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)
