| /frameworks/ml/nn/common/operations/ |
| RNN.h | 38 class RNN {
40 RNN(const android::hardware::neuralnetworks::V1_1::Operation &operation,
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| RNN.cpp | 17 #include "RNN.h"
25 RNN::RNN(const Operation& operation,
40 bool RNN::Prepare(const Operation &operation,
80 bool RNN::Eval() {
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| RNNTest.cpp | 17 #include "RNN.h"
224 ASSERT_EQ(execution.setInput(RNN::k##X##Tensor, X##_.data(), \
233 ASSERT_EQ(execution.setOutput(RNN::k##X##Tensor, X##_.data(), \
241 ASSERT_EQ(execution.setInput(RNN::kActivationParam, &activation_,
266 BasicRNNOpModel rnn(2, 16, 8);
267 rnn.SetWeights(
291 rnn.SetBias({0.065691948, -0.69055247, 0.1107955, -0.97084129, -0.23957068,
296 rnn.SetRecurrentWeights({0.1, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0,
313 rnn.ResetHiddenState();
315 (rnn.input_size() * rnn.num_batches())
[all...] |
| /external/tensorflow/tensorflow/python/keras/_impl/keras/layers/ |
| recurrent_test.py | 51 layer = keras.layers.RNN(cell)
61 layer = keras.layers.RNN(cells)
89 layer = keras.layers.RNN(cell)
99 layer = keras.layers.RNN(cells)
140 layer = keras.layers.RNN(cell)
152 layer = keras.layers.RNN.from_config(config)
163 layer = keras.layers.RNN(cells)
169 # Test stacked RNN serialization.
175 layer = keras.layers.RNN.from_config(config)
230 layer = keras.layers.RNN(cell
[all...] |
| recurrent.py | 41 """Wrapper allowing a stack of RNN cells to behave as a single cell.
46 cells: List of RNN cell instances.
58 x = keras.layers.RNN(cells)(inputs)
229 @tf_export('keras.layers.RNN')
230 class RNN(Layer):
234 cell: A RNN cell instance. A RNN cell is a class that has:
247 It is also possible for `cell` to be a list of RNN cell instances,
248 in which cases the cells get stacked on after the other in the RNN,
249 implementing an efficient stacked RNN
[all...] |
| /hardware/interfaces/neuralnetworks/1.0/ |
| types.hal | [all...] |
| /frameworks/ml/nn/runtime/test/generated/vts_models/ |
| rnn.model.cpp | 81 .type = OperationType::RNN,
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| rnn_relaxed.model.cpp | 81 .type = OperationType::RNN,
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| rnn_state.model.cpp | 81 .type = OperationType::RNN,
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| rnn_state_relaxed.model.cpp | 81 .type = OperationType::RNN,
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| /external/tensorflow/tensorflow/contrib/eager/python/examples/rnn_ptb/ |
| rnn_ptb.py | 15 """Penn Treebank RNN model definition compatible with eager execution.
18 https://github.com/tensorflow/models/tree/master/tutorials/rnn/ptb
42 class RNN(tfe.Network):
43 """A static RNN.
49 super(RNN, self).__init__()
98 https://github.com/tensorflow/models/tree/master/tutorials/rnn/ptb
115 self.rnn = cudnn_rnn.CudnnLSTM(
118 self.rnn = RNN(hidden_dim, num_layers, self.keep_ratio)
119 self.track_layer(self.rnn)
[all...] |
| /frameworks/ml/nn/common/ |
| ValidateHal.cpp | 249 case V1_0::OperationType::RNN:
287 case V1_1::OperationType::RNN:
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| CpuExecutor.cpp | [all...] |
| Utils.cpp | 150 "RNN",
[all...] |
| /external/tensorflow/tensorflow/python/keras/layers/ |
| __init__.py | 140 from tensorflow.python.keras._impl.keras.layers.recurrent import RNN
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| /frameworks/ml/nn/runtime/ |
| NeuralNetworks.cpp | 207 static_assert(static_cast<int32_t>(OperationType::RNN) == ANEURALNETWORKS_RNN,
208 "OperationType::RNN != ANEURALNETWORKS_RNN");
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| /external/tensorflow/tensorflow/python/ops/ |
| control_flow_ops.py | [all...] |
