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PINTO0309 / openvino2tensorflow

This script converts the ONNX/OpenVINO IR model to Tensorflow's saved_model, tflite, h5, tfjs, tftrt(TensorRT), CoreML, EdgeTPU, ONNX and pb. PyTorch (NCHW) -> ONNX (NCHW) -> OpenVINO (NCHW) -> openvino2tensorflow -> Tensorflow/Keras (NHWC/NCHW) -> TFLite (NHWC/NCHW). And the conversion from .pb to saved_model and from saved_model to .pb and from .pb to .tflite and saved_model to .tflite and saved_model to onnx. Support for building environments with Docker. It is possible to directly access the host PC GUI and the camera to verify the operation. NVIDIA GPU (dGPU) support. Intel iHD GPU (iGPU) support.
MIT License
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TypeError: cannot pickle 'module' object #144

Closed Mukulareddy closed 9 months ago

Mukulareddy commented 9 months ago

Issue Type

Bug

OS

Ubuntu

OS architecture

x86_64

Programming Language

Python

Framework

OpenVINO

Download URL for ONNX / OpenVINO IR

https://github.com/Megvii-BaseDetection/YOLOX/releases/download/0.1.1rc0/yolox_tiny_openvino.tar.gz

Convert Script

python openvino2tensorflow.py --model_path /yolox_tiny_sim.xml --model_output_path saved_h5_416_416 --output_h5

Description

When i tried converting the OpenVINO IR format of the model to .h5 model using the above command I am facing the below issue. TypeError: cannot pickle 'module' object It would be great if someone could help me with this.

Relevant Log Output

layer_type: Const
layer_id: 453
tf_layers_dict_shape: (1, 96, 1, 1)
tf_layers_dict_value: [[[[ 2.3701844 ]]

  [[ 1.9270271 ]]

  [[ 1.1629344 ]]

  [[-0.13331127]]

  [[ 1.1646254 ]]

  [[ 1.6272382 ]]

  [[ 2.0330715 ]]

  [[ 2.4103541 ]]

  [[ 1.1794468 ]]

  [[ 3.1922562 ]]

  [[ 0.80192804]]

  [[ 0.918452  ]]

  [[ 1.6562974 ]]

  [[ 0.8284194 ]]

  [[ 1.5944452 ]]

  [[-0.43591785]]

  [[ 1.4425404 ]]

  [[-2.1579928 ]]

  [[ 2.5115259 ]]

  [[ 0.10604887]]

  [[ 0.53013325]]

  [[ 2.4593568 ]]

  [[ 3.8425333 ]]

  [[ 1.510612  ]]

  [[ 2.6186988 ]]

  [[-0.365788  ]]

  [[-0.07304868]]

  [[ 1.9684379 ]]

  [[ 1.0933251 ]]

  [[ 0.34470552]]

  [[ 1.1178714 ]]

  [[ 3.5374014 ]]

  [[ 2.1186767 ]]

  [[ 0.66732824]]

  [[ 1.0683035 ]]

  [[ 2.7602077 ]]

  [[ 3.2852457 ]]

  [[-0.38651127]]

  [[ 1.9059887 ]]

  [[ 1.5833094 ]]

  [[ 1.889504  ]]

  [[ 0.8861643 ]]

  [[ 1.2405196 ]]

  [[ 1.3878361 ]]

  [[ 1.956938  ]]

  [[ 1.8078754 ]]

  [[ 1.3849156 ]]

  [[ 3.4051569 ]]

  [[ 3.1490602 ]]

  [[-1.0523298 ]]

  [[ 1.1143126 ]]

  [[ 0.8821161 ]]

  [[-0.2029241 ]]

  [[ 1.4012253 ]]

  [[ 1.7876036 ]]

  [[-2.3801851 ]]

  [[ 1.4638995 ]]

  [[ 0.89194554]]

  [[-0.9520595 ]]

  [[ 1.6488714 ]]

  [[ 0.8080565 ]]

  [[ 1.416472  ]]

  [[ 1.9556634 ]]

  [[-0.6152393 ]]

  [[-2.6198537 ]]

  [[ 1.3389992 ]]

  [[ 0.62451863]]

  [[-1.3831    ]]

  [[ 2.601157  ]]

  [[ 4.2489877 ]]

  [[ 0.956818  ]]

  [[ 1.4448963 ]]

