from tensorflow.python.saved_model import loader_impl
from tensorflow.python.saved_model import nested_structure_coder
from tensorflow.python.saved_model import revived_types
from tensorflow.python.training.tracking import base as trackable
from tensorflow.python.training.tracking import data_structures
from tensorflow.python.training.tracking.tracking import delete_tracking
from tensorflow.python.util import compat
from tensorflow.python.util import nest
# To avoid circular dependencies between keras/engine and keras/saving,
# code in keras/saving must delay imports.
# TODO(b/134426265): Switch back to single-quotes to match the rest of the file
# once the issue with copybara is fixed.
# pylint:disable=g-inconsistent-quotes
models_lib = LazyLoader("models_lib", globals(),
"tensorflow.python.keras.models")
base_layer = LazyLoader(
"base_layer", globals(),
"tensorflow.python.keras.engine.base_layer")
layers_module = LazyLoader(
"layers_module", globals(),
"tensorflow.python.keras.layers")
input_layer = LazyLoader(
"input_layer", globals(),
"tensorflow.python.keras.engine.input_layer")
functional_lib = LazyLoader(
"functional_lib", globals(),
"tensorflow.python.keras.engine.functional")
training_lib = LazyLoader(
"training_lib", globals(),
"tensorflow.python.keras.engine.training")
from tensorflow.python.keras.utils.io_utils import ask_to_proceed_with_overwrite
from tensorflow.python.ops import variables as variables_module
from tensorflow.python.platform import tf_logging as logging
# pylint: disable=g-import-not-at-top
try:
import h5py
HDF5_OBJECT_HEADER_LIMIT = 64512
except ImportError:
h5py = None
# pylint: enable=g-import-not-at-top
# TODO(b/134426265): Switch back to single-quotes to match the rest of the file
# once the issue with copybara is fixed.
# pylint:disable=g-inconsistent-quotes
sequential_lib = LazyLoader("sequential_lib", globals(),
"tensorflow.python.keras.engine.sequential")
# pylint:enable=g-inconsistent-quotes
def save_model_to_hdf5(model,
filepath,
overwrite=True,
include_optimizer=True):
"""Saves a model to a HDF5 file.
The saved model contains:
- the model's configuration (topology)
- the model's weights
- the model's optimizer's state (if any)
Thus the saved model can be reinstantiated in
from __future__ import print_function
import itertools
import types
from tensorflow.python.eager import context
from tensorflow.python.keras import backend as K
from tensorflow.python.keras.engine import base_layer_utils
from tensorflow.python.keras.utils import control_flow_util
from tensorflow.python.keras.utils import layer_utils
from tensorflow.python.keras.utils import tf_inspect
from tensorflow.python.keras.utils.generic_utils import LazyLoader
from tensorflow.python.util import tf_decorator
# pylint:disable=g-inconsistent-quotes
training_lib = LazyLoader("training_lib", globals(),
"tensorflow.python.keras.engine.training")
# pylint:enable=g-inconsistent-quotes
def use_wrapped_call(layer,
call_fn,
default_training_value=None,
return_method=False):
"""Creates fn that adds the losses returned by call_fn & returns the outputs.
Args:
layer: A Keras layer object
call_fn: tf.function that takes layer inputs (and possibly a training arg),
and returns a tuple of (outputs, list of losses).
default_training_value: Default value of the training kwarg. If `None`, the
default is `K.learning_phase()`.
from tensorflow.python.saved_model import constants
from tensorflow.python.saved_model import save as save_lib
from tensorflow.python.saved_model import utils_impl as saved_model_utils
from tensorflow.python.training import saver as saver_lib
from tensorflow.python.training.tracking import graph_view
from tensorflow.python.util import compat
from tensorflow.python.util import nest
from tensorflow.python.util.tf_export import keras_export
# To avoid circular dependencies between keras/engine and keras/saving,
# code in keras/saving must delay imports.
# TODO(b/134426265): Switch back to single-quotes to match the rest of the file
# once the issue with copybara is fixed.
# pylint:disable=g-inconsistent-quotes
metrics_lib = LazyLoader("metrics_lib", globals(),
"tensorflow.python.keras.metrics")
models_lib = LazyLoader("models_lib", globals(),
"tensorflow.python.keras.models")
sequential = LazyLoader(
"sequential", globals(),
"tensorflow.python.keras.engine.sequential")
# pylint:enable=g-inconsistent-quotes
@keras_export(v1=['keras.experimental.export_saved_model'])
def export_saved_model(model,
saved_model_path,
custom_objects=None,
as_text=False,
input_signature=None,
serving_only=False):
