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std::system_error' what(): Resource temporarily unavailable Aborted

Dears,

I applied bellow command in the jupyter notebook of "intel_distribution_for_python_3_2019u2", as per documentation providede in the OpenVino Toolkit.

! python3 /opt/intel/openvino/deployment_tools/model_optimizer/mo_tf.py --input_model /home/u37452/DataSet/TomatoModel/m_tomato_tensorflowmodel.pb --output_dir /home/u37452/DataSet/TomatoModel --input_shape [1,224,224,3]

I faced bellow errors,

Model Optimizer arguments: Common parameters: - Path to the Input Model: /home/u37452/DataSet/TomatoModel/m_tomato_tensorflowmodel.pb - Path for generated IR: /home/u37452/DataSet/TomatoModel - IR output name: m_tomato_tensorflowmodel - Log level: ERROR - Batch: Not specified, inherited from the model - Input layers: Not specified, inherited from the model - Output layers: Not specified, inherited from the model - Input shapes: [1,224,224,3] - 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 - 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: 2019.3.0-408-gac8584cb7 /usr/local/lib/python3.6/dist-packages/tensorflow/python/framework/dtypes.py:516: FutureWarning: Passing (type, 1) or '1type' as a synonym of type is deprecated; in a future version of numpy, it will be understood as (type, (1,)) / '(1,)type'. _np_qint8 = np.dtype([("qint8", np.int8, 1)]) /usr/local/lib/python3.6/dist-packages/tensorflow/python/framework/dtypes.py:517: FutureWarning: Passing (type, 1) or '1type' as a synonym of type is deprecated; in a future version of numpy, it will be understood as (type, (1,)) / '(1,)type'. _np_quint8 = np.dtype([("quint8", np.uint8, 1)]) /usr/local/lib/python3.6/dist-packages/tensorflow/python/framework/dtypes.py:518: FutureWarning: Passing (type, 1) or '1type' as a synonym of type is deprecated; in a future version of numpy, it will be understood as (type, (1,)) / '(1,)type'. _np_qint16 = np.dtype([("qint16", np.int16, 1)]) /usr/local/lib/python3.6/dist-packages/tensorflow/python/framework/dtypes.py:519: FutureWarning: Passing (type, 1) or '1type' as a synonym of type is deprecated; in a future version of numpy, it will be understood as (type, (1,)) / '(1,)type'. _np_quint16 = np.dtype([("quint16", np.uint16, 1)]) /usr/local/lib/python3.6/dist-packages/tensorflow/python/framework/dtypes.py:520: FutureWarning: Passing (type, 1) or '1type' as a synonym of type is deprecated; in a future version of numpy, it will be understood as (type, (1,)) / '(1,)type'. _np_qint32 = np.dtype([("qint32", np.int32, 1)]) /usr/local/lib/python3.6/dist-packages/tensorflow/python/framework/dtypes.py:525: FutureWarning: Passing (type, 1) or '1type' as a synonym of type is deprecated; in a future version of numpy, it will be understood as (type, (1,)) / '(1,)type'. np_resource = np.dtype([("resource", np.ubyte, 1)]) /usr/local/lib/python3.6/dist-packages/tensorboard/compat/tensorflow_stub/dtypes.py:541: FutureWarning: Passing (type, 1) or '1type' as a synonym of type is deprecated; in a future version of numpy, it will be understood as (type, (1,)) / '(1,)type'. _np_qint8 = np.dtype([("qint8", np.int8, 1)]) /usr/local/lib/python3.6/dist-packages/tensorboard/compat/tensorflow_stub/dtypes.py:542: FutureWarning: Passing (type, 1) or '1type' as a synonym of type is deprecated; in a future version of numpy, it will be understood as (type, (1,)) / '(1,)type'. _np_quint8 = np.dtype([("quint8", np.uint8, 1)]) /usr/local/lib/python3.6/dist-packages/tensorboard/compat/tensorflow_stub/dtypes.py:543: FutureWarning: Passing (type, 1) or '1type' as a synonym of type is deprecated; in a future version of numpy, it will be understood as (type, (1,)) / '(1,)type'. _np_qint16 = np.dtype([("qint16", np.int16, 1)]) /usr/local/lib/python3.6/dist-packages/tensorboard/compat/tensorflow_stub/dtypes.py:544: FutureWarning: Passing (type, 1) or '1type' as a synonym of type is deprecated; in a future version of numpy, it will be understood as (type, (1,)) / '(1,)type'. _np_quint16 = np.dtype([("quint16", np.uint16, 1)]) /usr/local/lib/python3.6/dist-packages/tensorboard/compat/tensorflow_stub/dtypes.py:545: FutureWarning: Passing (type, 1) or '1type' as a synonym of type is deprecated; in a future version of numpy, it will be understood as (type, (1,)) / '(1,)type'. _np_qint32 = np.dtype([("qint32", np.int32, 1)]) /usr/local/lib/python3.6/dist-packages/tensorboard/compat/tensorflow_stub/dtypes.py:550: FutureWarning: Passing (type, 1) or '1type' as a synonym of type is deprecated; in a future version of numpy, it will be understood as (type, (1,)) / '(1,)type'. np_resource = np.dtype([("resource", np.ubyte, 1)]) terminate called after throwing an instance of 'std::system_error' what(): Resource temporarily unavailable Aborted'

What is the reason behind this error ?

Model optimization and inferencing runs perfectly well, generates IR, BIN and Mapping files through openvino_2019.3.376 in my local Ubuntu (Release:18.04, Codename: bionic.)

I applied the same command in the dev cloud edge shell too,

u37452@s099-n001:/opt/intel/openvino_2019.3.376/deployment_tools/model_optimizer/python3 mo_tf.py --input_model /home/u37452/DataSet/TomatoModel/m_tomato_tensorflowmodel.pb --output_dir /home/u37452/DataSet/TomatoModel --input_shape [1,224,224,3]

and got the same error,

" 'std::system_error' what():  Resource temporarily unavailable Aborted"

The OS version of the dev cloud edge(Description: Ubuntu 18.04, Release: 18.04, Codename: bionic) is the same as my PC.

Can anyone explain how to solve it?

Thanks

Fakrul

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My image sizes were 224*224*3. During optimization, a model of size 715MB faced the problem due to 1 core CPU and 4GB ram in dev cloud edge. Then I reduced the images by 32*32*3 and solved the problem.

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hi Fakrul

We are investigating to increase the Memory allocated on the Dev Node,

until then, you can submit the running of the model-optimizer as a job to the Edge node (has more memory ) for now as a work-around

Let me know if you succeed?  

Cheers

rama

 

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