def test_transformer_implementation(): test.create_resource_config() test.create_input_data_config() test.create_hyperparameters_config({"sagemaker_program": "user_script.py"}) model_path = os.path.join(env.model_dir, "fake_ml_model") fake_ml_framework.Model(weights=[6, 9, 42]).save(model_path) transform = transformer.Transformer(model_fn=model_fn, predict_fn=predict_fn) transform.initialize() with worker.Worker(transform_fn=transform.transform, module_name="fake_ml_model").test_client() as client: payload = [6, 9, 42.0] response = post(client, payload, content_types.NPY, content_types.JSON) assert response.status_code == http_client.OK assert response.get_data(as_text=True) == "[36.0, 81.0, 1764.0]" response = post(client, payload, content_types.JSON, content_types.CSV) assert response.status_code == http_client.OK assert response.get_data(as_text=True) == "36.0\n81.0\n1764.0\n" response = post(client, payload, content_types.CSV, content_types.NPY) assert response.status_code == http_client.OK response_data = encoders.npy_to_numpy(response.get_data()) np.testing.assert_array_almost_equal(response_data, np.asarray([36.0, 81.0, 1764.0]))
def main(environ, start_response): global app if app is None: serving_env = env.ServingEnv() user_module = modules.import_module(serving_env.module_dir, serving_env.module_name) user_module_transformer = _user_module_transformer(user_module) user_module_transformer.initialize() app = worker.Worker(transform_fn=user_module_transformer.transform, module_name=serving_env.module_name) return app(environ, start_response)
def main(environ, start_response): global app if app is None: serving_env = env.ServingEnv() _update_mxnet_env_vars() user_module = modules.import_module(serving_env.module_dir, serving_env.module_name) user_transformer = _user_module_transformer(user_module, serving_env.model_dir) app = worker.Worker(transform_fn=user_transformer.transform, module_name=serving_env.module_name) return app(environ, start_response)
def main(environ, start_response): global app if app is None: serving_env = env.ServingEnv() logger.setLevel(serving_env.log_level) user_module = modules.import_module(serving_env.module_dir, serving_env.module_name) user_module_transformer = _user_module_transformer(user_module) user_module_transformer.initialize() app = worker.Worker(transform_fn=user_module_transformer.transform, module_name=serving_env.module_name, healthcheck_fn=default_healthcheck_fn) return app(environ, start_response)
def main(environ, start_response): global app if app is None: serving_env = env.ServingEnv() user_module_transformer, execution_parameters_fn = import_module( serving_env.module_name, serving_env.module_dir) app = worker.Worker(transform_fn=user_module_transformer.transform, module_name=serving_env.module_name, execution_parameters_fn=execution_parameters_fn) return app(environ, start_response)
def main(environ, start_response): serving_env = env.ServingEnv() logger.setLevel(serving_env.log_level) user_module = modules.import_module_from_s3(serving_env.module_dir, serving_env.module_name) user_module_transformer = _user_module_transformer(user_module) user_module_transformer.initialize() app = worker.Worker(transform_fn=user_module_transformer.transform, module_name=serving_env.module_name) return app(environ, start_response)