src/sagemaker/serve/model_server/multi_model_server/inference.py [45:80]:
- - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - -
    try:
        if hasattr(schema_builder, "custom_input_translator"):
            deserialized_data = schema_builder.custom_input_translator.deserialize(
                (
                    io.BytesIO(input_data.encode("utf-8"))
                    if not any(
                        [
                            isinstance(input_data, bytes),
                            isinstance(input_data, bytearray),
                        ]
                    )
                    else io.BytesIO(input_data)
                ),
                content_type,
            )
        else:
            deserialized_data = schema_builder.input_deserializer.deserialize(
                (
                    io.BytesIO(input_data.encode("utf-8"))
                    if not any(
                        [
                            isinstance(input_data, bytes),
                            isinstance(input_data, bytearray),
                        ]
                    )
                    else io.BytesIO(input_data)
                ),
                content_type[0],
            )

        # Check if preprocess method is defined and call it
        if hasattr(inference_spec, "preprocess"):
            return inference_spec.preprocess(deserialized_data)

        return deserialized_data
    except Exception as e:
- - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - -



src/sagemaker/serve/model_server/torchserve/inference.py [67:102]:
- - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - -
    try:
        if hasattr(schema_builder, "custom_input_translator"):
            deserialized_data = schema_builder.custom_input_translator.deserialize(
                (
                    io.BytesIO(input_data.encode("utf-8"))
                    if not any(
                        [
                            isinstance(input_data, bytes),
                            isinstance(input_data, bytearray),
                        ]
                    )
                    else io.BytesIO(input_data)
                ),
                content_type,
            )
        else:
            deserialized_data = schema_builder.input_deserializer.deserialize(
                (
                    io.BytesIO(input_data.encode("utf-8"))
                    if not any(
                        [
                            isinstance(input_data, bytes),
                            isinstance(input_data, bytearray),
                        ]
                    )
                    else io.BytesIO(input_data)
                ),
                content_type[0],
            )

        # Check if preprocess method is defined and call it
        if hasattr(inference_spec, "preprocess"):
            return inference_spec.preprocess(deserialized_data)

        return deserialized_data
    except Exception as e:
- - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - -