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Searched refs:recurrent_kernel (Results 1 – 6 of 6) sorted by relevance

/external/tensorflow/tensorflow/python/keras/layers/
Drecurrent_v2.py493 'recurrent_kernel': _read_variable_value(self.cell.recurrent_kernel),
508 'recurrent_kernel': _read_variable_value(self.cell.recurrent_kernel),
541 def standard_gru(inputs, init_h, kernel, recurrent_kernel, bias, mask, argument
598 matrix_inner = backend.dot(h_tm1, recurrent_kernel)
625 def gpu_gru(inputs, init_h, kernel, recurrent_kernel, bias, mask, time_major, argument
638 weights += array_ops.split(recurrent_kernel, 3, axis=1)
711 def gru_with_backend_selection(inputs, init_h, kernel, recurrent_kernel, bias, argument
752 'recurrent_kernel': recurrent_kernel,
761 def gpu_gru_with_fallback(inputs, init_h, kernel, recurrent_kernel, bias, argument
770 recurrent_kernel=recurrent_kernel,
[all …]
Dcudnn_recurrent.py139 return [self.kernel, self.recurrent_kernel, self.bias]
145 return [self.kernel, self.recurrent_kernel, self.bias]
252 self.recurrent_kernel = self.add_weight(
279 self.recurrent_kernel[:, self.units:self.units * 2],
280 self.recurrent_kernel[:, :self.units],
281 self.recurrent_kernel[:, self.units * 2:],
438 self.recurrent_kernel = self.add_weight(
478 self.recurrent_kernel[:, :self.units],
479 self.recurrent_kernel[:, self.units:self.units * 2],
480 self.recurrent_kernel[:, self.units * 2:self.units * 3],
[all …]
Drecurrent.py1357 self.recurrent_kernel = self.add_weight(
1391 output = h + backend.dot(prev_output, self.recurrent_kernel)
1808 self.recurrent_kernel = self.add_weight(
1876 recurrent_z = backend.dot(h_tm1_z, self.recurrent_kernel[:, :self.units])
1878 h_tm1_r, self.recurrent_kernel[:, self.units:self.units * 2])
1890 h_tm1_h, self.recurrent_kernel[:, self.units * 2:])
1897 r * h_tm1_h, self.recurrent_kernel[:, self.units * 2:])
1914 matrix_inner = backend.dot(h_tm1, self.recurrent_kernel)
1920 h_tm1, self.recurrent_kernel[:, :2 * self.units])
1932 r * h_tm1, self.recurrent_kernel[:, 2 * self.units:])
[all …]
Dconvolutional_recurrent.py559 self.recurrent_kernel = self.add_weight(
624 recurrent_kernel_o) = array_ops.split(self.recurrent_kernel, 4, axis=3)
/external/tensorflow/tensorflow/python/keras/saving/
Dhdf5_format.py369 recurrent_kernel = np.concatenate(
372 weights = [kernel, recurrent_kernel, bias]
380 recurrent_kernel = np.concatenate(
384 weights = [kernel, recurrent_kernel, bias]
390 recurrent_kernel = np.concatenate(
398 recurrent_kernel = np.transpose(recurrent_kernel, (2, 3, 1, 0))
399 weights = [kernel, recurrent_kernel, bias]
/external/tensorflow/tensorflow/compiler/mlir/lite/utils/
Dlstm_utils.cc641 Value recurrent_kernel = func_op.getArgument(4); in ConvertKerasLSTMLayer() local
687 recurrent_kernel.getType().cast<RankedTensorType>(); in ConvertKerasLSTMLayer()
691 builder, recurrent_kernel, recurrent_kernel_type, func_op.getLoc()); in ConvertKerasLSTMLayer()