Support TF Modules inside Keras Layers and Models.
With this change, it is now possible to mix-and-match tf.keras.Layers and
tf.Modules inside a tf.keras.Model and everything will be tracked properly.
- Variables in tf.Modules that are set as attributes of custom Layers and
Models now show up properly in properties such as Layer.trainable_variables
and Model.trainable_variables.
- tf.Modules do not show up in Model.layers. Instead, a new method
Layer._flatten_modules is added that iterates over tf.Modules and Layers in
the order that Keras expects. The existing method Layer.submodules (inherited
from tf.Module) can still be used to iterate over tf.Modules and Layer with the
tf.Module ordering. Layer._flatten_layers is built on top of
Layer._flatten_modules
- Layer._layers is renamed to Layer._self_tracked_trackables to avoid naming
conflicts with user-defined attributes (and to reflect that this attr
contains Layers, Modules, and TrackableDataStructures)
- A new property is added to tf.Module to enable this, namely
tf.Module.non_trainable_variables
PiperOrigin-RevId: 339917644
Change-Id: I96a7302745280a6261de8c4295c5cbf5f4d7dd5c
diff --git a/RELEASE.md b/RELEASE.md
index af3acb1..962cc87 100644
--- a/RELEASE.md
+++ b/RELEASE.md
@@ -386,10 +386,14 @@
True, the function may use type annotations to optimize the tracing
performance.
* Added support for `iter(DistributedDataset)` in AutoGraph `for` loops.
- * AutoGraph now allows creating new symbols inside a TensorFLow loop, if
+ * AutoGraph now allows creating new symbols inside a TensorFlow loop, if
the values of these symbols at an iteration does not depend on the
previous iteration. These types of loops must run at least one
iteration, and will raise a runtime error otherwise.
+ * Variables contained in `tf.Module`s that are set as attributes of
+ custom Keras `Layer`s and `Model`s are now tracked in
+ the properties `layer.trainable_variables` and
+ `layer.non_trainable_variables`.
Example:
diff --git a/tensorflow/python/keras/engine/base_layer.py b/tensorflow/python/keras/engine/base_layer.py
index a18e419..a2fcba1 100644
--- a/tensorflow/python/keras/engine/base_layer.py
+++ b/tensorflow/python/keras/engine/base_layer.py
@@ -397,10 +397,10 @@
self._autocast = kwargs.get('autocast',
base_layer_utils.v2_dtype_behavior_enabled())
- # Dependencies tracked via attribute assignment.
- # All layers in order of horizontal graph traversal.
- # Entries are unique. For models includes input and output layers.
- self._maybe_create_attribute('_layers', [])
+ # Tracks `TrackableDataStructure`s, `Module`s, and `Layer`s.
+ # Ordered by when the object was assigned as an attr.
+ # Entries are unique.
+ self._maybe_create_attribute('_self_tracked_trackables', [])
# These lists will be filled via successive calls
# to self._add_inbound_node().
@@ -1351,14 +1351,11 @@
Trainable weights are updated via gradient descent during training.
- Note: This will not track the weights of nested `tf.Modules` that are not
- themselves Keras layers.
-
Returns:
A list of trainable variables.
"""
if self.trainable:
- children_weights = self._gather_children_attribute('trainable_weights')
+ children_weights = self._gather_children_attribute('trainable_variables')
return self._dedup_weights(self._trainable_weights + children_weights)
else:
return []
@@ -1370,18 +1367,15 @@
Non-trainable weights are *not* updated during training. They are expected
to be updated manually in `call()`.
- Note: This will not track the weights of nested `tf.Modules` that are not
- themselves Keras layers.
-
Returns:
A list of non-trainable variables.
"""
if self.trainable:
children_weights = self._gather_children_attribute(
- 'non_trainable_weights')
+ 'non_trainable_variables')
non_trainable_weights = self._non_trainable_weights + children_weights
else:
- children_weights = self._gather_children_attribute('weights')
+ children_weights = self._gather_children_attribute('variables')
non_trainable_weights = (
self._trainable_weights + self._non_trainable_weights +
children_weights)
@@ -1391,9 +1385,6 @@
def weights(self):
"""Returns the list of all layer variables/weights.
- Note: This will not track the weights of nested `tf.Modules` that are not
- themselves Keras layers.
-
Returns:
A list of variables.
"""
@@ -1609,7 +1600,8 @@
def _clear_losses(self):
"""Used every step in eager to reset losses."""
# Set to thread local directly to avoid Layer.__setattr__ overhead.
- if not getattr(self, '_layers', None): # Fast path for single Layer.
+ if not getattr(self, '_self_tracked_trackables',
+ None): # Fast path for single Layer.
self._thread_local._eager_losses = []
else:
for layer in self._flatten_layers():
@@ -2779,7 +2771,7 @@
default_value: Object, the default value of the attribute.
"""
if not hasattr(self, name):
- super(Layer, self).__setattr__(name, default_value)
+ self.__setattr__(name, default_value)
def __delattr__(self, name):
# For any super.__delattr__() call, we will directly use the implementation
@@ -2813,8 +2805,8 @@
if (isinstance(existing_value, Layer)
or base_layer_utils.has_weights(existing_value)):
super(tracking.AutoTrackable, self).__setattr__(
- '_layers',
- [l for l in self._layers if l is not existing_value])
+ '_self_tracked_trackables',
+ [l for l in self._self_tracked_trackables if l is not existing_value])
if isinstance(existing_value, tf_variables.Variable):
super(tracking.AutoTrackable, self).__setattr__(
'_trainable_weights',
@@ -2837,7 +2829,7 @@
'different name.').format(name))
return
- # Keep track of trackable objects, for the needs of `Network.save_weights`.
+ # Wraps data structures in `Trackable`, unwraps `NoDependency` objects.
value = data_structures.sticky_attribute_assignment(
trackable=self, value=value, name=name)
@@ -2856,16 +2848,15 @@
if isinstance(val, metrics_mod.Metric) and hasattr(self, '_metrics'):
self._metrics.append(val)
- # TODO(scottzhu): Need to track Module object as well for weight tracking.
- # Be careful about metric if it becomes a Module in future.
- # Append value to self._layers if relevant
+ # Append value to self._self_tracked_trackables if relevant
if (getattr(self, '_auto_track_sub_layers', True) and
- (isinstance(value, Layer) or base_layer_utils.has_weights(value))):
- self._maybe_create_attribute('_layers', [])
+ (isinstance(value, module.Module) or
+ base_layer_utils.has_weights(value))):
+ self._maybe_create_attribute('_self_tracked_trackables', [])
# We need to check object identity to avoid de-duplicating empty
# container types which compare equal.
- if not any((layer is value for layer in self._layers)):
- self._layers.append(value)
+ if not any((layer is value for layer in self._self_tracked_trackables)):
+ self._self_tracked_trackables.append(value)
if hasattr(value, '_use_resource_variables'):
# Legacy layers (V1 tf.layers) must always use
# resource variables.
@@ -2903,45 +2894,59 @@
def _gather_children_attribute(self, attribute):
assert attribute in {
- 'weights', 'trainable_weights', 'non_trainable_weights'
+ 'variables', 'trainable_variables', 'non_trainable_variables'
}
- if hasattr(self, '_layers'):
- nested_layers = layer_utils.filter_empty_layer_containers(
- self._layers)
+ if hasattr(self, '_self_tracked_trackables'):
+ nested_layers = self._flatten_modules(include_self=False, recursive=False)
return list(
itertools.chain.from_iterable(
getattr(layer, attribute) for layer in nested_layers))
return []
def _flatten_layers(self, recursive=True, include_self=True):
+ for m in self._flatten_modules(
+ recursive=recursive, include_self=include_self):
+ if isinstance(m, Layer):
+ yield m
+
+ def _flatten_modules(self, recursive=True, include_self=True):
+ """Flattens `tf.Module` instances (excluding `Metrics`).
+
+ Arguments:
+ recursive: Whether to recursively flatten through submodules.
+ include_self: Whether to include this `Layer` instance.
+
+ Yields:
+ `tf.Module` instance tracked by this `Layer`.
+ """
if include_self:
yield self
# Only instantiate set and deque if needed.
- layers_or_containers = getattr(self, '_layers', None)
- if layers_or_containers:
+ trackables = getattr(self, '_self_tracked_trackables', None)
+ if trackables:
seen_object_ids = set()
- deque = collections.deque(layers_or_containers)
+ deque = collections.deque(trackables)
while deque:
- layer_or_container = deque.popleft()
-
- layer_or_container_id = id(layer_or_container)
- if layer_or_container_id in seen_object_ids:
+ trackable_obj = deque.popleft()
+ trackable_id = id(trackable_obj)
+ if trackable_id in seen_object_ids:
continue
- seen_object_ids.add(layer_or_container_id)
+ seen_object_ids.add(trackable_id)
- if (isinstance(layer_or_container, Layer) and
- not isinstance(layer_or_container, metrics_mod.Metric)):
- yield layer_or_container
+ # Metrics are not considered part of the Layer's topology.
