] and value.shape = () [ 2019-03-21 16:52:45,272 ] [ DEBUG ] [ utils:78 ] value = [1], shape = [], res = [1], res.shape = (1,) [ 2019-03-21 16:52:45,272 ] [ DEBUG ] [ const:33 ] Constant extractor for node gives shape = [] and value.shape = () [ 2019-03-21 16:52:45,275 ] [ DEBUG ] [ utils:78 ] value = [1], shape = [], res = [1], res.shape = (1,) [ 2019-03-21 16:52:45,275 ] [ DEBUG ] [ const:33 ] Constant extractor for node gives shape = [] and value.shape = () [ 2019-03-21 16:52:45,276 ] [ DEBUG ] [ utils:78 ] value = [1.0], shape = [], res = [1.], res.shape = (1,) [ 2019-03-21 16:52:45,276 ] [ DEBUG ] [ const:33 ] Constant extractor for node gives shape = [] and value.shape = () [ 2019-03-21 16:52:45,282 ] [ DEBUG ] [ utils:78 ] value = [1], shape = [], res = [1], res.shape = (1,) [ 2019-03-21 16:52:45,282 ] [ DEBUG ] [ const:33 ] Constant extractor for node gives shape = [] and value.shape = () [ 2019-03-21 16:52:45,285 ] [ DEBUG ] [ utils:78 ] value = [1], shape = [], res = [1], res.shape = (1,) [ 2019-03-21 16:52:45,285 ] [ DEBUG ] [ const:33 ] Constant extractor for node gives shape = [] and value.shape = () [ 2019-03-21 16:52:45,287 ] [ DEBUG ] [ utils:78 ] value = [1.0], shape = [], res = [1.], res.shape = (1,) [ 2019-03-21 16:52:45,287 ] [ DEBUG ] [ const:33 ] Constant extractor for node gives shape = [] and value.shape = () [ 2019-03-21 16:52:45,294 ] [ DEBUG ] [ utils:78 ] value = [1], shape = [], res = [1], res.shape = (1,) [ 2019-03-21 16:52:45,295 ] [ DEBUG ] [ const:33 ] Constant extractor for node gives shape = [] and value.shape = () [ 2019-03-21 16:52:45,301 ] [ DEBUG ] [ utils:78 ] value = [0], shape = [], res = [0], res.shape = (1,) [ 2019-03-21 16:52:45,302 ] [ DEBUG ] [ const:33 ] Constant extractor for node gives shape = [] and value.shape = () [ 2019-03-21 16:52:45,303 ] [ DEBUG ] [ utils:78 ] value = [1], shape = [], res = [1], res.shape = (1,) [ 2019-03-21 16:52:45,303 ] [ DEBUG ] [ const:33 ] Constant extractor for node gives shape = [] and value.shape = () [ 2019-03-21 16:52:45,305 ] [ DEBUG ] [ utils:78 ] value = [3], shape = [], res = [3], res.shape = (1,) [ 2019-03-21 16:52:45,305 ] [ DEBUG ] [ const:33 ] Constant extractor for node gives shape = [] and value.shape = () [ 2019-03-21 16:52:45,306 ] [ DEBUG ] [ utils:78 ] value = [2], shape = [], res = [2], res.shape = (1,) [ 2019-03-21 16:52:45,306 ] [ DEBUG ] [ const:33 ] Constant extractor for node gives shape = [] and value.shape = () [ 2019-03-21 16:52:45,307 ] [ DEBUG ] [ utils:78 ] value = [1], shape = [], res = [1], res.shape = (1,) [ 2019-03-21 16:52:45,307 ] [ DEBUG ] [ const:33 ] Constant extractor for node gives shape = [] and value.shape = () [ 2019-03-21 16:52:45,309 ] [ DEBUG ] [ const:33 ] Constant extractor for node gives shape = [2] and value.shape = (2,) [ 2019-03-21 16:52:45,310 ] [ DEBUG ] [ utils:78 ] value = [0], shape = [], res = [0], res.shape = (1,) [ 2019-03-21 16:52:45,310 ] [ DEBUG ] [ const:33 ] Constant extractor for node gives shape = [] and value.shape = () [ 2019-03-21 16:52:45,312 ] [ DEBUG ] [ const:33 ] Constant extractor for node gives shape = [3] and value.shape = (3,) [ WARNING ] Broadcast of scalar to shape: [1] [ 2019-03-21 16:52:45,313 ] [ DEBUG ] [ const:33 ] Constant extractor for node gives shape = [1] and value.shape = (1,) [ WARNING ] Broadcast of scalar to shape: [1] [ 2019-03-21 16:52:45,314 ] [ DEBUG ] [ const:33 ] Constant extractor for node gives shape = [1] and value.shape = (1,) [ WARNING ] Broadcast of scalar to shape: [1] [ 2019-03-21 16:52:45,315 ] [ DEBUG ] [ const:33 ] Constant extractor for node gives shape = [1] and value.shape = (1,) [ 2019-03-21 16:52:45,317 ] [ DEBUG ] [ utils:78 ] value = [-1], shape = [], res = [-1], res.shape = (1,) [ 2019-03-21 16:52:45,317 ] [ DEBUG ] [ const:33 ] Constant extractor for node gives shape = [] and value.shape = () [ 2019-03-21 16:52:45,319 ] [ DEBUG ] [ const:33 ] Constant extractor for node gives shape = [15360 7] and value.shape = (15360, 7) [ 2019-03-21 16:52:45,321 ] [ DEBUG ] [ const:33 ] Constant extractor for node gives shape = [7] and value.shape = (7,) [ WARNING ] Instructions/layers that do not have attribute extractors: [ WARNING ] Fill (6) [ WARNING ] spatial_temporal_network/rnn_net/rnn/MultiRNNCellZeroState/LSTMCellZeroState/zeros [ WARNING ] spatial_temporal_network/rnn_net/rnn/MultiRNNCellZeroState/LSTMCellZeroState/zeros_1 [ WARNING ] spatial_temporal_network/rnn_net/rnn/MultiRNNCellZeroState/LSTMCellZeroState_1/zeros [ WARNING ] spatial_temporal_network/rnn_net/rnn/MultiRNNCellZeroState/LSTMCellZeroState_1/zeros_1 [ WARNING ] spatial_temporal_network/rnn_net/rnn/MultiRNNCellZeroState/LSTMCellZeroState_2/zeros [ WARNING ] spatial_temporal_network/rnn_net/rnn/MultiRNNCellZeroState/LSTMCellZeroState_2/zeros_1 [ WARNING ] Less (2) [ WARNING ] spatial_temporal_network/rnn_net/rnn/while/Less [ WARNING ] spatial_temporal_network/rnn_net/rnn/while/Less_1 [ WARNING ] LogicalAnd (1) [ WARNING ] spatial_temporal_network/rnn_net/rnn/while/LogicalAnd [ WARNING ] LoopCond (1) [ WARNING ] spatial_temporal_network/rnn_net/rnn/while/LoopCond [ 2019-03-21 16:52:45,328 ] [ DEBUG ] [ class_registration:91 ] Replacer will be run after [ 2019-03-21 16:52:45,328 ] [ DEBUG ] [ class_registration:88 ] Replacer will be run before [ 2019-03-21 16:52:45,328 ] [ DEBUG ] [ class_registration:91 ] Replacer will be run after [ 2019-03-21 16:52:45,328 ] [ DEBUG ] [ class_registration:91 ] Replacer will be run after [ 2019-03-21 16:52:45,328 ] [ DEBUG ] [ class_registration:88 ] Replacer will be run before [ 2019-03-21 16:52:45,329 ] [ DEBUG ] [ class_registration:88 ] Replacer will be run before [ 2019-03-21 16:52:45,329 ] [ DEBUG ] [ class_registration:88 ] Replacer will be run before [ 2019-03-21 16:52:45,329 ] [ DEBUG ] [ class_registration:88 ] Replacer will be run before [ 2019-03-21 16:52:45,329 ] [ DEBUG ] [ class_registration:88 ] Replacer will be run before [ 2019-03-21 16:52:45,329 ] [ DEBUG ] [ class_registration:91 ] Replacer will be run after [ 2019-03-21 16:52:45,329 ] [ DEBUG ] [ class_registration:91 ] Replacer will be run after [ 2019-03-21 16:52:45,329 ] [ DEBUG ] [ class_registration:88 ] Replacer will be run before [ 2019-03-21 16:52:45,330 ] [ DEBUG ] [ class_registration:88 ] Replacer will be run before [ 2019-03-21 16:52:45,330 ] [ DEBUG ] [ class_registration:91 ] Replacer will be run after [ 2019-03-21 16:52:45,330 ] [ DEBUG ] [ class_registration:88 ] Replacer will be run before [ 2019-03-21 16:52:45,330 ] [ DEBUG ] [ class_registration:88 ] Replacer will be run before [ 2019-03-21 16:52:45,330 ] [ DEBUG ] [ class_registration:91 ] Replacer will be run after [ 2019-03-21 16:52:45,330 ] [ DEBUG ] [ class_registration:88 ] Replacer will be run before [ 2019-03-21 16:52:45,331 ] [ DEBUG ] [ class_registration:88 ] Replacer will be run before [ 2019-03-21 16:52:45,331 ] [ DEBUG ] [ class_registration:88 ] Replacer will be run before [ 2019-03-21 16:52:45,331 ] [ DEBUG ] [ class_registration:88 ] Replacer will be run before [ 2019-03-21 16:52:45,331 ] [ DEBUG ] [ class_registration:88 ] Replacer will be run before [ 2019-03-21 16:52:45,331 ] [ DEBUG ] [ class_registration:88 ] Replacer will be run before [ 2019-03-21 16:52:45,331 ] [ DEBUG ] [ class_registration:88 ] Replacer will be run before [ 2019-03-21 16:52:45,332 ] [ DEBUG ] [ class_registration:111 ] Run replacer [ 2019-03-21 16:52:45,379 ] [ DEBUG ] [ class_registration:111 ] Run replacer [ 2019-03-21 16:52:45,432 ] [ DEBUG ] [ class_registration:111 ] Run replacer [ 2019-03-21 16:52:45,485 ] [ DEBUG ] [ class_registration:111 ] Run replacer [ 2019-03-21 16:52:45,485 ] [ DEBUG ] [ mvn_unrolled:36 ] Enabled MVN replacement [ 2019-03-21 16:52:45,524 ] [ DEBUG ] [ class_registration:111 ] Run replacer [ 2019-03-21 16:52:45,524 ] [ DEBUG ] [ mvn:35 ] Enabled MVN replacement [ 2019-03-21 16:52:45,564 ] [ DEBUG ] [ class_registration:111 ] Run replacer [ 2019-03-21 16:52:45,605 ] [ DEBUG ] [ class_registration:111 ] Run replacer [ 2019-03-21 16:52:45,648 ] [ DEBUG ] [ class_registration:111 ] Run replacer [ 2019-03-21 16:52:45,691 ] [ DEBUG ] [ class_registration:111 ] Run replacer [ 2019-03-21 16:52:45,732 ] [ DEBUG ] [ class_registration:111 ] Run replacer [ 2019-03-21 16:52:45,771 ] [ DEBUG ] [ class_registration:111 ] Run replacer [ 2019-03-21 16:52:45,940 ] [ DEBUG ] [ class_registration:111 ] Run replacer [ 2019-03-21 16:52:45,982 ] [ DEBUG ] [ class_registration:111 ] Run replacer [ 2019-03-21 16:52:46,023 ] [ DEBUG ] [ class_registration:111 ] Run replacer [ 2019-03-21 16:52:46,070 ] [ DEBUG ] [ class_registration:111 ] Run replacer [ 2019-03-21 16:52:46,119 ] [ DEBUG ] [ class_registration:111 ] Run replacer [ 2019-03-21 16:52:46,161 ] [ DEBUG ] [ class_registration:111 ] Run replacer [ 2019-03-21 16:52:46,203 ] [ DEBUG ] [ class_registration:111 ] Run replacer [ 2019-03-21 16:52:46,243 ] [ DEBUG ] [ class_registration:111 ] Run replacer [ 2019-03-21 16:52:46,285 ] [ DEBUG ] [ class_registration:111 ] Run replacer [ 2019-03-21 16:52:46,326 ] [ DEBUG ] [ class_registration:111 ] Run replacer [ 2019-03-21 16:52:46,367 ] [ DEBUG ] [ class_registration:111 ] Run replacer [ 2019-03-21 16:52:46,409 ] [ DEBUG ] [ class_registration:111 ] Run replacer [ WARNING ] Configuration file for custom replacement with id 'SSDToolboxDetectionOutput' doesn't exist [ INFO ] Failed to find custom replacement description with id 'SSDToolboxDetectionOutput' [ 2019-03-21 16:52:46,410 ] [ DEBUG ] [ class_registration:111 ] Run replacer [ WARNING ] Configuration file for custom replacement with id 'RetinaNetFilteredDetectionsReplacement' doesn't exist [ INFO ] Failed to find custom replacement description with id 'RetinaNetFilteredDetectionsReplacement' [ 2019-03-21 16:52:46,410 ] [ DEBUG ] [ class_registration:111 ] Run replacer [ WARNING ] Configuration file for custom replacement with id 'ConvFlatten' doesn't exist [ INFO ] Failed to find custom replacement description with id 'ConvFlatten' [ 2019-03-21 16:52:46,411 ] [ DEBUG ] [ class_registration:111 ] Run replacer [ WARNING ] Configuration file for custom replacement with id 'TFYOLOV3' doesn't exist [ INFO ] Failed to find custom replacement description with id 'TFYOLOV3' [ 2019-03-21 16:52:46,411 ] [ DEBUG ] [ class_registration:111 ] Run replacer [ 2019-03-21 16:52:46,453 ] [ DEBUG ] [ class_registration:111 ] Run replacer [ WARNING ] Configuration file for custom replacement with id 'ObjectDetectionAPIOutputReplacement' doesn't exist [ INFO ] Failed to find custom replacement description with id 'ObjectDetectionAPIOutputReplacement' [ 2019-03-21 16:52:46,454 ] [ DEBUG ] [ class_registration:111 ] Run replacer [ WARNING ] Configuration file for custom replacement with id 'ObjectDetectionAPIPreprocessorReplacement' doesn't exist [ INFO ] Failed to find custom replacement description with id 'ObjectDetectionAPIPreprocessorReplacement' [ 2019-03-21 16:52:46,454 ] [ DEBUG ] [ class_registration:111 ] Run replacer [ WARNING ] Configuration file for custom replacement with id 'ObjectDetectionAPISSDPostprocessorReplacement' doesn't exist [ INFO ] Failed to find custom replacement description with id 'ObjectDetectionAPISSDPostprocessorReplacement' [ 2019-03-21 16:52:46,455 ] [ DEBUG ] [ class_registration:111 ] Run replacer [ 2019-03-21 16:52:46,522 ] [ DEBUG ] [ class_registration:111 ] Run replacer [ WARNING ] Configuration file for custom replacement with id 'TFYOLO' doesn't exist [ INFO ] Failed to find custom replacement description with id 'TFYOLO' [ 2019-03-21 16:52:46,523 ] [ DEBUG ] [ class_registration:111 ] Run replacer [ 2019-03-21 16:52:46,563 ] [ DEBUG ] [ class_registration:111 ] Run replacer [ WARNING ] Configuration file for custom replacement with id 'ObjectDetectionAPIProposalReplacement' doesn't exist [ INFO ] Failed to find custom replacement description with id 'ObjectDetectionAPIProposalReplacement' [ 2019-03-21 16:52:46,563 ] [ DEBUG ] [ class_registration:111 ] Run replacer [ 2019-03-21 16:52:46,603 ] [ DEBUG ] [ class_registration:111 ] Run replacer [ WARNING ] Configuration file for custom replacement with id 'ObjectDetectionAPIDetectionOutputReplacement' doesn't exist [ INFO ] Failed to find custom replacement description with id 'ObjectDetectionAPIDetectionOutputReplacement' [ 2019-03-21 16:52:46,604 ] [ DEBUG ] [ class_registration:111 ] Run replacer [ 2019-03-21 16:52:46,642 ] [ DEBUG ] [ replacement:89 ] Created edge from spatial_temporal_network/motion/conblock_1/bn/batchnorm/sub/add_ to spatial_temporal_network/motion/conblock_1/bn/batchnorm/add_1 with attrs: {'in': 1, 'out': 0, 'fw_tensor_debug_info': [('spatial_temporal_network/motion/conblock_1/bn/batchnorm/sub', 0)], 'in_attrs': ['in', 'control_flow_edge', 'permutation'], 'out_attrs': ['out', 'permutation'], 'data_attrs': ['fw_tensor_debug_info'], 'control_flow_edge': False} [ 2019-03-21 16:52:46,643 ] [ DEBUG ] [ replacement:197 ] Removing nodes: ['spatial_temporal_network/motion/conblock_1/bn/batchnorm/sub'] [ 2019-03-21 16:52:46,644 ] [ DEBUG ] [ replacement:89 ] Created edge from spatial_temporal_network/geo/conblock_1/bn/batchnorm/sub/add_ to spatial_temporal_network/geo/conblock_1/bn/batchnorm/add_1 with attrs: {'in': 1, 'out': 0, 'fw_tensor_debug_info': [('spatial_temporal_network/geo/conblock_1/bn/batchnorm/sub', 0)], 'in_attrs': ['in', 'control_flow_edge', 'permutation'], 'out_attrs': ['out', 'permutation'], 'data_attrs': ['fw_tensor_debug_info'], 'control_flow_edge': False} [ 2019-03-21 16:52:46,644 ] [ DEBUG ] [ replacement:197 ] Removing nodes: ['spatial_temporal_network/geo/conblock_1/bn/batchnorm/sub'] [ 2019-03-21 16:52:46,645 ] [ DEBUG ] [ replacement:89 ] Created edge from spatial_temporal_network/motion/conblock_4/bn/batchnorm/sub/add_ to spatial_temporal_network/motion/conblock_4/bn/batchnorm/add_1 with attrs: {'in': 1, 'out': 0, 'fw_tensor_debug_info': [('spatial_temporal_network/motion/conblock_4/bn/batchnorm/sub', 0)], 'in_attrs': ['in', 'control_flow_edge', 'permutation'], 'out_attrs': ['out', 'permutation'], 'data_attrs': ['fw_tensor_debug_info'], 'control_flow_edge': False} [ 2019-03-21 16:52:46,645 ] [ DEBUG ] [ replacement:197 ] Removing nodes: ['spatial_temporal_network/motion/conblock_4/bn/batchnorm/sub'] [ 2019-03-21 16:52:46,647 ] [ DEBUG ] [ replacement:89 ] Created edge from spatial_temporal_network/geo/conblock_2/bn/batchnorm/sub/add_ to spatial_temporal_network/geo/conblock_2/bn/batchnorm/add_1 with attrs: {'in': 1, 'out': 0, 'fw_tensor_debug_info': [('spatial_temporal_network/geo/conblock_2/bn/batchnorm/sub', 0)], 'in_attrs': ['in', 'control_flow_edge', 'permutation'], 'out_attrs': ['out', 'permutation'], 'data_attrs': ['fw_tensor_debug_info'], 'control_flow_edge': False} [ 2019-03-21 16:52:46,647 ] [ DEBUG ] [ replacement:197 ] Removing nodes: ['spatial_temporal_network/geo/conblock_2/bn/batchnorm/sub'] [ 2019-03-21 16:52:46,648 ] [ DEBUG ] [ replacement:89 ] Created edge from spatial_temporal_network/motion/conblock_2/bn/batchnorm/sub/add_ to spatial_temporal_network/motion/conblock_2/bn/batchnorm/add_1 with attrs: {'in': 1, 'out': 0, 'fw_tensor_debug_info': [('spatial_temporal_network/motion/conblock_2/bn/batchnorm/sub', 0)], 'in_attrs': ['in', 'control_flow_edge', 'permutation'], 'out_attrs': ['out', 'permutation'], 'data_attrs': ['fw_tensor_debug_info'], 'control_flow_edge': False} [ 2019-03-21 16:52:46,648 ] [ DEBUG ] [ replacement:197 ] Removing nodes: ['spatial_temporal_network/motion/conblock_2/bn/batchnorm/sub'] [ 2019-03-21 16:52:46,649 ] [ DEBUG ] [ replacement:89 ] Created edge from spatial_temporal_network/motion/conblock_3/bn/batchnorm/sub/add_ to spatial_temporal_network/motion/conblock_3/bn/batchnorm/add_1 with attrs: {'in': 1, 'out': 0, 'fw_tensor_debug_info': [('spatial_temporal_network/motion/conblock_3/bn/batchnorm/sub', 0)], 'in_attrs': ['in', 'control_flow_edge', 'permutation'], 'out_attrs': ['out', 'permutation'], 'data_attrs': ['fw_tensor_debug_info'], 'control_flow_edge': False} [ 2019-03-21 16:52:46,649 ] [ DEBUG ] [ replacement:197 ] Removing nodes: ['spatial_temporal_network/motion/conblock_3/bn/batchnorm/sub'] [ 2019-03-21 16:52:46,650 ] [ DEBUG ] [ replacement:89 ] Created edge from spatial_temporal_network/geo/conblock_3/bn/batchnorm/sub/add_ to spatial_temporal_network/geo/conblock_3/bn/batchnorm/add_1 with attrs: {'in': 1, 'out': 0, 'fw_tensor_debug_info': [('spatial_temporal_network/geo/conblock_3/bn/batchnorm/sub', 0)], 'in_attrs': ['in', 'control_flow_edge', 'permutation'], 'out_attrs': ['out', 'permutation'], 'data_attrs': ['fw_tensor_debug_info'], 'control_flow_edge': False} [ 2019-03-21 16:52:46,650 ] [ DEBUG ] [ replacement:197 ] Removing nodes: ['spatial_temporal_network/geo/conblock_3/bn/batchnorm/sub'] [ 2019-03-21 16:52:46,654 ] [ DEBUG ] [ class_registration:111 ] Run replacer [ 2019-03-21 16:52:46,694 ] [ DEBUG ] [ class_registration:111 ] Run replacer [ WARNING ] Configuration file for custom replacement with id 'ObjectDetectionAPIMaskRCNNROIPoolingSecondReplacement' doesn't exist [ INFO ] Failed to find custom replacement description with id 'ObjectDetectionAPIMaskRCNNROIPoolingSecondReplacement' [ 2019-03-21 16:52:46,695 ] [ DEBUG ] [ class_registration:111 ] Run replacer [ WARNING ] Configuration file for custom replacement with id 'ObjectDetectionAPIMaskRCNNSigmoidReplacement' doesn't exist [ INFO ] Failed to find custom replacement description with id 'ObjectDetectionAPIMaskRCNNSigmoidReplacement' [ 2019-03-21 16:52:46,695 ] [ DEBUG ] [ class_registration:111 ] Run replacer [ 2019-03-21 16:52:46,734 ] [ DEBUG ] [ replacement:89 ] Created edge from spatial_temporal_network/flatten/Reshape/shape/Concat_ to spatial_temporal_network/flatten/Reshape with attrs: {'in': 1, 'out': 0, 'fw_tensor_debug_info': [('spatial_temporal_network/flatten/Reshape/shape', 0)], 'in_attrs': ['in', 'control_flow_edge', 'permutation'], 'out_attrs': ['out', 'permutation'], 'data_attrs': ['fw_tensor_debug_info'], 'control_flow_edge': False} [ 2019-03-21 16:52:46,734 ] [ DEBUG ] [ replacement:197 ] Removing nodes: ['spatial_temporal_network/flatten/Reshape/shape'] [ 2019-03-21 16:52:46,830 ] [ DEBUG ] [ eliminate:64 ] The following nodes are seeded as output reachable: output/sink_port_0 [ 2019-03-21 16:52:46,980 ] [ DEBUG ] [ eliminate:130 ] Removing the following dead nodes: spatial_temporal_network/rnn_net/rnn/while/rnn/multi_rnn_cell/cell_0/lstm_cell/BiasAdd spatial_temporal_network/rnn_net/rnn/while/rnn/multi_rnn_cell/cell_0/lstm_cell/BiasAdd/Output_0/Data_ spatial_temporal_network/rnn_net/rnn/while/rnn/multi_rnn_cell/cell_0/lstm_cell/BiasAdd_1 spatial_temporal_network/rnn_net/rnn/while/rnn/multi_rnn_cell/cell_0/lstm_cell/BiasAdd_1/Output_0/Data_ spatial_temporal_network/rnn_net/rnn/while/rnn/multi_rnn_cell/cell_0/lstm_cell/BiasAdd_2 spatial_temporal_network/rnn_net/rnn/while/rnn/multi_rnn_cell/cell_0/lstm_cell/BiasAdd_2/Output_0/Data_ spatial_temporal_network/rnn_net/rnn/while/rnn/multi_rnn_cell/cell_0/lstm_cell/MatMul spatial_temporal_network/rnn_net/rnn/while/rnn/multi_rnn_cell/cell_0/lstm_cell/MatMul/Output_0/Data_ spatial_temporal_network/rnn_net/rnn/while/rnn/multi_rnn_cell/cell_0/lstm_cell/MatMul_1 spatial_temporal_network/rnn_net/rnn/while/rnn/multi_rnn_cell/cell_0/lstm_cell/MatMul_1/Output_0/Data_ spatial_temporal_network/rnn_net/rnn/while/rnn/multi_rnn_cell/cell_0/lstm_cell/MatMul_2 spatial_temporal_network/rnn_net/rnn/while/rnn/multi_rnn_cell/cell_0/lstm_cell/MatMul_2/Output_0/Data_ spatial_temporal_network/rnn_net/rnn/while/rnn/multi_rnn_cell/cell_0/lstm_cell/Sigmoid spatial_temporal_network/rnn_net/rnn/while/rnn/multi_rnn_cell/cell_0/lstm_cell/Sigmoid/Output_0/Data_ spatial_temporal_network/rnn_net/rnn/while/rnn/multi_rnn_cell/cell_0/lstm_cell/Sigmoid_1 spatial_temporal_network/rnn_net/rnn/while/rnn/multi_rnn_cell/cell_0/lstm_cell/Sigmoid_1/Output_0/Data_ spatial_temporal_network/rnn_net/rnn/while/rnn/multi_rnn_cell/cell_0/lstm_cell/Sigmoid_2 spatial_temporal_network/rnn_net/rnn/while/rnn/multi_rnn_cell/cell_0/lstm_cell/Sigmoid_3 spatial_temporal_network/rnn_net/rnn/while/rnn/multi_rnn_cell/cell_0/lstm_cell/Sigmoid_3/Output_0/Data_ spatial_temporal_network/rnn_net/rnn/while/rnn/multi_rnn_cell/cell_0/lstm_cell/Sigmoid_4 spatial_temporal_network/rnn_net/rnn/while/rnn/multi_rnn_cell/cell_0/lstm_cell/Sigmoid_4/Output_0/Data_ spatial_temporal_network/rnn_net/rnn/while/rnn/multi_rnn_cell/cell_0/lstm_cell/Sigmoid_5 spatial_temporal_network/rnn_net/rnn/while/rnn/multi_rnn_cell/cell_0/lstm_cell/Sigmoid_6 spatial_temporal_network/rnn_net/rnn/while/rnn/multi_rnn_cell/cell_0/lstm_cell/Sigmoid_6/Output_0/Data_ spatial_temporal_network/rnn_net/rnn/while/rnn/multi_rnn_cell/cell_0/lstm_cell/Sigmoid_7 spatial_temporal_network/rnn_net/rnn/while/rnn/multi_rnn_cell/cell_0/lstm_cell/Sigmoid_7/Output_0/Data_ spatial_temporal_network/rnn_net/rnn/while/rnn/multi_rnn_cell/cell_0/lstm_cell/Sigmoid_8 spatial_temporal_network/rnn_net/rnn/while/rnn/multi_rnn_cell/cell_0/lstm_cell/Tanh spatial_temporal_network/rnn_net/rnn/while/rnn/multi_rnn_cell/cell_0/lstm_cell/Tanh/Output_0/Data_ spatial_temporal_network/rnn_net/rnn/while/rnn/multi_rnn_cell/cell_0/lstm_cell/Tanh_2 spatial_temporal_network/rnn_net/rnn/while/rnn/multi_rnn_cell/cell_0/lstm_cell/Tanh_2/Output_0/Data_ spatial_temporal_network/rnn_net/rnn/while/rnn/multi_rnn_cell/cell_0/lstm_cell/Tanh_4 spatial_temporal_network/rnn_net/rnn/while/rnn/multi_rnn_cell/cell_0/lstm_cell/Tanh_4/Output_0/Data_ spatial_temporal_network/rnn_net/rnn/while/rnn/multi_rnn_cell/cell_0/lstm_cell/add spatial_temporal_network/rnn_net/rnn/while/rnn/multi_rnn_cell/cell_0/lstm_cell/add/Output_0/Data_ spatial_temporal_network/rnn_net/rnn/while/rnn/multi_rnn_cell/cell_0/lstm_cell/add_2 spatial_temporal_network/rnn_net/rnn/while/rnn/multi_rnn_cell/cell_0/lstm_cell/add_2/Output_0/Data_ spatial_temporal_network/rnn_net/rnn/while/rnn/multi_rnn_cell/cell_0/lstm_cell/add_4 spatial_temporal_network/rnn_net/rnn/while/rnn/multi_rnn_cell/cell_0/lstm_cell/add_4/Output_0/Data_ spatial_temporal_network/rnn_net/rnn/while/rnn/multi_rnn_cell/cell_0/lstm_cell/concat spatial_temporal_network/rnn_net/rnn/while/rnn/multi_rnn_cell/cell_0/lstm_cell/concat/Output_0/Data_ spatial_temporal_network/rnn_net/rnn/while/rnn/multi_rnn_cell/cell_0/lstm_cell/concat_1 spatial_temporal_network/rnn_net/rnn/while/rnn/multi_rnn_cell/cell_0/lstm_cell/concat_1/Output_0/Data_ spatial_temporal_network/rnn_net/rnn/while/rnn/multi_rnn_cell/cell_0/lstm_cell/concat_2 spatial_temporal_network/rnn_net/rnn/while/rnn/multi_rnn_cell/cell_0/lstm_cell/concat_2/Output_0/Data_ spatial_temporal_network/rnn_net/rnn/while/rnn/multi_rnn_cell/cell_0/lstm_cell/mul spatial_temporal_network/rnn_net/rnn/while/rnn/multi_rnn_cell/cell_0/lstm_cell/mul_1 spatial_temporal_network/rnn_net/rnn/while/rnn/multi_rnn_cell/cell_0/lstm_cell/mul_3 spatial_temporal_network/rnn_net/rnn/while/rnn/multi_rnn_cell/cell_0/lstm_cell/mul_4 spatial_temporal_network/rnn_net/rnn/while/rnn/multi_rnn_cell/cell_0/lstm_cell/mul_6 spatial_temporal_network/rnn_net/rnn/while/rnn/multi_rnn_cell/cell_0/lstm_cell/mul_7 spatial_temporal_network/rnn_net/rnn/while/rnn/multi_rnn_cell/cell_0/lstm_cell/split spatial_temporal_network/rnn_net/rnn/while/rnn/multi_rnn_cell/cell_0/lstm_cell/split/Output_0/Data_ spatial_temporal_network/rnn_net/rnn/while/rnn/multi_rnn_cell/cell_0/lstm_cell/split/Output_1/Data_ spatial_temporal_network/rnn_net/rnn/while/rnn/multi_rnn_cell/cell_0/lstm_cell/split/Output_2/Data_ spatial_temporal_network/rnn_net/rnn/while/rnn/multi_rnn_cell/cell_0/lstm_cell/split/Output_3/Data_ spatial_temporal_network/rnn_net/rnn/while/rnn/multi_rnn_cell/cell_0/lstm_cell/split_1 spatial_temporal_network/rnn_net/rnn/while/rnn/multi_rnn_cell/cell_0/lstm_cell/split_1/Output_0/Data_ spatial_temporal_network/rnn_net/rnn/while/rnn/multi_rnn_cell/cell_0/lstm_cell/split_1/Output_1/Data_ spatial_temporal_network/rnn_net/rnn/while/rnn/multi_rnn_cell/cell_0/lstm_cell/split_1/Output_2/Data_ spatial_temporal_network/rnn_net/rnn/while/rnn/multi_rnn_cell/cell_0/lstm_cell/split_1/Output_3/Data_ spatial_temporal_network/rnn_net/rnn/while/rnn/multi_rnn_cell/cell_0/lstm_cell/split_2 spatial_temporal_network/rnn_net/rnn/while/rnn/multi_rnn_cell/cell_0/lstm_cell/split_2/Output_0/Data_ spatial_temporal_network/rnn_net/rnn/while/rnn/multi_rnn_cell/cell_0/lstm_cell/split_2/Output_1/Data_ spatial_temporal_network/rnn_net/rnn/while/rnn/multi_rnn_cell/cell_0/lstm_cell/split_2/Output_2/Data_ spatial_temporal_network/rnn_net/rnn/while/rnn/multi_rnn_cell/cell_0/lstm_cell/split_2/Output_3/Data_ [ 2019-03-21 16:52:47,033 ] [ DEBUG ] [ infer:150 ] -------------------- [ 2019-03-21 16:52:47,033 ] [ DEBUG ] [ infer:151 ] Partial infer for 429 [ 2019-03-21 16:52:47,033 ] [ DEBUG ] [ infer:152 ] Op: Const [ 2019-03-21 16:52:47,034 ] [ DEBUG ] [ infer:163 ] Inputs: [ 2019-03-21 16:52:47,034 ] [ DEBUG ] [ infer:165 ] Outputs: [ 2019-03-21 16:52:47,035 ] [ DEBUG ] [ infer:40 ] output[0]: shape = [1], value = [0] [ 2019-03-21 16:52:47,036 ] [ DEBUG ] [ infer:150 ] -------------------- [ 2019-03-21 16:52:47,036 ] [ DEBUG ] [ infer:151 ] Partial infer for spatial_temporal_network/dense/bias [ 2019-03-21 16:52:47,036 ] [ DEBUG ] [ infer:152 ] Op: Const [ 2019-03-21 16:52:47,036 ] [ DEBUG ] [ infer:163 ] Inputs: [ 2019-03-21 16:52:47,037 ] [ DEBUG ] [ infer:165 ] Outputs: [ 2019-03-21 16:52:47,038 ] [ DEBUG ] [ infer:40 ] output[0]: shape = [7], value = [ 0.14485614 0.17269324 -0.0195503 -0.10251361 -0.04668584 -0.12757407 -0.0212258 ] [ 2019-03-21 16:52:47,038 ] [ DEBUG ] [ infer:150 ] -------------------- [ 2019-03-21 16:52:47,039 ] [ DEBUG ] [ infer:151 ] Partial infer for spatial_temporal_network/dense/bias/read [ 2019-03-21 16:52:47,039 ] [ DEBUG ] [ infer:152 ] Op: Identity [ 2019-03-21 16:52:47,039 ] [ DEBUG ] [ infer:163 ] Inputs: [ 2019-03-21 16:52:47,039 ] [ DEBUG ] [ infer:40 ] input[0]: shape = [7], value = [ 0.14485614 0.17269324 -0.0195503 -0.10251361 -0.04668584 -0.12757407 -0.0212258 ] [ 2019-03-21 16:52:47,040 ] [ DEBUG ] [ infer:165 ] Outputs: [ 2019-03-21 16:52:47,040 ] [ DEBUG ] [ infer:40 ] output[0]: shape = [7], value = [ 0.14485614 0.17269324 -0.0195503 -0.10251361 -0.04668584 -0.12757407 -0.0212258 ] [ 2019-03-21 16:52:47,041 ] [ DEBUG ] [ infer:150 ] -------------------- [ 2019-03-21 16:52:47,041 ] [ DEBUG ] [ infer:151 ] Partial infer for spatial_temporal_network/dense/kernel [ 2019-03-21 16:52:47,041 ] [ DEBUG ] [ infer:152 ] Op: Const [ 2019-03-21 16:52:47,041 ] [ DEBUG ] [ infer:163 ] Inputs: [ 2019-03-21 16:52:47,042 ] [ DEBUG ] [ infer:165 ] Outputs: [ 2019-03-21 16:52:47,043 ] [ DEBUG ] [ infer:40 ] output[0]: shape = [15360 7], value = [[ 0.00754917 -0.00470051 -0.01742837 ... 0.00815568 -0.01912938 -0.00964213] [-0.000457 -0... [ 2019-03-21 16:52:47,044 ] [ DEBUG ] [ infer:150 ] -------------------- [ 2019-03-21 16:52:47,044 ] [ DEBUG ] [ infer:151 ] Partial infer for spatial_temporal_network/dense/kernel/read [ 2019-03-21 16:52:47,044 ] [ DEBUG ] [ infer:152 ] Op: Identity [ 2019-03-21 16:52:47,045 ] [ DEBUG ] [ infer:163 ] Inputs: [ 2019-03-21 16:52:47,046 ] [ DEBUG ] [ infer:40 ] input[0]: shape = [15360 7], value = [[ 0.00754917 -0.00470051 -0.01742837 ... 0.00815568 -0.01912938 -0.00964213] [-0.000457 -0... [ 2019-03-21 16:52:47,047 ] [ DEBUG ] [ infer:165 ] Outputs: [ 2019-03-21 16:52:47,048 ] [ DEBUG ] [ infer:40 ] output[0]: shape = [15360 7], value = [[ 0.00754917 -0.00470051 -0.01742837 ... 0.00815568 -0.01912938 -0.00964213] [-0.000457 -0... [ 2019-03-21 16:52:47,048 ] [ DEBUG ] [ infer:150 ] -------------------- [ 2019-03-21 16:52:47,049 ] [ DEBUG ] [ infer:151 ] Partial infer for spatial_temporal_network/flatten/Reshape/shape/1 [ 2019-03-21 16:52:47,049 ] [ DEBUG ] [ infer:152 ] Op: Const [ 2019-03-21 16:52:47,049 ] [ DEBUG ] [ infer:163 ] Inputs: [ 2019-03-21 16:52:47,049 ] [ DEBUG ] [ infer:165 ] Outputs: [ 2019-03-21 16:52:47,050 ] [ DEBUG ] [ infer:40 ] output[0]: shape = [], value = -1 [ 2019-03-21 16:52:47,050 ] [ DEBUG ] [ infer:150 ] -------------------- [ 2019-03-21 16:52:47,050 ] [ DEBUG ] [ infer:151 ] Partial infer for spatial_temporal_network/flatten/Reshape/shape/ExpandDims_431 [ 2019-03-21 16:52:47,050 ] [ DEBUG ] [ infer:152 ] Op: ExpandDims [ 2019-03-21 16:52:47,051 ] [ DEBUG ] [ infer:163 ] Inputs: [ 2019-03-21 16:52:47,051 ] [ DEBUG ] [ infer:40 ] input[0]: shape = [], value = -1 [ 2019-03-21 16:52:47,051 ] [ DEBUG ] [ infer:165 ] Outputs: [ 2019-03-21 16:52:47,052 ] [ DEBUG ] [ infer:40 ] output[0]: shape = [1], value = [-1] [ 2019-03-21 16:52:47,052 ] [ DEBUG ] [ infer:150 ] -------------------- [ 2019-03-21 16:52:47,052 ] [ DEBUG ] [ infer:151 ] Partial infer for spatial_temporal_network/flatten/strided_slice/stack_2 [ 2019-03-21 16:52:47,053 ] [ DEBUG ] [ infer:152 ] Op: Const [ 2019-03-21 16:52:47,053 ] [ DEBUG ] [ infer:163 ] Inputs: [ 2019-03-21 16:52:47,053 ] [ DEBUG ] [ infer:165 ] Outputs: [ 2019-03-21 16:52:47,053 ] [ DEBUG ] [ infer:40 ] output[0]: shape = [1], value = [1] [ 2019-03-21 16:52:47,054 ] [ DEBUG ] [ infer:150 ] -------------------- [ 2019-03-21 16:52:47,054 ] [ DEBUG ] [ infer:151 ] Partial infer for spatial_temporal_network/flatten/strided_slice/stack_1 [ 2019-03-21 16:52:47,054 ] [ DEBUG ] [ infer:152 ] Op: Const [ 2019-03-21 16:52:47,054 ] [ DEBUG ] [ infer:163 ] Inputs: [ 2019-03-21 16:52:47,055 ] [ DEBUG ] [ infer:165 ] Outputs: [ 2019-03-21 16:52:47,055 ] [ DEBUG ] [ infer:40 ] output[0]: shape = [1], value = [1] [ 2019-03-21 16:52:47,055 ] [ DEBUG ] [ infer:150 ] -------------------- [ 2019-03-21 16:52:47,056 ] [ DEBUG ] [ infer:151 ] Partial infer for spatial_temporal_network/flatten/strided_slice/stack [ 2019-03-21 16:52:47,056 ] [ DEBUG ] [ infer:152 ] Op: Const [ 2019-03-21 16:52:47,056 ] [ DEBUG ] [ infer:163 ] Inputs: [ 2019-03-21 16:52:47,056 ] [ DEBUG ] [ infer:165 ] Outputs: [ 2019-03-21 16:52:47,057 ] [ DEBUG ] [ infer:40 ] output[0]: shape = [1], value = [0] [ 2019-03-21 16:52:47,057 ] [ DEBUG ] [ infer:150 ] -------------------- [ 2019-03-21 16:52:47,057 ] [ DEBUG ] [ infer:151 ] Partial infer for spatial_temporal_network/flatten/Shape [ 2019-03-21 16:52:47,057 ] [ DEBUG ] [ infer:152 ] Op: Const [ 2019-03-21 16:52:47,058 ] [ DEBUG ] [ infer:163 ] Inputs: [ 2019-03-21 16:52:47,058 ] [ DEBUG ] [ infer:165 ] Outputs: [ 2019-03-21 16:52:47,058 ] [ DEBUG ] [ infer:40 ] output[0]: shape = [3], value = [ 1 30 512] [ 2019-03-21 16:52:47,059 ] [ DEBUG ] [ infer:150 ] -------------------- [ 2019-03-21 16:52:47,059 ] [ DEBUG ] [ infer:151 ] Partial infer for spatial_temporal_network/flatten/strided_slice [ 2019-03-21 16:52:47,059 ] [ DEBUG ] [ infer:152 ] Op: StridedSlice [ 2019-03-21 16:52:47,060 ] [ DEBUG ] [ infer:163 ] Inputs: [ 2019-03-21 16:52:47,061 ] [ DEBUG ] [ infer:40 ] input[0]: shape = [3], value = [ 1 30 512] [ 2019-03-21 16:52:47,062 ] [ DEBUG ] [ infer:40 ] input[1]: shape = [1], value = [0] [ 2019-03-21 16:52:47,062 ] [ DEBUG ] [ infer:40 ] input[2]: shape = [1], value = [1] [ 2019-03-21 16:52:47,063 ] [ DEBUG ] [ infer:40 ] input[3]: shape = [1], value = [1] [ 2019-03-21 16:52:47,063 ] [ DEBUG ] [ infer:165 ] Outputs: [ 2019-03-21 16:52:47,063 ] [ DEBUG ] [ infer:40 ] output[0]: shape = [], value = 1 [ 2019-03-21 16:52:47,063 ] [ DEBUG ] [ infer:150 ] -------------------- [ 2019-03-21 16:52:47,064 ] [ DEBUG ] [ infer:151 ] Partial infer for spatial_temporal_network/flatten/Reshape/shape/ExpandDims_ [ 2019-03-21 16:52:47,064 ] [ DEBUG ] [ infer:152 ] Op: ExpandDims [ 2019-03-21 16:52:47,064 ] [ DEBUG ] [ infer:163 ] Inputs: [ 2019-03-21 16:52:47,065 ] [ DEBUG ] [ infer:40 ] input[0]: shape = [], value = 1 [ 2019-03-21 16:52:47,065 ] [ DEBUG ] [ infer:165 ] Outputs: [ 2019-03-21 16:52:47,065 ] [ DEBUG ] [ infer:40 ] output[0]: shape = [1], value = [1] [ 2019-03-21 16:52:47,066 ] [ DEBUG ] [ infer:150 ] -------------------- [ 2019-03-21 16:52:47,066 ] [ DEBUG ] [ infer:151 ] Partial infer for spatial_temporal_network/flatten/Reshape/shape/Concat_ [ 2019-03-21 16:52:47,066 ] [ DEBUG ] [ infer:152 ] Op: Concat [ 2019-03-21 16:52:47,067 ] [ DEBUG ] [ infer:163 ] Inputs: [ 2019-03-21 16:52:47,068 ] [ DEBUG ] [ infer:40 ] input[0]: shape = [1], value = [1] [ 2019-03-21 16:52:47,068 ] [ DEBUG ] [ infer:40 ] input[1]: shape = [1], value = [-1] [ 2019-03-21 16:52:47,068 ] [ DEBUG ] [ infer:165 ] Outputs: [ 2019-03-21 16:52:47,069 ] [ DEBUG ] [ infer:40 ] output[0]: shape = [2], value = [ 1 -1] [ 2019-03-21 16:52:47,069 ] [ DEBUG ] [ infer:150 ] -------------------- [ 2019-03-21 16:52:47,069 ] [ DEBUG ] [ infer:151 ] Partial infer for spatial_temporal_network/rnn_net/rnn/concat_2/axis [ 2019-03-21 16:52:47,070 ] [ DEBUG ] [ infer:152 ] Op: Const [ 2019-03-21 16:52:47,070 ] [ DEBUG ] [ infer:163 ] Inputs: [ 2019-03-21 16:52:47,070 ] [ DEBUG ] [ infer:165 ] Outputs: [ 2019-03-21 16:52:47,070 ] [ DEBUG ] [ infer:40 ] output[0]: shape = [], value = 0 [ 2019-03-21 16:52:47,071 ] [ DEBUG ] [ infer:150 ] -------------------- [ 2019-03-21 16:52:47,071 ] [ DEBUG ] [ infer:151 ] Partial infer for spatial_temporal_network/rnn_net/rnn/concat_2/values_0 [ 2019-03-21 16:52:47,071 ] [ DEBUG ] [ infer:152 ] Op: Const [ 2019-03-21 16:52:47,071 ] [ DEBUG ] [ infer:163 ] Inputs: [ 2019-03-21 16:52:47,071 ] [ DEBUG ] [ infer:165 ] Outputs: [ 2019-03-21 16:52:47,072 ] [ DEBUG ] [ infer:40 ] output[0]: shape = [2], value = [1 0] [ 2019-03-21 16:52:47,072 ] [ DEBUG ] [ infer:150 ] -------------------- [ 2019-03-21 16:52:47,072 ] [ DEBUG ] [ infer:151 ] Partial infer for spatial_temporal_network/rnn_net/rnn/range_1/delta [ 2019-03-21 16:52:47,072 ] [ DEBUG ] [ infer:152 ] Op: Const [ 2019-03-21 16:52:47,073 ] [ DEBUG ] [ infer:163 ] Inputs: [ 2019-03-21 16:52:47,073 ] [ DEBUG ] [ infer:165 ] Outputs: [ 2019-03-21 16:52:47,073 ] [ DEBUG ] [ infer:40 ] output[0]: shape = [], value = 1 [ 2019-03-21 16:52:47,073 ] [ DEBUG ] [ infer:150 ] -------------------- [ 2019-03-21 16:52:47,073 ] [ DEBUG ] [ infer:151 ] Partial infer for spatial_temporal_network/rnn_net/rnn/range_1/start [ 2019-03-21 16:52:47,074 ] [ DEBUG ] [ infer:152 ] Op: Const [ 2019-03-21 16:52:47,074 ] [ DEBUG ] [ infer:163 ] Inputs: [ 2019-03-21 16:52:47,074 ] [ DEBUG ] [ infer:165 ] Outputs: [ 2019-03-21 16:52:47,074 ] [ DEBUG ] [ infer:40 ] output[0]: shape = [], value = 2 [ 2019-03-21 16:52:47,075 ] [ DEBUG ] [ infer:150 ] -------------------- [ 2019-03-21 16:52:47,075 ] [ DEBUG ] [ infer:151 ] Partial infer for spatial_temporal_network/rnn_net/rnn/Rank_1 [ 2019-03-21 16:52:47,075 ] [ DEBUG ] [ infer:152 ] Op: Const [ 2019-03-21 16:52:47,075 ] [ DEBUG ] [ infer:163 ] Inputs: [ 2019-03-21 16:52:47,075 ] [ DEBUG ] [ infer:165 ] Outputs: [ 2019-03-21 16:52:47,076 ] [ DEBUG ] [ infer:40 ] output[0]: shape = [], value = 3 [ 2019-03-21 16:52:47,076 ] [ DEBUG ] [ infer:150 ] -------------------- [ 2019-03-21 16:52:47,076 ] [ DEBUG ] [ infer:151 ] Partial infer for spatial_temporal_network/rnn_net/rnn/range_1 [ 2019-03-21 16:52:47,076 ] [ DEBUG ] [ infer:152 ] Op: Range [ 2019-03-21 16:52:47,077 ] [ DEBUG ] [ infer:163 ] Inputs: [ 2019-03-21 16:52:47,077 ] [ DEBUG ] [ infer:40 ] input[1]: shape = [], value = 3 [ 2019-03-21 16:52:47,077 ] [ DEBUG ] [ infer:40 ] input[0]: shape = [], value = 2 [ 2019-03-21 16:52:47,078 ] [ DEBUG ] [ infer:40 ] input[2]: shape = [], value = 1 [ 2019-03-21 16:52:47,078 ] [ DEBUG ] [ infer:165 ] Outputs: [ 2019-03-21 16:52:47,078 ] [ DEBUG ] [ infer:40 ] output[0]: shape = [1], value = [2] [ 2019-03-21 16:52:47,078 ] [ DEBUG ] [ infer:150 ] -------------------- [ 2019-03-21 16:52:47,079 ] [ DEBUG ] [ infer:151 ] Partial infer for spatial_temporal_network/rnn_net/rnn/concat_2 [ 2019-03-21 16:52:47,079 ] [ DEBUG ] [ infer:152 ] Op: ConcatV2 [ 2019-03-21 16:52:47,079 ] [ DEBUG ] [ infer:163 ] Inputs: [ 2019-03-21 16:52:47,080 ] [ DEBUG ] [ infer:40 ] input[1]: shape = [1], value = [2] [ 2019-03-21 16:52:47,080 ] [ DEBUG ] [ infer:40 ] input[0]: shape = [2], value = [1 0] [ 2019-03-21 16:52:47,080 ] [ DEBUG ] [ infer:165 ] Outputs: [ 2019-03-21 16:52:47,081 ] [ DEBUG ] [ infer:40 ] output[0]: shape = [3], value = [1 0 2] [ 2019-03-21 16:52:47,081 ] [ DEBUG ] [ infer:150 ] -------------------- [ 2019-03-21 16:52:47,081 ] [ DEBUG ] [ infer:151 ] Partial infer for spatial_temporal_network/rnn_net/rnn/TensorArrayStack/range/delta [ 2019-03-21 16:52:47,081 ] [ DEBUG ] [ infer:152 ] Op: Const [ 2019-03-21 16:52:47,082 ] [ DEBUG ] [ infer:163 ] Inputs: [ 2019-03-21 16:52:47,082 ] [ DEBUG ] [ infer:165 ] Outputs: [ 2019-03-21 16:52:47,082 ] [ DEBUG ] [ infer:40 ] output[0]: shape = [], value = 1 [ 2019-03-21 16:52:47,082 ] [ DEBUG ] [ infer:150 ] -------------------- [ 2019-03-21 16:52:47,083 ] [ DEBUG ] [ infer:151 ] Partial infer for spatial_temporal_network/rnn_net/rnn/TensorArrayStack/range/start [ 2019-03-21 16:52:47,083 ] [ DEBUG ] [ infer:152 ] Op: Const [ 2019-03-21 16:52:47,083 ] [ DEBUG ] [ infer:163 ] Inputs: [ 2019-03-21 16:52:47,083 ] [ DEBUG ] [ infer:165 ] Outputs: [ 2019-03-21 16:52:47,083 ] [ DEBUG ] [ infer:40 ] output[0]: shape = [], value = 0 [ 2019-03-21 16:52:47,084 ] [ DEBUG ] [ infer:150 ] -------------------- [ 2019-03-21 16:52:47,084 ] [ DEBUG ] [ infer:151 ] Partial infer for spatial_temporal_network/rnn_net/rnn/multi_rnn_cell/cell_0/lstm_cell/bias [ 2019-03-21 16:52:47,084 ] [ DEBUG ] [ infer:152 ] Op: Const [ 2019-03-21 16:52:47,084 ] [ DEBUG ] [ infer:163 ] Inputs: [ 2019-03-21 16:52:47,085 ] [ DEBUG ] [ infer:165 ] Outputs: [ 2019-03-21 16:52:47,087 ] [ DEBUG ] [ infer:40 ] output[0]: shape = [2048], value = [-0.0019465 -0.00394747 -0.0043961 ... -0.00155008 -0.00426906 -0.00050209] [ 2019-03-21 16:52:47,087 ] [ DEBUG ] [ infer:150 ] -------------------- [ 2019-03-21 16:52:47,088 ] [ DEBUG ] [ infer:151 ] Partial infer for spatial_temporal_network/rnn_net/rnn/multi_rnn_cell/cell_0/lstm_cell/bias/read [ 2019-03-21 16:52:47,088 ] [ DEBUG ] [ infer:152 ] Op: Identity [ 2019-03-21 16:52:47,088 ] [ DEBUG ] [ infer:163 ] Inputs: [ 2019-03-21 16:52:47,089 ] [ DEBUG ] [ infer:40 ] input[0]: shape = [2048], value = [-0.0019465 -0.00394747 -0.0043961 ... -0.00155008 -0.00426906 -0.00050209] [ 2019-03-21 16:52:47,089 ] [ DEBUG ] [ infer:165 ] Outputs: [ 2019-03-21 16:52:47,090 ] [ DEBUG ] [ infer:40 ] output[0]: shape = [2048], value = [-0.0019465 -0.00394747 -0.0043961 ... -0.00155008 -0.00426906 -0.00050209] [ 2019-03-21 16:52:47,090 ] [ DEBUG ] [ infer:150 ] -------------------- [ 2019-03-21 16:52:47,090 ] [ DEBUG ] [ infer:151 ] Partial infer for spatial_temporal_network/rnn_net/rnn/while/rnn/multi_rnn_cell/cell_0/lstm_cell/BiasAdd/Enter [ 2019-03-21 16:52:47,091 ] [ DEBUG ] [ infer:152 ] Op: Enter [ 2019-03-21 16:52:47,091 ] [ DEBUG ] [ infer:163 ] Inputs: [ 2019-03-21 16:52:47,092 ] [ DEBUG ] [ infer:40 ] input[0]: shape = [2048], value = [-0.0019465 -0.00394747 -0.0043961 ... -0.00155008 -0.00426906 -0.00050209] [ 2019-03-21 16:52:47,092 ] [ DEBUG ] [ infer:165 ] Outputs: [ 2019-03-21 16:52:47,093 ] [ DEBUG ] [ infer:40 ] output[0]: shape = [2048], value = [-0.0019465 -0.00394747 -0.0043961 ... -0.00155008 -0.00426906 -0.00050209] [ 2019-03-21 16:52:47,093 ] [ DEBUG ] [ infer:150 ] -------------------- [ 2019-03-21 16:52:47,093 ] [ DEBUG ] [ infer:151 ] Partial infer for spatial_temporal_network/rnn_net/rnn/multi_rnn_cell/cell_0/lstm_cell/kernel [ 2019-03-21 16:52:47,093 ] [ DEBUG ] [ infer:152 ] Op: Const [ 2019-03-21 16:52:47,093 ] [ DEBUG ] [ infer:163 ] Inputs: [ 2019-03-21 16:52:47,094 ] [ DEBUG ] [ infer:165 ] Outputs: [ 2019-03-21 16:52:47,096 ] [ DEBUG ] [ infer:40 ] output[0]: shape = [1024 2048], value = [[ 0.01566458 0.02684669 -0.01590733 ... 0.05444227 0.03510743 -0.01613005] [-0.04275664 0... [ 2019-03-21 16:52:47,096 ] [ DEBUG ] [ infer:150 ] -------------------- [ 2019-03-21 16:52:47,096 ] [ DEBUG ] [ infer:151 ] Partial infer for spatial_temporal_network/rnn_net/rnn/multi_rnn_cell/cell_0/lstm_cell/kernel/read [ 2019-03-21 16:52:47,097 ] [ DEBUG ] [ infer:152 ] Op: Identity [ 2019-03-21 16:52:47,097 ] [ DEBUG ] [ infer:163 ] Inputs: [ 2019-03-21 16:52:47,099 ] [ DEBUG ] [ infer:40 ] input[0]: shape = [1024 2048], value = [[ 0.01566458 0.02684669 -0.01590733 ... 0.05444227 0.03510743 -0.01613005] [-0.04275664 0... [ 2019-03-21 16:52:47,099 ] [ DEBUG ] [ infer:165 ] Outputs: [ 2019-03-21 16:52:47,100 ] [ DEBUG ] [ infer:40 ] output[0]: shape = [1024 2048], value = [[ 0.01566458 0.02684669 -0.01590733 ... 0.05444227 0.03510743 -0.01613005] [-0.04275664 0... [ 2019-03-21 16:52:47,101 ] [ DEBUG ] [ infer:150 ] -------------------- [ 2019-03-21 16:52:47,101 ] [ DEBUG ] [ infer:151 ] Partial infer for spatial_temporal_network/rnn_net/rnn/while/rnn/multi_rnn_cell/cell_0/lstm_cell/MatMul/Enter [ 2019-03-21 16:52:47,101 ] [ DEBUG ] [ infer:152 ] Op: Enter [ 2019-03-21 16:52:47,105 ] [ DEBUG ] [ infer:163 ] Inputs: [ 2019-03-21 16:52:47,107 ] [ DEBUG ] [ infer:40 ] input[0]: shape = [1024 2048], value = [[ 0.01566458 0.02684669 -0.01590733 ... 0.05444227 0.03510743 -0.01613005] [-0.04275664 0... [ 2019-03-21 16:52:47,107 ] [ DEBUG ] [ infer:165 ] Outputs: [ 2019-03-21 16:52:47,109 ] [ DEBUG ] [ infer:40 ] output[0]: shape = [1024 2048], value = [[ 0.01566458 0.02684669 -0.01590733 ... 