/frameworks/ml/nn/common/operations/ |
D | LSHProjection.cpp | 49 NN_CHECK(SizeOfDimension(hash, 1) <= 32); in Prepare() 60 outputShape->dimensions = {SizeOfDimension(hash, 0)}; in Prepare() 66 NN_CHECK_EQ(SizeOfDimension(weight, 0), SizeOfDimension(input, 0)); in Prepare() 67 outputShape->dimensions = {SizeOfDimension(hash, 0) * SizeOfDimension(hash, 1)}; in Prepare() 90 SizeOfDimension(input, 0); in runningSignBit() 97 for (uint32_t i = 0; i < SizeOfDimension(input, 0); ++i) { in runningSignBit() 119 int num_hash = SizeOfDimension(hash, 0); in SparseLshProjection() 120 int num_bits = SizeOfDimension(hash, 1); in SparseLshProjection() 139 int num_hash = SizeOfDimension(hash, 0); in DenseLshProjection() 140 int num_bits = SizeOfDimension(hash, 1); in DenseLshProjection()
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D | SVDF.cpp | 66 const uint32_t batch_size = SizeOfDimension(input, 0); in Prepare() 67 const uint32_t num_filters = SizeOfDimension(weights_feature, 0); in Prepare() 70 const uint32_t memory_size = SizeOfDimension(weights_time, 1); in Prepare() 71 NN_CHECK_EQ(SizeOfDimension(input, 1), SizeOfDimension(weights_feature, 1)); in Prepare() 72 NN_CHECK_EQ(SizeOfDimension(weights_time, 0), num_filters); in Prepare() 77 NN_CHECK_EQ(SizeOfDimension(bias, 0), num_units); in Prepare() 154 const int batch_size = SizeOfDimension(input_, 0); in EvalFloat32() 155 const int input_size = SizeOfDimension(input_, 1); in EvalFloat32() 156 const int num_filters = SizeOfDimension(weights_feature_, 0); in EvalFloat32() 158 const int memory_size = SizeOfDimension(weights_time_, 1); in EvalFloat32()
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D | RNN.cpp | 65 const uint32_t batch_size = SizeOfDimension(input, 0); in Prepare() 66 const uint32_t num_units = SizeOfDimension(input_weights, 0); in Prepare() 67 NN_CHECK_EQ(SizeOfDimension(input, 1), SizeOfDimension(input_weights, 1)); in Prepare() 68 NN_CHECK_EQ(SizeOfDimension(input_weights, 0), SizeOfDimension(bias, 0)); in Prepare() 69 NN_CHECK_EQ(SizeOfDimension(recurrent_weights, 0), SizeOfDimension(bias, 0)); in Prepare() 70 NN_CHECK_EQ(SizeOfDimension(recurrent_weights, 1), SizeOfDimension(bias, 0)); in Prepare()
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D | QuantizedLSTM.cpp | 249 const uint32_t numBatches = SizeOfDimension(input, 0); in prepare() 250 const uint32_t inputSize = SizeOfDimension(input, 1); in prepare() 254 NN_RET_CHECK_EQ(SizeOfDimension(prevOutput, 0), numBatches); in prepare() 257 const uint32_t outputSize = SizeOfDimension(prevOutput, 1); in prepare() 266 NN_RET_CHECK_EQ(SizeOfDimension(weights, 0), outputSize); in prepare() 267 NN_RET_CHECK_EQ(SizeOfDimension(weights, 1), columns); in prepare() 298 NN_RET_CHECK_EQ(SizeOfDimension(bias, 0), outputSize); in prepare() 314 NN_CHECK_EQ(SizeOfDimension(prevCellState, 0), numBatches); in prepare() 315 NN_CHECK_EQ(SizeOfDimension(prevCellState, 1), outputSize); in prepare() 349 const int outputSize = SizeOfDimension(inputToInputWeights_, 0); in concatenateWeights() [all …]
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D | LSTM.cpp | 151 NN_CHECK_EQ(SizeOfDimension(input_to_input_weights, 0), n_cell); in CheckInputTensorDimensions() 152 NN_CHECK_EQ(SizeOfDimension(input_to_input_weights, 1), n_input); in CheckInputTensorDimensions() 156 NN_CHECK_EQ(SizeOfDimension(input_to_forget_weights, 0), n_cell); in CheckInputTensorDimensions() 157 NN_CHECK_EQ(SizeOfDimension(input_to_forget_weights, 1), n_input); in CheckInputTensorDimensions() 160 NN_CHECK_EQ(SizeOfDimension(input_to_cell_weights, 0), n_cell); in CheckInputTensorDimensions() 161 NN_CHECK_EQ(SizeOfDimension(input_to_cell_weights, 1), n_input); in CheckInputTensorDimensions() 165 NN_CHECK_EQ(SizeOfDimension(recurrent_to_input_weights, 0), n_cell); in CheckInputTensorDimensions() 166 NN_CHECK_EQ(SizeOfDimension(recurrent_to_input_weights, 1), n_output); in CheckInputTensorDimensions() 170 NN_CHECK_EQ(SizeOfDimension(recurrent_to_forget_weights, 0), n_cell); in CheckInputTensorDimensions() 171 NN_CHECK_EQ(SizeOfDimension(recurrent_to_forget_weights, 1), n_output); in CheckInputTensorDimensions() [all …]
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D | BidirectionalSequenceLSTM.cpp | 166 const uint32_t max_time = SizeOfDimension(input_, params_.time_major ? 0 : 1); in Prepare() 167 const uint32_t n_batch = SizeOfDimension(input_, params_.time_major ? 1 : 0); in Prepare() 168 const uint32_t n_input = SizeOfDimension(input_, 2); in Prepare() 170 const uint32_t n_fw_cell = SizeOfDimension(fw_input_to_output_weights_, 0); in Prepare() 172 NN_CHECK_EQ(SizeOfDimension(fw_input_to_output_weights_, 1), n_input); in Prepare() 175 NN_CHECK_EQ(SizeOfDimension(fw_recurrent_to_output_weights_, 0), n_fw_cell); in Prepare() 176 const uint32_t n_fw_output = SizeOfDimension(fw_recurrent_to_output_weights_, 1); in Prepare() 212 const uint32_t n_bw_cell = SizeOfDimension(bw_input_to_output_weights_, 0); in Prepare() 214 NN_CHECK_EQ(SizeOfDimension(bw_input_to_output_weights_, 1), n_input); in Prepare() 217 NN_CHECK_EQ(SizeOfDimension(bw_recurrent_to_output_weights_, 0), n_bw_cell); in Prepare() [all …]
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D | Multinomial.cpp | 65 const uint32_t batch_size = SizeOfDimension(input, 0); in Prepare() 99 const int batch_size = SizeOfDimension(input_, 0); in EvalFloat32() 100 const int class_size = SizeOfDimension(input_, 1); in EvalFloat32()
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/frameworks/ml/nn/common/include/ |
D | CpuExecutor.h | 257 inline uint32_t SizeOfDimension(const RunTimeOperandInfo *operand, int i) { in SizeOfDimension() function
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