+ if (isinstance(trackable_obj, module.Module) and
+ not isinstance(trackable_obj, metrics_mod.Metric)):
+ yield trackable_obj
# Introspect recursively through sublayers.
if recursive:
- sublayers = getattr(layer_or_container, '_layers', None)
- if sublayers:
- deque.extendleft(reversed(sublayers))
- elif isinstance(layer_or_container,
- data_structures.TrackableDataStructure):
+ subtrackables = getattr(trackable_obj, '_self_tracked_trackables',
+ None)
+ if subtrackables:
+ deque.extendleft(reversed(subtrackables))
+ elif isinstance(trackable_obj, data_structures.TrackableDataStructure):
# Data structures are introspected even with `recursive=False`.
- tracked_values = layer_or_container._values
+ tracked_values = trackable_obj._values
if tracked_values:
deque.extendleft(reversed(tracked_values))
diff --git a/tensorflow/python/keras/engine/base_layer_test.py b/tensorflow/python/keras/engine/base_layer_test.py
index dad73cb..f422e79 100644
--- a/tensorflow/python/keras/engine/base_layer_test.py
+++ b/tensorflow/python/keras/engine/base_layer_test.py
@@ -48,6 +48,7 @@
from tensorflow.python.keras.legacy_tf_layers import core as legacy_core
from tensorflow.python.keras.optimizer_v2 import rmsprop
from tensorflow.python.keras.utils import control_flow_util
+from tensorflow.python.module import module
from tensorflow.python.ops import array_ops
from tensorflow.python.ops import math_ops
from tensorflow.python.ops import state_ops
@@ -840,6 +841,58 @@
layer = MyLayer(activity_regularizer='l2')
self.assertIsInstance(layer.activity_regularizer, regularizers.L2)
+ def test_tf_module_tracking(self):
+
+ class MyModule(module.Module):
+
+ def __init__(self):
+ super(MyModule, self).__init__()
+ self.v1 = variables.Variable(1., trainable=True, name='v1')
+ self.v2 = variables.Variable(2., trainable=False, name='v2')
+
+ def __call__(self, x):
+ return x * self.v1 * self.v2
+
+ class MyLayer(base_layer.Layer):
+
+ def __init__(self, **kwargs):
+ super(MyLayer, self).__init__(self, **kwargs)
+ self.my_modules = {}
+ self.my_modules['a'] = MyModule()
+
+ def call(self, x):
+ return self.my_modules['a'](x)
+
+ layer = MyLayer()
+ self.assertLen(layer.variables, 2)
+ self.assertLen(layer.trainable_variables, 1)
+ self.assertLen(layer.non_trainable_variables, 1)
+
+ layer.trainable = False
+ self.assertLen(layer.variables, 2)
+ self.assertLen(layer.trainable_variables, 0)
+ self.assertLen(layer.non_trainable_variables, 2)
+
+ class MyModel(training_lib.Model):
+
+ def __init__(self):
+ super(MyModel, self).__init__()
+ self.my_modules = []
+ self.my_modules.append(MyModule())
+
+ def call(self, x):
+ return self.my_modules[0](x)
+
+ model = MyModel()
+ self.assertLen(model.variables, 2)
+ self.assertLen(model.trainable_variables, 1)
+ self.assertLen(model.non_trainable_variables, 1)
+
+ model.trainable = False
+ self.assertLen(model.variables, 2)
+ self.assertLen(model.trainable_variables, 0)
+ self.assertLen(model.non_trainable_variables, 2)
+
class SymbolicSupportTest(keras_parameterized.TestCase):
@@ -1078,12 +1131,13 @@
del l.c
l.d = last_assignment
del l.d
- self.assertEqual([last_assignment], l._layers)
+ sublayers = list(l._flatten_layers(include_self=False, recursive=False))
+ self.assertEqual([last_assignment], sublayers)
self.assertEqual([], l.trainable_weights)
self.assertEqual([], l.non_trainable_weights)
self.assertEqual([], l.weights)
del l.a
- self.assertEqual([], l._layers)
+ self.assertEqual([], l._self_tracked_trackables)
def test_assign_op_not_tracked_as_variable(self):
diff --git a/tensorflow/python/keras/engine/base_layer_v1.py b/tensorflow/python/keras/engine/base_layer_v1.py
index f5eece4..f7a6367 100644
--- a/tensorflow/python/keras/engine/base_layer_v1.py
+++ b/tensorflow/python/keras/engine/base_layer_v1.py
@@ -212,7 +212,7 @@
# Dependencies tracked via attribute assignment.
# All layers in order of horizontal graph traversal.
# Entries are unique. For models includes input and output layers.
- self._maybe_create_attribute('_layers', [])
+ self._maybe_create_attribute('_self_tracked_trackables', [])
# These lists will be filled via successive calls
# to self._add_inbound_node().
@@ -881,7 +881,7 @@
@trainable.setter
def trainable(self, value):
self._trainable = value
- for layer in getattr(self, '_layers', []):
+ for layer in getattr(self, '_self_tracked_trackables', []):
layer.trainable = value
@property
@@ -910,36 +910,6 @@
self._input_spec = value
@property
- def trainable_weights(self):
- if self.trainable:
- children_weights = self._gather_children_attribute('trainable_weights')
- return self._dedup_weights(self._trainable_weights + children_weights)
- else:
- return []
-
- @property
- def non_trainable_weights(self):
- if self.trainable:
- children_weights = self._gather_children_attribute(
- 'non_trainable_weights')
- non_trainable_weights = self._non_trainable_weights + children_weights
- else:
- children_weights = self._gather_children_attribute('weights')
- non_trainable_weights = (
- self._trainable_weights + self._non_trainable_weights +
- children_weights)
- return self._dedup_weights(non_trainable_weights)
-
- @property
- def weights(self):
- """Returns the list of all layer variables/weights.
-
- Returns:
- A list of variables.
- """
- return self.trainable_weights + self.non_trainable_weights
-
- @property
def updates(self):
collected_updates = []
all_layers = self._flatten_layers()
@@ -2137,21 +2107,20 @@
Returns:
A dict mapping all sublayers to their `trainable` value.
"""
- layers = layer_utils.filter_empty_layer_containers(self._layers)
- # Keep track of each top-level layers' `trainable` as well as the
- # state of all of its sublayers.
+ layers = self._flatten_layers(include_self=False, recursive=False)
trainable_state = {self: self.trainable}
- for layer in layers:
- trainable_state.update(layer._get_trainable_state())
+ for l in layers:
+ trainable_state.update(l._get_trainable_state())
return trainable_state
def _set_trainable_state(self, trainable_state):
"""Set `trainable` state for each sublayer."""
- layers = layer_utils.filter_empty_layer_containers(self._layers)
if self in trainable_state:
self.trainable = trainable_state[self]
- for layer in layers:
- layer._set_trainable_state(trainable_state)
+ layers = self._flatten_layers(include_self=False, recursive=False)
+ for l in layers:
+ if l in trainable_state:
+ l._set_trainable_state(trainable_state)
@property
def _obj_reference_counts(self):
@@ -2175,7 +2144,7 @@
default_value: Object, the default value of the attribute.
"""
if not hasattr(self, name):
- super(Layer, self).__setattr__(name, default_value)
+ self.__setattr__(name, default_value)
def __delattr__(self, name):
# For any super.__delattr__() call, we will directly use the implementation
@@ -2209,8 +2178,8 @@
if (isinstance(existing_value, Layer)
or base_layer_utils.has_weights(existing_value)):
super(tracking.AutoTrackable, self).__setattr__(
- '_layers',
- [l for l in self._layers if l is not existing_value])
+ '_self_tracked_trackables',
+ [l for l in self._self_tracked_trackables if l is not existing_value])
if isinstance(existing_value, tf_variables.Variable):
super(tracking.AutoTrackable, self).__setattr__(
'_trainable_weights',
@@ -2258,11 +2227,11 @@
# Append value to self._layers if relevant
if (getattr(self, '_auto_track_sub_layers', True) and
(isinstance(value, Layer) or base_layer_utils.has_weights(value))):
- self._maybe_create_attribute('_layers', [])
+ self._maybe_create_attribute('_self_tracked_trackables', [])
# We need to check object identity to avoid de-duplicating empty
# container types which compare equal.
- if not any((layer is value for layer in self._layers)):
- self._layers.append(value)
+ if not any((layer is value for layer in self._self_tracked_trackables)):
+ self._self_tracked_trackables.append(value)
if hasattr(value, '_use_resource_variables'):
# Legacy layers (V1 tf.layers) must always use
# resource variables.
@@ -2298,18 +2267,6 @@
# at __delattr__.
super(tracking.AutoTrackable, self).__setattr__(name, value)
- def _gather_children_attribute(self, attribute):
- assert attribute in {
- 'weights', 'trainable_weights', 'non_trainable_weights'
- }
- if hasattr(self, '_layers'):
- nested_layers = layer_utils.filter_empty_layer_containers(
- self._layers)
- return list(
- itertools.chain.from_iterable(
- getattr(layer, attribute) for layer in nested_layers))
- return []