0.05444227 0.03510743 -0.01613005] [-0.04275664 0... [ 2019-03-21 16:52:47,109 ] [ DEBUG ] [ infer:150 ] -------------------- [ 2019-03-21 16:52:47,110 ] [ DEBUG ] [ infer:151 ] Partial infer for spatial_temporal_network/rnn_net/rnn/while/iteration_counter [ 2019-03-21 16:52:47,110 ] [ DEBUG ] [ infer:152 ] Op: Const [ 2019-03-21 16:52:47,110 ] [ DEBUG ] [ infer:163 ] Inputs: [ 2019-03-21 16:52:47,110 ] [ DEBUG ] [ infer:165 ] Outputs: [ 2019-03-21 16:52:47,111 ] [ DEBUG ] [ infer:40 ] output[0]: shape = [], value = 0 [ 2019-03-21 16:52:47,111 ] [ DEBUG ] [ infer:150 ] -------------------- [ 2019-03-21 16:52:47,111 ] [ DEBUG ] [ infer:151 ] Partial infer for spatial_temporal_network/rnn_net/rnn/while/Enter [ 2019-03-21 16:52:47,111 ] [ DEBUG ] [ infer:152 ] Op: Enter [ 2019-03-21 16:52:47,112 ] [ DEBUG ] [ infer:163 ] Inputs: [ 2019-03-21 16:52:47,112 ] [ DEBUG ] [ infer:40 ] input[0]: shape = [], value = 0 [ 2019-03-21 16:52:47,112 ] [ DEBUG ] [ infer:165 ] Outputs: [ 2019-03-21 16:52:47,112 ] [ DEBUG ] [ infer:40 ] output[0]: shape = [], value = 0 [ 2019-03-21 16:52:47,113 ] [ DEBUG ] [ infer:150 ] -------------------- [ 2019-03-21 16:52:47,113 ] [ DEBUG ] [ infer:151 ] Partial infer for spatial_temporal_network/rnn_net/rnn/while/Merge [ 2019-03-21 16:52:47,113 ] [ DEBUG ] [ infer:152 ] Op: Merge [ 2019-03-21 16:52:47,113 ] [ DEBUG ] [ infer:163 ] Inputs: [ 2019-03-21 16:52:47,114 ] [ DEBUG ] [ infer:40 ] input[0]: shape = [], value = 0 [ 2019-03-21 16:52:47,114 ] [ DEBUG ] [ infer:40 ] input[1]: shape = , value = [ 2019-03-21 16:52:47,114 ] [ DEBUG ] [ infer:165 ] Outputs: [ 2019-03-21 16:52:47,116 ] [ DEBUG ] [ infer:40 ] output[0]: shape = [], value = [ 2019-03-21 16:52:47,116 ] [ DEBUG ] [ infer:150 ] -------------------- [ 2019-03-21 16:52:47,116 ] [ DEBUG ] [ infer:151 ] Partial infer for spatial_temporal_network/rnn_net/rnn/Maximum/x [ 2019-03-21 16:52:47,117 ] [ DEBUG ] [ infer:152 ] Op: Const [ 2019-03-21 16:52:47,117 ] [ DEBUG ] [ infer:163 ] Inputs: [ 2019-03-21 16:52:47,117 ] [ DEBUG ] [ infer:165 ] Outputs: [ 2019-03-21 16:52:47,117 ] [ DEBUG ] [ infer:40 ] output[0]: shape = [], value = 1 [ 2019-03-21 16:52:47,118 ] [ DEBUG ] [ infer:150 ] -------------------- [ 2019-03-21 16:52:47,118 ] [ DEBUG ] [ infer:151 ] Partial infer for spatial_temporal_network/rnn_net/rnn/TensorArrayUnstack/range/delta [ 2019-03-21 16:52:47,118 ] [ DEBUG ] [ infer:152 ] Op: Const [ 2019-03-21 16:52:47,118 ] [ DEBUG ] [ infer:163 ] Inputs: [ 2019-03-21 16:52:47,119 ] [ DEBUG ] [ infer:165 ] Outputs: [ 2019-03-21 16:52:47,119 ] [ DEBUG ] [ infer:40 ] output[0]: shape = [], value = 1 [ 2019-03-21 16:52:47,120 ] [ DEBUG ] [ infer:150 ] -------------------- [ 2019-03-21 16:52:47,120 ] [ DEBUG ] [ infer:151 ] Partial infer for spatial_temporal_network/rnn_net/rnn/TensorArrayUnstack/range/start [ 2019-03-21 16:52:47,120 ] [ DEBUG ] [ infer:152 ] Op: Const [ 2019-03-21 16:52:47,120 ] [ DEBUG ] [ infer:163 ] Inputs: [ 2019-03-21 16:52:47,121 ] [ DEBUG ] [ infer:165 ] Outputs: [ 2019-03-21 16:52:47,121 ] [ DEBUG ] [ infer:40 ] output[0]: shape = [], value = 0 [ 2019-03-21 16:52:47,121 ] [ DEBUG ] [ infer:150 ] -------------------- [ 2019-03-21 16:52:47,121 ] [ DEBUG ] [ infer:151 ] Partial infer for spatial_temporal_network/rnn_net/rnn/TensorArrayUnstack/strided_slice/stack_2 [ 2019-03-21 16:52:47,122 ] [ DEBUG ] [ infer:152 ] Op: Const [ 2019-03-21 16:52:47,122 ] [ DEBUG ] [ infer:163 ] Inputs: [ 2019-03-21 16:52:47,122 ] [ DEBUG ] [ infer:165 ] Outputs: [ 2019-03-21 16:52:47,122 ] [ DEBUG ] [ infer:40 ] output[0]: shape = [1], value = [1] [ 2019-03-21 16:52:47,123 ] [ DEBUG ] [ infer:150 ] -------------------- [ 2019-03-21 16:52:47,123 ] [ DEBUG ] [ infer:151 ] Partial infer for spatial_temporal_network/rnn_net/rnn/TensorArrayUnstack/strided_slice/stack_1 [ 2019-03-21 16:52:47,123 ] [ DEBUG ] [ infer:152 ] Op: Const [ 2019-03-21 16:52:47,123 ] [ DEBUG ] [ infer:163 ] Inputs: [ 2019-03-21 16:52:47,124 ] [ DEBUG ] [ infer:165 ] Outputs: [ 2019-03-21 16:52:47,124 ] [ DEBUG ] [ infer:40 ] output[0]: shape = [1], value = [1] [ 2019-03-21 16:52:47,124 ] [ DEBUG ] [ infer:150 ] -------------------- [ 2019-03-21 16:52:47,125 ] [ DEBUG ] [ infer:151 ] Partial infer for spatial_temporal_network/rnn_net/rnn/TensorArrayUnstack/strided_slice/stack [ 2019-03-21 16:52:47,125 ] [ DEBUG ] [ infer:152 ] Op: Const [ 2019-03-21 16:52:47,125 ] [ DEBUG ] [ infer:163 ] Inputs: [ 2019-03-21 16:52:47,125 ] [ DEBUG ] [ infer:165 ] Outputs: [ 2019-03-21 16:52:47,126 ] [ DEBUG ] [ infer:40 ] output[0]: shape = [1], value = [0] [ 2019-03-21 16:52:47,126 ] [ DEBUG ] [ infer:150 ] -------------------- [ 2019-03-21 16:52:47,126 ] [ DEBUG ] [ infer:151 ] Partial infer for spatial_temporal_network/rnn_net/rnn/TensorArrayUnstack/Shape [ 2019-03-21 16:52:47,126 ] [ DEBUG ] [ infer:152 ] Op: Const [ 2019-03-21 16:52:47,127 ] [ DEBUG ] [ infer:163 ] Inputs: [ 2019-03-21 16:52:47,127 ] [ DEBUG ] [ infer:165 ] Outputs: [ 2019-03-21 16:52:47,127 ] [ DEBUG ] [ infer:40 ] output[0]: shape = [3], value = [ 30 1 512] [ 2019-03-21 16:52:47,128 ] [ DEBUG ] [ infer:150 ] -------------------- [ 2019-03-21 16:52:47,128 ] [ DEBUG ] [ infer:151 ] Partial infer for spatial_temporal_network/rnn_net/rnn/TensorArrayUnstack/strided_slice [ 2019-03-21 16:52:47,128 ] [ DEBUG ] [ infer:152 ] Op: StridedSlice [ 2019-03-21 16:52:47,129 ] [ DEBUG ] [ infer:163 ] Inputs: [ 2019-03-21 16:52:47,129 ] [ DEBUG ] [ infer:40 ] input[0]: shape = [3], value = [ 30 1 512] [ 2019-03-21 16:52:47,130 ] [ DEBUG ] [ infer:40 ] input[1]: shape = [1], value = [0] [ 2019-03-21 16:52:47,130 ] [ DEBUG ] [ infer:40 ] input[2]: shape = [1], value = [1] [ 2019-03-21 16:52:47,131 ] [ DEBUG ] [ infer:40 ] input[3]: shape = [1], value = [1] [ 2019-03-21 16:52:47,131 ] [ DEBUG ] [ infer:165 ] Outputs: [ 2019-03-21 16:52:47,131 ] [ DEBUG ] [ infer:40 ] output[0]: shape = [], value = 30 [ 2019-03-21 16:52:47,131 ] [ DEBUG ] [ infer:150 ] -------------------- [ 2019-03-21 16:52:47,132 ] [ DEBUG ] [ infer:151 ] Partial infer for spatial_temporal_network/rnn_net/rnn/TensorArrayUnstack/range [ 2019-03-21 16:52:47,132 ] [ DEBUG ] [ infer:152 ] Op: Range [ 2019-03-21 16:52:47,133 ] [ DEBUG ] [ infer:163 ] Inputs: [ 2019-03-21 16:52:47,133 ] [ DEBUG ] [ infer:40 ] input[1]: shape = [], value = 30 [ 2019-03-21 16:52:47,133 ] [ DEBUG ] [ infer:40 ] input[0]: shape = [], value = 0 [ 2019-03-21 16:52:47,133 ] [ DEBUG ] [ infer:40 ] input[2]: shape = [], value = 1 [ 2019-03-21 16:52:47,133 ] [ DEBUG ] [ infer:165 ] Outputs: [ 2019-03-21 16:52:47,134 ] [ DEBUG ] [ infer:40 ] output[0]: shape = [30], value = [ 0 1 2 3 4 5 6 7 8 9 10 11 12 13 14 15 16 17 18 19 20 21 22 23 24 25 26 27 28 29] [ 2019-03-21 16:52:47,134 ] [ DEBUG ] [ infer:150 ] -------------------- [ 2019-03-21 16:52:47,134 ] [ DEBUG ] [ infer:151 ] Partial infer for spatial_temporal_network/rnn_net/rnn/time [ 2019-03-21 16:52:47,135 ] [ DEBUG ] [ infer:152 ] Op: Const [ 2019-03-21 16:52:47,135 ] [ DEBUG ] [ infer:163 ] Inputs: [ 2019-03-21 16:52:47,135 ] [ DEBUG ] [ infer:165 ] Outputs: [ 2019-03-21 16:52:47,135 ] [ DEBUG ] [ infer:40 ] output[0]: shape = [], value = 0 [ 2019-03-21 16:52:47,136 ] [ DEBUG ] [ infer:150 ] -------------------- [ 2019-03-21 16:52:47,136 ] [ DEBUG ] [ infer:151 ] Partial infer for spatial_temporal_network/rnn_net/rnn/while/Enter_1 [ 2019-03-21 16:52:47,136 ] [ DEBUG ] [ infer:152 ] Op: Enter [ 2019-03-21 16:52:47,136 ] [ DEBUG ] [ infer:163 ] Inputs: [ 2019-03-21 16:52:47,136 ] [ DEBUG ] [ infer:40 ] input[0]: shape = [], value = 0 [ 2019-03-21 16:52:47,137 ] [ DEBUG ] [ infer:165 ] Outputs: [ 2019-03-21 16:52:47,137 ] [ DEBUG ] [ infer:40 ] output[0]: shape = [], value = 0 [ 2019-03-21 16:52:47,137 ] [ DEBUG ] [ infer:150 ] -------------------- [ 2019-03-21 16:52:47,137 ] [ DEBUG ] [ infer:151 ] Partial infer for spatial_temporal_network/rnn_net/rnn/while/Merge_1 [ 2019-03-21 16:52:47,138 ] [ DEBUG ] [ infer:152 ] Op: Merge [ 2019-03-21 16:52:47,138 ] [ DEBUG ] [ infer:163 ] Inputs: [ 2019-03-21 16:52:47,139 ] [ DEBUG ] [ infer:40 ] input[0]: shape = [], value = 0 [ 2019-03-21 16:52:47,139 ] [ DEBUG ] [ infer:40 ] input[1]: shape = , value = [ 2019-03-21 16:52:47,139 ] [ DEBUG ] [ infer:165 ] Outputs: [ 2019-03-21 16:52:47,139 ] [ DEBUG ] [ infer:40 ] output[0]: shape = [], value = [ 2019-03-21 16:52:47,140 ] [ DEBUG ] [ infer:150 ] -------------------- [ 2019-03-21 16:52:47,140 ] [ DEBUG ] [ infer:151 ] Partial infer for spatial_temporal_network/rnn_net/rnn/strided_slice/stack_2 [ 2019-03-21 16:52:47,140 ] [ DEBUG ] [ infer:152 ] Op: Const [ 2019-03-21 16:52:47,140 ] [ DEBUG ] [ infer:163 ] Inputs: [ 2019-03-21 16:52:47,140 ] [ DEBUG ] [ infer:165 ] Outputs: [ 2019-03-21 16:52:47,141 ] [ DEBUG ] [ infer:40 ] output[0]: shape = [1], value = [1] [ 2019-03-21 16:52:47,141 ] [ DEBUG ] [ infer:150 ] -------------------- [ 2019-03-21 16:52:47,141 ] [ DEBUG ] [ infer:151 ] Partial infer for spatial_temporal_network/rnn_net/rnn/strided_slice/stack_1 [ 2019-03-21 16:52:47,141 ] [ DEBUG ] [ infer:152 ] Op: Const [ 2019-03-21 16:52:47,142 ] [ DEBUG ] [ infer:163 ] Inputs: [ 2019-03-21 16:52:47,142 ] [ DEBUG ] [ infer:165 ] Outputs: [ 2019-03-21 16:52:47,142 ] [ DEBUG ] [ infer:40 ] output[0]: shape = [1], value = [1] [ 2019-03-21 16:52:47,143 ] [ DEBUG ] [ infer:150 ] -------------------- [ 2019-03-21 16:52:47,143 ] [ DEBUG ] [ infer:151 ] Partial infer for spatial_temporal_network/rnn_net/rnn/strided_slice/stack [ 2019-03-21 16:52:47,143 ] [ DEBUG ] [ infer:152 ] Op: Const [ 2019-03-21 16:52:47,143 ] [ DEBUG ] [ infer:163 ] Inputs: [ 2019-03-21 16:52:47,143 ] [ DEBUG ] [ infer:165 ] Outputs: [ 2019-03-21 16:52:47,144 ] [ DEBUG ] [ infer:40 ] output[0]: shape = [1], value = [0] [ 2019-03-21 16:52:47,144 ] [ DEBUG ] [ infer:150 ] -------------------- [ 2019-03-21 16:52:47,145 ] [ DEBUG ] [ infer:151 ] Partial infer for spatial_temporal_network/rnn_net/rnn/Shape [ 2019-03-21 16:52:47,145 ] [ DEBUG ] [ infer:152 ] Op: Const [ 2019-03-21 16:52:47,145 ] [ DEBUG ] [ infer:163 ] Inputs: [ 2019-03-21 16:52:47,146 ] [ DEBUG ] [ infer:165 ] Outputs: [ 2019-03-21 16:52:47,147 ] [ DEBUG ] [ infer:40 ] output[0]: shape = [3], value = [ 30 1 512] [ 2019-03-21 16:52:47,147 ] [ DEBUG ] [ infer:150 ] -------------------- [ 2019-03-21 16:52:47,148 ] [ DEBUG ] [ infer:151 ] Partial infer for spatial_temporal_network/rnn_net/rnn/strided_slice [ 2019-03-21 16:52:47,148 ] [ DEBUG ] [ infer:152 ] Op: StridedSlice [ 2019-03-21 16:52:47,149 ] [ DEBUG ] [ infer:163 ] Inputs: [ 2019-03-21 16:52:47,150 ] [ DEBUG ] [ infer:40 ] input[0]: shape = [3], value = [ 30 1 512] [ 2019-03-21 16:52:47,150 ] [ DEBUG ] [ infer:40 ] input[1]: shape = [1], value = [0] [ 2019-03-21 16:52:47,150 ] [ DEBUG ] [ infer:40 ] input[2]: shape = [1], value = [1] [ 2019-03-21 16:52:47,151 ] [ DEBUG ] [ infer:40 ] input[3]: shape = [1], value = [1] [ 2019-03-21 16:52:47,151 ] [ DEBUG ] [ infer:165 ] Outputs: [ 2019-03-21 16:52:47,151 ] [ DEBUG ] [ infer:40 ] output[0]: shape = [], value = 30 [ 2019-03-21 16:52:47,152 ] [ DEBUG ] [ infer:150 ] -------------------- [ 2019-03-21 16:52:47,152 ] [ DEBUG ] [ infer:151 ] Partial infer for spatial_temporal_network/rnn_net/rnn/while/Less/Enter [ 2019-03-21 16:52:47,152 ] [ DEBUG ] [ infer:152 ] Op: Enter [ 2019-03-21 16:52:47,153 ] [ DEBUG ] [ infer:163 ] Inputs: [ 2019-03-21 16:52:47,153 ] [ DEBUG ] [ infer:40 ] input[0]: shape = [], value = 30 [ 2019-03-21 16:52:47,153 ] [ DEBUG ] [ infer:165 ] Outputs: [ 2019-03-21 16:52:47,153 ] [ DEBUG ] [ infer:40 ] output[0]: shape = [], value = 30 [ 2019-03-21 16:52:47,154 ] [ DEBUG ] [ infer:150 ] -------------------- [ 2019-03-21 16:52:47,154 ] [ DEBUG ] [ infer:151 ] Partial infer for spatial_temporal_network/rnn_net/rnn/while/Less [ 2019-03-21 16:52:47,154 ] [ DEBUG ] [ infer:152 ] Op: Less [ INFO ] Called "tf_native_tf_node_infer" for node "spatial_temporal_network/rnn_net/rnn/while/Less" [ 2019-03-21 16:52:47,160 ] [ DEBUG ] [ tf:222 ] Added placeholder with name 'spatial_temporal_network/rnn_net/rnn/while/Merge_port_0_ie_placeholder' [ 2019-03-21 16:52:47,162 ] [ DEBUG ] [ tf:222 ] Added placeholder with name 'spatial_temporal_network/rnn_net/rnn/while/Less/Enter_port_0_ie_placeholder' [ 2019-03-21 16:52:47,162 ] [ DEBUG ] [ tf:235 ] update_input_in_pbs: replace input 'spatial_temporal_network/rnn_net/rnn/while/Merge' with input 'spatial_temporal_network/rnn_net/rnn/while/Merge_port_0_ie_placeholder' [ 2019-03-21 16:52:47,162 ] [ DEBUG ] [ tf:243 ] Replacing input '0' of the node 'spatial_temporal_network/rnn_net/rnn/while/Less' with placeholder 'spatial_temporal_network/rnn_net/rnn/while/Merge_port_0_ie_placeholder' [ 2019-03-21 16:52:47,162 ] [ DEBUG ] [ tf:235 ] update_input_in_pbs: replace input 'spatial_temporal_network/rnn_net/rnn/while/Less/Enter' with input 'spatial_temporal_network/rnn_net/rnn/while/Less/Enter_port_0_ie_placeholder' [ 2019-03-21 16:52:47,163 ] [ DEBUG ] [ tf:243 ] Replacing input '1' of the node 'spatial_temporal_network/rnn_net/rnn/while/Less' with placeholder 'spatial_temporal_network/rnn_net/rnn/while/Less/Enter_port_0_ie_placeholder' [ 2019-03-21 16:52:47,196 ] [ DEBUG ] [ tf:142 ] Inferred shape of the output tensor with index '0' of the node 'spatial_temporal_network/rnn_net/rnn/while/Less': '[]' [ 2019-03-21 16:52:47,197 ] [ DEBUG ] [ infer:163 ] Inputs: [ 2019-03-21 16:52:47,197 ] [ DEBUG ] [ infer:40 ] input[0]: shape = [], value = [ 2019-03-21 16:52:47,198 ] [ DEBUG ] [ infer:40 ] input[1]: shape = [], value = 30 [ 2019-03-21 16:52:47,198 ] [ DEBUG ] [ infer:165 ] Outputs: [ 2019-03-21 16:52:47,199 ] [ DEBUG ] [ infer:40 ] output[0]: shape = [], value = [ 2019-03-21 16:52:47,199 ] [ DEBUG ] [ infer:150 ] -------------------- [ 2019-03-21 16:52:47,200 ] [ DEBUG ] [ infer:151 ] Partial infer for spatial_temporal_network/rnn_net/rnn/Maximum [ 2019-03-21 16:52:47,200 ] [ DEBUG ] [ infer:152 ] Op: Maximum [ 2019-03-21 16:52:47,200 ] [ DEBUG ] [ infer:163 ] Inputs: [ 2019-03-21 16:52:47,201 ] [ DEBUG ] [ infer:40 ] input[1]: shape = [], value = 30 [ 2019-03-21 16:52:47,201 ] [ DEBUG ] [ infer:40 ] input[0]: shape = [], value = 1 [ 2019-03-21 16:52:47,201 ] [ DEBUG ] [ infer:165 ] Outputs: [ 2019-03-21 16:52:47,202 ] [ DEBUG ] [ infer:40 ] output[0]: shape = [], value = 30 [ 2019-03-21 16:52:47,202 ] [ DEBUG ] [ infer:150 ] -------------------- [ 2019-03-21 16:52:47,203 ] [ DEBUG ] [ infer:151 ] Partial infer for spatial_temporal_network/rnn_net/rnn/Minimum [ 2019-03-21 16:52:47,203 ] [ DEBUG ] [ infer:152 ] Op: Minimum [ 2019-03-21 16:52:47,204 ] [ DEBUG ] [ infer:163 ] Inputs: [ 2019-03-21 16:52:47,206 ] [ DEBUG ] [ infer:40 ] input[0]: shape = [], value = 30 [ 2019-03-21 16:52:47,207 ] [ DEBUG ] [ infer:40 ] input[1]: shape = [], value = 30 [ 2019-03-21 16:52:47,207 ] [ DEBUG ] [ infer:165 ] Outputs: [ 2019-03-21 16:52:47,207 ] [ DEBUG ] [ infer:40 ] output[0]: shape = [], value = 30 [ 2019-03-21 16:52:47,208 ] [ DEBUG ] [ infer:150 ] -------------------- [ 2019-03-21 16:52:47,208 ] [ DEBUG ] [ infer:151 ] Partial infer for spatial_temporal_network/rnn_net/rnn/while/Less_1/Enter [ 2019-03-21 16:52:47,208 ] [ DEBUG ] [ infer:152 ] Op: Enter [ 2019-03-21 16:52:47,208 ] [ DEBUG ] [ infer:163 ] Inputs: [ 2019-03-21 16:52:47,210 ] [ DEBUG ] [ infer:40 ] input[0]: shape = [], value = 30 [ 2019-03-21 16:52:47,210 ] [ DEBUG ] [ infer:165 ] Outputs: [ 2019-03-21 16:52:47,210 ] [ DEBUG ] [ infer:40 ] output[0]: shape = [], value = 30 [ 2019-03-21 16:52:47,211 ] [ DEBUG ] [ infer:150 ] -------------------- [ 2019-03-21 16:52:47,211 ] [ DEBUG ] [ infer:151 ] Partial infer for spatial_temporal_network/rnn_net/rnn/while/Less_1 [ 2019-03-21 16:52:47,211 ] [ DEBUG ] [ infer:152 ] Op: Less [ INFO ] Called "tf_native_tf_node_infer" for node "spatial_temporal_network/rnn_net/rnn/while/Less_1" [ 2019-03-21 16:52:47,220 ] [ DEBUG ] [ tf:222 ] Added placeholder with name 'spatial_temporal_network/rnn_net/rnn/while/Merge_1_port_0_ie_placeholder' [ 2019-03-21 16:52:47,222 ] [ DEBUG ] [ tf:222 ] Added placeholder with name 'spatial_temporal_network/rnn_net/rnn/while/Less_1/Enter_port_0_ie_placeholder' [ 2019-03-21 16:52:47,222 ] [ DEBUG ] [ tf:235 ] update_input_in_pbs: replace input 'spatial_temporal_network/rnn_net/rnn/while/Merge_1' with input 'spatial_temporal_network/rnn_net/rnn/while/Merge_1_port_0_ie_placeholder' [ 2019-03-21 16:52:47,223 ] [ DEBUG ] [ tf:243 ] Replacing input '0' of the node 'spatial_temporal_network/rnn_net/rnn/while/Less_1' with placeholder 'spatial_temporal_network/rnn_net/rnn/while/Merge_1_port_0_ie_placeholder' [ 2019-03-21 16:52:47,223 ] [ DEBUG ] [ tf:235 ] update_input_in_pbs: replace input 'spatial_temporal_network/rnn_net/rnn/while/Less_1/Enter' with input 'spatial_temporal_network/rnn_net/rnn/while/Less_1/Enter_port_0_ie_placeholder' [ 2019-03-21 16:52:47,223 ] [ DEBUG ] [ tf:243 ] Replacing input '1' of the node 'spatial_temporal_network/rnn_net/rnn/while/Less_1' with placeholder 'spatial_temporal_network/rnn_net/rnn/while/Less_1/Enter_port_0_ie_placeholder' [ 2019-03-21 16:52:47,237 ] [ DEBUG ] [ tf:142 ] Inferred shape of the output tensor with index '0' of the node 'spatial_temporal_network/rnn_net/rnn/while/Less_1': '[]' [ 2019-03-21 16:52:47,237 ] [ DEBUG ] [ infer:163 ] Inputs: [ 2019-03-21 16:52:47,238 ] [ DEBUG ] [ infer:40 ] input[0]: shape = [], value = [ 2019-03-21 16:52:47,239 ] [ DEBUG ] [ infer:40 ] input[1]: shape = [], value = 30 [ 2019-03-21 16:52:47,239 ] [ DEBUG ] [ infer:165 ] Outputs: [ 2019-03-21 16:52:47,239 ] [ DEBUG ] [ infer:40 ] output[0]: shape = [], value = [ 2019-03-21 16:52:47,239 ] [ DEBUG ] [ infer:150 ] -------------------- [ 2019-03-21 16:52:47,239 ] [ DEBUG ] [ infer:151 ] Partial infer for spatial_temporal_network/rnn_net/rnn/while/LogicalAnd [ 2019-03-21 16:52:47,240 ] [ DEBUG ] [ infer:152 ] Op: LogicalAnd [ INFO ] Called "tf_native_tf_node_infer" for node "spatial_temporal_network/rnn_net/rnn/while/LogicalAnd" [ 2019-03-21 16:52:47,247 ] [ DEBUG ] [ tf:222 ] Added placeholder with name 'spatial_temporal_network/rnn_net/rnn/while/Less_port_0_ie_placeholder' [ 2019-03-21 16:52:47,254 ] [ DEBUG ] [ tf:222 ] Added placeholder with name 'spatial_temporal_network/rnn_net/rnn/while/Less_1_port_0_ie_placeholder' [ 2019-03-21 16:52:47,254 ] [ DEBUG ] [ tf:235 ] update_input_in_pbs: replace input 'spatial_temporal_network/rnn_net/rnn/while/Less' with input 'spatial_temporal_network/rnn_net/rnn/while/Less_port_0_ie_placeholder' [ 2019-03-21 16:52:47,254 ] [ DEBUG ] [ tf:243 ] Replacing input '0' of the node 'spatial_temporal_network/rnn_net/rnn/while/LogicalAnd' with placeholder 'spatial_temporal_network/rnn_net/rnn/while/Less_port_0_ie_placeholder' [ 2019-03-21 16:52:47,255 ] [ DEBUG ] [ tf:235 ] update_input_in_pbs: replace input 'spatial_temporal_network/rnn_net/rnn/while/Less_1' with input 'spatial_temporal_network/rnn_net/rnn/while/Less_1_port_0_ie_placeholder' [ 2019-03-21 16:52:47,255 ] [ DEBUG ] [ tf:243 ] Replacing input '1' of the node 'spatial_temporal_network/rnn_net/rnn/while/LogicalAnd' with placeholder 'spatial_temporal_network/rnn_net/rnn/while/Less_1_port_0_ie_placeholder' [ 2019-03-21 16:52:47,274 ] [ DEBUG ] [ tf:142 ] Inferred shape of the output tensor with index '0' of the node 'spatial_temporal_network/rnn_net/rnn/while/LogicalAnd': '[]' [ 2019-03-21 16:52:47,275 ] [ DEBUG ] [ infer:163 ] Inputs: [ 2019-03-21 16:52:47,275 ] [ DEBUG ] [ infer:40 ] input[0]: shape = [], value = [ 2019-03-21 16:52:47,275 ] [ DEBUG ] [ infer:40 ] input[1]: shape = [], value = [ 2019-03-21 16:52:47,275 ] [ DEBUG ] [ infer:165 ] Outputs: [ 2019-03-21 16:52:47,276 ] [ DEBUG ] [ infer:40 ] output[0]: shape = [], value = [ 2019-03-21 16:52:47,276 ] [ DEBUG ] [ infer:150 ] -------------------- [ 2019-03-21 16:52:47,276 ] [ DEBUG ] [ infer:151 ] Partial infer for spatial_temporal_network/rnn_net/rnn/while/LoopCond [ 2019-03-21 16:52:47,276 ] [ DEBUG ] [ infer:152 ] Op: LoopCond [ INFO ] Called "tf_native_tf_node_infer" for node "spatial_temporal_network/rnn_net/rnn/while/LoopCond" [ 2019-03-21 16:52:47,283 ] [ DEBUG ] [ tf:222 ] Added placeholder with name 'spatial_temporal_network/rnn_net/rnn/while/LogicalAnd_port_0_ie_placeholder' [ 2019-03-21 16:52:47,283 ] [ DEBUG ] [ tf:235 ] update_input_in_pbs: replace input 'spatial_temporal_network/rnn_net/rnn/while/LogicalAnd' with input 'spatial_temporal_network/rnn_net/rnn/while/LogicalAnd_port_0_ie_placeholder' [ 2019-03-21 16:52:47,283 ] [ DEBUG ] [ tf:243 ] Replacing input '0' of the node 'spatial_temporal_network/rnn_net/rnn/while/LoopCond' with placeholder 'spatial_temporal_network/rnn_net/rnn/while/LogicalAnd_port_0_ie_placeholder' [ 2019-03-21 16:52:47,292 ] [ DEBUG ] [ tf:142 ] Inferred shape of the output tensor with index '0' of the node 'spatial_temporal_network/rnn_net/rnn/while/LoopCond': '[]' [ 2019-03-21 16:52:47,294 ] [ DEBUG ] [ infer:163 ] Inputs: [ 2019-03-21 16:52:47,295 ] [ DEBUG ] [ infer:40 ] input[0]: shape = [], value = [ 2019-03-21 16:52:47,295 ] [ DEBUG ] [ infer:165 ] Outputs: [ 2019-03-21 16:52:47,295 ] [ DEBUG ] [ infer:40 ] output[0]: shape = [], value = [ 2019-03-21 16:52:47,296 ] [ DEBUG ] [ infer:150 ] -------------------- [ 2019-03-21 16:52:47,296 ] [ DEBUG ] [ infer:151 ] Partial infer for spatial_temporal_network/rnn_net/rnn/while/Switch_1 [ 2019-03-21 16:52:47,296 ] [ DEBUG ] [ infer:152 ] Op: Switch [ 2019-03-21 16:52:47,296 ] [ DEBUG ] [ infer:163 ] Inputs: [ 2019-03-21 16:52:47,297 ] [ DEBUG ] [ infer:40 ] input[0]: shape = [], value = [ 2019-03-21 16:52:47,297 ] [ DEBUG ] [ infer:40 ] input[1]: shape = [], value = [ 2019-03-21 16:52:47,297 ] [ DEBUG ] [ infer:165 ] Outputs: [ 2019-03-21 16:52:47,297 ] [ DEBUG ] [ infer:40 ] output[1]: shape = [], value = [ 2019-03-21 16:52:47,298 ] [ DEBUG ] [ infer:150 ] -------------------- [ 2019-03-21 16:52:47,298 ] [ DEBUG ] [ infer:151 ] Partial infer for spatial_temporal_network/rnn_net/rnn/while/Identity_1 [ 2019-03-21 16:52:47,298 ] [ DEBUG ] [ infer:152 ] Op: Identity [ 2019-03-21 16:52:47,299 ] [ DEBUG ] [ infer:163 ] Inputs: [ 2019-03-21 16:52:47,299 ] [ DEBUG ] [ infer:40 ] input[0]: shape = [], value = [ 2019-03-21 16:52:47,299 ] [ DEBUG ] [ infer:165 ] Outputs: [ 2019-03-21 16:52:47,299 ] [ DEBUG ] [ infer:40 ] output[0]: shape = [], value = [ 2019-03-21 16:52:47,300 ] [ DEBUG ] [ infer:150 ] -------------------- [ 2019-03-21 16:52:47,300 ] [ DEBUG ] [ infer:151 ] Partial infer for spatial_temporal_network/rnn_net/rnn/while/Switch [ 2019-03-21 16:52:47,300 ] [ DEBUG ] [ infer:152 ] Op: Switch [ 2019-03-21 16:52:47,301 ] [ DEBUG ] [ infer:163 ] Inputs: [ 2019-03-21 16:52:47,301 ] [ DEBUG ] [ infer:40 ] input[0]: shape = [], value = [ 2019-03-21 16:52:47,301 ] [ DEBUG ] [ infer:40 ] input[1]: shape = [], value = [ 2019-03-21 16:52:47,301 ] [ DEBUG ] [ infer:165 ] Outputs: [ 2019-03-21 16:52:47,302 ] [ DEBUG ] [ infer:40 ] output[1]: shape = [], value = [ 2019-03-21 16:52:47,303 ] [ DEBUG ] [ infer:150 ] -------------------- [ 2019-03-21 16:52:47,303 ] [ DEBUG ] [ infer:151 ] Partial infer for spatial_temporal_network/rnn_net/rnn/while/Identity [ 2019-03-21 16:52:47,303 ] [ DEBUG ] [ infer:152 ] Op: Identity [ 2019-03-21 16:52:47,304 ] [ DEBUG ] [ infer:163 ] Inputs: [ 2019-03-21 16:52:47,304 ] [ DEBUG ] [ infer:40 ] input[0]: shape = [], value = [ 2019-03-21 16:52:47,304 ] [ DEBUG ] [ infer:165 ] Outputs: [ 2019-03-21 16:52:47,304 ] [ DEBUG ] [ infer:40 ] output[0]: shape = [], value = [ 2019-03-21 16:52:47,305 ] [ DEBUG ] [ infer:150 ] -------------------- [ 2019-03-21 16:52:47,305 ] [ DEBUG ] [ infer:151 ] Partial infer for spatial_temporal_network/rnn_net/rnn/while/add_1/y [ 2019-03-21 16:52:47,305 ] [ DEBUG ] [ infer:152 ] Op: Const [ 2019-03-21 16:52:47,305 ] [ DEBUG ] [ infer:163 ] Inputs: [ 2019-03-21 16:52:47,306 ] [ DEBUG ] [ infer:165 ] Outputs: [ 2019-03-21 16:52:47,306 ] [ DEBUG ] [ infer:40 ] output[0]: shape = [], value = 1 [ 2019-03-21 16:52:47,306 ] [ DEBUG ] [ infer:150 ] -------------------- [ 2019-03-21 16:52:47,307 ] [ DEBUG ] [ infer:151 ] Partial infer for spatial_temporal_network/rnn_net/rnn/while/add_1 [ 2019-03-21 16:52:47,307 ] [ DEBUG ] [ infer:152 ] Op: Add [ 2019-03-21 16:52:47,307 ] [ DEBUG ] [ infer:163 ] Inputs: [ 2019-03-21 16:52:47,307 ] [ DEBUG ] [ infer:40 ] input[0]: shape = [], value = [ 2019-03-21 16:52:47,308 ] [ DEBUG ] [ infer:40 ] input[1]: shape = [], value = 1 [ 2019-03-21 16:52:47,308 ] [ DEBUG ] [ infer:165 ] Outputs: [ 2019-03-21 16:52:47,308 ] [ DEBUG ] [ infer:40 ] output[0]: shape = [], value = [ 2019-03-21 16:52:47,308 ] [ DEBUG ] [ infer:150 ] -------------------- [ 2019-03-21 16:52:47,309 ] [ DEBUG ] [ infer:151 ] Partial infer for spatial_temporal_network/rnn_net/rnn/while/NextIteration_1 [ 2019-03-21 16:52:47,309 ] [ DEBUG ] [ infer:152 ] Op: NextIteration [ 2019-03-21 16:52:47,309 ] [ DEBUG ] [ infer:163 ] Inputs: [ 2019-03-21 16:52:47,309 ] [ DEBUG ] [ infer:40 ] input[0]: shape = [], value = [ 2019-03-21 16:52:47,310 ] [ DEBUG ] [ infer:165 ] Outputs: [ 2019-03-21 16:52:47,310 ] [ DEBUG ] [ infer:40 ] output[0]: shape = [], value = [ 2019-03-21 16:52:47,310 ] [ DEBUG ] [ infer:150 ] -------------------- [ 2019-03-21 16:52:47,310 ] [ DEBUG ] [ infer:151 ] Partial infer for spatial_temporal_network/rnn_net/rnn/while/rnn/multi_rnn_cell/cell_0/lstm_cell/add_4/y [ 2019-03-21 16:52:47,311 ] [ DEBUG ] [ infer:152 ] Op: Const [ 2019-03-21 16:52:47,311 ] [ DEBUG ] [ infer:163 ] Inputs: [ 2019-03-21 16:52:47,311 ] [ DEBUG ] [ infer:165 ] Outputs: [ 2019-03-21 16:52:47,311 ] [ DEBUG ] [ infer:40 ] output[0]: shape = [], value = 1.0 [ 2019-03-21 16:52:47,312 ] [ DEBUG ] [ infer:150 ] -------------------- [ 2019-03-21 16:52:47,312 ] [ DEBUG ] [ infer:151 ] Partial infer for spatial_temporal_network/rnn_net/rnn/while/rnn/multi_rnn_cell/cell_0/lstm_cell/split_2/split_dim [ 2019-03-21 16:52:47,312 ] [ DEBUG ] [ infer:152 ] Op: Const [ 2019-03-21 16:52:47,312 ] [ DEBUG ] [ infer:163 ] Inputs: [ 2019-03-21 16:52:47,313 ] [ DEBUG ] [ infer:165 ] Outputs: [ 2019-03-21 16:52:47,313 ] [ DEBUG ] [ infer:40 ] output[0]: shape = [], value = 1 [ 2019-03-21 16:52:47,313 ] [ DEBUG ] [ infer:150 ] -------------------- [ 2019-03-21 16:52:47,313 ] [ DEBUG ] [ infer:151 ] Partial infer for spatial_temporal_network/rnn_net/rnn/while/rnn/multi_rnn_cell/cell_0/lstm_cell/concat_2/axis [ 2019-03-21 16:52:47,314 ] [ DEBUG ] [ infer:152 ] Op: Const [ 2019-03-21 16:52:47,314 ] [ DEBUG ] [ infer:163 ] Inputs: [ 2019-03-21 16:52:47,314 ] [ DEBUG ] [ infer:165 ] Outputs: [ 2019-03-21 16:52:47,315 ] [ DEBUG ] [ infer:40 ] output[0]: shape = [], value = 1 [ 2019-03-21 16:52:47,320 ] [ DEBUG ] [ infer:150 ] -------------------- [ 2019-03-21 16:52:47,320 ] [ DEBUG ] [ infer:151 ] Partial infer for spatial_temporal_network/rnn_net/rnn/while/rnn/multi_rnn_cell/cell_0/lstm_cell/add_2/y [ 2019-03-21 16:52:47,320 ] [ DEBUG ] [ infer:152 ] Op: Const [ 2019-03-21 16:52:47,320 ] [ DEBUG ] [ infer:163 ] Inputs: [ 2019-03-21 16:52:47,321 ] [ DEBUG ] [ infer:165 ] Outputs: [ 2019-03-21 16:52:47,321 ] [ DEBUG ] [ infer:40 ] output[0]: shape = [], value = 1.0 [ 2019-03-21 16:52:47,321 ] [ DEBUG ] [ infer:150 ] -------------------- [ 2019-03-21 16:52:47,322 ] [ DEBUG ] [ infer:151 ] Partial infer for spatial_temporal_network/rnn_net/rnn/while/rnn/multi_rnn_cell/cell_0/lstm_cell/split_1/split_dim [ 2019-03-21 16:52:47,322 ] [ DEBUG ] [ infer:152 ] Op: Const [ 2019-03-21 16:52:47,322 ] [ DEBUG ] [ infer:163 ] Inputs: [ 2019-03-21 16:52:47,322 ] [ DEBUG ] [ infer:165 ] Outputs: [ 2019-03-21 16:52:47,323 ] [ DEBUG ] [ infer:40 ] output[0]: shape = [], value = 1 [ 2019-03-21 16:52:47,323 ] [ DEBUG ] [ infer:150 ] -------------------- [ 2019-03-21 16:52:47,323 ] [ DEBUG ] [ infer:151 ] Partial infer for spatial_temporal_network/rnn_net/rnn/while/rnn/multi_rnn_cell/cell_0/lstm_cell/concat_1/axis [ 2019-03-21 16:52:47,323 ] [ DEBUG ] [ infer:152 ] Op: Const [ 2019-03-21 16:52:47,324 ] [ DEBUG ] [ infer:163 ] Inputs: [ 2019-03-21 16:52:47,324 ] [ DEBUG ] [ infer:165 ] Outputs: [ 2019-03-21 16:52:47,324 ] [ DEBUG ] [ infer:40 ] output[0]: shape = [], value = 1 [ 2019-03-21 16:52:47,325 ] [ DEBUG ] [ infer:150 ] -------------------- [ 2019-03-21 16:52:47,325 ] [ DEBUG ] [ infer:151 ] Partial infer for spatial_temporal_network/rnn_net/rnn/while/rnn/multi_rnn_cell/cell_0/lstm_cell/add/y [ 2019-03-21 16:52:47,325 ] [ DEBUG ] [ infer:152 ] Op: Const [ 2019-03-21 16:52:47,326 ] [ DEBUG ] [ infer:163 ] Inputs: [ 2019-03-21 16:52:47,328 ] [ DEBUG ] [ infer:165 ] Outputs: [ 2019-03-21 16:52:47,328 ] [ DEBUG ] [ infer:40 ] output[0]: shape = [], value = 1.0 [ 2019-03-21 16:52:47,330 ] [ DEBUG ] [ infer:150 ] -------------------- [ 2019-03-21 16:52:47,330 ] [ DEBUG ] [ infer:151 ] Partial infer for spatial_temporal_network/rnn_net/rnn/while/rnn/multi_rnn_cell/cell_0/lstm_cell/split/split_dim [ 2019-03-21 16:52:47,330 ] [ DEBUG ] [ infer:152 ] Op: Const [ 2019-03-21 16:52:47,331 ] [ DEBUG ] [ infer:163 ] Inputs: [ 2019-03-21 16:52:47,331 ] [ DEBUG ] [ infer:165 ] Outputs: [ 2019-03-21 16:52:47,331 ] [ DEBUG ] [ infer:40 ] output[0]: shape = [], value = 1 [ 2019-03-21 16:52:47,332 ] [ DEBUG ] [ infer:150 ] -------------------- [ 2019-03-21 16:52:47,332 ] [ DEBUG ] [ infer:151 ] Partial infer for spatial_temporal_network/rnn_net/rnn/while/rnn/multi_rnn_cell/cell_0/lstm_cell/concat/axis [ 2019-03-21 16:52:47,332 ] [ DEBUG ] [ infer:152 ] Op: Const [ 2019-03-21 16:52:47,332 ] [ DEBUG ] [ infer:163 ] Inputs: [ 2019-03-21 16:52:47,333 ] [ DEBUG ] [ infer:165 ] Outputs: [ 2019-03-21 16:52:47,333 ] [ DEBUG ] [ infer:40 ] output[0]: shape = [], value = 1 [ 2019-03-21 16:52:47,333 ] [ DEBUG ] [ infer:150 ] -------------------- [ 2019-03-21 16:52:47,333 ] [ DEBUG ] [ infer:151 ] Partial infer for spatial_temporal_network/rnn_net/rnn/while/add/y [ 2019-03-21 16:52:47,334 ] [ DEBUG ] [ infer:152 ] Op: Const [ 2019-03-21 16:52:47,334 ] [ DEBUG ] [ infer:163 ] Inputs: [ 2019-03-21 16:52:47,334 ] [ DEBUG ] [ infer:165 ] Outputs: [ 2019-03-21 16:52:47,335 ] [ DEBUG ] [ infer:40 ] output[0]: shape = [], value = 1 [ 2019-03-21 16:52:47,335 ] [ DEBUG ] [ infer:150 ] -------------------- [ 2019-03-21 16:52:47,335 ] [ DEBUG ] [ infer:151 ] Partial infer for spatial_temporal_network/rnn_net/rnn/while/add [ 2019-03-21 16:52:47,335 ] [ DEBUG ] [ infer:152 ] Op: Add [ 2019-03-21 16:52:47,336 ] [ DEBUG ] [ infer:163 ] Inputs: [ 2019-03-21 16:52:47,336 ] [ DEBUG ] [ infer:40 ] input[0]: shape = [], value = [ 2019-03-21 16:52:47,336 ] [ DEBUG ] [ infer:40 ] input[1]: shape = [], value = 1 [ 2019-03-21 16:52:47,337 ] [ DEBUG ] [ infer:165 ] Outputs: [ 2019-03-21 16:52:47,337 ] [ DEBUG ] [ infer:40 ] output[0]: shape = [], value = [ 2019-03-21 16:52:47,337 ] [ DEBUG ] [ infer:150 ] -------------------- [ 2019-03-21 16:52:47,337 ] [ DEBUG ] [ infer:151 ] Partial infer for spatial_temporal_network/rnn_net/rnn/while/NextIteration [ 2019-03-21 16:52:47,338 ] [ DEBUG ] [ infer:152 ] Op: NextIteration [ 2019-03-21 16:52:47,338 ] [ DEBUG ] [ infer:163 ] Inputs: [ 2019-03-21 16:52:47,338 ] [ DEBUG ] [ infer:40 ] input[0]: shape = [], value = [ 2019-03-21 16:52:47,338 ] [ DEBUG ] [ infer:165 ] Outputs: [ 2019-03-21 16:52:47,339 ] [ DEBUG ] [ infer:40 ] output[0]: shape = [], value = [ 2019-03-21 16:52:47,339 ] [ DEBUG ] [ infer:150 ] -------------------- [ 2019-03-21 16:52:47,339 ] [ DEBUG ] [ infer:151 ] Partial infer for spatial_temporal_network/rnn_net/rnn/TensorArray_1 [ 2019-03-21 16:52:47,339 ] [ DEBUG ] [ infer:152 ] Op: TensorArrayV3 [ 2019-03-21 16:52:47,340 ] [ DEBUG ] [ infer:163 ] Inputs: [ 2019-03-21 16:52:47,340 ] [ DEBUG ] [ infer:40 ] input[0]: shape = [], value = 30 [ 2019-03-21 16:52:47,340 ] [ DEBUG ] [ infer:165 ] Outputs: [ 2019-03-21 16:52:47,341 ] [ DEBUG ] [ infer:40 ] output[0]: shape = [], value = spatial_temporal_network/rnn_net/rnn/TensorArray_1/Output_0/Data_ [ 2019-03-21 16:52:47,341 ] [ DEBUG ] [ infer:40 ] output[1]: shape = [], value = [ 2019-03-21 16:52:47,341 ] [ DEBUG ] [ infer:150 ] -------------------- [ 2019-03-21 16:52:47,341 ] [ DEBUG ] [ infer:151 ] Partial infer for spatial_temporal_network/rnn_net/rnn/while/TensorArrayReadV3/Enter [ 2019-03-21 16:52:47,342 ] [ DEBUG ] [ infer:152 ] Op: Enter [ 2019-03-21 16:52:47,342 ] [ DEBUG ] [ infer:163 ] Inputs: [ 2019-03-21 16:52:47,342 ] [ DEBUG ] [ infer:40 ] input[0]: shape = [], value = spatial_temporal_network/rnn_net/rnn/TensorArray_1/Output_0/Data_ [ 2019-03-21 16:52:47,342 ] [ DEBUG ] [ infer:165 ] Outputs: [ 2019-03-21 16:52:47,343 ] [ DEBUG ] [ infer:40 ] output[0]: shape = [], value = spatial_temporal_network/rnn_net/rnn/TensorArray_1/Output_0/Data_ [ 2019-03-21 16:52:47,343 ] [ DEBUG ] [ infer:150 ] -------------------- [ 2019-03-21 16:52:47,343 ] [ DEBUG ] [ infer:151 ] Partial infer for spatial_temporal_network/rnn_net/rnn/TensorArray [ 2019-03-21 16:52:47,343 ] [ DEBUG ] [ infer:152 ] Op: TensorArrayV3 [ 2019-03-21 16:52:47,344 ] [ DEBUG ] [ infer:163 ] Inputs: [ 2019-03-21 16:52:47,344 ] [ DEBUG ] [ infer:40 ] input[0]: shape = [], value = 30 [ 2019-03-21 16:52:47,345 ] [ DEBUG ] [ infer:165 ] Outputs: [ 2019-03-21 16:52:47,345 ] [ DEBUG ] [ infer:40 ] output[1]: shape = [], value = [ 2019-03-21 16:52:47,345 ] [ DEBUG ] [ infer:40 ] output[0]: shape = [], value = spatial_temporal_network/rnn_net/rnn/TensorArray/Output_0/Data_ [ 2019-03-21 16:52:47,345 ] [ DEBUG ] [ infer:150 ] -------------------- [ 2019-03-21 16:52:47,346 ] [ DEBUG ] [ infer:151 ] Partial infer for spatial_temporal_network/rnn_net/rnn/while/TensorArrayWrite/TensorArrayWriteV3/Enter [ 2019-03-21 16:52:47,346 ] [ DEBUG ] [ infer:152 ] Op: Enter [ 2019-03-21 16:52:47,346 ] [ DEBUG ] [ infer:163 ] Inputs: [ 2019-03-21 16:52:47,347 ] [ DEBUG ] [ infer:40 ] input[0]: shape = [], value = spatial_temporal_network/rnn_net/rnn/TensorArray/Output_0/Data_ [ 2019-03-21 16:52:47,347 ] [ DEBUG ] [ infer:165 ] Outputs: [ 2019-03-21 16:52:47,347 ] [ DEBUG ] [ infer:40 ] output[0]: shape = [], value = spatial_temporal_network/rnn_net/rnn/TensorArray/Output_0/Data_ [ 2019-03-21 16:52:47,348 ] [ DEBUG ] [ infer:150 ] -------------------- [ 2019-03-21 16:52:47,348 ] [ DEBUG ] [ infer:151 ] Partial infer for spatial_temporal_network/rnn_net/rnn/while/Enter_2 [ 2019-03-21 16:52:47,348 ] [ DEBUG ] [ infer:152 ] Op: Enter [ 2019-03-21 16:52:47,348 ] [ DEBUG ] [ infer:163 ] Inputs: [ 2019-03-21 16:52:47,349 ] [ DEBUG ] [ infer:40 ] input[0]: shape = [], value = [ 2019-03-21 16:52:47,349 ] [ DEBUG ] [ infer:165 ] Outputs: [ 2019-03-21 16:52:47,349 ] [ DEBUG ] [ infer:40 ] output[0]: shape = [], value = [ 2019-03-21 16:52:47,349 ] [ DEBUG ] [ infer:150 ] -------------------- [ 2019-03-21 16:52:47,349 ] [ DEBUG ] [ infer:151 ] Partial infer for spatial_temporal_network/rnn_net/rnn/while/Merge_2 [ 2019-03-21 16:52:47,350 ] [ DEBUG ] [ infer:152 ] Op: Merge [ 2019-03-21 16:52:47,350 ] [ DEBUG ] [ infer:163 ] Inputs: [ 2019-03-21 16:52:47,350 ] [ DEBUG ] [ infer:40 ] input[0]: shape = [], value = [ 2019-03-21 16:52:47,351 ] [ DEBUG ] [ infer:40 ] input[1]: shape = , value = [ 2019-03-21 16:52:47,351 ] [ DEBUG ] [ infer:165 ] Outputs: [ 2019-03-21 16:52:47,351 ] [ DEBUG ] [ infer:40 ] output[0]: shape = [], value = [ 2019-03-21 16:52:47,351 ] [ DEBUG ] [ infer:150 ] -------------------- [ 2019-03-21 16:52:47,352 ] [ DEBUG ] [ infer:151 ] Partial infer for spatial_temporal_network/rnn_net/rnn/while/Switch_2 [ 2019-03-21 16:52:47,352 ] [ DEBUG ] [ infer:152 ] Op: Switch [ 2019-03-21 16:52:47,352 ] [ DEBUG ] [ infer:163 ] Inputs: [ 2019-03-21 16:52:47,352 ] [ DEBUG ] [ infer:40 ] input[0]: shape = [], value = [ 2019-03-21 16:52:47,353 ] [ DEBUG ] [ infer:40 ] input[1]: shape = [], value = [ 2019-03-21 16:52:47,353 ] [ DEBUG ] [ infer:165 ] Outputs: [ 2019-03-21 16:52:47,353 ] [ DEBUG ] [ infer:40 ] output[1]: shape = [], value = [ 2019-03-21 16:52:47,354 ] [ DEBUG ] [ infer:40 ] output[0]: shape = [], value = [ 2019-03-21 16:52:47,355 ] [ DEBUG ] [ infer:150 ] -------------------- [ 2019-03-21 16:52:47,355 ] [ DEBUG ] [ infer:151 ] Partial infer for spatial_temporal_network/rnn_net/rnn/while/Identity_2 [ 2019-03-21 16:52:47,356 ] [ DEBUG ] [ infer:152 ] Op: Identity [ 2019-03-21 16:52:47,356 ] [ DEBUG ] [ infer:163 ] Inputs: [ 2019-03-21 16:52:47,356 ] [ DEBUG ] [ infer:40 ] input[0]: shape = [], value = [ 2019-03-21 16:52:47,357 ] [ DEBUG ] [ infer:165 ] Outputs: [ 2019-03-21 16:52:47,357 ] [ DEBUG ] [ infer:40 ] output[0]: shape = [], value = [ 2019-03-21 16:52:47,357 ] [ DEBUG ] [ infer:150 ] -------------------- [ 2019-03-21 16:52:47,357 ] [ DEBUG ] [ infer:151 ] Partial infer for spatial_temporal_network/rnn_net/rnn/MultiRNNCellZeroState/LSTMCellZeroState_2/zeros_1/Const [ 2019-03-21 16:52:47,358 ] [ DEBUG ] [ infer:152 ] Op: Const [ 2019-03-21 16:52:47,358 ] [ DEBUG ] [ infer:163 ] Inputs: [ 2019-03-21 16:52:47,358 ] [ DEBUG ] [ infer:165 ] Outputs: [ 2019-03-21 16:52:47,359 ] [ DEBUG ] [ infer:40 ] output[0]: shape = [], value = 0.0 [ 2019-03-21 16:52:47,359 ] [ DEBUG ] [ infer:150 ] -------------------- [ 2019-03-21 16:52:47,359 ] [ DEBUG ] [ infer:151 ] Partial infer for spatial_temporal_network/rnn_net/rnn/MultiRNNCellZeroState/LSTMCellZeroState_2/concat_1/axis [ 2019-03-21 16:52:47,359 ] [ DEBUG ] [ infer:152 ] Op: Const [ 2019-03-21 16:52:47,360 ] [ DEBUG ] [ infer:163 ] Inputs: [ 2019-03-21 16:52:47,360 ] [ DEBUG ] [ infer:165 ] Outputs: [ 2019-03-21 16:52:47,360 ] [ DEBUG ] [ infer:40 ] output[0]: shape = [], value = 0 [ 2019-03-21 16:52:47,360 ] [ DEBUG ] [ infer:150 ] -------------------- [ 2019-03-21 16:52:47,361 ] [ DEBUG ] [ infer:151 ] Partial infer for spatial_temporal_network/rnn_net/rnn/MultiRNNCellZeroState/LSTMCellZeroState_2/Const_5 [ 2019-03-21 16:52:47,361 ] [ DEBUG ] [ infer:152 ] Op: Const [ 2019-03-21 16:52:47,361 ] [ DEBUG ] [ infer:163 ] Inputs: [ 2019-03-21 16:52:47,361 ] [ DEBUG ] [ infer:165 ] Outputs: [ 2019-03-21 16:52:47,362 ] [ DEBUG ] [ infer:40 ] output[0]: shape = [1], value = [512] [ 2019-03-21 16:52:47,362 ] [ DEBUG ] [ infer:150 ] -------------------- [ 2019-03-21 16:52:47,362 ] [ DEBUG ] [ infer:151 ] Partial infer for spatial_temporal_network/rnn_net/rnn/MultiRNNCellZeroState/LSTMCellZeroState_2/Const_4 [ 2019-03-21 16:52:47,363 ] [ DEBUG ] [ infer:152 ] Op: Const [ 2019-03-21 16:52:47,363 ] [ DEBUG ] [ infer:163 ] Inputs: [ 2019-03-21 16:52:47,363 ] [ DEBUG ] [ infer:165 ] Outputs: [ 2019-03-21 16:52:47,364 ] [ DEBUG ] [ infer:40 ] output[0]: shape = [1], value = [1] [ 2019-03-21 16:52:47,364 ] [ DEBUG ] [ infer:150 ] -------------------- [ 2019-03-21 16:52:47,364 ] [ DEBUG ] [ infer:151 ] Partial infer for spatial_temporal_network/rnn_net/rnn/MultiRNNCellZeroState/LSTMCellZeroState_2/concat_1 [ 2019-03-21 16:52:47,364 ] [ DEBUG ] [ infer:152 ] Op: ConcatV2 [ 2019-03-21 16:52:47,365 ] [ DEBUG ] [ infer:163 ] Inputs: [ 2019-03-21 16:52:47,366 ] [ DEBUG ] [ infer:40 ] input[0]: shape = [1], value = [1] [ 2019-03-21 16:52:47,367 ] [ DEBUG ] [ infer:40 ] input[1]: shape = [1], value = [512] [ 2019-03-21 16:52:47,367 ] [ DEBUG ] [ infer:165 ] Outputs: [ 2019-03-21 16:52:47,367 ] [ DEBUG ] [ infer:40 ] output[0]: shape = [2], value = [ 1 512] [ 2019-03-21 16:52:47,368 ] [ DEBUG ] [ infer:150 ] -------------------- [ 2019-03-21 16:52:47,368 ] [ DEBUG ] [ infer:151 ] Partial infer for spatial_temporal_network/rnn_net/rnn/MultiRNNCellZeroState/LSTMCellZeroState_2/zeros_1 [ 2019-03-21 16:52:47,368 ] [ DEBUG ] [ infer:152 ] Op: Fill [ INFO ] Called "tf_native_tf_node_infer" for node "spatial_temporal_network/rnn_net/rnn/MultiRNNCellZeroState/LSTMCellZeroState_2/zeros_1" [ 2019-03-21 16:52:47,372 ] [ DEBUG ] [ tf:222 ] Added placeholder with name 'spatial_temporal_network/rnn_net/rnn/MultiRNNCellZeroState/LSTMCellZeroState_2/concat_1_port_0_ie_placeholder' [ 2019-03-21 16:52:47,379 ] [ DEBUG ] [ tf:222 ] Added placeholder with name 'spatial_temporal_network/rnn_net/rnn/MultiRNNCellZeroState/LSTMCellZeroState_2/zeros_1/Const_port_0_ie_placeholder' [ 2019-03-21 16:52:47,379 ] [ DEBUG ] [ tf:235 ] update_input_in_pbs: replace input 'spatial_temporal_network/rnn_net/rnn/MultiRNNCellZeroState/LSTMCellZeroState_2/concat_1' with input 'spatial_temporal_network/rnn_net/rnn/MultiRNNCellZeroState/LSTMCellZeroState_2/concat_1_port_0_ie_placeholder' [ 2019-03-21 16:52:47,379 ] [ DEBUG ] [ tf:243 ] Replacing input '0' of the node 'spatial_temporal_network/rnn_net/rnn/MultiRNNCellZeroState/LSTMCellZeroState_2/zeros_1' with placeholder 'spatial_temporal_network/rnn_net/rnn/MultiRNNCellZeroState/LSTMCellZeroState_2/concat_1_port_0_ie_placeholder' [ 2019-03-21 16:52:47,379 ] [ DEBUG ] [ tf:235 ] update_input_in_pbs: replace input 'spatial_temporal_network/rnn_net/rnn/MultiRNNCellZeroState/LSTMCellZeroState_2/zeros_1/Const' with input 'spatial_temporal_network/rnn_net/rnn/MultiRNNCellZeroState/LSTMCellZeroState_2/zeros_1/Const_port_0_ie_placeholder' [ 2019-03-21 16:52:47,380 ] [ DEBUG ] [ tf:243 ] Replacing input '1' of the node 'spatial_temporal_network/rnn_net/rnn/MultiRNNCellZeroState/LSTMCellZeroState_2/zeros_1' with placeholder 'spatial_temporal_network/rnn_net/rnn/MultiRNNCellZeroState/LSTMCellZeroState_2/zeros_1/Const_port_0_ie_placeholder' [ 2019-03-21 16:52:47,396 ] [ DEBUG ] [ tf:142 ] Inferred shape of the output tensor with index '0' of the node 'spatial_temporal_network/rnn_net/rnn/MultiRNNCellZeroState/LSTMCellZeroState_2/zeros_1': '[ 1 512]' [ 2019-03-21 16:52:47,397 ] [ DEBUG ] [ infer:163 ] Inputs: [ 2019-03-21 16:52:47,397 ] [ DEBUG ] [ infer:40 ] input[0]: shape = [2], value = [ 1 512] [ 2019-03-21 16:52:47,397 ] [ DEBUG ] [ infer:40 ] input[1]: shape = [], value = 0.0 [ 2019-03-21 16:52:47,398 ] [ DEBUG ] [ infer:165 ] Outputs: [ 2019-03-21 16:52:47,410 ] [ DEBUG ] [ infer:40 ] output[0]: shape = [ 1 512], value = [[0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. ... [ 2019-03-21 16:52:47,411 ] [ DEBUG ] [ infer:150 ] -------------------- [ 2019-03-21 16:52:47,411 ] [ DEBUG ] [ infer:151 ] Partial infer for spatial_temporal_network/rnn_net/rnn/while/Enter_8 [ 2019-03-21 16:52:47,411 ] [ DEBUG ] [ infer:152 ] Op: Enter [ 2019-03-21 16:52:47,411 ] [ DEBUG ] [ infer:163 ] Inputs: [ 2019-03-21 16:52:47,423 ] [ DEBUG ] [ infer:40 ] input[0]: shape = [ 1 512], value = [[0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. ... [ 2019-03-21 16:52:47,423 ] [ DEBUG ] [ infer:165 ] Outputs: [ 2019-03-21 16:52:47,438 ] [ DEBUG ] [ infer:40 ] output[0]: shape = [ 1 512], value = [[0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. ... [ 2019-03-21 16:52:47,439 ] [ DEBUG ] [ infer:150 ] -------------------- [ 2019-03-21 16:52:47,439 ] [ DEBUG ] [ infer:151 ] Partial infer for spatial_temporal_network/rnn_net/rnn/while/Merge_8 [ 2019-03-21 16:52:47,440 ] [ DEBUG ] [ infer:152 ] Op: Merge [ 2019-03-21 16:52:47,440 ] [ DEBUG ] [ infer:163 ] Inputs: [ 2019-03-21 16:52:47,452 ] [ DEBUG ] [ infer:40 ] input[0]: shape = [ 1 512], value = [[0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. ... [ 2019-03-21 16:52:47,453 ] [ DEBUG ] [ infer:40 ] input[1]: shape = , value = [ 2019-03-21 16:52:47,453 ] [ DEBUG ] [ infer:165 ] Outputs: [ 2019-03-21 16:52:47,453 ] [ DEBUG ] [ infer:40 ] output[0]: shape = [ 1 512], value = [ 2019-03-21 16:52:47,454 ] [ DEBUG ] [ infer:150 ] -------------------- [ 2019-03-21 16:52:47,454 ] [ DEBUG ] [ infer:151 ] Partial infer for spatial_temporal_network/rnn_net/rnn/while/Switch_8 [ 2019-03-21 16:52:47,454 ] [ DEBUG ] [ infer:152 ] Op: Switch [ 2019-03-21 16:52:47,455 ] [ DEBUG ] [ infer:163 ] Inputs: [ 2019-03-21 16:52:47,455 ] [ DEBUG ] [ infer:40 ] input[0]: shape = [ 1 512], value = [ 2019-03-21 16:52:47,455 ] [ DEBUG ] [ infer:40 ] input[1]: shape = [], value = [ 2019-03-21 16:52:47,455 ] [ DEBUG ] [ infer:165 ] Outputs: [ 2019-03-21 16:52:47,456 ] [ DEBUG ] [ infer:40 ] output[1]: shape = [ 1 512], value = [ 2019-03-21 16:52:47,456 ] [ DEBUG ] [ infer:150 ] -------------------- [ 2019-03-21 16:52:47,456 ] [ DEBUG ] [ infer:151 ] Partial infer for spatial_temporal_network/rnn_net/rnn/while/Identity_8 [ 2019-03-21 16:52:47,456 ] [ DEBUG ] [ infer:152 ] Op: Identity [ 2019-03-21 16:52:47,457 ] [ DEBUG ] [ infer:163 ] Inputs: [ 2019-03-21 16:52:47,457 ] [ DEBUG ] [ infer:40 ] input[0]: shape = [ 1 512], value = [ 2019-03-21 16:52:47,457 ] [ DEBUG ] [ infer:165 ] Outputs: [ 2019-03-21 16:52:47,458 ] [ DEBUG ] [ infer:40 ] output[0]: shape = [ 1 512], value = [ 2019-03-21 16:52:47,458 ] [ DEBUG ] [ infer:150 ] -------------------- [ 2019-03-21 16:52:47,458 ] [ DEBUG ] [ infer:151 ] Partial infer for spatial_temporal_network/rnn_net/rnn/MultiRNNCellZeroState/LSTMCellZeroState_2/zeros/Const [ 2019-03-21 16:52:47,458 ] [ DEBUG ] [ infer:152 ] Op: Const [ 2019-03-21 16:52:47,459 ] [ DEBUG ] [ infer:163 ] Inputs: [ 2019-03-21 16:52:47,459 ] [ DEBUG ] [ infer:165 ] Outputs: [ 2019-03-21 16:52:47,459 ] [ DEBUG ] [ infer:40 ] output[0]: shape = [], value = 0.0 [ 2019-03-21 16:52:47,459 ] [ DEBUG ] [ infer:150 ] -------------------- [ 2019-03-21 16:52:47,459 ] [ DEBUG ] [ infer:151 ] Partial infer for spatial_temporal_network/rnn_net/rnn/MultiRNNCellZeroState/LSTMCellZeroState_2/concat/axis [ 2019-03-21 16:52:47,460 ] [ DEBUG ] [ infer:152 ] Op: Const [ 2019-03-21 16:52:47,460 ] [ DEBUG ] [ infer:163 ] Inputs: [ 2019-03-21 16:52:47,460 ] [ DEBUG ] [ infer:165 ] Outputs: [ 2019-03-21 16:52:47,460 ] [ DEBUG ] [ infer:40 ] output[0]: shape = [], value = 0 [ 2019-03-21 16:52:47,461 ] [ DEBUG ] [ infer:150 ] -------------------- [ 2019-03-21 16:52:47,461 ] [ DEBUG ] [ infer:151 ] Partial infer for spatial_temporal_network/rnn_net/rnn/MultiRNNCellZeroState/LSTMCellZeroState_2/Const_1 [ 2019-03-21 16:52:47,461 ] [ DEBUG ] [ infer:152 ] Op: Const [ 2019-03-21 16:52:47,461 ] [ DEBUG ] [ infer:163 ] Inputs: [ 2019-03-21 16:52:47,461 ] [ DEBUG ] [ infer:165 ] Outputs: [ 2019-03-21 16:52:47,462 ] [ DEBUG ] [ infer:40 ] output[0]: shape = [1], value = [512] [ 2019-03-21 16:52:47,462 ] [ DEBUG ] [ infer:150 ] -------------------- [ 2019-03-21 16:52:47,462 ] [ DEBUG ] [ infer:151 ] Partial infer for spatial_temporal_network/rnn_net/rnn/MultiRNNCellZeroState/LSTMCellZeroState_2/Const [ 2019-03-21 16:52:47,462 ] [ DEBUG ] [ infer:152 ] Op: Const [ 2019-03-21 16:52:47,463 ] [ DEBUG ] [ infer:163 ] Inputs: [ 2019-03-21 16:52:47,463 ] [ DEBUG ] [ infer:165 ] Outputs: [ 2019-03-21 16:52:47,463 ] [ DEBUG ] [ infer:40 ] output[0]: shape = [1], value = [1] [ 2019-03-21 16:52:47,464 ] [ DEBUG ] [ infer:150 ] -------------------- [ 2019-03-21 16:52:47,464 ] [ DEBUG ] [ infer:151 ] Partial infer for spatial_temporal_network/rnn_net/rnn/MultiRNNCellZeroState/LSTMCellZeroState_2/concat [ 2019-03-21 16:52:47,464 ] [ DEBUG ] [ infer:152 ] Op: ConcatV2 [ 2019-03-21 16:52:47,465 ] [ DEBUG ] [ infer:163 ] Inputs: [ 2019-03-21 16:52:47,465 ] [ DEBUG ] [ infer:40 ] input[0]: shape = [1], value = [1] [ 2019-03-21 16:52:47,466 ] [ DEBUG ] [ infer:40 ] input[1]: shape = [1], value = [512] [ 2019-03-21 16:52:47,466 ] [ DEBUG ] [ infer:165 ] Outputs: [ 2019-03-21 16:52:47,466 ] [ DEBUG ] [ infer:40 ] output[0]: shape = [2], value = [ 1 512] [ 2019-03-21 16:52:47,467 ] [ DEBUG ] [ infer:150 ] -------------------- [ 2019-03-21 16:52:47,467 ] [ DEBUG ] [ infer:151 ] Partial infer for spatial_temporal_network/rnn_net/rnn/MultiRNNCellZeroState/LSTMCellZeroState_2/zeros [ 2019-03-21 16:52:47,467 ] [ DEBUG ] [ infer:152 ] Op: Fill [ INFO ] Called "tf_native_tf_node_infer" for node "spatial_temporal_network/rnn_net/rnn/MultiRNNCellZeroState/LSTMCellZeroState_2/zeros" [ 2019-03-21 16:52:47,471 ] [ DEBUG ] [ tf:222 ] Added placeholder with name 'spatial_temporal_network/rnn_net/rnn/MultiRNNCellZeroState/LSTMCellZeroState_2/concat_port_0_ie_placeholder' [ 2019-03-21 16:52:47,472 ] [ DEBUG ] [ tf:222 ] Added placeholder with name 'spatial_temporal_network/rnn_net/rnn/MultiRNNCellZeroState/LSTMCellZeroState_2/zeros/Const_port_0_ie_placeholder' [ 2019-03-21 16:52:47,472 ] [ DEBUG ] [ tf:235 ] update_input_in_pbs: replace input 'spatial_temporal_network/rnn_net/rnn/MultiRNNCellZeroState/LSTMCellZeroState_2/concat' with input 'spatial_temporal_network/rnn_net/rnn/MultiRNNCellZeroState/LSTMCellZeroState_2/concat_port_0_ie_placeholder' [ 