  [[ 1.2242935 ]]

  [[ 1.7796409 ]]

  [[ 1.0258006 ]]

  [[-2.1094725 ]]

  [[-0.2001234 ]]

  [[-0.27974838]]

  [[ 1.2242429 ]]

  [[-0.8142648 ]]

  [[ 0.9820821 ]]

  [[ 1.9820187 ]]

  [[ 1.4535207 ]]

  [[ 3.1459603 ]]

  [[ 0.8010211 ]]

  [[ 3.373296  ]]

  [[ 2.507955  ]]

  [[ 2.4872022 ]]

  [[ 1.7825925 ]]

  [[-1.1367719 ]]

  [[ 0.3731116 ]]

  [[ 1.4726274 ]]

  [[-0.5747317 ]]

  [[ 1.4636103 ]]

  [[ 1.4617355 ]]

  [[ 1.5335329 ]]]]
====================================================================================
layer_type: Add
layer_id: 454
input_layer0: layer_id=452: KerasTensor(type_spec=TensorSpec(shape=(1, 13, 13, 96), dtype=tf.float32, name=None), name='conv2d_81/Conv2D:0', description="created by layer 'conv2d_81'")
input_layer1_value: layer_id=453: [[[[ 2.3701844 ]]

  [[ 1.9270271 ]]

  [[ 1.1629344 ]]

  [[-0.13331127]]

  [[ 1.1646254 ]]

  [[ 1.6272382 ]]

  [[ 2.0330715 ]]

  [[ 2.4103541 ]]

  [[ 1.1794468 ]]

  [[ 3.1922562 ]]

  [[ 0.80192804]]

  [[ 0.918452  ]]

  [[ 1.6562974 ]]

  [[ 0.8284194 ]]

  [[ 1.5944452 ]]

  [[-0.43591785]]

  [[ 1.4425404 ]]

  [[-2.1579928 ]]

  [[ 2.5115259 ]]

  [[ 0.10604887]]

  [[ 0.53013325]]

  [[ 2.4593568 ]]

  [[ 3.8425333 ]]

  [[ 1.510612  ]]

  [[ 2.6186988 ]]

  [[-0.365788  ]]

  [[-0.07304868]]

  [[ 1.9684379 ]]

  [[ 1.0933251 ]]

  [[ 0.34470552]]

  [[ 1.1178714 ]]

  [[ 3.5374014 ]]

  [[ 2.1186767 ]]

  [[ 0.66732824]]

  [[ 1.0683035 ]]

  [[ 2.7602077 ]]

  [[ 3.2852457 ]]

  [[-0.38651127]]

  [[ 1.9059887 ]]

  [[ 1.5833094 ]]

  [[ 1.889504  ]]

  [[ 0.8861643 ]]

  [[ 1.2405196 ]]

  [[ 1.3878361 ]]

  [[ 1.956938  ]]

  [[ 1.8078754 ]]

  [[ 1.3849156 ]]

  [[ 3.4051569 ]]

  [[ 3.1490602 ]]

  [[-1.0523298 ]]

  [[ 1.1143126 ]]

  [[ 0.8821161 ]]

  [[-0.2029241 ]]

  [[ 1.4012253 ]]

  [[ 1.7876036 ]]

  [[-2.3801851 ]]

  [[ 1.4638995 ]]

  [[ 0.89194554]]

  [[-0.9520595 ]]

  [[ 1.6488714 ]]

  [[ 0.8080565 ]]

  [[ 1.416472  ]]

  [[ 1.9556634 ]]

  [[-0.6152393 ]]

  [[-2.6198537 ]]

  [[ 1.3389992 ]]

  [[ 0.62451863]]

  [[-1.3831    ]]

  [[ 2.601157  ]]

  [[ 4.2489877 ]]

  [[ 0.956818  ]]

  [[ 1.4448963 ]]

  [[ 1.2242935 ]]

  [[ 1.7796409 ]]

  [[ 1.0258006 ]]

  [[-2.1094725 ]]

  [[-0.2001234 ]]

  [[-0.27974838]]

  [[ 1.2242429 ]]

  [[-0.8142648 ]]

  [[ 0.9820821 ]]

  [[ 1.9820187 ]]

  [[ 1.4535207 ]]

  [[ 3.1459603 ]]

  [[ 0.8010211 ]]

  [[ 3.373296  ]]

