Self-Created Tools to convert ONNX files (NCHW) to TensorFlow/TFLite/Keras format (NHWC). The purpose of this tool is to solve the massive Transpose extrapolation problem in onnx-tensorflow (onnx-tf). I don't need a Star, but give me a pull request.
Added the ability to automatically compensate for accuracy degradation due to dimensional transposition errors.
AveragePool
Only very few edge cases are supported.
The dynamic tensor AveragePool is difficult to replace exactly with TensorFlow's AveragePooling.
INFO: 39 / 1464
INFO: onnx_op_type: AveragePool onnx_op_name: wa/xvector/block1/tdnnd1/cam_layer/AveragePool
INFO: input_name.1: wa/xvector/block1/tdnnd1/nonlinear2/relu/Relu_output_0 shape: [1, 128, 'unk__71'] dtype: float32
INFO: output_name.1: wa/xvector/block1/tdnnd1/cam_layer/AveragePool_output_0 shape: [1, 128, 'unk__77'] dtype: float32
ERROR: The trace log is below.
Traceback (most recent call last):
File "/home/xxxxx/git/onnx2tf/onnx2tf/utils/common_functions.py", line 312, in print_wrapper_func
result = func(*args, **kwargs)
File "/home/xxxxx/git/onnx2tf/onnx2tf/utils/common_functions.py", line 385, in inverted_operation_enable_disable_wrapper_func
result = func(*args, **kwargs)
File "/home/xxxxx/git/onnx2tf/onnx2tf/utils/common_functions.py", line 55, in get_replacement_parameter_wrapper_func
func(*args, **kwargs)
File "/home/xxxxx/git/onnx2tf/onnx2tf/ops/AveragePool.py", line 171, in make_node
output_spatial_shape = [
File "/home/xxxxx/git/onnx2tf/onnx2tf/ops/AveragePool.py", line 172, in <listcomp>
func((i + pb + pe - d * (k - 1) - 1) / s + 1)
TypeError: unsupported operand type(s) for +: 'NoneType' and 'int'
ERROR: input_onnx_file_path: ../cam++_vin.onnx
ERROR: onnx_op_name: wa/xvector/block1/tdnnd1/cam_layer/AveragePool
ERROR: Read this and deal with it. https://github.com/PINTO0309/onnx2tf#parameter-replacement
ERROR: Alternatively, if the input OP has a dynamic dimension, use the -b or -ois option to rewrite it to a static shape and try again.
ERROR: If the input OP of ONNX before conversion is NHWC or an irregular channel arrangement other than NCHW, use the -kt or -kat option.
ERROR: Also, for models that include NonMaxSuppression in the post-processing, try the -onwdt option.
2. Summary of corrections
3. Before/After (If there is an operating log that can be used as a reference)
4. Issue number (only if there is a related issue)
1. Content and background
Expand,BatchNormalization,GatherAveragePoolAveragePoolis difficult to replace exactly with TensorFlow'sAveragePooling.ERROR: input_onnx_file_path: ../cam++_vin.onnx ERROR: onnx_op_name: wa/xvector/block1/tdnnd1/cam_layer/AveragePool ERROR: Read this and deal with it. https://github.com/PINTO0309/onnx2tf#parameter-replacement ERROR: Alternatively, if the input OP has a dynamic dimension, use the -b or -ois option to rewrite it to a static shape and try again. ERROR: If the input OP of ONNX before conversion is NHWC or an irregular channel arrangement other than NCHW, use the -kt or -kat option. ERROR: Also, for models that include NonMaxSuppression in the post-processing, try the -onwdt option.
2. Summary of corrections
3. Before/After (If there is an operating log that can be used as a reference)
4. Issue number (only if there is a related issue)