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Adam Osewski authored
* Use ConvolutionBackpropData in ONNX ConvTranspose operator. * Replace deprecated functions and update documentation. * Remove GroupConvolutionTranspose fused op. * Add more UT for GroupConvolutionBackpropData. - They're transformed from GroupConvolutionTranspose * Fix validate_and_infed types for ConvolutionBackpropData v1. * Add new constructor for GroupConvolutionBackpropData - Additionally do some code formatting. * Improve validation in GroupConvBackprop v0. * Update/fix upgrade & downgrade passes for (Group)ConvolutionBackpropData. * Add decomposition and validation for GroupConvolutionBackpropData:v1 * Type properties UT for GroupConvolutionBackprop v1 * Remove include of deleted header. * Add squeeze to opset1::builder. * Use opset1 squeeze. * Helper functions for padding and output spatial shape inference. These helper functions are specialized only for *ConvolutionBackpropData operators. * Update documentation. * Add more checks and remove deprecated assert. * Refactor GroupConvolutionBackpropData validation. - Use helper functions to infer padding and output shape. - Change get_output_shape to return only spatial features dimensions * Remove unnecessary code from donwgrade pass. The GroupConvolutionBackpropData node has already computed all those required information. * Call Node API. Small review suggestions. * Work only on spatial dimensions inside helper functions. * Enhance documentation for ConvolutionBackpropData * Refactoring. * Reuse values computed in downgraded operator. * Check for correct filters input shape. * Add additional check on auto pad value. * Remove unused variables. * Rename helper function. * Add more checks. * Override is dynamic and add more restrictive check. * Fix merge artifact and force unsigned type for argument. * Review comments: renaming. * Change Convolution + bias pattern. Change from bias broadcasting to appropriate convolution output shape into reshape into (1, C, 1, 1) shape, which sould work better. * Add few more test cases for ONNX ConvTranspose op. * Skip one UT failing on PlaidML backend due to accuracy.