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

• Improved INT8 quantization to be performed based on saved_model signature information
• Ref: https://www.tensorflow.org/lite/performance/post_training_quantization#full_integer_quantization
  • Improved matching of the input OP name specified in the dataset for calibration with the input OP name in the signature to prevent input order discrepancies.
  • When quantizing INT8 for models with multiple inputs, you no longer need to be aware of the order in which the calibration data sets are specified.
  • Only when performing INT8 quantization, the saved_model signature information of the converted model is displayed in the log as reference information, as shown in the figure below.
  • The input OP name in ONNX and the input OP name after conversion to saved_model may mismatch. This is due to automatic sanitization of strings that cannot be used in the input OP name of saved_model. e.g. :, /
  • [BERT-Squad] INT8 quantization: The input data type must be Float32. #248

• Improved INT8 quantization to be performed based on saved_model signature information by @PINTO0309 in https://github.com/PINTO0309/onnx2tf/pull/249

Full Changelog: https://github.com/PINTO0309/onnx2tf/compare/1.7.26...1.7.27