def testMaybeSessionBundleDir(self):
base_path = test.test_src_dir_path(SESSION_BUNDLE_PATH)
self.assertTrue(session_bundle.maybe_session_bundle_dir(base_path))
base_path = test.test_src_dir_path(SAVED_MODEL_PATH)
self.assertFalse(session_bundle.maybe_session_bundle_dir(base_path))
base_path = "complete_garbage"
self.assertFalse(session_bundle.maybe_session_bundle_dir(base_path))
def testMaybeSessionBundleDir(self):
base_path = tf.test.test_src_dir_path(SESSION_BUNDLE_PATH)
self.assertTrue(session_bundle.maybe_session_bundle_dir(base_path))
base_path = tf.test.test_src_dir_path(SAVED_MODEL_PATH)
self.assertFalse(session_bundle.maybe_session_bundle_dir(base_path))
base_path = "complete_garbage"
self.assertFalse(session_bundle.maybe_session_bundle_dir(base_path))
def load_session_bundle_or_saved_model_bundle_from_path(export_dir,
tags=None,
target="",
config=None):
"""Load session bundle from the given path.
The function reads input from the export_dir, constructs the graph data to the
default graph and restores the parameters for the session created.
Args:
export_dir: the directory that contains files exported by exporter.
tags: Set of string tags to identify the required MetaGraphDef when model is
saved as SavedModel. These should correspond to the tags used when
saving the variables using the SavedModel `save()` API.
target: The execution engine to connect to. See target in tf.Session()
config: A ConfigProto proto with configuration options. See config in
tf.Session()
Returns:
session: a tensorflow session created from the variable files.
meta_graph: a meta graph proto saved in the exporter directory.
Raises:
RuntimeError: if the required files are missing or contain unrecognizable
fields, i.e. the exported model is invalid.
"""
metagraph_def = None
sess = None
if loader.maybe_saved_model_directory(export_dir):
sess = session.Session(target, graph=None, config=config)
metagraph_def = loader.load(sess, tags, export_dir)
elif session_bundle.maybe_session_bundle_dir(export_dir):
sess, metagraph_def = _load_saved_model_from_session_bundle_path(export_dir,
target,
config)
else:
raise RuntimeError("SessionBundle or SavedModelBundle not found at "
"specified export location: %s" % export_dir)
return sess, metagraph_def
def load_session_bundle_or_saved_model_bundle_from_path(export_dir,
tags=None,
target="",
config=None):
"""Load session bundle from the given path.
The function reads input from the export_dir, constructs the graph data to the
default graph and restores the parameters for the session created.
Args:
export_dir: the directory that contains files exported by exporter.
tags: Set of string tags to identify the required MetaGraphDef when model is
saved as SavedModel. These should correspond to the tags used when
saving the variables using the SavedModel `save()` API.
target: The execution engine to connect to. See target in tf.Session()
config: A ConfigProto proto with configuration options. See config in
tf.Session()
Returns:
session: a tensorflow session created from the variable files.
meta_graph: a meta graph proto saved in the exporter directory.
Raises:
RuntimeError: if the required files are missing or contain unrecognizable
fields, i.e. the exported model is invalid.
"""
metagraph_def = None
sess = None
if loader.maybe_saved_model_directory(export_dir):
sess = session.Session(target, graph=None, config=config)
metagraph_def = loader.load(sess, tags, export_dir)
elif session_bundle.maybe_session_bundle_dir(export_dir):
sess, metagraph_def = _load_saved_model_from_session_bundle_path(export_dir,
target,
config)
else:
raise RuntimeError("SessionBundle or SavedModelBundle not found at "
"specified export location: %s" % export_dir)
return sess, metagraph_def