2019-03-21 16:52:47,473 ] [ DEBUG ] [ tf:243 ] Replacing input '0' of the node 'spatial_temporal_network/rnn_net/rnn/MultiRNNCellZeroState/LSTMCellZeroState_2/zeros' with placeholder 'spatial_temporal_network/rnn_net/rnn/MultiRNNCellZeroState/LSTMCellZeroState_2/concat_port_0_ie_placeholder' [ 2019-03-21 16:52:47,473 ] [ DEBUG ] [ tf:235 ] update_input_in_pbs: replace input 'spatial_temporal_network/rnn_net/rnn/MultiRNNCellZeroState/LSTMCellZeroState_2/zeros/Const' with input 'spatial_temporal_network/rnn_net/rnn/MultiRNNCellZeroState/LSTMCellZeroState_2/zeros/Const_port_0_ie_placeholder' [ 2019-03-21 16:52:47,473 ] [ DEBUG ] [ tf:243 ] Replacing input '1' of the node 'spatial_temporal_network/rnn_net/rnn/MultiRNNCellZeroState/LSTMCellZeroState_2/zeros' with placeholder 'spatial_temporal_network/rnn_net/rnn/MultiRNNCellZeroState/LSTMCellZeroState_2/zeros/Const_port_0_ie_placeholder' [ 2019-03-21 16:52:47,484 ] [ DEBUG ] [ tf:142 ] Inferred shape of the output tensor with index '0' of the node 'spatial_temporal_network/rnn_net/rnn/MultiRNNCellZeroState/LSTMCellZeroState_2/zeros': '[ 1 512]' [ 2019-03-21 16:52:47,486 ] [ DEBUG ] [ infer:163 ] Inputs: [ 2019-03-21 16:52:47,486 ] [ DEBUG ] [ infer:40 ] input[0]: shape = [2], value = [ 1 512] [ 2019-03-21 16:52:47,487 ] [ DEBUG ] [ infer:40 ] input[1]: shape = [], value = 0.0 [ 2019-03-21 16:52:47,487 ] [ DEBUG ] [ infer:165 ] Outputs: [ 2019-03-21 16:52:47,499 ] [ DEBUG ] [ infer:40 ] output[0]: shape = [ 1 512], value = [[0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. ... [ 2019-03-21 16:52:47,499 ] [ DEBUG ] [ infer:150 ] -------------------- [ 2019-03-21 16:52:47,499 ] [ DEBUG ] [ infer:151 ] Partial infer for spatial_temporal_network/rnn_net/rnn/while/Enter_7 [ 2019-03-21 16:52:47,499 ] [ DEBUG ] [ infer:152 ] Op: Enter [ 2019-03-21 16:52:47,500 ] [ DEBUG ] [ infer:163 ] Inputs: [ 2019-03-21 16:52:47,512 ] [ DEBUG ] [ infer:40 ] input[0]: shape = [ 1 512], value = [[0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. ... [ 2019-03-21 16:52:47,512 ] [ DEBUG ] [ infer:165 ] Outputs: [ 2019-03-21 16:52:47,524 ] [ DEBUG ] [ infer:40 ] output[0]: shape = [ 1 512], value = [[0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. ... [ 2019-03-21 16:52:47,525 ] [ DEBUG ] [ infer:150 ] -------------------- [ 2019-03-21 16:52:47,525 ] [ DEBUG ] [ infer:151 ] Partial infer for spatial_temporal_network/rnn_net/rnn/while/Merge_7 [ 2019-03-21 16:52:47,525 ] [ DEBUG ] [ infer:152 ] Op: Merge [ 2019-03-21 16:52:47,525 ] [ DEBUG ] [ infer:163 ] Inputs: [ 2019-03-21 16:52:47,536 ] [ DEBUG ] [ infer:40 ] input[0]: shape = [ 1 512], value = [[0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. ... [ 2019-03-21 16:52:47,537 ] [ DEBUG ] [ infer:40 ] input[1]: shape = , value = [ 2019-03-21 16:52:47,537 ] [ DEBUG ] [ infer:165 ] Outputs: [ 2019-03-21 16:52:47,537 ] [ DEBUG ] [ infer:40 ] output[0]: shape = [ 1 512], value = [ 2019-03-21 16:52:47,538 ] [ DEBUG ] [ infer:150 ] -------------------- [ 2019-03-21 16:52:47,538 ] [ DEBUG ] [ infer:151 ] Partial infer for spatial_temporal_network/rnn_net/rnn/while/Switch_7 [ 2019-03-21 16:52:47,538 ] [ DEBUG ] [ infer:152 ] Op: Switch [ 2019-03-21 16:52:47,538 ] [ DEBUG ] [ infer:163 ] Inputs: [ 2019-03-21 16:52:47,539 ] [ DEBUG ] [ infer:40 ] input[0]: shape = [ 1 512], value = [ 2019-03-21 16:52:47,539 ] [ DEBUG ] [ infer:40 ] input[1]: shape = [], value = [ 2019-03-21 16:52:47,539 ] [ DEBUG ] [ infer:165 ] Outputs: [ 2019-03-21 16:52:47,539 ] [ DEBUG ] [ infer:40 ] output[1]: shape = [ 1 512], value = [ 2019-03-21 16:52:47,540 ] [ DEBUG ] [ infer:150 ] -------------------- [ 2019-03-21 16:52:47,540 ] [ DEBUG ] [ infer:151 ] Partial infer for spatial_temporal_network/rnn_net/rnn/while/Identity_7 [ 2019-03-21 16:52:47,540 ] [ DEBUG ] [ infer:152 ] Op: Identity [ 2019-03-21 16:52:47,541 ] [ DEBUG ] [ infer:163 ] Inputs: [ 2019-03-21 16:52:47,541 ] [ DEBUG ] [ infer:40 ] input[0]: shape = [ 1 512], value = [ 2019-03-21 16:52:47,541 ] [ DEBUG ] [ infer:165 ] Outputs: [ 2019-03-21 16:52:47,542 ] [ DEBUG ] [ infer:40 ] output[0]: shape = [ 1 512], value = [ 2019-03-21 16:52:47,542 ] [ DEBUG ] [ infer:150 ] -------------------- [ 2019-03-21 16:52:47,542 ] [ DEBUG ] [ infer:151 ] Partial infer for spatial_temporal_network/rnn_net/rnn/MultiRNNCellZeroState/LSTMCellZeroState_1/zeros_1/Const [ 2019-03-21 16:52:47,542 ] [ DEBUG ] [ infer:152 ] Op: Const [ 2019-03-21 16:52:47,543 ] [ DEBUG ] [ infer:163 ] Inputs: [ 2019-03-21 16:52:47,543 ] [ DEBUG ] [ infer:165 ] Outputs: [ 2019-03-21 16:52:47,543 ] [ DEBUG ] [ infer:40 ] output[0]: shape = [], value = 0.0 [ 2019-03-21 16:52:47,543 ] [ DEBUG ] [ infer:150 ] -------------------- [ 2019-03-21 16:52:47,543 ] [ DEBUG ] [ infer:151 ] Partial infer for spatial_temporal_network/rnn_net/rnn/MultiRNNCellZeroState/LSTMCellZeroState_1/concat_1/axis [ 2019-03-21 16:52:47,544 ] [ DEBUG ] [ infer:152 ] Op: Const [ 2019-03-21 16:52:47,544 ] [ DEBUG ] [ infer:163 ] Inputs: [ 2019-03-21 16:52:47,544 ] [ DEBUG ] [ infer:165 ] Outputs: [ 2019-03-21 16:52:47,544 ] [ DEBUG ] [ infer:40 ] output[0]: shape = [], value = 0 [ 2019-03-21 16:52:47,545 ] [ DEBUG ] [ infer:150 ] -------------------- [ 2019-03-21 16:52:47,545 ] [ DEBUG ] [ infer:151 ] Partial infer for spatial_temporal_network/rnn_net/rnn/MultiRNNCellZeroState/LSTMCellZeroState_1/Const_5 [ 2019-03-21 16:52:47,545 ] [ DEBUG ] [ infer:152 ] Op: Const [ 2019-03-21 16:52:47,545 ] [ DEBUG ] [ infer:163 ] Inputs: [ 2019-03-21 16:52:47,545 ] [ DEBUG ] [ infer:165 ] Outputs: [ 2019-03-21 16:52:47,546 ] [ DEBUG ] [ infer:40 ] output[0]: shape = [1], value = [512] [ 2019-03-21 16:52:47,546 ] [ DEBUG ] [ infer:150 ] -------------------- [ 2019-03-21 16:52:47,546 ] [ DEBUG ] [ infer:151 ] Partial infer for spatial_temporal_network/rnn_net/rnn/MultiRNNCellZeroState/LSTMCellZeroState_1/Const_4 [ 2019-03-21 16:52:47,546 ] [ DEBUG ] [ infer:152 ] Op: Const [ 2019-03-21 16:52:47,547 ] [ DEBUG ] [ infer:163 ] Inputs: [ 2019-03-21 16:52:47,547 ] [ DEBUG ] [ infer:165 ] Outputs: [ 2019-03-21 16:52:47,547 ] [ DEBUG ] [ infer:40 ] output[0]: shape = [1], value = [1] [ 2019-03-21 16:52:47,548 ] [ DEBUG ] [ infer:150 ] -------------------- [ 2019-03-21 16:52:47,548 ] [ DEBUG ] [ infer:151 ] Partial infer for spatial_temporal_network/rnn_net/rnn/MultiRNNCellZeroState/LSTMCellZeroState_1/concat_1 [ 2019-03-21 16:52:47,548 ] [ DEBUG ] [ infer:152 ] Op: ConcatV2 [ 2019-03-21 16:52:47,549 ] [ DEBUG ] [ infer:163 ] Inputs: [ 2019-03-21 16:52:47,549 ] [ DEBUG ] [ infer:40 ] input[0]: shape = [1], value = [1] [ 2019-03-21 16:52:47,550 ] [ DEBUG ] [ infer:40 ] input[1]: shape = [1], value = [512] [ 2019-03-21 16:52:47,550 ] [ DEBUG ] [ infer:165 ] Outputs: [ 2019-03-21 16:52:47,551 ] [ DEBUG ] [ infer:40 ] output[0]: shape = [2], value = [ 1 512] [ 2019-03-21 16:52:47,551 ] [ DEBUG ] [ infer:150 ] -------------------- [ 2019-03-21 16:52:47,551 ] [ DEBUG ] [ infer:151 ] Partial infer for spatial_temporal_network/rnn_net/rnn/MultiRNNCellZeroState/LSTMCellZeroState_1/zeros_1 [ 2019-03-21 16:52:47,551 ] [ DEBUG ] [ infer:152 ] Op: Fill [ INFO ] Called "tf_native_tf_node_infer" for node "spatial_temporal_network/rnn_net/rnn/MultiRNNCellZeroState/LSTMCellZeroState_1/zeros_1" [ 2019-03-21 16:52:47,555 ] [ DEBUG ] [ tf:222 ] Added placeholder with name 'spatial_temporal_network/rnn_net/rnn/MultiRNNCellZeroState/LSTMCellZeroState_1/concat_1_port_0_ie_placeholder' [ 2019-03-21 16:52:47,557 ] [ DEBUG ] [ tf:222 ] Added placeholder with name 'spatial_temporal_network/rnn_net/rnn/MultiRNNCellZeroState/LSTMCellZeroState_1/zeros_1/Const_port_0_ie_placeholder' [ 2019-03-21 16:52:47,557 ] [ DEBUG ] [ tf:235 ] update_input_in_pbs: replace input 'spatial_temporal_network/rnn_net/rnn/MultiRNNCellZeroState/LSTMCellZeroState_1/concat_1' with input 'spatial_temporal_network/rnn_net/rnn/MultiRNNCellZeroState/LSTMCellZeroState_1/concat_1_port_0_ie_placeholder' [ 2019-03-21 16:52:47,557 ] [ DEBUG ] [ tf:243 ] Replacing input '0' of the node 'spatial_temporal_network/rnn_net/rnn/MultiRNNCellZeroState/LSTMCellZeroState_1/zeros_1' with placeholder 'spatial_temporal_network/rnn_net/rnn/MultiRNNCellZeroState/LSTMCellZeroState_1/concat_1_port_0_ie_placeholder' [ 2019-03-21 16:52:47,557 ] [ DEBUG ] [ tf:235 ] update_input_in_pbs: replace input 'spatial_temporal_network/rnn_net/rnn/MultiRNNCellZeroState/LSTMCellZeroState_1/zeros_1/Const' with input 'spatial_temporal_network/rnn_net/rnn/MultiRNNCellZeroState/LSTMCellZeroState_1/zeros_1/Const_port_0_ie_placeholder' [ 2019-03-21 16:52:47,557 ] [ DEBUG ] [ tf:243 ] Replacing input '1' of the node 'spatial_temporal_network/rnn_net/rnn/MultiRNNCellZeroState/LSTMCellZeroState_1/zeros_1' with placeholder 'spatial_temporal_network/rnn_net/rnn/MultiRNNCellZeroState/LSTMCellZeroState_1/zeros_1/Const_port_0_ie_placeholder' [ 2019-03-21 16:52:47,569 ] [ DEBUG ] [ tf:142 ] Inferred shape of the output tensor with index '0' of the node 'spatial_temporal_network/rnn_net/rnn/MultiRNNCellZeroState/LSTMCellZeroState_1/zeros_1': '[ 1 512]' [ 2019-03-21 16:52:47,572 ] [ DEBUG ] [ infer:163 ] Inputs: [ 2019-03-21 16:52:47,572 ] [ DEBUG ] [ infer:40 ] input[0]: shape = [2], value = [ 1 512] [ 2019-03-21 16:52:47,573 ] [ DEBUG ] [ infer:40 ] input[1]: shape = [], value = 0.0 [ 2019-03-21 16:52:47,573 ] [ DEBUG ] [ infer:165 ] Outputs: [ 2019-03-21 16:52:47,584 ] [ DEBUG ] [ infer:40 ] output[0]: shape = [ 1 512], value = [[0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. ... [ 2019-03-21 16:52:47,585 ] [ DEBUG ] [ infer:150 ] -------------------- [ 2019-03-21 16:52:47,585 ] [ DEBUG ] [ infer:151 ] Partial infer for spatial_temporal_network/rnn_net/rnn/while/Enter_6 [ 2019-03-21 16:52:47,585 ] [ DEBUG ] [ infer:152 ] Op: Enter [ 2019-03-21 16:52:47,586 ] [ DEBUG ] [ infer:163 ] Inputs: [ 2019-03-21 16:52:47,597 ] [ DEBUG ] [ infer:40 ] input[0]: shape = [ 1 512], value = [[0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. ... [ 2019-03-21 16:52:47,598 ] [ DEBUG ] [ infer:165 ] Outputs: [ 2019-03-21 16:52:47,610 ] [ DEBUG ] [ infer:40 ] output[0]: shape = [ 1 512], value = [[0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. ... [ 2019-03-21 16:52:47,611 ] [ DEBUG ] [ infer:150 ] -------------------- [ 2019-03-21 16:52:47,611 ] [ DEBUG ] [ infer:151 ] Partial infer for spatial_temporal_network/rnn_net/rnn/while/Merge_6 [ 2019-03-21 16:52:47,611 ] [ DEBUG ] [ infer:152 ] Op: Merge [ 2019-03-21 16:52:47,611 ] [ DEBUG ] [ infer:163 ] Inputs: [ 2019-03-21 16:52:47,624 ] [ DEBUG ] [ infer:40 ] input[0]: shape = [ 1 512], value = [[0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. ... [ 2019-03-21 16:52:47,624 ] [ DEBUG ] [ infer:40 ] input[1]: shape = , value = [ 2019-03-21 16:52:47,624 ] [ DEBUG ] [ infer:165 ] Outputs: [ 2019-03-21 16:52:47,624 ] [ DEBUG ] [ infer:40 ] output[0]: shape = [ 1 512], value = [ 2019-03-21 16:52:47,625 ] [ DEBUG ] [ infer:150 ] -------------------- [ 2019-03-21 16:52:47,625 ] [ DEBUG ] [ infer:151 ] Partial infer for spatial_temporal_network/rnn_net/rnn/while/Switch_6 [ 2019-03-21 16:52:47,625 ] [ DEBUG ] [ infer:152 ] Op: Switch [ 2019-03-21 16:52:47,625 ] [ DEBUG ] [ infer:163 ] Inputs: [ 2019-03-21 16:52:47,626 ] [ DEBUG ] [ infer:40 ] input[0]: shape = [ 1 512], value = [ 2019-03-21 16:52:47,626 ] [ DEBUG ] [ infer:40 ] input[1]: shape = [], value = [ 2019-03-21 16:52:47,626 ] [ DEBUG ] [ infer:165 ] Outputs: [ 2019-03-21 16:52:47,627 ] [ DEBUG ] [ infer:40 ] output[1]: shape = [ 1 512], value = [ 2019-03-21 16:52:47,627 ] [ DEBUG ] [ infer:150 ] -------------------- [ 2019-03-21 16:52:47,627 ] [ DEBUG ] [ infer:151 ] Partial infer for spatial_temporal_network/rnn_net/rnn/while/Identity_6 [ 2019-03-21 16:52:47,627 ] [ DEBUG ] [ infer:152 ] Op: Identity [ 2019-03-21 16:52:47,628 ] [ DEBUG ] [ infer:163 ] Inputs: [ 2019-03-21 16:52:47,628 ] [ DEBUG ] [ infer:40 ] input[0]: shape = [ 1 512], value = [ 2019-03-21 16:52:47,628 ] [ DEBUG ] [ infer:165 ] Outputs: [ 2019-03-21 16:52:47,629 ] [ DEBUG ] [ infer:40 ] output[0]: shape = [ 1 512], value = [ 2019-03-21 16:52:47,629 ] [ DEBUG ] [ infer:150 ] -------------------- [ 2019-03-21 16:52:47,629 ] [ DEBUG ] [ infer:151 ] Partial infer for spatial_temporal_network/rnn_net/rnn/MultiRNNCellZeroState/LSTMCellZeroState_1/zeros/Const [ 2019-03-21 16:52:47,629 ] [ DEBUG ] [ infer:152 ] Op: Const [ 2019-03-21 16:52:47,629 ] [ DEBUG ] [ infer:163 ] Inputs: [ 2019-03-21 16:52:47,630 ] [ DEBUG ] [ infer:165 ] Outputs: [ 2019-03-21 16:52:47,630 ] [ DEBUG ] [ infer:40 ] output[0]: shape = [], value = 0.0 [ 2019-03-21 16:52:47,630 ] [ DEBUG ] [ infer:150 ] -------------------- [ 2019-03-21 16:52:47,630 ] [ DEBUG ] [ infer:151 ] Partial infer for spatial_temporal_network/rnn_net/rnn/MultiRNNCellZeroState/LSTMCellZeroState_1/concat/axis [ 2019-03-21 16:52:47,631 ] [ DEBUG ] [ infer:152 ] Op: Const [ 2019-03-21 16:52:47,631 ] [ DEBUG ] [ infer:163 ] Inputs: [ 2019-03-21 16:52:47,631 ] [ DEBUG ] [ infer:165 ] Outputs: [ 2019-03-21 16:52:47,631 ] [ DEBUG ] [ infer:40 ] output[0]: shape = [], value = 0 [ 2019-03-21 16:52:47,631 ] [ DEBUG ] [ infer:150 ] -------------------- [ 2019-03-21 16:52:47,632 ] [ DEBUG ] [ infer:151 ] Partial infer for spatial_temporal_network/rnn_net/rnn/MultiRNNCellZeroState/LSTMCellZeroState_1/Const_1 [ 2019-03-21 16:52:47,632 ] [ DEBUG ] [ infer:152 ] Op: Const [ 2019-03-21 16:52:47,632 ] [ DEBUG ] [ infer:163 ] Inputs: [ 2019-03-21 16:52:47,632 ] [ DEBUG ] [ infer:165 ] Outputs: [ 2019-03-21 16:52:47,633 ] [ DEBUG ] [ infer:40 ] output[0]: shape = [1], value = [512] [ 2019-03-21 16:52:47,633 ] [ DEBUG ] [ infer:150 ] -------------------- [ 2019-03-21 16:52:47,633 ] [ DEBUG ] [ infer:151 ] Partial infer for spatial_temporal_network/rnn_net/rnn/MultiRNNCellZeroState/LSTMCellZeroState_1/Const [ 2019-03-21 16:52:47,633 ] [ DEBUG ] [ infer:152 ] Op: Const [ 2019-03-21 16:52:47,634 ] [ DEBUG ] [ infer:163 ] Inputs: [ 2019-03-21 16:52:47,634 ] [ DEBUG ] [ infer:165 ] Outputs: [ 2019-03-21 16:52:47,634 ] [ DEBUG ] [ infer:40 ] output[0]: shape = [1], value = [1] [ 2019-03-21 16:52:47,635 ] [ DEBUG ] [ infer:150 ] -------------------- [ 2019-03-21 16:52:47,635 ] [ DEBUG ] [ infer:151 ] Partial infer for spatial_temporal_network/rnn_net/rnn/MultiRNNCellZeroState/LSTMCellZeroState_1/concat [ 2019-03-21 16:52:47,635 ] [ DEBUG ] [ infer:152 ] Op: ConcatV2 [ 2019-03-21 16:52:47,636 ] [ DEBUG ] [ infer:163 ] Inputs: [ 2019-03-21 16:52:47,636 ] [ DEBUG ] [ infer:40 ] input[0]: shape = [1], value = [1] [ 2019-03-21 16:52:47,637 ] [ DEBUG ] [ infer:40 ] input[1]: shape = [1], value = [512] [ 2019-03-21 16:52:47,637 ] [ DEBUG ] [ infer:165 ] Outputs: [ 2019-03-21 16:52:47,637 ] [ DEBUG ] [ infer:40 ] output[0]: shape = [2], value = [ 1 512] [ 2019-03-21 16:52:47,638 ] [ DEBUG ] [ infer:150 ] -------------------- [ 2019-03-21 16:52:47,638 ] [ DEBUG ] [ infer:151 ] Partial infer for spatial_temporal_network/rnn_net/rnn/MultiRNNCellZeroState/LSTMCellZeroState_1/zeros [ 2019-03-21 16:52:47,638 ] [ DEBUG ] [ infer:152 ] Op: Fill [ INFO ] Called "tf_native_tf_node_infer" for node "spatial_temporal_network/rnn_net/rnn/MultiRNNCellZeroState/LSTMCellZeroState_1/zeros" [ 2019-03-21 16:52:47,641 ] [ DEBUG ] [ tf:222 ] Added placeholder with name 'spatial_temporal_network/rnn_net/rnn/MultiRNNCellZeroState/LSTMCellZeroState_1/concat_port_0_ie_placeholder' [ 2019-03-21 16:52:47,643 ] [ DEBUG ] [ tf:222 ] Added placeholder with name 'spatial_temporal_network/rnn_net/rnn/MultiRNNCellZeroState/LSTMCellZeroState_1/zeros/Const_port_0_ie_placeholder' [ 2019-03-21 16:52:47,643 ] [ DEBUG ] [ tf:235 ] update_input_in_pbs: replace input 'spatial_temporal_network/rnn_net/rnn/MultiRNNCellZeroState/LSTMCellZeroState_1/concat' with input 'spatial_temporal_network/rnn_net/rnn/MultiRNNCellZeroState/LSTMCellZeroState_1/concat_port_0_ie_placeholder' [ 2019-03-21 16:52:47,643 ] [ DEBUG ] [ tf:243 ] Replacing input '0' of the node 'spatial_temporal_network/rnn_net/rnn/MultiRNNCellZeroState/LSTMCellZeroState_1/zeros' with placeholder 'spatial_temporal_network/rnn_net/rnn/MultiRNNCellZeroState/LSTMCellZeroState_1/concat_port_0_ie_placeholder' [ 2019-03-21 16:52:47,643 ] [ DEBUG ] [ tf:235 ] update_input_in_pbs: replace input 'spatial_temporal_network/rnn_net/rnn/MultiRNNCellZeroState/LSTMCellZeroState_1/zeros/Const' with input 'spatial_temporal_network/rnn_net/rnn/MultiRNNCellZeroState/LSTMCellZeroState_1/zeros/Const_port_0_ie_placeholder' [ 2019-03-21 16:52:47,644 ] [ DEBUG ] [ tf:243 ] Replacing input '1' of the node 'spatial_temporal_network/rnn_net/rnn/MultiRNNCellZeroState/LSTMCellZeroState_1/zeros' with placeholder 'spatial_temporal_network/rnn_net/rnn/MultiRNNCellZeroState/LSTMCellZeroState_1/zeros/Const_port_0_ie_placeholder' [ 2019-03-21 16:52:47,659 ] [ DEBUG ] [ tf:142 ] Inferred shape of the output tensor with index '0' of the node 'spatial_temporal_network/rnn_net/rnn/MultiRNNCellZeroState/LSTMCellZeroState_1/zeros': '[ 1 512]' [ 2019-03-21 16:52:47,660 ] [ DEBUG ] [ infer:163 ] Inputs: [ 2019-03-21 16:52:47,661 ] [ DEBUG ] [ infer:40 ] input[0]: shape = [2], value = [ 1 512] [ 2019-03-21 16:52:47,661 ] [ DEBUG ] [ infer:40 ] input[1]: shape = [], value = 0.0 [ 2019-03-21 16:52:47,661 ] [ DEBUG ] [ infer:165 ] Outputs: [ 2019-03-21 16:52:47,674 ] [ DEBUG ] [ infer:40 ] output[0]: shape = [ 1 512], value = [[0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. ... [ 2019-03-21 16:52:47,674 ] [ DEBUG ] [ infer:150 ] -------------------- [ 2019-03-21 16:52:47,674 ] [ DEBUG ] [ infer:151 ] Partial infer for spatial_temporal_network/rnn_net/rnn/while/Enter_5 [ 2019-03-21 16:52:47,675 ] [ DEBUG ] [ infer:152 ] Op: Enter [ 2019-03-21 16:52:47,675 ] [ DEBUG ] [ infer:163 ] Inputs: [ 2019-03-21 16:52:47,687 ] [ DEBUG ] [ infer:40 ] input[0]: shape = [ 1 512], value = [[0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. ... [ 2019-03-21 16:52:47,687 ] [ DEBUG ] [ infer:165 ] Outputs: [ 2019-03-21 16:52:47,699 ] [ DEBUG ] [ infer:40 ] output[0]: shape = [ 1 512], value = [[0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. ... [ 2019-03-21 16:52:47,700 ] [ DEBUG ] [ infer:150 ] -------------------- [ 2019-03-21 16:52:47,700 ] [ DEBUG ] [ infer:151 ] Partial infer for spatial_temporal_network/rnn_net/rnn/while/Merge_5 [ 2019-03-21 16:52:47,700 ] [ DEBUG ] [ infer:152 ] Op: Merge [ 2019-03-21 16:52:47,700 ] [ DEBUG ] [ infer:163 ] Inputs: [ 2019-03-21 16:52:47,714 ] [ DEBUG ] [ infer:40 ] input[0]: shape = [ 1 512], value = [[0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. ... [ 2019-03-21 16:52:47,714 ] [ DEBUG ] [ infer:40 ] input[1]: shape = , value = [ 2019-03-21 16:52:47,715 ] [ DEBUG ] [ infer:165 ] Outputs: [ 2019-03-21 16:52:47,715 ] [ DEBUG ] [ infer:40 ] output[0]: shape = [ 1 512], value = [ 2019-03-21 16:52:47,715 ] [ DEBUG ] [ infer:150 ] -------------------- [ 2019-03-21 16:52:47,716 ] [ DEBUG ] [ infer:151 ] Partial infer for spatial_temporal_network/rnn_net/rnn/while/Switch_5 [ 2019-03-21 16:52:47,716 ] [ DEBUG ] [ infer:152 ] Op: Switch [ 2019-03-21 16:52:47,716 ] [ DEBUG ] [ infer:163 ] Inputs: [ 2019-03-21 16:52:47,717 ] [ DEBUG ] [ infer:40 ] input[0]: shape = [ 1 512], value = [ 2019-03-21 16:52:47,717 ] [ DEBUG ] [ infer:40 ] input[1]: shape = [], value = [ 2019-03-21 16:52:47,717 ] [ DEBUG ] [ infer:165 ] Outputs: [ 2019-03-21 16:52:47,717 ] [ DEBUG ] [ infer:40 ] output[1]: shape = [ 1 512], value = [ 2019-03-21 16:52:47,718 ] [ DEBUG ] [ infer:150 ] -------------------- [ 2019-03-21 16:52:47,718 ] [ DEBUG ] [ infer:151 ] Partial infer for spatial_temporal_network/rnn_net/rnn/while/Identity_5 [ 2019-03-21 16:52:47,718 ] [ DEBUG ] [ infer:152 ] Op: Identity [ 2019-03-21 16:52:47,719 ] [ DEBUG ] [ infer:163 ] Inputs: [ 2019-03-21 16:52:47,719 ] [ DEBUG ] [ infer:40 ] input[0]: shape = [ 1 512], value = [ 2019-03-21 16:52:47,719 ] [ DEBUG ] [ infer:165 ] Outputs: [ 2019-03-21 16:52:47,720 ] [ DEBUG ] [ infer:40 ] output[0]: shape = [ 1 512], value = [ 2019-03-21 16:52:47,720 ] [ DEBUG ] [ infer:150 ] -------------------- [ 2019-03-21 16:52:47,720 ] [ DEBUG ] [ infer:151 ] Partial infer for spatial_temporal_network/rnn_net/rnn/MultiRNNCellZeroState/LSTMCellZeroState/zeros_1/Const [ 2019-03-21 16:52:47,720 ] [ DEBUG ] [ infer:152 ] Op: Const [ 2019-03-21 16:52:47,721 ] [ DEBUG ] [ infer:163 ] Inputs: [ 2019-03-21 16:52:47,721 ] [ DEBUG ] [ infer:165 ] Outputs: [ 2019-03-21 16:52:47,721 ] [ DEBUG ] [ infer:40 ] output[0]: shape = [], value = 0.0 [ 2019-03-21 16:52:47,722 ] [ DEBUG ] [ infer:150 ] -------------------- [ 2019-03-21 16:52:47,722 ] [ DEBUG ] [ infer:151 ] Partial infer for spatial_temporal_network/rnn_net/rnn/MultiRNNCellZeroState/LSTMCellZeroState/concat_1/axis [ 2019-03-21 16:52:47,722 ] [ DEBUG ] [ infer:152 ] Op: Const [ 2019-03-21 16:52:47,723 ] [ DEBUG ] [ infer:163 ] Inputs: [ 2019-03-21 16:52:47,723 ] [ DEBUG ] [ infer:165 ] Outputs: [ 2019-03-21 16:52:47,723 ] [ DEBUG ] [ infer:40 ] output[0]: shape = [], value = 0 [ 2019-03-21 16:52:47,723 ] [ DEBUG ] [ infer:150 ] -------------------- [ 2019-03-21 16:52:47,724 ] [ DEBUG ] [ infer:151 ] Partial infer for spatial_temporal_network/rnn_net/rnn/MultiRNNCellZeroState/LSTMCellZeroState/Const_5 [ 2019-03-21 16:52:47,724 ] [ DEBUG ] [ infer:152 ] Op: Const [ 2019-03-21 16:52:47,724 ] [ DEBUG ] [ infer:163 ] Inputs: [ 2019-03-21 16:52:47,724 ] [ DEBUG ] [ infer:165 ] Outputs: [ 2019-03-21 16:52:47,725 ] [ DEBUG ] [ infer:40 ] output[0]: shape = [1], value = [512] [ 2019-03-21 16:52:47,725 ] [ DEBUG ] [ infer:150 ] -------------------- [ 2019-03-21 16:52:47,725 ] [ DEBUG ] [ infer:151 ] Partial infer for spatial_temporal_network/rnn_net/rnn/MultiRNNCellZeroState/LSTMCellZeroState/Const_4 [ 2019-03-21 16:52:47,725 ] [ DEBUG ] [ infer:152 ] Op: Const [ 2019-03-21 16:52:47,726 ] [ DEBUG ] [ infer:163 ] Inputs: [ 2019-03-21 16:52:47,726 ] [ DEBUG ] [ infer:165 ] Outputs: [ 2019-03-21 16:52:47,727 ] [ DEBUG ] [ infer:40 ] output[0]: shape = [1], value = [1] [ 2019-03-21 16:52:47,727 ] [ DEBUG ] [ infer:150 ] -------------------- [ 2019-03-21 16:52:47,727 ] [ DEBUG ] [ infer:151 ] Partial infer for spatial_temporal_network/rnn_net/rnn/MultiRNNCellZeroState/LSTMCellZeroState/concat_1 [ 2019-03-21 16:52:47,727 ] [ DEBUG ] [ infer:152 ] Op: ConcatV2 [ 2019-03-21 16:52:47,728 ] [ DEBUG ] [ infer:163 ] Inputs: [ 2019-03-21 16:52:47,729 ] [ DEBUG ] [ infer:40 ] input[0]: shape = [1], value = [1] [ 2019-03-21 16:52:47,729 ] [ DEBUG ] [ infer:40 ] input[1]: shape = [1], value = [512] [ 2019-03-21 16:52:47,729 ] [ DEBUG ] [ infer:165 ] Outputs: [ 2019-03-21 16:52:47,730 ] [ DEBUG ] [ infer:40 ] output[0]: shape = [2], value = [ 1 512] [ 2019-03-21 16:52:47,730 ] [ DEBUG ] [ infer:150 ] -------------------- [ 2019-03-21 16:52:47,731 ] [ DEBUG ] [ infer:151 ] Partial infer for spatial_temporal_network/rnn_net/rnn/MultiRNNCellZeroState/LSTMCellZeroState/zeros_1 [ 2019-03-21 16:52:47,731 ] [ DEBUG ] [ infer:152 ] Op: Fill [ INFO ] Called "tf_native_tf_node_infer" for node "spatial_temporal_network/rnn_net/rnn/MultiRNNCellZeroState/LSTMCellZeroState/zeros_1" [ 2019-03-21 16:52:47,735 ] [ DEBUG ] [ tf:222 ] Added placeholder with name 'spatial_temporal_network/rnn_net/rnn/MultiRNNCellZeroState/LSTMCellZeroState/concat_1_port_0_ie_placeholder' [ 2019-03-21 16:52:47,736 ] [ DEBUG ] [ tf:222 ] Added placeholder with name 'spatial_temporal_network/rnn_net/rnn/MultiRNNCellZeroState/LSTMCellZeroState/zeros_1/Const_port_0_ie_placeholder' [ 2019-03-21 16:52:47,737 ] [ DEBUG ] [ tf:235 ] update_input_in_pbs: replace input 'spatial_temporal_network/rnn_net/rnn/MultiRNNCellZeroState/LSTMCellZeroState/concat_1' with input 'spatial_temporal_network/rnn_net/rnn/MultiRNNCellZeroState/LSTMCellZeroState/concat_1_port_0_ie_placeholder' [ 2019-03-21 16:52:47,737 ] [ DEBUG ] [ tf:243 ] Replacing input '0' of the node 'spatial_temporal_network/rnn_net/rnn/MultiRNNCellZeroState/LSTMCellZeroState/zeros_1' with placeholder 'spatial_temporal_network/rnn_net/rnn/MultiRNNCellZeroState/LSTMCellZeroState/concat_1_port_0_ie_placeholder' [ 2019-03-21 16:52:47,737 ] [ DEBUG ] [ tf:235 ] update_input_in_pbs: replace input 'spatial_temporal_network/rnn_net/rnn/MultiRNNCellZeroState/LSTMCellZeroState/zeros_1/Const' with input 'spatial_temporal_network/rnn_net/rnn/MultiRNNCellZeroState/LSTMCellZeroState/zeros_1/Const_port_0_ie_placeholder' [ 2019-03-21 16:52:47,737 ] [ DEBUG ] [ tf:243 ] Replacing input '1' of the node 'spatial_temporal_network/rnn_net/rnn/MultiRNNCellZeroState/LSTMCellZeroState/zeros_1' with placeholder 'spatial_temporal_network/rnn_net/rnn/MultiRNNCellZeroState/LSTMCellZeroState/zeros_1/Const_port_0_ie_placeholder' [ 2019-03-21 16:52:47,748 ] [ DEBUG ] [ tf:142 ] Inferred shape of the output tensor with index '0' of the node 'spatial_temporal_network/rnn_net/rnn/MultiRNNCellZeroState/LSTMCellZeroState/zeros_1': '[ 1 512]' [ 2019-03-21 16:52:47,749 ] [ DEBUG ] [ infer:163 ] Inputs: [ 2019-03-21 16:52:47,750 ] [ DEBUG ] [ infer:40 ] input[0]: shape = [2], value = [ 1 512] [ 2019-03-21 16:52:47,750 ] [ DEBUG ] [ infer:40 ] input[1]: shape = [], value = 0.0 [ 2019-03-21 16:52:47,750 ] [ DEBUG ] [ infer:165 ] Outputs: [ 2019-03-21 16:52:47,762 ] [ DEBUG ] [ infer:40 ] output[0]: shape = [ 1 512], value = [[0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. ... [ 2019-03-21 16:52:47,763 ] [ DEBUG ] [ infer:150 ] -------------------- [ 2019-03-21 16:52:47,763 ] [ DEBUG ] [ infer:151 ] Partial infer for spatial_temporal_network/rnn_net/rnn/while/Enter_4 [ 2019-03-21 16:52:47,763 ] [ DEBUG ] [ infer:152 ] Op: Enter [ 2019-03-21 16:52:47,764 ] [ DEBUG ] [ infer:163 ] Inputs: [ 2019-03-21 16:52:47,776 ] [ DEBUG ] [ infer:40 ] input[0]: shape = [ 1 512], value = [[0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. ... [ 2019-03-21 16:52:47,776 ] [ DEBUG ] [ infer:165 ] Outputs: [ 2019-03-21 16:52:47,788 ] [ DEBUG ] [ infer:40 ] output[0]: shape = [ 1 512], value = [[0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. ... [ 2019-03-21 16:52:47,789 ] [ DEBUG ] [ infer:150 ] -------------------- [ 2019-03-21 16:52:47,789 ] [ DEBUG ] [ infer:151 ] Partial infer for spatial_temporal_network/rnn_net/rnn/while/Merge_4 [ 2019-03-21 16:52:47,789 ] [ DEBUG ] [ infer:152 ] Op: Merge [ 2019-03-21 16:52:47,790 ] [ DEBUG ] [ infer:163 ] Inputs: [ 2019-03-21 16:52:47,802 ] [ DEBUG ] [ infer:40 ] input[0]: shape = [ 1 512], value = [[0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. ... [ 2019-03-21 16:52:47,803 ] [ DEBUG ] [ infer:40 ] input[1]: shape = , value = [ 2019-03-21 16:52:47,803 ] [ DEBUG ] [ infer:165 ] Outputs: [ 2019-03-21 16:52:47,803 ] [ DEBUG ] [ infer:40 ] output[0]: shape = [ 1 512], value = [ 2019-03-21 16:52:47,803 ] [ DEBUG ] [ infer:150 ] -------------------- [ 2019-03-21 16:52:47,804 ] [ DEBUG ] [ infer:151 ] Partial infer for spatial_temporal_network/rnn_net/rnn/while/Switch_4 [ 2019-03-21 16:52:47,804 ] [ DEBUG ] [ infer:152 ] Op: Switch [ 2019-03-21 16:52:47,804 ] [ DEBUG ] [ infer:163 ] Inputs: [ 2019-03-21 16:52:47,805 ] [ DEBUG ] [ infer:40 ] input[0]: shape = [ 1 512], value = [ 2019-03-21 16:52:47,805 ] [ DEBUG ] [ infer:40 ] input[1]: shape = [], value = [ 2019-03-21 16:52:47,805 ] [ DEBUG ] [ infer:165 ] Outputs: [ 2019-03-21 16:52:47,805 ] [ DEBUG ] [ infer:40 ] output[1]: shape = [ 1 512], value = [ 2019-03-21 16:52:47,806 ] [ DEBUG ] [ infer:150 ] -------------------- [ 2019-03-21 16:52:47,806 ] [ DEBUG ] [ infer:151 ] Partial infer for spatial_temporal_network/rnn_net/rnn/while/Identity_4 [ 2019-03-21 16:52:47,806 ] [ DEBUG ] [ infer:152 ] Op: Identity [ 2019-03-21 16:52:47,806 ] [ DEBUG ] [ infer:163 ] Inputs: [ 2019-03-21 16:52:47,807 ] [ DEBUG ] [ infer:40 ] input[0]: shape = [ 1 512], value = [ 2019-03-21 16:52:47,807 ] [ DEBUG ] [ infer:165 ] Outputs: [ 2019-03-21 16:52:47,807 ] [ DEBUG ] [ infer:40 ] output[0]: shape = [ 1 512], value = [ 2019-03-21 16:52:47,808 ] [ DEBUG ] [ infer:150 ] -------------------- [ 2019-03-21 16:52:47,808 ] [ DEBUG ] [ infer:151 ] Partial infer for spatial_temporal_network/rnn_net/rnn/MultiRNNCellZeroState/LSTMCellZeroState/zeros/Const [ 2019-03-21 16:52:47,808 ] [ DEBUG ] [ infer:152 ] Op: Const [ 2019-03-21 16:52:47,808 ] [ DEBUG ] [ infer:163 ] Inputs: [ 2019-03-21 16:52:47,808 ] [ DEBUG ] [ infer:165 ] Outputs: [ 2019-03-21 16:52:47,809 ] [ DEBUG ] [ infer:40 ] output[0]: shape = [], value = 0.0 [ 2019-03-21 16:52:47,809 ] [ DEBUG ] [ infer:150 ] -------------------- [ 2019-03-21 16:52:47,809 ] [ DEBUG ] [ infer:151 ] Partial infer for spatial_temporal_network/rnn_net/rnn/MultiRNNCellZeroState/LSTMCellZeroState/concat/axis [ 2019-03-21 16:52:47,809 ] [ DEBUG ] [ infer:152 ] Op: Const [ 2019-03-21 16:52:47,810 ] [ DEBUG ] [ infer:163 ] Inputs: [ 2019-03-21 16:52:47,810 ] [ DEBUG ] [ infer:165 ] Outputs: [ 2019-03-21 16:52:47,810 ] [ DEBUG ] [ infer:40 ] output[0]: shape = [], value = 0 [ 2019-03-21 16:52:47,810 ] [ DEBUG ] [ infer:150 ] -------------------- [ 2019-03-21 16:52:47,811 ] [ DEBUG ] [ infer:151 ] Partial infer for spatial_temporal_network/rnn_net/rnn/MultiRNNCellZeroState/LSTMCellZeroState/Const_1 [ 2019-03-21 16:52:47,811 ] [ DEBUG ] [ infer:152 ] Op: Const [ 2019-03-21 16:52:47,811 ] [ DEBUG ] [ infer:163 ] Inputs: [ 2019-03-21 16:52:47,811 ] [ DEBUG ] [ infer:165 ] Outputs: [ 2019-03-21 16:52:47,812 ] [ DEBUG ] [ infer:40 ] output[0]: shape = [1], value = [512] [ 2019-03-21 16:52:47,812 ] [ DEBUG ] [ infer:150 ] -------------------- [ 2019-03-21 16:52:47,812 ] [ DEBUG ] [ infer:151 ] Partial infer for spatial_temporal_network/rnn_net/rnn/MultiRNNCellZeroState/LSTMCellZeroState/Const [ 2019-03-21 16:52:47,813 ] [ DEBUG ] [ infer:152 ] Op: Const [ 2019-03-21 16:52:47,813 ] [ DEBUG ] [ infer:163 ] Inputs: [ 2019-03-21 16:52:47,813 ] [ DEBUG ] [ infer:165 ] Outputs: [ 2019-03-21 16:52:47,813 ] [ DEBUG ] [ infer:40 ] output[0]: shape = [1], value = [1] [ 2019-03-21 16:52:47,814 ] [ DEBUG ] [ infer:150 ] -------------------- [ 2019-03-21 16:52:47,814 ] [ DEBUG ] [ infer:151 ] Partial infer for spatial_temporal_network/rnn_net/rnn/MultiRNNCellZeroState/LSTMCellZeroState/concat [ 2019-03-21 16:52:47,814 ] [ DEBUG ] [ infer:152 ] Op: ConcatV2 [ 2019-03-21 16:52:47,815 ] [ DEBUG ] [ infer:163 ] Inputs: [ 2019-03-21 16:52:47,816 ] [ DEBUG ] [ infer:40 ] input[0]: shape = [1], value = [1] [ 2019-03-21 16:52:47,816 ] [ DEBUG ] [ infer:40 ] input[1]: shape = [1], value = [512] [ 2019-03-21 16:52:47,816 ] [ DEBUG ] [ infer:165 ] Outputs: [ 2019-03-21 16:52:47,817 ] [ DEBUG ] [ infer:40 ] output[0]: shape = [2], value = [ 1 512] [ 2019-03-21 16:52:47,817 ] [ DEBUG ] [ infer:150 ] -------------------- [ 2019-03-21 16:52:47,817 ] [ DEBUG ] [ infer:151 ] Partial infer for spatial_temporal_network/rnn_net/rnn/MultiRNNCellZeroState/LSTMCellZeroState/zeros [ 2019-03-21 16:52:47,818 ] [ DEBUG ] [ infer:152 ] Op: Fill [ INFO ] Called "tf_native_tf_node_infer" for node "spatial_temporal_network/rnn_net/rnn/MultiRNNCellZeroState/LSTMCellZeroState/zeros" [ 2019-03-21 16:52:47,821 ] [ DEBUG ] [ tf:222 ] Added placeholder with name 'spatial_temporal_network/rnn_net/rnn/MultiRNNCellZeroState/LSTMCellZeroState/concat_port_0_ie_placeholder' [ 2019-03-21 16:52:47,823 ] [ DEBUG ] [ tf:222 ] Added placeholder with name 'spatial_temporal_network/rnn_net/rnn/MultiRNNCellZeroState/LSTMCellZeroState/zeros/Const_port_0_ie_placeholder' [ 2019-03-21 16:52:47,823 ] [ DEBUG ] [ tf:235 ] update_input_in_pbs: replace input 'spatial_temporal_network/rnn_net/rnn/MultiRNNCellZeroState/LSTMCellZeroState/concat' with input 'spatial_temporal_network/rnn_net/rnn/MultiRNNCellZeroState/LSTMCellZeroState/concat_port_0_ie_placeholder' [ 2019-03-21 16:52:47,823 ] [ DEBUG ] [ tf:243 ] Replacing input '0' of the node 'spatial_temporal_network/rnn_net/rnn/MultiRNNCellZeroState/LSTMCellZeroState/zeros' with placeholder 'spatial_temporal_network/rnn_net/rnn/MultiRNNCellZeroState/LSTMCellZeroState/concat_port_0_ie_placeholder' [ 2019-03-21 16:52:47,823 ] [ DEBUG ] [ tf:235 ] update_input_in_pbs: replace input 'spatial_temporal_network/rnn_net/rnn/MultiRNNCellZeroState/LSTMCellZeroState/zeros/Const' with input 'spatial_temporal_network/rnn_net/rnn/MultiRNNCellZeroState/LSTMCellZeroState/zeros/Const_port_0_ie_placeholder' [ 2019-03-21 16:52:47,823 ] [ DEBUG ] [ tf:243 ] Replacing input '1' of the node 'spatial_temporal_network/rnn_net/rnn/MultiRNNCellZeroState/LSTMCellZeroState/zeros' with placeholder 'spatial_temporal_network/rnn_net/rnn/MultiRNNCellZeroState/LSTMCellZeroState/zeros/Const_port_0_ie_placeholder' [ 2019-03-21 16:52:47,836 ] [ DEBUG ] [ tf:142 ] Inferred shape of the output tensor with index '0' of the node 'spatial_temporal_network/rnn_net/rnn/MultiRNNCellZeroState/LSTMCellZeroState/zeros': '[ 1 512]' [ 2019-03-21 16:52:47,838 ] [ DEBUG ] [ infer:163 ] Inputs: [ 2019-03-21 16:52:47,839 ] [ DEBUG ] [ infer:40 ] input[0]: shape = [2], value = [ 1 512] [ 2019-03-21 16:52:47,839 ] [ DEBUG ] [ infer:40 ] input[1]: shape = [], value = 0.0 [ 2019-03-21 16:52:47,839 ] [ DEBUG ] [ infer:165 ] Outputs: [ 2019-03-21 16:52:47,851 ] [ DEBUG ] [ infer:40 ] output[0]: shape = [ 1 512], value = [[0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. ... [ 2019-03-21 16:52:47,851 ] [ DEBUG ] [ infer:150 ] -------------------- [ 2019-03-21 16:52:47,851 ] [ DEBUG ] [ infer:151 ] Partial infer for spatial_temporal_network/rnn_net/rnn/while/Enter_3 [ 2019-03-21 16:52:47,852 ] [ DEBUG ] [ infer:152 ] Op: Enter [ 2019-03-21 16:52:47,852 ] [ DEBUG ] [ infer:163 ] Inputs: [ 2019-03-21 16:52:47,864 ] [ DEBUG ] [ infer:40 ] input[0]: shape = [ 1 512], value = [[0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. ... [ 2019-03-21 16:52:47,864 ] [ DEBUG ] [ infer:165 ] Outputs: [ 2019-03-21 16:52:47,876 ] [ DEBUG ] [ infer:40 ] output[0]: shape = [ 1 512], value = [[0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. ... [ 2019-03-21 16:52:47,876 ] [ DEBUG ] [ infer:150 ] -------------------- [ 2019-03-21 16:52:47,877 ] [ DEBUG ] [ infer:151 ] Partial infer for spatial_temporal_network/rnn_net/rnn/while/Merge_3 [ 2019-03-21 16:52:47,877 ] [ DEBUG ] [ infer:152 ] Op: Merge [ 2019-03-21 16:52:47,877 ] [ DEBUG ] [ infer:163 ] Inputs: [ 2019-03-21 16:52:47,891 ] [ DEBUG ] [ infer:40 ] input[0]: shape = [ 1 512], value = [[0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. ... [ 2019-03-21 16:52:47,892 ] [ DEBUG ] [ infer:40 ] input[1]: shape = , value = [ 2019-03-21 16:52:47,892 ] [ DEBUG ] [ infer:165 ] Outputs: [ 2019-03-21 16:52:47,893 ] [ DEBUG ] [ infer:40 ] output[0]: shape = [ 1 512], value = [ 2019-03-21 16:52:47,893 ] [ DEBUG ] [ infer:150 ] -------------------- [ 2019-03-21 16:52:47,893 ] [ DEBUG ] [ infer:151 ] Partial infer for spatial_temporal_network/rnn_net/rnn/while/Switch_3 [ 2019-03-21 16:52:47,893 ] [ DEBUG ] [ infer:152 ] Op: Switch [ 2019-03-21 16:52:47,894 ] [ DEBUG ] [ infer:163 ] Inputs: [ 2019-03-21 16:52:47,894 ] [ DEBUG ] [ infer:40 ] input[0]: shape = [ 1 512], value = [ 2019-03-21 16:52:47,895 ] [ DEBUG ] [ infer:40 ] input[1]: shape = [], value = [ 2019-03-21 16:52:47,895 ] [ DEBUG ] [ infer:165 ] Outputs: [ 2019-03-21 16:52:47,895 ] [ DEBUG ] [ infer:40 ] output[1]: shape = [ 1 512], value = [ 2019-03-21 16:52:47,896 ] [ DEBUG ] [ infer:150 ] -------------------- [ 2019-03-21 16:52:47,896 ] [ DEBUG ] [ infer:151 ] Partial infer for spatial_temporal_network/rnn_net/rnn/while/Identity_3 [ 2019-03-21 16:52:47,896 ] [ DEBUG ] [ infer:152 ] Op: Identity [ 2019-03-21 16:52:47,896 ] [ DEBUG ] [ infer:163 ] Inputs: [ 2019-03-21 16:52:47,897 ] [ DEBUG ] [ infer:40 ] input[0]: shape = [ 1 512], value = [ 2019-03-21 16:52:47,897 ] [ DEBUG ] [ infer:165 ] Outputs: [ 2019-03-21 16:52:47,897 ] [ DEBUG ] [ infer:40 ] output[0]: shape = [ 1 512], value = [ 2019-03-21 16:52:47,898 ] [ DEBUG ] [ infer:150 ] -------------------- [ 2019-03-21 16:52:47,898 ] [ DEBUG ] [ infer:151 ] Partial infer for spatial_temporal_network/rnn_net/rnn/concat/axis [ 2019-03-21 16:52:47,898 ] [ DEBUG ] [ infer:152 ] Op: Const [ 2019-03-21 16:52:47,898 ] [ DEBUG ] [ infer:163 ] Inputs: [ 2019-03-21 16:52:47,899 ] [ DEBUG ] [ infer:165 ] Outputs: [ 2019-03-21 16:52:47,899 ] [ DEBUG ] [ infer:40 ] output[0]: shape = [], value = 0 [ 2019-03-21 16:52:47,899 ] [ DEBUG ] [ infer:150 ] -------------------- [ 2019-03-21 16:52:47,899 ] [ DEBUG ] [ infer:151 ] Partial infer for spatial_temporal_network/rnn_net/rnn/concat/values_0 [ 2019-03-21 16:52:47,899 ] [ DEBUG ] [ infer:152 ] Op: Const [ 2019-03-21 16:52:47,900 ] [ DEBUG ] [ infer:163 ] Inputs: [ 2019-03-21 16:52:47,900 ] [ DEBUG ] [ infer:165 ] Outputs: [ 2019-03-21 16:52:47,900 ] [ DEBUG ] [ infer:40 ] output[0]: shape = [2], value = [1 0] [ 2019-03-21 16:52:47,901 ] [ DEBUG ] [ infer:150 ] -------------------- [ 2019-03-21 16:52:47,901 ] [ DEBUG ] [ infer:151 ] Partial infer for spatial_temporal_network/rnn_net/rnn/range/delta [ 2019-03-21 16:52:47,901 ] [ DEBUG ] [ infer:152 ] Op: Const [ 2019-03-21 16:52:47,902 ] [ DEBUG ] [ infer:163 ] Inputs: [ 2019-03-21 16:52:47,902 ] [ DEBUG ] [ infer:165 ] Outputs: [ 2019-03-21 16:52:47,903 ] [ DEBUG ] [ infer:40 ] output[0]: shape = [], value = 1 [ 2019-03-21 16:52:47,903 ] [ DEBUG ] [ infer:150 ] -------------------- [ 2019-03-21 16:52:47,903 ] [ DEBUG ] [ infer:151 ] Partial infer for spatial_temporal_network/rnn_net/rnn/range/start [ 2019-03-21 16:52:47,903 ] [ DEBUG ] [ infer:152 ] Op: Const [ 2019-03-21 16:52:47,904 ] [ DEBUG ] [ infer:163 ] Inputs: [ 2019-03-21 16:52:47,904 ] [ DEBUG ] [ infer:165 ] Outputs: [ 2019-03-21 16:52:47,904 ] [ DEBUG ] [ infer:40 ] output[0]: shape = [], value = 2 [ 2019-03-21 16:52:47,904 ] [ DEBUG ] [ infer:150 ] -------------------- [ 2019-03-21 16:52:47,905 ] [ DEBUG ] [ infer:151 ] Partial infer for spatial_temporal_network/rnn_net/rnn/Rank [ 2019-03-21 16:52:47,905 ] [ DEBUG ] [ infer:152 ] Op: Const [ 2019-03-21 16:52:47,905 ] [ DEBUG ] [ infer:163 ] Inputs: [ 2019-03-21 16:52:47,905 ] [ DEBUG ] [ infer:165 ] Outputs: [ 2019-03-21 16:52:47,906 ] [ DEBUG ] [ infer:40 ] output[0]: shape = [], value = 3 [ 2019-03-21 16:52:47,906 ] [ DEBUG ] [ infer:150 ] -------------------- [ 2019-03-21 16:52:47,906 ] [ DEBUG ] [ infer:151 ] Partial infer for spatial_temporal_network/rnn_net/rnn/range [ 2019-03-21 16:52:47,906 ] [ DEBUG ] [ infer:152 ] Op: Range [ 2019-03-21 16:52:47,907 ] [ DEBUG ] [ infer:163 ] Inputs: [ 2019-03-21 16:52:47,907 ] [ DEBUG ] [ infer:40 ] input[1]: shape = [], value = 3 [ 2019-03-21 16:52:47,907 ] [ DEBUG ] [ infer:40 ] input[0]: shape = [], value = 2 [ 2019-03-21 16:52:47,908 ] [ DEBUG ] [ infer:40 ] input[2]: shape = [], value = 1 [ 2019-03-21 16:52:47,908 ] [ DEBUG ] [ infer:165 ] Outputs: [ 2019-03-21 16:52:47,908 ] [ DEBUG ] [ infer:40 ] output[0]: shape = [1], value = [2] [ 2019-03-21 16:52:47,909 ] [ DEBUG ] [ infer:150 ] -------------------- [ 2019-03-21 16:52:47,909 ] [ DEBUG ] [ infer:151 ] Partial infer for spatial_temporal_network/rnn_net/rnn/concat [ 2019-03-21 16:52:47,909 ] [ DEBUG ] [ infer:152 ] Op: ConcatV2 [ 2019-03-21 16:52:47,910 ] [ DEBUG ] [ infer:163 ] Inputs: [ 2019-03-21 16:52:47,910 ] [ DEBUG ] [ infer:40 ] input[1]: shape = [1], value = [2] [ 2019-03-21 16:52:47,911 ] [ DEBUG ] [ infer:40 ] input[0]: shape = [2], value = [1 0] [ 2019-03-21 16:52:47,911 ] [ DEBUG ] [ infer:165 ] Outputs: [ 2019-03-21 16:52:47,911 ] [ DEBUG ] [ infer:40 ] output[0]: shape = [3], value = [1 0 2] [ 2019-03-21 16:52:47,912 ] [ DEBUG ] [ infer:150 ] -------------------- [ 2019-03-21 16:52:47,912 ] [ DEBUG ] [ infer:151 ] Partial infer for spatial_temporal_network/geo/conblock_3/bn/batchnorm/add/y [ 2019-03-21 16:52:47,912 ] [ DEBUG ] [ infer:152 ] Op: Const [ 2019-03-21 16:52:47,912 ] [ DEBUG ] [ infer:163 ] Inputs: [ 2019-03-21 16:52:47,913 ] [ DEBUG ] [ infer:165 ] Outputs: [ 2019-03-21 16:52:47,913 ] [ DEBUG ] [ infer:40 ] output[0]: shape = [], value = 0.001 [ 2019-03-21 16:52:47,913 ] [ DEBUG ] [ infer:150 ] -------------------- [ 2019-03-21 16:52:47,913 ] [ DEBUG ] [ infer:151 ] Partial infer for spatial_temporal_network/geo/conblock_3/bn/moving_variance [ 2019-03-21 16:52:47,914 ] [ DEBUG ] [ infer:152 ] Op: Const [ 2019-03-21 16:52:47,914 ] [ DEBUG ] [ infer:163 ] Inputs: [ 2019-03-21 16:52:47,914 ] [ DEBUG ] [ infer:165 ] Outputs: [ 2019-03-21 16:52:47,927 ] [ DEBUG ] [ infer:40 ] output[0]: shape = [512], value = [1. 1. 1. 1. 1. 1. 1. 1. 1. 1. 1. 1. 1. 1. 1. 1. 1. 1. 1. 1. 1. 1. 1. 1. 1. 1. 1. 1. 1. 1. 1. 1.... [ 2019-03-21 16:52:47,928 ] [ DEBUG ] [ infer:150 ] -------------------- [ 2019-03-21 16:52:47,928 ] [ DEBUG ] [ infer:151 ] Partial infer for spatial_temporal_network/geo/conblock_3/bn/moving_variance/read [ 2019-03-21 16:52:47,928 ] [ DEBUG ] [ infer:152 ] Op: Identity [ 2019-03-21 16:52:47,929 ] [ DEBUG ] [ infer:163 ] Inputs: [ 2019-03-21 16:52:47,946 ] [ DEBUG ] [ infer:40 ] input[0]: shape = [512], value = [1. 1. 1. 1. 1. 1. 1. 1. 1. 1. 1. 1. 1. 1. 1. 1. 1. 1. 1. 1. 1. 1. 1. 1. 1. 1. 1. 1. 1. 1. 1. 1.... [ 2019-03-21 16:52:47,947 ] [ DEBUG ] [ infer:165 ] Outputs: [ 2019-03-21 16:52:47,958 ] [ DEBUG ] [ infer:40 ] output[0]: shape = [512], value = [1. 1. 1. 1. 1. 1. 1. 1. 1. 1. 1. 1. 1. 1. 1. 1. 1. 1. 1. 1. 1. 1. 1. 1. 1. 1. 1. 1. 1. 1. 1. 1.... [ 2019-03-21 16:52:47,959 ] [ DEBUG ] [ infer:150 ] -------------------- [ 2019-03-21 16:52:47,959 ] [ DEBUG ] [ infer:151 ] Partial infer for spatial_temporal_network/geo/conblock_3/bn/batchnorm/add [ 2019-03-21 16:52:47,959 ] [ DEBUG ] [ infer:152 ] Op: Add [ 2019-03-21 16:52:47,960 ] [ DEBUG ] [ infer:163 ] Inputs: [ 2019-03-21 16:52:47,972 ] [ DEBUG ] [ infer:40 ] input[0]: shape = [512], value = [1. 1. 1. 1. 1. 1. 1. 1. 1. 1. 1. 1. 1. 1. 1. 1. 1. 1. 1. 1. 1. 1. 1. 1. 1. 1. 1. 1. 1. 1. 1. 