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Add WeightNorm support for RNNs #769

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Dec 14, 2019
Merged

Add WeightNorm support for RNNs #769

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20 changes: 13 additions & 7 deletions tensorflow_addons/layers/wrappers.py
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Original file line number Diff line number Diff line change
Expand Up @@ -58,31 +58,34 @@ def __init__(self, layer, data_init=True, **kwargs):
super(WeightNormalization, self).__init__(layer, **kwargs)
self.data_init = data_init
self._track_trackable(layer, name='layer')
self.is_rnn = isinstance(self.layer, tf.keras.layers.RNN)

def build(self, input_shape):
"""Build `Layer`"""
input_shape = tf.TensorShape(input_shape).as_list()
input_shape = tf.TensorShape(input_shape)
self.input_spec = tf.keras.layers.InputSpec(
shape=[None] + input_shape[1:])

if not self.layer.built:
self.layer.build(input_shape)

if not hasattr(self.layer, 'kernel'):
kernel_layer = self.layer.cell if self.is_rnn else self.layer

if not hasattr(kernel_layer, 'kernel'):
raise ValueError('`WeightNormalization` must wrap a layer that'
' contains a `kernel` for weights')

# The kernel's filter or unit dimension is -1
self.layer_depth = int(self.layer.kernel.shape[-1])
self.kernel_norm_axes = list(range(self.layer.kernel.shape.rank - 1))
self.layer_depth = int(kernel_layer.kernel.shape[-1])
self.kernel_norm_axes = list(range(kernel_layer.kernel.shape.rank - 1))

self.g = self.add_weight(
name='g',
shape=(self.layer_depth,),
initializer='ones',
dtype=self.layer.kernel.dtype,
dtype=kernel_layer.kernel.dtype,
trainable=True)
self.v = self.layer.kernel
self.v = kernel_layer.kernel

self._initialized = self.add_weight(
name='initialized',
Expand All @@ -100,7 +103,10 @@ def build(self, input_shape):
layer_config)
self._naked_clone_layer.build(input_shape)
self._naked_clone_layer.set_weights(self.layer.get_weights())
self._naked_clone_layer.activation = None
if self.is_rnn:
self._naked_clone_layer.cell.activation = None
else:
self._naked_clone_layer.activation = None

self.built = True

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7 changes: 7 additions & 0 deletions tensorflow_addons/layers/wrappers_test.py
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Original file line number Diff line number Diff line change
Expand Up @@ -89,6 +89,13 @@ def test_weightnorm_with_time_dist(self):
out = tf.keras.layers.TimeDistributed(b)(inputs)
model = tf.keras.Model(inputs, out)

def test_weightnorm_with_rnn(self):
inputs = tf.keras.layers.Input(shape=(None, 3))
rnn_layer = tf.keras.layers.SimpleRNN(4)
wt_rnn = wrappers.WeightNormalization(rnn_layer)
dense = tf.keras.layers.Dense(1)
model = tf.keras.models.Sequential(layers=[inputs, wt_rnn, dense])

def test_save_file_h5(self):
self.create_tempfile('wrapper_test_model.h5')
conv = tf.keras.layers.Conv1D(1, 1)
Expand Down