| /external/tensorflow/tensorflow/python/keras/layers/ |
| D | cudnn_recurrent.py | 57 return_sequences=False, argument
66 self.return_sequences = return_sequences
126 'return_sequences': self.return_sequences,
211 return_sequences=False, argument
220 return_sequences=return_sequences,
310 if self.return_sequences:
396 return_sequences=False, argument
405 return_sequences=return_sequences,
512 if self.return_sequences:
|
| D | convolutional_recurrent_test.py | 36 return_sequences=[True, False]))
37 def test_conv_lstm(self, data_format, return_sequences): argument
58 'return_sequences': return_sequences,
79 'return_sequences': return_sequences,
210 return_sequences=False, return_state=True)
217 return_sequences=False, return_state=False)
|
| D | serialization_test.py | 142 lstm = layer(5, return_sequences=True)
147 self.assertEqual(new_layer.return_sequences, True)
156 gru = layer(5, return_sequences=True)
161 self.assertEqual(new_layer.return_sequences, True)
|
| D | cudnn_recurrent_test.py | 45 return_sequences=[True, False]))
47 def test_cudnn_rnn_return_sequence(self, layer_class, return_sequences): argument
55 'return_sequences': return_sequences},
113 layer = layer_class(units, time_major=True, return_sequences=True)
177 return_sequences=False,
187 return_sequences=False,
217 units, return_sequences=False, stateful=True, weights=None)
431 rnn(output_dim, return_sequences=True),
|
| D | gru_v2_test.py | 139 model.add(rnn.GRU(10, return_sequences=True, unroll=False))
140 model.add(rnn.GRU(5, return_sequences=True, unroll=False))
303 return_sequences=True,
337 model.add(layer_class(units=5, return_sequences=True, unroll=False))
352 model.add(rnn.GRU(10, return_sequences=True, unroll=False))
353 model.add(rnn.GRU(5, return_sequences=True, unroll=False))
426 return_sequences=False,
454 return_sequences=False,
490 units, return_sequences=False, stateful=True, weights=None)
561 rnn.GRU(units, return_sequences=True, stateful=True),
[all …]
|
| D | lstm_test.py | 75 layer = keras.layers.LSTM(units, return_sequences=True)
134 return_sequences=False,
156 model.add(layer_class(units=5, return_sequences=True, unroll=unroll))
172 lstm_cells, return_sequences=True, unroll=unroll))
327 layer = keras.layers.LSTM(units, return_state=True, return_sequences=True)
372 return_sequences=False,
406 units, return_sequences=False, stateful=True, weights=None)
|
| D | simplernn_test.py | 108 return_sequences=False,
126 model.add(layer_class(units=5, return_sequences=True, unroll=False))
148 return_sequences=False,
180 units, return_sequences=False, stateful=True, weights=None)
|
| D | lstm_v2_test.py | 102 layer = rnn.LSTM(units, return_sequences=True)
125 model.add(rnn.LSTM(10, return_sequences=True, unroll=False))
126 model.add(rnn.LSTM(5, return_sequences=True, unroll=False))
287 units, return_state=True, return_sequences=True)
397 return_sequences=False,
414 model.add(layer_class(units=5, return_sequences=True, unroll=False))
429 model.add(rnn.LSTM(10, return_sequences=True, unroll=False))
430 model.add(rnn.LSTM(5, return_sequences=True, unroll=False))
457 return_sequences=True,
619 return_sequences=False,
[all …]
|
| D | gru_test.py | 145 model.add(layer_class(units=5, return_sequences=True, unroll=False))
170 units, return_sequences=False, stateful=True, weights=None)
239 return_sequences=False,
268 return_sequences=False,
|
| D | convolutional_recurrent.py | 159 return_sequences=False, argument
173 return_sequences,
211 if not self.return_sequences:
339 if self.return_sequences:
360 if self.return_sequences:
849 return_sequences=False, argument
879 return_sequences=return_sequences,
|
| D | recurrent_v2_test.py | 59 layer(units, return_sequences=True, stateful=True),
101 layer(128, stateful=True, return_sequences=True, dropout=0.2,
|