  [[ 2.507955  ]]

  [[ 2.4872022 ]]

  [[ 1.7825925 ]]

  [[-1.1367719 ]]

  [[ 0.3731116 ]]

  [[ 1.4726274 ]]

  [[-0.5747317 ]]

  [[ 1.4636103 ]]

  [[ 1.4617355 ]]

  [[ 1.5335329 ]]]]
tf_layers_dict: KerasTensor(type_spec=TensorSpec(shape=(1, 13, 13, 96), dtype=tf.float32, name=None), name='tf.math.add_88/Add:0', description="created by layer 'tf.math.add_88'")
====================================================================================
layer_type: Swish
layer_id: 455
input_layer0: layer_id=454: KerasTensor(type_spec=TensorSpec(shape=(1, 13, 13, 96), dtype=tf.float32, name=None), name='tf.math.add_88/Add:0', description="created by layer 'tf.math.add_88'")
tf_layers_dict: KerasTensor(type_spec=TensorSpec(shape=(1, 13, 13, 96), dtype=tf.float32, name=None), name='tf.nn.silu_73/IdentityN:0', description="created by layer 'tf.nn.silu_73'")
====================================================================================
layer_type: Const
layer_id: 456
tf_layers_dict_shape: (80, 96, 1, 1)
tf_layers_dict_value: [[[[-0.00134261]]

  [[ 0.02483658]]

  [[ 0.01132369]]

  ...

  [[ 0.05432326]]

  [[ 0.02210934]]

  [[-0.10504632]]]

 [[[ 0.01528567]]

  [[-0.04844463]]

  [[ 0.0257682 ]]

  ...

  [[ 0.04475677]]

  [[-0.04777099]]

  [[-0.05116702]]]

 [[[ 0.06951346]]

  [[-0.0500924 ]]

  [[ 0.01201853]]

  ...

  [[ 0.03735595]]

  [[ 0.06382217]]

  [[ 0.06946969]]]

 ...

 [[[-0.02434462]]

  [[-0.01090814]]

  [[-0.04184687]]

  ...

  [[ 0.02591012]]

  [[-0.04448308]]

  [[-0.02062458]]]

 [[[-0.01642143]]

  [[-0.01935942]]

  [[-0.0281077 ]]

  ...

  [[-0.02653849]]

  [[-0.02628284]]

  [[-0.02066284]]]

 [[[-0.0185364 ]]

  [[-0.00245801]]

  [[-0.03015505]]

  ...

  [[-0.02596138]]

  [[-0.03245317]]

  [[-0.01943119]]]]
====================================================================================
layer_type: Convolution
layer_id: 457
input_layer0: layer_id=455: KerasTensor(type_spec=TensorSpec(shape=(1, 13, 13, 96), dtype=tf.float32, name=None), name='tf.nn.silu_73/IdentityN:0', description="created by layer 'tf.nn.silu_73'")
input_layer1_value: layer_id=456: [[[[-0.00134261]]

  [[ 0.02483658]]

  [[ 0.01132369]]

  ...

  [[ 0.05432326]]

  [[ 0.02210934]]

  [[-0.10504632]]]

 [[[ 0.01528567]]

  [[-0.04844463]]

  [[ 0.0257682 ]]

  ...

  [[ 0.04475677]]

  [[-0.04777099]]

  [[-0.05116702]]]

 [[[ 0.06951346]]

  [[-0.0500924 ]]

  [[ 0.01201853]]

  ...

  [[ 0.03735595]]

  [[ 0.06382217]]

  [[ 0.06946969]]]

 ...

 [[[-0.02434462]]

  [[-0.01090814]]

  [[-0.04184687]]

  ...

  [[ 0.02591012]]

  [[-0.04448308]]

  [[-0.02062458]]]

 [[[-0.01642143]]

  [[-0.01935942]]

  [[-0.0281077 ]]

  ...

  [[-0.02653849]]

  [[-0.02628284]]

  [[-0.02066284]]]

 [[[-0.0185364 ]]

  [[-0.00245801]]

  [[-0.03015505]]

  ...

