def load(self, tags):
"""Creates an object from the MetaGraph identified by `tags`."""
meta_graph_def = self.get_meta_graph_def_from_tags(tags)
load_graph_returns = [None]
wrapped = wrap_function.wrap_function(
functools.partial(self.load_graph, load_graph_returns, meta_graph_def),
signature=[])
saver, = load_graph_returns
self.restore_variables(wrapped, saver)
with wrapped.graph.as_default():
init_op = loader_impl.get_init_op(meta_graph_def)
root = tracking.AutoTrackable()
if init_op is not None:
asset_feed_tensors = []
asset_paths = []
for tensor_name, value in loader_impl.get_asset_tensors(
self._export_dir, meta_graph_def).items():
asset_feed_tensors.append(wrapped.graph.as_graph_element(tensor_name))
asset_paths.append(tracking.TrackableAsset(value))
init_fn = wrapped.prune(
feeds=asset_feed_tensors,
fetches=[wrapped.graph.as_graph_element(init_op)])
initializer = _Initializer(init_fn, asset_paths)
initializer.initialize()
root.initializer = initializer
root.asset_paths = asset_paths
else:
root.asset_paths = []
signature_functions = self._extract_signatures(wrapped, meta_graph_def)
root.signatures = signature_serialization.create_signature_map(
signature_functions)
root.variables = list(wrapped.graph.variables)
return root
def load(self, tags):
"""Creates an object from the MetaGraph identified by `tags`."""
meta_graph_def = self.get_meta_graph_def_from_tags(tags)
for node in meta_graph_def.graph_def.node:
if node.op == "VariableV2":
raise NotImplementedError(
"Importing a SavedModel which contains RefVariables. This is not "
"currently supported. Running tf.enable_resource_variables() "
"before creating exported variables will fix this.")
load_graph_returns = [None]
wrapped = wrap_function.wrap_function(
functools.partial(self.load_graph, load_graph_returns, meta_graph_def),
signature=[])
saver, = load_graph_returns
self.restore_variables(wrapped, saver)
with wrapped.graph.as_default():
init_op = loader_impl.get_init_op(meta_graph_def)
if init_op is not None:
# TODO(allenl): Deal with assets
wrapped.prune(feeds=[],
fetches=[wrapped.graph.as_graph_element(init_op)])()
signature_functions = self._extract_signatures(wrapped, meta_graph_def)
root = tracking.AutoCheckpointable()
root.signatures = signature_serialization.create_signature_map(
signature_functions)
root.variables = list(wrapped.graph.variables)
return root
def load(self, tags):
"""Creates an object from the MetaGraph identified by `tags`."""
meta_graph_def = self.get_meta_graph_def_from_tags(tags)
load_graph_returns = [None]
wrapped = wrap_function.wrap_function(
functools.partial(self.load_graph, load_graph_returns, meta_graph_def),
signature=[])
saver, = load_graph_returns
self.restore_variables(wrapped, saver)
with wrapped.graph.as_default():
init_op = loader_impl.get_init_op(meta_graph_def)
root = tracking.AutoTrackable()
if init_op is not None:
asset_feed_tensors = []
asset_paths = []
for tensor_name, value in loader_impl.get_asset_tensors(
self._export_dir, meta_graph_def).items():
asset_feed_tensors.append(wrapped.graph.as_graph_element(tensor_name))
asset_paths.append(tracking.TrackableAsset(value))
init_fn = wrapped.prune(
feeds=asset_feed_tensors,
fetches=[wrapped.graph.as_graph_element(init_op)])
initializer = _Initializer(init_fn, asset_paths)
initializer._initialize() # pylint: disable=protected-access
root.initializer = initializer
root.asset_paths = asset_paths
else:
root.asset_paths = []
signature_functions = self._extract_signatures(wrapped, meta_graph_def)
root.signatures = signature_serialization.create_signature_map(
signature_functions)
root.variables = list(wrapped.graph.variables)
return root
def load(self, tags):
"""Creates an object from the MetaGraph identified by `tags`."""
