| /frameworks/ml/nn/common/operations/ |
| D | Multinomial.cpp | 56 input_ = GetInput(operation, operands, kInputTensor); in Multinomial()
86 switch (input_->type) { in Eval()
88 std::vector<float> inputDataFloat32(getNumberOfElements(input_->shape())); in Eval()
89 convertFloat16ToFloat32(GetBuffer<_Float16>(input_), &inputDataFloat32); in Eval()
94 EvalFloat32(GetBuffer<float>(input_)); in Eval()
98 LOG(ERROR) << "Unsupported data type: " << static_cast<int>(input_->type); in Eval()
106 const int batch_size = SizeOfDimension(input_, 0); in EvalFloat32()
107 const int class_size = SizeOfDimension(input_, 1); in EvalFloat32()
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| D | BidirectionalSequenceLSTM.cpp | 83 input_ = GetInput(operation, operands, kInputTensor); in BidirectionalSequenceLSTM()
177 if (input_->type == OperandType::TENSOR_FLOAT32) { in BidirectionalSequenceLSTM()
254 if (input_->type == OperandType::TENSOR_FLOAT32) { in Prepare()
268 NN_CHECK(NumDimensions(input_) == 3); in Prepare()
269 const uint32_t max_time = SizeOfDimension(input_, params_.time_major ? 0 : 1); in Prepare()
270 const uint32_t n_batch = SizeOfDimension(input_, params_.time_major ? 1 : 0); in Prepare()
271 const uint32_t n_fw_input = SizeOfDimension(input_, 2); in Prepare()
289 input_, fw_input_to_input_weights_, fw_input_to_forget_weights_, in Prepare()
337 NN_CHECK_EQ(aux_input_->shape().dimensions[0], input_->shape().dimensions[0]); in Prepare()
338 NN_CHECK_EQ(aux_input_->shape().dimensions[1], input_->shape().dimensions[1]); in Prepare()
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| D | SVDF.cpp | 35 input_ = GetInput(operation, operands, kInputTensor); in SVDF()
114 switch (input_->type) { in Eval()
116 std::vector<float> inputDataFloat32(getNumberOfElements(input_->shape())); in Eval()
117 convertFloat16ToFloat32(reinterpret_cast<_Float16*>(input_->buffer), &inputDataFloat32); in Eval()
147 EvalFloat32(reinterpret_cast<float*>(input_->buffer), in Eval()
157 LOG(ERROR) << "Unsupported data type: " << static_cast<int>(input_->type); in Eval()
170 const int batch_size = SizeOfDimension(input_, 0); in EvalFloat32()
171 const int input_size = SizeOfDimension(input_, 1); in EvalFloat32()
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| D | MultinomialTest.cpp | 69 input_.push_back(srng.RandDouble()); in Invoke()
71 ASSERT_EQ(execution.setInput(Multinomial::kInputTensor, input_.data(), in Invoke()
72 sizeof(float) * input_.size()), in Invoke()
91 const std::vector<float>& GetInput() const { return input_; } in GetInput()
101 std::vector<float> input_; member in android::nn::wrapper::MultinomialOpModel
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| D | RNN.cpp | 36 input_ = GetInput(operation, operands, kInputTensor); in RNN()
86 switch (input_->type) { in Eval()
88 RNNStep<_Float16>(reinterpret_cast<_Float16*>(input_->buffer), input_->shape(), in Eval()
100 RNNStep<float>(reinterpret_cast<float*>(input_->buffer), input_->shape(), in Eval()
112 LOG(ERROR) << "Unsupported data type: " << static_cast<int>(input_->type); in Eval()
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| D | LSTM.cpp | 55 input_ = GetInput(operation, operands, kInputTensor); in LSTMCell()
92 if (input_->type == OperandType::TENSOR_FLOAT32) { in LSTMCell()
133 const RunTimeOperandInfo* input_, const RunTimeOperandInfo* input_to_input_weights, in CheckInputTensorDimensions() argument
337 if (input_->type == OperandType::TENSOR_FLOAT32) { in Prepare()
347 NN_CHECK(NumDimensions(input_) > 1); in Prepare()
348 const uint32_t n_batch = SizeOfDimension(input_, 0); in Prepare()
349 const uint32_t n_input = SizeOfDimension(input_, 1); in Prepare()
361 input_, input_to_input_weights_, input_to_forget_weights_, input_to_cell_weights_, in Prepare()
373 const Shape& inputShape = input_->shape(); in Prepare()
995 switch (input_->type) { in Eval()
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| D | QuantizedLSTM.cpp | 224 input_ = GetInput(operation, operands, kInputTensor); in QuantizedLSTMCell()
382 SizeOfDimension(input_, 1) + SizeOfDimension(prevOutput_, 1)}; in eval()
392 concatTempShape.dimensions = {SizeOfDimension(input_, 0), getSizeOfDimension(weightsShape, 1)}; in eval()
395 activationTempShape.dimensions = {SizeOfDimension(input_, 0), in eval()
415 GetBuffer<const uint8_t>(input_), convertShapeToDims(input_->shape()), in eval()
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| D | LSHProjection.cpp | 35 input_ = GetInput(operation, operands, kInputTensor); in LSHProjection()
168 DenseLshProjection<T>(hash_, input_, weight_, out_buf); in Eval()
172 SparseLshProjection<T>(type_, hash_, input_, weight_, out_buf); in Eval()
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| D | QuantizedLSTMTest.cpp | 76 initializeInputData(inputOperandTypeParams[QuantizedLSTMCell::kInputTensor], &input_); in QuantizedLSTMOpModel()
96 ASSERT_EQ(setInputTensor(&execution, QuantizedLSTMCell::kInputTensor, input_), in invoke()
156 void setInput(const std::vector<uint8_t>& input) { input_ = input; } in setInput()
202 std::vector<uint8_t> input_; member in android::nn::wrapper::QuantizedLSTMOpModel
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| D | Multinomial.h | 51 RunTimeOperandInfo* input_; variable
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| D | SVDF.h | 65 const RunTimeOperandInfo* input_; variable
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| D | LSTM.h | 185 const RunTimeOperandInfo* input_, const RunTimeOperandInfo* input_to_input_weights,
207 const RunTimeOperandInfo* input_; variable
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| D | LSHProjection.h | 58 const RunTimeOperandInfo* input_; variable
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| D | QuantizedLSTM.h | 65 const RunTimeOperandInfo* input_;
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| D | RNN.h | 67 const RunTimeOperandInfo* input_; variable
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| D | BidirectionalSequenceLSTM.h | 163 const RunTimeOperandInfo* input_; variable
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| /frameworks/ml/nn/runtime/test/specs/V1_2/ |
| D | quantized_lstm.mod.py | 26 input_ = Input("input", InputType) variable
61 input_,
79 input_: [166, 179, 50, 150],
113 input_ = Input("input", InputType) variable
158 model = model.Operation("QUANTIZED_16BIT_LSTM", input_, input_to_input_weights,
168 input_: [166, 179],
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