Onnx2tf

- `Flatten`
- Addressed the issue of missing conversions when multi-dimensional flattening is performed and the batch size of the first dimension is an undefined dimension.
|ONNX|TFLite|
|:-:|:-:|
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- [[EfficientNetV2_m] Output size is constant not variable 688](https://github.com/PINTO0309/onnx2tf/issues/688)

What's Changed
* Addressed the issue of missing conversions when multi-dimensional flattening is performed and the batch size of the first dimension is an undefined dimension. by PINTO0309 in https://github.com/PINTO0309/onnx2tf/pull/689


**Full Changelog**: https://github.com/PINTO0309/onnx2tf/compare/1.25.9...1.25.10

- `Add`, `Sub`
- https://huggingface.co/onnx-community/metric3d-vit-small/blob/main/onnx/model.onnx
- metric3d-vit-small.onnx
- Fixed a bug in the optimization process for arithmetic operations. The error of the final output was less than `1e-4`.
- A bug in the optimization process for the `y = (200 - x) - 200` operation caused an incorrect `Sub` merge operation to be performed.
- [Model gives inaccurate results post conversion to tflite 685](https://github.com/PINTO0309/onnx2tf/issues/685)

What's Changed
* Fixed a bug in the optimization process for arithmetic operations by PINTO0309 in https://github.com/PINTO0309/onnx2tf/pull/686


**Full Changelog**: https://github.com/PINTO0309/onnx2tf/compare/1.25.8...1.25.9

- `Shape`
- Fixed problem of being stuck in an infinite loop.
- [An input to an ADD node keeps getting casted to float32 despite being float16 in the onnx file causing issues with the ADD op 681](https://github.com/PINTO0309/onnx2tf/issues/681)

What's Changed
* Fixed problem of being stuck in an infinite loop by PINTO0309 in https://github.com/PINTO0309/onnx2tf/pull/682


**Full Changelog**: https://github.com/PINTO0309/onnx2tf/compare/1.25.7...1.25.8

- `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`.
- I have fixed and released the critical problems except for `AveragePool`, but `AveragePool (with ceil_mode=1)` with dynamic tensor as input is extremely difficult to fix due to compatibility issues with TensorFlow.
- The problem is that the error was not occurring in the `AveragePool (with ceil_mode=1)` where the conversion error should have occurred, and the latest onnx2tf should now generate a conversion error in the `AveragePool (with ceil_mode=1)`.


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.

- [Unable to convert a model with 3d input shape of dynamic length into tflite int8 format 673](https://github.com/PINTO0309/onnx2tf/issues/673)

What's Changed
* Automatic accuracy compensation `Expand`, `BatchNormalization`, `Gather` by PINTO0309 in https://github.com/PINTO0309/onnx2tf/pull/675


**Full Changelog**: https://github.com/PINTO0309/onnx2tf/compare/1.25.6...1.25.7

- `Concat`
- Bug fix for `Dynamic Resize` optimization pattern.
https://github.com/yakhyo/face-parsing
|ONNX|TFLite|
|:-:|:-:|
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What's Changed
* Bug fix for Resize optimization pattern by PINTO0309 in https://github.com/PINTO0309/onnx2tf/pull/672


**Full Changelog**: https://github.com/PINTO0309/onnx2tf/compare/1.25.5...1.25.6

- `Transpose`
- Fixed NHWC flag judgment bug in `Transpose` of ViT for 3D tensor

What's Changed
* Fixed NHWC flag judgment bug in Transpose of ViT for 3D tensor by PINTO0309 in https://github.com/PINTO0309/onnx2tf/pull/671


**Full Changelog**: https://github.com/PINTO0309/onnx2tf/compare/1.25.4...1.25.5