| /frameworks/ml/nn/common/operations/ |
| D | RNN.cpp | 34 RNN::RNN(const Operation& operation, RunTimeOperandInfo* operands) { in RNN() function in android::nn::RNN
49 bool RNN::Prepare(const Operation& operation, RunTimeOperandInfo* operands, Shape* hiddenStateShape, in Prepare()
85 bool RNN::Eval() { in Eval()
120 bool RNN::RNNStep(const T* inputData, const Shape& inputShape, const T* hiddenStateInputData, in RNNStep()
140 bool RNN::RNNStep(const T* inputData, const Shape& inputShape, const T* auxInputData, in RNNStep()
227 template bool RNN::RNNStep<_Float16>(const _Float16* inputData, const Shape& inputShape,
233 template bool RNN::RNNStep<_Float16>(const _Float16* inputData, const Shape& inputShape,
243 template bool RNN::RNNStep<float>(const float* inputData, const Shape& inputShape,
249 template bool RNN::RNNStep<float>(const float* inputData, const Shape& inputShape,
|
| D | RNN.h | 31 class RNN {
33 RNN(const hal::Operation& operation, RunTimeOperandInfo* operands);
|
| D | RNNTest.cpp | 200 ASSERT_EQ(execution.setInput(RNN::k##X##Tensor, X##_.data(), sizeof(float) * X##_.size()), \ in Invoke()
208 ASSERT_EQ(execution.setOutput(RNN::k##X##Tensor, X##_.data(), sizeof(float) * X##_.size()), \ in Invoke()
215 ASSERT_EQ(execution.setInput(RNN::kActivationParam, &activation_, sizeof(activation_)), in Invoke()
|
| D | BidirectionalSequenceRNN.cpp | 267 RNN::RNNStep<T>(inputBatchPtr, fixedTimeInputShape, auxInputBatchPtr, in executeTyped()
295 RNN::RNNStep<T>(inputBatchPtr, fixedTimeInputShape, auxInputBatchPtr, in executeTyped()
|
| D | UnidirectionalSequenceRNN.cpp | 109 RNN::RNNStep<T>(input, fixedTimeInputShape, hiddenState, bias, weights, weightsShape, in executeTyped()
|
| /frameworks/ml/nn/runtime/test/android_fuzzing/corpus/ |
| D | seed037 | 147 type: RNN
|
| D | seed459 | 310 type: RNN
|
| D | seed499 | 456 type: RNN
|
| D | seed403 | 1109 type: RNN
|
| D | seed206 | 1427 type: RNN
|
| /frameworks/ml/nn/runtime/test/generated/spec_V1_0/ |
| D | rnn.example.cpp | 100 .type = TestOperationType::RNN in get_test_model()
377 .type = TestOperationType::RNN in get_test_model_all_inputs_as_internal()
|
| D | rnn_state.example.cpp | 100 .type = TestOperationType::RNN in get_test_model()
377 .type = TestOperationType::RNN in get_test_model_all_inputs_as_internal()
|
| /frameworks/ml/nn/runtime/test/generated/spec_V1_2/ |
| D | rnn_float16.example.cpp | 100 .type = TestOperationType::RNN in get_test_model()
377 .type = TestOperationType::RNN in get_test_model_all_inputs_as_internal()
|
| /frameworks/ml/nn/runtime/test/generated/spec_V1_1/ |
| D | rnn_state_relaxed.example.cpp | 100 .type = TestOperationType::RNN in get_test_model()
377 .type = TestOperationType::RNN in get_test_model_all_inputs_as_internal()
|
| D | rnn_relaxed.example.cpp | 100 .type = TestOperationType::RNN in get_test_model()
377 .type = TestOperationType::RNN in get_test_model_all_inputs_as_internal()
|
| /frameworks/ml/nn/runtime/test/android_fuzzing/ |
| D | StaticAssert.cpp | 80 static_assert(static_cast<TestOperationType>(RNN) == TestOperationType::RNN);
|
| D | Model.proto | 64 RNN = 24; enumerator
|
| /frameworks/ml/nn/runtime/test/ |
| D | TestAssertions.cpp | 67 CHECK_TEST_ENUM(TestOperationType, RNN);
|
| /frameworks/ml/nn/common/ |
| D | Android.bp | 173 "operations/RNN.cpp",
|
| D | CpuExecutor.cpp | 1125 case OperationType::RNN: { in executeOperation()
1130 RunTimeOperandInfo& hiddenStateOut = operands[outs[RNN::kHiddenStateOutTensor]]; in executeOperation()
1131 RunTimeOperandInfo& output = operands[outs[RNN::kOutputTensor]]; in executeOperation()
1134 RNN rnn_cell(operation, operands); in executeOperation()
1136 success = RNN::Prepare(operation, operands, &hiddenStateShape, &outputShape) && in executeOperation()
|
| /frameworks/ml/nn/tools/test_generator/test_harness/include/ |
| D | TestHarness.h | 119 RNN = 24, enumerator
|
| /frameworks/ml/nn/runtime/ |
| D | NeuralNetworks.cpp | 333 static_assert(static_cast<int32_t>(OperationType::RNN) == ANEURALNETWORKS_RNN,
|
| /frameworks/ml/nn/tools/api/ |
| D | types.spec | 2124 %{DeclareOperation RNN 24},
3113 * one input into the two RNN cells in the following way:
3123 * An op with cross-linking takes two inputs and feeds them into the RNN
3145 * In this case, the cell feeds inputs into the RNN in the following way:
|