def test_trasformer_pytorch_logger(integration_test_url, project_name,
use_google_oauth):
merlin.set_url(integration_test_url, use_google_oauth=use_google_oauth)
merlin.set_project(project_name)
merlin.set_model("transformer-logger", ModelType.PYTORCH)
model_dir = "test/transformer"
undeploy_all_version()
resource_request = ResourceRequest(1, 1, "100m", "200Mi")
transformer = Transformer(
"gcr.io/kubeflow-ci/kfserving/image-transformer:latest",
resource_request=resource_request,
)
logger = Logger(
model=LoggerConfig(enabled=True, mode=LoggerMode.ALL),
transformer=LoggerConfig(enabled=True, mode=LoggerMode.ALL),
)
with merlin.new_model_version() as v:
merlin.log_pytorch_model(model_dir=model_dir)
endpoint = merlin.deploy(transformer=transformer, logger=logger)
assert endpoint.logger is not None
model_config = endpoint.logger.model
assert model_config is not None
assert model_config.enabled
assert model_config.mode == LoggerMode.ALL
transformer_config = endpoint.logger.transformer
assert transformer_config is not None
assert transformer_config.enabled
assert transformer_config.mode == LoggerMode.ALL
with open(os.path.join("test/transformer", "input.json"), "r") as f:
req = json.load(f)
sleep(5)
resp = requests.post(f"{endpoint.url}", json=req)
assert resp.status_code == 200
assert resp.json() is not None
assert len(resp.json()["predictions"]) == len(req["instances"])
model_endpoint = merlin.serve_traffic({endpoint: 100})
sleep(5)
resp = requests.post(f"{model_endpoint.url}", json=req)
assert resp.status_code == 200
assert resp.json() is not None
assert len(resp.json()["predictions"]) == len(req["instances"])
# Try to undeploy serving model version. It must be fail
with pytest.raises(Exception):
assert merlin.undeploy(v)
# Undeploy other running model version endpoints
undeploy_all_version()
def test_pytorch_logger(integration_test_url, project_name, use_google_oauth):
merlin.set_url(integration_test_url, use_google_oauth=use_google_oauth)
merlin.set_project(project_name)
merlin.set_model("pytorch-logger", ModelType.PYTORCH)
model_dir = "test/pytorch-model"
undeploy_all_version()
logger = Logger(model=LoggerConfig(enabled=True, mode=LoggerMode.REQUEST))
with merlin.new_model_version() as v:
merlin.log_pytorch_model(model_dir=model_dir)
endpoint = merlin.deploy(logger=logger)
model_config = endpoint.logger.model
assert model_config is not None
assert model_config.enabled
assert model_config.mode == LoggerMode.REQUEST
transformer_config = endpoint.logger.transformer
assert transformer_config is None
resp = requests.post(f"{endpoint.url}", json=request_json)
assert resp.status_code == 200
assert resp.json() is not None
assert len(resp.json()["predictions"]) == len(request_json["instances"])
undeploy_all_version()
def test_mlflow_tracking(integration_test_url, project_name, use_google_oauth):
merlin.set_url(integration_test_url, use_google_oauth=use_google_oauth)
merlin.set_project(project_name)
merlin.set_model("mlflow-tracking", ModelType.PYTORCH)
model_dir = "test/pytorch-model"
undeploy_all_version()
with merlin.new_model_version() as v:
merlin.log_pytorch_model(model_dir=model_dir)
merlin.log_param("model_type", "pytorch")
merlin.log_param("iteration", 5)
merlin.set_tag("version", "v1.0")
merlin.set_tag("build", "latest")
merlin.set_tag("team_id", 1)
merlin.log_metric("model_loaded", 10.23)
assert merlin.get_param("model_type") == "pytorch"
# Stringify value which is integer originally
assert merlin.get_param("iteration") == '5'
assert merlin.get_param("random_key") is None
assert merlin.get_tag("version") == "v1.0"
assert merlin.get_tag("xxx") is None
# Stringify value which is integer originally
assert merlin.get_tag("team_id") == "1"
assert merlin.get_metric("model_loaded") == 10.23
assert merlin.get_metric("response_time") is None
assert merlin.list_tag() == {
"version": "v1.0", "build": "latest", "team_id": "1"}
def test_pytorch(integration_test_url, project_name, use_google_oauth):
merlin.set_url(integration_test_url, use_google_oauth=use_google_oauth)
merlin.set_project(project_name)
merlin.set_model("pytorch-sample", ModelType.PYTORCH)
model_dir = "test/pytorch-model"
with merlin.new_model_version() as v:
merlin.log_pytorch_model(model_dir=model_dir)
port = _get_free_port()
p = Process(target=v.start_server, kwargs={"port": port, "build_image": True})
p.start()
_wait_server_ready(f"http://{host}:{port}")
resp = requests.post(_get_local_endpoint(v, port), json=request_json)
assert resp.status_code == 200
assert resp.json() is not None
assert len(resp.json()['predictions']) == len(request_json['instances'])
p.terminate()
def test_pytorch(integration_test_url, project_name, use_google_oauth):
merlin.set_url(integration_test_url, use_google_oauth=use_google_oauth)
merlin.set_project(project_name)
merlin.set_model("pytorch-sample", ModelType.PYTORCH)
model_dir = "test/pytorch-model"
undeploy_all_version()
with merlin.new_model_version() as v:
merlin.log_pytorch_model(model_dir=model_dir)
endpoint = merlin.deploy()
resp = requests.post(f"{endpoint.url}", json=request_json)
assert resp.status_code == 200
assert resp.json() is not None
assert len(resp.json()["predictions"]) == len(request_json["instances"])
merlin.undeploy(v)