-
# This is a hack so that the is_layer (within
# training/trackable/layer_utils.py) check doesn't get the weights attr.
# TODO(b/110718070): Remove when fixed.
diff --git a/tensorflow/python/keras/engine/deferred_sequential_test.py b/tensorflow/python/keras/engine/deferred_sequential_test.py
index 06f0aa3..5e1cc5b 100644
--- a/tensorflow/python/keras/engine/deferred_sequential_test.py
+++ b/tensorflow/python/keras/engine/deferred_sequential_test.py
@@ -129,7 +129,10 @@
path = os.path.join(self.get_temp_dir(), 'model_path')
model.save(path)
new_model = keras.models.load_model(path)
- for layer1, layer2 in zip(model._layers, new_model._layers):
+ model_layers = model._flatten_layers(include_self=True, recursive=False)
+ new_model_layers = new_model._flatten_layers(
+ include_self=True, recursive=False)
+ for layer1, layer2 in zip(model_layers, new_model_layers):
self.assertEqual(layer1.name, layer2.name)
for w1, w2 in zip(layer1.weights, layer2.weights):
self.assertAllClose(w1, w2)
@@ -144,7 +147,10 @@
path = os.path.join(self.get_temp_dir(), 'model_path.h5')
model.save(path)
new_model = keras.models.load_model(path)
- for layer1, layer2 in zip(model._layers, new_model._layers):
+ model_layers = model._flatten_layers(include_self=True, recursive=False)
+ new_model_layers = new_model._flatten_layers(
+ include_self=True, recursive=False)
+ for layer1, layer2 in zip(model_layers, new_model_layers):
self.assertEqual(layer1.name, layer2.name)
for w1, w2 in zip(layer1.weights, layer2.weights):
self.assertAllClose(w1, w2)
diff --git a/tensorflow/python/keras/engine/functional.py b/tensorflow/python/keras/engine/functional.py
index 57ae9ee..213975f 100644
--- a/tensorflow/python/keras/engine/functional.py
+++ b/tensorflow/python/keras/engine/functional.py
@@ -204,9 +204,9 @@
self.inputs, self.outputs)
self._network_nodes = nodes
self._nodes_by_depth = nodes_by_depth
- self._layers = layers
+ self._self_tracked_trackables = layers
self._layer_call_argspecs = {}
- for layer in self._layers:
+ for layer in self._self_tracked_trackables:
self._layer_call_argspecs[layer] = tf_inspect.getfullargspec(layer.call)
# Build self.input_names and self.output_names.
@@ -797,11 +797,11 @@
self._nodes_by_depth[depth].append(node)
# Insert layers and update other layer attrs.
- layer_set = set(self._layers)
+ layer_set = set(self._self_tracked_trackables)
deferred_layers = []
for layer in layers:
if layer not in layer_set:
- self._layers.append(layer)
+ self._self_tracked_trackables.append(layer)
deferred_layers.append(layer)
self._layer_call_argspecs[layer] = tf_inspect.getfullargspec(layer.call)
layer_set.add(layer)
@@ -1089,7 +1089,8 @@
# the network config.
return (isinstance(layer, Functional) and
# Filter out Sequential models without an input shape.
- isinstance(layer._layers[0], input_layer_module.InputLayer))
+ isinstance(layer._self_tracked_trackables[0],
+ input_layer_module.InputLayer))
def connect_ancillary_layers(model, created_layers):
diff --git a/tensorflow/python/keras/engine/sequential.py b/tensorflow/python/keras/engine/sequential.py
index 75bbcd0..a54f803 100644
--- a/tensorflow/python/keras/engine/sequential.py
+++ b/tensorflow/python/keras/engine/sequential.py
@@ -192,7 +192,8 @@
self.built = False
set_inputs = False
- if not self._layers:
+ self._maybe_create_attribute('_self_tracked_trackables', [])
+ if not self._self_tracked_trackables:
if isinstance(layer, input_layer.InputLayer):
# Case where the user passes an Input or InputLayer layer via `add`.
set_inputs = True
@@ -230,7 +231,7 @@
self._init_graph_network(self.inputs, self.outputs)
self._graph_initialized = True
else:
- self._layers.append(layer)
+ self._self_tracked_trackables.append(layer)
self._handle_deferred_layer_dependencies([layer])
self._layer_call_argspecs[layer] = tf_inspect.getfullargspec(layer.call)
@@ -245,7 +246,7 @@
if not self.layers:
raise TypeError('There are no layers in the model.')
- layer = self._layers.pop()
+ layer = self._self_tracked_trackables.pop()
self._layer_call_argspecs.pop(layer)
if not self.layers:
self.outputs = None
@@ -466,8 +467,8 @@
layer_configs = []
for layer in super(Sequential, self).layers:
# `super().layers` include the InputLayer if available (it is filtered out
- # of `self.layers`). Note that `self._layers` is managed by the
- # tracking infrastructure and should not be used.
+ # of `self.layers`). Note that `self._self_tracked_trackables` is managed
+ # by the tracking infrastructure and should not be used.
layer_configs.append(generic_utils.serialize_keras_object(layer))
config = {
'name': self.name,
diff --git a/tensorflow/python/keras/engine/sequential_test.py b/tensorflow/python/keras/engine/sequential_test.py
index 6a9a3bf..39fcb2e 100644
--- a/tensorflow/python/keras/engine/sequential_test.py
+++ b/tensorflow/python/keras/engine/sequential_test.py
@@ -412,20 +412,30 @@
"""Test that Sequential only tracks layers added in init or `.add`."""
layer = keras.layers.Dense(1)
model = keras.Sequential([layer])
- self.assertEqual(model._layers[-1], layer)
+ self.assertEqual(
+ list(model._flatten_layers(include_self=False, recursive=False))[-1],
+ layer)
model.a = [keras.layers.Dense(3)] # should not be added to the layers list.
- self.assertEqual(model._layers[-1], layer)
+ self.assertEqual(
+ list(model._flatten_layers(include_self=False, recursive=False))[-1],
+ layer)
layer2 = keras.layers.Dense(2)
model.add(layer2)
- self.assertEqual(model._layers[-1], layer2)
+ self.assertEqual(
+ list(model._flatten_layers(include_self=False, recursive=False))[-1],
+ layer2)
model.a = [keras.layers.Dense(3)] # should not be added to the layers list.
- self.assertEqual(model._layers[-1], layer2)
+ self.assertEqual(
+ list(model._flatten_layers(include_self=False, recursive=False))[-1],
+ layer2)
model.pop()
- self.assertEqual(model._layers[-1], layer)
+ self.assertEqual(
+ list(model._flatten_layers(include_self=False, recursive=False))[-1],
+ layer)
def test_config_preserves_input_layer(self):
model = keras.Sequential([
@@ -436,8 +446,10 @@
config = model.get_config()
new_model = keras.Sequential.from_config(config)
self.assertTrue(new_model.built)
- self.assertEqual(new_model._layers[0].dtype, 'int32')
- self.assertEqual(new_model._layers[0].name, 'my_embedding_input')
+ layers = list(
+ new_model._flatten_layers(include_self=False, recursive=False))
+ self.assertEqual(layers[0].dtype, 'int32')
+ self.assertEqual(layers[0].name, 'my_embedding_input')
def test_name_unicity(self):
model = keras.Sequential()
diff --git a/tensorflow/python/keras/engine/training.py b/tensorflow/python/keras/engine/training.py
index b4fb582..7ccfd39 100644
--- a/tensorflow/python/keras/engine/training.py
+++ b/tensorflow/python/keras/engine/training.py
@@ -78,7 +78,6 @@
from tensorflow.python.training import py_checkpoint_reader
from tensorflow.python.training.tracking import base as trackable
from tensorflow.python.training.tracking import data_structures
-from tensorflow.python.training.tracking import layer_utils as trackable_layer_utils
from tensorflow.python.training.tracking import util as trackable_utils
from tensorflow.python.util import nest
from tensorflow.python.util import tf_decorator
@@ -1922,21 +1921,35 @@
@property
def trainable_weights(self):
self._assert_weights_created()
- return self._dedup_weights(
- trackable_layer_utils.gather_trainable_weights(
- trainable=self.trainable,
- sub_layers=self._layers,
- extra_variables=self._trainable_weights))
+ if not self._trainable:
+ return []
+ trainable_variables = []
+ for trackable_obj in self._self_tracked_trackables:
+ trainable_variables += trackable_obj.trainable_variables
+ trainable_variables += self._trainable_weights
+ return self._dedup_weights(trainable_variables)
@property
def non_trainable_weights(self):
self._assert_weights_created()
- return self._dedup_weights(
- trackable_layer_utils.gather_non_trainable_weights(
- trainable=self.trainable,
- sub_layers=self._layers,
- extra_variables=self._non_trainable_weights +
- self._trainable_weights))
+ non_trainable_variables = []
+ for trackable_obj in self._self_tracked_trackables:
+ non_trainable_variables += trackable_obj.non_trainable_variables
+
+ if not self._trainable:
+ # Return order is all trainable vars, then all non-trainable vars.
+ trainable_variables = []
+ for trackable_obj in self._self_tracked_trackables:
+ trainable_variables += trackable_obj.trainable_variables
+
+ non_trainable_variables = (
+ trainable_variables + self._trainable_weights +
+ non_trainable_variables + self._non_trainable_weights)
+ else:
+ non_trainable_variables = (
+ non_trainable_variables + self._non_trainable_weights)
+
+ return self._dedup_weights(non_trainable_variables)
def get_weights(self):
"""Retrieves the weights of the model.