1.... [ 2019-03-21 16:52:47,972 ] [ DEBUG ] [ infer:40 ] input[1]: shape = [], value = 0.001 [ 2019-03-21 16:52:47,973 ] [ DEBUG ] [ infer:165 ] Outputs: [ 2019-03-21 16:52:47,984 ] [ DEBUG ] [ infer:40 ] output[0]: shape = [512], value = [1.001 1.001 1.001 1.001 1.001 1.001 1.001 1.001 1.001 1.001 1.001 1.001 1.001 1.001 1.001 1.001... [ 2019-03-21 16:52:47,985 ] [ DEBUG ] [ infer:150 ] -------------------- [ 2019-03-21 16:52:47,985 ] [ DEBUG ] [ infer:151 ] Partial infer for spatial_temporal_network/geo/conblock_3/bn/batchnorm/Rsqrt [ 2019-03-21 16:52:47,985 ] [ DEBUG ] [ infer:152 ] Op: Rsqrt [ 2019-03-21 16:52:47,986 ] [ DEBUG ] [ infer:163 ] Inputs: [ 2019-03-21 16:52:47,998 ] [ DEBUG ] [ infer:40 ] input[0]: shape = [512], value = [1.001 1.001 1.001 1.001 1.001 1.001 1.001 1.001 1.001 1.001 1.001 1.001 1.001 1.001 1.001 1.001... [ 2019-03-21 16:52:47,999 ] [ DEBUG ] [ infer:165 ] Outputs: [ 2019-03-21 16:52:48,012 ] [ DEBUG ] [ infer:40 ] output[0]: shape = [512], value = [0.9995004 0.9995004 0.9995004 0.9995004 0.9995004 0.9995004 0.9995004 0.9995004 0.9995004 0.999... [ 2019-03-21 16:52:48,012 ] [ DEBUG ] [ infer:150 ] -------------------- [ 2019-03-21 16:52:48,012 ] [ DEBUG ] [ infer:151 ] Partial infer for spatial_temporal_network/geo/conblock_3/bn/moving_mean [ 2019-03-21 16:52:48,013 ] [ DEBUG ] [ infer:152 ] Op: Const [ 2019-03-21 16:52:48,013 ] [ DEBUG ] [ infer:163 ] Inputs: [ 2019-03-21 16:52:48,013 ] [ DEBUG ] [ infer:165 ] Outputs: [ 2019-03-21 16:52:48,025 ] [ DEBUG ] [ infer:40 ] output[0]: shape = [512], value = [0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0.... [ 2019-03-21 16:52:48,025 ] [ DEBUG ] [ infer:150 ] -------------------- [ 2019-03-21 16:52:48,025 ] [ DEBUG ] [ infer:151 ] Partial infer for spatial_temporal_network/geo/conblock_3/bn/moving_mean/read [ 2019-03-21 16:52:48,026 ] [ DEBUG ] [ infer:152 ] Op: Identity [ 2019-03-21 16:52:48,026 ] [ DEBUG ] [ infer:163 ] Inputs: [ 2019-03-21 16:52:48,038 ] [ DEBUG ] [ infer:40 ] input[0]: shape = [512], value = [0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0.... [ 2019-03-21 16:52:48,038 ] [ DEBUG ] [ infer:165 ] Outputs: [ 2019-03-21 16:52:48,050 ] [ DEBUG ] [ infer:40 ] output[0]: shape = [512], value = [0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0.... [ 2019-03-21 16:52:48,051 ] [ DEBUG ] [ infer:150 ] -------------------- [ 2019-03-21 16:52:48,051 ] [ DEBUG ] [ infer:151 ] Partial infer for spatial_temporal_network/geo/conblock_3/bn/beta [ 2019-03-21 16:52:48,051 ] [ DEBUG ] [ infer:152 ] Op: Const [ 2019-03-21 16:52:48,051 ] [ DEBUG ] [ infer:163 ] Inputs: [ 2019-03-21 16:52:48,051 ] [ DEBUG ] [ infer:165 ] Outputs: [ 2019-03-21 16:52:48,065 ] [ DEBUG ] [ infer:40 ] output[0]: shape = [512], value = [-7.80042727e-04 -7.66557734e-03 2.13933340e-03 -1.08347991e-02 -3.28366039e-03 -1.10146878e-02... [ 2019-03-21 16:52:48,065 ] [ DEBUG ] [ infer:150 ] -------------------- [ 2019-03-21 16:52:48,065 ] [ DEBUG ] [ infer:151 ] Partial infer for spatial_temporal_network/geo/conblock_3/bn/beta/read [ 2019-03-21 16:52:48,065 ] [ DEBUG ] [ infer:152 ] Op: Identity [ 2019-03-21 16:52:48,066 ] [ DEBUG ] [ infer:163 ] Inputs: [ 2019-03-21 16:52:48,080 ] [ DEBUG ] [ infer:40 ] input[0]: shape = [512], value = [-7.80042727e-04 -7.66557734e-03 2.13933340e-03 -1.08347991e-02 -3.28366039e-03 -1.10146878e-02... [ 2019-03-21 16:52:48,080 ] [ DEBUG ] [ infer:165 ] Outputs: [ 2019-03-21 16:52:48,093 ] [ DEBUG ] [ infer:40 ] output[0]: shape = [512], value = [-7.80042727e-04 -7.66557734e-03 2.13933340e-03 -1.08347991e-02 -3.28366039e-03 -1.10146878e-02... [ 2019-03-21 16:52:48,094 ] [ DEBUG ] [ infer:150 ] -------------------- [ 2019-03-21 16:52:48,094 ] [ DEBUG ] [ infer:151 ] Partial infer for spatial_temporal_network/geo/conblock_3/bn/gamma [ 2019-03-21 16:52:48,094 ] [ DEBUG ] [ infer:152 ] Op: Const [ 2019-03-21 16:52:48,095 ] [ DEBUG ] [ infer:163 ] Inputs: [ 2019-03-21 16:52:48,095 ] [ DEBUG ] [ infer:165 ] Outputs: [ 2019-03-21 16:52:48,108 ] [ DEBUG ] [ infer:40 ] output[0]: shape = [512], value = [1.007963 1.0060503 1.0073595 1.0039784 1.0015347 1.0157379 1.0070839 1.0236577 0.999778... [ 2019-03-21 16:52:48,108 ] [ DEBUG ] [ infer:150 ] -------------------- [ 2019-03-21 16:52:48,109 ] [ DEBUG ] [ infer:151 ] Partial infer for spatial_temporal_network/geo/conblock_3/bn/gamma/read [ 2019-03-21 16:52:48,109 ] [ DEBUG ] [ infer:152 ] Op: Identity [ 2019-03-21 16:52:48,109 ] [ DEBUG ] [ infer:163 ] Inputs: [ 2019-03-21 16:52:48,122 ] [ DEBUG ] [ infer:40 ] input[0]: shape = [512], value = [1.007963 1.0060503 1.0073595 1.0039784 1.0015347 1.0157379 1.0070839 1.0236577 0.999778... [ 2019-03-21 16:52:48,122 ] [ DEBUG ] [ infer:165 ] Outputs: [ 2019-03-21 16:52:48,135 ] [ DEBUG ] [ infer:40 ] output[0]: shape = [512], value = [1.007963 1.0060503 1.0073595 1.0039784 1.0015347 1.0157379 1.0070839 1.0236577 0.999778... [ 2019-03-21 16:52:48,136 ] [ DEBUG ] [ infer:150 ] -------------------- [ 2019-03-21 16:52:48,136 ] [ DEBUG ] [ infer:151 ] Partial infer for spatial_temporal_network/geo/conblock_3/bn/batchnorm/mul [ 2019-03-21 16:52:48,136 ] [ DEBUG ] [ infer:152 ] Op: Mul [ 2019-03-21 16:52:48,137 ] [ DEBUG ] [ infer:163 ] Inputs: [ 2019-03-21 16:52:48,149 ] [ DEBUG ] [ infer:40 ] input[1]: shape = [512], value = [1.007963 1.0060503 1.0073595 1.0039784 1.0015347 1.0157379 1.0070839 1.0236577 0.999778... [ 2019-03-21 16:52:48,163 ] [ DEBUG ] [ infer:40 ] input[0]: shape = [512], value = [0.9995004 0.9995004 0.9995004 0.9995004 0.9995004 0.9995004 0.9995004 0.9995004 0.9995004 0.999... [ 2019-03-21 16:52:48,163 ] [ DEBUG ] [ infer:165 ] Outputs: [ 2019-03-21 16:52:48,176 ] [ DEBUG ] [ infer:40 ] output[0]: shape = [512], value = [1.0074594 1.0055478 1.0068562 1.0034767 1.0010344 1.0152304 1.0065807 1.0231463 0.999278... [ 2019-03-21 16:52:48,177 ] [ DEBUG ] [ infer:150 ] -------------------- [ 2019-03-21 16:52:48,177 ] [ DEBUG ] [ infer:151 ] Partial infer for spatial_temporal_network/geo/conblock_3/bn/batchnorm/mul_2 [ 2019-03-21 16:52:48,177 ] [ DEBUG ] [ infer:152 ] Op: Mul [ 2019-03-21 16:52:48,178 ] [ DEBUG ] [ infer:163 ] Inputs: [ 2019-03-21 16:52:48,190 ] [ DEBUG ] [ infer:40 ] input[0]: shape = [512], value = [0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0.... [ 2019-03-21 16:52:48,202 ] [ DEBUG ] [ infer:40 ] input[1]: shape = [512], value = [1.0074594 1.0055478 1.0068562 1.0034767 1.0010344 1.0152304 1.0065807 1.0231463 0.999278... [ 2019-03-21 16:52:48,203 ] [ DEBUG ] [ infer:165 ] Outputs: [ 2019-03-21 16:52:48,214 ] [ DEBUG ] [ infer:40 ] output[0]: shape = [512], value = [0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0.... [ 2019-03-21 16:52:48,215 ] [ DEBUG ] [ infer:150 ] -------------------- [ 2019-03-21 16:52:48,215 ] [ DEBUG ] [ infer:151 ] Partial infer for spatial_temporal_network/geo/conblock_3/bn/batchnorm/sub/negate_ [ 2019-03-21 16:52:48,215 ] [ DEBUG ] [ infer:152 ] Op: Power [ 2019-03-21 16:52:48,216 ] [ DEBUG ] [ infer:163 ] Inputs: [ 2019-03-21 16:52:48,227 ] [ DEBUG ] [ infer:40 ] input[0]: shape = [512], value = [0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0.... [ 2019-03-21 16:52:48,227 ] [ DEBUG ] [ infer:165 ] Outputs: [ 2019-03-21 16:52:48,240 ] [ DEBUG ] [ infer:40 ] output[0]: shape = [512], value = [0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0.... [ 2019-03-21 16:52:48,240 ] [ DEBUG ] [ infer:150 ] -------------------- [ 2019-03-21 16:52:48,241 ] [ DEBUG ] [ infer:151 ] Partial infer for spatial_temporal_network/geo/conblock_3/bn/batchnorm/sub/add_ [ 2019-03-21 16:52:48,241 ] [ DEBUG ] [ infer:152 ] Op: Add [ 2019-03-21 16:52:48,241 ] [ DEBUG ] [ infer:163 ] Inputs: [ 2019-03-21 16:52:48,255 ] [ DEBUG ] [ infer:40 ] input[0]: shape = [512], value = [-7.80042727e-04 -7.66557734e-03 2.13933340e-03 -1.08347991e-02 -3.28366039e-03 -1.10146878e-02... [ 2019-03-21 16:52:48,266 ] [ DEBUG ] [ infer:40 ] input[1]: shape = [512], value = [0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0.... [ 2019-03-21 16:52:48,267 ] [ DEBUG ] [ infer:165 ] Outputs: [ 2019-03-21 16:52:48,280 ] [ DEBUG ] [ infer:40 ] output[0]: shape = [512], value = [-7.80042727e-04 -7.66557734e-03 2.13933340e-03 -1.08347991e-02 -3.28366039e-03 -1.10146878e-02... [ 2019-03-21 16:52:48,281 ] [ DEBUG ] [ infer:150 ] -------------------- [ 2019-03-21 16:52:48,281 ] [ DEBUG ] [ infer:151 ] Partial infer for spatial_temporal_network/geo/conblock_3/cov/conv1d/ExpandDims_1/dim [ 2019-03-21 16:52:48,281 ] [ DEBUG ] [ infer:152 ] Op: Const [ 2019-03-21 16:52:48,281 ] [ DEBUG ] [ infer:163 ] Inputs: [ 2019-03-21 16:52:48,282 ] [ DEBUG ] [ infer:165 ] Outputs: [ 2019-03-21 16:52:48,282 ] [ DEBUG ] [ infer:40 ] output[0]: shape = [], value = 0 [ 2019-03-21 16:52:48,282 ] [ DEBUG ] [ infer:150 ] -------------------- [ 2019-03-21 16:52:48,283 ] [ DEBUG ] [ infer:151 ] Partial infer for spatial_temporal_network/geo/conblock_3/cov/conv1d/ExpandDims/dim [ 2019-03-21 16:52:48,283 ] [ DEBUG ] [ infer:152 ] Op: Const [ 2019-03-21 16:52:48,283 ] [ DEBUG ] [ infer:163 ] Inputs: [ 2019-03-21 16:52:48,283 ] [ DEBUG ] [ infer:165 ] Outputs: [ 2019-03-21 16:52:48,283 ] [ DEBUG ] [ infer:40 ] output[0]: shape = [], value = 1 [ 2019-03-21 16:52:48,284 ] [ DEBUG ] [ infer:150 ] -------------------- [ 2019-03-21 16:52:48,284 ] [ DEBUG ] [ infer:151 ] Partial infer for spatial_temporal_network/geo/conblock_3/cov/bias [ 2019-03-21 16:52:48,284 ] [ DEBUG ] [ infer:152 ] Op: Const [ 2019-03-21 16:52:48,285 ] [ DEBUG ] [ infer:163 ] Inputs: [ 2019-03-21 16:52:48,285 ] [ DEBUG ] [ infer:165 ] Outputs: [ 2019-03-21 16:52:48,299 ] [ DEBUG ] [ infer:40 ] output[0]: shape = [512], value = [-8.40652036e-04 -7.68809207e-03 2.11746455e-03 -1.09434035e-02 -3.32584139e-03 -1.10903960e-02... [ 2019-03-21 16:52:48,299 ] [ DEBUG ] [ infer:150 ] -------------------- [ 2019-03-21 16:52:48,300 ] [ DEBUG ] [ infer:151 ] Partial infer for spatial_temporal_network/geo/conblock_3/cov/bias/read [ 2019-03-21 16:52:48,300 ] [ DEBUG ] [ infer:152 ] Op: Identity [ 2019-03-21 16:52:48,300 ] [ DEBUG ] [ infer:163 ] Inputs: [ 2019-03-21 16:52:48,314 ] [ DEBUG ] [ infer:40 ] input[0]: shape = [512], value = [-8.40652036e-04 -7.68809207e-03 2.11746455e-03 -1.09434035e-02 -3.32584139e-03 -1.10903960e-02... [ 2019-03-21 16:52:48,314 ] [ DEBUG ] [ infer:165 ] Outputs: [ 2019-03-21 16:52:48,327 ] [ DEBUG ] [ infer:40 ] output[0]: shape = [512], value = [-8.40652036e-04 -7.68809207e-03 2.11746455e-03 -1.09434035e-02 -3.32584139e-03 -1.10903960e-02... [ 2019-03-21 16:52:48,328 ] [ DEBUG ] [ infer:150 ] -------------------- [ 2019-03-21 16:52:48,328 ] [ DEBUG ] [ infer:151 ] Partial infer for spatial_temporal_network/geo/conblock_3/cov/kernel [ 2019-03-21 16:52:48,328 ] [ DEBUG ] [ infer:152 ] Op: Const [ 2019-03-21 16:52:48,328 ] [ DEBUG ] [ infer:163 ] Inputs: [ 2019-03-21 16:52:48,329 ] [ DEBUG ] [ infer:165 ] Outputs: [ 2019-03-21 16:52:48,333 ] [ DEBUG ] [ infer:40 ] output[0]: shape = [ 3 512 512], value = [[[ 7.0989966e-02 -5.0314654e-02 -6.5823540e-02 ... -2.6750781e-03 2.6358338e-02 -2.6148457e-... [ 2019-03-21 16:52:48,333 ] [ DEBUG ] [ infer:150 ] -------------------- [ 2019-03-21 16:52:48,334 ] [ DEBUG ] [ infer:151 ] Partial infer for spatial_temporal_network/geo/conblock_3/cov/kernel/read [ 2019-03-21 16:52:48,334 ] [ DEBUG ] [ infer:152 ] Op: Identity [ 2019-03-21 16:52:48,334 ] [ DEBUG ] [ infer:163 ] Inputs: [ 2019-03-21 16:52:48,338 ] [ DEBUG ] [ infer:40 ] input[0]: shape = [ 3 512 512], value = [[[ 7.0989966e-02 -5.0314654e-02 -6.5823540e-02 ... -2.6750781e-03 2.6358338e-02 -2.6148457e-... [ 2019-03-21 16:52:48,338 ] [ DEBUG ] [ infer:165 ] Outputs: [ 2019-03-21 16:52:48,342 ] [ DEBUG ] [ infer:40 ] output[0]: shape = [ 3 512 512], value = [[[ 7.0989966e-02 -5.0314654e-02 -6.5823540e-02 ... -2.6750781e-03 2.6358338e-02 -2.6148457e-... [ 2019-03-21 16:52:48,342 ] [ DEBUG ] [ infer:150 ] -------------------- [ 2019-03-21 16:52:48,342 ] [ DEBUG ] [ infer:151 ] Partial infer for spatial_temporal_network/geo/conblock_3/cov/conv1d/ExpandDims_1 [ 2019-03-21 16:52:48,342 ] [ DEBUG ] [ infer:152 ] Op: ExpandDims [ 2019-03-21 16:52:48,344 ] [ DEBUG ] [ infer:163 ] Inputs: [ 2019-03-21 16:52:48,348 ] [ DEBUG ] [ infer:40 ] input[0]: shape = [ 3 512 512], value = [[[ 7.0989966e-02 -5.0314654e-02 -6.5823540e-02 ... -2.6750781e-03 2.6358338e-02 -2.6148457e-... [ 2019-03-21 16:52:48,349 ] [ DEBUG ] [ infer:165 ] Outputs: [ 2019-03-21 16:52:48,352 ] [ DEBUG ] [ infer:40 ] output[0]: shape = [ 1 3 512 512], value = [[[[ 7.0989966e-02 -5.0314654e-02 -6.5823540e-02 ... -2.6750781e-03 2.6358338e-02 -2.6148457... [ 2019-03-21 16:52:48,352 ] [ DEBUG ] [ infer:150 ] -------------------- [ 2019-03-21 16:52:48,353 ] [ DEBUG ] [ infer:151 ] Partial infer for spatial_temporal_network/geo/conblock_2/bn/batchnorm/add/y [ 2019-03-21 16:52:48,353 ] [ DEBUG ] [ infer:152 ] Op: Const [ 2019-03-21 16:52:48,353 ] [ DEBUG ] [ infer:163 ] Inputs: [ 2019-03-21 16:52:48,353 ] [ DEBUG ] [ infer:165 ] Outputs: [ 2019-03-21 16:52:48,354 ] [ DEBUG ] [ infer:40 ] output[0]: shape = [], value = 0.001 [ 2019-03-21 16:52:48,354 ] [ DEBUG ] [ infer:150 ] -------------------- [ 2019-03-21 16:52:48,354 ] [ DEBUG ] [ infer:151 ] Partial infer for spatial_temporal_network/geo/conblock_2/bn/moving_variance [ 2019-03-21 16:52:48,354 ] [ DEBUG ] [ infer:152 ] Op: Const [ 2019-03-21 16:52:48,355 ] [ DEBUG ] [ infer:163 ] Inputs: [ 2019-03-21 16:52:48,355 ] [ DEBUG ] [ infer:165 ] Outputs: [ 2019-03-21 16:52:48,367 ] [ DEBUG ] [ infer:40 ] output[0]: shape = [512], value = [1. 1. 1. 1. 1. 1. 1. 1. 1. 1. 1. 1. 1. 1. 1. 1. 1. 1. 1. 1. 1. 1. 1. 1. 1. 1. 1. 1. 1. 1. 1. 1.... [ 2019-03-21 16:52:48,367 ] [ DEBUG ] [ infer:150 ] -------------------- [ 2019-03-21 16:52:48,368 ] [ DEBUG ] [ infer:151 ] Partial infer for spatial_temporal_network/geo/conblock_2/bn/moving_variance/read [ 2019-03-21 16:52:48,368 ] [ DEBUG ] [ infer:152 ] Op: Identity [ 2019-03-21 16:52:48,368 ] [ DEBUG ] [ infer:163 ] Inputs: [ 2019-03-21 16:52:48,379 ] [ DEBUG ] [ infer:40 ] input[0]: shape = [512], value = [1. 1. 1. 1. 1. 1. 1. 1. 1. 1. 1. 1. 1. 1. 1. 1. 1. 1. 1. 1. 1. 1. 1. 1. 1. 1. 1. 1. 1. 1. 1. 1.... [ 2019-03-21 16:52:48,380 ] [ DEBUG ] [ infer:165 ] Outputs: [ 2019-03-21 16:52:48,392 ] [ DEBUG ] [ infer:40 ] output[0]: shape = [512], value = [1. 1. 1. 1. 1. 1. 1. 1. 1. 1. 1. 1. 1. 1. 1. 1. 1. 1. 1. 1. 1. 1. 1. 1. 1. 1. 1. 1. 1. 1. 1. 1.... [ 2019-03-21 16:52:48,393 ] [ DEBUG ] [ infer:150 ] -------------------- [ 2019-03-21 16:52:48,393 ] [ DEBUG ] [ infer:151 ] Partial infer for spatial_temporal_network/geo/conblock_2/bn/batchnorm/add [ 2019-03-21 16:52:48,393 ] [ DEBUG ] [ infer:152 ] Op: Add [ 2019-03-21 16:52:48,394 ] [ DEBUG ] [ infer:163 ] Inputs: [ 2019-03-21 16:52:48,407 ] [ DEBUG ] [ infer:40 ] input[0]: shape = [512], value = [1. 1. 1. 1. 1. 1. 1. 1. 1. 1. 1. 1. 1. 1. 1. 1. 1. 1. 1. 1. 1. 1. 1. 1. 1. 1. 1. 1. 1. 1. 1. 1.... [ 2019-03-21 16:52:48,408 ] [ DEBUG ] [ infer:40 ] input[1]: shape = [], value = 0.001 [ 2019-03-21 16:52:48,408 ] [ DEBUG ] [ infer:165 ] Outputs: [ 2019-03-21 16:52:48,420 ] [ DEBUG ] [ infer:40 ] output[0]: shape = [512], value = [1.001 1.001 1.001 1.001 1.001 1.001 1.001 1.001 1.001 1.001 1.001 1.001 1.001 1.001 1.001 1.001... [ 2019-03-21 16:52:48,420 ] [ DEBUG ] [ infer:150 ] -------------------- [ 2019-03-21 16:52:48,420 ] [ DEBUG ] [ infer:151 ] Partial infer for spatial_temporal_network/geo/conblock_2/bn/batchnorm/Rsqrt [ 2019-03-21 16:52:48,420 ] [ DEBUG ] [ infer:152 ] Op: Rsqrt [ 2019-03-21 16:52:48,421 ] [ DEBUG ] [ infer:163 ] Inputs: [ 2019-03-21 16:52:48,433 ] [ DEBUG ] [ infer:40 ] input[0]: shape = [512], value = [1.001 1.001 1.001 1.001 1.001 1.001 1.001 1.001 1.001 1.001 1.001 1.001 1.001 1.001 1.001 1.001... [ 2019-03-21 16:52:48,433 ] [ DEBUG ] [ infer:165 ] Outputs: [ 2019-03-21 16:52:48,446 ] [ DEBUG ] [ infer:40 ] output[0]: shape = [512], value = [0.9995004 0.9995004 0.9995004 0.9995004 0.9995004 0.9995004 0.9995004 0.9995004 0.9995004 0.999... [ 2019-03-21 16:52:48,447 ] [ DEBUG ] [ infer:150 ] -------------------- [ 2019-03-21 16:52:48,447 ] [ DEBUG ] [ infer:151 ] Partial infer for spatial_temporal_network/geo/conblock_2/bn/moving_mean [ 2019-03-21 16:52:48,447 ] [ DEBUG ] [ infer:152 ] Op: Const [ 2019-03-21 16:52:48,447 ] [ DEBUG ] [ infer:163 ] Inputs: [ 2019-03-21 16:52:48,447 ] [ DEBUG ] [ infer:165 ] Outputs: [ 2019-03-21 16:52:48,459 ] [ DEBUG ] [ infer:40 ] output[0]: shape = [512], value = [0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0.... [ 2019-03-21 16:52:48,460 ] [ DEBUG ] [ infer:150 ] -------------------- [ 2019-03-21 16:52:48,460 ] [ DEBUG ] [ infer:151 ] Partial infer for spatial_temporal_network/geo/conblock_2/bn/moving_mean/read [ 2019-03-21 16:52:48,460 ] [ DEBUG ] [ infer:152 ] Op: Identity [ 2019-03-21 16:52:48,460 ] [ DEBUG ] [ infer:163 ] Inputs: [ 2019-03-21 16:52:48,471 ] [ DEBUG ] [ infer:40 ] input[0]: shape = [512], value = [0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0.... [ 2019-03-21 16:52:48,471 ] [ DEBUG ] [ infer:165 ] Outputs: [ 2019-03-21 16:52:48,483 ] [ DEBUG ] [ infer:40 ] output[0]: shape = [512], value = [0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0.... [ 2019-03-21 16:52:48,484 ] [ DEBUG ] [ infer:150 ] -------------------- [ 2019-03-21 16:52:48,484 ] [ DEBUG ] [ infer:151 ] Partial infer for spatial_temporal_network/geo/conblock_2/bn/beta [ 2019-03-21 16:52:48,484 ] [ DEBUG ] [ infer:152 ] Op: Const [ 2019-03-21 16:52:48,484 ] [ DEBUG ] [ infer:163 ] Inputs: [ 2019-03-21 16:52:48,485 ] [ DEBUG ] [ infer:165 ] Outputs: [ 2019-03-21 16:52:48,498 ] [ DEBUG ] [ infer:40 ] output[0]: shape = [512], value = [ 1.1206801e-03 -2.3367635e-03 -7.1355500e-03 -2.4223847e-03 3.8753857e-03 -3.6522618e-03 -1.96... [ 2019-03-21 16:52:48,499 ] [ DEBUG ] [ infer:150 ] -------------------- [ 2019-03-21 16:52:48,499 ] [ DEBUG ] [ infer:151 ] Partial infer for spatial_temporal_network/geo/conblock_2/bn/beta/read [ 2019-03-21 16:52:48,499 ] [ DEBUG ] [ infer:152 ] Op: Identity [ 2019-03-21 16:52:48,500 ] [ DEBUG ] [ infer:163 ] Inputs: [ 2019-03-21 16:52:48,513 ] [ DEBUG ] [ infer:40 ] input[0]: shape = [512], value = [ 1.1206801e-03 -2.3367635e-03 -7.1355500e-03 -2.4223847e-03 3.8753857e-03 -3.6522618e-03 -1.96... [ 2019-03-21 16:52:48,514 ] [ DEBUG ] [ infer:165 ] Outputs: [ 2019-03-21 16:52:48,526 ] [ DEBUG ] [ infer:40 ] output[0]: shape = [512], value = [ 1.1206801e-03 -2.3367635e-03 -7.1355500e-03 -2.4223847e-03 3.8753857e-03 -3.6522618e-03 -1.96... [ 2019-03-21 16:52:48,527 ] [ DEBUG ] [ infer:150 ] -------------------- [ 2019-03-21 16:52:48,527 ] [ DEBUG ] [ infer:151 ] Partial infer for spatial_temporal_network/geo/conblock_2/bn/gamma [ 2019-03-21 16:52:48,527 ] [ DEBUG ] [ infer:152 ] Op: Const [ 2019-03-21 16:52:48,528 ] [ DEBUG ] [ infer:163 ] Inputs: [ 2019-03-21 16:52:48,528 ] [ DEBUG ] [ infer:165 ] Outputs: [ 2019-03-21 16:52:48,541 ] [ DEBUG ] [ infer:40 ] output[0]: shape = [512], value = [1.0004603 1.002532 1.0017502 1.0052316 1.0066941 1.0020176 0.999534 1.0097615 1.009179... [ 2019-03-21 16:52:48,541 ] [ DEBUG ] [ infer:150 ] -------------------- [ 2019-03-21 16:52:48,541 ] [ DEBUG ] [ infer:151 ] Partial infer for spatial_temporal_network/geo/conblock_2/bn/gamma/read [ 2019-03-21 16:52:48,541 ] [ DEBUG ] [ infer:152 ] Op: Identity [ 2019-03-21 16:52:48,542 ] [ DEBUG ] [ infer:163 ] Inputs: [ 2019-03-21 16:52:48,555 ] [ DEBUG ] [ infer:40 ] input[0]: shape = [512], value = [1.0004603 1.002532 1.0017502 1.0052316 1.0066941 1.0020176 0.999534 1.0097615 1.009179... [ 2019-03-21 16:52:48,555 ] [ DEBUG ] [ infer:165 ] Outputs: [ 2019-03-21 16:52:48,568 ] [ DEBUG ] [ infer:40 ] output[0]: shape = [512], value = [1.0004603 1.002532 1.0017502 1.0052316 1.0066941 1.0020176 0.999534 1.0097615 1.009179... [ 2019-03-21 16:52:48,568 ] [ DEBUG ] [ infer:150 ] -------------------- [ 2019-03-21 16:52:48,568 ] [ DEBUG ] [ infer:151 ] Partial infer for spatial_temporal_network/geo/conblock_2/bn/batchnorm/mul [ 2019-03-21 16:52:48,569 ] [ DEBUG ] [ infer:152 ] Op: Mul [ 2019-03-21 16:52:48,569 ] [ DEBUG ] [ infer:163 ] Inputs: [ 2019-03-21 16:52:48,581 ] [ DEBUG ] [ infer:40 ] input[1]: shape = [512], value = [1.0004603 1.002532 1.0017502 1.0052316 1.0066941 1.0020176 0.999534 1.0097615 1.009179... [ 2019-03-21 16:52:48,594 ] [ DEBUG ] [ infer:40 ] input[0]: shape = [512], value = [0.9995004 0.9995004 0.9995004 0.9995004 0.9995004 0.9995004 0.9995004 0.9995004 0.9995004 0.999... [ 2019-03-21 16:52:48,594 ] [ DEBUG ] [ infer:165 ] Outputs: [ 2019-03-21 16:52:48,606 ] [ DEBUG ] [ infer:40 ] output[0]: shape = [512], value = [0.9999604 1.0020311 1.0012498 1.0047294 1.0061911 1.001517 0.99903464 1.009257 1.0086752... [ 2019-03-21 16:52:48,607 ] [ DEBUG ] [ infer:150 ] -------------------- [ 2019-03-21 16:52:48,607 ] [ DEBUG ] [ infer:151 ] Partial infer for spatial_temporal_network/geo/conblock_2/bn/batchnorm/mul_2 [ 2019-03-21 16:52:48,607 ] [ DEBUG ] [ infer:152 ] Op: Mul [ 2019-03-21 16:52:48,607 ] [ DEBUG ] [ infer:163 ] Inputs: [ 2019-03-21 16:52:48,619 ] [ DEBUG ] [ infer:40 ] input[0]: shape = [512], value = [0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0.... [ 2019-03-21 16:52:48,631 ] [ DEBUG ] [ infer:40 ] input[1]: shape = [512], value = [0.9999604 1.0020311 1.0012498 1.0047294 1.0061911 1.001517 0.99903464 1.009257 1.0086752... [ 2019-03-21 16:52:48,631 ] [ DEBUG ] [ infer:165 ] Outputs: [ 2019-03-21 16:52:48,643 ] [ DEBUG ] [ infer:40 ] output[0]: shape = [512], value = [0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0.... [ 2019-03-21 16:52:48,643 ] [ DEBUG ] [ infer:150 ] -------------------- [ 2019-03-21 16:52:48,643 ] [ DEBUG ] [ infer:151 ] Partial infer for spatial_temporal_network/geo/conblock_2/bn/batchnorm/sub/negate_ [ 2019-03-21 16:52:48,643 ] [ DEBUG ] [ infer:152 ] Op: Power [ 2019-03-21 16:52:48,645 ] [ DEBUG ] [ infer:163 ] Inputs: [ 2019-03-21 16:52:48,658 ] [ DEBUG ] [ infer:40 ] input[0]: shape = [512], value = [0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0.... [ 2019-03-21 16:52:48,658 ] [ DEBUG ] [ infer:165 ] Outputs: [ 2019-03-21 16:52:48,670 ] [ DEBUG ] [ infer:40 ] output[0]: shape = [512], value = [0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0.... [ 2019-03-21 16:52:48,670 ] [ DEBUG ] [ infer:150 ] -------------------- [ 2019-03-21 16:52:48,671 ] [ DEBUG ] [ infer:151 ] Partial infer for spatial_temporal_network/geo/conblock_2/bn/batchnorm/sub/add_ [ 2019-03-21 16:52:48,671 ] [ DEBUG ] [ infer:152 ] Op: Add [ 2019-03-21 16:52:48,671 ] [ DEBUG ] [ infer:163 ] Inputs: [ 2019-03-21 16:52:48,685 ] [ DEBUG ] [ infer:40 ] input[0]: shape = [512], value = [ 1.1206801e-03 -2.3367635e-03 -7.1355500e-03 -2.4223847e-03 3.8753857e-03 -3.6522618e-03 -1.96... [ 2019-03-21 16:52:48,697 ] [ DEBUG ] [ infer:40 ] input[1]: shape = [512], value = [0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0.... [ 2019-03-21 16:52:48,697 ] [ DEBUG ] [ infer:165 ] Outputs: [ 2019-03-21 16:52:48,711 ] [ DEBUG ] [ infer:40 ] output[0]: shape = [512], value = [ 1.1206801e-03 -2.3367635e-03 -7.1355500e-03 -2.4223847e-03 3.8753857e-03 -3.6522618e-03 -1.96... [ 2019-03-21 16:52:48,712 ] [ DEBUG ] [ infer:150 ] -------------------- [ 2019-03-21 16:52:48,712 ] [ DEBUG ] [ infer:151 ] Partial infer for spatial_temporal_network/geo/conblock_2/cov/conv1d/ExpandDims_1/dim [ 2019-03-21 16:52:48,712 ] [ DEBUG ] [ infer:152 ] Op: Const [ 2019-03-21 16:52:48,712 ] [ DEBUG ] [ infer:163 ] Inputs: [ 2019-03-21 16:52:48,712 ] [ DEBUG ] [ infer:165 ] Outputs: [ 2019-03-21 16:52:48,713 ] [ DEBUG ] [ infer:40 ] output[0]: shape = [], value = 0 [ 2019-03-21 16:52:48,713 ] [ DEBUG ] [ infer:150 ] -------------------- [ 2019-03-21 16:52:48,713 ] [ DEBUG ] [ infer:151 ] Partial infer for spatial_temporal_network/geo/conblock_2/cov/conv1d/ExpandDims/dim [ 2019-03-21 16:52:48,713 ] [ DEBUG ] [ infer:152 ] Op: Const [ 2019-03-21 16:52:48,714 ] [ DEBUG ] [ infer:163 ] Inputs: [ 2019-03-21 16:52:48,714 ] [ DEBUG ] [ infer:165 ] Outputs: [ 2019-03-21 16:52:48,714 ] [ DEBUG ] [ infer:40 ] output[0]: shape = [], value = 1 [ 2019-03-21 16:52:48,715 ] [ DEBUG ] [ infer:150 ] -------------------- [ 2019-03-21 16:52:48,715 ] [ DEBUG ] [ infer:151 ] Partial infer for spatial_temporal_network/geo/conblock_2/cov/bias [ 2019-03-21 16:52:48,715 ] [ DEBUG ] [ infer:152 ] Op: Const [ 2019-03-21 16:52:48,715 ] [ DEBUG ] [ infer:163 ] Inputs: [ 2019-03-21 16:52:48,715 ] [ DEBUG ] [ infer:165 ] Outputs: [ 2019-03-21 16:52:48,729 ] [ DEBUG ] [ infer:40 ] output[0]: shape = [512], value = [ 1.11946207e-03 -2.37401924e-03 -7.16306688e-03 -2.47903494e-03 3.83454352e-03 -3.67252529e-03... [ 2019-03-21 16:52:48,730 ] [ DEBUG ] [ infer:150 ] -------------------- [ 2019-03-21 16:52:48,730 ] [ DEBUG ] [ infer:151 ] Partial infer for spatial_temporal_network/geo/conblock_2/cov/bias/read [ 2019-03-21 16:52:48,730 ] [ DEBUG ] [ infer:152 ] Op: Identity [ 2019-03-21 16:52:48,730 ] [ DEBUG ] [ infer:163 ] Inputs: [ 2019-03-21 16:52:48,744 ] [ DEBUG ] [ infer:40 ] input[0]: shape = [512], value = [ 1.11946207e-03 -2.37401924e-03 -7.16306688e-03 -2.47903494e-03 3.83454352e-03 -3.67252529e-03... [ 2019-03-21 16:52:48,744 ] [ DEBUG ] [ infer:165 ] Outputs: [ 2019-03-21 16:52:48,758 ] [ DEBUG ] [ infer:40 ] output[0]: shape = [512], value = [ 1.11946207e-03 -2.37401924e-03 -7.16306688e-03 -2.47903494e-03 3.83454352e-03 -3.67252529e-03... [ 2019-03-21 16:52:48,758 ] [ DEBUG ] [ infer:150 ] -------------------- [ 2019-03-21 16:52:48,759 ] [ DEBUG ] [ infer:151 ] Partial infer for spatial_temporal_network/geo/conblock_2/cov/kernel [ 2019-03-21 16:52:48,759 ] [ DEBUG ] [ infer:152 ] Op: Const [ 2019-03-21 16:52:48,759 ] [ DEBUG ] [ infer:163 ] Inputs: [ 2019-03-21 16:52:48,759 ] [ DEBUG ] [ infer:165 ] Outputs: [ 2019-03-21 16:52:48,763 ] [ DEBUG ] [ infer:40 ] output[0]: shape = [ 3 256 512], value = [[[-3.21085914e-03 -2.21884232e-02 -8.55684727e-02 ... -1.63935199e-02 1.23029929e-02 -6.2155... [ 2019-03-21 16:52:48,763 ] [ DEBUG ] [ infer:150 ] -------------------- [ 2019-03-21 16:52:48,763 ] [ DEBUG ] [ infer:151 ] Partial infer for spatial_temporal_network/geo/conblock_2/cov/kernel/read [ 2019-03-21 16:52:48,764 ] [ DEBUG ] [ infer:152 ] Op: Identity [ 2019-03-21 16:52:48,764 ] [ DEBUG ] [ infer:163 ] Inputs: [ 2019-03-21 16:52:48,768 ] [ DEBUG ] [ infer:40 ] input[0]: shape = [ 3 256 512], value = [[[-3.21085914e-03 -2.21884232e-02 -8.55684727e-02 ... -1.63935199e-02 1.23029929e-02 -6.2155... [ 2019-03-21 16:52:48,768 ] [ DEBUG ] [ infer:165 ] Outputs: [ 2019-03-21 16:52:48,772 ] [ DEBUG ] [ infer:40 ] output[0]: shape = [ 3 256 512], value = [[[-3.21085914e-03 -2.21884232e-02 -8.55684727e-02 ... -1.63935199e-02 1.23029929e-02 -6.2155... [ 2019-03-21 16:52:48,772 ] [ DEBUG ] [ infer:150 ] -------------------- [ 2019-03-21 16:52:48,772 ] [ DEBUG ] [ infer:151 ] Partial infer for spatial_temporal_network/geo/conblock_2/cov/conv1d/ExpandDims_1 [ 2019-03-21 16:52:48,773 ] [ DEBUG ] [ infer:152 ] Op: ExpandDims [ 2019-03-21 16:52:48,774 ] [ DEBUG ] [ infer:163 ] Inputs: [ 2019-03-21 16:52:48,777 ] [ DEBUG ] [ infer:40 ] input[0]: shape = [ 3 256 512], value = [[[-3.21085914e-03 -2.21884232e-02 -8.55684727e-02 ... -1.63935199e-02 1.23029929e-02 -6.2155... [ 2019-03-21 16:52:48,777 ] [ DEBUG ] [ infer:165 ] Outputs: [ 2019-03-21 16:52:48,781 ] [ DEBUG ] [ infer:40 ] output[0]: shape = [ 1 3 256 512], value = [[[[-3.21085914e-03 -2.21884232e-02 -8.55684727e-02 ... -1.63935199e-02 1.23029929e-02 -6.21... [ 2019-03-21 16:52:48,781 ] [ DEBUG ] [ infer:150 ] -------------------- [ 2019-03-21 16:52:48,781 ] [ DEBUG ] [ infer:151 ] Partial infer for spatial_temporal_network/geo/conblock_1/bn/batchnorm/add/y [ 2019-03-21 16:52:48,781 ] [ DEBUG ] [ infer:152 ] Op: Const [ 2019-03-21 16:52:48,782 ] [ DEBUG ] [ infer:163 ] Inputs: [ 2019-03-21 16:52:48,782 ] [ DEBUG ] [ infer:165 ] Outputs: [ 2019-03-21 16:52:48,782 ] [ DEBUG ] [ infer:40 ] output[0]: shape = [], value = 0.001 [ 2019-03-21 16:52:48,783 ] [ DEBUG ] [ infer:150 ] -------------------- [ 2019-03-21 16:52:48,783 ] [ DEBUG ] [ infer:151 ] Partial infer for spatial_temporal_network/geo/conblock_1/bn/moving_variance [ 2019-03-21 16:52:48,783 ] [ DEBUG ] [ infer:152 ] Op: Const [ 2019-03-21 16:52:48,783 ] [ DEBUG ] [ infer:163 ] Inputs: [ 2019-03-21 16:52:48,783 ] [ DEBUG ] [ infer:165 ] Outputs: [ 2019-03-21 16:52:48,791 ] [ DEBUG ] [ infer:40 ] output[0]: shape = [256], value = [1. 1. 1. 1. 1. 1. 1. 1. 1. 1. 1. 1. 1. 1. 1. 1. 1. 1. 1. 1. 1. 1. 1. 1. 1. 1. 1. 1. 1. 1. 1. 1.... [ 2019-03-21 16:52:48,791 ] [ DEBUG ] [ infer:150 ] -------------------- [ 2019-03-21 16:52:48,791 ] [ DEBUG ] [ infer:151 ] Partial infer for spatial_temporal_network/geo/conblock_1/bn/moving_variance/read [ 2019-03-21 16:52:48,792 ] [ DEBUG ] [ infer:152 ] Op: Identity [ 2019-03-21 16:52:48,792 ] [ DEBUG ] [ infer:163 ] Inputs: [ 2019-03-21 16:52:48,798 ] [ DEBUG ] [ infer:40 ] input[0]: shape = [256], value = [1. 1. 1. 1. 1. 1. 1. 1. 1. 1. 1. 1. 1. 1. 1. 1. 1. 1. 1. 1. 1. 1. 1. 1. 1. 1. 1. 1. 1. 1. 1. 1.... [ 2019-03-21 16:52:48,799 ] [ DEBUG ] [ infer:165 ] Outputs: [ 2019-03-21 16:52:48,805 ] [ DEBUG ] [ infer:40 ] output[0]: shape = [256], value = [1. 1. 1. 1. 1. 1. 1. 1. 1. 1. 1. 1. 1. 1. 1. 1. 1. 1. 1. 1. 1. 1. 1. 1. 1. 1. 1. 1. 1. 1. 1. 1.... [ 2019-03-21 16:52:48,806 ] [ DEBUG ] [ infer:150 ] -------------------- [ 2019-03-21 16:52:48,806 ] [ DEBUG ] [ infer:151 ] Partial infer for spatial_temporal_network/geo/conblock_1/bn/batchnorm/add [ 2019-03-21 16:52:48,806 ] [ DEBUG ] [ infer:152 ] Op: Add [ 2019-03-21 16:52:48,807 ] [ DEBUG ] [ infer:163 ] Inputs: [ 2019-03-21 16:52:48,814 ] [ DEBUG ] [ infer:40 ] input[0]: shape = [256], value = [1. 1. 1. 1. 1. 1. 1. 1. 1. 1. 1. 1. 1. 1. 1. 1. 1. 1. 1. 1. 1. 1. 1. 1. 1. 1. 1. 1. 1. 1. 1. 1.... [ 2019-03-21 16:52:48,814 ] [ DEBUG ] [ infer:40 ] input[1]: shape = [], value = 0.001 [ 2019-03-21 16:52:48,814 ] [ DEBUG ] [ infer:165 ] Outputs: [ 2019-03-21 16:52:48,820 ] [ DEBUG ] [ infer:40 ] output[0]: shape = [256], value = [1.001 1.001 1.001 1.001 1.001 1.001 1.001 1.001 1.001 1.001 1.001 1.001 1.001 1.001 1.001 1.001... [ 2019-03-21 16:52:48,821 ] [ DEBUG ] [ infer:150 ] -------------------- [ 2019-03-21 16:52:48,821 ] [ DEBUG ] [ infer:151 ] Partial infer for spatial_temporal_network/geo/conblock_1/bn/batchnorm/Rsqrt [ 2019-03-21 16:52:48,821 ] [ DEBUG ] [ infer:152 ] Op: Rsqrt [ 2019-03-21 16:52:48,822 ] [ DEBUG ] [ infer:163 ] Inputs: [ 2019-03-21 16:52:48,829 ] [ DEBUG ] [ infer:40 ] input[0]: shape = [256], value = [1.001 1.001 1.001 1.001 1.001 1.001 1.001 1.001 1.001 1.001 1.001 1.001 1.001 1.001 1.001 1.001... [ 2019-03-21 16:52:48,829 ] [ DEBUG ] [ infer:165 ] Outputs: [ 2019-03-21 16:52:48,836 ] [ DEBUG ] [ infer:40 ] output[0]: shape = [256], value = [0.9995004 0.9995004 0.9995004 0.9995004 0.9995004 0.9995004 0.9995004 0.9995004 0.9995004 0.999... [ 2019-03-21 16:52:48,836 ] [ DEBUG ] [ infer:150 ] -------------------- [ 2019-03-21 16:52:48,836 ] [ DEBUG ] [ infer:151 ] Partial infer for spatial_temporal_network/geo/conblock_1/bn/moving_mean [ 2019-03-21 16:52:48,836 ] [ DEBUG ] [ infer:152 ] Op: Const [ 2019-03-21 16:52:48,837 ] [ DEBUG ] [ infer:163 ] Inputs: [ 2019-03-21 16:52:48,837 ] [ DEBUG ] [ infer:165 ] Outputs: [ 2019-03-21 16:52:48,844 ] [ DEBUG ] [ infer:40 ] output[0]: shape = [256], value = [0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0.... [ 2019-03-21 16:52:48,844 ] [ DEBUG ] [ infer:150 ] -------------------- [ 2019-03-21 16:52:48,844 ] [ DEBUG ] [ infer:151 ] Partial infer for spatial_temporal_network/geo/conblock_1/bn/moving_mean/read [ 2019-03-21 16:52:48,844 ] [ DEBUG ] [ infer:152 ] Op: Identity [ 2019-03-21 16:52:48,845 ] [ DEBUG ] [ infer:163 ] Inputs: [ 2019-03-21 16:52:48,851 ] [ DEBUG ] [ infer:40 ] input[0]: shape = [256], value = [0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0.... [ 2019-03-21 16:52:48,851 ] [ DEBUG ] [ infer:165 ] Outputs: [ 2019-03-21 16:52:48,857 ] [ DEBUG ] [ infer:40 ] output[0]: shape = [256], value = [0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0.... [ 2019-03-21 16:52:48,858 ] [ DEBUG ] [ infer:150 ] -------------------- [ 2019-03-21 16:52:48,858 ] [ DEBUG ] [ infer:151 ] Partial infer for spatial_temporal_network/geo/conblock_1/bn/beta [ 2019-03-21 16:52:48,859 ] [ DEBUG ] [ infer:152 ] Op: Const [ 2019-03-21 16:52:48,859 ] [ DEBUG ] [ infer:163 ] Inputs: [ 2019-03-21 16:52:48,859 ] [ DEBUG ] [ infer:165 ] Outputs: [ 2019-03-21 16:52:48,866 ] [ DEBUG ] [ infer:40 ] output[0]: shape = [256], value = [ 3.95187829e-03 -9.82402544e-03 -1.87268723e-02 7.15974765e-03 4.58617788e-03 1.59223359e-02... [ 2019-03-21 16:52:48,866 ] [ DEBUG ] [ infer:150 ] -------------------- [ 2019-03-21 16:52:48,866 ] [ DEBUG ] [ infer:151 ] Partial infer for spatial_temporal_network/geo/conblock_1/bn/beta/read [ 2019-03-21 16:52:48,867 ] [ DEBUG ] [ infer:152 ] Op: Identity [ 2019-03-21 16:52:48,867 ] [ DEBUG ] [ infer:163 ] Inputs: [ 2019-03-21 16:52:48,875 ] [ DEBUG ] [ infer:40 ] input[0]: shape = [256], value = [ 3.95187829e-03 -9.82402544e-03 -1.87268723e-02 7.15974765e-03 4.58617788e-03 1.59223359e-02... [ 2019-03-21 16:52:48,875 ] [ DEBUG ] [ infer:165 ] Outputs: [ 2019-03-21 16:52:48,881 ] [ DEBUG ] [ infer:40 ] output[0]: shape = [256], value = [ 3.95187829e-03 -9.82402544e-03 -1.87268723e-02 7.15974765e-03 4.58617788e-03 1.59223359e-02... [ 2019-03-21 16:52:48,882 ] [ DEBUG ] [ infer:150 ] -------------------- [ 2019-03-21 16:52:48,883 ] [ DEBUG ] [ infer:151 ] Partial infer for spatial_temporal_network/geo/conblock_1/bn/gamma [ 2019-03-21 16:52:48,883 ] [ DEBUG ] [ infer:152 ] Op: Const [ 2019-03-21 16:52:48,883 ] [ DEBUG ] [ infer:163 ] Inputs: [ 2019-03-21 16:52:48,883 ] [ DEBUG ] [ infer:165 ] Outputs: [ 2019-03-21 16:52:48,891 ] [ DEBUG ] [ infer:40 ] output[0]: shape = [256], value = [1.0167245 0.99858433 1.0485467 1.0163606 1.0311669 1.0108894 1.0163829 0.99374986 0.991899... [ 2019-03-21 16:52:48,892 ] [ DEBUG ] [ infer:150 ] -------------------- [ 2019-03-21 16:52:48,892 ] [ DEBUG ] [ infer:151 ] Partial infer for spatial_temporal_network/geo/conblock_1/bn/gamma/read [ 2019-03-21 16:52:48,892 ] [ DEBUG ] [ infer:152 ] Op: Identity [ 2019-03-21 16:52:48,893 ] [ DEBUG ] [ infer:163 ] Inputs: [ 2019-03-21 16:52:48,899 ] [ DEBUG ] [ infer:40 ] input[0]: shape = [256], value = [1.0167245 0.99858433 1.0485467 1.0163606 1.0311669 1.0108894 1.0163829 0.99374986 0.991899... [ 2019-03-21 16:52:48,899 ] [ DEBUG ] [ infer:165 ] Outputs: [ 2019-03-21 16:52:48,909 ] [ DEBUG ] [ infer:40 ] output[0]: shape = [256], value = [1.0167245 0.99858433 1.0485467 1.0163606 1.0311669 1.0108894 1.0163829 0.99374986 0.991899... [ 2019-03-21 16:52:48,909 ] [ DEBUG ] [ infer:150 ] -------------------- [ 2019-03-21 16:52:48,909 ] [ DEBUG ] [ infer:151 ] Partial infer for spatial_temporal_network/geo/conblock_1/bn/batchnorm/mul [ 2019-03-21 16:52:48,910 ] [ DEBUG ] [ infer:152 ] Op: Mul [ 2019-03-21 16:52:48,910 ] [ DEBUG ] [ infer:163 ] Inputs: [ 2019-03-21 16:52:48,917 ] [ DEBUG ] [ infer:40 ] input[1]: shape = [256], value = [1.0167245 0.99858433 1.0485467 1.0163606 1.0311669 1.0108894 1.0163829 0.99374986 0.991899... [ 2019-03-21 16:52:48,924 ] [ DEBUG ] [ infer:40 ] input[0]: shape = [256], value = [0.9995004 0.9995004 0.9995004 0.9995004 0.9995004 0.9995004 0.9995004 0.9995004 0.9995004 0.999... [ 2019-03-21 16:52:48,924 ] [ DEBUG ] [ infer:165 ] Outputs: [ 2019-03-21 16:52:48,931 ] [ DEBUG ] [ infer:40 ] output[0]: shape = [256], value = [1.0162165 0.99808544 1.0480229 1.0158528 1.0306517 1.0103843 1.0158751 0.99325335 0.991403... [ 2019-03-21 16:52:48,932 ] [ DEBUG ] [ infer:150 ] -------------------- [ 2019-03-21 16:52:48,932 ] [ DEBUG ] [ infer:151 ] Partial infer for spatial_temporal_network/geo/conblock_1/bn/batchnorm/mul_2 [ 2019-03-21 16:52:48,932 ] [ DEBUG ] [ infer:152 ] Op: Mul [ 2019-03-21 16:52:48,933 ] [ DEBUG ] [ infer:163 ] Inputs: [ 2019-03-21 16:52:48,939 ] [ DEBUG ] [ infer:40 ] input[0]: shape = [256], value = [0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0.... [ 2019-03-21 16:52:48,947 ] [ DEBUG ] [ infer:40 ] input[1]: shape = [256], value = [1.0162165 0.99808544 1.0480229 1.0158528 1.0306517 1.0103843 1.0158751 0.99325335 0.991403... [ 2019-03-21 16:52:48,947 ] [ DEBUG ] [ infer:165 ] Outputs: [ 2019-03-21 16:52:48,955 ] [ DEBUG ] [ infer:40 ] output[0]: shape = [256], value = [0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0.... [ 2019-03-21 16:52:48,955 ] [ DEBUG ] [ infer:150 ] -------------------- [ 2019-03-21 16:52:48,955 ] [ DEBUG ] [ infer:151 ] Partial infer for spatial_temporal_network/geo/conblock_1/bn/batchnorm/sub/negate_ [ 2019-03-21 16:52:48,955 ] [ DEBUG ] [ infer:152 ] Op: Power [ 2019-03-21 16:52:48,956 ] [ DEBUG ] [ infer:163 ] Inputs: [ 2019-03-21 16:52:48,962 ] [ DEBUG ] [ infer:40 ] input[0]: shape = [256], value = [0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0.... [ 2019-03-21 16:52:48,962 ] [ DEBUG ] [ infer:165 ] Outputs: [ 2019-03-21 16:52:48,969 ] [ DEBUG ] [ infer:40 ] output[0]: shape = [256], value = [0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0.... [ 2019-03-21 16:52:48,970 ] [ DEBUG ] [ infer:150 ] -------------------- [ 2019-03-21 16:52:48,970 ] [ DEBUG ] [ infer:151 ] Partial infer for spatial_temporal_network/geo/conblock_1/bn/batchnorm/sub/add_ [ 2019-03-21 16:52:48,970 ] [ DEBUG ] [ infer:152 ] Op: Add [ 2019-03-21 16:52:48,971 ] [ DEBUG ] [ infer:163 ] Inputs: [ 2019-03-21 16:52:48,977 ] [ DEBUG ] [ infer:40 ] input[0]: shape = [256], value = [ 3.95187829e-03 -9.82402544e-03 -1.87268723e-02 7.15974765e-03 4.58617788e-03 1.59223359e-02... [ 2019-03-21 16:52:48,984 ] [ DEBUG ] [ infer:40 ] input[1]: shape = [256], value = [0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0.... [ 2019-03-21 16:52:48,984 ] [ DEBUG ] [ infer:165 ] Outputs: [ 2019-03-21 16:52:48,993 ] [ DEBUG ] [ infer:40 ] output[0]: shape = [256], value = [ 3.95187829e-03 -9.82402544e-03 -1.87268723e-02 7.15974765e-03 4.58617788e-03 1.59223359e-02... [ 2019-03-21 16:52:48,993 ] [ DEBUG ] [ infer:150 ] -------------------- [ 2019-03-21 16:52:48,993 ] [ DEBUG ] [ infer:151 ] Partial infer for spatial_temporal_network/geo/conblock_1/cov/conv1d/ExpandDims_1/dim [ 2019-03-21 16:52:48,994 ] [ DEBUG ] [ infer:152 ] Op: Const [ 2019-03-21 16:52:48,994 ] [ DEBUG ] [ infer:163 ] Inputs: [ 2019-03-21 16:52:48,994 ] [ DEBUG ] [ infer:165 ] Outputs: [ 2019-03-21 16:52:48,995 ] [ DEBUG ] [ infer:40 ] output[0]: shape = [], value = 0 [ 2019-03-21 16:52:48,995 ] [ DEBUG ] [ infer:150 ] -------------------- [ 2019-03-21 16:52:48,995 ] [ DEBUG ] [ infer:151 ] Partial infer for spatial_temporal_network/geo/conblock_1/cov/conv1d/ExpandDims/dim [ 2019-03-21 16:52:48,996 ] [ DEBUG ] [ infer:152 ] Op: Const [ 2019-03-21 16:52:48,996 ] [ DEBUG ] [ infer:163 ] Inputs: [ 2019-03-21 16:52:48,996 ] [ DEBUG ] [ infer:165 ] Outputs: [ 2019-03-21 16:52:48,996 ] [ DEBUG ] [ infer:40 ] output[0]: shape = [], value = 1 [ 2019-03-21 16:52:48,997 ] [ DEBUG ] [ infer:150 ] -------------------- [ 2019-03-21 16:52:48,997 ] [ DEBUG ] [ infer:151 ] Partial infer for spatial_temporal_network/geo/conblock_1/cov/bias [ 2019-03-21 16:52:48,997 ] [ DEBUG ] [ infer:152 ] Op: Const [ 2019-03-21 16:52:48,997 ] [ DEBUG ] [ infer:163 ] Inputs: [ 2019-03-21 16:52:48,998 ] [ DEBUG ] [ infer:165 ] Outputs: [ 2019-03-21 16:52:49,005 ] [ DEBUG ] [ infer:40 ] output[0]: shape = [256], value = [ 3.97014339e-03 -1.03658428e-02 -1.96596421e-02 7.17372261e-03 4.47784411e-03 1.59283429e-02... [ 2019-03-21 16:52:49,006 ] [ DEBUG ] [ infer:150 ] -------------------- [ 2019-03-21 16:52:49,006 ] [ DEBUG ] [ infer:151 ] Partial infer for spatial_temporal_network/geo/conblock_1/cov/bias/read [ 2019-03-21 16:52:49,006 ] [ DEBUG ] [ infer:152 ] Op: Identity [ 2019-03-21 16:52:49,006 ] [ DEBUG ] [ infer:163 ] Inputs: [ 2019-03-21 16:52:49,013 ] [ DEBUG ] [ infer:40 ] input[0]: shape = [256], value = [ 3.97014339e-03 -1.03658428e-02 -1.96596421e-02 7.17372261e-03 4.47784411e-03 1.59283429e-02... [ 2019-03-21 16:52:49,013 ] [ DEBUG ] [ infer:165 ] Outputs: [ 2019-03-21 16:52:49,021 ] [ DEBUG ] [ infer:40 ] output[0]: shape = [256], value = [ 3.97014339e-03 -1.03658428e-02 -1.96596421e-02 7.17372261e-03 4.47784411e-03 1.59283429e-02... [ 2019-03-21 16:52:49,021 ] [ DEBUG ] [ infer:150 ] -------------------- [ 2019-03-21 16:52:49,022 ] [ DEBUG ] [ infer:151 ] Partial infer for spatial_temporal_network/geo/conblock_1/cov/kernel [ 2019-03-21 16:52:49,022 ] [ DEBUG ] [ infer:152 ] Op: Const [ 2019-03-21 16:52:49,022 ] [ DEBUG ] [ infer:163 ] Inputs: [ 2019-03-21 16:52:49,022 ] [ DEBUG ] [ infer:165 ] Outputs: [ 2019-03-21 16:52:49,026 ] [ DEBUG ] [ infer:40 ] output[0]: shape = [ 3 182 256], value = [[[ 0.10378325 0.01596859 -0.05274214 ... 0.07833526 -0.05113211 -0.050156 ] [ 0.02837425... [ 2019-03-21 16:52:49,027 ] [ DEBUG ] [ infer:150 ] -------------------- [ 2019-03-21 16:52:49,027 ] [ DEBUG ] [ infer:151 ] Partial infer for spatial_temporal_network/geo/conblock_1/cov/kernel/read [ 2019-03-21 16:52:49,027 ] [ DEBUG ] [ infer:152 ] Op: Identity [ 2019-03-21 16:52:49,027 ] [ DEBUG ] [ infer:163 ] Inputs: [ 2019-03-21 16:52:49,032 ] [ DEBUG ] [ infer:40 ] input[0]: shape = [ 3 182 256], value = [[[ 0.10378325 0.01596859 -0.05274214 ... 0.07833526 -0.05113211 -0.050156 ] [ 0.02837425... [ 2019-03-21 16:52:49,032 ] [ DEBUG ] [ infer:165 ] Outputs: [ 2019-03-21 16:52:49,036 ] [ DEBUG ] [ infer:40 ] output[0]: shape = [ 3 182 256], value = [[[ 0.10378325 0.01596859 -0.05274214 ... 0.07833526 -0.05113211 -0.050156 ] [ 0.02837425... [ 2019-03-21 16:52:49,037 ] [ DEBUG ] [ infer:150 ] -------------------- [ 2019-03-21 16:52:49,037 ] [ DEBUG ] [ infer:151 ] Partial infer for spatial_temporal_network/geo/conblock_1/cov/conv1d/ExpandDims_1 [ 2019-03-21 16:52:49,037 ] [ DEBUG ] [ infer:152 ] Op: ExpandDims [ 2019-03-21 16:52:49,038 ] [ DEBUG ] [ infer:163 ] Inputs: [ 2019-03-21 16:52:49,041 ] [ DEBUG ] [ infer:40 ] input[0]: shape = [ 3 182 256], value = [[[ 0.10378325 0.01596859 -0.05274214 ... 0.07833526 -0.05113211 -0.050156 ] [ 0.02837425... [ 2019-03-21 16:52:49,042 ] [ DEBUG ] [ infer:165 ] Outputs: [ 2019-03-21 16:52:49,045 ] [ DEBUG ] [ infer:40 ] output[0]: shape = [ 1 3 182 256], value = [[[[ 0.10378325 0.01596859 -0.05274214 ... 0.07833526 -0.05113211 -0.050156 ] [ 0.02837... [ 2019-03-21 16:52:49,045 ] [ DEBUG ] [ infer:150 ] -------------------- [ 2019-03-21 16:52:49,046 ] [ DEBUG ] [ infer:151 ] Partial infer for spatial_temporal_network/motion/conblock_4/bn/batchnorm/add/y [ 2019-03-21 16:52:49,046 ] [ DEBUG ] [ infer:152 ] Op: Const [ 2019-03-21 16:52:49,046 ] [ DEBUG ] [ infer:163 ] Inputs: [ 2019-03-21 16:52:49,046 ] [ DEBUG ] [ infer:165 ] Outputs: [ 2019-03-21 16:52:49,046 ] [ DEBUG ] [ infer:40 ] output[0]: shape = [], value = 0.001 [ 2019-03-21 16:52:49,047 ] [ DEBUG ] [ infer:150 ] -------------------- [ 2019-03-21 16:52:49,047 ] [ DEBUG ] [ infer:151 ] Partial infer for spatial_temporal_network/motion/conblock_4/bn/moving_variance [ 2019-03-21 16:52:49,047 ] [ DEBUG ] [ infer:152 ] Op: Const [ 2019-03-21 16:52:49,047 ] [ DEBUG ] [ infer:163 ] Inputs: [ 2019-03-21 16:52:49,048 ] [ DEBUG ] [ infer:165 ] Outputs: [ 2019-03-21 16:52:49,061 ] [ DEBUG ] [ infer:40 ] output[0]: shape = [512], value = [1. 1. 1. 1. 1. 1. 1. 1. 1. 1. 1. 1. 1. 1. 1. 1. 1. 1. 1. 1. 1. 1. 1. 1. 1. 1. 1. 1. 1. 1. 1. 1.... [ 2019-03-21 16:52:49,061 ] [ DEBUG ] [ infer:150 ] -------------------- [ 2019-03-21 16:52:49,061 ] [ DEBUG ] [ infer:151 ] Partial infer for spatial_temporal_network/motion/conblock_4/bn/moving_variance/read [ 2019-03-21 16:52:49,062 ] [ DEBUG ] [ infer:152 ] Op: Identity [ 2019-03-21 16:52:49,062 ] [ DEBUG ] [ infer:163 ] Inputs: [ 2019-03-21 16:52:49,076 ] [ DEBUG ] [ infer:40 ] input[0]: shape = [512], value = [1. 1. 1. 1. 1. 1. 1. 1. 1. 1. 1. 1. 1. 1. 1. 1. 1. 1. 1. 1. 1. 1. 1. 1. 1. 1. 1. 1. 1. 1. 1. 1.... [ 2019-03-21 16:52:49,076 ] [ DEBUG ] [ infer:165 ] Outputs: [ 2019-03-21 16:52:49,090 ] [ DEBUG ] [ infer:40 ] output[0]: shape = [512], value = [1. 1. 1. 1. 1. 1. 1. 1. 1. 1. 1. 1. 1. 1. 1. 1. 1. 1. 1. 1. 1. 1. 1. 1. 1. 1. 1. 1. 1. 1. 1. 1.... [ 2019-03-21 16:52:49,091 ] [ DEBUG ] [ infer:150 ] -------------------- [ 2019-03-21 16:52:49,091 ] [ DEBUG ] [ infer:151 ] Partial infer for spatial_temporal_network/motion/conblock_4/bn/batchnorm/add [ 2019-03-21 16:52:49,091 ] [ DEBUG ] [ infer:152 ] Op: Add [ 2019-03-21 16:52:49,092 ] [ DEBUG ] [ infer:163 ] Inputs: [ 2019-03-21 16:52:49,104 ] [ DEBUG ] [ infer:40 ] input[0]: shape = [512], value = [1. 1. 1. 1. 1. 1. 1. 1. 1. 1. 1. 1. 1. 1. 1. 1. 1. 1. 1. 1. 1. 1. 1. 1. 1. 1. 1. 1. 1. 1. 1. 