Onnx2tf

- `Softmax`, `LayerNormalization`
- If all axes are of different sizes and the axis sizes specified in axis are the same in onnx and TensorFlow, skip the accuracy check.
- Faster model transformations in some architectures, such as Transformer.
- OPs with multiple axes of the same size are corrected for accuracy as usual, so the conversion speed is not accelerated.

What's Changed
* If all axes are of different sizes and the axis sizes specified in axis are the same in onnx and TensorFlow, skip the accuracy check. by PINTO0309 in https://github.com/PINTO0309/onnx2tf/pull/534


**Full Changelog**: https://github.com/PINTO0309/onnx2tf/compare/1.18.10...1.18.11

- `Concat`
- Fixed an error when the input tensor was 1-dimensional during `Concat` accuracy correction.
- `Clip`
- Support for special max and min values for `Clip`.

What's Changed
* Fixed an error when the input tensor was 1-dimensional during `Concat` accuracy correction. by PINTO0309 in https://github.com/PINTO0309/onnx2tf/pull/532
* Support for special max and min values for `Clip` by PINTO0309 in https://github.com/PINTO0309/onnx2tf/pull/533


**Full Changelog**: https://github.com/PINTO0309/onnx2tf/compare/1.18.9...1.18.10

- `Reshape`
- Much stricter accuracy correction conditions for `Reshape`.
- The conversion speed is greatly reduced at the cost of not causing accuracy degradation.
- [mobileformer.onnx.zip](https://github.com/PINTO0309/onnx2tf/files/12782257/mobileformer.onnx.zip)
- `Concat`
- Fixed to skip accuracy check if one of the multiple input tensors contains np.ndarray (constant).

What's Changed
* Fixed to skip accuracy check if one of the multiple input tensors contains `np.ndarray (constant)` by PINTO0309 in https://github.com/PINTO0309/onnx2tf/pull/531
* Much stricter accuracy correction conditions for `Reshape` by PINTO0309 in https://github.com/PINTO0309/onnx2tf/pull/530


**Full Changelog**: https://github.com/PINTO0309/onnx2tf/compare/1.18.8...1.18.9

- https://s3.ap-northeast-2.wasabisys.com/temp-models/onnx2tf_529/latest.opset17.onnx
- `Reshape`
- Fixed a critical bug in `Reshape` accuracy correction process.
- Removed special workaround processing to accommodate ShuffleNet, which is no longer needed.
- `LayerNormalization`
- Added accuracy correction process.


- [[InSPyReNet] Swin Transformer Support question 312](https://github.com/PINTO0309/onnx2tf/issues/312)
- [Reshape Unmatched max abs error when doing ONNX and TF output value validation 478](https://github.com/PINTO0309/onnx2tf/issues/478)

What's Changed
* Fixed a critical bug in `Reshape`, `LayerNormalization` accuracy correction process by PINTO0309 in https://github.com/PINTO0309/onnx2tf/pull/529


**Full Changelog**: https://github.com/PINTO0309/onnx2tf/compare/1.18.7...1.18.8

- `MatMul`
- Improved processing speed of `MatMul` accuracy correction process.
- `Concat`
- Improved the high likelihood of accuracy degradation in `Concat` input tensors where all axes except the batch size are the same size.

What's Changed
* Improved processing speed of `MatMul` accuracy correction process by PINTO0309 in https://github.com/PINTO0309/onnx2tf/pull/527
* Improved the high likelihood of accuracy degradation in `Concat` input tensors where all axes except the batch size are the same size. by PINTO0309 in https://github.com/PINTO0309/onnx2tf/pull/528


**Full Changelog**: https://github.com/PINTO0309/onnx2tf/compare/1.18.6...1.18.7

- `MatMul`
- Improved `BatchMatMul` transformation stability in the presence of undefined dimensions in the input tensor.

What's Changed
* Improved `BatchMatMul` transformation stability in the presence of undefined dimensions in the input tensor. by PINTO0309 in https://github.com/PINTO0309/onnx2tf/pull/526


**Full Changelog**: https://github.com/PINTO0309/onnx2tf/compare/1.18.5...1.18.6