meta_graph_def = self.get_meta_graph_def_from_tags(tags)
load_graph_returns = [None]
wrapped = wrap_function.wrap_function(functools.partial(
self.load_graph, load_graph_returns, meta_graph_def),
signature=[])
saver, = load_graph_returns
self.restore_variables(wrapped, saver)
with wrapped.graph.as_default():
init_op = loader_impl.get_init_op(
meta_graph_def
) or monitored_session.Scaffold.default_local_init_op()
# Add a dummy Tensor we know we can fetch to add control dependencies to.
init_anchor = constant_op.constant(0., name="dummy_fetch")
root = tracking.AutoTrackable()
asset_feed_tensors = []
asset_paths = []
for tensor_name, value in loader_impl.get_asset_tensors(
self._export_dir, meta_graph_def).items():
asset_feed_tensors.append(
wrapped.graph.as_graph_element(tensor_name))
asset_paths.append(tracking.TrackableAsset(value))
init_fn = wrapped.prune(
feeds=asset_feed_tensors,
fetches=[init_anchor,
wrapped.graph.as_graph_element(init_op)])
initializer = _Initializer(init_fn, asset_paths)
# pylint: disable=protected-access
local_init_op, _ = initializer._initialize()
# pylint: enable=protected-access
with ops.init_scope():
if not context.executing_eagerly():
ops.add_to_collection(ops.GraphKeys.TABLE_INITIALIZERS,
local_init_op)
for variable in wrapped.graph.get_collection_ref(
ops.GraphKeys.LOCAL_VARIABLES):
# pylint: disable=protected-access
variable._initializer_op = local_init_op
# pylint: enable=protected-access
root.initializer = initializer
root.asset_paths = asset_paths
signature_functions = self._extract_signatures(wrapped, meta_graph_def)
root.signatures = signature_serialization.create_signature_map(
signature_functions)
root.variables = list(wrapped.graph.variables)
root.tensorflow_version = (
meta_graph_def.meta_info_def.tensorflow_version)
root.tensorflow_git_version = (
meta_graph_def.meta_info_def.tensorflow_git_version)
root.graph = wrapped.graph
root.prune = wrapped.prune
return root
def load(self, tags):
"""Creates an object from the MetaGraph identified by `tags`."""
meta_graph_def = self.get_meta_graph_def_from_tags(tags)
load_graph_returns = [None]
wrapped = wrap_function.wrap_function(
functools.partial(self.load_graph, load_graph_returns, meta_graph_def),
signature=[])
saver, = load_graph_returns
self.restore_variables(wrapped, saver)
with wrapped.graph.as_default():
init_op = loader_impl.get_init_op(
meta_graph_def) or monitored_session.Scaffold.default_local_init_op()
# Add a dummy Tensor we know we can fetch to add control dependencies to.
init_anchor = constant_op.constant(0., name="dummy_fetch")
root = tracking.AutoTrackable()
asset_feed_tensors = []
asset_paths = []
for tensor_name, value in loader_impl.get_asset_tensors(
self._export_dir, meta_graph_def).items():
asset_feed_tensors.append(wrapped.graph.as_graph_element(tensor_name))
asset_paths.append(tracking.TrackableAsset(value))
init_fn = wrapped.prune(
feeds=asset_feed_tensors,
fetches=[init_anchor, wrapped.graph.as_graph_element(init_op)])
initializer = _Initializer(init_fn, asset_paths)
# pylint: disable=protected-access
local_init_op, _ = initializer._initialize()
# pylint: enable=protected-access
with ops.init_scope():
if not context.executing_eagerly():
ops.add_to_collection(ops.GraphKeys.TABLE_INITIALIZERS, local_init_op)
for variable in wrapped.graph.get_collection_ref(
ops.GraphKeys.LOCAL_VARIABLES):
# pylint: disable=protected-access
variable._initializer_op = local_init_op
# pylint: enable=protected-access
root.initializer = initializer
root.asset_paths = asset_paths
signature_functions = self._extract_signatures(wrapped, meta_graph_def)
root.signatures = signature_serialization.create_signature_map(
signature_functions)
root.variables = list(wrapped.graph.variables)
root.tensorflow_version = (
meta_graph_def.meta_info_def.tensorflow_version)
root.tensorflow_git_version = (
meta_graph_def.meta_info_def.tensorflow_git_version)
root.graph = wrapped.graph
root.prune = wrapped.prune
return root
def load(self, tags):
"""Creates an object from the MetaGraph identified by `tags`."""