@@ -2349,8 +2362,8 @@
"""Returns the undeduplicated list of all layer variables/weights."""
self._assert_weights_created()
weights = []
- for layer in self._layers:
- weights += layer.weights
+ for layer in self._self_tracked_trackables:
+ weights += layer.variables
weights += (self._trainable_weights + self._non_trainable_weights)
return weights
diff --git a/tensorflow/python/keras/engine/training_test.py b/tensorflow/python/keras/engine/training_test.py
index dee1055..be85bc4 100644
--- a/tensorflow/python/keras/engine/training_test.py
+++ b/tensorflow/python/keras/engine/training_test.py
@@ -846,7 +846,8 @@
return self.layer2(self.layer1(inputs))
l = LayerWithWeightSharedLayers()
- self.assertEqual(l._layers, [l.layer1, l.layer2])
+ layers = list(l._flatten_layers(include_self=False, recursive=False))
+ self.assertEqual(layers, [l.layer1, l.layer2])
self.assertEqual(l.variables,
[l.layer1.trainable_var, l.layer1.non_trainable_var])
self.assertEqual(l.trainable_variables, [l.layer1.trainable_var])
diff --git a/tensorflow/python/keras/engine/training_v1.py b/tensorflow/python/keras/engine/training_v1.py
index cea6b1b..c843646 100644
--- a/tensorflow/python/keras/engine/training_v1.py
+++ b/tensorflow/python/keras/engine/training_v1.py
@@ -504,7 +504,9 @@
return super(Model, self).metrics
metrics += self._compile_metric_functions
metrics.extend(self._metrics)
- metrics.extend(_get_metrics_from_layers(self._layers))
+ metrics.extend(
+ _get_metrics_from_layers(
+ list(self._flatten_layers(include_self=False, recursive=False))))
return metrics
@property
@@ -1717,7 +1719,7 @@
# Avoids the override in Sequential.layers which filters Input layers.
# (Which are often the very layers that we're after.)
- layers = layer_utils.filter_empty_layer_containers(self._layers)
+ layers = self._flatten_layers(include_self=False, recursive=False)
first_layer = next(layers, None)
if first_layer:
# The per-replica static batch size.
diff --git a/tensorflow/python/keras/models.py b/tensorflow/python/keras/models.py
index b3737b5..cb4528b 100644
--- a/tensorflow/python/keras/models.py
+++ b/tensorflow/python/keras/models.py
@@ -318,10 +318,10 @@
layers = [] # Layers needed to compute the model's outputs.
layer_map = {}
- # Use model._layers to ensure that all layers are cloned. The model's layers
+ # Ensure that all layers are cloned. The model's layers
# property will exclude the initial InputLayer (if it exists) in the model,
# resulting in a different Sequential model structure.
- for layer in model._layers:
+ for layer in model._flatten_layers(include_self=False, recursive=False):
if isinstance(layer, InputLayer) and input_tensors is not None:
# If input tensors are provided, the original model's InputLayer is
# overwritten with a different InputLayer.
@@ -460,9 +460,8 @@
# Retrieve all layers tracked by the model as well as their attribute names
attributes_cache = {}
for name in dir(model):
- # Skip the check of methods in tf.Module since they basically
- # recursively query all the other attributes within same module.
- if name == 'submodules':
+ # Skip attrs that track other trackables.
+ if name == 'submodules' or name == '_self_tracked_trackables':
continue
try:
@@ -489,10 +488,11 @@
# Replace layers on the model with fresh layers
layers_to_names = {value: key for key, value in attributes_cache.items()}
- original_layers = model._layers[:]
+ original_layers = list(
+ model._flatten_layers(include_self=False, recursive=False))
setattr_tracking = model._setattr_tracking
model._setattr_tracking = False
- model._layers = []
+ model._self_tracked_trackables = []
for layer in original_layers: # We preserve layer order.
config = layer.get_config()
# This will not work for nested subclassed models used as layers.
@@ -505,7 +505,7 @@
fresh_layer = layer.__class__.from_config(config)
name = layers_to_names[layer]
setattr(model, name, fresh_layer)
- model._layers.append(fresh_layer)
+ model._self_tracked_trackables.append(fresh_layer)
# Cache original model build attributes (in addition to layers)
if (not hasattr(model, '_original_attributes_cache') or
@@ -576,11 +576,11 @@
# when they're constructed.
setattr_tracking = model._setattr_tracking
model._setattr_tracking = False
- model._layers = []
+ model._self_tracked_trackables = []
for name, value in model._original_attributes_cache.items():
setattr(model, name, value)
if isinstance(value, Layer):
- model._layers.append(value)
+ model._self_tracked_trackables.append(value)
model._original_attributes_cache = None
model._setattr_tracking = setattr_tracking
else:
diff --git a/tensorflow/python/keras/models_test.py b/tensorflow/python/keras/models_test.py
index 854a0ca..0ece5ac 100644
--- a/tensorflow/python/keras/models_test.py
+++ b/tensorflow/python/keras/models_test.py
@@ -111,16 +111,20 @@
model = models.Sequential(_get_layers(input_shape, add_input_layer))
# Sanity check
self.assertEqual(
- isinstance(model._layers[0], keras.layers.InputLayer),
- add_input_layer)
+ isinstance(
+ list(model._flatten_layers(include_self=False, recursive=False))[0],
+ keras.layers.InputLayer), add_input_layer)
self.assertEqual(model._is_graph_network, add_input_layer)
# With placeholder creation -- clone model should have an InputLayer
# if the original model has one.
new_model = clone_fn(model)
self.assertEqual(
- isinstance(new_model._layers[0], keras.layers.InputLayer),
- add_input_layer)
+ isinstance(
+ list(
+ new_model._flatten_layers(include_self=False,
+ recursive=False))[0],
+ keras.layers.InputLayer), add_input_layer)
self.assertEqual(new_model._is_graph_network, model._is_graph_network)
if input_shape and not ops.executing_eagerly_outside_functions():
# update ops from batch norm needs to be included
@@ -129,7 +133,9 @@
# On top of new tensor -- clone model should always have an InputLayer.
input_a = keras.Input(shape=(4,))
new_model = clone_fn(model, input_tensors=input_a)
- self.assertIsInstance(new_model._layers[0], keras.layers.InputLayer)
+ self.assertIsInstance(
+ list(new_model._flatten_layers(include_self=False, recursive=False))[0],
+ keras.layers.InputLayer)
self.assertTrue(new_model._is_graph_network)
# On top of new, non-Keras tensor -- clone model should always have an
@@ -139,7 +145,10 @@
# saying they should not be used with EagerTensors
input_a = keras.backend.variable(val_a)
new_model = clone_fn(model, input_tensors=input_a)
- self.assertIsInstance(new_model._layers[0], keras.layers.InputLayer)
+ self.assertIsInstance(
+ list(new_model._flatten_layers(include_self=False,
+ recursive=False))[0],
+ keras.layers.InputLayer)
self.assertTrue(new_model._is_graph_network)
@keras_parameterized.run_all_keras_modes
diff --git a/tensorflow/python/keras/saving/saved_model/revive_test.py b/tensorflow/python/keras/saving/saved_model/revive_test.py
index 80170db..d994421 100644
--- a/tensorflow/python/keras/saving/saved_model/revive_test.py
+++ b/tensorflow/python/keras/saving/saved_model/revive_test.py
@@ -328,7 +328,9 @@
])
model.save(self.path, save_format='tf')
revived = keras_load.load(self.path)
- self.assertEqual(dtypes.string, revived._layers[0].dtype)
+ revived_layers = list(
+ revived._flatten_layers(include_self=False, recursive=False))
+ self.assertEqual(dtypes.string, revived_layers[0].dtype)
@parameterized.named_parameters(
('default_config', CustomNetworkDefaultConfig),
diff --git a/tensorflow/python/keras/saving/saved_model/utils.py b/tensorflow/python/keras/saving/saved_model/utils.py
index c3e470f..5162822 100644
--- a/tensorflow/python/keras/saving/saved_model/utils.py
+++ b/tensorflow/python/keras/saving/saved_model/utils.py
@@ -25,7 +25,6 @@
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_contextlib
from tensorflow.python.keras.utils import tf_inspect
from tensorflow.python.keras.utils.generic_utils import LazyLoader
@@ -117,10 +116,11 @@
def list_all_layers(obj):
if isinstance(obj, training_lib.Model):
+ # Handle special case of Sequential, which doesn't return
+ # the `Input` layer.
return obj.layers
else:
- return list(
- layer_utils.filter_empty_layer_containers(obj._layers)) # pylint: disable=protected-access
+ return list(obj._flatten_layers(include_self=False, recursive=False)) # pylint: disable=protected-access
def list_all_layers_and_sublayers(obj):
diff --git a/tensorflow/python/module/module.py b/tensorflow/python/module/module.py
index ca42de8..ad46af0 100644
--- a/tensorflow/python/module/module.py
+++ b/tensorflow/python/module/module.py
@@ -176,6 +176,21 @@
self._flatten(predicate=_is_trainable_variable, expand_composites=True))
@property
+ def non_trainable_variables(self):
+ """Sequence of non-trainable variables owned by this module and its submodules.
+
+ Note: this method uses reflection to find variables on the current instance
+ and submodules. For performance reasons you may wish to cache the result
+ of calling this method if you don't expect the return value to change.
