624d14284e35d6ce9c371c39f7e387002ccf4913,onnx_coreml/converter.py,,convert,#Any#Any#Any#Any#Any#Any#Any#Any#Any#Any#,248

Before Change

                bias = node.attrs.get("bias", [0,0,0])
                if not (len(bias) == 1 or len(bias) == 3):
                    continue
                bias_r_g_b_gray = [0,0,0,0]
                if len(bias) == 1:
                    bias_r_g_b_gray[3] = bias[0]
                else:
                    bias_r_g_b_gray[:3] = bias
                if inp_name not in image_input_names:
                    image_input_names.append(inp_name) // type: ignore
                preprocessing_args["is_bgr"] = {inp_name: False}
                preprocessing_args["red_bias"] = {inp_name: bias_r_g_b_gray[0]}
                preprocessing_args["green_bias"] = {inp_name: bias_r_g_b_gray[1]}
                preprocessing_args["blue_bias"] = {inp_name: bias_r_g_b_gray[2]}
                preprocessing_args["gray_bias"] = {inp_name: bias_r_g_b_gray[3]}
                preprocessing_args["image_scale"] = {inp_name: scale}

After Change

                else:
                    preprocessing_args["image_scale"] = {inp_name: scale}
                if len(bias) == 3:
                    for i, color in enumerate(["red", "green", "blue"]):
                        if color + "_bias" in preprocessing_args:
                            preprocessing_args[color + "_bias"][inp_name] = bias[i]
                        else:
                            preprocessing_args[color + "_bias"] = {inp_name: bias[i]}
                else:
                    if "gray_bias" in preprocessing_args:
                        preprocessing_args["gray_bias"][inp_name] = bias[0]
                    else:

Instances