  [[-0.02596138]]

  [[-0.03245317]]

  [[-0.01943119]]]]
tf_layers_dict: KerasTensor(type_spec=TensorSpec(shape=(1, 13, 13, 80), dtype=tf.float32, name=None), name='conv2d_82/Conv2D:0', description="created by layer 'conv2d_82'")
====================================================================================
layer_type: Const
layer_id: 458
tf_layers_dict_shape: (1, 80, 1, 1)
tf_layers_dict_value: [[[[-3.0110283]]

  [[-4.6342773]]

  [[-4.209836 ]]

  [[-4.5913563]]

  [[-4.3242917]]

  [[-4.577049 ]]

  [[-4.11077  ]]

  [[-4.2169895]]

  [[-4.38152  ]]

  [[-4.8655734]]

  [[-4.770194 ]]

  [[-4.879881 ]]

  [[-4.8631897]]

  [[-4.050074 ]]

  [[-4.5508194]]

  [[-4.6962743]]

  [[-4.732042 ]]

  [[-4.658122 ]]

  [[-4.57228  ]]

  [[-4.7797318]]

  [[-4.6175857]]

  [[-4.8918033]]

  [[-4.8631897]]

  [[-4.5341277]]

  [[-4.8774962]]

  [[-4.3076005]]

  [[-4.8822656]]

  [[-4.825037 ]]

  [[-4.5555887]]

  [[-4.9371085]]

  [[-4.7845006]]

  [[-4.817884 ]]

  [[-4.9681077]]

  [[-4.5889716]]

  [[-4.8608046]]

  [[-4.9204173]]

  [[-4.7964234]]

  [[-4.6152015]]

  [[-4.7964234]]

  [[-4.81073  ]]

  [[-4.863189 ]]

  [[-4.867958 ]]

  [[-4.8870344]]

  [[-4.898957 ]]

  [[-4.9347243]]

  [[-4.7034273]]

  [[-4.631893 ]]

  [[-4.853651 ]]

  [[-4.977645 ]]

  [[-4.827422 ]]

  [[-4.960954 ]]

  [[-4.9379005]]

  [[-4.8918033]]

  [[-4.827422 ]]

  [[-4.957451 ]]

  [[-4.717735 ]]

  [[-4.3600593]]

  [[-4.119225 ]]

  [[-4.391058 ]]

  [[-4.131644 ]]

  [[-3.1292489]]

  [[-4.52459  ]]

  [[-4.4935913]]

  [[-4.608048 ]]

  [[-5.0134125]]

  [[-4.8154993]]

  [[-4.6605067]]

  [[-4.7916546]]

  [[-4.851267 ]]

  [[-4.505514 ]]

  [[-4.9824147]]

  [[-4.6557374]]

  [[-4.391058 ]]

  [[-4.632957 ]]

  [[-4.803577 ]]

  [[-4.844113 ]]

  [[-4.8488827]]

  [[-4.832191 ]]

  [[-4.999106 ]]

  [[-4.944262 ]]]]
====================================================================================
layer_type: Add
layer_id: 459
input_layer0: layer_id=457: KerasTensor(type_spec=TensorSpec(shape=(1, 13, 13, 80), dtype=tf.float32, name=None), name='conv2d_82/Conv2D:0', description="created by layer 'conv2d_82'")
input_layer1_value: layer_id=458: [[[[-3.0110283]]

  [[-4.6342773]]

  [[-4.209836 ]]

  [[-4.5913563]]

  [[-4.3242917]]

  [[-4.577049 ]]

  [[-4.11077  ]]

  [[-4.2169895]]

  [[-4.38152  ]]

  [[-4.8655734]]

  [[-4.770194 ]]

  [[-4.879881 ]]

  [[-4.8631897]]

  [[-4.050074 ]]

  [[-4.5508194]]

  [[-4.6962743]]

  [[-4.732042 ]]

  [[-4.658122 ]]

  [[-4.57228  ]]

  [[-4.7797318]]

  [[-4.6175857]]

  [[-4.8918033]]

  [[-4.8631897]]

  [[-4.5341277]]

  [[-4.8774962]]

  [[-4.3076005]]

  [[-4.8822656]]

  [[-4.825037 ]]

  [[-4.5555887]]

  [[-4.9371085]]

  [[-4.7845006]]

  [[-4.817884 ]]

  [[-4.9681077]]

  [[-4.5889716]]

  [[-4.8608046]]

  [[-4.9204173]]

  [[-4.7964234]]

  [[-4.6152015]]

  [[-4.7964234]]

  [[-4.81073  ]]

  [[-4.863189 ]]

  [[-4.867958 ]]