+
+ Returns:
+ A sequence of variables for the current module (sorted by attribute
+ name) followed by variables from all submodules recursively (breadth
+ first).
+ """
+ return tuple(self._flatten(predicate=_is_non_trainable_variable))
+
+ @property
def submodules(self):
"""Sequence of all sub-modules.
@@ -310,6 +325,10 @@
return _is_variable(obj) and getattr(obj, "trainable", False)
+def _is_non_trainable_variable(obj):
+ return _is_variable(obj) and not getattr(obj, "trainable", False)
+
+
def _is_module(obj):
return isinstance(obj, Module)
diff --git a/tensorflow/python/training/tracking/data_structures.py b/tensorflow/python/training/tracking/data_structures.py
index 1d2398d..38cc50a 100644
--- a/tensorflow/python/training/tracking/data_structures.py
+++ b/tensorflow/python/training/tracking/data_structures.py
@@ -35,8 +35,12 @@
from tensorflow.python.saved_model import revived_types
from tensorflow.python.training.tracking import base
from tensorflow.python.training.tracking import layer_utils
+from tensorflow.python.util import lazy_loader
from tensorflow.python.util.compat import collections_abc
+module = lazy_loader.LazyLoader(
+ "module", globals(), "tensorflow.python.module.module")
+
class NoDependency(object):
"""Allows attribute assignment to `Trackable` objects with no dependency.
@@ -213,17 +217,45 @@
@property
def trainable_weights(self):
- return layer_utils.gather_trainable_weights(
- trainable=self.trainable,
- sub_layers=self._layers,
- extra_variables=self._self_extra_variables)
+ if not self._self_trainable:
+ return []
+ trainable_variables = []
+ for obj in self._values:
+ if isinstance(obj, (TrackableDataStructure, module.Module)):
+ trainable_variables += obj.trainable_variables
+ trainable_extra_variables = [
+ v for v in self._self_extra_variables if v.trainable
+ ]
+ return trainable_variables + trainable_extra_variables
@property
def non_trainable_weights(self):
- return layer_utils.gather_non_trainable_weights(
- trainable=self.trainable,
- sub_layers=self._layers,
- extra_variables=self._self_extra_variables)
+ trainable_extra_variables = [
+ v for v in self._self_extra_variables if v.trainable
+ ]
+ non_trainable_extra_variables = [
+ v for v in self._self_extra_variables if not v.trainable
+ ]
+ non_trainable_variables = []
+ for obj in self._values:
+ if isinstance(obj, (TrackableDataStructure, module.Module)):
+ non_trainable_variables += obj.non_trainable_variables
+
+ if not self._self_trainable:
+ # Return order is all trainable vars, then all non-trainable vars.
+ trainable_variables = []
+ for obj in self._values:
+ if isinstance(obj, (TrackableDataStructure, module.Module)):
+ trainable_variables += obj.trainable_variables
+
+ non_trainable_variables = (
+ trainable_variables + trainable_extra_variables +
+ non_trainable_variables + non_trainable_extra_variables)
+ else:
+ non_trainable_variables = (
+ non_trainable_variables + non_trainable_extra_variables)
+
+ return non_trainable_variables
@property
def weights(self):
diff --git a/tensorflow/tools/api/golden/v1/tensorflow.-module.pbtxt b/tensorflow/tools/api/golden/v1/tensorflow.-module.pbtxt
index 8c3438e..7019451 100644
--- a/tensorflow/tools/api/golden/v1/tensorflow.-module.pbtxt
+++ b/tensorflow/tools/api/golden/v1/tensorflow.-module.pbtxt
@@ -13,6 +13,10 @@
mtype: "<type \'property\'>"
}
member {
+ name: "non_trainable_variables"
+ mtype: "<type \'property\'>"
+ }
+ member {
name: "submodules"
mtype: "<type \'property\'>"
}
diff --git a/tensorflow/tools/api/golden/v1/tensorflow.linalg.-linear-operator-adjoint.pbtxt b/tensorflow/tools/api/golden/v1/tensorflow.linalg.-linear-operator-adjoint.pbtxt
index cd2342f..b3b31b9 100644
--- a/tensorflow/tools/api/golden/v1/tensorflow.linalg.-linear-operator-adjoint.pbtxt
+++ b/tensorflow/tools/api/golden/v1/tensorflow.linalg.-linear-operator-adjoint.pbtxt
@@ -51,6 +51,10 @@
mtype: "<type \'property\'>"
}
member {
+ name: "non_trainable_variables"
+ mtype: "<type \'property\'>"
+ }
+ member {
name: "operator"
mtype: "<type \'property\'>"
}
diff --git a/tensorflow/tools/api/golden/v1/tensorflow.linalg.-linear-operator-block-diag.pbtxt b/tensorflow/tools/api/golden/v1/tensorflow.linalg.-linear-operator-block-diag.pbtxt
index 37cab1c..de44920 100644
--- a/tensorflow/tools/api/golden/v1/tensorflow.linalg.-linear-operator-block-diag.pbtxt
+++ b/tensorflow/tools/api/golden/v1/tensorflow.linalg.-linear-operator-block-diag.pbtxt
@@ -51,6 +51,10 @@
mtype: "<type \'property\'>"
}
member {
+ name: "non_trainable_variables"
+ mtype: "<type \'property\'>"
+ }
+ member {
name: "operators"
mtype: "<type \'property\'>"
}
diff --git a/tensorflow/tools/api/golden/v1/tensorflow.linalg.-linear-operator-block-lower-triangular.pbtxt b/tensorflow/tools/api/golden/v1/tensorflow.linalg.-linear-operator-block-lower-triangular.pbtxt
index 1554866..127f506 100644
--- a/tensorflow/tools/api/golden/v1/tensorflow.linalg.-linear-operator-block-lower-triangular.pbtxt
+++ b/tensorflow/tools/api/golden/v1/tensorflow.linalg.-linear-operator-block-lower-triangular.pbtxt
@@ -51,6 +51,10 @@
mtype: "<type \'property\'>"
}
member {
+ name: "non_trainable_variables"
+ mtype: "<type \'property\'>"
+ }
+ member {
name: "operators"
mtype: "<type \'property\'>"
}
diff --git a/tensorflow/tools/api/golden/v1/tensorflow.linalg.-linear-operator-circulant.pbtxt b/tensorflow/tools/api/golden/v1/tensorflow.linalg.-linear-operator-circulant.pbtxt
index 96f3f45..977eab3 100644
--- a/tensorflow/tools/api/golden/v1/tensorflow.linalg.-linear-operator-circulant.pbtxt
+++ b/tensorflow/tools/api/golden/v1/tensorflow.linalg.-linear-operator-circulant.pbtxt
@@ -60,6 +60,10 @@
mtype: "<type \'property\'>"
}
member {
+ name: "non_trainable_variables"
+ mtype: "<type \'property\'>"
+ }
+ member {
name: "parameters"
mtype: "<type \'property\'>"
}
diff --git a/tensorflow/tools/api/golden/v1/tensorflow.linalg.-linear-operator-circulant2-d.pbtxt b/tensorflow/tools/api/golden/v1/tensorflow.linalg.-linear-operator-circulant2-d.pbtxt
index 8269661..7288980 100644
--- a/tensorflow/tools/api/golden/v1/tensorflow.linalg.-linear-operator-circulant2-d.pbtxt
+++ b/tensorflow/tools/api/golden/v1/tensorflow.linalg.-linear-operator-circulant2-d.pbtxt
@@ -60,6 +60,10 @@
mtype: "<type \'property\'>"
}
member {
+ name: "non_trainable_variables"
+ mtype: "<type \'property\'>"
+ }
+ member {
name: "parameters"
mtype: "<type \'property\'>"
}
diff --git a/tensorflow/tools/api/golden/v1/tensorflow.linalg.-linear-operator-circulant3-d.pbtxt b/tensorflow/tools/api/golden/v1/tensorflow.linalg.-linear-operator-circulant3-d.pbtxt
index fa9ff47..3936db5 100644
--- a/tensorflow/tools/api/golden/v1/tensorflow.linalg.-linear-operator-circulant3-d.pbtxt
+++ b/tensorflow/tools/api/golden/v1/tensorflow.linalg.-linear-operator-circulant3-d.pbtxt
@@ -60,6 +60,10 @@
mtype: "<type \'property\'>"
}
member {
+ name: "non_trainable_variables"
+ mtype: "<type \'property\'>"
+ }
+ member {
name: "parameters"
mtype: "<type \'property\'>"
}
