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Fix WeightNormalization wrapped layer has use_biase=False #696

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Merged
merged 1 commit into from
Nov 13, 2019
Merged

Fix WeightNormalization wrapped layer has use_biase=False #696

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2 changes: 1 addition & 1 deletion tensorflow_addons/layers/wrappers.py
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Original file line number Diff line number Diff line change
Expand Up @@ -168,7 +168,7 @@ def _data_dep_init(self, inputs):

# Assign data dependent init values
g_tensor = self.g.assign(self.g * scale_init)
if hasattr(self.layer, 'bias'):
if hasattr(self.layer, 'bias') and self.layer.bias is not None:
bias_tensor = self.layer.bias.assign(-m_init * scale_init)
return [g_tensor, bias_tensor]
else:
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8 changes: 8 additions & 0 deletions tensorflow_addons/layers/wrappers_test.py
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Expand Up @@ -34,6 +34,14 @@ def test_weightnorm(self):
},
input_shape=(2, 4, 4, 3))

def test_weightnorm_no_bias(self):
test_utils.layer_test(
wrappers.WeightNormalization,
kwargs={
'layer': tf.keras.layers.Dense(5, use_bias=False),
},
input_shape=(2, 4))

def _check_data_init(self, data_init, input_data, expected_output):
layer = tf.keras.layers.Dense(
input_data.shape[-1],
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