def test_undeploy_pipeline_docker(inference_pipeline: Pipeline,
docker_runtime: SeldonDockerRuntime):
inference_pipeline.undeploy()
for model in inference_pipeline._models:
with pytest.raises(docker.errors.NotFound):
docker_runtime._get_container(model._details)
async def test_pipeline_save_load(inference_pipeline: Pipeline, tmp_path: str):
inference_pipeline.details.local_folder = tmp_path
inference_pipeline.save()
loaded_pipeline = Pipeline.load(tmp_path)
y_pred = loaded_pipeline(np.array([[4.9, 3.1, 1.5, 0.2]]))
np.testing.assert_allclose(y_pred, [[0.8, 0.19, 0.01]], atol=1e-2)
async def test_pipeline_save(inference_pipeline: Pipeline, tmp_path: str):
pipeline_path = os.path.join(tmp_path, "pipeline.pickle")
inference_pipeline.save(pipeline_path)
loaded_pipeline = Pipeline.load(pipeline_path)
y_pred = loaded_pipeline(np.array([[4.9, 3.1, 1.5, 0.2]]))
np.testing.assert_allclose(y_pred, [[0.8, 0.19, 0.01]], atol=1e-2)
def _pipeline(f):
if inspect.isclass(f):
K = f
func = None
for a in dir(K):
if not a.startswith("__") and callable(getattr(
K, a)) and hasattr(getattr(K, a), "predict"):
func = getattr(K, a)
break
K.pipeline = Pipeline(
name,
runtime=runtime,
local_folder=local_folder,
uri=uri,
models=models,
inputs=inputs,
outputs=outputs,
pipeline_func=func,
conda_env=conda_env,
)
setattr(K, "deploy", K.pipeline.deploy)
setattr(K, "deploy_models", K.pipeline.deploy_models)
setattr(K, "wait_ready", K.pipeline.wait_ready)
setattr(K, "undeploy", K.pipeline.undeploy)
setattr(K, "undeploy_models", K.pipeline.undeploy_models)
setattr(K, "request", K.pipeline.request)
setattr(K, "set_runtime", K.pipeline.set_runtime)
setattr(K, "to_k8s_yaml", K.pipeline.to_k8s_yaml)
setattr(K, "save", K.pipeline.save)
setattr(K, "remote", K.pipeline.remote)
setattr(K, "upload", K.pipeline.upload)
setattr(K, "download", K.pipeline.download)
orig_init = K.__init__
# Make copy of original __init__, so we can call it without recursion
def __init__(self, *args, **kws):
K.pipeline.set_cls(self)
orig_init(self, *args, **kws) # Call the original __init__
K.__init__ = __init__ # Set the class' __init__ to the new one
return K
else:
return Pipeline(
name,
runtime=runtime,
local_folder=local_folder,
uri=uri,
models=models,
inputs=inputs,
outputs=outputs,
pipeline_func=f,
conda_env=conda_env,
)
def _pipeline(f):
if inspect.isclass(f):
K = f
func = None
for a in dir(K):
if (not a.startswith("__") and callable(getattr(K, a))
and hasattr(getattr(K, a), "predict")):
func = getattr(K, a)
break
K.pipeline = Pipeline(
name,
runtime=runtime,
models=models,
inputs=inputs,
outputs=outputs,
pipeline_func=func,
)
setattr(K, "deploy", K.pipeline.deploy)
setattr(K, "deploy_models", K.pipeline.deploy_models)
setattr(K, "undeploy", K.pipeline.undeploy)
setattr(K, "undeploy_models", K.pipeline.undeploy_models)
setattr(K, "request", K.pipeline.request)
orig_init = K.__init__
# Make copy of original __init__, so we can call it without recursion
def __init__(self, *args, **kws):
K.pipeline.set_cls(self)
orig_init(self, *args, **kws) # Call the original __init__
K.__init__ = __init__ # Set the class' __init__ to the new one
return K
else:
return Pipeline(
name,
runtime=runtime,
models=models,
inputs=inputs,
outputs=outputs,
pipeline_func=f,
)
def test_pipeline_k8s(k8s_inference_pipeline: Pipeline, x_input):
y_pred = k8s_inference_pipeline.remote(payload=x_input)
np.testing.assert_allclose(y_pred, [2.0], atol=1e-2)
def test_seldon_pipeline_request_docker(
inference_pipeline: Pipeline, x_input, expected
):
y_pred = inference_pipeline.request(x_input)
assert y_pred == expected
def test_pipeline_remote(inference_pipeline: Pipeline,
runtime: SeldonDockerRuntime, x_input):
y_pred = inference_pipeline.remote(payload=x_input)
np.testing.assert_allclose(y_pred, [2.0], atol=1e-2)
def pipeline_uri(inference_pipeline: Pipeline) -> str:
inference_pipeline.save(save_env=False)
return inference_pipeline.details.local_folder
def test_seldon_pipeline_request_docker(
inference_pipeline_deployed_with_runtime: Pipeline, x_input, expected):
y_pred = inference_pipeline_deployed_with_runtime.request(x_input)
assert y_pred == expected
async def load(self) -> bool:
pipeline_uri = await get_model_uri(self._settings)
self._pipeline = Pipeline.load(pipeline_uri)
self.ready = True
return self.ready
