def _load_config()

in src/sagemaker/job.py [0:0]

• 42 lines of code
• 7 McCabe index (conditional complexity)

    def _load_config(inputs, estimator, expand_role=True, validate_uri=True):
        """Placeholder docstring"""
        input_config = _Job._format_inputs_to_input_config(inputs, validate_uri)
        role = (
            estimator.sagemaker_session.expand_role(estimator.role)
            if expand_role
            else estimator.role
        )
        output_config = _Job._prepare_output_config(estimator.output_path, estimator.output_kms_key)
        resource_config = _Job._prepare_resource_config(
            estimator.instance_count,
            estimator.instance_type,
            estimator.volume_size,
            estimator.volume_kms_key,
        )
        stop_condition = _Job._prepare_stop_condition(estimator.max_run, estimator.max_wait)
        vpc_config = estimator.get_vpc_config()

        model_channel = _Job._prepare_channel(
            input_config,
            estimator.model_uri,
            estimator.model_channel_name,
            validate_uri,
            content_type="application/x-sagemaker-model",
            input_mode="File",
        )
        if model_channel:
            input_config = [] if input_config is None else input_config
            input_config.append(model_channel)

        if estimator.enable_network_isolation():
            code_channel = _Job._prepare_channel(
                input_config, estimator.code_uri, estimator.code_channel_name, validate_uri
            )

            if code_channel:
                input_config = [] if input_config is None else input_config
                input_config.append(code_channel)

        return {
            "input_config": input_config,
            "role": role,
            "output_config": output_config,
            "resource_config": resource_config,
            "stop_condition": stop_condition,
            "vpc_config": vpc_config,
        }