Searched refs:cell_inputs (Results 1 – 6 of 6) sorted by relevance
/external/tensorflow/tensorflow/python/keras/layers/ |
D | recurrent_v2.py | 225 def step(cell_inputs, cell_states): argument 226 return self.cell.call(cell_inputs, cell_states, **kwargs) 358 def step(cell_inputs, cell_states): argument 363 matrix_x = K.dot(cell_inputs, kernel) 756 def step(cell_inputs, cell_states): argument 761 z = K.dot(cell_inputs, kernel)
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/external/tensorflow/tensorflow/contrib/grid_rnn/python/ops/ |
D | grid_rnn_cell.py | 629 cell_inputs = array_ops.concat(ls_cell_inputs, 1) 631 cell_inputs = array_ops.zeros([m_prev[0].get_shape().as_list()[0], 0], 641 linear_args = array_ops.concat([cell_inputs, last_dim_output], 1) 668 new_output[d.idx], new_state[d.idx] = cell(cell_inputs, cell_state)
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/external/tensorflow/tensorflow/contrib/rnn/python/ops/ |
D | rnn_cell.py | 271 cell_inputs = array_ops.concat([inputs, m_prev], 1) 272 lstm_matrix = math_ops.matmul(cell_inputs, concat_w) 443 cell_inputs = array_ops.concat([freq_inputs[fq], m_prev, m_prev_freq], 1) 444 lstm_matrix = nn_ops.bias_add(math_ops.matmul(cell_inputs, concat_w), b) 760 cell_inputs = array_ops.concat( 765 math_ops.matmul(cell_inputs, concat_w_f), b_f) 781 math_ops.matmul(cell_inputs, concat_w_t), b_t) 1700 cell_inputs = array_ops.concat([inputs, state], 1) 1702 self._linear = _Linear(cell_inputs, 2 * self._num_units, True) 1703 rnn_matrix = self._linear(cell_inputs) [all …]
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/external/tensorflow/tensorflow/contrib/cudnn_rnn/python/kernel_tests/ |
D | cudnn_rnn_test.py | 979 cell_inputs = array_ops.placeholder( 983 (outputs, states) = _CreateCudnnCompatibleCanonicalRNN(rnn, cell_inputs) 994 rnn, cell_inputs, is_bidi=True) 1017 feed_dict={cell_inputs: inference_input}) 1025 feed_dict={cell_inputs: inference_input})
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/external/tensorflow/tensorflow/contrib/rnn/python/kernel_tests/ |
D | lstm_ops_test.py | 455 cell_inputs = array_ops.stack(inputs) 478 cell_inputs, dtype=dtypes.float32, sequence_length=seq_lengths)
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/external/tensorflow/tensorflow/contrib/seq2seq/python/ops/ |
D | attention_wrapper.py | 2422 cell_inputs = self._cell_input_fn(inputs, state.attention) 2424 cell_output, next_cell_state = self._cell(cell_inputs, cell_state)
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