1.... [ 2019-03-21 16:52:49,105 ] [ DEBUG ] [ infer:40 ] input[1]: shape = [], value = 0.001 [ 2019-03-21 16:52:49,105 ] [ DEBUG ] [ infer:165 ] Outputs: [ 2019-03-21 16:52:49,117 ] [ DEBUG ] [ infer:40 ] output[0]: shape = [512], value = [1.001 1.001 1.001 1.001 1.001 1.001 1.001 1.001 1.001 1.001 1.001 1.001 1.001 1.001 1.001 1.001... [ 2019-03-21 16:52:49,119 ] [ DEBUG ] [ infer:150 ] -------------------- [ 2019-03-21 16:52:49,119 ] [ DEBUG ] [ infer:151 ] Partial infer for spatial_temporal_network/motion/conblock_4/bn/batchnorm/Rsqrt [ 2019-03-21 16:52:49,119 ] [ DEBUG ] [ infer:152 ] Op: Rsqrt [ 2019-03-21 16:52:49,120 ] [ DEBUG ] [ infer:163 ] Inputs: [ 2019-03-21 16:52:49,132 ] [ DEBUG ] [ infer:40 ] input[0]: shape = [512], value = [1.001 1.001 1.001 1.001 1.001 1.001 1.001 1.001 1.001 1.001 1.001 1.001 1.001 1.001 1.001 1.001... [ 2019-03-21 16:52:49,132 ] [ DEBUG ] [ infer:165 ] Outputs: [ 2019-03-21 16:52:49,145 ] [ DEBUG ] [ infer:40 ] output[0]: shape = [512], value = [0.9995004 0.9995004 0.9995004 0.9995004 0.9995004 0.9995004 0.9995004 0.9995004 0.9995004 0.999... [ 2019-03-21 16:52:49,146 ] [ DEBUG ] [ infer:150 ] -------------------- [ 2019-03-21 16:52:49,146 ] [ DEBUG ] [ infer:151 ] Partial infer for spatial_temporal_network/motion/conblock_4/bn/moving_mean [ 2019-03-21 16:52:49,146 ] [ DEBUG ] [ infer:152 ] Op: Const [ 2019-03-21 16:52:49,147 ] [ DEBUG ] [ infer:163 ] Inputs: [ 2019-03-21 16:52:49,147 ] [ DEBUG ] [ infer:165 ] Outputs: [ 2019-03-21 16:52:49,159 ] [ DEBUG ] [ infer:40 ] output[0]: shape = [512], value = [0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0.... [ 2019-03-21 16:52:49,160 ] [ DEBUG ] [ infer:150 ] -------------------- [ 2019-03-21 16:52:49,161 ] [ DEBUG ] [ infer:151 ] Partial infer for spatial_temporal_network/motion/conblock_4/bn/moving_mean/read [ 2019-03-21 16:52:49,161 ] [ DEBUG ] [ infer:152 ] Op: Identity [ 2019-03-21 16:52:49,161 ] [ DEBUG ] [ infer:163 ] Inputs: [ 2019-03-21 16:52:49,173 ] [ DEBUG ] [ infer:40 ] input[0]: shape = [512], value = [0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0.... [ 2019-03-21 16:52:49,173 ] [ DEBUG ] [ infer:165 ] Outputs: [ 2019-03-21 16:52:49,184 ] [ DEBUG ] [ infer:40 ] output[0]: shape = [512], value = [0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0.... [ 2019-03-21 16:52:49,184 ] [ DEBUG ] [ infer:150 ] -------------------- [ 2019-03-21 16:52:49,186 ] [ DEBUG ] [ infer:151 ] Partial infer for spatial_temporal_network/motion/conblock_4/bn/beta [ 2019-03-21 16:52:49,186 ] [ DEBUG ] [ infer:152 ] Op: Const [ 2019-03-21 16:52:49,186 ] [ DEBUG ] [ infer:163 ] Inputs: [ 2019-03-21 16:52:49,186 ] [ DEBUG ] [ infer:165 ] Outputs: [ 2019-03-21 16:52:49,200 ] [ DEBUG ] [ infer:40 ] output[0]: shape = [512], value = [-5.32524893e-03 -3.41834291e-03 8.63424037e-04 -1.87578250e-03 9.49341280e-04 -4.33250470e-03... [ 2019-03-21 16:52:49,200 ] [ DEBUG ] [ infer:150 ] -------------------- [ 2019-03-21 16:52:49,201 ] [ DEBUG ] [ infer:151 ] Partial infer for spatial_temporal_network/motion/conblock_4/bn/beta/read [ 2019-03-21 16:52:49,201 ] [ DEBUG ] [ infer:152 ] Op: Identity [ 2019-03-21 16:52:49,201 ] [ DEBUG ] [ infer:163 ] Inputs: [ 2019-03-21 16:52:49,214 ] [ DEBUG ] [ infer:40 ] input[0]: shape = [512], value = [-5.32524893e-03 -3.41834291e-03 8.63424037e-04 -1.87578250e-03 9.49341280e-04 -4.33250470e-03... [ 2019-03-21 16:52:49,214 ] [ DEBUG ] [ infer:165 ] Outputs: [ 2019-03-21 16:52:49,229 ] [ DEBUG ] [ infer:40 ] output[0]: shape = [512], value = [-5.32524893e-03 -3.41834291e-03 8.63424037e-04 -1.87578250e-03 9.49341280e-04 -4.33250470e-03... [ 2019-03-21 16:52:49,229 ] [ DEBUG ] [ infer:150 ] -------------------- [ 2019-03-21 16:52:49,230 ] [ DEBUG ] [ infer:151 ] Partial infer for spatial_temporal_network/motion/conblock_4/bn/gamma [ 2019-03-21 16:52:49,230 ] [ DEBUG ] [ infer:152 ] Op: Const [ 2019-03-21 16:52:49,230 ] [ DEBUG ] [ infer:163 ] Inputs: [ 2019-03-21 16:52:49,230 ] [ DEBUG ] [ infer:165 ] Outputs: [ 2019-03-21 16:52:49,243 ] [ DEBUG ] [ infer:40 ] output[0]: shape = [512], value = [0.9999211 1.0018882 0.99904627 1.0000513 1.0047655 0.9999031 0.9999081 0.9988252 1.002743... [ 2019-03-21 16:52:49,243 ] [ DEBUG ] [ infer:150 ] -------------------- [ 2019-03-21 16:52:49,244 ] [ DEBUG ] [ infer:151 ] Partial infer for spatial_temporal_network/motion/conblock_4/bn/gamma/read [ 2019-03-21 16:52:49,244 ] [ DEBUG ] [ infer:152 ] Op: Identity [ 2019-03-21 16:52:49,244 ] [ DEBUG ] [ infer:163 ] Inputs: [ 2019-03-21 16:52:49,258 ] [ DEBUG ] [ infer:40 ] input[0]: shape = [512], value = [0.9999211 1.0018882 0.99904627 1.0000513 1.0047655 0.9999031 0.9999081 0.9988252 1.002743... [ 2019-03-21 16:52:49,258 ] [ DEBUG ] [ infer:165 ] Outputs: [ 2019-03-21 16:52:49,271 ] [ DEBUG ] [ infer:40 ] output[0]: shape = [512], value = [0.9999211 1.0018882 0.99904627 1.0000513 1.0047655 0.9999031 0.9999081 0.9988252 1.002743... [ 2019-03-21 16:52:49,271 ] [ DEBUG ] [ infer:150 ] -------------------- [ 2019-03-21 16:52:49,272 ] [ DEBUG ] [ infer:151 ] Partial infer for spatial_temporal_network/motion/conblock_4/bn/batchnorm/mul [ 2019-03-21 16:52:49,272 ] [ DEBUG ] [ infer:152 ] Op: Mul [ 2019-03-21 16:52:49,272 ] [ DEBUG ] [ infer:163 ] Inputs: [ 2019-03-21 16:52:49,285 ] [ DEBUG ] [ infer:40 ] input[1]: shape = [512], value = [0.9999211 1.0018882 0.99904627 1.0000513 1.0047655 0.9999031 0.9999081 0.9988252 1.002743... [ 2019-03-21 16:52:49,298 ] [ DEBUG ] [ infer:40 ] input[0]: shape = [512], value = [0.9995004 0.9995004 0.9995004 0.9995004 0.9995004 0.9995004 0.9995004 0.9995004 0.9995004 0.999... [ 2019-03-21 16:52:49,298 ] [ DEBUG ] [ infer:165 ] Outputs: [ 2019-03-21 16:52:49,311 ] [ DEBUG ] [ infer:40 ] output[0]: shape = [512], value = [0.99942154 1.0013876 0.99854714 0.99955165 1.0042635 0.99940354 0.99940854 0.9983262 1.00224... [ 2019-03-21 16:52:49,311 ] [ DEBUG ] [ infer:150 ] -------------------- [ 2019-03-21 16:52:49,312 ] [ DEBUG ] [ infer:151 ] Partial infer for spatial_temporal_network/motion/conblock_4/bn/batchnorm/mul_2 [ 2019-03-21 16:52:49,312 ] [ DEBUG ] [ infer:152 ] Op: Mul [ 2019-03-21 16:52:49,312 ] [ DEBUG ] [ infer:163 ] Inputs: [ 2019-03-21 16:52:49,324 ] [ DEBUG ] [ infer:40 ] input[0]: shape = [512], value = [0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0.... [ 2019-03-21 16:52:49,337 ] [ DEBUG ] [ infer:40 ] input[1]: shape = [512], value = [0.99942154 1.0013876 0.99854714 0.99955165 1.0042635 0.99940354 0.99940854 0.9983262 1.00224... [ 2019-03-21 16:52:49,337 ] [ DEBUG ] [ infer:165 ] Outputs: [ 2019-03-21 16:52:49,349 ] [ DEBUG ] [ infer:40 ] output[0]: shape = [512], value = [0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0.... [ 2019-03-21 16:52:49,350 ] [ DEBUG ] [ infer:150 ] -------------------- [ 2019-03-21 16:52:49,350 ] [ DEBUG ] [ infer:151 ] Partial infer for spatial_temporal_network/motion/conblock_4/bn/batchnorm/sub/negate_ [ 2019-03-21 16:52:49,350 ] [ DEBUG ] [ infer:152 ] Op: Power [ 2019-03-21 16:52:49,351 ] [ DEBUG ] [ infer:163 ] Inputs: [ 2019-03-21 16:52:49,362 ] [ DEBUG ] [ infer:40 ] input[0]: shape = [512], value = [0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0.... [ 2019-03-21 16:52:49,363 ] [ DEBUG ] [ infer:165 ] Outputs: [ 2019-03-21 16:52:49,374 ] [ DEBUG ] [ infer:40 ] output[0]: shape = [512], value = [0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0.... [ 2019-03-21 16:52:49,375 ] [ DEBUG ] [ infer:150 ] -------------------- [ 2019-03-21 16:52:49,375 ] [ DEBUG ] [ infer:151 ] Partial infer for spatial_temporal_network/motion/conblock_4/bn/batchnorm/sub/add_ [ 2019-03-21 16:52:49,375 ] [ DEBUG ] [ infer:152 ] Op: Add [ 2019-03-21 16:52:49,375 ] [ DEBUG ] [ infer:163 ] Inputs: [ 2019-03-21 16:52:49,389 ] [ DEBUG ] [ infer:40 ] input[0]: shape = [512], value = [-5.32524893e-03 -3.41834291e-03 8.63424037e-04 -1.87578250e-03 9.49341280e-04 -4.33250470e-03... [ 2019-03-21 16:52:49,401 ] [ DEBUG ] [ infer:40 ] input[1]: shape = [512], value = [0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0.... [ 2019-03-21 16:52:49,402 ] [ DEBUG ] [ infer:165 ] Outputs: [ 2019-03-21 16:52:49,417 ] [ DEBUG ] [ infer:40 ] output[0]: shape = [512], value = [-5.32524893e-03 -3.41834291e-03 8.63424037e-04 -1.87578250e-03 9.49341280e-04 -4.33250470e-03... [ 2019-03-21 16:52:49,417 ] [ DEBUG ] [ infer:150 ] -------------------- [ 2019-03-21 16:52:49,418 ] [ DEBUG ] [ infer:151 ] Partial infer for spatial_temporal_network/motion/conblock_4/cov/conv1d/ExpandDims_1/dim [ 2019-03-21 16:52:49,418 ] [ DEBUG ] [ infer:152 ] Op: Const [ 2019-03-21 16:52:49,419 ] [ DEBUG ] [ infer:163 ] Inputs: [ 2019-03-21 16:52:49,419 ] [ DEBUG ] [ infer:165 ] Outputs: [ 2019-03-21 16:52:49,419 ] [ DEBUG ] [ infer:40 ] output[0]: shape = [], value = 0 [ 2019-03-21 16:52:49,420 ] [ DEBUG ] [ infer:150 ] -------------------- [ 2019-03-21 16:52:49,420 ] [ DEBUG ] [ infer:151 ] Partial infer for spatial_temporal_network/motion/conblock_4/cov/conv1d/ExpandDims/dim [ 2019-03-21 16:52:49,420 ] [ DEBUG ] [ infer:152 ] Op: Const [ 2019-03-21 16:52:49,420 ] [ DEBUG ] [ infer:163 ] Inputs: [ 2019-03-21 16:52:49,420 ] [ DEBUG ] [ infer:165 ] Outputs: [ 2019-03-21 16:52:49,421 ] [ DEBUG ] [ infer:40 ] output[0]: shape = [], value = 1 [ 2019-03-21 16:52:49,421 ] [ DEBUG ] [ infer:150 ] -------------------- [ 2019-03-21 16:52:49,421 ] [ DEBUG ] [ infer:151 ] Partial infer for spatial_temporal_network/motion/conblock_4/cov/bias [ 2019-03-21 16:52:49,421 ] [ DEBUG ] [ infer:152 ] Op: Const [ 2019-03-21 16:52:49,422 ] [ DEBUG ] [ infer:163 ] Inputs: [ 2019-03-21 16:52:49,422 ] [ DEBUG ] [ infer:165 ] Outputs: [ 2019-03-21 16:52:49,435 ] [ DEBUG ] [ infer:40 ] output[0]: shape = [512], value = [-5.32235624e-03 -3.40969069e-03 8.59346939e-04 -1.87482859e-03 9.48017405e-04 -4.33015497e-03... [ 2019-03-21 16:52:49,436 ] [ DEBUG ] [ infer:150 ] -------------------- [ 2019-03-21 16:52:49,436 ] [ DEBUG ] [ infer:151 ] Partial infer for spatial_temporal_network/motion/conblock_4/cov/bias/read [ 2019-03-21 16:52:49,436 ] [ DEBUG ] [ infer:152 ] Op: Identity [ 2019-03-21 16:52:49,437 ] [ DEBUG ] [ infer:163 ] Inputs: [ 2019-03-21 16:52:49,450 ] [ DEBUG ] [ infer:40 ] input[0]: shape = [512], value = [-5.32235624e-03 -3.40969069e-03 8.59346939e-04 -1.87482859e-03 9.48017405e-04 -4.33015497e-03... [ 2019-03-21 16:52:49,451 ] [ DEBUG ] [ infer:165 ] Outputs: [ 2019-03-21 16:52:49,464 ] [ DEBUG ] [ infer:40 ] output[0]: shape = [512], value = [-5.32235624e-03 -3.40969069e-03 8.59346939e-04 -1.87482859e-03 9.48017405e-04 -4.33015497e-03... [ 2019-03-21 16:52:49,465 ] [ DEBUG ] [ infer:150 ] -------------------- [ 2019-03-21 16:52:49,465 ] [ DEBUG ] [ infer:151 ] Partial infer for spatial_temporal_network/motion/conblock_4/cov/kernel [ 2019-03-21 16:52:49,465 ] [ DEBUG ] [ infer:152 ] Op: Const [ 2019-03-21 16:52:49,465 ] [ DEBUG ] [ infer:163 ] Inputs: [ 2019-03-21 16:52:49,466 ] [ DEBUG ] [ infer:165 ] Outputs: [ 2019-03-21 16:52:49,470 ] [ DEBUG ] [ infer:40 ] output[0]: shape = [ 3 256 512], value = [[[-0.00075483 -0.00761538 0.02321353 ... 0.08803348 -0.06521032 -0.06899805] [ 0.03653132... [ 2019-03-21 16:52:49,471 ] [ DEBUG ] [ infer:150 ] -------------------- [ 2019-03-21 16:52:49,471 ] [ DEBUG ] [ infer:151 ] Partial infer for spatial_temporal_network/motion/conblock_4/cov/kernel/read [ 2019-03-21 16:52:49,471 ] [ DEBUG ] [ infer:152 ] Op: Identity [ 2019-03-21 16:52:49,471 ] [ DEBUG ] [ infer:163 ] Inputs: [ 2019-03-21 16:52:49,475 ] [ DEBUG ] [ infer:40 ] input[0]: shape = [ 3 256 512], value = [[[-0.00075483 -0.00761538 0.02321353 ... 0.08803348 -0.06521032 -0.06899805] [ 0.03653132... [ 2019-03-21 16:52:49,475 ] [ DEBUG ] [ infer:165 ] Outputs: [ 2019-03-21 16:52:49,478 ] [ DEBUG ] [ infer:40 ] output[0]: shape = [ 3 256 512], value = [[[-0.00075483 -0.00761538 0.02321353 ... 0.08803348 -0.06521032 -0.06899805] [ 0.03653132... [ 2019-03-21 16:52:49,479 ] [ DEBUG ] [ infer:150 ] -------------------- [ 2019-03-21 16:52:49,479 ] [ DEBUG ] [ infer:151 ] Partial infer for spatial_temporal_network/motion/conblock_4/cov/conv1d/ExpandDims_1 [ 2019-03-21 16:52:49,479 ] [ DEBUG ] [ infer:152 ] Op: ExpandDims [ 2019-03-21 16:52:49,480 ] [ DEBUG ] [ infer:163 ] Inputs: [ 2019-03-21 16:52:49,483 ] [ DEBUG ] [ infer:40 ] input[0]: shape = [ 3 256 512], value = [[[-0.00075483 -0.00761538 0.02321353 ... 0.08803348 -0.06521032 -0.06899805] [ 0.03653132... [ 2019-03-21 16:52:49,483 ] [ DEBUG ] [ infer:165 ] Outputs: [ 2019-03-21 16:52:49,487 ] [ DEBUG ] [ infer:40 ] output[0]: shape = [ 1 3 256 512], value = [[[[-0.00075483 -0.00761538 0.02321353 ... 0.08803348 -0.06521032 -0.06899805] [ 0.03653... [ 2019-03-21 16:52:49,487 ] [ DEBUG ] [ infer:150 ] -------------------- [ 2019-03-21 16:52:49,488 ] [ DEBUG ] [ infer:151 ] Partial infer for spatial_temporal_network/motion/conblock_3/bn/batchnorm/add/y [ 2019-03-21 16:52:49,488 ] [ DEBUG ] [ infer:152 ] Op: Const [ 2019-03-21 16:52:49,488 ] [ DEBUG ] [ infer:163 ] Inputs: [ 2019-03-21 16:52:49,488 ] [ DEBUG ] [ infer:165 ] Outputs: [ 2019-03-21 16:52:49,488 ] [ DEBUG ] [ infer:40 ] output[0]: shape = [], value = 0.001 [ 2019-03-21 16:52:49,489 ] [ DEBUG ] [ infer:150 ] -------------------- [ 2019-03-21 16:52:49,489 ] [ DEBUG ] [ infer:151 ] Partial infer for spatial_temporal_network/motion/conblock_3/bn/moving_variance [ 2019-03-21 16:52:49,489 ] [ DEBUG ] [ infer:152 ] Op: Const [ 2019-03-21 16:52:49,489 ] [ DEBUG ] [ infer:163 ] Inputs: [ 2019-03-21 16:52:49,490 ] [ DEBUG ] [ infer:165 ] Outputs: [ 2019-03-21 16:52:49,496 ] [ DEBUG ] [ infer:40 ] output[0]: shape = [256], value = [1. 1. 1. 1. 1. 1. 1. 1. 1. 1. 1. 1. 1. 1. 1. 1. 1. 1. 1. 1. 1. 1. 1. 1. 1. 1. 1. 1. 1. 1. 1. 1.... [ 2019-03-21 16:52:49,497 ] [ DEBUG ] [ infer:150 ] -------------------- [ 2019-03-21 16:52:49,497 ] [ DEBUG ] [ infer:151 ] Partial infer for spatial_temporal_network/motion/conblock_3/bn/moving_variance/read [ 2019-03-21 16:52:49,497 ] [ DEBUG ] [ infer:152 ] Op: Identity [ 2019-03-21 16:52:49,498 ] [ DEBUG ] [ infer:163 ] Inputs: [ 2019-03-21 16:52:49,504 ] [ DEBUG ] [ infer:40 ] input[0]: shape = [256], value = [1. 1. 1. 1. 1. 1. 1. 1. 1. 1. 1. 1. 1. 1. 1. 1. 1. 1. 1. 1. 1. 1. 1. 1. 1. 1. 1. 1. 1. 1. 1. 1.... [ 2019-03-21 16:52:49,504 ] [ DEBUG ] [ infer:165 ] Outputs: [ 2019-03-21 16:52:49,511 ] [ DEBUG ] [ infer:40 ] output[0]: shape = [256], value = [1. 1. 1. 1. 1. 1. 1. 1. 1. 1. 1. 1. 1. 1. 1. 1. 1. 1. 1. 1. 1. 1. 1. 1. 1. 1. 1. 1. 1. 1. 1. 1.... [ 2019-03-21 16:52:49,512 ] [ DEBUG ] [ infer:150 ] -------------------- [ 2019-03-21 16:52:49,512 ] [ DEBUG ] [ infer:151 ] Partial infer for spatial_temporal_network/motion/conblock_3/bn/batchnorm/add [ 2019-03-21 16:52:49,512 ] [ DEBUG ] [ infer:152 ] Op: Add [ 2019-03-21 16:52:49,512 ] [ DEBUG ] [ infer:163 ] Inputs: [ 2019-03-21 16:52:49,520 ] [ DEBUG ] [ infer:40 ] input[0]: shape = [256], value = [1. 1. 1. 1. 1. 1. 1. 1. 1. 1. 1. 1. 1. 1. 1. 1. 1. 1. 1. 1. 1. 1. 1. 1. 1. 1. 1. 1. 1. 1. 1. 1.... [ 2019-03-21 16:52:49,520 ] [ DEBUG ] [ infer:40 ] input[1]: shape = [], value = 0.001 [ 2019-03-21 16:52:49,520 ] [ DEBUG ] [ infer:165 ] Outputs: [ 2019-03-21 16:52:49,527 ] [ DEBUG ] [ infer:40 ] output[0]: shape = [256], value = [1.001 1.001 1.001 1.001 1.001 1.001 1.001 1.001 1.001 1.001 1.001 1.001 1.001 1.001 1.001 1.001... [ 2019-03-21 16:52:49,528 ] [ DEBUG ] [ infer:150 ] -------------------- [ 2019-03-21 16:52:49,528 ] [ DEBUG ] [ infer:151 ] Partial infer for spatial_temporal_network/motion/conblock_3/bn/batchnorm/Rsqrt [ 2019-03-21 16:52:49,528 ] [ DEBUG ] [ infer:152 ] Op: Rsqrt [ 2019-03-21 16:52:49,529 ] [ DEBUG ] [ infer:163 ] Inputs: [ 2019-03-21 16:52:49,538 ] [ DEBUG ] [ infer:40 ] input[0]: shape = [256], value = [1.001 1.001 1.001 1.001 1.001 1.001 1.001 1.001 1.001 1.001 1.001 1.001 1.001 1.001 1.001 1.001... [ 2019-03-21 16:52:49,538 ] [ DEBUG ] [ infer:165 ] Outputs: [ 2019-03-21 16:52:49,545 ] [ DEBUG ] [ infer:40 ] output[0]: shape = [256], value = [0.9995004 0.9995004 0.9995004 0.9995004 0.9995004 0.9995004 0.9995004 0.9995004 0.9995004 0.999... [ 2019-03-21 16:52:49,546 ] [ DEBUG ] [ infer:150 ] -------------------- [ 2019-03-21 16:52:49,546 ] [ DEBUG ] [ infer:151 ] Partial infer for spatial_temporal_network/motion/conblock_3/bn/moving_mean [ 2019-03-21 16:52:49,546 ] [ DEBUG ] [ infer:152 ] Op: Const [ 2019-03-21 16:52:49,546 ] [ DEBUG ] [ infer:163 ] Inputs: [ 2019-03-21 16:52:49,547 ] [ DEBUG ] [ infer:165 ] Outputs: [ 2019-03-21 16:52:49,553 ] [ DEBUG ] [ infer:40 ] output[0]: shape = [256], value = [0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0.... [ 2019-03-21 16:52:49,553 ] [ DEBUG ] [ infer:150 ] -------------------- [ 2019-03-21 16:52:49,554 ] [ DEBUG ] [ infer:151 ] Partial infer for spatial_temporal_network/motion/conblock_3/bn/moving_mean/read [ 2019-03-21 16:52:49,554 ] [ DEBUG ] [ infer:152 ] Op: Identity [ 2019-03-21 16:52:49,554 ] [ DEBUG ] [ infer:163 ] Inputs: [ 2019-03-21 16:52:49,561 ] [ DEBUG ] [ infer:40 ] input[0]: shape = [256], value = [0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0.... [ 2019-03-21 16:52:49,561 ] [ DEBUG ] [ infer:165 ] Outputs: [ 2019-03-21 16:52:49,567 ] [ DEBUG ] [ infer:40 ] output[0]: shape = [256], value = [0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0.... [ 2019-03-21 16:52:49,568 ] [ DEBUG ] [ infer:150 ] -------------------- [ 2019-03-21 16:52:49,568 ] [ DEBUG ] [ infer:151 ] Partial infer for spatial_temporal_network/motion/conblock_3/bn/beta [ 2019-03-21 16:52:49,569 ] [ DEBUG ] [ infer:152 ] Op: Const [ 2019-03-21 16:52:49,569 ] [ DEBUG ] [ infer:163 ] Inputs: [ 2019-03-21 16:52:49,570 ] [ DEBUG ] [ infer:165 ] Outputs: [ 2019-03-21 16:52:49,576 ] [ DEBUG ] [ infer:40 ] output[0]: shape = [256], value = [ 1.12557262e-02 1.98826529e-02 9.55713633e-03 4.63132225e-02 -5.92820998e-03 1.76003464e-02... [ 2019-03-21 16:52:49,577 ] [ DEBUG ] [ infer:150 ] -------------------- [ 2019-03-21 16:52:49,577 ] [ DEBUG ] [ infer:151 ] Partial infer for spatial_temporal_network/motion/conblock_3/bn/beta/read [ 2019-03-21 16:52:49,577 ] [ DEBUG ] [ infer:152 ] Op: Identity [ 2019-03-21 16:52:49,578 ] [ DEBUG ] [ infer:163 ] Inputs: [ 2019-03-21 16:52:49,585 ] [ DEBUG ] [ infer:40 ] input[0]: shape = [256], value = [ 1.12557262e-02 1.98826529e-02 9.55713633e-03 4.63132225e-02 -5.92820998e-03 1.76003464e-02... [ 2019-03-21 16:52:49,586 ] [ DEBUG ] [ infer:165 ] Outputs: [ 2019-03-21 16:52:49,593 ] [ DEBUG ] [ infer:40 ] output[0]: shape = [256], value = [ 1.12557262e-02 1.98826529e-02 9.55713633e-03 4.63132225e-02 -5.92820998e-03 1.76003464e-02... [ 2019-03-21 16:52:49,593 ] [ DEBUG ] [ infer:150 ] -------------------- [ 2019-03-21 16:52:49,593 ] [ DEBUG ] [ infer:151 ] Partial infer for spatial_temporal_network/motion/conblock_3/bn/gamma [ 2019-03-21 16:52:49,594 ] [ DEBUG ] [ infer:152 ] Op: Const [ 2019-03-21 16:52:49,594 ] [ DEBUG ] [ infer:163 ] Inputs: [ 2019-03-21 16:52:49,594 ] [ DEBUG ] [ infer:165 ] Outputs: [ 2019-03-21 16:52:49,601 ] [ DEBUG ] [ infer:40 ] output[0]: shape = [256], value = [1.0005053 1.0223469 1.0006596 1.0053079 0.9998968 1.0001366 1.0010912 0.9990738 1.000009... [ 2019-03-21 16:52:49,601 ] [ DEBUG ] [ infer:150 ] -------------------- [ 2019-03-21 16:52:49,601 ] [ DEBUG ] [ infer:151 ] Partial infer for spatial_temporal_network/motion/conblock_3/bn/gamma/read [ 2019-03-21 16:52:49,601 ] [ DEBUG ] [ infer:152 ] Op: Identity [ 2019-03-21 16:52:49,602 ] [ DEBUG ] [ infer:163 ] Inputs: [ 2019-03-21 16:52:49,610 ] [ DEBUG ] [ infer:40 ] input[0]: shape = [256], value = [1.0005053 1.0223469 1.0006596 1.0053079 0.9998968 1.0001366 1.0010912 0.9990738 1.000009... [ 2019-03-21 16:52:49,610 ] [ DEBUG ] [ infer:165 ] Outputs: [ 2019-03-21 16:52:49,622 ] [ DEBUG ] [ infer:40 ] output[0]: shape = [256], value = [1.0005053 1.0223469 1.0006596 1.0053079 0.9998968 1.0001366 1.0010912 0.9990738 1.000009... [ 2019-03-21 16:52:49,623 ] [ DEBUG ] [ infer:150 ] -------------------- [ 2019-03-21 16:52:49,623 ] [ DEBUG ] [ infer:151 ] Partial infer for spatial_temporal_network/motion/conblock_3/bn/batchnorm/mul [ 2019-03-21 16:52:49,623 ] [ DEBUG ] [ infer:152 ] Op: Mul [ 2019-03-21 16:52:49,624 ] [ DEBUG ] [ infer:163 ] Inputs: [ 2019-03-21 16:52:49,633 ] [ DEBUG ] [ infer:40 ] input[1]: shape = [256], value = [1.0005053 1.0223469 1.0006596 1.0053079 0.9998968 1.0001366 1.0010912 0.9990738 1.000009... [ 2019-03-21 16:52:49,644 ] [ DEBUG ] [ infer:40 ] input[0]: shape = [256], value = [0.9995004 0.9995004 0.9995004 0.9995004 0.9995004 0.9995004 0.9995004 0.9995004 0.9995004 0.999... [ 2019-03-21 16:52:49,644 ] [ DEBUG ] [ infer:165 ] Outputs: [ 2019-03-21 16:52:49,653 ] [ DEBUG ] [ infer:40 ] output[0]: shape = [256], value = [1.0000055 1.021836 1.0001596 1.0048057 0.9993973 0.99963695 1.000591 0.9985747 0.99951... [ 2019-03-21 16:52:49,654 ] [ DEBUG ] [ infer:150 ] -------------------- [ 2019-03-21 16:52:49,654 ] [ DEBUG ] [ infer:151 ] Partial infer for spatial_temporal_network/motion/conblock_3/bn/batchnorm/mul_2 [ 2019-03-21 16:52:49,654 ] [ DEBUG ] [ infer:152 ] Op: Mul [ 2019-03-21 16:52:49,655 ] [ DEBUG ] [ infer:163 ] Inputs: [ 2019-03-21 16:52:49,664 ] [ DEBUG ] [ infer:40 ] input[0]: shape = [256], value = [0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0.... [ 2019-03-21 16:52:49,675 ] [ DEBUG ] [ infer:40 ] input[1]: shape = [256], value = [1.0000055 1.021836 1.0001596 1.0048057 0.9993973 0.99963695 1.000591 0.9985747 0.99951... [ 2019-03-21 16:52:49,675 ] [ DEBUG ] [ infer:165 ] Outputs: [ 2019-03-21 16:52:49,685 ] [ DEBUG ] [ infer:40 ] output[0]: shape = [256], value = [0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0.... [ 2019-03-21 16:52:49,685 ] [ DEBUG ] [ infer:150 ] -------------------- [ 2019-03-21 16:52:49,686 ] [ DEBUG ] [ infer:151 ] Partial infer for spatial_temporal_network/motion/conblock_3/bn/batchnorm/sub/negate_ [ 2019-03-21 16:52:49,686 ] [ DEBUG ] [ infer:152 ] Op: Power [ 2019-03-21 16:52:49,687 ] [ DEBUG ] [ infer:163 ] Inputs: [ 2019-03-21 16:52:49,694 ] [ DEBUG ] [ infer:40 ] input[0]: shape = [256], value = [0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0.... [ 2019-03-21 16:52:49,694 ] [ DEBUG ] [ infer:165 ] Outputs: [ 2019-03-21 16:52:49,700 ] [ DEBUG ] [ infer:40 ] output[0]: shape = [256], value = [0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0.... [ 2019-03-21 16:52:49,701 ] [ DEBUG ] [ infer:150 ] -------------------- [ 2019-03-21 16:52:49,701 ] [ DEBUG ] [ infer:151 ] Partial infer for spatial_temporal_network/motion/conblock_3/bn/batchnorm/sub/add_ [ 2019-03-21 16:52:49,702 ] [ DEBUG ] [ infer:152 ] Op: Add [ 2019-03-21 16:52:49,703 ] [ DEBUG ] [ infer:163 ] Inputs: [ 2019-03-21 16:52:49,710 ] [ DEBUG ] [ infer:40 ] input[0]: shape = [256], value = [ 1.12557262e-02 1.98826529e-02 9.55713633e-03 4.63132225e-02 -5.92820998e-03 1.76003464e-02... [ 2019-03-21 16:52:49,717 ] [ DEBUG ] [ infer:40 ] input[1]: shape = [256], value = [0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0.... [ 2019-03-21 16:52:49,717 ] [ DEBUG ] [ infer:165 ] Outputs: [ 2019-03-21 16:52:49,727 ] [ DEBUG ] [ infer:40 ] output[0]: shape = [256], value = [ 1.12557262e-02 1.98826529e-02 9.55713633e-03 4.63132225e-02 -5.92820998e-03 1.76003464e-02... [ 2019-03-21 16:52:49,728 ] [ DEBUG ] [ infer:150 ] -------------------- [ 2019-03-21 16:52:49,728 ] [ DEBUG ] [ infer:151 ] Partial infer for spatial_temporal_network/motion/conblock_3/cov/conv1d/ExpandDims_1/dim [ 2019-03-21 16:52:49,728 ] [ DEBUG ] [ infer:152 ] Op: Const [ 2019-03-21 16:52:49,729 ] [ DEBUG ] [ infer:163 ] Inputs: [ 2019-03-21 16:52:49,729 ] [ DEBUG ] [ infer:165 ] Outputs: [ 2019-03-21 16:52:49,730 ] [ DEBUG ] [ infer:40 ] output[0]: shape = [], value = 0 [ 2019-03-21 16:52:49,730 ] [ DEBUG ] [ infer:150 ] -------------------- [ 2019-03-21 16:52:49,730 ] [ DEBUG ] [ infer:151 ] Partial infer for spatial_temporal_network/motion/conblock_3/cov/conv1d/ExpandDims/dim [ 2019-03-21 16:52:49,730 ] [ DEBUG ] [ infer:152 ] Op: Const [ 2019-03-21 16:52:49,731 ] [ DEBUG ] [ infer:163 ] Inputs: [ 2019-03-21 16:52:49,731 ] [ DEBUG ] [ infer:165 ] Outputs: [ 2019-03-21 16:52:49,731 ] [ DEBUG ] [ infer:40 ] output[0]: shape = [], value = 1 [ 2019-03-21 16:52:49,732 ] [ DEBUG ] [ infer:150 ] -------------------- [ 2019-03-21 16:52:49,732 ] [ DEBUG ] [ infer:151 ] Partial infer for spatial_temporal_network/motion/conblock_3/cov/bias [ 2019-03-21 16:52:49,732 ] [ DEBUG ] [ infer:152 ] Op: Const [ 2019-03-21 16:52:49,732 ] [ DEBUG ] [ infer:163 ] Inputs: [ 2019-03-21 16:52:49,732 ] [ DEBUG ] [ infer:165 ] Outputs: [ 2019-03-21 16:52:49,744 ] [ DEBUG ] [ infer:40 ] output[0]: shape = [256], value = [ 1.12529919e-02 2.01415345e-02 9.55318753e-03 4.63739149e-02 -5.92489168e-03 1.75937712e-02... [ 2019-03-21 16:52:49,745 ] [ DEBUG ] [ infer:150 ] -------------------- [ 2019-03-21 16:52:49,746 ] [ DEBUG ] [ infer:151 ] Partial infer for spatial_temporal_network/motion/conblock_3/cov/bias/read [ 2019-03-21 16:52:49,746 ] [ DEBUG ] [ infer:152 ] Op: Identity [ 2019-03-21 16:52:49,747 ] [ DEBUG ] [ infer:163 ] Inputs: [ 2019-03-21 16:52:49,754 ] [ DEBUG ] [ infer:40 ] input[0]: shape = [256], value = [ 1.12529919e-02 2.01415345e-02 9.55318753e-03 4.63739149e-02 -5.92489168e-03 1.75937712e-02... [ 2019-03-21 16:52:49,755 ] [ DEBUG ] [ infer:165 ] Outputs: [ 2019-03-21 16:52:49,762 ] [ DEBUG ] [ infer:40 ] output[0]: shape = [256], value = [ 1.12529919e-02 2.01415345e-02 9.55318753e-03 4.63739149e-02 -5.92489168e-03 1.75937712e-02... [ 2019-03-21 16:52:49,762 ] [ DEBUG ] [ infer:150 ] -------------------- [ 2019-03-21 16:52:49,763 ] [ DEBUG ] [ infer:151 ] Partial infer for spatial_temporal_network/motion/conblock_3/cov/kernel [ 2019-03-21 16:52:49,763 ] [ DEBUG ] [ infer:152 ] Op: Const [ 2019-03-21 16:52:49,763 ] [ DEBUG ] [ infer:163 ] Inputs: [ 2019-03-21 16:52:49,763 ] [ DEBUG ] [ infer:165 ] Outputs: [ 2019-03-21 16:52:49,766 ] [ DEBUG ] [ infer:40 ] output[0]: shape = [ 3 128 256], value = [[[ 0.05045054 0.05083888 0.02092816 ... -0.03865567 -0.14738685 -0.07135887] [ 0.0071032 ... [ 2019-03-21 16:52:49,767 ] [ DEBUG ] [ infer:150 ] -------------------- [ 2019-03-21 16:52:49,767 ] [ DEBUG ] [ infer:151 ] Partial infer for spatial_temporal_network/motion/conblock_3/cov/kernel/read [ 2019-03-21 16:52:49,767 ] [ DEBUG ] [ infer:152 ] Op: Identity [ 2019-03-21 16:52:49,769 ] [ DEBUG ] [ infer:163 ] Inputs: [ 2019-03-21 16:52:49,774 ] [ DEBUG ] [ infer:40 ] input[0]: shape = [ 3 128 256], value = [[[ 0.05045054 0.05083888 0.02092816 ... -0.03865567 -0.14738685 -0.07135887] [ 0.0071032 ... [ 2019-03-21 16:52:49,774 ] [ DEBUG ] [ infer:165 ] Outputs: [ 2019-03-21 16:52:49,779 ] [ DEBUG ] [ infer:40 ] output[0]: shape = [ 3 128 256], value = [[[ 0.05045054 0.05083888 0.02092816 ... -0.03865567 -0.14738685 -0.07135887] [ 0.0071032 ... [ 2019-03-21 16:52:49,780 ] [ DEBUG ] [ infer:150 ] -------------------- [ 2019-03-21 16:52:49,780 ] [ DEBUG ] [ infer:151 ] Partial infer for spatial_temporal_network/motion/conblock_3/cov/conv1d/ExpandDims_1 [ 2019-03-21 16:52:49,780 ] [ DEBUG ] [ infer:152 ] Op: ExpandDims [ 2019-03-21 16:52:49,781 ] [ DEBUG ] [ infer:163 ] Inputs: [ 2019-03-21 16:52:49,787 ] [ DEBUG ] [ infer:40 ] input[0]: shape = [ 3 128 256], value = [[[ 0.05045054 0.05083888 0.02092816 ... -0.03865567 -0.14738685 -0.07135887] [ 0.0071032 ... [ 2019-03-21 16:52:49,787 ] [ DEBUG ] [ infer:165 ] Outputs: [ 2019-03-21 16:52:49,791 ] [ DEBUG ] [ infer:40 ] output[0]: shape = [ 1 3 128 256], value = [[[[ 0.05045054 0.05083888 0.02092816 ... -0.03865567 -0.14738685 -0.07135887] [ 0.00710... [ 2019-03-21 16:52:49,791 ] [ DEBUG ] [ infer:150 ] -------------------- [ 2019-03-21 16:52:49,791 ] [ DEBUG ] [ infer:151 ] Partial infer for spatial_temporal_network/motion/conblock_2/bn/batchnorm/add/y [ 2019-03-21 16:52:49,791 ] [ DEBUG ] [ infer:152 ] Op: Const [ 2019-03-21 16:52:49,792 ] [ DEBUG ] [ infer:163 ] Inputs: [ 2019-03-21 16:52:49,792 ] [ DEBUG ] [ infer:165 ] Outputs: [ 2019-03-21 16:52:49,792 ] [ DEBUG ] [ infer:40 ] output[0]: shape = [], value = 0.001 [ 2019-03-21 16:52:49,793 ] [ DEBUG ] [ infer:150 ] -------------------- [ 2019-03-21 16:52:49,793 ] [ DEBUG ] [ infer:151 ] Partial infer for spatial_temporal_network/motion/conblock_2/bn/moving_variance [ 2019-03-21 16:52:49,793 ] [ DEBUG ] [ infer:152 ] Op: Const [ 2019-03-21 16:52:49,793 ] [ DEBUG ] [ infer:163 ] Inputs: [ 2019-03-21 16:52:49,793 ] [ DEBUG ] [ infer:165 ] Outputs: [ 2019-03-21 16:52:49,798 ] [ DEBUG ] [ infer:40 ] output[0]: shape = [128], value = [1. 1. 1. 1. 1. 1. 1. 1. 1. 1. 1. 1. 1. 1. 1. 1. 1. 1. 1. 1. 1. 1. 1. 1. 1. 1. 1. 1. 1. 1. 1. 1.... [ 2019-03-21 16:52:49,799 ] [ DEBUG ] [ infer:150 ] -------------------- [ 2019-03-21 16:52:49,799 ] [ DEBUG ] [ infer:151 ] Partial infer for spatial_temporal_network/motion/conblock_2/bn/moving_variance/read [ 2019-03-21 16:52:49,799 ] [ DEBUG ] [ infer:152 ] Op: Identity [ 2019-03-21 16:52:49,799 ] [ DEBUG ] [ infer:163 ] Inputs: [ 2019-03-21 16:52:49,805 ] [ DEBUG ] [ infer:40 ] input[0]: shape = [128], value = [1. 1. 1. 1. 1. 1. 1. 1. 1. 1. 1. 1. 1. 1. 1. 1. 1. 1. 1. 1. 1. 1. 1. 1. 1. 1. 1. 1. 1. 1. 1. 1.... [ 2019-03-21 16:52:49,805 ] [ DEBUG ] [ infer:165 ] Outputs: [ 2019-03-21 16:52:49,809 ] [ DEBUG ] [ infer:40 ] output[0]: shape = [128], value = [1. 1. 1. 1. 1. 1. 1. 1. 1. 1. 1. 1. 1. 1. 1. 1. 1. 1. 1. 1. 1. 1. 1. 1. 1. 1. 1. 1. 1. 1. 1. 1.... [ 2019-03-21 16:52:49,809 ] [ DEBUG ] [ infer:150 ] -------------------- [ 2019-03-21 16:52:49,809 ] [ DEBUG ] [ infer:151 ] Partial infer for spatial_temporal_network/motion/conblock_2/bn/batchnorm/add [ 2019-03-21 16:52:49,810 ] [ DEBUG ] [ infer:152 ] Op: Add [ 2019-03-21 16:52:49,810 ] [ DEBUG ] [ infer:163 ] Inputs: [ 2019-03-21 16:52:49,813 ] [ DEBUG ] [ infer:40 ] input[0]: shape = [128], value = [1. 1. 1. 1. 1. 1. 1. 1. 1. 1. 1. 1. 1. 1. 1. 1. 1. 1. 1. 1. 1. 1. 1. 1. 1. 1. 1. 1. 1. 1. 1. 1.... [ 2019-03-21 16:52:49,814 ] [ DEBUG ] [ infer:40 ] input[1]: shape = [], value = 0.001 [ 2019-03-21 16:52:49,814 ] [ DEBUG ] [ infer:165 ] Outputs: [ 2019-03-21 16:52:49,817 ] [ DEBUG ] [ infer:40 ] output[0]: shape = [128], value = [1.001 1.001 1.001 1.001 1.001 1.001 1.001 1.001 1.001 1.001 1.001 1.001 1.001 1.001 1.001 1.001... [ 2019-03-21 16:52:49,817 ] [ DEBUG ] [ infer:150 ] -------------------- [ 2019-03-21 16:52:49,818 ] [ DEBUG ] [ infer:151 ] Partial infer for spatial_temporal_network/motion/conblock_2/bn/batchnorm/Rsqrt [ 2019-03-21 16:52:49,818 ] [ DEBUG ] [ infer:152 ] Op: Rsqrt [ 2019-03-21 16:52:49,818 ] [ DEBUG ] [ infer:163 ] Inputs: [ 2019-03-21 16:52:49,822 ] [ DEBUG ] [ infer:40 ] input[0]: shape = [128], value = [1.001 1.001 1.001 1.001 1.001 1.001 1.001 1.001 1.001 1.001 1.001 1.001 1.001 1.001 1.001 1.001... [ 2019-03-21 16:52:49,822 ] [ DEBUG ] [ infer:165 ] Outputs: [ 2019-03-21 16:52:49,825 ] [ DEBUG ] [ infer:40 ] output[0]: shape = [128], value = [0.9995004 0.9995004 0.9995004 0.9995004 0.9995004 0.9995004 0.9995004 0.9995004 0.9995004 0.999... [ 2019-03-21 16:52:49,825 ] [ DEBUG ] [ infer:150 ] -------------------- [ 2019-03-21 16:52:49,826 ] [ DEBUG ] [ infer:151 ] Partial infer for spatial_temporal_network/motion/conblock_2/bn/moving_mean [ 2019-03-21 16:52:49,826 ] [ DEBUG ] [ infer:152 ] Op: Const [ 2019-03-21 16:52:49,826 ] [ DEBUG ] [ infer:163 ] Inputs: [ 2019-03-21 16:52:49,826 ] [ DEBUG ] [ infer:165 ] Outputs: [ 2019-03-21 16:52:49,830 ] [ DEBUG ] [ infer:40 ] output[0]: shape = [128], value = [0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0.... [ 2019-03-21 16:52:49,831 ] [ DEBUG ] [ infer:150 ] -------------------- [ 2019-03-21 16:52:49,831 ] [ DEBUG ] [ infer:151 ] Partial infer for spatial_temporal_network/motion/conblock_2/bn/moving_mean/read [ 2019-03-21 16:52:49,831 ] [ DEBUG ] [ infer:152 ] Op: Identity [ 2019-03-21 16:52:49,831 ] [ DEBUG ] [ infer:163 ] Inputs: [ 2019-03-21 16:52:49,834 ] [ DEBUG ] [ infer:40 ] input[0]: shape = [128], value = [0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0.... [ 2019-03-21 16:52:49,834 ] [ DEBUG ] [ infer:165 ] Outputs: [ 2019-03-21 16:52:49,838 ] [ DEBUG ] [ infer:40 ] output[0]: shape = [128], value = [0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0.... [ 2019-03-21 16:52:49,838 ] [ DEBUG ] [ infer:150 ] -------------------- [ 2019-03-21 16:52:49,839 ] [ DEBUG ] [ infer:151 ] Partial infer for spatial_temporal_network/motion/conblock_2/bn/beta [ 2019-03-21 16:52:49,839 ] [ DEBUG ] [ infer:152 ] Op: Const [ 2019-03-21 16:52:49,839 ] [ DEBUG ] [ infer:163 ] Inputs: [ 2019-03-21 16:52:49,839 ] [ DEBUG ] [ infer:165 ] Outputs: [ 2019-03-21 16:52:49,842 ] [ DEBUG ] [ infer:40 ] output[0]: shape = [128], value = [ 0.03457135 -0.00338286 0.0029945 0.00918203 -0.01435596 0.01305742 0.02449914 -0.00520663... [ 2019-03-21 16:52:49,843 ] [ DEBUG ] [ infer:150 ] -------------------- [ 2019-03-21 16:52:49,843 ] [ DEBUG ] [ infer:151 ] Partial infer for spatial_temporal_network/motion/conblock_2/bn/beta/read [ 2019-03-21 16:52:49,843 ] [ DEBUG ] [ infer:152 ] Op: Identity [ 2019-03-21 16:52:49,844 ] [ DEBUG ] [ infer:163 ] Inputs: [ 2019-03-21 16:52:49,849 ] [ DEBUG ] [ infer:40 ] input[0]: shape = [128], value = [ 0.03457135 -0.00338286 0.0029945 0.00918203 -0.01435596 0.01305742 0.02449914 -0.00520663... [ 2019-03-21 16:52:49,849 ] [ DEBUG ] [ infer:165 ] Outputs: [ 2019-03-21 16:52:49,854 ] [ DEBUG ] [ infer:40 ] output[0]: shape = [128], value = [ 0.03457135 -0.00338286 0.0029945 0.00918203 -0.01435596 0.01305742 0.02449914 -0.00520663... [ 2019-03-21 16:52:49,855 ] [ DEBUG ] [ infer:150 ] -------------------- [ 2019-03-21 16:52:49,855 ] [ DEBUG ] [ infer:151 ] Partial infer for spatial_temporal_network/motion/conblock_2/bn/gamma [ 2019-03-21 16:52:49,855 ] [ DEBUG ] [ infer:152 ] Op: Const [ 2019-03-21 16:52:49,855 ] [ DEBUG ] [ infer:163 ] Inputs: [ 2019-03-21 16:52:49,855 ] [ DEBUG ] [ infer:165 ] Outputs: [ 2019-03-21 16:52:49,859 ] [ DEBUG ] [ infer:40 ] output[0]: shape = [128], value = [1.0047828 0.9999741 1.0000383 1.0022126 0.99973905 1.021062 1.0131278 0.9998973 1.0015028... [ 2019-03-21 16:52:49,859 ] [ DEBUG ] [ infer:150 ] -------------------- [ 2019-03-21 16:52:49,860 ] [ DEBUG ] [ infer:151 ] Partial infer for spatial_temporal_network/motion/conblock_2/bn/gamma/read [ 2019-03-21 16:52:49,860 ] [ DEBUG ] [ infer:152 ] Op: Identity [ 2019-03-21 16:52:49,860 ] [ DEBUG ] [ infer:163 ] Inputs: [ 2019-03-21 16:52:49,863 ] [ DEBUG ] [ infer:40 ] input[0]: shape = [128], value = [1.0047828 0.9999741 1.0000383 1.0022126 0.99973905 1.021062 1.0131278 0.9998973 1.0015028... [ 2019-03-21 16:52:49,864 ] [ DEBUG ] [ infer:165 ] Outputs: [ 2019-03-21 16:52:49,869 ] [ DEBUG ] [ infer:40 ] output[0]: shape = [128], value = [1.0047828 0.9999741 1.0000383 1.0022126 0.99973905 1.021062 1.0131278 0.9998973 1.0015028... [ 2019-03-21 16:52:49,869 ] [ DEBUG ] [ infer:150 ] -------------------- [ 2019-03-21 16:52:49,869 ] [ DEBUG ] [ infer:151 ] Partial infer for spatial_temporal_network/motion/conblock_2/bn/batchnorm/mul [ 2019-03-21 16:52:49,870 ] [ DEBUG ] [ infer:152 ] Op: Mul [ 2019-03-21 16:52:49,871 ] [ DEBUG ] [ infer:163 ] Inputs: [ 2019-03-21 16:52:49,874 ] [ DEBUG ] [ infer:40 ] input[1]: shape = [128], value = [1.0047828 0.9999741 1.0000383 1.0022126 0.99973905 1.021062 1.0131278 0.9998973 1.0015028... [ 2019-03-21 16:52:49,878 ] [ DEBUG ] [ infer:40 ] input[0]: shape = [128], value = [0.9995004 0.9995004 0.9995004 0.9995004 0.9995004 0.9995004 0.9995004 0.9995004 0.9995004 0.999... [ 2019-03-21 16:52:49,878 ] [ DEBUG ] [ infer:165 ] Outputs: [ 2019-03-21 16:52:49,882 ] [ DEBUG ] [ infer:40 ] output[0]: shape = [128], value = [1.0042808 0.99947447 0.99953866 1.001712 0.99923956 1.0205519 1.0126216 0.99939775 1.001002... [ 2019-03-21 16:52:49,883 ] [ DEBUG ] [ infer:150 ] -------------------- [ 2019-03-21 16:52:49,883 ] [ DEBUG ] [ infer:151 ] Partial infer for spatial_temporal_network/motion/conblock_2/bn/batchnorm/mul_2 [ 2019-03-21 16:52:49,883 ] [ DEBUG ] [ infer:152 ] Op: Mul [ 2019-03-21 16:52:49,883 ] [ DEBUG ] [ infer:163 ] Inputs: [ 2019-03-21 16:52:49,888 ] [ DEBUG ] [ infer:40 ] input[0]: shape = [128], value = [0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0.... [ 2019-03-21 16:52:49,893 ] [ DEBUG ] [ infer:40 ] input[1]: shape = [128], value = [1.0042808 0.99947447 0.99953866 1.001712 0.99923956 1.0205519 1.0126216 0.99939775 1.001002... [ 2019-03-21 16:52:49,893 ] [ DEBUG ] [ infer:165 ] Outputs: [ 2019-03-21 16:52:49,898 ] [ DEBUG ] [ infer:40 ] output[0]: shape = [128], value = [0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0.... [ 2019-03-21 16:52:49,899 ] [ DEBUG ] [ infer:150 ] -------------------- [ 2019-03-21 16:52:49,899 ] [ DEBUG ] [ infer:151 ] Partial infer for spatial_temporal_network/motion/conblock_2/bn/batchnorm/sub/negate_ [ 2019-03-21 16:52:49,899 ] [ DEBUG ] [ infer:152 ] Op: Power [ 2019-03-21 16:52:49,900 ] [ DEBUG ] [ infer:163 ] Inputs: [ 2019-03-21 16:52:49,905 ] [ DEBUG ] [ infer:40 ] input[0]: shape = [128], value = [0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0.... [ 2019-03-21 16:52:49,905 ] [ DEBUG ] [ infer:165 ] Outputs: [ 2019-03-21 16:52:49,910 ] [ DEBUG ] [ infer:40 ] output[0]: shape = [128], value = [0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0.... [ 2019-03-21 16:52:49,910 ] [ DEBUG ] [ infer:150 ] -------------------- [ 2019-03-21 16:52:49,911 ] [ DEBUG ] [ infer:151 ] Partial infer for spatial_temporal_network/motion/conblock_2/bn/batchnorm/sub/add_ [ 2019-03-21 16:52:49,911 ] [ DEBUG ] [ infer:152 ] Op: Add [ 2019-03-21 16:52:49,912 ] [ DEBUG ] [ infer:163 ] Inputs: [ 2019-03-21 16:52:49,917 ] [ DEBUG ] [ infer:40 ] input[0]: shape = [128], value = [ 0.03457135 -0.00338286 0.0029945 0.00918203 -0.01435596 0.01305742 0.02449914 -0.00520663... [ 2019-03-21 16:52:49,923 ] [ DEBUG ] [ infer:40 ] input[1]: shape = [128], value = [0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0.... [ 2019-03-21 16:52:49,923 ] [ DEBUG ] [ infer:165 ] Outputs: [ 2019-03-21 16:52:49,926 ] [ DEBUG ] [ infer:40 ] output[0]: shape = [128], value = [ 0.03457135 -0.00338286 0.0029945 0.00918203 -0.01435596 0.01305742 0.02449914 -0.00520663... [ 2019-03-21 16:52:49,927 ] [ DEBUG ] [ infer:150 ] -------------------- [ 2019-03-21 16:52:49,927 ] [ DEBUG ] [ infer:151 ] Partial infer for spatial_temporal_network/motion/conblock_2/cov/conv1d/ExpandDims_1/dim [ 2019-03-21 16:52:49,927 ] [ DEBUG ] [ infer:152 ] Op: Const [ 2019-03-21 16:52:49,927 ] [ DEBUG ] [ infer:163 ] Inputs: [ 2019-03-21 16:52:49,928 ] [ DEBUG ] [ infer:165 ] Outputs: [ 2019-03-21 16:52:49,928 ] [ DEBUG ] [ infer:40 ] output[0]: shape = [], value = 0 [ 2019-03-21 16:52:49,928 ] [ DEBUG ] [ infer:150 ] -------------------- [ 2019-03-21 16:52:49,929 ] [ DEBUG ] [ infer:151 ] Partial infer for spatial_temporal_network/motion/conblock_2/cov/conv1d/ExpandDims/dim [ 2019-03-21 16:52:49,929 ] [ DEBUG ] [ infer:152 ] Op: Const [ 2019-03-21 16:52:49,929 ] [ DEBUG ] [ infer:163 ] Inputs: [ 2019-03-21 16:52:49,930 ] [ DEBUG ] [ infer:165 ] Outputs: [ 2019-03-21 16:52:49,930 ] [ DEBUG ] [ infer:40 ] output[0]: shape = [], value = 1 [ 2019-03-21 16:52:49,930 ] [ DEBUG ] [ infer:150 ] -------------------- [ 2019-03-21 16:52:49,930 ] [ DEBUG ] [ infer:151 ] Partial infer for spatial_temporal_network/motion/conblock_2/cov/bias [ 2019-03-21 16:52:49,931 ] [ DEBUG ] [ infer:152 ] Op: Const [ 2019-03-21 16:52:49,931 ] [ DEBUG ] [ infer:163 ] Inputs: [ 2019-03-21 16:52:49,931 ] [ DEBUG ] [ infer:165 ] Outputs: [ 2019-03-21 16:52:49,935 ] [ DEBUG ] [ infer:40 ] output[0]: shape = [128], value = [ 0.03464565 -0.00338112 0.00299308 0.00915942 -0.01434684 0.01314972 0.02465082 -0.00520379... [ 2019-03-21 16:52:49,936 ] [ DEBUG ] [ infer:150 ] -------------------- [ 2019-03-21 16:52:49,936 ] [ DEBUG ] [ infer:151 ] Partial infer for spatial_temporal_network/motion/conblock_2/cov/bias/read [ 2019-03-21 16:52:49,936 ] [ DEBUG ] [ infer:152 ] Op: Identity [ 2019-03-21 16:52:49,937 ] [ DEBUG ] [ infer:163 ] Inputs: [ 2019-03-21 16:52:49,940 ] [ DEBUG ] [ infer:40 ] input[0]: shape = [128], value = [ 0.03464565 -0.00338112 0.00299308 0.00915942 -0.01434684 0.01314972 0.02465082 -0.00520379... [ 2019-03-21 16:52:49,940 ] [ DEBUG ] [ infer:165 ] Outputs: [ 2019-03-21 16:52:49,948 ] [ DEBUG ] [ infer:40 ] output[0]: shape = [128], value = [ 0.03464565 -0.00338112 0.00299308 0.00915942 -0.01434684 0.01314972 0.02465082 -0.00520379... [ 2019-03-21 16:52:49,948 ] [ DEBUG ] [ infer:150 ] -------------------- [ 2019-03-21 16:52:49,949 ] [ DEBUG ] [ infer:151 ] Partial infer for spatial_temporal_network/motion/conblock_2/cov/kernel [ 2019-03-21 16:52:49,949 ] [ DEBUG ] [ infer:152 ] Op: Const [ 2019-03-21 16:52:49,949 ] [ DEBUG ] [ infer:163 ] Inputs: [ 2019-03-21 16:52:49,949 ] [ DEBUG ] [ infer:165 ] Outputs: [ 2019-03-21 16:52:49,956 ] [ DEBUG ] [ infer:40 ] output[0]: shape = [ 3 64 128], value = [[[-0.11197457 -0.0777042 0.11070485 ... -0.05704582 0.09222797 0.02990874] [ 0.08435752... [ 2019-03-21 16:52:49,956 ] [ DEBUG ] [ infer:150 ] -------------------- [ 2019-03-21 16:52:49,956 ] [ DEBUG ] [ infer:151 ] Partial infer for spatial_temporal_network/motion/conblock_2/cov/kernel/read [ 2019-03-21 16:52:49,957 ] [ DEBUG ] [ infer:152 ] Op: Identity [ 2019-03-21 16:52:49,957 ] [ DEBUG ] [ infer:163 ] Inputs: [ 2019-03-21 16:52:49,963 ] [ DEBUG ] [ infer:40 ] input[0]: shape = [ 3 64 128], value = [[[-0.11197457 -0.0777042 0.11070485 ... -0.05704582 0.09222797 0.02990874] [ 0.08435752... [ 2019-03-21 16:52:49,963 ] [ DEBUG ] [ infer:165 ] Outputs: [ 2019-03-21 16:52:49,969 ] [ DEBUG ] [ infer:40 ] output[0]: shape = [ 3 64 128], value = [[[-0.11197457 -0.0777042 0.11070485 ... -0.05704582 0.09222797 0.02990874] [ 0.08435752... [ 2019-03-21 16:52:49,970 ] [ DEBUG ] [ infer:150 ] -------------------- [ 2019-03-21 16:52:49,970 ] [ DEBUG ] [ infer:151 ] Partial infer for spatial_temporal_network/motion/conblock_2/cov/conv1d/ExpandDims_1 [ 2019-03-21 16:52:49,971 ] [ DEBUG ] [ infer:152 ] Op: ExpandDims [ 2019-03-21 16:52:49,972 ] [ DEBUG ] [ infer:163 ] Inputs: [ 2019-03-21 16:52:49,977 ] [ DEBUG ] [ infer:40 ] input[0]: shape = [ 3 64 128], value = [[[-0.11197457 -0.0777042 0.11070485 ... -0.05704582 0.09222797 0.02990874] [ 0.08435752... [ 2019-03-21 16:52:49,977 ] [ DEBUG ] [ infer:165 ] Outputs: [ 2019-03-21 16:52:49,987 ] [ DEBUG ] [ infer:40 ] output[0]: shape = [ 1 3 64 128], value = [[[[-0.11197457 -0.0777042 0.11070485 ... -0.05704582 0.09222797 0.02990874] [ 0.08435... [ 2019-03-21 16:52:49,988 ] [ DEBUG ] [ infer:150 ] -------------------- [ 2019-03-21 16:52:49,989 ] [ DEBUG ] [ infer:151 ] Partial infer for spatial_temporal_network/motion/conblock_1/bn/batchnorm/add/y [ 2019-03-21 16:52:49,989 ] [ DEBUG ] [ infer:152 ] Op: Const [ 2019-03-21 16:52:49,989 ] [ DEBUG ] [ infer:163 ] Inputs: [ 2019-03-21 16:52:49,989 ] [ DEBUG ] [ infer:165 ] Outputs: [ 2019-03-21 16:52:49,990 ] [ DEBUG ] [ infer:40 ] output[0]: shape = [], value = 0.001 [ 2019-03-21 16:52:49,992 ] [ DEBUG ] [ infer:150 ] -------------------- [ 2019-03-21 16:52:49,992 ] [ DEBUG ] [ infer:151 ] Partial infer for spatial_temporal_network/motion/conblock_1/bn/moving_variance [ 2019-03-21 16:52:49,992 ] [ DEBUG ] [ infer:152 ] Op: Const [ 2019-03-21 16:52:49,993 ] [ DEBUG ] [ infer:163 ] Inputs: [ 2019-03-21 16:52:49,993 ] [ DEBUG ] [ infer:165 ] Outputs: [ 2019-03-21 16:52:49,996 ] [ DEBUG ] [ infer:40 ] output[0]: shape = [64], value = [1. 1. 1. 1. 1. 1. 1. 1. 1. 1. 1. 1. 1. 1. 1. 1. 1. 1. 1. 1. 1. 1. 1. 1. 1. 1. 1. 1. 1. 1. 1. 1.... [ 2019-03-21 16:52:49,996 ] [ DEBUG ] [ infer:150 ] -------------------- [ 2019-03-21 16:52:49,997 ] [ DEBUG ] [ infer:151 ] Partial infer for spatial_temporal_network/motion/conblock_1/bn/moving_variance/read [ 2019-03-21 16:52:49,997 ] [ DEBUG ] [ infer:152 ] Op: Identity [ 2019-03-21 16:52:49,997 ] [ DEBUG ] [ infer:163 ] Inputs: [ 2019-03-21 16:52:49,999 ] [ DEBUG ] [ infer:40 ] input[0]: shape = [64], value = [1. 1. 1. 1. 1. 1. 1. 1. 1. 1. 1. 1. 1. 1. 1. 1. 1. 1. 1. 1. 1. 1. 1. 1. 1. 1. 1. 1. 1. 1. 1. 1.... [ 2019-03-21 16:52:49,999 ] [ DEBUG ] [ infer:165 ] Outputs: [ 2019-03-21 16:52:50,001 ] [ DEBUG ] [ infer:40 ] output[0]: shape = [64], value = [1. 1. 1. 1. 1. 1. 1. 1. 1. 1. 1. 1. 1. 1. 1. 1. 1. 1. 1. 1. 1. 1. 1. 1. 1. 1. 1. 1. 1. 1. 1. 1.... [ 2019-03-21 16:52:50,002 ] [ DEBUG ] [ infer:150 ] -------------------- [ 2019-03-21 16:52:50,002 ] [ DEBUG ] [ infer:151 ] Partial infer for spatial_temporal_network/motion/conblock_1/bn/batchnorm/add [ 2019-03-21 16:52:50,002 ] [ DEBUG ] [ infer:152 ] Op: Add [ 2019-03-21 16:52:50,003 ] [ DEBUG ] [ infer:163 ] Inputs: [ 2019-03-21 16:52:50,005 ] [ DEBUG ] [ infer:40 ] input[0]: shape = [64], value = [1. 1. 1. 1. 1. 1. 1. 1. 1. 1. 1. 1. 1. 1. 1. 1. 1. 1. 1. 1. 1. 1. 1. 1. 1. 1. 1. 1. 1. 1. 1. 