c40305a954f3335c22cb98a42c8daa2ca9ca4a0a,onnxmltools/convert/keras/operator_converters/Conv.py,,convert_keras_conv_core,#Any#Any#Any#Any#Any#Any#Any#Any#,18

Before Change

    elif op.padding == "same":
        if is_transpose:  // bypass onnx engine issue on convtranpose support.
            attrs["auto_pad"] = "SAME_LOWER"
            shape = [-1 if i is None else i for i in op.output_shape]
            if channels_first:
                attrs["output_shape"] = shape
            else:

After Change

    if op.padding == "valid":
        attrs["auto_pad"] = "VALID"
    elif op.padding == "same":
        if op.input_shape.count(None) > 1:
            if is_transpose:
                attrs["auto_pad"] = "SAME_LOWER"  // the controversial def in onnx spec.
            else:
                attrs["auto_pad"] = "SAME_UPPER"
        else:
            output_padding = [0] * len(op.kernel_size)
            if hasattr(op, "output_padding") and op.output_padding is not None:
                output_padding = op.output_padding
            attrs["pads"] = _calc_explicit_padding(op.output_shape if is_transpose else op.input_shape,
                                                   op.input_shape if is_transpose else op.output_shape,
                                                   output_padding,
                                                   op.kernel_size,
                                                   op.strides,
                                                   op.dilation_rate,
                                                   list(range(len(op.input_shape))) if channels_first else input_perm_axes)
    else:
        raise RuntimeError("Unsupported padding type "{}"".format(op.padding))

    intermediate_output_name = scope.get_unique_variable_name("convolution_output")

Instances