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During Conversion of Onnx model to openvino we are facing some issues, can you please help us here.
(cenv) u47404@s099-n004:~/intelmac$ python /opt/intel/openvino/deployment_tools/model_optimizer/mo.py --input_model models_stats/torch/timeseries_enode_tcnn_l6.onnx --output_dir models_stats/torch --input_shape [128,80,15]
Model Optimizer arguments:
Common parameters:
- Path to the Input Model: /home/u47404/intelmac/models_stats/torch/timeseries_enode_tcnn_l6.onnx
- Path for generated IR: /home/u47404/intelmac/models_stats/torch
- IR output name: timeseries_enode_tcnn_l6
- 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: [128,80,15]
- 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: None
- Reverse input channels: False
ONNX specific parameters:
Model Optimizer version: 2021.1.0-1237-bece22ac675-releases/2021/1
2020-10-18 23:32:18.068320: W tensorflow/stream_executor/platform/default/dso_loader.cc:59] Could not load dynamic library 'libcudart.so.10.1'; dlerror: libcudart.so.10.1: cannot open shared object file: No such file or directory; LD_LIBRARY_PATH: /opt/intel/openvino/data_processing/dl_streamer/lib:/opt/intel/openvino/data_processing/gstreamer/lib:/opt/intel/openvino/opencv/lib:/opt/intel/openvino/deployment_tools/ngraph/lib:/opt/intel/openvino/deployment_tools/inference_engine/external/hddl_unite/lib:/opt/intel/openvino/deployment_tools/inference_engine/external/hddl/lib:/opt/intel/openvino/deployment_tools/inference_engine/external/gna/lib:/opt/intel/openvino/deployment_tools/inference_engine/external/mkltiny_lnx/lib:/opt/intel/openvino/deployment_tools/inference_engine/external/tbb/lib:/opt/intel/openvino/deployment_tools/inference_engine/lib/intel64:/opt/intel/openvino/data_processing/dl_streamer/lib:/opt/intel/openvino/data_processing/gstreamer/lib:/opt/intel/openvino/opencv/lib:/opt/intel/openvino/deployment_tools/ngraph/lib:/opt/intel/openvino/deployment_tools/inference_engine/external/hddl_unite/lib:/opt/intel/openvino/deployment_tools/inference_engine/external/hddl/lib:/opt/intel/openvino/deployment_tools/inference_engine/external/gna/lib:/opt/intel/openvino/deployment_tools/inference_engine/external/mkltiny_lnx/lib:/opt/intel/openvino/deployment_tools/inference_engine/external/tbb/lib:/opt/intel/openvino/deployment_tools/inference_engine/lib/intel64
2020-10-18 23:32:18.068367: I tensorflow/stream_executor/cuda/cudart_stub.cc:29] Ignore above cudart dlerror if you do not have a GPU set up on your machine.
[ 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 "fusing (<class 'extensions.middle.fusings.Fusing'>)":
[ ERROR ] Traceback (most recent call last):
File "/opt/intel/openvino_2021.1.110/deployment_tools/model_optimizer/mo/utils/class_registration.py", line 286, in apply_transform
replacer.find_and_replace_pattern(graph)
File "/opt/intel/openvino_2021.1.110/deployment_tools/model_optimizer/extensions/middle/fusings.py", line 57, in find_and_replace_pattern
for_graph_and_each_sub_graph_recursively(graph, fuse_pad)
File "/opt/intel/openvino_2021.1.110/deployment_tools/model_optimizer/mo/middle/pattern_match.py", line 58, in for_graph_and_each_sub_graph_recursively
func(graph)
File "/opt/intel/openvino_2021.1.110/deployment_tools/model_optimizer/mo/middle/passes/conv.py", line 73, in fuse_pad
action=pad_op_transform
File "/opt/intel/openvino_2021.1.110/deployment_tools/model_optimizer/mo/middle/pattern_match.py", line 95, in apply_pattern
action(graph, match)
File "/opt/intel/openvino_2021.1.110/deployment_tools/model_optimizer/mo/middle/passes/conv.py", line 45, in pad_op_transform
if pads[get_features_dim(op.graph.graph['layout'], input_tensor_dims)] != 0 or \
File "/opt/intel/openvino_2021.1.110/deployment_tools/model_optimizer/mo/front/common/layout.py", line 84, in get_features_dim
assert 4 <= shape_len <= 5
AssertionError
The above exception was the direct cause of the following exception:
Traceback (most recent call last):
File "/opt/intel/openvino_2021.1.110/deployment_tools/model_optimizer/mo/main.py", line 298, in main
ret_code = driver(argv)
File "/opt/intel/openvino_2021.1.110/deployment_tools/model_optimizer/mo/main.py", line 265, in driver
ret_res = emit_ir(prepare_ir(argv), argv)
File "/opt/intel/openvino_2021.1.110/deployment_tools/model_optimizer/mo/main.py", line 234, in prepare_ir
graph = unified_pipeline(argv)
File "/opt/intel/openvino_2021.1.110/deployment_tools/model_optimizer/mo/pipeline/unified.py", line 29, in unified_pipeline
class_registration.ClassType.BACK_REPLACER
File "/opt/intel/openvino_2021.1.110/deployment_tools/model_optimizer/mo/utils/class_registration.py", line 334, in apply_replacements
apply_replacements_list(graph, replacers_order)
File "/opt/intel/openvino_2021.1.110/deployment_tools/model_optimizer/mo/utils/class_registration.py", line 324, in apply_replacements_list
num_transforms=len(replacers_order))
File "/opt/intel/openvino_2021.1.110/deployment_tools/model_optimizer/mo/utils/logger.py", line 124, in wrapper
function(*args, **kwargs)
File "/opt/intel/openvino_2021.1.110/deployment_tools/model_optimizer/mo/utils/class_registration.py", line 312, in apply_transform
)) from err
Exception: Exception occurred during running replacer "fusing (<class 'extensions.middle.fusings.Fusing'>)":
[ ERROR ] ---------------- END OF BUG REPORT --------------
[ ERROR ] -------------------------------------------------
The issue seems to be due to,
self.pad = torch.nn.ZeroPad2d((padding, 0, 0, 0))
Can you please help.
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Greetings,
First and foremost,before proceeding further, please help to ensure that your topology and Pytorch/Paddle Models are listed in here: https://docs.openvinotoolkit.org/latest/openvino_docs_MO_DG_prepare_model_convert_model_Convert_Model_From_ONNX.html
Those listed are validated by Openvino and you should good to go if these are fulfilled.
Please also help to check whether your framework layer is supported : https://docs.openvinotoolkit.org/latest/openvino_docs_MO_DG_prepare_model_Supported_Frameworks_Layers.html
Sincerely,
Iffa
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Greetings,
Intel will no longer monitor this thread since we have provided a solution. If you need any additional information from Intel, please submit a new question
Sincerely,
Iffa
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