def upload(
self,
bento_service: "BentoService",
version: str = None,
labels: Dict = None,
) -> "BentoUri":
"""
Save and upload given :class:`~bentoml.BentoService`
to YataiService.
Args:
bento_service (:class:`~bentoml.BentoService`):
a BentoService instance
version (`str`, `optional`):
version of ``bento_service``
labels (`dict`, `optional`):
:class:`~bentoml.BentoService` metadata
Returns:
BentoUri as gRPC stub for save location of BentoService.
Example::
from bentoml.yatai.client import get_yatai_client
svc = MyBentoService()
svc.save()
remote_yatai_client = get_yatai_client('https://remote.yatai.service:50050')
remote_path = remote_yatai_client.repository.upload(svc)
"""
with TempDirectory() as tmpdir:
save_to_dir(bento_service, tmpdir, version, silent=True)
return self.upload_from_dir(tmpdir, labels)
def upload(self, bento_service, version=None, labels=None):
"""Save and upload given bento_service to yatai_service, which manages all your
saved BentoService bundles and model serving deployments.
Args:
bento_service (bentoml.service.BentoService): a Bento Service instance
version (str): optional,
Return:
URI to where the BentoService is being saved to
"""
with TempDirectory() as tmpdir:
save_to_dir(bento_service, tmpdir, version, silent=True)
return self.upload_from_dir(tmpdir, labels)
def save_to_dir(self, path, version=None):
"""Save this BentoService along with all its artifacts, source code and
dependencies to target file path, assuming path exist and empty. If target path
is not empty, this call may override existing files in the given path.
:param path (str): Destination of where the bento service will be saved
:param version: optional - save with version override
"""
return save_to_dir(self, path, version)
def gen_test_bundle(tmpdir):
# When the ExampleBentoService got saved and loaded again in the test, the two class
# attribute below got set to the loaded BentoService class. Resetting it here so it
# does not effect other tests
ExampleBentoService._bento_service_bundle_path = None
ExampleBentoService._bento_service_bundle_version = None
test_svc = ExampleBentoService()
pickle_model = PickleModel()
test_svc.pack('model', pickle_model)
sklearn_model = RandomForestRegressor(n_estimators=2)
sklearn_model.fit(
[[i] for _ in range(100) for i in range(10)],
[i for _ in range(100) for i in range(10)],
)
test_svc.pack('sk_model', sklearn_model)
save_to_dir(test_svc, tmpdir, silent=True)
return tmpdir
return [input_data.shape for input_data in input_datas]
def predict_legacy_images(self, original, compared):
return (original == compared).all()
def predict_json(self, input_datas):
assert input_datas is not None
return input_datas
if __name__ == "__main__":
# When the ExampleBentoService got saved and loaded again in the test, the two class
# attribute below got set to the loaded BentoService class. Resetting it here so it
# does not effect other tests
ExampleBentoService._bento_service_bundle_path = None
ExampleBentoService._bento_service_bundle_version = None
test_svc = ExampleBentoService()
pickle_model = PickleModel()
test_svc.pack('model', pickle_model)
sklearn_model = RandomForestRegressor(n_estimators=2)
sklearn_model.fit(
[[i] for _ in range(100) for i in range(10)],
[i for _ in range(100) for i in range(10)],
)
test_svc.pack('sk_model', sklearn_model)
tmpdir = sys.argv[1]
save_to_dir(test_svc, tmpdir, silent=True)
