Searched refs:prev_output (Results 1 – 5 of 5) sorted by relevance
| /external/tensorflow/tensorflow/python/keras/layers/ |
| D | recurrent_test.py | 71 prev_output = states[0]
72 output = keras.backend.dot(inputs, self.kernel) + prev_output
165 prev_output = states[0]
167 output = h + keras.backend.dot(prev_output, self.recurrent_kernel)
249 prev_output = states[0]
251 output = h + keras.backend.dot(prev_output, self.recurrent_kernel)
409 [prev_output] = states
412 h_state = keras.backend.dot(prev_output, self.recurrent_kernel)
539 [prev_output] = states
542 h_state = keras.backend.dot(prev_output, self.recurrent_kernel)
[all …]
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| D | recurrent.py | 1233 prev_output = states[0]
1236 prev_output, training)
1246 prev_output *= rec_dp_mask
1247 output = h + K.dot(prev_output, self.recurrent_kernel)
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| D | wrappers_test.py | 59 [prev_output] = states
62 h_state = keras.backend.dot(prev_output, self.recurrent_kernel)
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| /external/tensorflow/tensorflow/python/keras/ |
| D | backend.py | 3447 prev_output = zeros_like(output)
3449 prev_output = successive_outputs[-1]
3451 output = array_ops.where(tiled_mask_t, output, prev_output)
3548 def _step(time, output_ta_t, prev_output, *states): argument
3569 else nest.flatten(prev_output))
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| D | backend_test.py | 1023 prev_output = states[0]
1024 output = keras.backend.dot(x, w_i) + keras.backend.dot(prev_output, w_o)
1113 prev_output = states[0]
1114 output = keras.backend.dot(x, w_i) + keras.backend.dot(prev_output, w_o)
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