1.... [ 2019-03-21 16:52:50,005 ] [ DEBUG ] [ infer:40 ] input[1]: shape = [], value = 0.001 [ 2019-03-21 16:52:50,006 ] [ DEBUG ] [ infer:165 ] Outputs: [ 2019-03-21 16:52:50,009 ] [ DEBUG ] [ infer:40 ] output[0]: shape = [64], value = [1.001 1.001 1.001 1.001 1.001 1.001 1.001 1.001 1.001 1.001 1.001 1.001 1.001 1.001 1.001 1.001... [ 2019-03-21 16:52:50,009 ] [ DEBUG ] [ infer:150 ] -------------------- [ 2019-03-21 16:52:50,009 ] [ DEBUG ] [ infer:151 ] Partial infer for spatial_temporal_network/motion/conblock_1/bn/batchnorm/Rsqrt [ 2019-03-21 16:52:50,010 ] [ DEBUG ] [ infer:152 ] Op: Rsqrt [ 2019-03-21 16:52:50,010 ] [ DEBUG ] [ infer:163 ] Inputs: [ 2019-03-21 16:52:50,013 ] [ DEBUG ] [ infer:40 ] input[0]: shape = [64], value = [1.001 1.001 1.001 1.001 1.001 1.001 1.001 1.001 1.001 1.001 1.001 1.001 1.001 1.001 1.001 1.001... [ 2019-03-21 16:52:50,014 ] [ DEBUG ] [ infer:165 ] Outputs: [ 2019-03-21 16:52:50,017 ] [ DEBUG ] [ infer:40 ] output[0]: shape = [64], value = [0.9995004 0.9995004 0.9995004 0.9995004 0.9995004 0.9995004 0.9995004 0.9995004 0.9995004 0.999... [ 2019-03-21 16:52:50,017 ] [ DEBUG ] [ infer:150 ] -------------------- [ 2019-03-21 16:52:50,017 ] [ DEBUG ] [ infer:151 ] Partial infer for spatial_temporal_network/motion/conblock_1/bn/moving_mean [ 2019-03-21 16:52:50,017 ] [ DEBUG ] [ infer:152 ] Op: Const [ 2019-03-21 16:52:50,018 ] [ DEBUG ] [ infer:163 ] Inputs: [ 2019-03-21 16:52:50,018 ] [ DEBUG ] [ infer:165 ] Outputs: [ 2019-03-21 16:52:50,020 ] [ DEBUG ] [ infer:40 ] output[0]: shape = [64], value = [0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0.... [ 2019-03-21 16:52:50,021 ] [ DEBUG ] [ infer:150 ] -------------------- [ 2019-03-21 16:52:50,021 ] [ DEBUG ] [ infer:151 ] Partial infer for spatial_temporal_network/motion/conblock_1/bn/moving_mean/read [ 2019-03-21 16:52:50,021 ] [ DEBUG ] [ infer:152 ] Op: Identity [ 2019-03-21 16:52:50,022 ] [ DEBUG ] [ infer:163 ] Inputs: [ 2019-03-21 16:52:50,024 ] [ DEBUG ] [ infer:40 ] input[0]: shape = [64], value = [0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0.... [ 2019-03-21 16:52:50,024 ] [ DEBUG ] [ infer:165 ] Outputs: [ 2019-03-21 16:52:50,027 ] [ DEBUG ] [ infer:40 ] output[0]: shape = [64], value = [0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0.... [ 2019-03-21 16:52:50,028 ] [ DEBUG ] [ infer:150 ] -------------------- [ 2019-03-21 16:52:50,028 ] [ DEBUG ] [ infer:151 ] Partial infer for spatial_temporal_network/motion/conblock_1/bn/beta [ 2019-03-21 16:52:50,028 ] [ DEBUG ] [ infer:152 ] Op: Const [ 2019-03-21 16:52:50,029 ] [ DEBUG ] [ infer:163 ] Inputs: [ 2019-03-21 16:52:50,029 ] [ DEBUG ] [ infer:165 ] Outputs: [ 2019-03-21 16:52:50,033 ] [ DEBUG ] [ infer:40 ] output[0]: shape = [64], value = [-0.02776928 0.00860045 0.00802145 0.02333457 -0.02031355 -0.02512991 0.02157214 -0.00290838... [ 2019-03-21 16:52:50,033 ] [ DEBUG ] [ infer:150 ] -------------------- [ 2019-03-21 16:52:50,034 ] [ DEBUG ] [ infer:151 ] Partial infer for spatial_temporal_network/motion/conblock_1/bn/beta/read [ 2019-03-21 16:52:50,034 ] [ DEBUG ] [ infer:152 ] Op: Identity [ 2019-03-21 16:52:50,035 ] [ DEBUG ] [ infer:163 ] Inputs: [ 2019-03-21 16:52:50,038 ] [ DEBUG ] [ infer:40 ] input[0]: shape = [64], value = [-0.02776928 0.00860045 0.00802145 0.02333457 -0.02031355 -0.02512991 0.02157214 -0.00290838... [ 2019-03-21 16:52:50,039 ] [ DEBUG ] [ infer:165 ] Outputs: [ 2019-03-21 16:52:50,042 ] [ DEBUG ] [ infer:40 ] output[0]: shape = [64], value = [-0.02776928 0.00860045 0.00802145 0.02333457 -0.02031355 -0.02512991 0.02157214 -0.00290838... [ 2019-03-21 16:52:50,043 ] [ DEBUG ] [ infer:150 ] -------------------- [ 2019-03-21 16:52:50,043 ] [ DEBUG ] [ infer:151 ] Partial infer for spatial_temporal_network/motion/conblock_1/bn/gamma [ 2019-03-21 16:52:50,043 ] [ DEBUG ] [ infer:152 ] Op: Const [ 2019-03-21 16:52:50,043 ] [ DEBUG ] [ infer:163 ] Inputs: [ 2019-03-21 16:52:50,043 ] [ DEBUG ] [ infer:165 ] Outputs: [ 2019-03-21 16:52:50,046 ] [ DEBUG ] [ infer:40 ] output[0]: shape = [64], value = [0.9993789 1.0129192 1.0281241 1.0123947 0.9999961 0.9994045 1.0212008 1.0007131 1.013173... [ 2019-03-21 16:52:50,047 ] [ DEBUG ] [ infer:150 ] -------------------- [ 2019-03-21 16:52:50,047 ] [ DEBUG ] [ infer:151 ] Partial infer for spatial_temporal_network/motion/conblock_1/bn/gamma/read [ 2019-03-21 16:52:50,047 ] [ DEBUG ] [ infer:152 ] Op: Identity [ 2019-03-21 16:52:50,048 ] [ DEBUG ] [ infer:163 ] Inputs: [ 2019-03-21 16:52:50,051 ] [ DEBUG ] [ infer:40 ] input[0]: shape = [64], value = [0.9993789 1.0129192 1.0281241 1.0123947 0.9999961 0.9994045 1.0212008 1.0007131 1.013173... [ 2019-03-21 16:52:50,051 ] [ DEBUG ] [ infer:165 ] Outputs: [ 2019-03-21 16:52:50,054 ] [ DEBUG ] [ infer:40 ] output[0]: shape = [64], value = [0.9993789 1.0129192 1.0281241 1.0123947 0.9999961 0.9994045 1.0212008 1.0007131 1.013173... [ 2019-03-21 16:52:50,055 ] [ DEBUG ] [ infer:150 ] -------------------- [ 2019-03-21 16:52:50,055 ] [ DEBUG ] [ infer:151 ] Partial infer for spatial_temporal_network/motion/conblock_1/bn/batchnorm/mul [ 2019-03-21 16:52:50,055 ] [ DEBUG ] [ infer:152 ] Op: Mul [ 2019-03-21 16:52:50,056 ] [ DEBUG ] [ infer:163 ] Inputs: [ 2019-03-21 16:52:50,058 ] [ DEBUG ] [ infer:40 ] input[1]: shape = [64], value = [0.9993789 1.0129192 1.0281241 1.0123947 0.9999961 0.9994045 1.0212008 1.0007131 1.013173... [ 2019-03-21 16:52:50,060 ] [ DEBUG ] [ infer:40 ] input[0]: shape = [64], value = [0.9995004 0.9995004 0.9995004 0.9995004 0.9995004 0.9995004 0.9995004 0.9995004 0.9995004 0.999... [ 2019-03-21 16:52:50,060 ] [ DEBUG ] [ infer:165 ] Outputs: [ 2019-03-21 16:52:50,063 ] [ DEBUG ] [ infer:40 ] output[0]: shape = [64], value = [0.9988796 1.0124131 1.0276104 1.0118889 0.9994965 0.9989052 1.0206906 1.0002131 1.012667... [ 2019-03-21 16:52:50,063 ] [ DEBUG ] [ infer:150 ] -------------------- [ 2019-03-21 16:52:50,064 ] [ DEBUG ] [ infer:151 ] Partial infer for spatial_temporal_network/motion/conblock_1/bn/batchnorm/mul_2 [ 2019-03-21 16:52:50,064 ] [ DEBUG ] [ infer:152 ] Op: Mul [ 2019-03-21 16:52:50,064 ] [ DEBUG ] [ infer:163 ] Inputs: [ 2019-03-21 16:52:50,066 ] [ DEBUG ] [ infer:40 ] input[0]: shape = [64], value = [0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0.... [ 2019-03-21 16:52:50,068 ] [ DEBUG ] [ infer:40 ] input[1]: shape = [64], value = [0.9988796 1.0124131 1.0276104 1.0118889 0.9994965 0.9989052 1.0206906 1.0002131 1.012667... [ 2019-03-21 16:52:50,069 ] [ DEBUG ] [ infer:165 ] Outputs: [ 2019-03-21 16:52:50,071 ] [ DEBUG ] [ infer:40 ] output[0]: shape = [64], value = [0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0.... [ 2019-03-21 16:52:50,071 ] [ DEBUG ] [ infer:150 ] -------------------- [ 2019-03-21 16:52:50,071 ] [ DEBUG ] [ infer:151 ] Partial infer for spatial_temporal_network/motion/conblock_1/bn/batchnorm/sub/negate_ [ 2019-03-21 16:52:50,071 ] [ DEBUG ] [ infer:152 ] Op: Power [ 2019-03-21 16:52:50,072 ] [ DEBUG ] [ infer:163 ] Inputs: [ 2019-03-21 16:52:50,074 ] [ DEBUG ] [ infer:40 ] input[0]: shape = [64], value = [0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0.... [ 2019-03-21 16:52:50,074 ] [ DEBUG ] [ infer:165 ] Outputs: [ 2019-03-21 16:52:50,076 ] [ DEBUG ] [ infer:40 ] output[0]: shape = [64], value = [0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0.... [ 2019-03-21 16:52:50,077 ] [ DEBUG ] [ infer:150 ] -------------------- [ 2019-03-21 16:52:50,077 ] [ DEBUG ] [ infer:151 ] Partial infer for spatial_temporal_network/motion/conblock_1/bn/batchnorm/sub/add_ [ 2019-03-21 16:52:50,078 ] [ DEBUG ] [ infer:152 ] Op: Add [ 2019-03-21 16:52:50,078 ] [ DEBUG ] [ infer:163 ] Inputs: [ 2019-03-21 16:52:50,082 ] [ DEBUG ] [ infer:40 ] input[0]: shape = [64], value = [-0.02776928 0.00860045 0.00802145 0.02333457 -0.02031355 -0.02512991 0.02157214 -0.00290838... [ 2019-03-21 16:52:50,084 ] [ DEBUG ] [ infer:40 ] input[1]: shape = [64], value = [0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0.... [ 2019-03-21 16:52:50,084 ] [ DEBUG ] [ infer:165 ] Outputs: [ 2019-03-21 16:52:50,088 ] [ DEBUG ] [ infer:40 ] output[0]: shape = [64], value = [-0.02776928 0.00860045 0.00802145 0.02333457 -0.02031355 -0.02512991 0.02157214 -0.00290838... [ 2019-03-21 16:52:50,088 ] [ DEBUG ] [ infer:150 ] -------------------- [ 2019-03-21 16:52:50,089 ] [ DEBUG ] [ infer:151 ] Partial infer for spatial_temporal_network/motion/conblock_1/cov/conv1d/ExpandDims_1/dim [ 2019-03-21 16:52:50,089 ] [ DEBUG ] [ infer:152 ] Op: Const [ 2019-03-21 16:52:50,089 ] [ DEBUG ] [ infer:163 ] Inputs: [ 2019-03-21 16:52:50,089 ] [ DEBUG ] [ infer:165 ] Outputs: [ 2019-03-21 16:52:50,089 ] [ DEBUG ] [ infer:40 ] output[0]: shape = [], value = 0 [ 2019-03-21 16:52:50,090 ] [ DEBUG ] [ infer:150 ] -------------------- [ 2019-03-21 16:52:50,090 ] [ DEBUG ] [ infer:151 ] Partial infer for spatial_temporal_network/motion/conblock_1/cov/conv1d/ExpandDims/dim [ 2019-03-21 16:52:50,090 ] [ DEBUG ] [ infer:152 ] Op: Const [ 2019-03-21 16:52:50,090 ] [ DEBUG ] [ infer:163 ] Inputs: [ 2019-03-21 16:52:50,090 ] [ DEBUG ] [ infer:165 ] Outputs: [ 2019-03-21 16:52:50,091 ] [ DEBUG ] [ infer:40 ] output[0]: shape = [], value = 1 [ 2019-03-21 16:52:50,091 ] [ DEBUG ] [ infer:150 ] -------------------- [ 2019-03-21 16:52:50,091 ] [ DEBUG ] [ infer:151 ] Partial infer for spatial_temporal_network/motion/conblock_1/cov/bias [ 2019-03-21 16:52:50,091 ] [ DEBUG ] [ infer:152 ] Op: Const [ 2019-03-21 16:52:50,092 ] [ DEBUG ] [ infer:163 ] Inputs: [ 2019-03-21 16:52:50,092 ] [ DEBUG ] [ infer:165 ] Outputs: [ 2019-03-21 16:52:50,094 ] [ DEBUG ] [ infer:40 ] output[0]: shape = [64], value = [-0.02774801 0.00863148 0.00796828 0.02329118 -0.02030629 -0.02511107 0.02146086 -0.00290665... [ 2019-03-21 16:52:50,094 ] [ DEBUG ] [ infer:150 ] -------------------- [ 2019-03-21 16:52:50,095 ] [ DEBUG ] [ infer:151 ] Partial infer for spatial_temporal_network/motion/conblock_1/cov/bias/read [ 2019-03-21 16:52:50,095 ] [ DEBUG ] [ infer:152 ] Op: Identity [ 2019-03-21 16:52:50,095 ] [ DEBUG ] [ infer:163 ] Inputs: [ 2019-03-21 16:52:50,099 ] [ DEBUG ] [ infer:40 ] input[0]: shape = [64], value = [-0.02774801 0.00863148 0.00796828 0.02329118 -0.02030629 -0.02511107 0.02146086 -0.00290665... [ 2019-03-21 16:52:50,099 ] [ DEBUG ] [ infer:165 ] Outputs: [ 2019-03-21 16:52:50,102 ] [ DEBUG ] [ infer:40 ] output[0]: shape = [64], value = [-0.02774801 0.00863148 0.00796828 0.02329118 -0.02030629 -0.02511107 0.02146086 -0.00290665... [ 2019-03-21 16:52:50,103 ] [ DEBUG ] [ infer:150 ] -------------------- [ 2019-03-21 16:52:50,103 ] [ DEBUG ] [ infer:151 ] Partial infer for spatial_temporal_network/motion/conblock_1/cov/kernel [ 2019-03-21 16:52:50,103 ] [ DEBUG ] [ infer:152 ] Op: Const [ 2019-03-21 16:52:50,103 ] [ DEBUG ] [ infer:163 ] Inputs: [ 2019-03-21 16:52:50,104 ] [ DEBUG ] [ infer:165 ] Outputs: [ 2019-03-21 16:52:50,107 ] [ DEBUG ] [ infer:40 ] output[0]: shape = [ 3 28 64], value = [[[ 0.01322431 0.2028937 -0.03455529 ... 0.2793196 -0.0775563 0.20544897] [ 0.09738392 ... [ 2019-03-21 16:52:50,108 ] [ DEBUG ] [ infer:150 ] -------------------- [ 2019-03-21 16:52:50,108 ] [ DEBUG ] [ infer:151 ] Partial infer for spatial_temporal_network/motion/conblock_1/cov/kernel/read [ 2019-03-21 16:52:50,109 ] [ DEBUG ] [ infer:152 ] Op: Identity [ 2019-03-21 16:52:50,110 ] [ DEBUG ] [ infer:163 ] Inputs: [ 2019-03-21 16:52:50,115 ] [ DEBUG ] [ infer:40 ] input[0]: shape = [ 3 28 64], value = [[[ 0.01322431 0.2028937 -0.03455529 ... 0.2793196 -0.0775563 0.20544897] [ 0.09738392 ... [ 2019-03-21 16:52:50,115 ] [ DEBUG ] [ infer:165 ] Outputs: [ 2019-03-21 16:52:50,121 ] [ DEBUG ] [ infer:40 ] output[0]: shape = [ 3 28 64], value = [[[ 0.01322431 0.2028937 -0.03455529 ... 0.2793196 -0.0775563 0.20544897] [ 0.09738392 ... [ 2019-03-21 16:52:50,122 ] [ DEBUG ] [ infer:150 ] -------------------- [ 2019-03-21 16:52:50,122 ] [ DEBUG ] [ infer:151 ] Partial infer for spatial_temporal_network/motion/conblock_1/cov/conv1d/ExpandDims_1 [ 2019-03-21 16:52:50,122 ] [ DEBUG ] [ infer:152 ] Op: ExpandDims [ 2019-03-21 16:52:50,123 ] [ DEBUG ] [ infer:163 ] Inputs: [ 2019-03-21 16:52:50,129 ] [ DEBUG ] [ infer:40 ] input[0]: shape = [ 3 28 64], value = [[[ 0.01322431 0.2028937 -0.03455529 ... 0.2793196 -0.0775563 0.20544897] [ 0.09738392 ... [ 2019-03-21 16:52:50,129 ] [ DEBUG ] [ infer:165 ] Outputs: [ 2019-03-21 16:52:50,135 ] [ DEBUG ] [ infer:40 ] output[0]: shape = [ 1 3 28 64], value = [[[[ 0.01322431 0.2028937 -0.03455529 ... 0.2793196 -0.0775563 0.20544897] [ 0.097383... [ 2019-03-21 16:52:50,136 ] [ DEBUG ] [ infer:150 ] -------------------- [ 2019-03-21 16:52:50,136 ] [ DEBUG ] [ infer:151 ] Partial infer for input2 [ 2019-03-21 16:52:50,136 ] [ DEBUG ] [ infer:152 ] Op: Placeholder [ 2019-03-21 16:52:50,137 ] [ DEBUG ] [ infer:163 ] Inputs: [ 2019-03-21 16:52:50,137 ] [ DEBUG ] [ infer:165 ] Outputs: [ 2019-03-21 16:52:50,137 ] [ DEBUG ] [ infer:40 ] output[0]: shape = [ 1 30 28], value = [ 2019-03-21 16:52:50,138 ] [ DEBUG ] [ infer:150 ] -------------------- [ 2019-03-21 16:52:50,138 ] [ DEBUG ] [ infer:151 ] Partial infer for spatial_temporal_network/motion/conblock_1/cov/conv1d/ExpandDims [ 2019-03-21 16:52:50,138 ] [ DEBUG ] [ infer:152 ] Op: ExpandDims [ 2019-03-21 16:52:50,139 ] [ DEBUG ] [ infer:163 ] Inputs: [ 2019-03-21 16:52:50,140 ] [ DEBUG ] [ infer:40 ] input[0]: shape = [ 1 30 28], value = [ 2019-03-21 16:52:50,140 ] [ DEBUG ] [ infer:165 ] Outputs: [ 2019-03-21 16:52:50,140 ] [ DEBUG ] [ infer:40 ] output[0]: shape = [ 1 1 30 28], value = [ 2019-03-21 16:52:50,141 ] [ DEBUG ] [ infer:150 ] -------------------- [ 2019-03-21 16:52:50,141 ] [ DEBUG ] [ infer:151 ] Partial infer for spatial_temporal_network/motion/conblock_1/cov/conv1d/Conv2D [ 2019-03-21 16:52:50,141 ] [ DEBUG ] [ infer:152 ] Op: Conv2D [ 2019-03-21 16:52:50,144 ] [ DEBUG ] [ infer:163 ] Inputs: [ 2019-03-21 16:52:50,144 ] [ DEBUG ] [ infer:40 ] input[0]: shape = [ 1 1 30 28], value = [ 2019-03-21 16:52:50,149 ] [ DEBUG ] [ infer:40 ] input[1]: shape = [ 1 3 28 64], value = [[[[ 0.01322431 0.2028937 -0.03455529 ... 0.2793196 -0.0775563 0.20544897] [ 0.097383... [ 2019-03-21 16:52:50,149 ] [ DEBUG ] [ infer:165 ] Outputs: [ 2019-03-21 16:52:50,150 ] [ DEBUG ] [ infer:40 ] output[0]: shape = [ 1 1 30 64], value = [ 2019-03-21 16:52:50,151 ] [ DEBUG ] [ infer:150 ] -------------------- [ 2019-03-21 16:52:50,151 ] [ DEBUG ] [ infer:151 ] Partial infer for spatial_temporal_network/motion/conblock_1/cov/conv1d/Squeeze [ 2019-03-21 16:52:50,151 ] [ DEBUG ] [ infer:152 ] Op: Squeeze [ 2019-03-21 16:52:50,152 ] [ DEBUG ] [ squeeze:43 ] The reshape from "[ 1 1 30 64]" with squeezed dims "[ 1 30 64]" is not a spatial squeeze [ 2019-03-21 16:52:50,152 ] [ DEBUG ] [ infer:163 ] Inputs: [ 2019-03-21 16:52:50,153 ] [ DEBUG ] [ infer:40 ] input[0]: shape = [ 1 1 30 64], value = [ 2019-03-21 16:52:50,153 ] [ DEBUG ] [ infer:165 ] Outputs: [ 2019-03-21 16:52:50,153 ] [ DEBUG ] [ infer:40 ] output[0]: shape = [ 1 30 64], value = [ 2019-03-21 16:52:50,154 ] [ DEBUG ] [ infer:150 ] -------------------- [ 2019-03-21 16:52:50,155 ] [ DEBUG ] [ infer:151 ] Partial infer for spatial_temporal_network/motion/conblock_1/cov/BiasAdd [ 2019-03-21 16:52:50,155 ] [ DEBUG ] [ infer:152 ] Op: Add [ 2019-03-21 16:52:50,155 ] [ DEBUG ] [ infer:163 ] Inputs: [ 2019-03-21 16:52:50,158 ] [ DEBUG ] [ infer:40 ] input[1]: shape = [64], value = [-0.02774801 0.00863148 0.00796828 0.02329118 -0.02030629 -0.02511107 0.02146086 -0.00290665... [ 2019-03-21 16:52:50,158 ] [ DEBUG ] [ infer:40 ] input[0]: shape = [ 1 30 64], value = [ 2019-03-21 16:52:50,159 ] [ DEBUG ] [ infer:165 ] Outputs: [ 2019-03-21 16:52:50,159 ] [ DEBUG ] [ infer:40 ] output[0]: shape = [ 1 30 64], value = [ 2019-03-21 16:52:50,160 ] [ DEBUG ] [ infer:150 ] -------------------- [ 2019-03-21 16:52:50,160 ] [ DEBUG ] [ infer:151 ] Partial infer for spatial_temporal_network/motion/conblock_1/bn/batchnorm/mul_1 [ 2019-03-21 16:52:50,161 ] [ DEBUG ] [ infer:152 ] Op: Mul [ 2019-03-21 16:52:50,161 ] [ DEBUG ] [ infer:163 ] Inputs: [ 2019-03-21 16:52:50,162 ] [ DEBUG ] [ infer:40 ] input[0]: shape = [ 1 30 64], value = [ 2019-03-21 16:52:50,165 ] [ DEBUG ] [ infer:40 ] input[1]: shape = [64], value = [0.9988796 1.0124131 1.0276104 1.0118889 0.9994965 0.9989052 1.0206906 1.0002131 1.012667... [ 2019-03-21 16:52:50,165 ] [ DEBUG ] [ infer:165 ] Outputs: [ 2019-03-21 16:52:50,166 ] [ DEBUG ] [ infer:40 ] output[0]: shape = [ 1 30 64], value = [ 2019-03-21 16:52:50,167 ] [ DEBUG ] [ infer:150 ] -------------------- [ 2019-03-21 16:52:50,168 ] [ DEBUG ] [ infer:151 ] Partial infer for spatial_temporal_network/motion/conblock_1/bn/batchnorm/add_1 [ 2019-03-21 16:52:50,168 ] [ DEBUG ] [ infer:152 ] Op: Add [ 2019-03-21 16:52:50,169 ] [ DEBUG ] [ infer:163 ] Inputs: [ 2019-03-21 16:52:50,169 ] [ DEBUG ] [ infer:40 ] input[0]: shape = [ 1 30 64], value = [ 2019-03-21 16:52:50,175 ] [ DEBUG ] [ infer:40 ] input[1]: shape = [64], value = [-0.02776928 0.00860045 0.00802145 0.02333457 -0.02031355 -0.02512991 0.02157214 -0.00290838... [ 2019-03-21 16:52:50,175 ] [ DEBUG ] [ infer:165 ] Outputs: [ 2019-03-21 16:52:50,176 ] [ DEBUG ] [ infer:40 ] output[0]: shape = [ 1 30 64], value = [ 2019-03-21 16:52:50,177 ] [ DEBUG ] [ infer:150 ] -------------------- [ 2019-03-21 16:52:50,177 ] [ DEBUG ] [ infer:151 ] Partial infer for spatial_temporal_network/motion/conblock_1/Relu [ 2019-03-21 16:52:50,177 ] [ DEBUG ] [ infer:152 ] Op: Relu [ 2019-03-21 16:52:50,178 ] [ DEBUG ] [ infer:163 ] Inputs: [ 2019-03-21 16:52:50,179 ] [ DEBUG ] [ infer:40 ] input[0]: shape = [ 1 30 64], value = [ 2019-03-21 16:52:50,179 ] [ DEBUG ] [ infer:165 ] Outputs: [ 2019-03-21 16:52:50,180 ] [ DEBUG ] [ infer:40 ] output[0]: shape = [ 1 30 64], value = [ 2019-03-21 16:52:50,180 ] [ DEBUG ] [ infer:150 ] -------------------- [ 2019-03-21 16:52:50,181 ] [ DEBUG ] [ infer:151 ] Partial infer for spatial_temporal_network/motion/conblock_2/cov/conv1d/ExpandDims [ 2019-03-21 16:52:50,181 ] [ DEBUG ] [ infer:152 ] Op: ExpandDims [ 2019-03-21 16:52:50,182 ] [ DEBUG ] [ infer:163 ] Inputs: [ 2019-03-21 16:52:50,182 ] [ DEBUG ] [ infer:40 ] input[0]: shape = [ 1 30 64], value = [ 2019-03-21 16:52:50,183 ] [ DEBUG ] [ infer:165 ] Outputs: [ 2019-03-21 16:52:50,183 ] [ DEBUG ] [ infer:40 ] output[0]: shape = [ 1 1 30 64], value = [ 2019-03-21 16:52:50,184 ] [ DEBUG ] [ infer:150 ] -------------------- [ 2019-03-21 16:52:50,184 ] [ DEBUG ] [ infer:151 ] Partial infer for spatial_temporal_network/motion/conblock_2/cov/conv1d/Conv2D [ 2019-03-21 16:52:50,184 ] [ DEBUG ] [ infer:152 ] Op: Conv2D [ 2019-03-21 16:52:50,188 ] [ DEBUG ] [ infer:163 ] Inputs: [ 2019-03-21 16:52:50,188 ] [ DEBUG ] [ infer:40 ] input[0]: shape = [ 1 1 30 64], value = [ 2019-03-21 16:52:50,194 ] [ DEBUG ] [ infer:40 ] input[1]: shape = [ 1 3 64 128], value = [[[[-0.11197457 -0.0777042 0.11070485 ... -0.05704582 0.09222797 0.02990874] [ 0.08435... [ 2019-03-21 16:52:50,194 ] [ DEBUG ] [ infer:165 ] Outputs: [ 2019-03-21 16:52:50,195 ] [ DEBUG ] [ infer:40 ] output[0]: shape = [ 1 1 30 128], value = [ 2019-03-21 16:52:50,195 ] [ DEBUG ] [ infer:150 ] -------------------- [ 2019-03-21 16:52:50,195 ] [ DEBUG ] [ infer:151 ] Partial infer for spatial_temporal_network/motion/conblock_2/cov/conv1d/Squeeze [ 2019-03-21 16:52:50,196 ] [ DEBUG ] [ infer:152 ] Op: Squeeze [ 2019-03-21 16:52:50,197 ] [ DEBUG ] [ squeeze:43 ] The reshape from "[ 1 1 30 128]" with squeezed dims "[ 1 30 128]" is not a spatial squeeze [ 2019-03-21 16:52:50,197 ] [ DEBUG ] [ infer:163 ] Inputs: [ 2019-03-21 16:52:50,198 ] [ DEBUG ] [ infer:40 ] input[0]: shape = [ 1 1 30 128], value = [ 2019-03-21 16:52:50,198 ] [ DEBUG ] [ infer:165 ] Outputs: [ 2019-03-21 16:52:50,198 ] [ DEBUG ] [ infer:40 ] output[0]: shape = [ 1 30 128], value = [ 2019-03-21 16:52:50,199 ] [ DEBUG ] [ infer:150 ] -------------------- [ 2019-03-21 16:52:50,199 ] [ DEBUG ] [ infer:151 ] Partial infer for spatial_temporal_network/motion/conblock_2/cov/BiasAdd [ 2019-03-21 16:52:50,199 ] [ DEBUG ] [ infer:152 ] Op: Add [ 2019-03-21 16:52:50,200 ] [ DEBUG ] [ infer:163 ] Inputs: [ 2019-03-21 16:52:50,205 ] [ DEBUG ] [ infer:40 ] input[1]: shape = [128], value = [ 0.03464565 -0.00338112 0.00299308 0.00915942 -0.01434684 0.01314972 0.02465082 -0.00520379... [ 2019-03-21 16:52:50,206 ] [ DEBUG ] [ infer:40 ] input[0]: shape = [ 1 30 128], value = [ 2019-03-21 16:52:50,206 ] [ DEBUG ] [ infer:165 ] Outputs: [ 2019-03-21 16:52:50,207 ] [ DEBUG ] [ infer:40 ] output[0]: shape = [ 1 30 128], value = [ 2019-03-21 16:52:50,207 ] [ DEBUG ] [ infer:150 ] -------------------- [ 2019-03-21 16:52:50,208 ] [ DEBUG ] [ infer:151 ] Partial infer for spatial_temporal_network/motion/conblock_2/bn/batchnorm/mul_1 [ 2019-03-21 16:52:50,208 ] [ DEBUG ] [ infer:152 ] Op: Mul [ 2019-03-21 16:52:50,209 ] [ DEBUG ] [ infer:163 ] Inputs: [ 2019-03-21 16:52:50,209 ] [ DEBUG ] [ infer:40 ] input[0]: shape = [ 1 30 128], value = [ 2019-03-21 16:52:50,215 ] [ DEBUG ] [ infer:40 ] input[1]: shape = [128], value = [1.0042808 0.99947447 0.99953866 1.001712 0.99923956 1.0205519 1.0126216 0.99939775 1.001002... [ 2019-03-21 16:52:50,215 ] [ DEBUG ] [ infer:165 ] Outputs: [ 2019-03-21 16:52:50,216 ] [ DEBUG ] [ infer:40 ] output[0]: shape = [ 1 30 128], value = [ 2019-03-21 16:52:50,216 ] [ DEBUG ] [ infer:150 ] -------------------- [ 2019-03-21 16:52:50,216 ] [ DEBUG ] [ infer:151 ] Partial infer for spatial_temporal_network/motion/conblock_2/bn/batchnorm/add_1 [ 2019-03-21 16:52:50,217 ] [ DEBUG ] [ infer:152 ] Op: Add [ 2019-03-21 16:52:50,217 ] [ DEBUG ] [ infer:163 ] Inputs: [ 2019-03-21 16:52:50,218 ] [ DEBUG ] [ infer:40 ] input[0]: shape = [ 1 30 128], value = [ 2019-03-21 16:52:50,223 ] [ DEBUG ] [ infer:40 ] input[1]: shape = [128], value = [ 0.03457135 -0.00338286 0.0029945 0.00918203 -0.01435596 0.01305742 0.02449914 -0.00520663... [ 2019-03-21 16:52:50,223 ] [ DEBUG ] [ infer:165 ] Outputs: [ 2019-03-21 16:52:50,224 ] [ DEBUG ] [ infer:40 ] output[0]: shape = [ 1 30 128], value = [ 2019-03-21 16:52:50,224 ] [ DEBUG ] [ infer:150 ] -------------------- [ 2019-03-21 16:52:50,225 ] [ DEBUG ] [ infer:151 ] Partial infer for spatial_temporal_network/motion/conblock_2/Relu [ 2019-03-21 16:52:50,225 ] [ DEBUG ] [ infer:152 ] Op: Relu [ 2019-03-21 16:52:50,225 ] [ DEBUG ] [ infer:163 ] Inputs: [ 2019-03-21 16:52:50,226 ] [ DEBUG ] [ infer:40 ] input[0]: shape = [ 1 30 128], value = [ 2019-03-21 16:52:50,227 ] [ DEBUG ] [ infer:165 ] Outputs: [ 2019-03-21 16:52:50,227 ] [ DEBUG ] [ infer:40 ] output[0]: shape = [ 1 30 128], value = [ 2019-03-21 16:52:50,228 ] [ DEBUG ] [ infer:150 ] -------------------- [ 2019-03-21 16:52:50,228 ] [ DEBUG ] [ infer:151 ] Partial infer for spatial_temporal_network/motion/conblock_3/cov/conv1d/ExpandDims [ 2019-03-21 16:52:50,228 ] [ DEBUG ] [ infer:152 ] Op: ExpandDims [ 2019-03-21 16:52:50,229 ] [ DEBUG ] [ infer:163 ] Inputs: [ 2019-03-21 16:52:50,230 ] [ DEBUG ] [ infer:40 ] input[0]: shape = [ 1 30 128], value = [ 2019-03-21 16:52:50,230 ] [ DEBUG ] [ infer:165 ] Outputs: [ 2019-03-21 16:52:50,231 ] [ DEBUG ] [ infer:40 ] output[0]: shape = [ 1 1 30 128], value = [ 2019-03-21 16:52:50,231 ] [ DEBUG ] [ infer:150 ] -------------------- [ 2019-03-21 16:52:50,232 ] [ DEBUG ] [ infer:151 ] Partial infer for spatial_temporal_network/motion/conblock_3/cov/conv1d/Conv2D [ 2019-03-21 16:52:50,232 ] [ DEBUG ] [ infer:152 ] Op: Conv2D [ 2019-03-21 16:52:50,235 ] [ DEBUG ] [ infer:163 ] Inputs: [ 2019-03-21 16:52:50,236 ] [ DEBUG ] [ infer:40 ] input[0]: shape = [ 1 1 30 128], value = [ 2019-03-21 16:52:50,242 ] [ DEBUG ] [ infer:40 ] input[1]: shape = [ 1 3 128 256], value = [[[[ 0.05045054 0.05083888 0.02092816 ... -0.03865567 -0.14738685 -0.07135887] [ 0.00710... [ 2019-03-21 16:52:50,242 ] [ DEBUG ] [ infer:165 ] Outputs: [ 2019-03-21 16:52:50,243 ] [ DEBUG ] [ infer:40 ] output[0]: shape = [ 1 1 30 256], value = [ 2019-03-21 16:52:50,243 ] [ DEBUG ] [ infer:150 ] -------------------- [ 2019-03-21 16:52:50,243 ] [ DEBUG ] [ infer:151 ] Partial infer for spatial_temporal_network/motion/conblock_3/cov/conv1d/Squeeze [ 2019-03-21 16:52:50,244 ] [ DEBUG ] [ infer:152 ] Op: Squeeze [ 2019-03-21 16:52:50,244 ] [ DEBUG ] [ squeeze:43 ] The reshape from "[ 1 1 30 256]" with squeezed dims "[ 1 30 256]" is not a spatial squeeze [ 2019-03-21 16:52:50,245 ] [ DEBUG ] [ infer:163 ] Inputs: [ 2019-03-21 16:52:50,245 ] [ DEBUG ] [ infer:40 ] input[0]: shape = [ 1 1 30 256], value = [ 2019-03-21 16:52:50,245 ] [ DEBUG ] [ infer:165 ] Outputs: [ 2019-03-21 16:52:50,246 ] [ DEBUG ] [ infer:40 ] output[0]: shape = [ 1 30 256], value = [ 2019-03-21 16:52:50,246 ] [ DEBUG ] [ infer:150 ] -------------------- [ 2019-03-21 16:52:50,247 ] [ DEBUG ] [ infer:151 ] Partial infer for spatial_temporal_network/motion/conblock_3/cov/BiasAdd [ 2019-03-21 16:52:50,247 ] [ DEBUG ] [ infer:152 ] Op: Add [ 2019-03-21 16:52:50,247 ] [ DEBUG ] [ infer:163 ] Inputs: [ 2019-03-21 16:52:50,258 ] [ DEBUG ] [ infer:40 ] input[1]: shape = [256], value = [ 1.12529919e-02 2.01415345e-02 9.55318753e-03 4.63739149e-02 -5.92489168e-03 1.75937712e-02... [ 2019-03-21 16:52:50,258 ] [ DEBUG ] [ infer:40 ] input[0]: shape = [ 1 30 256], value = [ 2019-03-21 16:52:50,259 ] [ DEBUG ] [ infer:165 ] Outputs: [ 2019-03-21 16:52:50,259 ] [ DEBUG ] [ infer:40 ] output[0]: shape = [ 1 30 256], value = [ 2019-03-21 16:52:50,260 ] [ DEBUG ] [ infer:150 ] -------------------- [ 2019-03-21 16:52:50,260 ] [ DEBUG ] [ infer:151 ] Partial infer for spatial_temporal_network/motion/conblock_3/bn/batchnorm/mul_1 [ 2019-03-21 16:52:50,260 ] [ DEBUG ] [ infer:152 ] Op: Mul [ 2019-03-21 16:52:50,261 ] [ DEBUG ] [ infer:163 ] Inputs: [ 2019-03-21 16:52:50,261 ] [ DEBUG ] [ infer:40 ] input[0]: shape = [ 1 30 256], value = [ 2019-03-21 16:52:50,273 ] [ DEBUG ] [ infer:40 ] input[1]: shape = [256], value = [1.0000055 1.021836 1.0001596 1.0048057 0.9993973 0.99963695 1.000591 0.9985747 0.99951... [ 2019-03-21 16:52:50,273 ] [ DEBUG ] [ infer:165 ] Outputs: [ 2019-03-21 16:52:50,274 ] [ DEBUG ] [ infer:40 ] output[0]: shape = [ 1 30 256], value = [ 2019-03-21 16:52:50,275 ] [ DEBUG ] [ infer:150 ] -------------------- [ 2019-03-21 16:52:50,275 ] [ DEBUG ] [ infer:151 ] Partial infer for spatial_temporal_network/motion/conblock_3/bn/batchnorm/add_1 [ 2019-03-21 16:52:50,276 ] [ DEBUG ] [ infer:152 ] Op: Add [ 2019-03-21 16:52:50,276 ] [ DEBUG ] [ infer:163 ] Inputs: [ 2019-03-21 16:52:50,277 ] [ DEBUG ] [ infer:40 ] input[0]: shape = [ 1 30 256], value = [ 2019-03-21 16:52:50,288 ] [ DEBUG ] [ infer:40 ] input[1]: shape = [256], value = [ 1.12557262e-02 1.98826529e-02 9.55713633e-03 4.63132225e-02 -5.92820998e-03 1.76003464e-02... [ 2019-03-21 16:52:50,288 ] [ DEBUG ] [ infer:165 ] Outputs: [ 2019-03-21 16:52:50,289 ] [ DEBUG ] [ infer:40 ] output[0]: shape = [ 1 30 256], value = [ 2019-03-21 16:52:50,290 ] [ DEBUG ] [ infer:150 ] -------------------- [ 2019-03-21 16:52:50,290 ] [ DEBUG ] [ infer:151 ] Partial infer for spatial_temporal_network/motion/conblock_3/Relu [ 2019-03-21 16:52:50,290 ] [ DEBUG ] [ infer:152 ] Op: Relu [ 2019-03-21 16:52:50,291 ] [ DEBUG ] [ infer:163 ] Inputs: [ 2019-03-21 16:52:50,292 ] [ DEBUG ] [ infer:40 ] input[0]: shape = [ 1 30 256], value = [ 2019-03-21 16:52:50,292 ] [ DEBUG ] [ infer:165 ] Outputs: [ 2019-03-21 16:52:50,292 ] [ DEBUG ] [ infer:40 ] output[0]: shape = [ 1 30 256], value = [ 2019-03-21 16:52:50,293 ] [ DEBUG ] [ infer:150 ] -------------------- [ 2019-03-21 16:52:50,293 ] [ DEBUG ] [ infer:151 ] Partial infer for spatial_temporal_network/motion/conblock_4/cov/conv1d/ExpandDims [ 2019-03-21 16:52:50,293 ] [ DEBUG ] [ infer:152 ] Op: ExpandDims [ 2019-03-21 16:52:50,294 ] [ DEBUG ] [ infer:163 ] Inputs: [ 2019-03-21 16:52:50,295 ] [ DEBUG ] [ infer:40 ] input[0]: shape = [ 1 30 256], value = [ 2019-03-21 16:52:50,295 ] [ DEBUG ] [ infer:165 ] Outputs: [ 2019-03-21 16:52:50,296 ] [ DEBUG ] [ infer:40 ] output[0]: shape = [ 1 1 30 256], value = [ 2019-03-21 16:52:50,297 ] [ DEBUG ] [ infer:150 ] -------------------- [ 2019-03-21 16:52:50,297 ] [ DEBUG ] [ infer:151 ] Partial infer for spatial_temporal_network/motion/conblock_4/cov/conv1d/Conv2D [ 2019-03-21 16:52:50,297 ] [ DEBUG ] [ infer:152 ] Op: Conv2D [ 2019-03-21 16:52:50,301 ] [ DEBUG ] [ infer:163 ] Inputs: [ 2019-03-21 16:52:50,304 ] [ DEBUG ] [ infer:40 ] input[0]: shape = [ 1 1 30 256], value = [ 2019-03-21 16:52:50,309 ] [ DEBUG ] [ infer:40 ] input[1]: shape = [ 1 3 256 512], value = [[[[-0.00075483 -0.00761538 0.02321353 ... 0.08803348 -0.06521032 -0.06899805] [ 0.03653... [ 2019-03-21 16:52:50,310 ] [ DEBUG ] [ infer:165 ] Outputs: [ 2019-03-21 16:52:50,310 ] [ DEBUG ] [ infer:40 ] output[0]: shape = [ 1 1 30 512], value = [ 2019-03-21 16:52:50,311 ] [ DEBUG ] [ infer:150 ] -------------------- [ 2019-03-21 16:52:50,311 ] [ DEBUG ] [ infer:151 ] Partial infer for spatial_temporal_network/motion/conblock_4/cov/conv1d/Squeeze [ 2019-03-21 16:52:50,312 ] [ DEBUG ] [ infer:152 ] Op: Squeeze [ 2019-03-21 16:52:50,313 ] [ DEBUG ] [ squeeze:43 ] The reshape from "[ 1 1 30 512]" with squeezed dims "[ 1 30 512]" is not a spatial squeeze [ 2019-03-21 16:52:50,313 ] [ DEBUG ] [ infer:163 ] Inputs: [ 2019-03-21 16:52:50,314 ] [ DEBUG ] [ infer:40 ] input[0]: shape = [ 1 1 30 512], value = [ 2019-03-21 16:52:50,314 ] [ DEBUG ] [ infer:165 ] Outputs: [ 2019-03-21 16:52:50,315 ] [ DEBUG ] [ infer:40 ] output[0]: shape = [ 1 30 512], value = [ 2019-03-21 16:52:50,315 ] [ DEBUG ] [ infer:150 ] -------------------- [ 2019-03-21 16:52:50,315 ] [ DEBUG ] [ infer:151 ] Partial infer for spatial_temporal_network/motion/conblock_4/cov/BiasAdd [ 2019-03-21 16:52:50,315 ] [ DEBUG ] [ infer:152 ] Op: Add [ 2019-03-21 16:52:50,316 ] [ DEBUG ] [ infer:163 ] Inputs: [ 2019-03-21 16:52:50,339 ] [ DEBUG ] [ infer:40 ] input[1]: shape = [512], value = [-5.32235624e-03 -3.40969069e-03 8.59346939e-04 -1.87482859e-03 9.48017405e-04 -4.33015497e-03... [ 2019-03-21 16:52:50,340 ] [ DEBUG ] [ infer:40 ] input[0]: shape = [ 1 30 512], value = [ 2019-03-21 16:52:50,340 ] [ DEBUG ] [ infer:165 ] Outputs: [ 2019-03-21 16:52:50,340 ] [ DEBUG ] [ infer:40 ] output[0]: shape = [ 1 30 512], value = [ 2019-03-21 16:52:50,341 ] [ DEBUG ] [ infer:150 ] -------------------- [ 2019-03-21 16:52:50,341 ] [ DEBUG ] [ infer:151 ] Partial infer for spatial_temporal_network/motion/conblock_4/bn/batchnorm/mul_1 [ 2019-03-21 16:52:50,342 ] [ DEBUG ] [ infer:152 ] Op: Mul [ 2019-03-21 16:52:50,342 ] [ DEBUG ] [ infer:163 ] Inputs: [ 2019-03-21 16:52:50,343 ] [ DEBUG ] [ infer:40 ] input[0]: shape = [ 1 30 512], value = [ 2019-03-21 16:52:50,361 ] [ DEBUG ] [ infer:40 ] input[1]: shape = [512], value = [0.99942154 1.0013876 0.99854714 0.99955165 1.0042635 0.99940354 0.99940854 0.9983262 1.00224... [ 2019-03-21 16:52:50,362 ] [ DEBUG ] [ infer:165 ] Outputs: [ 2019-03-21 16:52:50,362 ] [ DEBUG ] [ infer:40 ] output[0]: shape = [ 1 30 512], value = [ 2019-03-21 16:52:50,363 ] [ DEBUG ] [ infer:150 ] -------------------- [ 2019-03-21 16:52:50,363 ] [ DEBUG ] [ infer:151 ] Partial infer for spatial_temporal_network/motion/conblock_4/bn/batchnorm/add_1 [ 2019-03-21 16:52:50,363 ] [ DEBUG ] [ infer:152 ] Op: Add [ 2019-03-21 16:52:50,364 ] [ DEBUG ] [ infer:163 ] Inputs: [ 2019-03-21 16:52:50,365 ] [ DEBUG ] [ infer:40 ] input[0]: shape = [ 1 30 512], value = [ 2019-03-21 16:52:50,386 ] [ DEBUG ] [ infer:40 ] input[1]: shape = [512], value = [-5.32524893e-03 -3.41834291e-03 8.63424037e-04 -1.87578250e-03 9.49341280e-04 -4.33250470e-03... [ 2019-03-21 16:52:50,386 ] [ DEBUG ] [ infer:165 ] Outputs: [ 2019-03-21 16:52:50,387 ] [ DEBUG ] [ infer:40 ] output[0]: shape = [ 1 30 512], value = [ 2019-03-21 16:52:50,388 ] [ DEBUG ] [ infer:150 ] -------------------- [ 2019-03-21 16:52:50,388 ] [ DEBUG ] [ infer:151 ] Partial infer for spatial_temporal_network/motion/conblock_4/Relu [ 2019-03-21 16:52:50,388 ] [ DEBUG ] [ infer:152 ] Op: Relu [ 2019-03-21 16:52:50,389 ] [ DEBUG ] [ infer:163 ] Inputs: [ 2019-03-21 16:52:50,389 ] [ DEBUG ] [ infer:40 ] input[0]: shape = [ 1 30 512], value = [ 2019-03-21 16:52:50,390 ] [ DEBUG ] [ infer:165 ] Outputs: [ 2019-03-21 16:52:50,390 ] [ DEBUG ] [ infer:40 ] output[0]: shape = [ 1 30 512], value = [ 2019-03-21 16:52:50,391 ] [ DEBUG ] [ infer:150 ] -------------------- [ 2019-03-21 16:52:50,391 ] [ DEBUG ] [ infer:151 ] Partial infer for input1 [ 2019-03-21 16:52:50,391 ] [ DEBUG ] [ infer:152 ] Op: Placeholder [ 2019-03-21 16:52:50,391 ] [ DEBUG ] [ infer:163 ] Inputs: [ 2019-03-21 16:52:50,392 ] [ DEBUG ] [ infer:165 ] Outputs: [ 2019-03-21 16:52:50,392 ] [ DEBUG ] [ infer:40 ] output[0]: shape = [ 1 30 128], value = [ 2019-03-21 16:52:50,393 ] [ DEBUG ] [ infer:150 ] -------------------- [ 2019-03-21 16:52:50,393 ] [ DEBUG ] [ infer:151 ] Partial infer for spatial_temporal_network/geo/conblock_1/cov/conv1d/ExpandDims [ 2019-03-21 16:52:50,393 ] [ DEBUG ] [ infer:152 ] Op: ExpandDims [ 2019-03-21 16:52:50,394 ] [ DEBUG ] [ infer:163 ] Inputs: [ 2019-03-21 16:52:50,395 ] [ DEBUG ] [ infer:40 ] input[0]: shape = [ 1 30 128], value = [ 2019-03-21 16:52:50,395 ] [ DEBUG ] [ infer:165 ] Outputs: [ 2019-03-21 16:52:50,396 ] [ DEBUG ] [ infer:40 ] output[0]: shape = [ 1 1 30 128], value = [ 2019-03-21 16:52:50,396 ] [ DEBUG ] [ infer:150 ] -------------------- [ 2019-03-21 16:52:50,396 ] [ DEBUG ] [ infer:151 ] Partial infer for spatial_temporal_network/geo/conblock_1/cov/conv1d/Conv2D [ 2019-03-21 16:52:50,396 ] [ DEBUG ] [ infer:152 ] Op: Conv2D [ 2019-03-21 16:52:50,400 ] [ DEBUG ] [ infer:163 ] Inputs: [ 2019-03-21 16:52:50,400 ] [ DEBUG ] [ infer:40 ] input[0]: shape = [ 1 1 30 128], value = [ 2019-03-21 16:52:50,406 ] [ DEBUG ] [ infer:40 ] input[1]: shape = [ 1 3 182 256], value = [[[[ 0.10378325 0.01596859 -0.05274214 ... 0.07833526 -0.05113211 -0.050156 ] [ 0.02837... [ 2019-03-21 16:52:50,406 ] [ DEBUG ] [ infer:165 ] Outputs: [ 2019-03-21 16:52:50,407 ] [ DEBUG ] [ infer:40 ] output[0]: shape = [ 1 1 30 256], value = [ 2019-03-21 16:52:50,407 ] [ DEBUG ] [ infer:150 ] -------------------- [ 2019-03-21 16:52:50,407 ] [ DEBUG ] [ infer:151 ] Partial infer for spatial_temporal_network/geo/conblock_1/cov/conv1d/Squeeze [ 2019-03-21 16:52:50,408 ] [ DEBUG ] [ infer:152 ] Op: Squeeze [ 2019-03-21 16:52:50,409 ] [ DEBUG ] [ squeeze:43 ] The reshape from "[ 1 1 30 256]" with squeezed dims "[ 1 30 256]" is not a spatial squeeze [ 2019-03-21 16:52:50,410 ] [ DEBUG ] [ infer:163 ] Inputs: [ 2019-03-21 16:52:50,410 ] [ DEBUG ] [ infer:40 ] input[0]: shape = [ 1 1 30 256], value = [ 2019-03-21 16:52:50,410 ] [ DEBUG ] [ infer:165 ] Outputs: [ 2019-03-21 16:52:50,411 ] [ DEBUG ] [ infer:40 ] output[0]: shape = [ 1 30 256], value = [ 2019-03-21 16:52:50,411 ] [ DEBUG ] [ infer:150 ] -------------------- [ 2019-03-21 16:52:50,412 ] [ DEBUG ] [ infer:151 ] Partial infer for spatial_temporal_network/geo/conblock_1/cov/BiasAdd [ 2019-03-21 16:52:50,412 ] [ DEBUG ] [ infer:152 ] Op: Add [ 2019-03-21 16:52:50,412 ] [ DEBUG ] [ infer:163 ] Inputs: [ 2019-03-21 16:52:50,440 ] [ DEBUG ] [ infer:40 ] input[1]: shape = [256], value = [ 3.97014339e-03 -1.03658428e-02 -1.96596421e-02 7.17372261e-03 4.47784411e-03 1.59283429e-02... [ 2019-03-21 16:52:50,440 ] [ DEBUG ] [ infer:40 ] input[0]: shape = [ 1 30 256], value = [ 2019-03-21 16:52:50,441 ] [ DEBUG ] [ infer:165 ] Outputs: [ 2019-03-21 16:52:50,441 ] [ DEBUG ] [ infer:40 ] output[0]: shape = [ 1 30 256], value = [ 2019-03-21 16:52:50,443 ] [ DEBUG ] [ infer:150 ] -------------------- [ 2019-03-21 16:52:50,443 ] [ DEBUG ] [ infer:151 ] Partial infer for spatial_temporal_network/geo/conblock_1/bn/batchnorm/mul_1 [ 2019-03-21 16:52:50,443 ] [ DEBUG ] [ infer:152 ] Op: Mul [ 2019-03-21 16:52:50,444 ] [ DEBUG ] [ infer:163 ] Inputs: [ 2019-03-21 16:52:50,445 ] [ DEBUG ] [ infer:40 ] input[0]: shape = [ 1 30 256], value = [ 2019-03-21 16:52:50,456 ] [ DEBUG ] [ infer:40 ] input[1]: shape = [256], value = [1.0162165 0.99808544 1.0480229 1.0158528 1.0306517 1.0103843 1.0158751 0.99325335 0.991403... [ 2019-03-21 16:52:50,456 ] [ DEBUG ] [ infer:165 ] Outputs: [ 2019-03-21 16:52:50,456 ] [ DEBUG ] [ infer:40 ] output[0]: shape = [ 1 30 256], value = [ 2019-03-21 16:52:50,457 ] [ DEBUG ] [ infer:150 ] -------------------- [ 2019-03-21 16:52:50,457 ] [ DEBUG ] [ infer:151 ] Partial infer for spatial_temporal_network/geo/conblock_1/bn/batchnorm/add_1 [ 2019-03-21 16:52:50,457 ] [ DEBUG ] [ infer:152 ] Op: Add [ 2019-03-21 16:52:50,457 ] [ DEBUG ] [ infer:163 ] Inputs: [ 2019-03-21 16:52:50,458 ] [ DEBUG ] [ infer:40 ] input[0]: shape = [ 1 30 256], value = [ 2019-03-21 16:52:50,471 ] [ DEBUG ] [ infer:40 ] input[1]: shape = [256], value = [ 3.95187829e-03 -9.82402544e-03 -1.87268723e-02 7.15974765e-03 4.58617788e-03 1.59223359e-02... [ 2019-03-21 16:52:50,471 ] [ DEBUG ] [ infer:165 ] Outputs: [ 2019-03-21 16:52:50,472 ] [ DEBUG ] [ infer:40 ] output[0]: shape = [ 1 30 256], value = [ 2019-03-21 16:52:50,472 ] [ DEBUG ] [ infer:150 ] -------------------- [ 2019-03-21 16:52:50,472 ] [ DEBUG ] [ infer:151 ] Partial infer for spatial_temporal_network/geo/conblock_1/Relu [ 2019-03-21 16:52:50,472 ] [ DEBUG ] [ infer:152 ] Op: Relu [ 2019-03-21 16:52:50,473 ] [ DEBUG ] [ infer:163 ] Inputs: [ 2019-03-21 16:52:50,473 ] [ DEBUG ] [ infer:40 ] input[0]: shape = [ 1 30 256], value = [ 2019-03-21 16:52:50,474 ] [ DEBUG ] [ infer:165 ] Outputs: [ 2019-03-21 16:52:50,474 ] [ DEBUG ] [ infer:40 ] output[0]: shape = [ 1 30 256], value = [ 2019-03-21 16:52:50,475 ] [ DEBUG ] [ infer:150 ] -------------------- [ 2019-03-21 16:52:50,476 ] [ DEBUG ] [ infer:151 ] Partial infer for spatial_temporal_network/geo/conblock_2/cov/conv1d/ExpandDims [ 2019-03-21 16:52:50,476 ] [ DEBUG ] [ infer:152 ] Op: ExpandDims [ 2019-03-21 16:52:50,477 ] [ DEBUG ] [ infer:163 ] Inputs: [ 2019-03-21 16:52:50,478 ] [ DEBUG ] [ infer:40 ] input[0]: shape = [ 1 30 256], value = [ 2019-03-21 16:52:50,478 ] [ DEBUG ] [ infer:165 ] Outputs: [ 2019-03-21 16:52:50,479 ] [ DEBUG ] [ infer:40 ] output[0]: shape = [ 1 1 30 256], value = [ 2019-03-21 16:52:50,488 ] [ DEBUG ] [ infer:150 ] -------------------- [ 2019-03-21 16:52:50,489 ] [ DEBUG ] [ infer:151 ] Partial infer for spatial_temporal_network/geo/conblock_2/cov/conv1d/Conv2D [ 2019-03-21 16:52:50,489 ] [ DEBUG ] [ infer:152 ] Op: Conv2D [ 2019-03-21 16:52:50,492 ] [ DEBUG ] [ infer:163 ] Inputs: [ 2019-03-21 16:52:50,492 ] [ DEBUG ] [ infer:40 ] input[0]: shape = [ 1 1 30 256], value = [ 2019-03-21 16:52:50,504 ] [ DEBUG ] [ infer:40 ] input[1]: shape = [ 1 3 256 512], value = [[[[-3.21085914e-03 -2.21884232e-02 -8.55684727e-02 ... -1.63935199e-02 1.23029929e-02 -6.21... [ 2019-03-21 16:52:50,504 ] [ DEBUG ] [ infer:165 ] Outputs: [ 2019-03-21 16:52:50,505 ] [ DEBUG ] [ infer:40 ] output[0]: shape = [ 1 1 30 512], value = [ 2019-03-21 16:52:50,507 ] [ DEBUG ] [ infer:150 ] -------------------- [ 2019-03-21 16:52:50,507 ] [ DEBUG ] [ infer:151 ] Partial infer for spatial_temporal_network/geo/conblock_2/cov/conv1d/Squeeze [ 2019-03-21 16:52:50,507 ] [ DEBUG ] [ infer:152 ] Op: Squeeze [ 2019-03-21 16:52:50,515 ] [ DEBUG ] [ squeeze:43 ] The reshape from "[ 1 1 30 512]" with squeezed dims "[ 1 30 512]" is not a spatial squeeze [ 2019-03-21 16:52:50,516 ] [ DEBUG ] [ infer:163 ] Inputs: [ 2019-03-21 16:52:50,518 ] [ DEBUG ] [ infer:40 ] input[0]: shape = [ 1 1 30 512], value = [ 2019-03-21 16:52:50,518 ] [ DEBUG ] [ infer:165 ] Outputs: [ 2019-03-21 16:52:50,519 ] [ DEBUG ] [ infer:40 ] output[0]: shape = [ 1 30 512], value = [ 2019-03-21 16:52:50,520 ] [ DEBUG ] [ infer:150 ] -------------------- [ 2019-03-21 16:52:50,520 ] [ DEBUG ] [ infer:151 ] Partial infer for spatial_temporal_network/geo/conblock_2/cov/BiasAdd [ 2019-03-21 16:52:50,520 ] [ DEBUG ] [ infer:152 ] Op: Add [ 2019-03-21 16:52:50,521 ] [ DEBUG ] [ infer:163 ] Inputs: [ 2019-03-21 16:52:50,550 ] [ DEBUG ] [ infer:40 ] input[1]: shape = [512], value = [ 1.11946207e-03 -2.37401924e-03 -7.16306688e-03 -2.47903494e-03 3.83454352e-03 -3.67252529e-03... [ 2019-03-21 16:52:50,551 ] [ DEBUG ] [ infer:40 ] input[0]: shape = [ 1 30 512], value = [ 2019-03-21 16:52:50,551 ] [ DEBUG ] [ infer:165 ] Outputs: [ 2019-03-21 16:52:50,552 ] [ DEBUG ] [ infer:40 ] output[0]: shape = [ 1 30 512], value = [ 2019-03-21 16:52:50,552 ] [ DEBUG ] [ infer:150 ] -------------------- [ 2019-03-21 16:52:50,553 ] [ DEBUG ] [ infer:151 ] Partial infer for spatial_temporal_network/geo/conblock_2/bn/batchnorm/mul_1 [ 2019-03-21 16:52:50,553 ] [ DEBUG ] [ infer:152 ] Op: Mul [ 2019-03-21 16:52:50,554 ] [ DEBUG ] [ infer:163 ] Inputs: [ 2019-03-21 16:52:50,554 ] [ DEBUG ] [ infer:40 ] input[0]: shape = [ 1 30 512], value = [ 2019-03-21 16:52:50,579 ] [ DEBUG ] [ infer:40 ] input[1]: shape = [512], value = [0.9999604 1.0020311 1.0012498 1.0047294 1.0061911 1.001517 0.99903464 1.009257 1.0086752... [ 2019-03-21 16:52:50,579 ] [ DEBUG ] [ infer:165 ] Outputs: [ 2019-03-21 16:52:50,580 ] [ DEBUG ] [ infer:40 ] output[0]: shape = [ 1 30 512], value = [ 2019-03-21 16:52:50,580 ] [ DEBUG ] [ infer:150 ] -------------------- [ 2019-03-21 16:52:50,581 ] [ DEBUG ] [ infer:151 ] Partial infer for spatial_temporal_network/geo/conblock_2/bn/batchnorm/add_1 [ 2019-03-21 16:52:50,581 ] [ DEBUG ] [ infer:152 ] Op: Add [ 2019-03-21 16:52:50,583 ] [ DEBUG ] [ infer:163 ] Inputs: [ 2019-03-21 16:52:50,584 ] [ DEBUG ] [ infer:40 ] input[0]: shape = [ 1 30 512], value = [ 2019-03-21 16:52:50,604 ] [ DEBUG ] [ infer:40 ] input[1]: shape = [512], value = [ 1.1206801e-03 -2.3367635e-03 -7.1355500e-03 -2.4223847e-03 3.8753857e-03 -3.6522618e-03 -1.96... [ 2019-03-21 16:52:50,605 ] [ DEBUG ] [ infer:165 ] Outputs: [ 2019-03-21 16:52:50,606 ] [ DEBUG ] [ infer:40 ] output[0]: shape = [ 1 30 512], value = [ 2019-03-21 16:52:50,607 ] [ DEBUG ] [ infer:150 ] -------------------- [ 2019-03-21 16:52:50,607 ] [ DEBUG ] [ infer:151 ] Partial infer for spatial_temporal_network/geo/conblock_2/Relu [ 2019-03-21 16:52:50,607 ] [ DEBUG ] [ infer:152 ] Op: Relu [ 2019-03-21 16:52:50,608 ] [ DEBUG ] [ infer:163 ] Inputs: [ 2019-03-21 16:52:50,609 ] [ DEBUG ] [ infer:40 ] input[0]: shape = [ 1 30 512], value = [ 2019-03-21 16:52:50,609 ] [ DEBUG ] [ infer:165 ] Outputs: [ 2019-03-21 16:52:50,610 ] [ DEBUG ] [ infer:40 ] output[0]: shape = [ 1 30 512], value = [ 2019-03-21 16:52:50,612 ] [ DEBUG ] [ infer:150 ] -------------------- [ 2019-03-21 16:52:50,612 ] [ DEBUG ] [ infer:151 ] Partial infer for spatial_temporal_network/geo/conblock_3/cov/conv1d/ExpandDims [ 2019-03-21 16:52:50,612 ] [ DEBUG ] [ infer:152 ] Op: ExpandDims [ 2019-03-21 16:52:50,613 ] [ DEBUG ] [ infer:163 ] Inputs: [ 2019-03-21 16:52:50,614 ] [ DEBUG ] [ infer:40 ] input[0]: shape = [ 1 30 512], value = [ 2019-03-21 16:52:50,615 ] [ DEBUG ] [ infer:165 ] Outputs: [ 2019-03-21 16:52:50,615 ] [ DEBUG ] [ infer:40 ] output[0]: shape = [ 1 1 30 512], value = [ 2019-03-21 16:52:50,616 ] [ DEBUG ] [ infer:150 ] -------------------- [ 2019-03-21 16:52:50,616 ] [ DEBUG ] [ infer:151 ] Partial infer for spatial_temporal_network/geo/conblock_3/cov/conv1d/Conv2D [ 2019-03-21 16:52:50,617 ] [ DEBUG ] [ infer:152 ] Op: Conv2D [ 2019-03-21 16:52:50,623 ] [ DEBUG ] [ infer:163 ] Inputs: [ 2019-03-21 16:52:50,624 ] [ DEBUG ] [ infer:40 ] input[0]: shape = [ 1 1 30 512], value = [ 2019-03-21 16:52:50,631 ] [ DEBUG ] [ infer:40 ] input[1]: shape = [ 1 3 512 512], value = [[[[ 7.0989966e-02 -5.0314654e-02 -6.5823540e-02 ... -2.6750781e-03 2.6358338e-02 -2.6148457... [ 2019-03-21 16:52:50,632 ] [ DEBUG ] [ infer:165 ] Outputs: [ 2019-03-21 16:52:50,632 ] [ DEBUG ] [ infer:40 ] output[0]: shape = [ 1 1 30 512], value = [ 2019-03-21 16:52:50,633 ] [ DEBUG ] [ infer:150 ] -------------------- [ 2019-03-21 16:52:50,633 ] [ DEBUG ] [ infer:151 ] Partial infer for spatial_temporal_network/geo/conblock_3/cov/conv1d/Squeeze [ 2019-03-21 16:52:50,634 ] [ DEBUG ] [ infer:152 ] Op: Squeeze [ 2019-03-21 16:52:50,635 ] [ DEBUG ] [ squeeze:43 ] The reshape from "[ 1 1 30 512]" with squeezed dims "[ 1 30 512]" is not a spatial squeeze [ 2019-03-21 16:52:50,636 ] [ DEBUG ] [ infer:163 ] Inputs: [ 2019-03-21 16:52:50,637 ] [ DEBUG ] [ infer:40 ] input[0]: shape = [ 1 1 30 512], value = [ 2019-03-21 16:52:50,638 ] [ DEBUG ] [ infer:165 ] Outputs: [ 2019-03-21 16:52:50,638 ] [ DEBUG ] [ infer:40 ] output[0]: shape = [ 1 30 512], value = [ 2019-03-21 16:52:50,639 ] [ DEBUG ] [ infer:150 ] -------------------- [ 2019-03-21 16:52:50,639 ] [ DEBUG ] [ infer:151 ] Partial infer for spatial_temporal_network/geo/conblock_3/cov/BiasAdd [ 2019-03-21 16:52:50,640 ] [ DEBUG ] [ infer:152 ] Op: Add [ 2019-03-21 16:52:50,640 ] [ DEBUG ] [ infer:163 ] Inputs: [ 2019-03-21 16:52:50,662 ] [ DEBUG ] [ infer:40 ] input[1]: shape = [512], value = [-8.40652036e-04 -7.68809207e-03 2.11746455e-03 -1.09434035e-02 -3.32584139e-03 -1.10903960e-02... [ 2019-03-21 16:52:50,663 ] [ DEBUG ] [ infer:40 ] input[0]: shape = [ 1 30 512], value = [ 2019-03-21 16:52:50,664 ] [ DEBUG ] [ infer:165 ] Outputs: [ 2019-03-21 16:52:50,664 ] [ DEBUG ] [ infer:40 ] output[0]: shape = [ 1 30 512], value = [ 2019-03-21 16:52:50,665 ] [ DEBUG ] [ infer:150 ] -------------------- [ 2019-03-21 16:52:50,665 ] [ DEBUG ] [ infer:151 ] Partial infer for spatial_temporal_network/geo/conblock_3/bn/batchnorm/mul_1 [ 2019-03-21 16:52:50,665 ] [ DEBUG ] [ infer:152 ] Op: Mul [ 2019-03-21 16:52:50,666 ] [ DEBUG ] [ infer:163 ] Inputs: [ 2019-03-21 16:52:50,667 ] [ DEBUG ] [ infer:40 ] input[0]: shape = [ 1 30 512], value = [ 2019-03-21 16:52:50,688 ] [ DEBUG ] [ infer:40 ] input[1]: shape = [512], value = [1.0074594 1.0055478 1.0068562 1.0034767 1.0010344 1.0152304 1.0065807 1.0231463 0.999278... [ 2019-03-21 16:52:50,689 ] [ DEBUG ] [ infer:165 ] Outputs: [ 2019-03-21 16:52:50,689 ] [ DEBUG ] [ infer:40 ] output[0]: shape = [ 1 30 512], value = [ 2019-03-21 16:52:50,690 ] [ DEBUG ] [ infer:150 ] -------------------- [ 2019-03-21 16:52:50,691 ] [ DEBUG ] [ infer:151 ] Partial infer for spatial_temporal_network/geo/conblock_3/bn/batchnorm/add_1 [ 2019-03-21 16:52:50,691 ] [ DEBUG ] [ infer:152 ] Op: Add [ 2019-03-21 16:52:50,691 ] [ DEBUG ] [ infer:163 ] Inputs: [ 2019-03-21 16:52:50,692 ] [ DEBUG ] [ infer:40 ] input[0]: shape = [ 1 30 512], value = [ 2019-03-21 16:52:50,734 ] [ DEBUG ] [ infer:40 ] input[1]: shape = [512], value = [-7.80042727e-04 -7.66557734e-03 2.13933340e-03 -1.08347991e-02 -3.28366039e-03 -1.10146878e-02... [ 2019-03-21 16:52:50,735 ] [ DEBUG ] [ infer:165 ] Outputs: [ 2019-03-21 16:52:50,736 ] [ DEBUG ] [ infer:40 ] output[0]: shape = [ 1 30 512], value = [ 2019-03-21 16:52:50,736 ] [ DEBUG ] [ infer:150 ] -------------------- [ 2019-03-21 16:52:50,737 ] [ DEBUG ] [ infer:151 ] Partial infer for spatial_temporal_network/geo/conblock_3/Relu [ 2019-03-21 16:52:50,737 ] [ DEBUG ] [ infer:152 ] Op: Relu [ 2019-03-21 16:52:50,737 ] [ DEBUG ] [ infer:163 ] Inputs: [ 2019-03-21 16:52:50,738 ] [ DEBUG ] [ infer:40 ] input[0]: shape = [ 1 30 512], value = [ 2019-03-21 16:52:50,738 ] [ DEBUG ] [ infer:165 ] Outputs: [ 2019-03-21 16:52:50,739 ] [ DEBUG ] [ infer:40 ] output[0]: shape = [ 1 30 512], value = [ 2019-03-21 16:52:50,739 ] [ DEBUG ] [ infer:150 ] -------------------- [ 2019-03-21 16:52:50,740 ] [ DEBUG ] [ infer:151 ] Partial infer for spatial_temporal_network/rnn_net/Add [ 2019-03-21 16:52:50,740 ] [ DEBUG ] [ infer:152 ] Op: Add [ 2019-03-21 16:52:50,741 ] [ DEBUG ] [ infer:163 ] Inputs: [ 2019-03-21 16:52:50,741 ] [ DEBUG ] [ infer:40 ] input[0]: shape = [ 1 30 512], value = [ 2019-03-21 16:52:50,742 ] [ DEBUG ] [ infer:40 ] input[1]: shape = [ 1 30 512], value = [ 2019-03-21 16:52:50,742 ] [ DEBUG ] [ infer:165 ] Outputs: [ 2019-03-21 16:52:50,743 ] [ DEBUG ] [ infer:40 ] output[0]: shape = [ 1 30 512], value = [ 2019-03-21 16:52:50,743 ] [ DEBUG ] [ infer:150 ] -------------------- [ 2019-03-21 16:52:50,744 ] [ DEBUG ] [ infer:151 ] Partial infer for spatial_temporal_network/rnn_net/rnn/transpose [ 2019-03-21 16:52:50,744 ] [ DEBUG ] [ infer:152 ] Op: Transpose [ 2019-03-21 16:52:50,745 ] [ DEBUG ] [ infer:163 ] Inputs: [ 2019-03-21 16:52:50,745 ] [ DEBUG ] [ infer:40 ] input[0]: shape = [ 1 30 512], value = [ 2019-03-21 16:52:50,746 ] [ DEBUG ] [ infer:165 ] Outputs: [ 2019-03-21 16:52:50,746 ] [ DEBUG ] [ infer:40 ] output[0]: shape = [ 30 1 512], value = [ 2019-03-21 16:52:50,747 ] [ DEBUG ] [ infer:150 ] -------------------- [ 2019-03-21 16:52:50,747 ] [ DEBUG ] [ infer:151 ] Partial infer for spatial_temporal_network/rnn_net/rnn/TensorArrayUnstack/TensorArrayScatter/TensorArrayScatterV3 [ 2019-03-21 16:52:50,747 ] [ DEBUG ] [ infer:152 ] Op: TensorArrayScatterV3 [ 2019-03-21 16:52:50,748 ] [ DEBUG ] [ infer:163 ] Inputs: [ 2019-03-21 16:52:50,750 ] [ DEBUG ] [ infer:40 ] input[2]: shape = [ 30 1 512], value = [ 2019-03-21 16:52:50,752 ] [ DEBUG ] [ infer:40 ] input[0]: shape = [], value = spatial_temporal_network/rnn_net/rnn/TensorArray_1/Output_0/Data_ [ 2019-03-21 16:52:50,756 ] [ DEBUG ] [ infer:40 ] input[3]: shape = [], value = [ 2019-03-21 16:52:50,757 ] [ DEBUG ] [ infer:40 ] input[1]: shape = [30], value = [ 0 1 2 3 4 5 6 7 8 9 10 11 12 13 14 15 16 17 18 19 20 21 22 23 24 25 26 27 28 29] [ 2019-03-21 16:52:50,757 ] [ DEBUG ] [ infer:165 ] Outputs: [ 2019-03-21 16:52:50,758 ] [ DEBUG ] [ infer:40 ] output[0]: shape = [], value = [ 2019-03-21 16:52:50,759 ] [ DEBUG ] [ infer:150 ] -------------------- [ 2019-03-21 16:52:50,760 ] [ DEBUG ] [ infer:151 ] Partial infer for spatial_temporal_network/rnn_net/rnn/while/TensorArrayReadV3/Enter_1 [ 2019-03-21 16:52:50,761 ] [ DEBUG ] [ infer:152 ] Op: Enter [ 2019-03-21 16:52:50,761 ] [ DEBUG ] [ infer:163 ] Inputs: [ 2019-03-21 16:52:50,762 ] [ DEBUG ] [ infer:40 ] input[0]: shape = [], value = [ 2019-03-21 16:52:50,762 ] [ DEBUG ] [ infer:165 ] Outputs: [ 2019-03-21 16:52:50,763 ] [ DEBUG ] [ infer:40 ] output[0]: shape = [], value = [ 2019-03-21 16:52:50,764 ] [ DEBUG ] [ infer:150 ] -------------------- [ 2019-03-21 16:52:50,764 ] [ DEBUG ] [ infer:151 ] Partial infer for spatial_temporal_network/rnn_net/rnn/while/TensorArrayReadV3 [ 2019-03-21 16:52:50,764 ] [ DEBUG ] [ infer:152 ] Op: TensorArrayReadV3 [ 2019-03-21 16:52:50,765 ] [ DEBUG ] [ infer:163 ] Inputs: [ 2019-03-21 16:52:50,765 ] [ DEBUG ] [ infer:40 ] input[1]: shape = [], value = [ 2019-03-21 16:52:50,771 ] [ DEBUG ] [ infer:40 ] input[0]: shape = [], value = spatial_temporal_network/rnn_net/rnn/TensorArray_1/Output_0/Data_ [ 2019-03-21 16:52:50,773 ] [ DEBUG ] [ infer:40 ] input[2]: shape = [], value = [ 2019-03-21 16:52:50,773 ] [ DEBUG ] [ infer:165 ] Outputs: [ 2019-03-21 16:52:50,774 ] [ DEBUG ] [ infer:40 ] output[0]: shape = [ 1 512], value = [ 2019-03-21 16:52:50,774 ] [ DEBUG ] [ infer:150 ] -------------------- [ 2019-03-21 16:52:50,775 ] [ DEBUG ] [ infer:151 ] Partial infer for spatial_temporal_network/rnn_net/rnn/while/rnn/multi_rnn_cell/cell_0/lstm_cell/concat/LSTMCell [ 2019-03-21 16:52:50,775 ] [ DEBUG ] [ infer:152 ] Op: LSTMCell [ 2019-03-21 16:52:50,780 ] [ DEBUG ] [ infer:163 ] Inputs: [ 2019-03-21 16:52:50,782 ] [ DEBUG ] [ infer:40 ] input[2]: shape = [ 1 512], value = [ 2019-03-21 16:52:50,782 ] [ DEBUG ] [ infer:40 ] input[1]: shape = [ 1 512], value = [ 2019-03-21 16:52:50,783 ] [ DEBUG ] [ infer:40 ] input[0]: shape = [ 1 512], value = [ 2019-03-21 16:52:50,783 ] [ DEBUG ] [ infer:40 ] input[5]: shape = [], value = 1 [ 2019-03-21 16:52:50,786 ] [ DEBUG ] [ infer:40 ] input[3]: shape = [1024 2048], value = [[ 0.01566458 0.02684669 -0.01590733 ... 