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initializations -> initializers

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farizrahman4u
2017-03-19 09:19:51 +05:30
parent de4ab68ed2
commit 1128d8767a
2 changed files with 15 additions and 15 deletions
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keras_contrib/layers/core.py
+10 -10
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@@ -50,7 +50,7 @@ class CosineDense(Layer):
# Arguments
units: Positive integer, dimensionality of the output space.
init: name of initialization function for the weights of the layer
(see [initializations](../initializations.md)),
(see [initializers](../initializers.md)),
or alternatively, Theano function to use for weights
initialization. This parameter is only relevant
if you don't pass a `weights` argument.
@@ -94,7 +94,7 @@ class CosineDense(Layer):
kernel_regularizer=None, bias_regularizer=None, activity_regularizer=None,
kernel_constraint=None, bias_constraint=None,
use_bias=True, input_dim=None, **kwargs):
self.init = initializations.get(init)
self.init = initializers.get(init)
self.activation = activations.get(activation)
self.units = units
self.input_dim = input_dim
@@ -122,16 +122,16 @@ class CosineDense(Layer):
ndim='2+')]
self.kernel = self.add_weight((input_dim, self.units),
initializer=self.init,
name='{}_W'.format(self.name),
regularizer=self.kernel_regularizer,
constraint=self.kernel_constraint)
initializer=self.init,
name='{}_W'.format(self.name),
regularizer=self.kernel_regularizer,
constraint=self.kernel_constraint)
if self.use_bias:
self.bias = self.add_weight((self.units,),
initializer='zero',
name='{}_b'.format(self.name),
regularizer=self.bias_regularizer,
constraint=self.bias_constraint)
initializer='zero',
name='{}_b'.format(self.name),
regularizer=self.bias_regularizer,
constraint=self.bias_constraint)
else:
self.bias = None
tests/keras_contrib/layers/test_core.py
+5 -5
View File
@@ -15,23 +15,23 @@ def test_cosinedense():
from keras.models import Sequential
layer_test(core.CosineDense,
kwargs={'output_dim': 3},
kwargs={'units': 3},
input_shape=(3, 2))
layer_test(core.CosineDense,
kwargs={'output_dim': 3},
kwargs={'units': 3},
input_shape=(3, 4, 2))
layer_test(core.CosineDense,
kwargs={'output_dim': 3},
kwargs={'units': 3},
input_shape=(None, None, 2))
layer_test(core.CosineDense,
kwargs={'output_dim': 3},
kwargs={'units': 3},
input_shape=(3, 4, 5, 2))
layer_test(core.CosineDense,
kwargs={'output_dim': 3,
kwargs={'units': 3,
'W_regularizer': regularizers.l2(0.01),
'b_regularizer': regularizers.l1(0.01),
'activity_regularizer': regularizers.activity_l2(0.01),