def testWrapperWeights(self, wrapper):
"""Tests that wrapper weights contain wrapped cells weights."""
base_cell = layers.SimpleRNNCell(1, name="basic_rnn_cell")
rnn_cell = wrapper(base_cell)
rnn_layer = layers.RNN(rnn_cell)
inputs = tf.convert_to_tensor([[[1]]], dtype=tf.float32)
rnn_layer(inputs)
wrapper_name = generic_utils.to_snake_case(wrapper.__name__)
expected_weights = [
"rnn/" + wrapper_name + "/" + var
for var in ("kernel:0", "recurrent_kernel:0", "bias:0")
]
self.assertLen(rnn_cell.weights, 3)
self.assertCountEqual(
[v.name for v in rnn_cell.weights], expected_weights
)
self.assertCountEqual(
[v.name for v in rnn_cell.trainable_variables], expected_weights
)
self.assertCountEqual(
[v.name for v in rnn_cell.non_trainable_variables], []
)
self.assertCountEqual(
[v.name for v in rnn_cell.cell.weights], expected_weights
)
def get_custom_object_name(obj):
"""Returns the name to use for a custom loss or metric callable.
Args:
obj: Custom loss of metric callable
Returns:
Name to use, or `None` if the object was not recognized.
"""
if hasattr(obj, 'name'): # Accept `Loss` instance as `Metric`.
return obj.name
elif hasattr(obj, '__name__'): # Function.
return obj.__name__
elif hasattr(obj, '__class__'): # Class instance.
return generic_utils.to_snake_case(obj.__class__.__name__)
else: # Unrecognized object.
return None
def test_snake_case(self):
self.assertEqual(generic_utils.to_snake_case('SomeClass'),
'some_class')
self.assertEqual(generic_utils.to_snake_case('Conv2D'), 'conv2d')
self.assertEqual(generic_utils.to_snake_case('ConvLSTM2D'),
'conv_lstm2d')
def test_snake_case(self):
self.assertEqual(generic_utils.to_snake_case("SomeClass"),
"some_class")
self.assertEqual(generic_utils.to_snake_case("Conv2D"), "conv2d")
self.assertEqual(generic_utils.to_snake_case("ConvLSTM2D"),
"conv_lstm2d")
def populate_deserializable_objects():
"""Populates dict ALL_OBJECTS with every built-in initializer."""
global LOCAL
if not hasattr(LOCAL, "ALL_OBJECTS"):
LOCAL.ALL_OBJECTS = {}
LOCAL.GENERATED_WITH_V2 = None
if (LOCAL.ALL_OBJECTS
and LOCAL.GENERATED_WITH_V2 == tf.__internal__.tf2.enabled()):
# Objects dict is already generated for the proper TF version:
# do nothing.
return
LOCAL.ALL_OBJECTS = {}
LOCAL.GENERATED_WITH_V2 = tf.__internal__.tf2.enabled()