0.05444227 0.03510743 -0.01613005] [-0.04275664 0... [ 2019-03-21 16:52:50,788 ] [ DEBUG ] [ infer:40 ] input[4]: shape = [2048], value = [-0.0019465 -0.00394747 -0.0043961 ... -0.00155008 -0.00426906 -0.00050209] [ 2019-03-21 16:52:50,788 ] [ DEBUG ] [ infer:40 ] input[6]: shape = [], value = 1 [ 2019-03-21 16:52:50,788 ] [ DEBUG ] [ infer:40 ] input[7]: shape = [], value = 1.0 [ 2019-03-21 16:52:50,789 ] [ DEBUG ] [ infer:165 ] Outputs: [ 2019-03-21 16:52:50,789 ] [ DEBUG ] [ infer:40 ] output[0]: shape = [ 1 512], value = [ 2019-03-21 16:52:50,790 ] [ DEBUG ] [ infer:40 ] output[1]: shape = [ 1 512], value = [ 2019-03-21 16:52:50,791 ] [ DEBUG ] [ infer:150 ] -------------------- [ 2019-03-21 16:52:50,791 ] [ DEBUG ] [ infer:151 ] Partial infer for spatial_temporal_network/rnn_net/rnn/while/NextIteration_3 [ 2019-03-21 16:52:50,791 ] [ DEBUG ] [ infer:152 ] Op: NextIteration [ 2019-03-21 16:52:50,792 ] [ DEBUG ] [ infer:163 ] Inputs: [ 2019-03-21 16:52:50,792 ] [ DEBUG ] [ infer:40 ] input[0]: shape = [ 1 512], value = [ 2019-03-21 16:52:50,793 ] [ DEBUG ] [ infer:165 ] Outputs: [ 2019-03-21 16:52:50,793 ] [ DEBUG ] [ infer:40 ] output[0]: shape = [ 1 512], value = [ 2019-03-21 16:52:50,794 ] [ DEBUG ] [ infer:150 ] -------------------- [ 2019-03-21 16:52:50,794 ] [ DEBUG ] [ infer:151 ] Partial infer for spatial_temporal_network/rnn_net/rnn/while/rnn/multi_rnn_cell/cell_0/lstm_cell/concat_1/LSTMCell [ 2019-03-21 16:52:50,794 ] [ DEBUG ] [ infer:152 ] Op: LSTMCell [ 2019-03-21 16:52:50,799 ] [ DEBUG ] [ infer:163 ] Inputs: [ 2019-03-21 16:52:50,800 ] [ DEBUG ] [ infer:40 ] input[2]: shape = [ 1 512], value = [ 2019-03-21 16:52:50,801 ] [ DEBUG ] [ infer:40 ] input[1]: shape = [ 1 512], value = [ 2019-03-21 16:52:50,805 ] [ DEBUG ] [ infer:40 ] input[3]: shape = [1024 2048], value = [[ 0.01566458 0.02684669 -0.01590733 ... 0.05444227 0.03510743 -0.01613005] [-0.04275664 0... [ 2019-03-21 16:52:50,806 ] [ DEBUG ] [ infer:40 ] input[4]: shape = [2048], value = [-0.0019465 -0.00394747 -0.0043961 ... -0.00155008 -0.00426906 -0.00050209] [ 2019-03-21 16:52:50,806 ] [ DEBUG ] [ infer:40 ] input[5]: shape = [], value = 1 [ 2019-03-21 16:52:50,807 ] [ DEBUG ] [ infer:40 ] input[6]: shape = [], value = 1 [ 2019-03-21 16:52:50,807 ] [ DEBUG ] [ infer:40 ] input[7]: shape = [], value = 1.0 [ 2019-03-21 16:52:50,808 ] [ DEBUG ] [ infer:40 ] input[0]: shape = [ 1 512], value = [ 2019-03-21 16:52:50,808 ] [ DEBUG ] [ infer:165 ] Outputs: [ 2019-03-21 16:52:50,809 ] [ DEBUG ] [ infer:40 ] output[0]: shape = [ 1 512], value = [ 2019-03-21 16:52:50,809 ] [ DEBUG ] [ infer:40 ] output[1]: shape = [ 1 512], value = [ 2019-03-21 16:52:50,810 ] [ DEBUG ] [ infer:150 ] -------------------- [ 2019-03-21 16:52:50,810 ] [ DEBUG ] [ infer:151 ] Partial infer for spatial_temporal_network/rnn_net/rnn/while/NextIteration_5 [ 2019-03-21 16:52:50,810 ] [ DEBUG ] [ infer:152 ] Op: NextIteration [ 2019-03-21 16:52:50,811 ] [ DEBUG ] [ infer:163 ] Inputs: [ 2019-03-21 16:52:50,811 ] [ DEBUG ] [ infer:40 ] input[0]: shape = [ 1 512], value = [ 2019-03-21 16:52:50,811 ] [ DEBUG ] [ infer:165 ] Outputs: [ 2019-03-21 16:52:50,812 ] [ DEBUG ] [ infer:40 ] output[0]: shape = [ 1 512], value = [ 2019-03-21 16:52:50,812 ] [ DEBUG ] [ infer:150 ] -------------------- [ 2019-03-21 16:52:50,813 ] [ DEBUG ] [ infer:151 ] Partial infer for spatial_temporal_network/rnn_net/rnn/while/rnn/multi_rnn_cell/cell_0/lstm_cell/concat_2/LSTMCell [ 2019-03-21 16:52:50,813 ] [ DEBUG ] [ infer:152 ] Op: LSTMCell [ 2019-03-21 16:52:50,816 ] [ DEBUG ] [ infer:163 ] Inputs: [ 2019-03-21 16:52:50,818 ] [ DEBUG ] [ infer:40 ] input[2]: shape = [ 1 512], value = [ 2019-03-21 16:52:50,819 ] [ DEBUG ] [ infer:40 ] input[1]: shape = [ 1 512], value = [ 2019-03-21 16:52:50,821 ] [ DEBUG ] [ infer:40 ] input[3]: shape = [1024 2048], value = [[ 0.01566458 0.02684669 -0.01590733 ... 0.05444227 0.03510743 -0.01613005] [-0.04275664 0... [ 2019-03-21 16:52:50,824 ] [ DEBUG ] [ infer:40 ] input[4]: shape = [2048], value = [-0.0019465 -0.00394747 -0.0043961 ... -0.00155008 -0.00426906 -0.00050209] [ 2019-03-21 16:52:50,825 ] [ DEBUG ] [ infer:40 ] input[5]: shape = [], value = 1 [ 2019-03-21 16:52:50,825 ] [ DEBUG ] [ infer:40 ] input[6]: shape = [], value = 1 [ 2019-03-21 16:52:50,826 ] [ DEBUG ] [ infer:40 ] input[7]: shape = [], value = 1.0 [ 2019-03-21 16:52:50,826 ] [ DEBUG ] [ infer:40 ] input[0]: shape = [ 1 512], value = [ 2019-03-21 16:52:50,827 ] [ DEBUG ] [ infer:165 ] Outputs: [ 2019-03-21 16:52:50,827 ] [ DEBUG ] [ infer:40 ] output[0]: shape = [ 1 512], value = [ 2019-03-21 16:52:50,827 ] [ DEBUG ] [ infer:40 ] output[1]: shape = [ 1 512], value = [ 2019-03-21 16:52:50,828 ] [ DEBUG ] [ infer:150 ] -------------------- [ 2019-03-21 16:52:50,828 ] [ DEBUG ] [ infer:151 ] Partial infer for spatial_temporal_network/rnn_net/rnn/while/NextIteration_7 [ 2019-03-21 16:52:50,829 ] [ DEBUG ] [ infer:152 ] Op: NextIteration [ 2019-03-21 16:52:50,829 ] [ DEBUG ] [ infer:163 ] Inputs: [ 2019-03-21 16:52:50,830 ] [ DEBUG ] [ infer:40 ] input[0]: shape = [ 1 512], value = [ 2019-03-21 16:52:50,830 ] [ DEBUG ] [ infer:165 ] Outputs: [ 2019-03-21 16:52:50,831 ] [ DEBUG ] [ infer:40 ] output[0]: shape = [ 1 512], value = [ 2019-03-21 16:52:50,831 ] [ DEBUG ] [ infer:150 ] -------------------- [ 2019-03-21 16:52:50,831 ] [ DEBUG ] [ infer:151 ] Partial infer for spatial_temporal_network/rnn_net/rnn/while/NextIteration_8 [ 2019-03-21 16:52:50,832 ] [ DEBUG ] [ infer:152 ] Op: NextIteration [ 2019-03-21 16:52:50,832 ] [ DEBUG ] [ infer:163 ] Inputs: [ 2019-03-21 16:52:50,833 ] [ DEBUG ] [ infer:40 ] input[0]: shape = [ 1 512], value = [ 2019-03-21 16:52:50,833 ] [ DEBUG ] [ infer:165 ] Outputs: [ 2019-03-21 16:52:50,834 ] [ DEBUG ] [ infer:40 ] output[0]: shape = [ 1 512], value = [ 2019-03-21 16:52:50,844 ] [ DEBUG ] [ infer:150 ] -------------------- [ 2019-03-21 16:52:50,844 ] [ DEBUG ] [ infer:151 ] Partial infer for spatial_temporal_network/rnn_net/rnn/while/TensorArrayWrite/TensorArrayWriteV3 [ 2019-03-21 16:52:50,845 ] [ DEBUG ] [ infer:152 ] Op: TensorArrayWriteV3 [ 2019-03-21 16:52:50,851 ] [ DEBUG ] [ infer:163 ] Inputs: [ 2019-03-21 16:52:50,852 ] [ DEBUG ] [ infer:40 ] input[1]: shape = [], value = [ 2019-03-21 16:52:50,852 ] [ DEBUG ] [ infer:40 ] input[3]: shape = [], value = [ 2019-03-21 16:52:50,853 ] [ DEBUG ] [ infer:40 ] input[0]: shape = [], value = spatial_temporal_network/rnn_net/rnn/TensorArray/Output_0/Data_ [ 2019-03-21 16:52:50,853 ] [ DEBUG ] [ infer:40 ] input[2]: shape = [ 1 512], value = [ 2019-03-21 16:52:50,854 ] [ DEBUG ] [ infer:165 ] Outputs: [ 2019-03-21 16:52:50,854 ] [ DEBUG ] [ infer:40 ] output[0]: shape = [], value = [ 2019-03-21 16:52:50,855 ] [ DEBUG ] [ infer:150 ] -------------------- [ 2019-03-21 16:52:50,855 ] [ DEBUG ] [ infer:151 ] Partial infer for spatial_temporal_network/rnn_net/rnn/while/NextIteration_2 [ 2019-03-21 16:52:50,855 ] [ DEBUG ] [ infer:152 ] Op: NextIteration [ 2019-03-21 16:52:50,856 ] [ DEBUG ] [ infer:163 ] Inputs: [ 2019-03-21 16:52:50,856 ] [ DEBUG ] [ infer:40 ] input[0]: shape = [], value = [ 2019-03-21 16:52:50,857 ] [ DEBUG ] [ infer:165 ] Outputs: [ 2019-03-21 16:52:50,857 ] [ DEBUG ] [ infer:40 ] output[0]: shape = [], value = [ 2019-03-21 16:52:50,858 ] [ DEBUG ] [ infer:150 ] -------------------- [ 2019-03-21 16:52:50,858 ] [ DEBUG ] [ infer:151 ] Partial infer for spatial_temporal_network/rnn_net/rnn/while/NextIteration_6 [ 2019-03-21 16:52:50,858 ] [ DEBUG ] [ infer:152 ] Op: NextIteration [ 2019-03-21 16:52:50,859 ] [ DEBUG ] [ infer:163 ] Inputs: [ 2019-03-21 16:52:50,859 ] [ DEBUG ] [ infer:40 ] input[0]: shape = [ 1 512], value = [ 2019-03-21 16:52:50,860 ] [ DEBUG ] [ infer:165 ] Outputs: [ 2019-03-21 16:52:50,860 ] [ DEBUG ] [ infer:40 ] output[0]: shape = [ 1 512], value = [ 2019-03-21 16:52:50,861 ] [ DEBUG ] [ infer:150 ] -------------------- [ 2019-03-21 16:52:50,861 ] [ DEBUG ] [ infer:151 ] Partial infer for spatial_temporal_network/rnn_net/rnn/while/NextIteration_4 [ 2019-03-21 16:52:50,861 ] [ DEBUG ] [ infer:152 ] Op: NextIteration [ 2019-03-21 16:52:50,862 ] [ DEBUG ] [ infer:163 ] Inputs: [ 2019-03-21 16:52:50,863 ] [ DEBUG ] [ infer:40 ] input[0]: shape = [ 1 512], value = [ 2019-03-21 16:52:50,863 ] [ DEBUG ] [ infer:165 ] Outputs: [ 2019-03-21 16:52:50,864 ] [ DEBUG ] [ infer:40 ] output[0]: shape = [ 1 512], value = [ 2019-03-21 16:52:50,864 ] [ DEBUG ] [ infer:150 ] -------------------- [ 2019-03-21 16:52:50,865 ] [ DEBUG ] [ infer:151 ] Partial infer for spatial_temporal_network/rnn_net/rnn/while/Exit_2 [ 2019-03-21 16:52:50,865 ] [ DEBUG ] [ infer:152 ] Op: Exit [ 2019-03-21 16:52:50,866 ] [ DEBUG ] [ infer:163 ] Inputs: [ 2019-03-21 16:52:50,868 ] [ DEBUG ] [ infer:40 ] input[0]: shape = [], value = [ 2019-03-21 16:52:50,868 ] [ DEBUG ] [ infer:165 ] Outputs: [ 2019-03-21 16:52:50,869 ] [ DEBUG ] [ infer:40 ] output[0]: shape = [], value = [ 2019-03-21 16:52:50,869 ] [ DEBUG ] [ infer:150 ] -------------------- [ 2019-03-21 16:52:50,870 ] [ DEBUG ] [ infer:151 ] Partial infer for spatial_temporal_network/rnn_net/rnn/TensorArrayStack/TensorArraySizeV3 [ 2019-03-21 16:52:50,870 ] [ DEBUG ] [ infer:152 ] Op: TensorArraySizeV3 [ 2019-03-21 16:52:50,871 ] [ DEBUG ] [ infer:163 ] Inputs: [ 2019-03-21 16:52:50,871 ] [ DEBUG ] [ infer:40 ] input[0]: shape = [], value = spatial_temporal_network/rnn_net/rnn/TensorArray/Output_0/Data_ [ 2019-03-21 16:52:50,872 ] [ DEBUG ] [ infer:40 ] input[1]: shape = [], value = [ 2019-03-21 16:52:50,872 ] [ DEBUG ] [ infer:165 ] Outputs: [ 2019-03-21 16:52:50,872 ] [ DEBUG ] [ infer:40 ] output[0]: shape = [], value = 30 [ 2019-03-21 16:52:50,873 ] [ DEBUG ] [ infer:150 ] -------------------- [ 2019-03-21 16:52:50,873 ] [ DEBUG ] [ infer:151 ] Partial infer for spatial_temporal_network/rnn_net/rnn/TensorArrayStack/range [ 2019-03-21 16:52:50,873 ] [ DEBUG ] [ infer:152 ] Op: Range [ 2019-03-21 16:52:50,875 ] [ DEBUG ] [ infer:163 ] Inputs: [ 2019-03-21 16:52:50,875 ] [ DEBUG ] [ infer:40 ] input[1]: shape = [], value = 30 [ 2019-03-21 16:52:50,876 ] [ DEBUG ] [ infer:40 ] input[0]: shape = [], value = 0 [ 2019-03-21 16:52:50,876 ] [ DEBUG ] [ infer:40 ] input[2]: shape = [], value = 1 [ 2019-03-21 16:52:50,876 ] [ DEBUG ] [ infer:165 ] Outputs: [ 2019-03-21 16:52:50,877 ] [ DEBUG ] [ infer:40 ] output[0]: shape = [30], value = [ 0 1 2 3 4 5 6 7 8 9 10 11 12 13 14 15 16 17 18 19 20 21 22 23 24 25 26 27 28 29] [ 2019-03-21 16:52:50,878 ] [ DEBUG ] [ infer:150 ] -------------------- [ 2019-03-21 16:52:50,878 ] [ DEBUG ] [ infer:151 ] Partial infer for spatial_temporal_network/rnn_net/rnn/TensorArrayStack/TensorArrayGatherV3 [ 2019-03-21 16:52:50,878 ] [ DEBUG ] [ infer:152 ] Op: TensorArrayGatherV3 [ 2019-03-21 16:52:50,880 ] [ DEBUG ] [ infer:163 ] Inputs: [ 2019-03-21 16:52:50,881 ] [ DEBUG ] [ infer:40 ] input[0]: shape = [], value = spatial_temporal_network/rnn_net/rnn/TensorArray/Output_0/Data_ [ 2019-03-21 16:52:50,881 ] [ DEBUG ] [ infer:40 ] input[2]: shape = [], value = [ 2019-03-21 16:52:50,883 ] [ DEBUG ] [ infer:40 ] input[1]: shape = [30], value = [ 0 1 2 3 4 5 6 7 8 9 10 11 12 13 14 15 16 17 18 19 20 21 22 23 24 25 26 27 28 29] [ 2019-03-21 16:52:50,883 ] [ DEBUG ] [ infer:165 ] Outputs: [ 2019-03-21 16:52:50,885 ] [ DEBUG ] [ infer:40 ] output[0]: shape = [ 30 1 512], value = [ 2019-03-21 16:52:50,886 ] [ DEBUG ] [ infer:150 ] -------------------- [ 2019-03-21 16:52:50,886 ] [ DEBUG ] [ infer:151 ] Partial infer for spatial_temporal_network/rnn_net/rnn/transpose_1 [ 2019-03-21 16:52:50,887 ] [ DEBUG ] [ infer:152 ] Op: Transpose [ 2019-03-21 16:52:50,890 ] [ DEBUG ] [ infer:163 ] Inputs: [ 2019-03-21 16:52:50,892 ] [ DEBUG ] [ infer:40 ] input[0]: shape = [ 30 1 512], value = [ 2019-03-21 16:52:50,893 ] [ DEBUG ] [ infer:165 ] Outputs: [ 2019-03-21 16:52:50,894 ] [ DEBUG ] [ infer:40 ] output[0]: shape = [ 1 30 512], value = [ 2019-03-21 16:52:50,894 ] [ DEBUG ] [ infer:150 ] -------------------- [ 2019-03-21 16:52:50,895 ] [ DEBUG ] [ infer:151 ] Partial infer for spatial_temporal_network/flatten/Reshape [ 2019-03-21 16:52:50,895 ] [ DEBUG ] [ infer:152 ] Op: Reshape [ 2019-03-21 16:52:50,896 ] [ DEBUG ] [ infer:163 ] Inputs: [ 2019-03-21 16:52:50,897 ] [ DEBUG ] [ infer:40 ] input[0]: shape = [ 1 30 512], value = [ 2019-03-21 16:52:50,898 ] [ DEBUG ] [ infer:40 ] input[1]: shape = [2], value = [ 1 -1] [ 2019-03-21 16:52:50,898 ] [ DEBUG ] [ infer:165 ] Outputs: [ 2019-03-21 16:52:50,899 ] [ DEBUG ] [ infer:40 ] output[0]: shape = [ 1 15360], value = [ 2019-03-21 16:52:50,900 ] [ DEBUG ] [ infer:150 ] -------------------- [ 2019-03-21 16:52:50,901 ] [ DEBUG ] [ infer:151 ] Partial infer for spatial_temporal_network/dense/MatMul [ 2019-03-21 16:52:50,901 ] [ DEBUG ] [ infer:152 ] Op: MatMul [ 2019-03-21 16:52:50,905 ] [ DEBUG ] [ matmul:30 ] matmul shapes: [array([ 1, 15360]), array([15360, 7])] [ 2019-03-21 16:52:50,906 ] [ DEBUG ] [ matmul:74 ] shape_tuple: (array([1]), array([7])) [ 2019-03-21 16:52:50,911 ] [ DEBUG ] [ matmul:77 ] matmul shape: [1 7] [ 2019-03-21 16:52:50,911 ] [ DEBUG ] [ infer:163 ] Inputs: [ 2019-03-21 16:52:50,913 ] [ DEBUG ] [ infer:40 ] input[0]: shape = [ 1 15360], value = [ 2019-03-21 16:52:50,915 ] [ DEBUG ] [ infer:40 ] input[1]: shape = [15360 7], value = [[ 0.00754917 -0.00470051 -0.01742837 ... 0.00815568 -0.01912938 -0.00964213] [-0.000457 -0... [ 2019-03-21 16:52:50,915 ] [ DEBUG ] [ infer:165 ] Outputs: [ 2019-03-21 16:52:50,920 ] [ DEBUG ] [ infer:40 ] output[0]: shape = [1 7], value = [ 2019-03-21 16:52:50,930 ] [ DEBUG ] [ infer:150 ] -------------------- [ 2019-03-21 16:52:50,931 ] [ DEBUG ] [ infer:151 ] Partial infer for spatial_temporal_network/dense/BiasAdd [ 2019-03-21 16:52:50,932 ] [ DEBUG ] [ infer:152 ] Op: Add [ 2019-03-21 16:52:50,933 ] [ DEBUG ] [ infer:163 ] Inputs: [ 2019-03-21 16:52:50,934 ] [ DEBUG ] [ infer:40 ] input[1]: shape = [7], value = [ 0.14485614 0.17269324 -0.0195503 -0.10251361 -0.04668584 -0.12757407 -0.0212258 ] [ 2019-03-21 16:52:50,935 ] [ DEBUG ] [ infer:40 ] input[0]: shape = [1 7], value = [ 2019-03-21 16:52:50,935 ] [ DEBUG ] [ infer:165 ] Outputs: [ 2019-03-21 16:52:50,936 ] [ DEBUG ] [ infer:40 ] output[0]: shape = [1 7], value = [ 2019-03-21 16:52:50,936 ] [ DEBUG ] [ infer:150 ] -------------------- [ 2019-03-21 16:52:50,937 ] [ DEBUG ] [ infer:151 ] Partial infer for output [ 2019-03-21 16:52:50,937 ] [ DEBUG ] [ infer:152 ] Op: SoftMax [ 2019-03-21 16:52:50,940 ] [ DEBUG ] [ infer:163 ] Inputs: [ 2019-03-21 16:52:50,941 ] [ DEBUG ] [ infer:40 ] input[0]: shape = [1 7], value = [ 2019-03-21 16:52:50,941 ] [ DEBUG ] [ infer:165 ] Outputs: [ 2019-03-21 16:52:50,942 ] [ DEBUG ] [ infer:40 ] output[0]: shape = [1 7], value = [ 2019-03-21 16:52:50,958 ] [ DEBUG ] [ infer:94 ] Removing control flow edge from spatial_temporal_network/rnn_net/rnn/while/Identity/Output_0/Data_ to spatial_temporal_network/rnn_net/rnn/while/add/y [ 2019-03-21 16:52:50,958 ] [ DEBUG ] [ infer:94 ] Removing control flow edge from spatial_temporal_network/rnn_net/rnn/while/Identity/Output_0/Data_ to spatial_temporal_network/rnn_net/rnn/while/rnn/multi_rnn_cell/cell_0/lstm_cell/concat/axis [ 2019-03-21 16:52:50,958 ] [ DEBUG ] [ infer:94 ] Removing control flow edge from spatial_temporal_network/rnn_net/rnn/while/Identity/Output_0/Data_ to spatial_temporal_network/rnn_net/rnn/while/rnn/multi_rnn_cell/cell_0/lstm_cell/split/split_dim [ 2019-03-21 16:52:50,959 ] [ DEBUG ] [ infer:94 ] Removing control flow edge from spatial_temporal_network/rnn_net/rnn/while/Identity/Output_0/Data_ to spatial_temporal_network/rnn_net/rnn/while/rnn/multi_rnn_cell/cell_0/lstm_cell/add/y [ 2019-03-21 16:52:50,959 ] [ DEBUG ] [ infer:94 ] Removing control flow edge from spatial_temporal_network/rnn_net/rnn/while/Identity/Output_0/Data_ to spatial_temporal_network/rnn_net/rnn/while/rnn/multi_rnn_cell/cell_0/lstm_cell/concat_1/axis [ 2019-03-21 16:52:50,959 ] [ DEBUG ] [ infer:94 ] Removing control flow edge from spatial_temporal_network/rnn_net/rnn/while/Identity/Output_0/Data_ to spatial_temporal_network/rnn_net/rnn/while/rnn/multi_rnn_cell/cell_0/lstm_cell/split_1/split_dim [ 2019-03-21 16:52:50,959 ] [ DEBUG ] [ infer:94 ] Removing control flow edge from spatial_temporal_network/rnn_net/rnn/while/Identity/Output_0/Data_ to spatial_temporal_network/rnn_net/rnn/while/rnn/multi_rnn_cell/cell_0/lstm_cell/add_2/y [ 2019-03-21 16:52:50,959 ] [ DEBUG ] [ infer:94 ] Removing control flow edge from spatial_temporal_network/rnn_net/rnn/while/Identity/Output_0/Data_ to spatial_temporal_network/rnn_net/rnn/while/rnn/multi_rnn_cell/cell_0/lstm_cell/concat_2/axis [ 2019-03-21 16:52:50,959 ] [ DEBUG ] [ infer:94 ] Removing control flow edge from spatial_temporal_network/rnn_net/rnn/while/Identity/Output_0/Data_ to spatial_temporal_network/rnn_net/rnn/while/rnn/multi_rnn_cell/cell_0/lstm_cell/split_2/split_dim [ 2019-03-21 16:52:50,960 ] [ DEBUG ] [ infer:94 ] Removing control flow edge from spatial_temporal_network/rnn_net/rnn/while/Identity/Output_0/Data_ to spatial_temporal_network/rnn_net/rnn/while/rnn/multi_rnn_cell/cell_0/lstm_cell/add_4/y [ 2019-03-21 16:52:50,960 ] [ DEBUG ] [ infer:94 ] Removing control flow edge from spatial_temporal_network/rnn_net/rnn/while/Identity/Output_0/Data_ to spatial_temporal_network/rnn_net/rnn/while/add_1/y [ 2019-03-21 16:52:51,272 ] [ DEBUG ] [ TensorIteratorInput:119 ] ================== SmartInputFind =============== [ WARNING ] You network cannot be reshaped since shapes of placeholders is a contants.Please, provide non-constant shapes. [ 2019-03-21 16:52:51,274 ] [ DEBUG ] [ op:195 ] Start running infer function for individual op node with attributes: {'precision': 'FP32', 'kind': 'op', 'op': 'TensorIteratorInput', 'axis': 0, 'start': 0, 'end': None, 'stride': None, 'part_size': None, 'infer': , 'external_port_id': 'spatial_temporal_network/rnn_net/rnn/TensorArray_1/Output_0/Data_', 'internal_layer_id': 'spatial_temporal_network/rnn_net/rnn/while/TensorArrayReadV3/Output_0/Data_', 'name': 'spatial_temporal_network/rnn_net/rnn/while/TensorArrayReadV3/TensorIteratorInput_', 'dim_attrs': ['spatial_dims', 'channel_dims', 'axis', 'batch_dims'], 'shape_attrs': ['output_shape', 'shape', 'pad', 'window', 'stride'], 'IE': [('layer', [('id', . at 0x7fb075a79e18>), 'name', 'precision', 'type'], [('data', ['external_port_id', 'internal_layer_id', 'internal_port_id', 'axis', 'start', 'stride', 'part_size'], []), '@ports', '@consts'])]} [ 2019-03-21 16:52:51,286 ] [ DEBUG ] [ op:208 ] Finished running infer function, data nodes attributes: {'name': 'spatial_temporal_network/rnn_net/rnn/while/TensorArrayReadV3/Output_0/Data_', 'kind': 'data', 'shape': array([ 1, 512]), 'value': None, 'data_type': None, 'infer': None, 'dim_attrs': ['spatial_dims', 'channel_dims', 'axis', 'batch_dims'], 'shape_attrs': ['output_shape', 'shape', 'pad', 'window', 'stride'], 'fw_tensor_debug_info': [('spatial_temporal_network/rnn_net/rnn/while/TensorArrayReadV3', 0)], 'is_output_reachable': True, 'is_undead': False, 'is_const_producer': False, 'is_partial_inferred': True, 'executable': True} [ 2019-03-21 16:52:51,400 ] [ DEBUG ] [ TensorIteratorOutput:125 ] ================== SmartOutputFind =============== [ 2019-03-21 16:52:51,401 ] [ DEBUG ] [ op:195 ] Start running infer function for individual op node with attributes: {'precision': 'FP32', 'kind': 'op', 'op': 'TensorIteratorOutput', 'axis': 0, 'start': None, 'end': None, 'stride': None, 'part_size': None, 'infer': , 'external_port_id': 'spatial_temporal_network/rnn_net/rnn/TensorArray/Output_0/Data_', 'internal_layer_id': 'spatial_temporal_network/rnn_net/rnn/while/rnn/multi_rnn_cell/cell_0/lstm_cell/concat_2/LSTMCell/Output_0/Data_', 'name': 'spatial_temporal_network/rnn_net/rnn/while/TensorArrayWrite/TensorArrayWriteV3/TensorIteratorOutput_', 'dim_attrs': ['spatial_dims', 'channel_dims', 'axis', 'batch_dims'], 'shape_attrs': ['output_shape', 'shape', 'pad', 'window', 'stride'], 'IE': [('layer', [('id', . at 0x7fb075ab1840>), 'name', 'precision', 'type'], [('data', ['external_port_id', 'internal_layer_id', 'internal_port_id', 'axis', 'start', 'stride', 'part_size'], []), '@ports', '@consts'])]} [ 2019-03-21 16:52:51,402 ] [ DEBUG ] [ op:208 ] Finished running infer function, data nodes attributes: {'name': 'spatial_temporal_network/rnn_net/rnn/TensorArrayStack/TensorArrayGatherV3/Output_0/Data_', 'kind': 'data', 'shape': array([ 30, 1, 512]), 'value': None, 'data_type': None, 'infer': None, 'dim_attrs': ['spatial_dims', 'channel_dims', 'axis', 'batch_dims'], 'shape_attrs': ['output_shape', 'shape', 'pad', 'window', 'stride'], 'fw_tensor_debug_info': [('spatial_temporal_network/rnn_net/rnn/TensorArrayStack/TensorArrayGatherV3', 0)], 'is_output_reachable': True, 'is_undead': False, 'is_const_producer': False, 'is_partial_inferred': True, 'executable': True} [ 2019-03-21 16:52:51,411 ] [ DEBUG ] [ TensorIteratorCondition:52 ] +++++++++++++++ ConditionMatching ++++++++++++++++ [ 2019-03-21 16:52:51,602 ] [ DEBUG ] [ TensorIteratorCondition:172 ] ================== ConditionFind =============== [ 2019-03-21 16:52:51,603 ] [ DEBUG ] [ op:195 ] Start running infer function for individual op node with attributes: {'precision': 'FP32', 'kind': 'op', 'op': 'TensorIteratorCondition', 'infer': , 'time': {'init': 0, 'step': 1}, 'iter': {'init': 0, 'step': 1}, 'name': 'spatial_temporal_network/rnn_net/rnn/while/LoopCond/TensorIteratorCondition_', 'dim_attrs': ['spatial_dims', 'channel_dims', 'axis', 'batch_dims'], 'shape_attrs': ['output_shape', 'shape', 'pad', 'window', 'stride'], 'IE': [('layer', [('id', . at 0x7fb075a41158>), 'name', 'precision', 'type'], [('data', ['time', 'iter'], []), '@ports', '@consts'])]} [ 2019-03-21 16:52:51,603 ] [ DEBUG ] [ op:208 ] Finished running infer function, data nodes attributes: {'name': 'spatial_temporal_network/rnn_net/rnn/while/LoopCond/Output_0/Data_', 'kind': 'data', 'shape': array([], dtype=float64), 'value': None, 'data_type': dtype('bool'), 'infer': None, 'dim_attrs': ['spatial_dims', 'channel_dims', 'axis', 'batch_dims'], 'shape_attrs': ['output_shape', 'shape', 'pad', 'window', 'stride'], 'fw_tensor_debug_info': [('spatial_temporal_network/rnn_net/rnn/while/LoopCond', 0)], 'is_output_reachable': True, 'is_undead': False, 'is_const_producer': False, 'is_partial_inferred': True, 'executable': True} [ 2019-03-21 16:52:51,603 ] [ DEBUG ] [ op:208 ] Finished running infer function, data nodes attributes: {'name': 'spatial_temporal_network/rnn_net/rnn/while/Identity_1/Output_0/Data_', 'kind': 'data', 'shape': array([], dtype=int64), 'value': None, 'data_type': None, 'infer': None, 'dim_attrs': ['spatial_dims', 'channel_dims', 'axis', 'batch_dims'], 'shape_attrs': ['output_shape', 'shape', 'pad', 'window', 'stride'], 'fw_tensor_debug_info': [('spatial_temporal_network/rnn_net/rnn/while/Identity_1', 0)], 'is_output_reachable': True, 'is_undead': False, 'is_const_producer': False, 'is_partial_inferred': True, 'executable': True} [ 2019-03-21 16:52:51,609 ] [ DEBUG ] [ TensorIteratorCondition:217 ] +++++++++++++++ SimpleConditionMatching ++++++++++++++++ [ 2019-03-21 16:52:51,913 ] [ DEBUG ] [ TensorIteratorBackEdge:87 ] ================== BackEdgeFind =============== [ 2019-03-21 16:52:51,914 ] [ DEBUG ] [ op:195 ] Start running infer function for individual op node with attributes: {'precision': 'FP32', 'kind': 'op', 'op': 'TensorIteratorBackEdge', 'infer': , 'name': 'spatial_temporal_network/rnn_net/rnn/while/Identity_4/TensorIteratorBackEdge_', 'dim_attrs': ['spatial_dims', 'channel_dims', 'axis', 'batch_dims'], 'shape_attrs': ['output_shape', 'shape', 'pad', 'window', 'stride'], 'IE': [('layer', [('id', . at 0x7fb075a4c510>), 'name', 'precision', 'type'], [('data', ['is_output'], []), '@ports', '@consts'])]} [ 2019-03-21 16:52:51,914 ] [ DEBUG ] [ op:208 ] Finished running infer function, data nodes attributes: {'name': 'spatial_temporal_network/rnn_net/rnn/while/Identity_4/Output_0/Data_', 'kind': 'data', 'shape': array([ 1, 512]), 'value': None, 'data_type': None, 'infer': None, 'dim_attrs': ['spatial_dims', 'channel_dims', 'axis', 'batch_dims'], 'shape_attrs': ['output_shape', 'shape', 'pad', 'window', 'stride'], 'fw_tensor_debug_info': [('spatial_temporal_network/rnn_net/rnn/while/Identity_4', 0)], 'is_output_reachable': True, 'is_undead': False, 'is_const_producer': False, 'is_partial_inferred': True, 'executable': True} [ 2019-03-21 16:52:51,915 ] [ DEBUG ] [ TensorIteratorBackEdge:87 ] ================== BackEdgeFind =============== [ 2019-03-21 16:52:51,915 ] [ DEBUG ] [ op:195 ] Start running infer function for individual op node with attributes: {'precision': 'FP32', 'kind': 'op', 'op': 'TensorIteratorBackEdge', 'infer': , 'name': 'spatial_temporal_network/rnn_net/rnn/while/Identity_8/TensorIteratorBackEdge_', 'dim_attrs': ['spatial_dims', 'channel_dims', 'axis', 'batch_dims'], 'shape_attrs': ['output_shape', 'shape', 'pad', 'window', 'stride'], 'IE': [('layer', [('id', . at 0x7fb075aa8598>), 'name', 'precision', 'type'], [('data', ['is_output'], []), '@ports', '@consts'])]} [ 2019-03-21 16:52:51,916 ] [ DEBUG ] [ op:208 ] Finished running infer function, data nodes attributes: {'name': 'spatial_temporal_network/rnn_net/rnn/while/Identity_8/Output_0/Data_', 'kind': 'data', 'shape': array([ 1, 512]), 'value': None, 'data_type': None, 'infer': None, 'dim_attrs': ['spatial_dims', 'channel_dims', 'axis', 'batch_dims'], 'shape_attrs': ['output_shape', 'shape', 'pad', 'window', 'stride'], 'fw_tensor_debug_info': [('spatial_temporal_network/rnn_net/rnn/while/Identity_8', 0)], 'is_output_reachable': True, 'is_undead': False, 'is_const_producer': False, 'is_partial_inferred': True, 'executable': True} [ 2019-03-21 16:52:51,916 ] [ DEBUG ] [ TensorIteratorBackEdge:87 ] ================== BackEdgeFind =============== [ 2019-03-21 16:52:51,917 ] [ DEBUG ] [ op:195 ] Start running infer function for individual op node with attributes: {'precision': 'FP32', 'kind': 'op', 'op': 'TensorIteratorBackEdge', 'infer': , 'name': 'spatial_temporal_network/rnn_net/rnn/while/Identity_6/TensorIteratorBackEdge_', 'dim_attrs': ['spatial_dims', 'channel_dims', 'axis', 'batch_dims'], 'shape_attrs': ['output_shape', 'shape', 'pad', 'window', 'stride'], 'IE': [('layer', [('id', . at 0x7fb075a46730>), 'name', 'precision', 'type'], [('data', ['is_output'], []), '@ports', '@consts'])]} [ 2019-03-21 16:52:51,918 ] [ DEBUG ] [ op:208 ] Finished running infer function, data nodes attributes: {'name': 'spatial_temporal_network/rnn_net/rnn/while/Identity_6/Output_0/Data_', 'kind': 'data', 'shape': array([ 1, 512]), 'value': None, 'data_type': None, 'infer': None, 'dim_attrs': ['spatial_dims', 'channel_dims', 'axis', 'batch_dims'], 'shape_attrs': ['output_shape', 'shape', 'pad', 'window', 'stride'], 'fw_tensor_debug_info': [('spatial_temporal_network/rnn_net/rnn/while/Identity_6', 0)], 'is_output_reachable': True, 'is_undead': False, 'is_const_producer': False, 'is_partial_inferred': True, 'executable': True} [ 2019-03-21 16:52:51,918 ] [ DEBUG ] [ TensorIteratorBackEdge:87 ] ================== BackEdgeFind =============== [ 2019-03-21 16:52:51,919 ] [ DEBUG ] [ op:195 ] Start running infer function for individual op node with attributes: {'precision': 'FP32', 'kind': 'op', 'op': 'TensorIteratorBackEdge', 'infer': , 'name': 'spatial_temporal_network/rnn_net/rnn/while/Identity_5/TensorIteratorBackEdge_', 'dim_attrs': ['spatial_dims', 'channel_dims', 'axis', 'batch_dims'], 'shape_attrs': ['output_shape', 'shape', 'pad', 'window', 'stride'], 'IE': [('layer', [('id', . at 0x7fb075a4bae8>), 'name', 'precision', 'type'], [('data', ['is_output'], []), '@ports', '@consts'])]} [ 2019-03-21 16:52:51,920 ] [ DEBUG ] [ op:208 ] Finished running infer function, data nodes attributes: {'name': 'spatial_temporal_network/rnn_net/rnn/while/Identity_5/Output_0/Data_', 'kind': 'data', 'shape': array([ 1, 512]), 'value': None, 'data_type': None, 'infer': None, 'dim_attrs': ['spatial_dims', 'channel_dims', 'axis', 'batch_dims'], 'shape_attrs': ['output_shape', 'shape', 'pad', 'window', 'stride'], 'fw_tensor_debug_info': [('spatial_temporal_network/rnn_net/rnn/while/Identity_5', 0)], 'is_output_reachable': True, 'is_undead': False, 'is_const_producer': False, 'is_partial_inferred': True, 'executable': True} [ 2019-03-21 16:52:51,920 ] [ DEBUG ] [ TensorIteratorBackEdge:87 ] ================== BackEdgeFind =============== [ 2019-03-21 16:52:51,921 ] [ DEBUG ] [ op:195 ] Start running infer function for individual op node with attributes: {'precision': 'FP32', 'kind': 'op', 'op': 'TensorIteratorBackEdge', 'infer': , 'name': 'spatial_temporal_network/rnn_net/rnn/while/Identity_3/TensorIteratorBackEdge_', 'dim_attrs': ['spatial_dims', 'channel_dims', 'axis', 'batch_dims'], 'shape_attrs': ['output_shape', 'shape', 'pad', 'window', 'stride'], 'IE': [('layer', [('id', . at 0x7fb075a4a2f0>), 'name', 'precision', 'type'], [('data', ['is_output'], []), '@ports', '@consts'])]} [ 2019-03-21 16:52:51,922 ] [ DEBUG ] [ op:208 ] Finished running infer function, data nodes attributes: {'name': 'spatial_temporal_network/rnn_net/rnn/while/Identity_3/Output_0/Data_', 'kind': 'data', 'shape': array([ 1, 512]), 'value': None, 'data_type': None, 'infer': None, 'dim_attrs': ['spatial_dims', 'channel_dims', 'axis', 'batch_dims'], 'shape_attrs': ['output_shape', 'shape', 'pad', 'window', 'stride'], 'fw_tensor_debug_info': [('spatial_temporal_network/rnn_net/rnn/while/Identity_3', 0)], 'is_output_reachable': True, 'is_undead': False, 'is_const_producer': False, 'is_partial_inferred': True, 'executable': True} [ 2019-03-21 16:52:51,922 ] [ DEBUG ] [ TensorIteratorBackEdge:87 ] ================== BackEdgeFind =============== [ 2019-03-21 16:52:51,923 ] [ DEBUG ] [ op:195 ] Start running infer function for individual op node with attributes: {'precision': 'FP32', 'kind': 'op', 'op': 'TensorIteratorBackEdge', 'infer': , 'name': 'spatial_temporal_network/rnn_net/rnn/while/Identity_7/TensorIteratorBackEdge_', 'dim_attrs': ['spatial_dims', 'channel_dims', 'axis', 'batch_dims'], 'shape_attrs': ['output_shape', 'shape', 'pad', 'window', 'stride'], 'IE': [('layer', [('id', . at 0x7fb075a4a048>), 'name', 'precision', 'type'], [('data', ['is_output'], []), '@ports', '@consts'])]} [ 2019-03-21 16:52:51,923 ] [ DEBUG ] [ op:208 ] Finished running infer function, data nodes attributes: {'name': 'spatial_temporal_network/rnn_net/rnn/while/Identity_7/Output_0/Data_', 'kind': 'data', 'shape': array([ 1, 512]), 'value': None, 'data_type': None, 'infer': None, 'dim_attrs': ['spatial_dims', 'channel_dims', 'axis', 'batch_dims'], 'shape_attrs': ['output_shape', 'shape', 'pad', 'window', 'stride'], 'fw_tensor_debug_info': [('spatial_temporal_network/rnn_net/rnn/while/Identity_7', 0)], 'is_output_reachable': True, 'is_undead': False, 'is_const_producer': False, 'is_partial_inferred': True, 'executable': True} [ 2019-03-21 16:52:51,930 ] [ DEBUG ] [ TensorIteratorConditionChecker:27 ] +++++++++++++++ ConditionCheckerMatching ++++++++++++++++ [ 2019-03-21 16:52:52,008 ] [ DEBUG ] [ infer:86 ] Removing the following not executable nodes: [ 2019-03-21 16:52:52,012 ] [ DEBUG ] [ eliminate:64 ] The following nodes are seeded as output reachable: output/Output_0/Data_ [ 2019-03-21 16:52:52,123 ] [ DEBUG ] [ eliminate:130 ] Removing the following dead nodes: 429 429/Output_0/Data_ spatial_temporal_network/dense/bias spatial_temporal_network/dense/bias/read spatial_temporal_network/dense/kernel spatial_temporal_network/dense/kernel/read spatial_temporal_network/flatten/Reshape/shape/1 spatial_temporal_network/flatten/Reshape/shape/Concat_ spatial_temporal_network/flatten/Reshape/shape/ExpandDims_ spatial_temporal_network/flatten/Reshape/shape/ExpandDims_431 spatial_temporal_network/flatten/Shape spatial_temporal_network/flatten/strided_slice spatial_temporal_network/flatten/strided_slice/stack spatial_temporal_network/flatten/strided_slice/stack_1 spatial_temporal_network/flatten/strided_slice/stack_2 spatial_temporal_network/geo/conblock_1/bn/batchnorm/Rsqrt spatial_temporal_network/geo/conblock_1/bn/batchnorm/add spatial_temporal_network/geo/conblock_1/bn/batchnorm/add/y spatial_temporal_network/geo/conblock_1/bn/batchnorm/mul spatial_temporal_network/geo/conblock_1/bn/batchnorm/mul_2 spatial_temporal_network/geo/conblock_1/bn/batchnorm/sub/add_ spatial_temporal_network/geo/conblock_1/bn/batchnorm/sub/negate_ spatial_temporal_network/geo/conblock_1/bn/beta spatial_temporal_network/geo/conblock_1/bn/beta/read spatial_temporal_network/geo/conblock_1/bn/gamma spatial_temporal_network/geo/conblock_1/bn/gamma/read spatial_temporal_network/geo/conblock_1/bn/moving_mean spatial_temporal_network/geo/conblock_1/bn/moving_mean/read spatial_temporal_network/geo/conblock_1/bn/moving_variance spatial_temporal_network/geo/conblock_1/bn/moving_variance/read spatial_temporal_network/geo/conblock_1/cov/bias spatial_temporal_network/geo/conblock_1/cov/bias/read spatial_temporal_network/geo/conblock_1/cov/conv1d/ExpandDims/dim spatial_temporal_network/geo/conblock_1/cov/conv1d/ExpandDims/dim/Output_0/Data_ spatial_temporal_network/geo/conblock_1/cov/conv1d/ExpandDims_1 spatial_temporal_network/geo/conblock_1/cov/conv1d/ExpandDims_1/dim spatial_temporal_network/geo/conblock_1/cov/conv1d/ExpandDims_1/dim/Output_0/Data_ spatial_temporal_network/geo/conblock_1/cov/kernel spatial_temporal_network/geo/conblock_1/cov/kernel/read spatial_temporal_network/geo/conblock_2/bn/batchnorm/Rsqrt spatial_temporal_network/geo/conblock_2/bn/batchnorm/add spatial_temporal_network/geo/conblock_2/bn/batchnorm/add/y spatial_temporal_network/geo/conblock_2/bn/batchnorm/mul spatial_temporal_network/geo/conblock_2/bn/batchnorm/mul_2 spatial_temporal_network/geo/conblock_2/bn/batchnorm/sub/add_ spatial_temporal_network/geo/conblock_2/bn/batchnorm/sub/negate_ spatial_temporal_network/geo/conblock_2/bn/beta spatial_temporal_network/geo/conblock_2/bn/beta/read spatial_temporal_network/geo/conblock_2/bn/gamma spatial_temporal_network/geo/conblock_2/bn/gamma/read spatial_temporal_network/geo/conblock_2/bn/moving_mean spatial_temporal_network/geo/conblock_2/bn/moving_mean/read spatial_temporal_network/geo/conblock_2/bn/moving_variance spatial_temporal_network/geo/conblock_2/bn/moving_variance/read spatial_temporal_network/geo/conblock_2/cov/bias spatial_temporal_network/geo/conblock_2/cov/bias/read spatial_temporal_network/geo/conblock_2/cov/conv1d/ExpandDims/dim spatial_temporal_network/geo/conblock_2/cov/conv1d/ExpandDims/dim/Output_0/Data_ spatial_temporal_network/geo/conblock_2/cov/conv1d/ExpandDims_1 spatial_temporal_network/geo/conblock_2/cov/conv1d/ExpandDims_1/dim spatial_temporal_network/geo/conblock_2/cov/conv1d/ExpandDims_1/dim/Output_0/Data_ spatial_temporal_network/geo/conblock_2/cov/kernel spatial_temporal_network/geo/conblock_2/cov/kernel/read spatial_temporal_network/geo/conblock_3/bn/batchnorm/Rsqrt spatial_temporal_network/geo/conblock_3/bn/batchnorm/add spatial_temporal_network/geo/conblock_3/bn/batchnorm/add/y spatial_temporal_network/geo/conblock_3/bn/batchnorm/mul spatial_temporal_network/geo/conblock_3/bn/batchnorm/mul_2 spatial_temporal_network/geo/conblock_3/bn/batchnorm/sub/add_ spatial_temporal_network/geo/conblock_3/bn/batchnorm/sub/negate_ spatial_temporal_network/geo/conblock_3/bn/beta spatial_temporal_network/geo/conblock_3/bn/beta/read spatial_temporal_network/geo/conblock_3/bn/gamma spatial_temporal_network/geo/conblock_3/bn/gamma/read spatial_temporal_network/geo/conblock_3/bn/moving_mean spatial_temporal_network/geo/conblock_3/bn/moving_mean/read spatial_temporal_network/geo/conblock_3/bn/moving_variance spatial_temporal_network/geo/conblock_3/bn/moving_variance/read spatial_temporal_network/geo/conblock_3/cov/bias spatial_temporal_network/geo/conblock_3/cov/bias/read spatial_temporal_network/geo/conblock_3/cov/conv1d/ExpandDims/dim spatial_temporal_network/geo/conblock_3/cov/conv1d/ExpandDims/dim/Output_0/Data_ spatial_temporal_network/geo/conblock_3/cov/conv1d/ExpandDims_1 spatial_temporal_network/geo/conblock_3/cov/conv1d/ExpandDims_1/dim spatial_temporal_network/geo/conblock_3/cov/conv1d/ExpandDims_1/dim/Output_0/Data_ spatial_temporal_network/geo/conblock_3/cov/kernel spatial_temporal_network/geo/conblock_3/cov/kernel/read spatial_temporal_network/motion/conblock_1/bn/batchnorm/Rsqrt spatial_temporal_network/motion/conblock_1/bn/batchnorm/add spatial_temporal_network/motion/conblock_1/bn/batchnorm/add/y spatial_temporal_network/motion/conblock_1/bn/batchnorm/mul spatial_temporal_network/motion/conblock_1/bn/batchnorm/mul_2 spatial_temporal_network/motion/conblock_1/bn/batchnorm/sub/add_ spatial_temporal_network/motion/conblock_1/bn/batchnorm/sub/negate_ spatial_temporal_network/motion/conblock_1/bn/beta spatial_temporal_network/motion/conblock_1/bn/beta/read spatial_temporal_network/motion/conblock_1/bn/gamma spatial_temporal_network/motion/conblock_1/bn/gamma/read spatial_temporal_network/motion/conblock_1/bn/moving_mean spatial_temporal_network/motion/conblock_1/bn/moving_mean/read spatial_temporal_network/motion/conblock_1/bn/moving_variance spatial_temporal_network/motion/conblock_1/bn/moving_variance/read spatial_temporal_network/motion/conblock_1/cov/bias spatial_temporal_network/motion/conblock_1/cov/bias/read spatial_temporal_network/motion/conblock_1/cov/conv1d/ExpandDims/dim spatial_temporal_network/motion/conblock_1/cov/conv1d/ExpandDims/dim/Output_0/Data_ spatial_temporal_network/motion/conblock_1/cov/conv1d/ExpandDims_1 spatial_temporal_network/motion/conblock_1/cov/conv1d/ExpandDims_1/dim spatial_temporal_network/motion/conblock_1/cov/conv1d/ExpandDims_1/dim/Output_0/Data_ spatial_temporal_network/motion/conblock_1/cov/kernel spatial_temporal_network/motion/conblock_1/cov/kernel/read spatial_temporal_network/motion/conblock_2/bn/batchnorm/Rsqrt spatial_temporal_network/motion/conblock_2/bn/batchnorm/add spatial_temporal_network/motion/conblock_2/bn/batchnorm/add/y spatial_temporal_network/motion/conblock_2/bn/batchnorm/mul spatial_temporal_network/motion/conblock_2/bn/batchnorm/mul_2 spatial_temporal_network/motion/conblock_2/bn/batchnorm/sub/add_ spatial_temporal_network/motion/conblock_2/bn/batchnorm/sub/negate_ spatial_temporal_network/motion/conblock_2/bn/beta spatial_temporal_network/motion/conblock_2/bn/beta/read spatial_temporal_network/motion/conblock_2/bn/gamma spatial_temporal_network/motion/conblock_2/bn/gamma/read spatial_temporal_network/motion/conblock_2/bn/moving_mean spatial_temporal_network/motion/conblock_2/bn/moving_mean/read spatial_temporal_network/motion/conblock_2/bn/moving_variance spatial_temporal_network/motion/conblock_2/bn/moving_variance/read spatial_temporal_network/motion/conblock_2/cov/bias spatial_temporal_network/motion/conblock_2/cov/bias/read spatial_temporal_network/motion/conblock_2/cov/conv1d/ExpandDims/dim spatial_temporal_network/motion/conblock_2/cov/conv1d/ExpandDims/dim/Output_0/Data_ spatial_temporal_network/motion/conblock_2/cov/conv1d/ExpandDims_1 spatial_temporal_network/motion/conblock_2/cov/conv1d/ExpandDims_1/dim spatial_temporal_network/motion/conblock_2/cov/conv1d/ExpandDims_1/dim/Output_0/Data_ spatial_temporal_network/motion/conblock_2/cov/kernel spatial_temporal_network/motion/conblock_2/cov/kernel/read spatial_temporal_network/motion/conblock_3/bn/batchnorm/Rsqrt spatial_temporal_network/motion/conblock_3/bn/batchnorm/add spatial_temporal_network/motion/conblock_3/bn/batchnorm/add/y spatial_temporal_network/motion/conblock_3/bn/batchnorm/mul spatial_temporal_network/motion/conblock_3/bn/batchnorm/mul_2 spatial_temporal_network/motion/conblock_3/bn/batchnorm/sub/add_ spatial_temporal_network/motion/conblock_3/bn/batchnorm/sub/negate_ spatial_temporal_network/motion/conblock_3/bn/beta spatial_temporal_network/motion/conblock_3/bn/beta/read spatial_temporal_network/motion/conblock_3/bn/gamma spatial_temporal_network/motion/conblock_3/bn/gamma/read spatial_temporal_network/motion/conblock_3/bn/moving_mean spatial_temporal_network/motion/conblock_3/bn/moving_mean/read spatial_temporal_network/motion/conblock_3/bn/moving_variance spatial_temporal_network/motion/conblock_3/bn/moving_variance/read spatial_temporal_network/motion/conblock_3/cov/bias spatial_temporal_network/motion/conblock_3/cov/bias/read