| /external/tensorflow/tensorflow/python/keras/layers/ |
| D | recurrent.py | 1741 recurrent_activation='hard_sigmoid', argument
1764 self.recurrent_activation = activations.get(recurrent_activation)
1879 z = self.recurrent_activation(x_z + recurrent_z)
1880 r = self.recurrent_activation(x_r + recurrent_r)
1917 z = self.recurrent_activation(x_z + recurrent_z)
1918 r = self.recurrent_activation(x_r + recurrent_r)
1937 activations.serialize(self.recurrent_activation),
2057 recurrent_activation='hard_sigmoid', argument
2091 recurrent_activation=recurrent_activation,
2133 def recurrent_activation(self): member in GRU
[all …]
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| D | convolutional_recurrent.py | 499 recurrent_activation='hard_sigmoid', argument
523 self.recurrent_activation = activations.get(recurrent_activation)
643 i = self.recurrent_activation(x_i + h_i)
644 f = self.recurrent_activation(x_f + h_f)
646 o = self.recurrent_activation(x_o + h_o)
675 self.recurrent_activation),
836 recurrent_activation='hard_sigmoid', argument
863 recurrent_activation=recurrent_activation,
921 def recurrent_activation(self): member in ConvLSTM2D
922 return self.cell.recurrent_activation
[all …]
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| D | recurrent_v2.py | 184 recurrent_activation='sigmoid', argument
202 recurrent_activation=recurrent_activation,
352 recurrent_activation='sigmoid', argument
381 recurrent_activation=recurrent_activation,
407 self.recurrent_activation in (activations.sigmoid, nn.sigmoid) and
922 recurrent_activation='sigmoid', argument
940 recurrent_activation=recurrent_activation,
1075 recurrent_activation='sigmoid', argument
1104 recurrent_activation=recurrent_activation,
1133 self.recurrent_activation in (activations.sigmoid, nn.sigmoid) and
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| D | gru_v2_test.py | 74 def test_could_use_defun_backend(self, activation, recurrent_activation, argument
79 recurrent_activation=recurrent_activation,
91 layer = rnn.GRU(1, recurrent_activation=nn.sigmoid)
180 recurrent_activation='sigmoid',
192 recurrent_activation='sigmoid',
272 recurrent_activation='sigmoid',
301 recurrent_activation='sigmoid',
684 recurrent_activation='sigmoid',
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| D | lstm_v2_test.py | 73 def test_could_use_defun_backend(self, activation, recurrent_activation, argument
78 recurrent_activation=recurrent_activation,
89 layer = rnn.LSTM(1, recurrent_activation=nn.sigmoid)
353 recurrent_activation='sigmoid')
455 recurrent_activation='sigmoid',
572 layer = rnn_v1.LSTM(rnn_state_size, recurrent_activation='sigmoid')
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| D | recurrent_test.py | 1285 recurrent_activation='sigmoid',
1290 recurrent_activation='sigmoid',
1295 recurrent_activation='sigmoid',
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| /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…
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| /external/rnnoise/src/ |
| D | rnn_train.py | 24 x = GRU(128, activation='tanh', recurrent_activation='sigmoid', return_sequences=True)(x)
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| /external/libopus/scripts/ |
| D | rnn_train.py | 30 x = GRU(12, dropout=0.1, recurrent_dropout=0.1, activation='tanh', recurrent_activation='sigmoid', …
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| /external/libopus/training/ |
| D | rnn_dump.py | 42 x = GRU(24, activation='tanh', recurrent_activation='sigmoid', return_sequences=True)(x)
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| D | rnn_train.py | 61 x = GRU(24, recurrent_activation='sigmoid', activation='tanh', return_sequences=True, kernel_constr…
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| /external/tensorflow/tensorflow/tools/api/golden/v1/ |
| D | tensorflow.keras.layers.-g-r-u.pbtxt | 128 name: "recurrent_activation"
205 …argspec: "args=[\'self\', \'units\', \'activation\', \'recurrent_activation\', \'use_bias\', \'ker…
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| D | tensorflow.keras.layers.-l-s-t-m.pbtxt | 128 name: "recurrent_activation"
205 …argspec: "args=[\'self\', \'units\', \'activation\', \'recurrent_activation\', \'use_bias\', \'ker…
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| D | tensorflow.keras.layers.-conv-l-s-t-m2-d.pbtxt | 145 name: "recurrent_activation"
222 …'padding\', \'data_format\', \'dilation_rate\', \'activation\', \'recurrent_activation\', \'use_bi…
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| D | tensorflow.keras.layers.-l-s-t-m-cell.pbtxt | 133 …argspec: "args=[\'self\', \'units\', \'activation\', \'recurrent_activation\', \'use_bias\', \'ker…
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| D | tensorflow.keras.experimental.-peephole-l-s-t-m-cell.pbtxt | 134 …argspec: "args=[\'self\', \'units\', \'activation\', \'recurrent_activation\', \'use_bias\', \'ker…
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| D | tensorflow.keras.layers.-g-r-u-cell.pbtxt | 133 …argspec: "args=[\'self\', \'units\', \'activation\', \'recurrent_activation\', \'use_bias\', \'ker…
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| /external/tensorflow/tensorflow/tools/api/golden/v2/ |
| D | tensorflow.keras.layers.-g-r-u.pbtxt | 130 name: "recurrent_activation"
207 …argspec: "args=[\'self\', \'units\', \'activation\', \'recurrent_activation\', \'use_bias\', \'ker…
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| D | tensorflow.keras.layers.-conv-l-s-t-m2-d.pbtxt | 145 name: "recurrent_activation"
222 …'padding\', \'data_format\', \'dilation_rate\', \'activation\', \'recurrent_activation\', \'use_bi…
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| D | tensorflow.keras.layers.-l-s-t-m.pbtxt | 130 name: "recurrent_activation"
207 …argspec: "args=[\'self\', \'units\', \'activation\', \'recurrent_activation\', \'use_bias\', \'ker…
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| D | tensorflow.keras.layers.-l-s-t-m-cell.pbtxt | 134 …argspec: "args=[\'self\', \'units\', \'activation\', \'recurrent_activation\', \'use_bias\', \'ker…
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| D | tensorflow.keras.layers.-g-r-u-cell.pbtxt | 134 …argspec: "args=[\'self\', \'units\', \'activation\', \'recurrent_activation\', \'use_bias\', \'ker…
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| D | tensorflow.keras.experimental.-peephole-l-s-t-m-cell.pbtxt | 134 …argspec: "args=[\'self\', \'units\', \'activation\', \'recurrent_activation\', \'use_bias\', \'ker…
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| /external/tensorflow/ |
| D | RELEASE.md | 1826 …r 1.x pre-trained checkpoint, please construct the layer with GRU(recurrent_activation='hard_sigmo…
2465 GRU(recurrent_activation='hard_sigmoid', reset_after=False) to fallback
2675 construct the layer with LSTM(recurrent_activation='hard_sigmoid') to
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