src/sagemaker/serve/model_server/smd/server.py [20:52]:
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        self,
        model_path: str,
        sagemaker_session: Session,
        secret_key: str,
        s3_model_data_url: str = None,
        image: str = None,
        should_upload_artifacts: bool = False,
    ):
        """Tar the model artifact and upload to S3 bucket, then prepare for the environment variables"""
        s3_upload_path = None
        if _is_s3_uri(model_path):
            s3_upload_path = model_path
        elif should_upload_artifacts:
            if s3_model_data_url:
                bucket, key_prefix = parse_s3_url(url=s3_model_data_url)
            else:
                bucket, key_prefix = None, None

            code_key_prefix = fw_utils.model_code_key_prefix(key_prefix, None, image)

            bucket, code_key_prefix = determine_bucket_and_prefix(
                bucket=bucket, key_prefix=code_key_prefix, sagemaker_session=sagemaker_session
            )

            logger.debug(
                "Uploading the model resources to bucket=%s, key_prefix=%s.",
                bucket,
                code_key_prefix,
            )
            s3_upload_path = upload(sagemaker_session, model_path, bucket, code_key_prefix)
            logger.debug("Model resources uploaded to: %s", s3_upload_path)

        env_vars = {
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src/sagemaker/serve/model_server/tensorflow_serving/server.py [99:140]:
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        self,
        model_path: str,
        sagemaker_session: Session,
        secret_key: str,
        s3_model_data_url: str = None,
        image: str = None,
        should_upload_artifacts: bool = False,
    ):
        """Uploads the model artifacts to S3.

        Args:
            model_path: Path to the model
            sagemaker_session: SageMaker session
            secret_key: Secret key to use for authentication
            s3_model_data_url: S3 model data URL
            image: Image to use
            model_data_s3_path: S3 model data URI
        """
        s3_upload_path = None
        if _is_s3_uri(model_path):
            s3_upload_path = model_path
        elif should_upload_artifacts:
            if s3_model_data_url:
                bucket, key_prefix = parse_s3_url(url=s3_model_data_url)
            else:
                bucket, key_prefix = None, None

            code_key_prefix = fw_utils.model_code_key_prefix(key_prefix, None, image)

            bucket, code_key_prefix = determine_bucket_and_prefix(
                bucket=bucket, key_prefix=code_key_prefix, sagemaker_session=sagemaker_session
            )

            logger.debug(
                "Uploading the model resources to bucket=%s, key_prefix=%s.",
                bucket,
                code_key_prefix,
            )
            s3_upload_path = upload(sagemaker_session, model_path, bucket, code_key_prefix)
            logger.debug("Model resources uploaded to: %s", s3_upload_path)

        env_vars = {
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