from tensorflow.python.keras.utils import tf_inspect
from tensorflow.python.keras.utils import version_utils
from tensorflow.python.keras.utils.generic_utils import LazyLoader
from tensorflow.python.platform import tf_logging as logging
from tensorflow.python.training.tracking import base as trackable
from tensorflow.python.training.tracking import data_structures
from tensorflow.python.util import nest
from tensorflow.python.util import tf_decorator
# To avoid circular dependencies between keras/engine and keras/saving,
# code in keras/saving must delay imports.
# TODO(b/134426265): Switch back to single-quotes to match the rest of the file
# once the issue with copybara is fixed.
# pylint:disable=g-inconsistent-quotes
base_layer = LazyLoader("base_layer", globals(),
"tensorflow.python.keras.engine.base_layer")
metrics = LazyLoader("metrics", globals(), "tensorflow.python.keras.metrics")
input_layer = LazyLoader("input_layer", globals(),
"tensorflow.python.keras.engine.input_layer")
training_lib = LazyLoader("training_lib", globals(),
"tensorflow.python.keras.engine.training")
sequential_lib = LazyLoader("sequential_lib", globals(),
"tensorflow.python.keras.engine.sequential")
# pylint:enable=g-inconsistent-quotes
def should_skip_serialization(layer):
"""Skip serializing extra objects and functions if layer inputs aren't set."""
saved_model_input_spec_set = (
isinstance(layer, training_lib.Model)
and layer._saved_model_inputs_spec is not None) # pylint: disable=protected-access
from tensorflow.core.framework import versions_pb2
from tensorflow.python.keras import backend as K
from tensorflow.python.keras.protobuf import saved_metadata_pb2
from tensorflow.python.keras.saving import saving_utils
from tensorflow.python.keras.saving.saved_model import constants
from tensorflow.python.keras.saving.saved_model import save_impl
from tensorflow.python.keras.saving.saved_model import utils
from tensorflow.python.keras.utils.generic_utils import LazyLoader
from tensorflow.python.keras.utils.io_utils import ask_to_proceed_with_overwrite
from tensorflow.python.platform import gfile
from tensorflow.python.saved_model import save as save_lib
# To avoid circular dependencies between keras/engine and keras/saving,
# code in keras/saving must delay imports.
base_layer = LazyLoader("base_layer", globals(),
"tensorflow.python.keras.engine.base_layer")
training_lib = LazyLoader("training_lib", globals(),
"tensorflow.python.keras.engine.training")
def save(model,
filepath,
overwrite,
include_optimizer,
signatures=None,
options=None,
save_traces=True):
"""Saves a model as a SavedModel to the filepath.
Args:
model: Keras model instance to be saved.
# limitations under the License.
# ==============================================================================
# pylint: disable=protected-access
"""Utilities for Keras classes with v1 and v2 versions."""
from __future__ import absolute_import
from __future__ import division
from __future__ import print_function
from tensorflow.python.eager import context
from tensorflow.python.framework import ops
from tensorflow.python.keras.utils.generic_utils import LazyLoader
# TODO(b/134426265): Switch back to single-quotes once the issue
# with copybara is fixed.
# pylint: disable=g-inconsistent-quotes
training = LazyLoader("training", globals(),
"tensorflow.python.keras.engine.training")
training_v1 = LazyLoader("training_v1", globals(),
"tensorflow.python.keras.engine.training_v1")
base_layer = LazyLoader("base_layer", globals(),
"tensorflow.python.keras.engine.base_layer")
base_layer_v1 = LazyLoader("base_layer_v1", globals(),
"tensorflow.python.keras.engine.base_layer_v1")
callbacks = LazyLoader("callbacks", globals(),
"tensorflow.python.keras.callbacks")
callbacks_v1 = LazyLoader("callbacks_v1", globals(),
"tensorflow.python.keras.callbacks_v1")
# pylint: enable=g-inconsistent-quotes
class ModelVersionSelector(object):
"""
from __future__ import absolute_import
from __future__ import division
from __future__ import print_function
from tensorflow.python.eager import def_function
from tensorflow.python.keras.saving.saved_model import constants
from tensorflow.python.keras.utils.generic_utils import LazyLoader
from tensorflow.python.training.tracking import base as trackable
from tensorflow.python.training.tracking.tracking import AutoTrackable
# TODO(b/134426265): Switch back to single-quotes to match the rest of the file
# once the issue with copybara is fixed.
# pylint:disable=g-inconsistent-quotes
base_layer = LazyLoader(
"base_layer", globals(),
"tensorflow.python.keras.engine.base_layer")
training_lib = LazyLoader(
"training_lib", globals(),
"tensorflow.python.keras.engine.training")
metrics = LazyLoader("metrics", globals(),
"tensorflow.python.keras.metrics")
recurrent = LazyLoader(
"recurrent", globals(),
"tensorflow.python.keras.layers.recurrent")
# pylint:enable=g-inconsistent-quotes
class SerializedAttributes(object):
"""Class that tracks and validates all serialization attributes.
