/external/tensorflow/tensorflow/lite/toco/graph_transformations/ |
D | graph_transformations.cc | 83 for (const auto& rnn_state : model->flags.rnn_states()) { in DiscardUselessConnectedComponentsAndRNNBackEdges() local 85 useful_arrays.count(rnn_state.state_array()); in DiscardUselessConnectedComponentsAndRNNBackEdges() 88 !useful_arrays.count(rnn_state.back_edge_source_array()); in DiscardUselessConnectedComponentsAndRNNBackEdges() 89 useful_arrays.insert(rnn_state.back_edge_source_array()); in DiscardUselessConnectedComponentsAndRNNBackEdges() 114 for (const auto& rnn_state : model->flags.rnn_states()) { in DiscardUselessConnectedComponentsAndRNNBackEdges() local 116 !model->HasArray(rnn_state.back_edge_source_array()) || in DiscardUselessConnectedComponentsAndRNNBackEdges() 117 !model->HasArray(rnn_state.state_array()); in DiscardUselessConnectedComponentsAndRNNBackEdges() 119 CHECK(rnn_state.discardable()); in DiscardUselessConnectedComponentsAndRNNBackEdges() 121 rnn_states_to_keep.push_back(rnn_state); in DiscardUselessConnectedComponentsAndRNNBackEdges() 125 for (const auto& rnn_state : rnn_states_to_keep) { in DiscardUselessConnectedComponentsAndRNNBackEdges() local [all …]
|
D | remove_unused_op.cc | 50 for (const auto& rnn_state : model->flags.rnn_states()) { in Run() local 51 if (output == rnn_state.state_array()) { in Run() 66 for (const auto& rnn_state : model->flags.rnn_states()) { in Run() local 67 if (output == rnn_state.back_edge_source_array()) { in Run() 69 if (!IsDiscardableArray(*model, rnn_state.back_edge_source_array()) || in Run() 70 !IsDiscardableArray(*model, rnn_state.state_array()) || in Run() 71 CountOpsWithInput(*model, rnn_state.state_array())) { in Run()
|
D | lstm_utils.cc | 88 for (const auto& rnn_state : model->flags.rnn_states()) { in GetMatchingRnnArray() local 89 if (rnn_state.back_edge_source_array() == back_edge_source_array) { in GetMatchingRnnArray() 90 *rnn_array = rnn_state.state_array(); in GetMatchingRnnArray()
|
D | dequantize.cc | 141 for (const auto& rnn_state : model->flags.rnn_states()) { in DequantizeArray() local 142 if (array_name == rnn_state.state_array()) { in DequantizeArray() 145 if (array_name == rnn_state.back_edge_source_array()) { in DequantizeArray()
|
D | resolve_constant_unary.cc | 148 for (const auto& rnn_state : model->flags.rnn_states()) { in Run() local 149 if (unary_op->inputs[0] == rnn_state.back_edge_source_array()) { in Run() 152 if (unary_op->inputs[0] == rnn_state.state_array()) { in Run()
|
D | quantize.cc | 601 for (const auto& rnn_state : model->flags.rnn_states()) { in Run() local 602 if (rnn_state.state_array() == input) { in Run()
|
/external/tensorflow/tensorflow/lite/toco/ |
D | tooling_util.cc | 124 for (const auto& rnn_state : model.flags.rnn_states()) { in IsArrayConsumed() local 125 if (rnn_state.back_edge_source_array() == name) { in IsArrayConsumed() 916 for (const auto& rnn_state : model.flags.rnn_states()) { in CheckNonExistentIOArrays() local 917 if (!rnn_state.discardable()) { in CheckNonExistentIOArrays() 919 QCHECK(GetOpWithInput(model, rnn_state.state_array())) in CheckNonExistentIOArrays() 920 << "Specified RNN state \"" << rnn_state.state_array() in CheckNonExistentIOArrays() 923 QCHECK(GetOpWithOutput(model, rnn_state.back_edge_source_array())) in CheckNonExistentIOArrays() 925 << rnn_state.back_edge_source_array() in CheckNonExistentIOArrays() 963 for (const auto& rnn_state : model->flags.rnn_states()) { in FixNoMissingArray() local 964 model->GetOrCreateArray(rnn_state.state_array()); in FixNoMissingArray() [all …]
