def compile_model()

in sample-apps/custom-model/code/model/model.py [0:0]

• 23 lines of code
• 1 McCabe index (conditional complexity)

    def compile_model(self, s3_uri, input_name='input_1', input_shape='224,224,3', framework='TENSORFLOW', device='jetson_xavier'):
        """Compiles a model with Amazon Sagemaker Neo."""
        MODEL_INPUT_SHAPE = '{{"{}":[1,{}]}}'.format(input_name,input_shape)
        COMPILED_MODEL_FOLDER_URI = 's3://{}/models-compiled'.format(self.bucket_name)
        COMPILATION_JOB = 'panorama-custom-model-'+ str(time.time()).split('.')[0]
        logger.info('Compiling {}'.format(s3_uri))
        response = sagemaker_client.create_compilation_job(
                CompilationJobName=COMPILATION_JOB,
                RoleArn=self.service_role_arn,
                InputConfig={
                    'S3Uri': s3_uri,
                    'DataInputConfig': MODEL_INPUT_SHAPE,
                    'Framework': framework
                },
                OutputConfig={
                    'S3OutputLocation': COMPILED_MODEL_FOLDER_URI,
                    'TargetDevice': device
                },
                StoppingCondition={
                    'MaxRuntimeInSeconds': 900
                }
            )
        logger.info(response)
        return COMPILATION_JOB