spatial_temporal_network/motion/conblock_3/cov/conv1d/ExpandDims/dim spatial_temporal_network/motion/conblock_3/cov/conv1d/ExpandDims/dim/Output_0/Data_ spatial_temporal_network/motion/conblock_3/cov/conv1d/ExpandDims_1 spatial_temporal_network/motion/conblock_3/cov/conv1d/ExpandDims_1/dim spatial_temporal_network/motion/conblock_3/cov/conv1d/ExpandDims_1/dim/Output_0/Data_ spatial_temporal_network/motion/conblock_3/cov/kernel spatial_temporal_network/motion/conblock_3/cov/kernel/read spatial_temporal_network/motion/conblock_4/bn/batchnorm/Rsqrt spatial_temporal_network/motion/conblock_4/bn/batchnorm/add spatial_temporal_network/motion/conblock_4/bn/batchnorm/add/y spatial_temporal_network/motion/conblock_4/bn/batchnorm/mul spatial_temporal_network/motion/conblock_4/bn/batchnorm/mul_2 spatial_temporal_network/motion/conblock_4/bn/batchnorm/sub/add_ spatial_temporal_network/motion/conblock_4/bn/batchnorm/sub/negate_ spatial_temporal_network/motion/conblock_4/bn/beta spatial_temporal_network/motion/conblock_4/bn/beta/read spatial_temporal_network/motion/conblock_4/bn/gamma spatial_temporal_network/motion/conblock_4/bn/gamma/read spatial_temporal_network/motion/conblock_4/bn/moving_mean spatial_temporal_network/motion/conblock_4/bn/moving_mean/read spatial_temporal_network/motion/conblock_4/bn/moving_variance spatial_temporal_network/motion/conblock_4/bn/moving_variance/read spatial_temporal_network/motion/conblock_4/cov/bias spatial_temporal_network/motion/conblock_4/cov/bias/read spatial_temporal_network/motion/conblock_4/cov/conv1d/ExpandDims/dim spatial_temporal_network/motion/conblock_4/cov/conv1d/ExpandDims/dim/Output_0/Data_ spatial_temporal_network/motion/conblock_4/cov/conv1d/ExpandDims_1 spatial_temporal_network/motion/conblock_4/cov/conv1d/ExpandDims_1/dim spatial_temporal_network/motion/conblock_4/cov/conv1d/ExpandDims_1/dim/Output_0/Data_ spatial_temporal_network/motion/conblock_4/cov/kernel spatial_temporal_network/motion/conblock_4/cov/kernel/read spatial_temporal_network/rnn_net/rnn/Maximum spatial_temporal_network/rnn_net/rnn/Maximum/x spatial_temporal_network/rnn_net/rnn/Minimum spatial_temporal_network/rnn_net/rnn/MultiRNNCellZeroState/LSTMCellZeroState/Const spatial_temporal_network/rnn_net/rnn/MultiRNNCellZeroState/LSTMCellZeroState/Const_1 spatial_temporal_network/rnn_net/rnn/MultiRNNCellZeroState/LSTMCellZeroState/Const_4 spatial_temporal_network/rnn_net/rnn/MultiRNNCellZeroState/LSTMCellZeroState/Const_5 spatial_temporal_network/rnn_net/rnn/MultiRNNCellZeroState/LSTMCellZeroState/concat spatial_temporal_network/rnn_net/rnn/MultiRNNCellZeroState/LSTMCellZeroState/concat/axis spatial_temporal_network/rnn_net/rnn/MultiRNNCellZeroState/LSTMCellZeroState/concat/axis/Output_0/Data_ spatial_temporal_network/rnn_net/rnn/MultiRNNCellZeroState/LSTMCellZeroState/concat_1 spatial_temporal_network/rnn_net/rnn/MultiRNNCellZeroState/LSTMCellZeroState/concat_1/axis spatial_temporal_network/rnn_net/rnn/MultiRNNCellZeroState/LSTMCellZeroState/concat_1/axis/Output_0/Data_ spatial_temporal_network/rnn_net/rnn/MultiRNNCellZeroState/LSTMCellZeroState/zeros spatial_temporal_network/rnn_net/rnn/MultiRNNCellZeroState/LSTMCellZeroState/zeros/Const spatial_temporal_network/rnn_net/rnn/MultiRNNCellZeroState/LSTMCellZeroState/zeros_1 spatial_temporal_network/rnn_net/rnn/MultiRNNCellZeroState/LSTMCellZeroState/zeros_1/Const spatial_temporal_network/rnn_net/rnn/MultiRNNCellZeroState/LSTMCellZeroState_1/Const spatial_temporal_network/rnn_net/rnn/MultiRNNCellZeroState/LSTMCellZeroState_1/Const_1 spatial_temporal_network/rnn_net/rnn/MultiRNNCellZeroState/LSTMCellZeroState_1/Const_4 spatial_temporal_network/rnn_net/rnn/MultiRNNCellZeroState/LSTMCellZeroState_1/Const_5 spatial_temporal_network/rnn_net/rnn/MultiRNNCellZeroState/LSTMCellZeroState_1/concat spatial_temporal_network/rnn_net/rnn/MultiRNNCellZeroState/LSTMCellZeroState_1/concat/axis spatial_temporal_network/rnn_net/rnn/MultiRNNCellZeroState/LSTMCellZeroState_1/concat/axis/Output_0/Data_ spatial_temporal_network/rnn_net/rnn/MultiRNNCellZeroState/LSTMCellZeroState_1/concat_1 spatial_temporal_network/rnn_net/rnn/MultiRNNCellZeroState/LSTMCellZeroState_1/concat_1/axis spatial_temporal_network/rnn_net/rnn/MultiRNNCellZeroState/LSTMCellZeroState_1/concat_1/axis/Output_0/Data_ spatial_temporal_network/rnn_net/rnn/MultiRNNCellZeroState/LSTMCellZeroState_1/zeros spatial_temporal_network/rnn_net/rnn/MultiRNNCellZeroState/LSTMCellZeroState_1/zeros/Const spatial_temporal_network/rnn_net/rnn/MultiRNNCellZeroState/LSTMCellZeroState_1/zeros_1 spatial_temporal_network/rnn_net/rnn/MultiRNNCellZeroState/LSTMCellZeroState_1/zeros_1/Const spatial_temporal_network/rnn_net/rnn/MultiRNNCellZeroState/LSTMCellZeroState_2/Const spatial_temporal_network/rnn_net/rnn/MultiRNNCellZeroState/LSTMCellZeroState_2/Const_1 spatial_temporal_network/rnn_net/rnn/MultiRNNCellZeroState/LSTMCellZeroState_2/Const_4 spatial_temporal_network/rnn_net/rnn/MultiRNNCellZeroState/LSTMCellZeroState_2/Const_5 spatial_temporal_network/rnn_net/rnn/MultiRNNCellZeroState/LSTMCellZeroState_2/concat spatial_temporal_network/rnn_net/rnn/MultiRNNCellZeroState/LSTMCellZeroState_2/concat/axis spatial_temporal_network/rnn_net/rnn/MultiRNNCellZeroState/LSTMCellZeroState_2/concat/axis/Output_0/Data_ spatial_temporal_network/rnn_net/rnn/MultiRNNCellZeroState/LSTMCellZeroState_2/concat_1 spatial_temporal_network/rnn_net/rnn/MultiRNNCellZeroState/LSTMCellZeroState_2/concat_1/axis spatial_temporal_network/rnn_net/rnn/MultiRNNCellZeroState/LSTMCellZeroState_2/concat_1/axis/Output_0/Data_ spatial_temporal_network/rnn_net/rnn/MultiRNNCellZeroState/LSTMCellZeroState_2/zeros spatial_temporal_network/rnn_net/rnn/MultiRNNCellZeroState/LSTMCellZeroState_2/zeros/Const spatial_temporal_network/rnn_net/rnn/MultiRNNCellZeroState/LSTMCellZeroState_2/zeros_1 spatial_temporal_network/rnn_net/rnn/MultiRNNCellZeroState/LSTMCellZeroState_2/zeros_1/Const spatial_temporal_network/rnn_net/rnn/Rank spatial_temporal_network/rnn_net/rnn/Rank/Output_0/Data_ spatial_temporal_network/rnn_net/rnn/Rank_1 spatial_temporal_network/rnn_net/rnn/Rank_1/Output_0/Data_ spatial_temporal_network/rnn_net/rnn/Shape spatial_temporal_network/rnn_net/rnn/TensorArrayUnstack/Shape spatial_temporal_network/rnn_net/rnn/TensorArrayUnstack/Shape/Output_0/Data_ spatial_temporal_network/rnn_net/rnn/concat spatial_temporal_network/rnn_net/rnn/concat/Output_0/Data_ spatial_temporal_network/rnn_net/rnn/concat/axis spatial_temporal_network/rnn_net/rnn/concat/axis/Output_0/Data_ spatial_temporal_network/rnn_net/rnn/concat/values_0 spatial_temporal_network/rnn_net/rnn/concat/values_0/Output_0/Data_ spatial_temporal_network/rnn_net/rnn/concat_2 spatial_temporal_network/rnn_net/rnn/concat_2/Output_0/Data_ spatial_temporal_network/rnn_net/rnn/concat_2/axis spatial_temporal_network/rnn_net/rnn/concat_2/axis/Output_0/Data_ spatial_temporal_network/rnn_net/rnn/concat_2/values_0 spatial_temporal_network/rnn_net/rnn/concat_2/values_0/Output_0/Data_ spatial_temporal_network/rnn_net/rnn/multi_rnn_cell/cell_0/lstm_cell/bias spatial_temporal_network/rnn_net/rnn/multi_rnn_cell/cell_0/lstm_cell/bias/read spatial_temporal_network/rnn_net/rnn/multi_rnn_cell/cell_0/lstm_cell/kernel spatial_temporal_network/rnn_net/rnn/multi_rnn_cell/cell_0/lstm_cell/kernel/read spatial_temporal_network/rnn_net/rnn/range spatial_temporal_network/rnn_net/rnn/range/Output_0/Data_ spatial_temporal_network/rnn_net/rnn/range/delta spatial_temporal_network/rnn_net/rnn/range/delta/Output_0/Data_ spatial_temporal_network/rnn_net/rnn/range/start spatial_temporal_network/rnn_net/rnn/range/start/Output_0/Data_ spatial_temporal_network/rnn_net/rnn/range_1 spatial_temporal_network/rnn_net/rnn/range_1/Output_0/Data_ spatial_temporal_network/rnn_net/rnn/range_1/delta spatial_temporal_network/rnn_net/rnn/range_1/delta/Output_0/Data_ spatial_temporal_network/rnn_net/rnn/range_1/start spatial_temporal_network/rnn_net/rnn/range_1/start/Output_0/Data_ spatial_temporal_network/rnn_net/rnn/strided_slice spatial_temporal_network/rnn_net/rnn/strided_slice/stack spatial_temporal_network/rnn_net/rnn/strided_slice/stack_1 spatial_temporal_network/rnn_net/rnn/strided_slice/stack_2 spatial_temporal_network/rnn_net/rnn/while/Enter_3 spatial_temporal_network/rnn_net/rnn/while/Enter_4 spatial_temporal_network/rnn_net/rnn/while/Enter_5 spatial_temporal_network/rnn_net/rnn/while/Enter_6 spatial_temporal_network/rnn_net/rnn/while/Enter_7 spatial_temporal_network/rnn_net/rnn/while/Enter_8 spatial_temporal_network/rnn_net/rnn/while/NextIteration/Output_0/Data_ spatial_temporal_network/rnn_net/rnn/while/NextIteration_1/Output_0/Data_ spatial_temporal_network/rnn_net/rnn/while/NextIteration_2/Output_0/Data_ spatial_temporal_network/rnn_net/rnn/while/rnn/multi_rnn_cell/cell_0/lstm_cell/BiasAdd/Enter spatial_temporal_network/rnn_net/rnn/while/rnn/multi_rnn_cell/cell_0/lstm_cell/MatMul/Enter spatial_temporal_network/rnn_net/rnn/while/rnn/multi_rnn_cell/cell_0/lstm_cell/add/y spatial_temporal_network/rnn_net/rnn/while/rnn/multi_rnn_cell/cell_0/lstm_cell/add_2/y spatial_temporal_network/rnn_net/rnn/while/rnn/multi_rnn_cell/cell_0/lstm_cell/add_4/y spatial_temporal_network/rnn_net/rnn/while/rnn/multi_rnn_cell/cell_0/lstm_cell/concat/axis spatial_temporal_network/rnn_net/rnn/while/rnn/multi_rnn_cell/cell_0/lstm_cell/concat_1/axis spatial_temporal_network/rnn_net/rnn/while/rnn/multi_rnn_cell/cell_0/lstm_cell/concat_2/axis spatial_temporal_network/rnn_net/rnn/while/rnn/multi_rnn_cell/cell_0/lstm_cell/split/split_dim spatial_temporal_network/rnn_net/rnn/while/rnn/multi_rnn_cell/cell_0/lstm_cell/split_1/split_dim spatial_temporal_network/rnn_net/rnn/while/rnn/multi_rnn_cell/cell_0/lstm_cell/split_2/split_dim [ 2019-03-21 16:52:52,202 ] [ DEBUG ] [ TensorIteratorInput:207 ] ================== SimpleBackEdgeInputFind =============== [ 2019-03-21 16:52:52,203 ] [ DEBUG ] [ op:195 ] Start running infer function for individual op node with attributes: {'precision': 'FP32', 'kind': 'op', 'op': 'TensorIteratorInput', 'axis': None, 'start': None, 'end': None, 'stride': None, 'part_size': None, 'infer': , 'external_port_id': None, 'internal_layer_id': None, 'name': 'spatial_temporal_network/rnn_net/rnn/while/Identity_4/TensorIteratorBackEdge_/TensorIteratorInput_', 'dim_attrs': ['spatial_dims', 'channel_dims', 'axis', 'batch_dims'], 'shape_attrs': ['output_shape', 'shape', 'pad', 'window', 'stride'], 'IE': [('layer', [('id', . at 0x7fb075ba0378>), 'name', 'precision', 'type'], [('data', ['external_port_id', 'internal_layer_id', 'internal_port_id', 'axis', 'start', 'stride', 'part_size'], []), '@ports', '@consts'])]} [ 2019-03-21 16:52:52,203 ] [ DEBUG ] [ op:208 ] Finished running infer function, data nodes attributes: {'kind': 'data', 'precision': 'FP32', 'name': '863', 'value': None, 'shape': None, 'data_type': None, 'infer': None, 'dim_attrs': ['spatial_dims', 'channel_dims', 'axis', 'batch_dims'], 'shape_attrs': ['output_shape', 'shape', 'pad', 'window', 'stride']} [ 2019-03-21 16:52:52,204 ] [ DEBUG ] [ TensorIteratorInput:207 ] ================== SimpleBackEdgeInputFind =============== [ 2019-03-21 16:52:52,205 ] [ DEBUG ] [ op:195 ] Start running infer function for individual op node with attributes: {'precision': 'FP32', 'kind': 'op', 'op': 'TensorIteratorInput', 'axis': None, 'start': None, 'end': None, 'stride': None, 'part_size': None, 'infer': , 'external_port_id': None, 'internal_layer_id': None, 'name': 'spatial_temporal_network/rnn_net/rnn/while/Identity_5/TensorIteratorBackEdge_/TensorIteratorInput_', 'dim_attrs': ['spatial_dims', 'channel_dims', 'axis', 'batch_dims'], 'shape_attrs': ['output_shape', 'shape', 'pad', 'window', 'stride'], 'IE': [('layer', [('id', . at 0x7fb075acc950>), 'name', 'precision', 'type'], [('data', ['external_port_id', 'internal_layer_id', 'internal_port_id', 'axis', 'start', 'stride', 'part_size'], []), '@ports', '@consts'])]} [ 2019-03-21 16:52:52,206 ] [ DEBUG ] [ op:208 ] Finished running infer function, data nodes attributes: {'kind': 'data', 'precision': 'FP32', 'name': '865', 'value': None, 'shape': None, 'data_type': None, 'infer': None, 'dim_attrs': ['spatial_dims', 'channel_dims', 'axis', 'batch_dims'], 'shape_attrs': ['output_shape', 'shape', 'pad', 'window', 'stride']} [ 2019-03-21 16:52:52,206 ] [ DEBUG ] [ TensorIteratorInput:207 ] ================== SimpleBackEdgeInputFind =============== [ 2019-03-21 16:52:52,207 ] [ DEBUG ] [ op:195 ] Start running infer function for individual op node with attributes: {'precision': 'FP32', 'kind': 'op', 'op': 'TensorIteratorInput', 'axis': None, 'start': None, 'end': None, 'stride': None, 'part_size': None, 'infer': , 'external_port_id': None, 'internal_layer_id': None, 'name': 'spatial_temporal_network/rnn_net/rnn/while/Identity_3/TensorIteratorBackEdge_/TensorIteratorInput_', 'dim_attrs': ['spatial_dims', 'channel_dims', 'axis', 'batch_dims'], 'shape_attrs': ['output_shape', 'shape', 'pad', 'window', 'stride'], 'IE': [('layer', [('id', . at 0x7fb075accf28>), 'name', 'precision', 'type'], [('data', ['external_port_id', 'internal_layer_id', 'internal_port_id', 'axis', 'start', 'stride', 'part_size'], []), '@ports', '@consts'])]} [ 2019-03-21 16:52:52,207 ] [ DEBUG ] [ op:208 ] Finished running infer function, data nodes attributes: {'kind': 'data', 'precision': 'FP32', 'name': '867', 'value': None, 'shape': None, 'data_type': None, 'infer': None, 'dim_attrs': ['spatial_dims', 'channel_dims', 'axis', 'batch_dims'], 'shape_attrs': ['output_shape', 'shape', 'pad', 'window', 'stride']} [ 2019-03-21 16:52:52,207 ] [ DEBUG ] [ TensorIteratorInput:207 ] ================== SimpleBackEdgeInputFind =============== [ 2019-03-21 16:52:52,208 ] [ DEBUG ] [ op:195 ] Start running infer function for individual op node with attributes: {'precision': 'FP32', 'kind': 'op', 'op': 'TensorIteratorInput', 'axis': None, 'start': None, 'end': None, 'stride': None, 'part_size': None, 'infer': , 'external_port_id': None, 'internal_layer_id': None, 'name': 'spatial_temporal_network/rnn_net/rnn/while/Identity_6/TensorIteratorBackEdge_/TensorIteratorInput_', 'dim_attrs': ['spatial_dims', 'channel_dims', 'axis', 'batch_dims'], 'shape_attrs': ['output_shape', 'shape', 'pad', 'window', 'stride'], 'IE': [('layer', [('id', . at 0x7fb075a139d8>), 'name', 'precision', 'type'], [('data', ['external_port_id', 'internal_layer_id', 'internal_port_id', 'axis', 'start', 'stride', 'part_size'], []), '@ports', '@consts'])]} [ 2019-03-21 16:52:52,209 ] [ DEBUG ] [ op:208 ] Finished running infer function, data nodes attributes: {'kind': 'data', 'precision': 'FP32', 'name': '869', 'value': None, 'shape': None, 'data_type': None, 'infer': None, 'dim_attrs': ['spatial_dims', 'channel_dims', 'axis', 'batch_dims'], 'shape_attrs': ['output_shape', 'shape', 'pad', 'window', 'stride']} [ 2019-03-21 16:52:52,209 ] [ DEBUG ] [ TensorIteratorInput:207 ] ================== SimpleBackEdgeInputFind =============== [ 2019-03-21 16:52:52,210 ] [ DEBUG ] [ op:195 ] Start running infer function for individual op node with attributes: {'precision': 'FP32', 'kind': 'op', 'op': 'TensorIteratorInput', 'axis': None, 'start': None, 'end': None, 'stride': None, 'part_size': None, 'infer': , 'external_port_id': None, 'internal_layer_id': None, 'name': 'spatial_temporal_network/rnn_net/rnn/while/Identity_8/TensorIteratorBackEdge_/TensorIteratorInput_', 'dim_attrs': ['spatial_dims', 'channel_dims', 'axis', 'batch_dims'], 'shape_attrs': ['output_shape', 'shape', 'pad', 'window', 'stride'], 'IE': [('layer', [('id', . at 0x7fb075b77a60>), 'name', 'precision', 'type'], [('data', ['external_port_id', 'internal_layer_id', 'internal_port_id', 'axis', 'start', 'stride', 'part_size'], []), '@ports', '@consts'])]} [ 2019-03-21 16:52:52,210 ] [ DEBUG ] [ op:208 ] Finished running infer function, data nodes attributes: {'kind': 'data', 'precision': 'FP32', 'name': '871', 'value': None, 'shape': None, 'data_type': None, 'infer': None, 'dim_attrs': ['spatial_dims', 'channel_dims', 'axis', 'batch_dims'], 'shape_attrs': ['output_shape', 'shape', 'pad', 'window', 'stride']} [ 2019-03-21 16:52:52,210 ] [ DEBUG ] [ TensorIteratorInput:207 ] ================== SimpleBackEdgeInputFind =============== [ 2019-03-21 16:52:52,211 ] [ DEBUG ] [ op:195 ] Start running infer function for individual op node with attributes: {'precision': 'FP32', 'kind': 'op', 'op': 'TensorIteratorInput', 'axis': None, 'start': None, 'end': None, 'stride': None, 'part_size': None, 'infer': , 'external_port_id': None, 'internal_layer_id': None, 'name': 'spatial_temporal_network/rnn_net/rnn/while/Identity_7/TensorIteratorBackEdge_/TensorIteratorInput_', 'dim_attrs': ['spatial_dims', 'channel_dims', 'axis', 'batch_dims'], 'shape_attrs': ['output_shape', 'shape', 'pad', 'window', 'stride'], 'IE': [('layer', [('id', . at 0x7fb075a22510>), 'name', 'precision', 'type'], [('data', ['external_port_id', 'internal_layer_id', 'internal_port_id', 'axis', 'start', 'stride', 'part_size'], []), '@ports', '@consts'])]} [ 2019-03-21 16:52:52,211 ] [ DEBUG ] [ op:208 ] Finished running infer function, data nodes attributes: {'kind': 'data', 'precision': 'FP32', 'name': '873', 'value': None, 'shape': None, 'data_type': None, 'infer': None, 'dim_attrs': ['spatial_dims', 'channel_dims', 'axis', 'batch_dims'], 'shape_attrs': ['output_shape', 'shape', 'pad', 'window', 'stride']} [ 2019-03-21 16:52:52,275 ] [ DEBUG ] [ op:195 ] Start running infer function for individual op node with attributes: {'precision': 'FP32', 'kind': 'op', 'type': 'Reshape', 'op': 'Reshape', 'infer': . at 0x7fb075b70e18>, 'name': 'spatial_temporal_network/rnn_net/rnn/while/TensorArrayReadV3/Output_0/Data_/InputSqueeze', 'dim': array([ -1, 512]), 'dim_attrs': ['spatial_dims', 'channel_dims', 'axis', 'batch_dims'], 'shape_attrs': ['output_shape', 'shape', 'pad', 'window', 'stride'], 'IE': [('layer', [('id', . at 0x7fb075a22488>), 'name', 'precision', 'type'], [('data', [('dim', . at 0x7fb075a22400>)], []), '@ports', '@consts'])]} [ 2019-03-21 16:52:52,276 ] [ DEBUG ] [ op:208 ] Finished running infer function, data nodes attributes: {'name': 'spatial_temporal_network/rnn_net/rnn/while/TensorArrayReadV3/Output_0/Data_', 'kind': 'data', 'shape': array([ 1, 512]), 'value': None, 'data_type': None, 'infer': None, 'dim_attrs': ['spatial_dims', 'channel_dims', 'axis', 'batch_dims'], 'shape_attrs': ['output_shape', 'shape', 'pad', 'window', 'stride'], 'fw_tensor_debug_info': [('spatial_temporal_network/rnn_net/rnn/while/TensorArrayReadV3', 0)], 'is_output_reachable': True, 'is_undead': False, 'is_const_producer': False, 'is_partial_inferred': True, 'executable': True, 'prev': 'spatial_temporal_network/rnn_net/rnn/while/TensorArrayReadV3/TensorIteratorInput_'} [ 2019-03-21 16:52:52,278 ] [ DEBUG ] [ op:195 ] Start running infer function for individual op node with attributes: {'precision': 'FP32', 'kind': 'op', 'type': 'Reshape', 'op': 'Reshape', 'infer': . at 0x7fb075a13a60>, 'name': 'spatial_temporal_network/rnn_net/rnn/while/rnn/multi_rnn_cell/cell_0/lstm_cell/concat_2/LSTMCell/Output_0/Data_/OutputUnsqueeze', 'dim': array([ 1, -1, 512]), 'dim_attrs': ['spatial_dims', 'channel_dims', 'axis', 'batch_dims'], 'shape_attrs': ['output_shape', 'shape', 'pad', 'window', 'stride'], 'IE': [('layer', [('id', . at 0x7fb075acc840>), 'name', 'precision', 'type'], [('data', [('dim', . at 0x7fb075acc7b8>)], []), '@ports', '@consts'])]} [ 2019-03-21 16:52:52,280 ] [ DEBUG ] [ op:208 ] Finished running infer function, data nodes attributes: {'kind': 'data', 'precision': 'FP32', 'name': '877', 'value': None, 'shape': array([ 1, 1, 512]), 'data_type': None, 'infer': None, 'dim_attrs': ['spatial_dims', 'channel_dims', 'axis', 'batch_dims'], 'shape_attrs': ['output_shape', 'shape', 'pad', 'window', 'stride']} [ 2019-03-21 16:52:52,281 ] [ DEBUG ] [ op:195 ] Start running infer function for individual op node with attributes: {'precision': 'FP32', 'kind': 'op', 'type': 'TensorIterator', 'op': 'TensorIterator', 'input_port_map': [{'external_port_id': 15, 'internal_layer_id': 16, 'internal_port_id': 17, 'axis': 0, 'stride': None, 'part_size': None, 'start': 0, 'end': None}, {'external_port_id': 18, 'internal_layer_id': 0, 'internal_port_id': 2, 'axis': None, 'stride': None, 'part_size': None, 'start': None, 'end': None}, {'external_port_id': 19, 'internal_layer_id': 0, 'internal_port_id': 12, 'axis': None, 'stride': None, 'part_size': None, 'start': None, 'end': None}, {'external_port_id': 20, 'internal_layer_id': 6, 'internal_port_id': 8, 'axis': None, 'stride': None, 'part_size': None, 'start': None, 'end': None}, {'external_port_id': 21, 'internal_layer_id': 6, 'internal_port_id': 10, 'axis': None, 'stride': None, 'part_size': None, 'start': None, 'end': None}, {'external_port_id': 22, 'internal_layer_id': 3, 'internal_port_id': 5, 'axis': None, 'stride': None, 'part_size': None, 'start': None, 'end': None}, {'external_port_id': 23, 'internal_layer_id': 3, 'internal_port_id': 14, 'axis': None, 'stride': None, 'part_size': None, 'start': None, 'end': None}], 'output_port_map': [{'external_port_id': 26, 'internal_layer_id': 24, 'internal_port_id': 25, 'axis': 0, 'stride': None, 'part_size': None, 'start': None, 'end': None}], 'back_edges': [{'from_layer': 0, 'from_port': 1, 'to_layer': 0, 'to_port': 2}, {'from_layer': 3, 'from_port': 4, 'to_layer': 3, 'to_port': 5}, {'from_layer': 6, 'from_port': 7, 'to_layer': 6, 'to_port': 8}, {'from_layer': 6, 'from_port': 9, 'to_layer': 6, 'to_port': 10}, {'from_layer': 0, 'from_port': 11, 'to_layer': 0, 'to_port': 12}, {'from_layer': 3, 'from_port': 13, 'to_layer': 3, 'to_port': 14}], 'body': , 'sub_graphs': ['body'], 'infer': , 'name': 'spatial_temporal_network/rnn_net/rnn/while/LoopCond/TensorIteratorCondition_/TensorIterator', 'dim_attrs': ['spatial_dims', 'channel_dims', 'axis', 'batch_dims'], 'shape_attrs': ['output_shape', 'shape', 'pad', 'window', 'stride'], 'IE': [('layer', [('id', . at 0x7fb075b4a7b8>), 'name', 'precision', 'type'], [('data', [], []), '@ports', ('port_map', [], [('@list', . at 0x7fb075b4a6a8>, ('input', ['external_port_id', 'internal_layer_id', 'internal_port_id', 'axis', 'start', 'stride', 'end', 'part_size'], [])), ('@list', . at 0x7fb075b4a620>, ('output', ['external_port_id', 'internal_layer_id', 'internal_port_id', 'axis', 'start', 'stride', 'end', 'part_size'], []))]), ('back_edges', [], [('@list', . at 0x7fb075b4a598>, ('edge', [('from-layer', 'from_layer'), ('from-port', 'from_port'), ('to-layer', 'to_layer'), ('to-port', 'to_port')], []))]), ('body', [], [('@network', 'body')])])]} [ 2019-03-21 16:52:52,283 ] [ DEBUG ] [ op:208 ] Finished running infer function, data nodes attributes: {'name': 'spatial_temporal_network/rnn_net/rnn/TensorArrayStack/TensorArrayGatherV3/Output_0/Data_', 'kind': 'data', 'shape': array([ 30, 1, 512]), 'value': None, 'data_type': None, 'infer': None, 'dim_attrs': ['spatial_dims', 'channel_dims', 'axis', 'batch_dims'], 'shape_attrs': ['output_shape', 'shape', 'pad', 'window', 'stride'], 'fw_tensor_debug_info': [('spatial_temporal_network/rnn_net/rnn/TensorArrayStack/TensorArrayGatherV3', 0)], 'is_output_reachable': True, 'is_undead': False, 'is_const_producer': False, 'is_partial_inferred': True, 'executable': True, 'prev': None} [ 2019-03-21 16:52:52,310 ] [ DEBUG ] [ eliminate:64 ] The following nodes are seeded as output reachable: output/Output_0/Data_ [ 2019-03-21 16:52:52,363 ] [ DEBUG ] [ eliminate:130 ] Removing the following dead nodes: spatial_temporal_network/dense/bias/Output_0/Data_ spatial_temporal_network/dense/kernel/Output_0/Data_ spatial_temporal_network/flatten/Reshape/shape/1/Output_0/Data_ spatial_temporal_network/flatten/Reshape/shape/ExpandDims_/Output_0/Data_ spatial_temporal_network/flatten/Reshape/shape/ExpandDims_431/Output_0/Data_ spatial_temporal_network/flatten/Shape/Output_0/Data_ spatial_temporal_network/flatten/strided_slice/Output_0/Data_ spatial_temporal_network/flatten/strided_slice/stack/Output_0/Data_ spatial_temporal_network/flatten/strided_slice/stack_1/Output_0/Data_ spatial_temporal_network/flatten/strided_slice/stack_2/Output_0/Data_ spatial_temporal_network/geo/conblock_1/bn/batchnorm/Rsqrt/Output_0/Data_ spatial_temporal_network/geo/conblock_1/bn/batchnorm/add/Output_0/Data_ spatial_temporal_network/geo/conblock_1/bn/batchnorm/add/y/Output_0/Data_ spatial_temporal_network/geo/conblock_1/bn/batchnorm/mul_2/Output_0/Data_ spatial_temporal_network/geo/conblock_1/bn/batchnorm/sub/negate_/Output_0/Data_ spatial_temporal_network/geo/conblock_1/bn/beta/Output_0/Data_ spatial_temporal_network/geo/conblock_1/bn/beta/read/Output_0/Data_ spatial_temporal_network/geo/conblock_1/bn/gamma/Output_0/Data_ spatial_temporal_network/geo/conblock_1/bn/gamma/read/Output_0/Data_ spatial_temporal_network/geo/conblock_1/bn/moving_mean/Output_0/Data_ spatial_temporal_network/geo/conblock_1/bn/moving_mean/read/Output_0/Data_ spatial_temporal_network/geo/conblock_1/bn/moving_variance/Output_0/Data_ spatial_temporal_network/geo/conblock_1/bn/moving_variance/read/Output_0/Data_ spatial_temporal_network/geo/conblock_1/cov/bias/Output_0/Data_ spatial_temporal_network/geo/conblock_1/cov/kernel/Output_0/Data_ spatial_temporal_network/geo/conblock_1/cov/kernel/read/Output_0/Data_ spatial_temporal_network/geo/conblock_2/bn/batchnorm/Rsqrt/Output_0/Data_ spatial_temporal_network/geo/conblock_2/bn/batchnorm/add/Output_0/Data_ spatial_temporal_network/geo/conblock_2/bn/batchnorm/add/y/Output_0/Data_ spatial_temporal_network/geo/conblock_2/bn/batchnorm/mul_2/Output_0/Data_ spatial_temporal_network/geo/conblock_2/bn/batchnorm/sub/negate_/Output_0/Data_ spatial_temporal_network/geo/conblock_2/bn/beta/Output_0/Data_ spatial_temporal_network/geo/conblock_2/bn/beta/read/Output_0/Data_ spatial_temporal_network/geo/conblock_2/bn/gamma/Output_0/Data_ spatial_temporal_network/geo/conblock_2/bn/gamma/read/Output_0/Data_ spatial_temporal_network/geo/conblock_2/bn/moving_mean/Output_0/Data_ spatial_temporal_network/geo/conblock_2/bn/moving_mean/read/Output_0/Data_ spatial_temporal_network/geo/conblock_2/bn/moving_variance/Output_0/Data_ spatial_temporal_network/geo/conblock_2/bn/moving_variance/read/Output_0/Data_ spatial_temporal_network/geo/conblock_2/cov/bias/Output_0/Data_ spatial_temporal_network/geo/conblock_2/cov/kernel/Output_0/Data_ spatial_temporal_network/geo/conblock_2/cov/kernel/read/Output_0/Data_ spatial_temporal_network/geo/conblock_3/bn/batchnorm/Rsqrt/Output_0/Data_ spatial_temporal_network/geo/conblock_3/bn/batchnorm/add/Output_0/Data_ spatial_temporal_network/geo/conblock_3/bn/batchnorm/add/y/Output_0/Data_ spatial_temporal_network/geo/conblock_3/bn/batchnorm/mul_2/Output_0/Data_ spatial_temporal_network/geo/conblock_3/bn/batchnorm/sub/negate_/Output_0/Data_ spatial_temporal_network/geo/conblock_3/bn/beta/Output_0/Data_ spatial_temporal_network/geo/conblock_3/bn/beta/read/Output_0/Data_ spatial_temporal_network/geo/conblock_3/bn/gamma/Output_0/Data_ spatial_temporal_network/geo/conblock_3/bn/gamma/read/Output_0/Data_ spatial_temporal_network/geo/conblock_3/bn/moving_mean/Output_0/Data_ spatial_temporal_network/geo/conblock_3/bn/moving_mean/read/Output_0/Data_ spatial_temporal_network/geo/conblock_3/bn/moving_variance/Output_0/Data_ spatial_temporal_network/geo/conblock_3/bn/moving_variance/read/Output_0/Data_ spatial_temporal_network/geo/conblock_3/cov/bias/Output_0/Data_ spatial_temporal_network/geo/conblock_3/cov/kernel/Output_0/Data_ spatial_temporal_network/geo/conblock_3/cov/kernel/read/Output_0/Data_ spatial_temporal_network/motion/conblock_1/bn/batchnorm/Rsqrt/Output_0/Data_ spatial_temporal_network/motion/conblock_1/bn/batchnorm/add/Output_0/Data_ spatial_temporal_network/motion/conblock_1/bn/batchnorm/add/y/Output_0/Data_ spatial_temporal_network/motion/conblock_1/bn/batchnorm/mul_2/Output_0/Data_ spatial_temporal_network/motion/conblock_1/bn/batchnorm/sub/negate_/Output_0/Data_ spatial_temporal_network/motion/conblock_1/bn/beta/Output_0/Data_ spatial_temporal_network/motion/conblock_1/bn/beta/read/Output_0/Data_ spatial_temporal_network/motion/conblock_1/bn/gamma/Output_0/Data_ spatial_temporal_network/motion/conblock_1/bn/gamma/read/Output_0/Data_ spatial_temporal_network/motion/conblock_1/bn/moving_mean/Output_0/Data_ spatial_temporal_network/motion/conblock_1/bn/moving_mean/read/Output_0/Data_ spatial_temporal_network/motion/conblock_1/bn/moving_variance/Output_0/Data_ spatial_temporal_network/motion/conblock_1/bn/moving_variance/read/Output_0/Data_ spatial_temporal_network/motion/conblock_1/cov/bias/Output_0/Data_ spatial_temporal_network/motion/conblock_1/cov/kernel/Output_0/Data_ spatial_temporal_network/motion/conblock_1/cov/kernel/read/Output_0/Data_ spatial_temporal_network/motion/conblock_2/bn/batchnorm/Rsqrt/Output_0/Data_ spatial_temporal_network/motion/conblock_2/bn/batchnorm/add/Output_0/Data_ spatial_temporal_network/motion/conblock_2/bn/batchnorm/add/y/Output_0/Data_ spatial_temporal_network/motion/conblock_2/bn/batchnorm/mul_2/Output_0/Data_ spatial_temporal_network/motion/conblock_2/bn/batchnorm/sub/negate_/Output_0/Data_ spatial_temporal_network/motion/conblock_2/bn/beta/Output_0/Data_ spatial_temporal_network/motion/conblock_2/bn/beta/read/Output_0/Data_ spatial_temporal_network/motion/conblock_2/bn/gamma/Output_0/Data_ spatial_temporal_network/motion/conblock_2/bn/gamma/read/Output_0/Data_ spatial_temporal_network/motion/conblock_2/bn/moving_mean/Output_0/Data_ spatial_temporal_network/motion/conblock_2/bn/moving_mean/read/Output_0/Data_ spatial_temporal_network/motion/conblock_2/bn/moving_variance/Output_0/Data_ spatial_temporal_network/motion/conblock_2/bn/moving_variance/read/Output_0/Data_ spatial_temporal_network/motion/conblock_2/cov/bias/Output_0/Data_ spatial_temporal_network/motion/conblock_2/cov/kernel/Output_0/Data_ spatial_temporal_network/motion/conblock_2/cov/kernel/read/Output_0/Data_ spatial_temporal_network/motion/conblock_3/bn/batchnorm/Rsqrt/Output_0/Data_ spatial_temporal_network/motion/conblock_3/bn/batchnorm/add/Output_0/Data_ spatial_temporal_network/motion/conblock_3/bn/batchnorm/add/y/Output_0/Data_ spatial_temporal_network/motion/conblock_3/bn/batchnorm/mul_2/Output_0/Data_ spatial_temporal_network/motion/conblock_3/bn/batchnorm/sub/negate_/Output_0/Data_ spatial_temporal_network/motion/conblock_3/bn/beta/Output_0/Data_ spatial_temporal_network/motion/conblock_3/bn/beta/read/Output_0/Data_ spatial_temporal_network/motion/conblock_3/bn/gamma/Output_0/Data_ spatial_temporal_network/motion/conblock_3/bn/gamma/read/Output_0/Data_ spatial_temporal_network/motion/conblock_3/bn/moving_mean/Output_0/Data_ spatial_temporal_network/motion/conblock_3/bn/moving_mean/read/Output_0/Data_ spatial_temporal_network/motion/conblock_3/bn/moving_variance/Output_0/Data_ spatial_temporal_network/motion/conblock_3/bn/moving_variance/read/Output_0/Data_ spatial_temporal_network/motion/conblock_3/cov/bias/Output_0/Data_ spatial_temporal_network/motion/conblock_3/cov/kernel/Output_0/Data_ spatial_temporal_network/motion/conblock_3/cov/kernel/read/Output_0/Data_ spatial_temporal_network/motion/conblock_4/bn/batchnorm/Rsqrt/Output_0/Data_ spatial_temporal_network/motion/conblock_4/bn/batchnorm/add/Output_0/Data_ spatial_temporal_network/motion/conblock_4/bn/batchnorm/add/y/Output_0/Data_ spatial_temporal_network/motion/conblock_4/bn/batchnorm/mul_2/Output_0/Data_ spatial_temporal_network/motion/conblock_4/bn/batchnorm/sub/negate_/Output_0/Data_ spatial_temporal_network/motion/conblock_4/bn/beta/Output_0/Data_ spatial_temporal_network/motion/conblock_4/bn/beta/read/Output_0/Data_ spatial_temporal_network/motion/conblock_4/bn/gamma/Output_0/Data_ spatial_temporal_network/motion/conblock_4/bn/gamma/read/Output_0/Data_ spatial_temporal_network/motion/conblock_4/bn/moving_mean/Output_0/Data_ spatial_temporal_network/motion/conblock_4/bn/moving_mean/read/Output_0/Data_ spatial_temporal_network/motion/conblock_4/bn/moving_variance/Output_0/Data_ spatial_temporal_network/motion/conblock_4/bn/moving_variance/read/Output_0/Data_ spatial_temporal_network/motion/conblock_4/cov/bias/Output_0/Data_ spatial_temporal_network/motion/conblock_4/cov/kernel/Output_0/Data_ spatial_temporal_network/motion/conblock_4/cov/kernel/read/Output_0/Data_ spatial_temporal_network/rnn_net/rnn/Maximum/Output_0/Data_ spatial_temporal_network/rnn_net/rnn/Maximum/x/Output_0/Data_ spatial_temporal_network/rnn_net/rnn/Minimum/Output_0/Data_ spatial_temporal_network/rnn_net/rnn/MultiRNNCellZeroState/LSTMCellZeroState/Const/Output_0/Data_ spatial_temporal_network/rnn_net/rnn/MultiRNNCellZeroState/LSTMCellZeroState/Const_1/Output_0/Data_ spatial_temporal_network/rnn_net/rnn/MultiRNNCellZeroState/LSTMCellZeroState/Const_4/Output_0/Data_ spatial_temporal_network/rnn_net/rnn/MultiRNNCellZeroState/LSTMCellZeroState/Const_5/Output_0/Data_ spatial_temporal_network/rnn_net/rnn/MultiRNNCellZeroState/LSTMCellZeroState/concat/Output_0/Data_ spatial_temporal_network/rnn_net/rnn/MultiRNNCellZeroState/LSTMCellZeroState/concat_1/Output_0/Data_ spatial_temporal_network/rnn_net/rnn/MultiRNNCellZeroState/LSTMCellZeroState/zeros/Const/Output_0/Data_ spatial_temporal_network/rnn_net/rnn/MultiRNNCellZeroState/LSTMCellZeroState/zeros/Output_0/Data_ spatial_temporal_network/rnn_net/rnn/MultiRNNCellZeroState/LSTMCellZeroState/zeros_1/Const/Output_0/Data_ spatial_temporal_network/rnn_net/rnn/MultiRNNCellZeroState/LSTMCellZeroState/zeros_1/Output_0/Data_ spatial_temporal_network/rnn_net/rnn/MultiRNNCellZeroState/LSTMCellZeroState_1/Const/Output_0/Data_ spatial_temporal_network/rnn_net/rnn/MultiRNNCellZeroState/LSTMCellZeroState_1/Const_1/Output_0/Data_ spatial_temporal_network/rnn_net/rnn/MultiRNNCellZeroState/LSTMCellZeroState_1/Const_4/Output_0/Data_ spatial_temporal_network/rnn_net/rnn/MultiRNNCellZeroState/LSTMCellZeroState_1/Const_5/Output_0/Data_ spatial_temporal_network/rnn_net/rnn/MultiRNNCellZeroState/LSTMCellZeroState_1/concat/Output_0/Data_ spatial_temporal_network/rnn_net/rnn/MultiRNNCellZeroState/LSTMCellZeroState_1/concat_1/Output_0/Data_ spatial_temporal_network/rnn_net/rnn/MultiRNNCellZeroState/LSTMCellZeroState_1/zeros/Const/Output_0/Data_ spatial_temporal_network/rnn_net/rnn/MultiRNNCellZeroState/LSTMCellZeroState_1/zeros/Output_0/Data_ spatial_temporal_network/rnn_net/rnn/MultiRNNCellZeroState/LSTMCellZeroState_1/zeros_1/Const/Output_0/Data_ spatial_temporal_network/rnn_net/rnn/MultiRNNCellZeroState/LSTMCellZeroState_1/zeros_1/Output_0/Data_ spatial_temporal_network/rnn_net/rnn/MultiRNNCellZeroState/LSTMCellZeroState_2/Const/Output_0/Data_ spatial_temporal_network/rnn_net/rnn/MultiRNNCellZeroState/LSTMCellZeroState_2/Const_1/Output_0/Data_ spatial_temporal_network/rnn_net/rnn/MultiRNNCellZeroState/LSTMCellZeroState_2/Const_4/Output_0/Data_ spatial_temporal_network/rnn_net/rnn/MultiRNNCellZeroState/LSTMCellZeroState_2/Const_5/Output_0/Data_ spatial_temporal_network/rnn_net/rnn/MultiRNNCellZeroState/LSTMCellZeroState_2/concat/Output_0/Data_ spatial_temporal_network/rnn_net/rnn/MultiRNNCellZeroState/LSTMCellZeroState_2/concat_1/Output_0/Data_ spatial_temporal_network/rnn_net/rnn/MultiRNNCellZeroState/LSTMCellZeroState_2/zeros/Const/Output_0/Data_ spatial_temporal_network/rnn_net/rnn/MultiRNNCellZeroState/LSTMCellZeroState_2/zeros/Output_0/Data_ spatial_temporal_network/rnn_net/rnn/MultiRNNCellZeroState/LSTMCellZeroState_2/zeros_1/Const/Output_0/Data_ spatial_temporal_network/rnn_net/rnn/MultiRNNCellZeroState/LSTMCellZeroState_2/zeros_1/Output_0/Data_ spatial_temporal_network/rnn_net/rnn/Shape/Output_0/Data_ spatial_temporal_network/rnn_net/rnn/multi_rnn_cell/cell_0/lstm_cell/bias/Output_0/Data_ spatial_temporal_network/rnn_net/rnn/multi_rnn_cell/cell_0/lstm_cell/bias/read/Output_0/Data_ spatial_temporal_network/rnn_net/rnn/multi_rnn_cell/cell_0/lstm_cell/kernel/Output_0/Data_ spatial_temporal_network/rnn_net/rnn/multi_rnn_cell/cell_0/lstm_cell/kernel/read/Output_0/Data_ spatial_temporal_network/rnn_net/rnn/strided_slice/stack/Output_0/Data_ spatial_temporal_network/rnn_net/rnn/strided_slice/stack_1/Output_0/Data_ spatial_temporal_network/rnn_net/rnn/strided_slice/stack_2/Output_0/Data_ [ 2019-03-21 16:52:52,365 ] [ DEBUG ] [ eliminate:64 ] The following nodes are seeded as output reachable: 877 spatial_temporal_network/rnn_net/rnn/while/rnn/multi_rnn_cell/cell_0/lstm_cell/concat/LSTMCell/Output_0/Data_ spatial_temporal_network/rnn_net/rnn/while/rnn/multi_rnn_cell/cell_0/lstm_cell/concat/LSTMCell/Output_1/Data_ spatial_temporal_network/rnn_net/rnn/while/rnn/multi_rnn_cell/cell_0/lstm_cell/concat_1/LSTMCell/Output_0/Data_ spatial_temporal_network/rnn_net/rnn/while/rnn/multi_rnn_cell/cell_0/lstm_cell/concat_1/LSTMCell/Output_1/Data_ spatial_temporal_network/rnn_net/rnn/while/rnn/multi_rnn_cell/cell_0/lstm_cell/concat_2/LSTMCell/Output_0/Data_ spatial_temporal_network/rnn_net/rnn/while/rnn/multi_rnn_cell/cell_0/lstm_cell/concat_2/LSTMCell/Output_1/Data_ [ 2019-03-21 16:52:52,372 ] [ DEBUG ] [ eliminate:130 ] Removing the following dead nodes: [ 2019-03-21 16:52:52,384 ] [ DEBUG ] [ eliminate:64 ] The following nodes are seeded as output reachable: output/Output_0/Data_ [ 2019-03-21 16:52:52,417 ] [ DEBUG ] [ eliminate:130 ] Removing the following dead nodes: [ 2019-03-21 16:52:52,427 ] [ DEBUG ] [ eliminate:64 ] The following nodes are seeded as output reachable: output/Output_0/Data_ [ 2019-03-21 16:52:52,464 ] [ DEBUG ] [ eliminate:130 ] Removing the following dead nodes: [ 2019-03-21 16:52:52,548 ] [ DEBUG ] [ eliminate:64 ] The following nodes are seeded as output reachable: output/Output_0/Data_ [ 2019-03-21 16:52:52,588 ] [ DEBUG ] [ eliminate:130 ] Removing the following dead nodes: [ 2019-03-21 16:52:52,590 ] [ DEBUG ] [ eliminate:64 ] The following nodes are seeded as output reachable: 877 spatial_temporal_network/rnn_net/rnn/while/rnn/multi_rnn_cell/cell_0/lstm_cell/concat/LSTMCell/Output_0/Data_ spatial_temporal_network/rnn_net/rnn/while/rnn/multi_rnn_cell/cell_0/lstm_cell/concat/LSTMCell/Output_1/Data_ spatial_temporal_network/rnn_net/rnn/while/rnn/multi_rnn_cell/cell_0/lstm_cell/concat_1/LSTMCell/Output_0/Data_ spatial_temporal_network/rnn_net/rnn/while/rnn/multi_rnn_cell/cell_0/lstm_cell/concat_1/LSTMCell/Output_1/Data_ spatial_temporal_network/rnn_net/rnn/while/rnn/multi_rnn_cell/cell_0/lstm_cell/concat_2/LSTMCell/Output_0/Data_ spatial_temporal_network/rnn_net/rnn/while/rnn/multi_rnn_cell/cell_0/lstm_cell/concat_2/LSTMCell/Output_1/Data_ [ 2019-03-21 16:52:52,597 ] [ DEBUG ] [ eliminate:130 ] Removing the following dead nodes: [ 2019-03-21 16:52:52,622 ] [ DEBUG ] [ eliminate:64 ] The following nodes are seeded as output reachable: output/Output_0/Data_ [ 2019-03-21 16:52:52,661 ] [ DEBUG ] [ eliminate:130 ] Removing the following dead nodes: [ 2019-03-21 16:52:52,709 ] [ DEBUG ] [ class_registration:91 ] Replacer will be run after [ 2019-03-21 16:52:52,709 ] [ DEBUG ] [ class_registration:88 ] Replacer will be run before [ 2019-03-21 16:52:52,709 ] [ DEBUG ] [ class_registration:91 ] Replacer will be run after [ 2019-03-21 16:52:52,710 ] [ DEBUG ] [ class_registration:88 ] Replacer will be run before [ 2019-03-21 16:52:52,710 ] [ DEBUG ] [ class_registration:91 ] Replacer will be run after [ 2019-03-21 16:52:52,710 ] [ DEBUG ] [ class_registration:88 ] Replacer will be run before [ 2019-03-21 16:52:52,710 ] [ DEBUG ] [ class_registration:91 ] Replacer will be run after [ 2019-03-21 16:52:52,711 ] [ DEBUG ] [ class_registration:91 ] Replacer will be run after [ 2019-03-21 16:52:52,711 ] [ DEBUG ] [ class_registration:88 ] Replacer will be run before [ 2019-03-21 16:52:52,711 ] [ DEBUG ] [ class_registration:91 ] Replacer will be run after [ 2019-03-21 16:52:52,711 ] [ DEBUG ] [ class_registration:91 ] Replacer will be run after [ 2019-03-21 16:52:52,711 ] [ DEBUG ] [ class_registration:88 ] Replacer will be run before [ 2019-03-21 16:52:52,711 ] [ DEBUG ] [ class_registration:88 ] Replacer will be run before [ 2019-03-21 16:52:52,712 ] [ DEBUG ] [ class_registration:91 ] Replacer will be run after [ 2019-03-21 16:52:52,712 ] [ DEBUG ] [ class_registration:88 ] Replacer will be run before [ 2019-03-21 16:52:52,712 ] [ DEBUG ] [ class_registration:88 ] Replacer will be run before [ 2019-03-21 16:52:52,712 ] [ DEBUG ] [ class_registration:88 ] Replacer will be run before [ 2019-03-21 16:52:52,712 ] [ DEBUG ] [ class_registration:91 ] Replacer will be run after [ 2019-03-21 16:52:52,713 ] [ DEBUG ] [ class_registration:88 ] Replacer will be run before [ 2019-03-21 16:52:52,713 ] [ DEBUG ] [ class_registration:91 ] Replacer will be run after [ 2019-03-21 16:52:52,713 ] [ DEBUG ] [ class_registration:91 ] Replacer will be run after [ 2019-03-21 16:52:52,713 ] [ DEBUG ] [ class_registration:91 ] Replacer will be run after [ 2019-03-21 16:52:52,713 ] [ DEBUG ] [ class_registration:91 ] Replacer will be run after [ 2019-03-21 16:52:52,713 ] [ DEBUG ] [ class_registration:91 ] Replacer will be run after [ 2019-03-21 16:52:52,714 ] [ DEBUG ] [ class_registration:91 ] Replacer will be run after [ 2019-03-21 16:52:52,714 ] [ DEBUG ] [ class_registration:91 ] Replacer will be run after [ 2019-03-21 16:52:52,714 ] [ DEBUG ] [ class_registration:91 ] Replacer will be run after [ 2019-03-21 16:52:52,714 ] [ DEBUG ] [ class_registration:91 ] Replacer will be run after [ 2019-03-21 16:52:52,714 ] [ DEBUG ] [ class_registration:91 ] Replacer will be run after [ 2019-03-21 16:52:52,714 ] [ DEBUG ] [ class_registration:91 ] Replacer will be run after [ 2019-03-21 16:52:52,715 ] [ DEBUG ] [ class_registration:111 ] Run replacer [ 2019-03-21 16:52:52,739 ] [ DEBUG ] [ class_registration:111 ] Run replacer [ 2019-03-21 16:52:52,768 ] [ DEBUG ] [ class_registration:111 ] Run replacer [ ERROR ] ------------------------------------------------- [ ERROR ] ----------------- INTERNAL ERROR ---------------- [ ERROR ] Unexpected exception happened. [ ERROR ] Please contact Model Optimizer developers and forward the following information: [ ERROR ] Exception occurred during running replacer "REPLACEMENT_ID ()": [ ERROR ] Traceback (most recent call last): File "/home/sweta/intel/computer_vision_sdk_2018.5.455/deployment_tools/model_optimizer/mo/utils/class_registration.py", line 114, in apply_replacements replacer.find_and_replace_pattern(graph) File "/home/sweta/intel/computer_vision_sdk_2018.5.455/deployment_tools/model_optimizer/mo/utils/replacement_pattern.py", line 28, in find_and_replace_pattern apply_pattern(graph, **self.pattern(), action=self.replace_pattern) # pylint: disable=no-member File "/home/sweta/intel/computer_vision_sdk_2018.5.455/deployment_tools/model_optimizer/mo/middle/pattern_match.py", line 98, in apply_pattern for_each_sub_graph(graph, lambda graph: apply_pattern(graph, nodes, edges, action, node_attrs, edge_attrs)) File "/home/sweta/intel/computer_vision_sdk_2018.5.455/deployment_tools/model_optimizer/mo/middle/pattern_match.py", line 39, in for_each_sub_graph func(node[sub_graph_name]) File "/home/sweta/intel/computer_vision_sdk_2018.5.455/deployment_tools/model_optimizer/mo/middle/pattern_match.py", line 98, in for_each_sub_graph(graph, lambda graph: apply_pattern(graph, nodes, edges, action, node_attrs, edge_attrs)) File "/home/sweta/intel/computer_vision_sdk_2018.5.455/deployment_tools/model_optimizer/mo/middle/pattern_match.py", line 95, in apply_pattern action(graph, match) File "/home/sweta/intel/computer_vision_sdk_2018.5.455/deployment_tools/model_optimizer/extensions/middle/TF_lstm_cell_to_generic.py", line 55, in replace_pattern assert len(weights_node.out_nodes()) == 1 AssertionError The above exception was the direct cause of the following exception: Traceback (most recent call last): File "/home/sweta/intel/computer_vision_sdk_2018.5.455/deployment_tools/model_optimizer/mo/main.py", line 325, in main return driver(argv) File "/home/sweta/intel/computer_vision_sdk_2018.5.455/deployment_tools/model_optimizer/mo/main.py", line 267, in driver mean_scale_values=mean_scale) File "/home/sweta/intel/computer_vision_sdk_2018.5.455/deployment_tools/model_optimizer/mo/pipeline/tf.py", line 328, in tf2nx class_registration.apply_replacements(graph, class_registration.ClassType.MIDDLE_REPLACER) File "/home/sweta/intel/computer_vision_sdk_2018.5.455/deployment_tools/model_optimizer/mo/utils/class_registration.py", line 127, in apply_replacements )) from err Exception: Exception occurred during running replacer "REPLACEMENT_ID ()": [ ERROR ] ---------------- END OF BUG REPORT -------------- [ ERROR ] -------------------------------------------------