|
D | dump_graphviz.cc | 128 for (const auto& rnn_state : model.flags.rnn_states()) { in GetArrayColorAndShape() local 130 if (array_name == rnn_state.state_array()) { in GetArrayColorAndShape() 137 if (array_name == rnn_state.back_edge_source_array()) { in GetArrayColorAndShape() 175 for (const auto& rnn_state : model.flags.rnn_states()) { in GetArrayCompassPt() local 177 if (array_name == rnn_state.state_array()) { in GetArrayCompassPt() 181 if (array_name == rnn_state.back_edge_source_array()) { in GetArrayCompassPt() 773 for (const auto& rnn_state : model.flags.rnn_states()) { in DumpGraphviz() local 774 AppendF(output_file, kRNNBackEdgeFmt, rnn_state.back_edge_source_array(), in DumpGraphviz() 775 rnn_state.state_array()); in DumpGraphviz()
|
D | allocate_transient_arrays.cc | 79 for (const auto& rnn_state : model.flags.rnn_states()) { in ComputeArrayLifespans() local 82 (*array_lifespans)[rnn_state.state_array()] = lifespan; in ComputeArrayLifespans() 172 for (const auto& rnn_state : model.flags.rnn_states()) { in TransientArraySize() local 173 if (rnn_state.state_array() == array_name) { in TransientArraySize()
|
D | import_tensorflow.cc | 2003 auto* rnn_state = model->flags.add_rnn_states(); in ConvertOperatorSpecialCasedAsRNNBackEdge() local 2006 rnn_state->set_discardable(true); in ConvertOperatorSpecialCasedAsRNNBackEdge() 2007 rnn_state->set_state_array(node.name()); in ConvertOperatorSpecialCasedAsRNNBackEdge() 2008 rnn_state->set_back_edge_source_array(node.input(0)); in ConvertOperatorSpecialCasedAsRNNBackEdge() 2097 for (const auto& rnn_state : model->flags.rnn_states()) { in AddExtraOutputs() local 2098 consumed_arrays.push_back(rnn_state.back_edge_source_array()); in AddExtraOutputs() 2608 for (const auto& rnn_state : model->flags.rnn_states()) { in ImportTensorFlowGraphDef() local 2609 model->GetArray(rnn_state.state_array()).buffer = nullptr; in ImportTensorFlowGraphDef()
|
D | export_tensorflow.cc | 2446 for (const auto& rnn_state : model.flags.rnn_states()) { in ExportTensorFlowGraphDefImplementation() local 2447 AddPlaceholderForRNNState(model, rnn_state.state_array(), rnn_state.size(), in ExportTensorFlowGraphDefImplementation()
|
/external/libopus/src/ |
D | analysis.h | 77 float rnn_state[MAX_NEURONS]; member
|
D | analysis.c | 894 compute_gru(&layer1, tonal->rnn_state, layer_out); in tonality_analysis() 895 compute_dense(&layer2, frame_probs, tonal->rnn_state); in tonality_analysis()
|
/external/tensorflow/tensorflow/core/kernels/ |
D | cudnn_rnn_ops.cc | 1008 RnnScratchSpace& rnn_state = (*cache)[key]; in GetCachedRnnDescriptor() local 1009 if (rnn_state.rnn_desc == nullptr || ResetRndGenState()) { in GetCachedRnnDescriptor() 1012 rnn_state.dropout_state_allocator.reset(dropout_state_allocator); in GetCachedRnnDescriptor() 1015 dropout_state_allocator, &rnn_state.rnn_desc); in GetCachedRnnDescriptor() 1018 *rnn_desc = rnn_state.rnn_desc.get(); in GetCachedRnnDescriptor()
|