Tools to convert ONNX files (NCHW) to TensorFlow format (NHWC)

• Corrected the decision condition to enable DepthwiseConv2D
• [japan_PP-OCRv3] For min_value and max_value in Clip.py #14
• japan_PP-OCRv3_rec_infer.onnx.zip

Solves the problem of TensorFlow runtime abort during inference when DepthwiseConv2D is generated with different values of strides in the row and column directions, such as [1,2] or [2,1] strides. DepthwiseConv2D seems to work correctly only when all strides have the same value. In this case, GroupConvolution is generated.

• e.g. TensorFlow (Keras) - DepthwiseConv2D error message ``` Current implementation only supports equal length strides in the row and column dimensions. [Op:DepthwiseConv2dNative]

Call arguments received by layer "tf.compat.v1.nn.depthwise_conv2d_3" " f"(type TFOpLambda): • input=tf.Tensor(shape=(3, 18, 82, 64), dtype=float32) • filter=tf.Tensor(shape=(3, 3, 64, 1), dtype=float32) • strides=['1', '2', '1', '1'] • padding='VALID' • rate=['1', '1'] • name=None • data_format=None • dilations=None ```

• Corrected the decision condition to enable DepthwiseConv2D by @PINTO0309 in https://github.com/PINTO0309/onnx2tf/pull/144

Full Changelog: https://github.com/PINTO0309/onnx2tf/compare/1.5.27...1.5.28