| D | recurrent_test.py | 296 units, time_major=True, return_sequences=True)
321 layer = keras.layers.RNN(cells, time_major=True, return_sequences=True)
341 units, time_major=True, return_sequences=True)(mask)
354 rnn_1 = keras.layers.SimpleRNN(units, return_sequences=True)
372 units, time_major=True, return_sequences=True)
660 return_sequences=True,
807 return_sequences=True,
814 return_sequences=True,
826 return_sequences=True,
859 layer = keras.layers.RNN(cells, return_state=True, return_sequences=True)
[all …]
|
| D | recurrent_v2.py | 366 return_sequences=False, argument
396 return_sequences=return_sequences,
467 if self.return_sequences:
1090 return_sequences=False, argument
1120 return_sequences=return_sequences,
1279 if self.return_sequences:
|
| D | recurrent.py | 396 return_sequences=False, argument
425 self.return_sequences = return_sequences
495 if self.return_sequences:
531 output_mask = mask if self.return_sequences else None
825 if self.return_sequences:
977 'return_sequences': self.return_sequences,
1539 return_sequences=False, argument
1575 return_sequences=return_sequences,
2071 return_sequences=False, argument
2111 return_sequences=return_sequences,
[all …]
|
| D | wrappers.py | 498 layer.zero_output_for_mask = layer.return_sequences
509 self.return_sequences = layer.return_sequences
714 if self.return_sequences:
751 if self.return_sequences:
|
| D | wrappers_test.py | 251 keras.layers.SimpleRNN(7, return_sequences=True)))
253 keras.layers.SimpleRNN(8, return_sequences=False)))
254 model.add(keras.layers.SimpleRNN(1, return_sequences=False))
382 rnn_layer = keras.layers.LSTM(4, return_sequences=True, stateful=True)
616 rnn(output_dim, return_sequences=True),
691 rnn(units, return_sequences=True), merge_mode=merge_mode)
744 forward_cell, time_major=time_major, return_sequences=True),
746 backward_cell, time_major=time_major, return_sequences=True,
800 rnn(units, return_state=True, return_sequences=True))
829 rnn(units, return_state=True, return_sequences=True))
[all …]
|
| /external/rnnoise/training/ |
| D | rnn_train.py | 65 vad_gru = GRU(24, activation='tanh', recurrent_activation='sigmoid', return_sequences=True, name='v…
68 noise_gru = GRU(48, activation='relu', recurrent_activation='sigmoid', return_sequences=True, name=…
71 denoise_gru = GRU(96, activation='tanh', recurrent_activation='sigmoid', return_sequences=True, nam…
|
| /external/tensorflow/tensorflow/python/keras/utils/ |
| D | vis_utils_test.py | 48 lstm = keras.layers.LSTM(6, return_sequences=True, name='lstm')
52 keras.layers.LSTM(16, return_sequences=True, name='bilstm'))
|
| /external/tensorflow/tensorflow/python/keras/tests/ |
| D | model_architectures.py | 60 x = keras.layers.LSTM(4, return_sequences=True)(inputs)
61 x = keras.layers.LSTM(3, return_sequences=True)(x)
62 x = keras.layers.LSTM(2, return_sequences=False)(x)
110 latent_dim, return_sequences=True, return_state=True)
|
| /external/rnnoise/src/ |
| D | rnn_train.py | 24 x = GRU(128, activation='tanh', recurrent_activation='sigmoid', return_sequences=True)(x)
|
| /external/libopus/scripts/ |
| D | rnn_train.py | 30 …recurrent_dropout=0.1, activation='tanh', recurrent_activation='sigmoid', return_sequences=True)(x)
|
| /external/libopus/training/ |
| D | rnn_dump.py | 42 x = GRU(24, activation='tanh', recurrent_activation='sigmoid', return_sequences=True)(x)
|
| /external/tensorflow/tensorflow/python/keras/benchmarks/ |
| D | optimizer_benchmarks_test.py | 34 tf.keras.layers.LSTM(64, return_sequences=True))(
|
| /external/tensorflow/tensorflow/python/keras/distribute/ |
| D | keras_stateful_lstm_model_correctness_test.py | 66 units=4, return_sequences=False, stateful=True)(
|
| D | keras_rnn_model_correctness_test.py | 55 rnn_embed = rnn_cls(units=4, return_sequences=False)(word_embed)
|