def _PrepareModelPath(
self, model_uri: Text,
serving_spec: infra_validator_pb2.ServingSpec) -> Text:
model_path = path_utils.serving_model_path(model_uri)
serving_binary = serving_spec.WhichOneof('serving_binary')
if serving_binary == 'tensorflow_serving':
# TensorFlow Serving requires model to be stored in its own directory
# structure flavor. If current model_path does not conform to the flavor,
# we need to make a copy to the temporary path.
try:
# Check whether current model_path conforms to the tensorflow serving
# model path flavor. (Parsed without exception)
tf_serving_flavor.parse_model_path(
model_path, expected_model_name=serving_spec.model_name)
except ValueError:
# Copy the model to comply with the tensorflow serving model path
# flavor.
temp_model_path = tf_serving_flavor.make_model_path(
model_base_path=self._get_tmp_dir(),
model_name=serving_spec.model_name,
version=int(time.time()))
io_utils.copy_dir(src=model_path, dst=temp_model_path)
return temp_model_path
return model_path
def _PrepareModelPath(
self, model: types.Artifact,
serving_spec: infra_validator_pb2.ServingSpec) -> str:
model_path = path_utils.serving_model_path(
model.uri, path_utils.is_old_model_artifact(model))
serving_binary = serving_spec.WhichOneof('serving_binary')
if serving_binary == _TENSORFLOW_SERVING:
# TensorFlow Serving requires model to be stored in its own directory
# structure flavor. If current model_path does not conform to the flavor,
# we need to make a copy to the temporary path.
try:
# Check whether current model_path conforms to the tensorflow serving
# model path flavor. (Parsed without exception)
tf_serving_flavor.parse_model_path(
model_path, expected_model_name=serving_spec.model_name)
except ValueError:
# Copy the model to comply with the tensorflow serving model path
# flavor.
temp_model_path = tf_serving_flavor.make_model_path(
model_base_path=self._get_tmp_dir(),
model_name=serving_spec.model_name,
version=int(time.time()))
io_utils.copy_dir(src=model_path, dst=temp_model_path)
self._AddCleanup(io_utils.delete_dir,
self._context.get_tmp_path())
return temp_model_path
return model_path
def testRoundTrip(self):
self.assertEqual(
tfs_flavor.parse_model_path(
tfs_flavor.make_model_path('/foo/bar', 'my-model', 123)),
('/foo/bar', 'my-model', 123))
self.assertEqual(
tfs_flavor.make_model_path(
*tfs_flavor.parse_model_path('/foo/bar/my-model/123')),
'/foo/bar/my-model/123')
def testParseModelPath(self):
self.assertEqual(
tfs_flavor.parse_model_path('/foo/bar/my-model/123',),
('/foo/bar', 'my-model', 123))
self.assertEqual(
tfs_flavor.parse_model_path('s3://bucket-name/foo/bar/my-model/123'),
('s3://bucket-name/foo/bar', 'my-model', 123))
self.assertEqual(
tfs_flavor.parse_model_path('gs://bucket-name/foo/bar/my-model/123'),
('gs://bucket-name/foo/bar', 'my-model', 123))
def testParseModelPath_Fail(self):
with self.assertRaises(ValueError):
tfs_flavor.parse_model_path('too-short')
with self.assertRaises(ValueError):
tfs_flavor.parse_model_path('/foo/bar/my-model/not-an-int-version')
with self.assertRaises(ValueError):
tfs_flavor.parse_model_path('/foo/bar/other-model/123',
expected_model_name='my-model')