meta_graph_def = self.get_meta_graph_def_from_tags(tags)
load_graph_returns = [None]
wrapped = wrap_function.wrap_function(functools.partial(
self.load_graph, load_graph_returns, meta_graph_def),
signature=[])
saver, = load_graph_returns
self.restore_variables(wrapped, saver)
with wrapped.graph.as_default():
init_op = loader_impl.get_init_op(meta_graph_def)
if init_op is not None:
# TODO(allenl): Deal with assets
wrapped.prune(feeds=[],
fetches=[wrapped.graph.as_graph_element(init_op)])()
signature_functions = self._extract_signatures(wrapped, meta_graph_def)
root = tracking.AutoCheckpointable()
root.signatures = signature_serialization.create_signature_map(
signature_functions)
root.variables = list(wrapped.graph.variables)
return root
def load(self, tags):
"""Creates an object from the MetaGraph identified by `tags`."""
meta_graph_def = self.get_meta_graph_def_from_tags(tags)
load_shared_name_suffix = "_load_{}".format(ops.uid())
functions = function_deserialization.load_function_def_library(
meta_graph_def.graph_def.library,
load_shared_name_suffix=load_shared_name_suffix)
# Replace existing functions in the MetaGraphDef with renamed functions so
# we don't have duplicates or name collisions.
meta_graph_def.graph_def.library.Clear()
for function in functions.values():
meta_graph_def.graph_def.library.function.add().CopyFrom(
function.function_def)
# We've renamed functions and shared names. We need the same operation on
# the GraphDef itself for consistency.
for node_def in meta_graph_def.graph_def.node:
function_deserialization.fix_node_def(
node_def,
functions,
load_shared_name_suffix,
debug_name="MetaGraph import")
load_graph_returns = [None]
wrapped = wrap_function.wrap_function(functools.partial(
self.load_graph, load_graph_returns, meta_graph_def),
signature=[])
saver, = load_graph_returns
self.restore_variables(wrapped, saver)
with wrapped.graph.as_default():
init_op = loader_impl.get_init_op(
meta_graph_def
) or monitored_session.Scaffold.default_local_init_op()
# Add a dummy Tensor we know we can fetch to add control dependencies to.
init_anchor = constant_op.constant(0., name="dummy_fetch")
root = tracking.AutoTrackable()
asset_feed_tensors = []
asset_paths = []
for tensor_name, value in loader_impl.get_asset_tensors(
self._export_dir, meta_graph_def).items():
asset_feed_tensors.append(
wrapped.graph.as_graph_element(tensor_name))
asset_paths.append(tracking.Asset(value))
init_fn = wrapped.prune(
feeds=asset_feed_tensors,
fetches=[init_anchor,
wrapped.graph.as_graph_element(init_op)])
initializer = _Initializer(init_fn, asset_paths)
# pylint: disable=protected-access
local_init_op, _ = initializer._initialize()
# pylint: enable=protected-access
with ops.init_scope():
if not context.executing_eagerly():
ops.add_to_collection(ops.GraphKeys.TABLE_INITIALIZERS,
local_init_op)
for variable in wrapped.graph.get_collection_ref(
ops.GraphKeys.LOCAL_VARIABLES):
# pylint: disable=protected-access
variable._initializer_op = local_init_op
# pylint: enable=protected-access
root.initializer = initializer
root.asset_paths = asset_paths
signature_functions = self._extract_signatures(wrapped, meta_graph_def)
root.signatures = signature_serialization.create_signature_map(
signature_functions)
root.variables = list(wrapped.graph.variables)
root.tensorflow_version = (
meta_graph_def.meta_info_def.tensorflow_version)
root.tensorflow_git_version = (
meta_graph_def.meta_info_def.tensorflow_git_version)
root.graph = wrapped.graph
root.prune = wrapped.prune
return root