diff --git a/tensorflow/tools/api/golden/v1/tensorflow.linalg.-linear-operator-composition.pbtxt b/tensorflow/tools/api/golden/v1/tensorflow.linalg.-linear-operator-composition.pbtxt
index 1f3a3e0..6e3e047 100644
--- a/tensorflow/tools/api/golden/v1/tensorflow.linalg.-linear-operator-composition.pbtxt
+++ b/tensorflow/tools/api/golden/v1/tensorflow.linalg.-linear-operator-composition.pbtxt
@@ -51,6 +51,10 @@
mtype: "<type \'property\'>"
}
member {
+ name: "non_trainable_variables"
+ mtype: "<type \'property\'>"
+ }
+ member {
name: "operators"
mtype: "<type \'property\'>"
}
diff --git a/tensorflow/tools/api/golden/v1/tensorflow.linalg.-linear-operator-diag.pbtxt b/tensorflow/tools/api/golden/v1/tensorflow.linalg.-linear-operator-diag.pbtxt
index 40aea95..b23dff8 100644
--- a/tensorflow/tools/api/golden/v1/tensorflow.linalg.-linear-operator-diag.pbtxt
+++ b/tensorflow/tools/api/golden/v1/tensorflow.linalg.-linear-operator-diag.pbtxt
@@ -55,6 +55,10 @@
mtype: "<type \'property\'>"
}
member {
+ name: "non_trainable_variables"
+ mtype: "<type \'property\'>"
+ }
+ member {
name: "parameters"
mtype: "<type \'property\'>"
}
diff --git a/tensorflow/tools/api/golden/v1/tensorflow.linalg.-linear-operator-full-matrix.pbtxt b/tensorflow/tools/api/golden/v1/tensorflow.linalg.-linear-operator-full-matrix.pbtxt
index c23af28..4df8050 100644
--- a/tensorflow/tools/api/golden/v1/tensorflow.linalg.-linear-operator-full-matrix.pbtxt
+++ b/tensorflow/tools/api/golden/v1/tensorflow.linalg.-linear-operator-full-matrix.pbtxt
@@ -51,6 +51,10 @@
mtype: "<type \'property\'>"
}
member {
+ name: "non_trainable_variables"
+ mtype: "<type \'property\'>"
+ }
+ member {
name: "parameters"
mtype: "<type \'property\'>"
}
diff --git a/tensorflow/tools/api/golden/v1/tensorflow.linalg.-linear-operator-householder.pbtxt b/tensorflow/tools/api/golden/v1/tensorflow.linalg.-linear-operator-householder.pbtxt
index ac861ce..03c8152 100644
--- a/tensorflow/tools/api/golden/v1/tensorflow.linalg.-linear-operator-householder.pbtxt
+++ b/tensorflow/tools/api/golden/v1/tensorflow.linalg.-linear-operator-householder.pbtxt
@@ -51,6 +51,10 @@
mtype: "<type \'property\'>"
}
member {
+ name: "non_trainable_variables"
+ mtype: "<type \'property\'>"
+ }
+ member {
name: "parameters"
mtype: "<type \'property\'>"
}
diff --git a/tensorflow/tools/api/golden/v1/tensorflow.linalg.-linear-operator-identity.pbtxt b/tensorflow/tools/api/golden/v1/tensorflow.linalg.-linear-operator-identity.pbtxt
index 1c8a107..3017499 100644
--- a/tensorflow/tools/api/golden/v1/tensorflow.linalg.-linear-operator-identity.pbtxt
+++ b/tensorflow/tools/api/golden/v1/tensorflow.linalg.-linear-operator-identity.pbtxt
@@ -52,6 +52,10 @@
mtype: "<type \'property\'>"
}
member {
+ name: "non_trainable_variables"
+ mtype: "<type \'property\'>"
+ }
+ member {
name: "parameters"
mtype: "<type \'property\'>"
}
diff --git a/tensorflow/tools/api/golden/v1/tensorflow.linalg.-linear-operator-inversion.pbtxt b/tensorflow/tools/api/golden/v1/tensorflow.linalg.-linear-operator-inversion.pbtxt
index 6379a67..2c059c5 100644
--- a/tensorflow/tools/api/golden/v1/tensorflow.linalg.-linear-operator-inversion.pbtxt
+++ b/tensorflow/tools/api/golden/v1/tensorflow.linalg.-linear-operator-inversion.pbtxt
@@ -51,6 +51,10 @@
mtype: "<type \'property\'>"
}
member {
+ name: "non_trainable_variables"
+ mtype: "<type \'property\'>"
+ }
+ member {
name: "operator"
mtype: "<type \'property\'>"
}
diff --git a/tensorflow/tools/api/golden/v1/tensorflow.linalg.-linear-operator-kronecker.pbtxt b/tensorflow/tools/api/golden/v1/tensorflow.linalg.-linear-operator-kronecker.pbtxt
index fda6139..f014040 100644
--- a/tensorflow/tools/api/golden/v1/tensorflow.linalg.-linear-operator-kronecker.pbtxt
+++ b/tensorflow/tools/api/golden/v1/tensorflow.linalg.-linear-operator-kronecker.pbtxt
@@ -51,6 +51,10 @@
mtype: "<type \'property\'>"
}
member {
+ name: "non_trainable_variables"
+ mtype: "<type \'property\'>"
+ }
+ member {
name: "operators"
mtype: "<type \'property\'>"
}
diff --git a/tensorflow/tools/api/golden/v1/tensorflow.linalg.-linear-operator-low-rank-update.pbtxt b/tensorflow/tools/api/golden/v1/tensorflow.linalg.-linear-operator-low-rank-update.pbtxt
index c07a18eb..767007fb 100644
--- a/tensorflow/tools/api/golden/v1/tensorflow.linalg.-linear-operator-low-rank-update.pbtxt
+++ b/tensorflow/tools/api/golden/v1/tensorflow.linalg.-linear-operator-low-rank-update.pbtxt
@@ -67,6 +67,10 @@
mtype: "<type \'property\'>"
}
member {
+ name: "non_trainable_variables"
+ mtype: "<type \'property\'>"
+ }
+ member {
name: "parameters"
mtype: "<type \'property\'>"
}
diff --git a/tensorflow/tools/api/golden/v1/tensorflow.linalg.-linear-operator-lower-triangular.pbtxt b/tensorflow/tools/api/golden/v1/tensorflow.linalg.-linear-operator-lower-triangular.pbtxt
index 39e44ed..809a560 100644
--- a/tensorflow/tools/api/golden/v1/tensorflow.linalg.-linear-operator-lower-triangular.pbtxt
+++ b/tensorflow/tools/api/golden/v1/tensorflow.linalg.-linear-operator-lower-triangular.pbtxt
@@ -51,6 +51,10 @@
mtype: "<type \'property\'>"
}
member {
+ name: "non_trainable_variables"
+ mtype: "<type \'property\'>"
+ }
+ member {
name: "parameters"
mtype: "<type \'property\'>"
}
diff --git a/tensorflow/tools/api/golden/v1/tensorflow.linalg.-linear-operator-permutation.pbtxt b/tensorflow/tools/api/golden/v1/tensorflow.linalg.-linear-operator-permutation.pbtxt
index 228bfd4..8cd1381 100644
--- a/tensorflow/tools/api/golden/v1/tensorflow.linalg.-linear-operator-permutation.pbtxt
+++ b/tensorflow/tools/api/golden/v1/tensorflow.linalg.-linear-operator-permutation.pbtxt
@@ -51,6 +51,10 @@
mtype: "<type \'property\'>"
}
member {
+ name: "non_trainable_variables"
+ mtype: "<type \'property\'>"
+ }
+ member {
name: "parameters"
mtype: "<type \'property\'>"
}
diff --git a/tensorflow/tools/api/golden/v1/tensorflow.linalg.-linear-operator-scaled-identity.pbtxt b/tensorflow/tools/api/golden/v1/tensorflow.linalg.-linear-operator-scaled-identity.pbtxt
index 358c0f8..7a0fa4d 100644
--- a/tensorflow/tools/api/golden/v1/tensorflow.linalg.-linear-operator-scaled-identity.pbtxt
+++ b/tensorflow/tools/api/golden/v1/tensorflow.linalg.-linear-operator-scaled-identity.pbtxt
@@ -56,6 +56,10 @@
mtype: "<type \'property\'>"
}
member {
+ name: "non_trainable_variables"
+ mtype: "<type \'property\'>"
+ }
+ member {
name: "parameters"
mtype: "<type \'property\'>"
}
diff --git a/tensorflow/tools/api/golden/v1/tensorflow.linalg.-linear-operator-toeplitz.pbtxt b/tensorflow/tools/api/golden/v1/tensorflow.linalg.-linear-operator-toeplitz.pbtxt
index 7f863ce..cbbab4d 100644
--- a/tensorflow/tools/api/golden/v1/tensorflow.linalg.-linear-operator-toeplitz.pbtxt
+++ b/tensorflow/tools/api/golden/v1/tensorflow.linalg.-linear-operator-toeplitz.pbtxt
@@ -55,6 +55,10 @@
mtype: "<type \'property\'>"
}
member {
+ name: "non_trainable_variables"
+ mtype: "<type \'property\'>"
+ }
+ member {
name: "parameters"
mtype: "<type \'property\'>"
}
diff --git a/tensorflow/tools/api/golden/v1/tensorflow.linalg.-linear-operator-tridiag.pbtxt b/tensorflow/tools/api/golden/v1/tensorflow.linalg.-linear-operator-tridiag.pbtxt