  [[-4.8870344]]

  [[-4.898957 ]]

  [[-4.9347243]]

  [[-4.7034273]]

  [[-4.631893 ]]

  [[-4.853651 ]]

  [[-4.977645 ]]

  [[-4.827422 ]]

  [[-4.960954 ]]

  [[-4.9379005]]

  [[-4.8918033]]

  [[-4.827422 ]]

  [[-4.957451 ]]

  [[-4.717735 ]]

  [[-4.3600593]]

  [[-4.119225 ]]

  [[-4.391058 ]]

  [[-4.131644 ]]

  [[-3.1292489]]

  [[-4.52459  ]]

  [[-4.4935913]]

  [[-4.608048 ]]

  [[-5.0134125]]

  [[-4.8154993]]

  [[-4.6605067]]

  [[-4.7916546]]

  [[-4.851267 ]]

  [[-4.505514 ]]

  [[-4.9824147]]

  [[-4.6557374]]

  [[-4.391058 ]]

  [[-4.632957 ]]

  [[-4.803577 ]]

  [[-4.844113 ]]

  [[-4.8488827]]

  [[-4.832191 ]]

  [[-4.999106 ]]

  [[-4.944262 ]]]]
tf_layers_dict: KerasTensor(type_spec=TensorSpec(shape=(1, 13, 13, 80), dtype=tf.float32, name=None), name='tf.math.add_89/Add:0', description="created by layer 'tf.math.add_89'")
====================================================================================
layer_type: Sigmoid
layer_id: 460
input_layer0: layer_id=459: KerasTensor(type_spec=TensorSpec(shape=(1, 13, 13, 80), dtype=tf.float32, name=None), name='tf.math.add_89/Add:0', description="created by layer 'tf.math.add_89'")
tf_layers_dict: KerasTensor(type_spec=TensorSpec(shape=(1, 13, 13, 80), dtype=tf.float32, name=None), name='tf.math.sigmoid_5/Sigmoid:0', description="created by layer 'tf.math.sigmoid_5'")
====================================================================================
layer_type: Concat
layer_id: 461
input_layer0: layer_id=440: KerasTensor(type_spec=TensorSpec(shape=(1, 13, 13, 4), dtype=tf.float32, name=None), name='tf.math.add_85/Add:0', description="created by layer 'tf.math.add_85'")
input_layer1: layer_id=445: KerasTensor(type_spec=TensorSpec(shape=(1, 13, 13, 1), dtype=tf.float32, name=None), name='tf.math.sigmoid_4/Sigmoid:0', description="created by layer 'tf.math.sigmoid_4'")
input_layer2: layer_id=460: KerasTensor(type_spec=TensorSpec(shape=(1, 13, 13, 80), dtype=tf.float32, name=None), name='tf.math.sigmoid_5/Sigmoid:0', description="created by layer 'tf.math.sigmoid_5'")
tf_layers_dict: KerasTensor(type_spec=TensorSpec(shape=(1, 13, 13, 85), dtype=tf.float32, name=None), name='tf.concat_16/concat:0', description="created by layer 'tf.concat_16'")
axis: -1
====================================================================================
layer_type: Reshape
layer_id: 462
input_layer0: layer_id=461: KerasTensor(type_spec=TensorSpec(shape=(1, 13, 13, 85), dtype=tf.float32, name=None), name='tf.concat_16/concat:0', description="created by layer 'tf.concat_16'")
input_layer1_value: layer_id=315: [ 1 85 -1]
tf_layers_dict: KerasTensor(type_spec=TensorSpec(shape=(1, 169, 85), dtype=tf.float32, name=None), name='tf.reshape_2/Reshape:0', description="created by layer 'tf.reshape_2'")
====================================================================================
layer_type: Concat
layer_id: 463
input_layer0: layer_id=316: KerasTensor(type_spec=TensorSpec(shape=(1, 2704, 85), dtype=tf.float32, name=None), name='tf.reshape/Reshape:0', description="created by layer 'tf.reshape'")
input_layer1: layer_id=389: KerasTensor(type_spec=TensorSpec(shape=(1, 676, 85), dtype=tf.float32, name=None), name='tf.reshape_1/Reshape:0', description="created by layer 'tf.reshape_1'")
input_layer2: layer_id=462: KerasTensor(type_spec=TensorSpec(shape=(1, 169, 85), dtype=tf.float32, name=None), name='tf.reshape_2/Reshape:0', description="created by layer 'tf.reshape_2'")
tf_layers_dict: KerasTensor(type_spec=TensorSpec(shape=(1, 3549, 85), dtype=tf.float32, name=None), name='tf.concat_17/concat:0', description="created by layer 'tf.concat_17'")
