Automatic accuracy compensation Expand, BatchNormalization, Gather

[PINTO0309]

1. Content and background

• Expand, BatchNormalization, Gather
  • Automatic accuracy compensation.
  • 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)

• Unable to convert a model with 3d input shape of dynamic length into tflite int8 format #673