index eadb8f0..b45a8fb 100644
--- a/tensorflow/tools/api/golden/v1/tensorflow.linalg.-linear-operator-tridiag.pbtxt
+++ b/tensorflow/tools/api/golden/v1/tensorflow.linalg.-linear-operator-tridiag.pbtxt
@@ -59,6 +59,10 @@
mtype: "<type \'property\'>"
}
member {
+ name: "non_trainable_variables"
+ mtype: "<type \'property\'>"
+ }
+ member {
name: "parameters"
mtype: "<type \'property\'>"
}
diff --git a/tensorflow/tools/api/golden/v1/tensorflow.linalg.-linear-operator-zeros.pbtxt b/tensorflow/tools/api/golden/v1/tensorflow.linalg.-linear-operator-zeros.pbtxt
index f905de2..3510ede 100644
--- a/tensorflow/tools/api/golden/v1/tensorflow.linalg.-linear-operator-zeros.pbtxt
+++ b/tensorflow/tools/api/golden/v1/tensorflow.linalg.-linear-operator-zeros.pbtxt
@@ -51,6 +51,10 @@
mtype: "<type \'property\'>"
}
member {
+ name: "non_trainable_variables"
+ mtype: "<type \'property\'>"
+ }
+ member {
name: "parameters"
mtype: "<type \'property\'>"
}
diff --git a/tensorflow/tools/api/golden/v1/tensorflow.linalg.-linear-operator.pbtxt b/tensorflow/tools/api/golden/v1/tensorflow.linalg.-linear-operator.pbtxt
index c9ee030..83df2d5 100644
--- a/tensorflow/tools/api/golden/v1/tensorflow.linalg.-linear-operator.pbtxt
+++ b/tensorflow/tools/api/golden/v1/tensorflow.linalg.-linear-operator.pbtxt
@@ -50,6 +50,10 @@
mtype: "<type \'property\'>"
}
member {
+ name: "non_trainable_variables"
+ mtype: "<type \'property\'>"
+ }
+ member {
name: "parameters"
mtype: "<type \'property\'>"
}
diff --git a/tensorflow/tools/api/golden/v2/tensorflow.-module.pbtxt b/tensorflow/tools/api/golden/v2/tensorflow.-module.pbtxt
index 8c3438e..7019451 100644
--- a/tensorflow/tools/api/golden/v2/tensorflow.-module.pbtxt
+++ b/tensorflow/tools/api/golden/v2/tensorflow.-module.pbtxt
@@ -13,6 +13,10 @@
mtype: "<type \'property\'>"
}
member {
+ name: "non_trainable_variables"
+ mtype: "<type \'property\'>"
+ }
+ member {
name: "submodules"
mtype: "<type \'property\'>"
}
diff --git a/tensorflow/tools/api/golden/v2/tensorflow.linalg.-linear-operator-adjoint.pbtxt b/tensorflow/tools/api/golden/v2/tensorflow.linalg.-linear-operator-adjoint.pbtxt
index cd2342f..b3b31b9 100644
--- a/tensorflow/tools/api/golden/v2/tensorflow.linalg.-linear-operator-adjoint.pbtxt
+++ b/tensorflow/tools/api/golden/v2/tensorflow.linalg.-linear-operator-adjoint.pbtxt
@@ -51,6 +51,10 @@
mtype: "<type \'property\'>"
}
member {
+ name: "non_trainable_variables"
+ mtype: "<type \'property\'>"
+ }
+ member {
name: "operator"
mtype: "<type \'property\'>"
}
diff --git a/tensorflow/tools/api/golden/v2/tensorflow.linalg.-linear-operator-block-diag.pbtxt b/tensorflow/tools/api/golden/v2/tensorflow.linalg.-linear-operator-block-diag.pbtxt
index 37cab1c..de44920 100644
--- a/tensorflow/tools/api/golden/v2/tensorflow.linalg.-linear-operator-block-diag.pbtxt
+++ b/tensorflow/tools/api/golden/v2/tensorflow.linalg.-linear-operator-block-diag.pbtxt
@@ -51,6 +51,10 @@
mtype: "<type \'property\'>"
}
member {
+ name: "non_trainable_variables"
+ mtype: "<type \'property\'>"
+ }
+ member {
name: "operators"
mtype: "<type \'property\'>"
}
diff --git a/tensorflow/tools/api/golden/v2/tensorflow.linalg.-linear-operator-block-lower-triangular.pbtxt b/tensorflow/tools/api/golden/v2/tensorflow.linalg.-linear-operator-block-lower-triangular.pbtxt
index 1554866..127f506 100644
--- a/tensorflow/tools/api/golden/v2/tensorflow.linalg.-linear-operator-block-lower-triangular.pbtxt
+++ b/tensorflow/tools/api/golden/v2/tensorflow.linalg.-linear-operator-block-lower-triangular.pbtxt
@@ -51,6 +51,10 @@
mtype: "<type \'property\'>"
}
member {
+ name: "non_trainable_variables"
+ mtype: "<type \'property\'>"
+ }
+ member {
name: "operators"
mtype: "<type \'property\'>"
}
diff --git a/tensorflow/tools/api/golden/v2/tensorflow.linalg.-linear-operator-circulant.pbtxt b/tensorflow/tools/api/golden/v2/tensorflow.linalg.-linear-operator-circulant.pbtxt
index 96f3f45..977eab3 100644
--- a/tensorflow/tools/api/golden/v2/tensorflow.linalg.-linear-operator-circulant.pbtxt
+++ b/tensorflow/tools/api/golden/v2/tensorflow.linalg.-linear-operator-circulant.pbtxt
@@ -60,6 +60,10 @@
mtype: "<type \'property\'>"
}
member {
+ name: "non_trainable_variables"
+ mtype: "<type \'property\'>"
+ }
+ member {
name: "parameters"
mtype: "<type \'property\'>"
}
diff --git a/tensorflow/tools/api/golden/v2/tensorflow.linalg.-linear-operator-circulant2-d.pbtxt b/tensorflow/tools/api/golden/v2/tensorflow.linalg.-linear-operator-circulant2-d.pbtxt
index 8269661..7288980 100644
--- a/tensorflow/tools/api/golden/v2/tensorflow.linalg.-linear-operator-circulant2-d.pbtxt
+++ b/tensorflow/tools/api/golden/v2/tensorflow.linalg.-linear-operator-circulant2-d.pbtxt
@@ -60,6 +60,10 @@
mtype: "<type \'property\'>"
}
member {
+ name: "non_trainable_variables"
+ mtype: "<type \'property\'>"
+ }
+ member {
name: "parameters"
mtype: "<type \'property\'>"
}
diff --git a/tensorflow/tools/api/golden/v2/tensorflow.linalg.-linear-operator-circulant3-d.pbtxt b/tensorflow/tools/api/golden/v2/tensorflow.linalg.-linear-operator-circulant3-d.pbtxt
index fa9ff47..3936db5 100644
--- a/tensorflow/tools/api/golden/v2/tensorflow.linalg.-linear-operator-circulant3-d.pbtxt
+++ b/tensorflow/tools/api/golden/v2/tensorflow.linalg.-linear-operator-circulant3-d.pbtxt
@@ -60,6 +60,10 @@
mtype: "<type \'property\'>"
}
member {
+ name: "non_trainable_variables"
+ mtype: "<type \'property\'>"
+ }
+ member {
name: "parameters"
mtype: "<type \'property\'>"
}
diff --git a/tensorflow/tools/api/golden/v2/tensorflow.linalg.-linear-operator-composition.pbtxt b/tensorflow/tools/api/golden/v2/tensorflow.linalg.-linear-operator-composition.pbtxt
index 1f3a3e0..6e3e047 100644
--- a/tensorflow/tools/api/golden/v2/tensorflow.linalg.-linear-operator-composition.pbtxt
+++ b/tensorflow/tools/api/golden/v2/tensorflow.linalg.-linear-operator-composition.pbtxt
@@ -51,6 +51,10 @@
mtype: "<type \'property\'>"
}
member {
+ name: "non_trainable_variables"
+ mtype: "<type \'property\'>"
+ }
+ member {
name: "operators"
mtype: "<type \'property\'>"
}
diff --git a/tensorflow/tools/api/golden/v2/tensorflow.linalg.-linear-operator-diag.pbtxt b/tensorflow/tools/api/golden/v2/tensorflow.linalg.-linear-operator-diag.pbtxt
index 40aea95..b23dff8 100644
--- a/tensorflow/tools/api/golden/v2/tensorflow.linalg.-linear-operator-diag.pbtxt
+++ b/tensorflow/tools/api/golden/v2/tensorflow.linalg.-linear-operator-diag.pbtxt
@@ -55,6 +55,10 @@
mtype: "<type \'property\'>"
}
member {
+ name: "non_trainable_variables"
+ mtype: "<type \'property\'>"
+ }
+ member {
name: "parameters"
mtype: "<type \'property\'>"
}
diff --git a/tensorflow/tools/api/golden/v2/tensorflow.linalg.-linear-operator-full-matrix.pbtxt b/tensorflow/tools/api/golden/v2/tensorflow.linalg.-linear-operator-full-matrix.pbtxt
index c23af28..4df8050 100644
--- a/tensorflow/tools/api/golden/v2/tensorflow.linalg.-linear-operator-full-matrix.pbtxt
+++ b/tensorflow/tools/api/golden/v2/tensorflow.linalg.-linear-operator-full-matrix.pbtxt
@@ -51,6 +51,10 @@
mtype: "<type \'property\'>"