axis: 1
====================================================================================
layer_type: Const
layer_id: 464
tf_layers_dict_shape: (3,)
tf_layers_dict_value: [0 2 1]
====================================================================================
layer_type: Transpose
layer_id: 465
input_layer0: layer_id=463: KerasTensor(type_spec=TensorSpec(shape=(1, 3549, 85), dtype=tf.float32, name=None), name='tf.concat_17/concat:0', description="created by layer 'tf.concat_17'")
input_layer1_value: layer_id=464: [0 2 1]
tf_layers_dict: KerasTensor(type_spec=TensorSpec(shape=(1, 85, 3549), dtype=tf.float32, name=None), name='tf.compat.v1.transpose/transpose:0', description="created by layer 'tf.compat.v1.transpose'")
====================================================================================
layer_type: Result
layer_id: 466
input_layer0: layer_id=465: KerasTensor(type_spec=TensorSpec(shape=(1, 85, 3549), dtype=tf.float32, name=None), name='tf.compat.v1.transpose/transpose:0', description="created by layer 'tf.compat.v1.transpose'")
tf_layers_dict: KerasTensor(type_spec=TensorSpec(shape=(1, 85, 3549), dtype=tf.float32, name=None), name='tf.identity/Identity:0', description="created by layer 'tf.identity'")
====================================================================================
TensorFlow/Keras model building process complete!
.h5 output started ==================================================================
ERROR: cannot pickle 'module' object
Traceback (most recent call last):
  File "/hdd/mukula_STS/SOW6.4/october/openvino2tensorflow/openvino2tensorflow/openvino2tensorflow.py", line 7149, in convert
    model.save(f'{model_output_path}/model_float32.h5', include_optimizer=False, save_format='h5')
  File "/home/user1/envs/py39/lib/python3.9/site-packages/keras/src/utils/traceback_utils.py", line 70, in error_handler
    raise e.with_traceback(filtered_tb) from None
  File "/usr/lib/python3.9/copy.py", line 146, in deepcopy
    y = copier(x, memo)
  File "/usr/lib/python3.9/copy.py", line 230, in _deepcopy_dict
    y[deepcopy(key, memo)] = deepcopy(value, memo)
  File "/usr/lib/python3.9/copy.py", line 146, in deepcopy
    y = copier(x, memo)
  File "/usr/lib/python3.9/copy.py", line 205, in _deepcopy_list
    append(deepcopy(a, memo))
  File "/usr/lib/python3.9/copy.py", line 172, in deepcopy
    y = _reconstruct(x, memo, *rv)
  File "/usr/lib/python3.9/copy.py", line 296, in _reconstruct
    value = deepcopy(value, memo)
  File "/usr/lib/python3.9/copy.py", line 146, in deepcopy
    y = copier(x, memo)
  File "/usr/lib/python3.9/copy.py", line 230, in _deepcopy_dict
    y[deepcopy(key, memo)] = deepcopy(value, memo)
  File "/usr/lib/python3.9/copy.py", line 146, in deepcopy
    y = copier(x, memo)
  File "/usr/lib/python3.9/copy.py", line 210, in _deepcopy_tuple
    y = [deepcopy(a, memo) for a in x]
  File "/usr/lib/python3.9/copy.py", line 210, in <listcomp>
    y = [deepcopy(a, memo) for a in x]
  File "/usr/lib/python3.9/copy.py", line 146, in deepcopy
    y = copier(x, memo)
  File "/usr/lib/python3.9/copy.py", line 210, in _deepcopy_tuple
    y = [deepcopy(a, memo) for a in x]
  File "/usr/lib/python3.9/copy.py", line 210, in <listcomp>
    y = [deepcopy(a, memo) for a in x]
  File "/usr/lib/python3.9/copy.py", line 161, in deepcopy
    rv = reductor(4)
TypeError: cannot pickle 'module' object
All the conversion process is finished! =============================================

Source code for simple inference testing code

No response

PINTO0309 commented 9 months ago

https://github.com/PINTO0309/onnx2tf