sagemaker_notebook_instance/containers/entity_recognition/entry_point.py [35:55]:
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    }
    return model_assets


def input_fn(request_body_str, request_content_type):
    assert (
        request_content_type == "application/json"
    ), "content_type must be 'application/json'"
    request_body = json.loads(request_body_str)
    return request_body


def get_parameter(request_body, parameter_name, default):
    parameter = default
    if 'parameters' in request_body:
        if parameter_name in request_body['parameters']:
            parameter = request_body['parameters'][parameter_name]
    return parameter


def predict_fn(request_body, model_assets):
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sagemaker_notebook_instance/containers/summarization/entry_point.py [21:41]:
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    }
    return model_assets


def input_fn(request_body_str, request_content_type):
    assert (
        request_content_type == "application/json"
    ), "content_type must be 'application/json'"
    request_body = json.loads(request_body_str)
    return request_body


def get_parameter(request_body, parameter_name, default):
    parameter = default
    if 'parameters' in request_body:
        if parameter_name in request_body['parameters']:
            parameter = request_body['parameters'][parameter_name]
    return parameter


def predict_fn(request_body, model_assets):
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