# Compatibility aliases (need to exist in both V1 and V2).
LOCAL.ALL_OBJECTS["ConstantV2"] = initializers_v2.Constant
LOCAL.ALL_OBJECTS["GlorotNormalV2"] = initializers_v2.GlorotNormal
LOCAL.ALL_OBJECTS["GlorotUniformV2"] = initializers_v2.GlorotUniform
LOCAL.ALL_OBJECTS["HeNormalV2"] = initializers_v2.HeNormal
LOCAL.ALL_OBJECTS["HeUniformV2"] = initializers_v2.HeUniform
LOCAL.ALL_OBJECTS["IdentityV2"] = initializers_v2.Identity
LOCAL.ALL_OBJECTS["LecunNormalV2"] = initializers_v2.LecunNormal
LOCAL.ALL_OBJECTS["LecunUniformV2"] = initializers_v2.LecunUniform
LOCAL.ALL_OBJECTS["OnesV2"] = initializers_v2.Ones
LOCAL.ALL_OBJECTS["OrthogonalV2"] = initializers_v2.Orthogonal
LOCAL.ALL_OBJECTS["RandomNormalV2"] = initializers_v2.RandomNormal
LOCAL.ALL_OBJECTS["RandomUniformV2"] = initializers_v2.RandomUniform
LOCAL.ALL_OBJECTS["TruncatedNormalV2"] = initializers_v2.TruncatedNormal
LOCAL.ALL_OBJECTS["VarianceScalingV2"] = initializers_v2.VarianceScaling
LOCAL.ALL_OBJECTS["ZerosV2"] = initializers_v2.Zeros
# Out of an abundance of caution we also include these aliases that have
# a non-zero probability of having been included in saved configs in the past.
LOCAL.ALL_OBJECTS["glorot_normalV2"] = initializers_v2.GlorotNormal
LOCAL.ALL_OBJECTS["glorot_uniformV2"] = initializers_v2.GlorotUniform
LOCAL.ALL_OBJECTS["he_normalV2"] = initializers_v2.HeNormal
LOCAL.ALL_OBJECTS["he_uniformV2"] = initializers_v2.HeUniform
LOCAL.ALL_OBJECTS["lecun_normalV2"] = initializers_v2.LecunNormal
LOCAL.ALL_OBJECTS["lecun_uniformV2"] = initializers_v2.LecunUniform
if tf.__internal__.tf2.enabled():
# For V2, entries are generated automatically based on the content of
# initializers_v2.py.
v2_objs = {}
base_cls = initializers_v2.Initializer
generic_utils.populate_dict_with_module_objects(
v2_objs,
[initializers_v2],
obj_filter=lambda x: inspect.isclass(x) and issubclass(
x, base_cls),
)
for key, value in v2_objs.items():
LOCAL.ALL_OBJECTS[key] = value
# Functional aliases.
LOCAL.ALL_OBJECTS[generic_utils.to_snake_case(key)] = value
else:
# V1 initializers.
v1_objs = {
"Constant": tf.compat.v1.constant_initializer,
"GlorotNormal": tf.compat.v1.glorot_normal_initializer,
"GlorotUniform": tf.compat.v1.glorot_uniform_initializer,
"Identity": tf.compat.v1.initializers.identity,
"Ones": tf.compat.v1.ones_initializer,
"Orthogonal": tf.compat.v1.orthogonal_initializer,
"VarianceScaling": tf.compat.v1.variance_scaling_initializer,
"Zeros": tf.compat.v1.zeros_initializer,
"HeNormal": initializers_v1.HeNormal,
"HeUniform": initializers_v1.HeUniform,
"LecunNormal": initializers_v1.LecunNormal,
"LecunUniform": initializers_v1.LecunUniform,
"RandomNormal": initializers_v1.RandomNormal,
"RandomUniform": initializers_v1.RandomUniform,
"TruncatedNormal": initializers_v1.TruncatedNormal,
}
for key, value in v1_objs.items():
LOCAL.ALL_OBJECTS[key] = value
# Functional aliases.
LOCAL.ALL_OBJECTS[generic_utils.to_snake_case(key)] = value
# More compatibility aliases.
LOCAL.ALL_OBJECTS["normal"] = LOCAL.ALL_OBJECTS["random_normal"]
LOCAL.ALL_OBJECTS["uniform"] = LOCAL.ALL_OBJECTS["random_uniform"]
LOCAL.ALL_OBJECTS["one"] = LOCAL.ALL_OBJECTS["ones"]
LOCAL.ALL_OBJECTS["zero"] = LOCAL.ALL_OBJECTS["zeros"]
def __init__(self, seed=None):
super().__init__(scale=2.,
mode='fan_in',
distribution='uniform',
seed=seed)
def get_config(self):
return {'seed': self.seed}
# Populate all initializers with their string names.
_ALL_INITIALIZERS = {}
for name, obj in inspect.getmembers(sys.modules[__name__]):
if inspect.isclass(obj) and issubclass(obj, initializers_v2.Initializer):
_ALL_INITIALIZERS[name] = obj
alternative_name = generic_utils.to_snake_case(name)
_ALL_INITIALIZERS[alternative_name] = obj
def serialize(initializer):
return generic_utils.serialize_keras_object(initializer)
def deserialize(config, custom_objects=None):
"""Return an `Initializer` object from its config."""
return generic_utils.deserialize_keras_object(
config,
module_objects=_ALL_INITIALIZERS,
custom_objects=custom_objects,
printable_module_name='initializer')
