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  /external/tensorflow/tensorflow/python/keras/layers/
serialization_test.py 86 @parameterized.parameters([rnn_v1.GRU, rnn_v2.GRU])
88 gru = layer(5, return_sequences=True)
89 config = keras.layers.serialize(gru)
90 self.assertEqual(config['class_name'], 'GRU')
95 self.assertIsInstance(new_layer, rnn_v2.GRU)
97 self.assertIsInstance(new_layer, rnn_v1.GRU)
98 self.assertNotIsInstance(new_layer, rnn_v2.GRU)
gru_test.py 15 """Tests for GRU layer."""
41 keras.layers.GRU,
51 layer = keras.layers.GRU(units, input_shape=(None, embedding_dim))
66 keras.layers.GRU,
79 keras.layers.GRU,
98 gru_layer = keras.layers.GRU(units,
108 layer_class = keras.layers.GRU
126 layer_class = keras.layers.GRU
190 layer_class = keras.layers.GRU
208 layer_class = keras.layers.GRU
    [all...]
gru_v2_test.py 72 layer = rnn.GRU(1,
96 layer = rnn.GRU(rnn_state_size)
113 layer = rnn.GRU(units, input_shape=(None, embedding_dim))
126 model.add(rnn.GRU(10, return_sequences=True, unroll=False))
127 model.add(rnn.GRU(5, return_sequences=True, unroll=False))
134 layer_class = rnn.GRU
157 gru_layer = rnn_v1.GRU(rnn_state_size,
169 cudnn_layer = rnn.GRU(rnn_state_size,
203 layer = rnn.GRU(
232 layer = rnn.GRU(rnn_state_size
    [all...]
recurrent_v2_test.py 15 """Tests for recurrent v2 layers functionality other than GRU, LSTM.
39 @parameterized.parameters([rnn_v2.LSTM, rnn_v2.GRU])
cudnn_recurrent_test.py 266 rnn_type=['LSTM', 'GRU'], to_cudnn=[True, False],
291 rnn_layer_class = keras.layers.GRU
347 rnn_type=['LSTM', 'GRU'], to_cudnn=[True, False]))
371 rnn_layer_class = keras.layers.GRU
455 def gru(cudnn=False, **kwargs): function in function:CuDNNV1OnlyTest.test_preprocess_weights_for_loading_gru_incompatible
456 layer_class = keras.layers.CuDNNGRU if cudnn else keras.layers.GRU
471 gru(),
472 gru(cudnn=True),
473 'GRU(reset_after=False) is not compatible with CuDNNGRU')
475 gru(cudnn=True)
    [all...]
__init__.py 157 from tensorflow.python.keras.layers.recurrent import GRU
159 from tensorflow.python.keras.layers.recurrent_v2 import GRU as GRU_v2
recurrent_v2.py 39 # of LSTM and GRU.
46 @keras_export('keras.layers.GRU', v1=[])
47 class GRU(recurrent.DropoutRNNCellMixin, recurrent.GRU):
66 There are two variants of the GRU implementation. The default one is based on
133 reset_after: GRU convention (whether to apply reset gate after or
179 super(GRU, self).__init__(
212 # GRU does not support constants. Ignore it during process.
222 # CuDNN does not support masking, fall back to use the normal GRU.
302 # Call the normal GRU impl and register the CuDNN impl function. Th
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recurrent.py     [all...]
recurrent_test.py 15 """Tests for recurrent layers functionality other than GRU, LSTM, SimpleRNN.
735 layer=[rnn_v1.SimpleRNN, rnn_v1.GRU, rnn_v1.LSTM,
736 rnn_v2.GRU, rnn_v2.LSTM],
    [all...]
  /external/libopus/scripts/
rnn_train.py 10 from keras.layers import GRU
25 #model.add(GRU(12, dropout=0.0, recurrent_dropout=0.0, activation='tanh', recurrent_activation='sigmoid', return_sequences=True))
30 x = GRU(12, dropout=0.1, recurrent_dropout=0.1, activation='tanh', recurrent_activation='sigmoid', return_sequences=True)(x)
dump_rnn.py 8 from keras.layers import GRU
  /external/tensorflow/tensorflow/python/keras/
integration_test.py 122 keras.layers.GRU(y_train.shape[-1], activation='softmax')
  /external/tensorflow/tensorflow/contrib/keras/api/keras/layers/
__init__.py 138 from tensorflow.python.keras.layers.recurrent import GRU
  /external/tensorflow/tensorflow/python/keras/saving/
hdf5_format_test.py 148 (keras.layers.GRU(output_dim)),
193 ('gru', keras.layers.GRU, {
197 ('gru_with_reset_after', keras.layers.GRU, {
    [all...]

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