}
member {
+ name: "non_trainable_variables"
+ mtype: "<type \'property\'>"
+ }
+ member {
name: "parameters"
mtype: "<type \'property\'>"
}
diff --git a/tensorflow/tools/api/golden/v2/tensorflow.linalg.-linear-operator-householder.pbtxt b/tensorflow/tools/api/golden/v2/tensorflow.linalg.-linear-operator-householder.pbtxt
index ac861ce..03c8152 100644
--- a/tensorflow/tools/api/golden/v2/tensorflow.linalg.-linear-operator-householder.pbtxt
+++ b/tensorflow/tools/api/golden/v2/tensorflow.linalg.-linear-operator-householder.pbtxt
@@ -51,6 +51,10 @@
mtype: "<type \'property\'>"
}
member {
+ name: "non_trainable_variables"
+ mtype: "<type \'property\'>"
+ }
+ member {
name: "parameters"
mtype: "<type \'property\'>"
}
diff --git a/tensorflow/tools/api/golden/v2/tensorflow.linalg.-linear-operator-identity.pbtxt b/tensorflow/tools/api/golden/v2/tensorflow.linalg.-linear-operator-identity.pbtxt
index 1c8a107..3017499 100644
--- a/tensorflow/tools/api/golden/v2/tensorflow.linalg.-linear-operator-identity.pbtxt
+++ b/tensorflow/tools/api/golden/v2/tensorflow.linalg.-linear-operator-identity.pbtxt
@@ -52,6 +52,10 @@
mtype: "<type \'property\'>"
}
member {
+ name: "non_trainable_variables"
+ mtype: "<type \'property\'>"
+ }
+ member {
name: "parameters"
mtype: "<type \'property\'>"
}
diff --git a/tensorflow/tools/api/golden/v2/tensorflow.linalg.-linear-operator-inversion.pbtxt b/tensorflow/tools/api/golden/v2/tensorflow.linalg.-linear-operator-inversion.pbtxt
index 6379a67..2c059c5 100644
--- a/tensorflow/tools/api/golden/v2/tensorflow.linalg.-linear-operator-inversion.pbtxt
+++ b/tensorflow/tools/api/golden/v2/tensorflow.linalg.-linear-operator-inversion.pbtxt
@@ -51,6 +51,10 @@
mtype: "<type \'property\'>"
}
member {
+ name: "non_trainable_variables"
+ mtype: "<type \'property\'>"
+ }
+ member {
name: "operator"
mtype: "<type \'property\'>"
}
diff --git a/tensorflow/tools/api/golden/v2/tensorflow.linalg.-linear-operator-kronecker.pbtxt b/tensorflow/tools/api/golden/v2/tensorflow.linalg.-linear-operator-kronecker.pbtxt
index fda6139..f014040 100644
--- a/tensorflow/tools/api/golden/v2/tensorflow.linalg.-linear-operator-kronecker.pbtxt
+++ b/tensorflow/tools/api/golden/v2/tensorflow.linalg.-linear-operator-kronecker.pbtxt
@@ -51,6 +51,10 @@
mtype: "<type \'property\'>"
}
member {
+ name: "non_trainable_variables"
+ mtype: "<type \'property\'>"
+ }
+ member {
name: "operators"
mtype: "<type \'property\'>"
}
diff --git a/tensorflow/tools/api/golden/v2/tensorflow.linalg.-linear-operator-low-rank-update.pbtxt b/tensorflow/tools/api/golden/v2/tensorflow.linalg.-linear-operator-low-rank-update.pbtxt
index c07a18eb..767007fb 100644
--- a/tensorflow/tools/api/golden/v2/tensorflow.linalg.-linear-operator-low-rank-update.pbtxt
+++ b/tensorflow/tools/api/golden/v2/tensorflow.linalg.-linear-operator-low-rank-update.pbtxt
@@ -67,6 +67,10 @@
mtype: "<type \'property\'>"
}
member {
+ name: "non_trainable_variables"
+ mtype: "<type \'property\'>"
+ }
+ member {
name: "parameters"
mtype: "<type \'property\'>"
}
diff --git a/tensorflow/tools/api/golden/v2/tensorflow.linalg.-linear-operator-lower-triangular.pbtxt b/tensorflow/tools/api/golden/v2/tensorflow.linalg.-linear-operator-lower-triangular.pbtxt
index 39e44ed..809a560 100644
--- a/tensorflow/tools/api/golden/v2/tensorflow.linalg.-linear-operator-lower-triangular.pbtxt
+++ b/tensorflow/tools/api/golden/v2/tensorflow.linalg.-linear-operator-lower-triangular.pbtxt
@@ -51,6 +51,10 @@
mtype: "<type \'property\'>"
}
member {
+ name: "non_trainable_variables"
+ mtype: "<type \'property\'>"
+ }
+ member {
name: "parameters"
mtype: "<type \'property\'>"
}
diff --git a/tensorflow/tools/api/golden/v2/tensorflow.linalg.-linear-operator-permutation.pbtxt b/tensorflow/tools/api/golden/v2/tensorflow.linalg.-linear-operator-permutation.pbtxt
index 228bfd4..8cd1381 100644
--- a/tensorflow/tools/api/golden/v2/tensorflow.linalg.-linear-operator-permutation.pbtxt
+++ b/tensorflow/tools/api/golden/v2/tensorflow.linalg.-linear-operator-permutation.pbtxt
@@ -51,6 +51,10 @@
mtype: "<type \'property\'>"
}
member {
+ name: "non_trainable_variables"
+ mtype: "<type \'property\'>"
+ }
+ member {
name: "parameters"
mtype: "<type \'property\'>"
}
diff --git a/tensorflow/tools/api/golden/v2/tensorflow.linalg.-linear-operator-scaled-identity.pbtxt b/tensorflow/tools/api/golden/v2/tensorflow.linalg.-linear-operator-scaled-identity.pbtxt
index 358c0f8..7a0fa4d 100644
--- a/tensorflow/tools/api/golden/v2/tensorflow.linalg.-linear-operator-scaled-identity.pbtxt
+++ b/tensorflow/tools/api/golden/v2/tensorflow.linalg.-linear-operator-scaled-identity.pbtxt
@@ -56,6 +56,10 @@
mtype: "<type \'property\'>"
}
member {
+ name: "non_trainable_variables"
+ mtype: "<type \'property\'>"
+ }
+ member {
name: "parameters"
mtype: "<type \'property\'>"
}
diff --git a/tensorflow/tools/api/golden/v2/tensorflow.linalg.-linear-operator-toeplitz.pbtxt b/tensorflow/tools/api/golden/v2/tensorflow.linalg.-linear-operator-toeplitz.pbtxt
index 7f863ce..cbbab4d 100644
--- a/tensorflow/tools/api/golden/v2/tensorflow.linalg.-linear-operator-toeplitz.pbtxt
+++ b/tensorflow/tools/api/golden/v2/tensorflow.linalg.-linear-operator-toeplitz.pbtxt
@@ -55,6 +55,10 @@
mtype: "<type \'property\'>"
}
member {
+ name: "non_trainable_variables"
+ mtype: "<type \'property\'>"
+ }
+ member {
name: "parameters"
mtype: "<type \'property\'>"
}
diff --git a/tensorflow/tools/api/golden/v2/tensorflow.linalg.-linear-operator-tridiag.pbtxt b/tensorflow/tools/api/golden/v2/tensorflow.linalg.-linear-operator-tridiag.pbtxt
index eadb8f0..b45a8fb 100644
--- a/tensorflow/tools/api/golden/v2/tensorflow.linalg.-linear-operator-tridiag.pbtxt
+++ b/tensorflow/tools/api/golden/v2/tensorflow.linalg.-linear-operator-tridiag.pbtxt
@@ -59,6 +59,10 @@
mtype: "<type \'property\'>"
}
member {
+ name: "non_trainable_variables"
+ mtype: "<type \'property\'>"
+ }
+ member {
name: "parameters"
mtype: "<type \'property\'>"
}
diff --git a/tensorflow/tools/api/golden/v2/tensorflow.linalg.-linear-operator-zeros.pbtxt b/tensorflow/tools/api/golden/v2/tensorflow.linalg.-linear-operator-zeros.pbtxt
index f905de2..3510ede 100644
--- a/tensorflow/tools/api/golden/v2/tensorflow.linalg.-linear-operator-zeros.pbtxt
+++ b/tensorflow/tools/api/golden/v2/tensorflow.linalg.-linear-operator-zeros.pbtxt
@@ -51,6 +51,10 @@
mtype: "<type \'property\'>"
}
member {
+ name: "non_trainable_variables"
+ mtype: "<type \'property\'>"
+ }
+ member {
name: "parameters"
mtype: "<type \'property\'>"
}
diff --git a/tensorflow/tools/api/golden/v2/tensorflow.linalg.-linear-operator.pbtxt b/tensorflow/tools/api/golden/v2/tensorflow.linalg.-linear-operator.pbtxt
index c9ee030..83df2d5 100644
--- a/tensorflow/tools/api/golden/v2/tensorflow.linalg.-linear-operator.pbtxt
+++ b/tensorflow/tools/api/golden/v2/tensorflow.linalg.-linear-operator.pbtxt
@@ -50,6 +50,10 @@
mtype: "<type \'property\'>"
}
member {
+ name: "non_trainable_variables"
+ mtype: "<type \'property\'>"
+ }
+ member {
name: "parameters"
mtype: "<type \'property\'>"
}
