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/external/tensorflow/tensorflow/lite/kernels/
Dbidirectional_sequence_lstm_test.cc32 BidirectionalLSTMOpModel(int n_batch, int n_input, int n_cell, int n_output, in BidirectionalLSTMOpModel() argument
44 n_fw_output_(n_output), in BidirectionalLSTMOpModel()
45 n_bw_output_(n_output), in BidirectionalLSTMOpModel()
434 const int n_output = 4; in TEST_P() local
441 n_batch, n_input, n_cell, n_output, sequence_length, /*use_cifg=*/false, in TEST_P()
455 {n_cell, n_output}, // recurrent_to_input_weight tensor in TEST_P()
456 {n_cell, n_output}, // recurrent_to_forget_weight tensor in TEST_P()
457 {n_cell, n_output}, // recurrent_to_cell_weight tensor in TEST_P()
458 {n_cell, n_output}, // recurrent_to_output_weight tensor in TEST_P()
478 {n_cell, n_output}, // recurrent_to_input_weight tensor in TEST_P()
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Dunidirectional_sequence_lstm_test.cc36 int n_batch, int n_input, int n_cell, int n_output, int sequence_length, in HybridUnidirectionalLSTMOpModel() argument
42 n_batch, n_input, n_cell, n_output, sequence_length, time_major, in HybridUnidirectionalLSTMOpModel()
252 const int n_output = 4; in TEST_F() local
256 n_batch, n_input, n_cell, n_output, sequence_length, in TEST_F()
269 {n_cell, n_output}, // recurrent_to_input_weight tensor in TEST_F()
270 {n_cell, n_output}, // recurrent_to_forget_weight tensor in TEST_F()
271 {n_cell, n_output}, // recurrent_to_cell_weight tensor in TEST_F()
272 {n_cell, n_output}, // recurrent_to_output_weight tensor in TEST_F()
286 {n_batch, n_output}, // output_state tensor in TEST_F()
314 const int n_output = 4; in TEST_F() local
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Dunidirectional_sequence_gru_test.cc34 explicit GRUOpModel(int n_batch, int n_input, int n_output, in GRUOpModel() argument
37 : n_batch_(n_batch), n_input_(n_input), n_output_(n_output) { in GRUOpModel()
40 AddVariableInput(TensorData{TensorType_FLOAT32, {n_batch, n_output}}); in GRUOpModel()
103 const int n_output = 3; in TEST() local
105 GRUOpModel m(n_batch, n_input, n_output, in TEST()
107 {n_batch, n_output}, in TEST()
108 {2 * n_output, n_input + n_output}, in TEST()
109 {2 * n_output}, in TEST()
110 {n_output, n_input + n_output}, in TEST()
111 {n_output}}); in TEST()
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Dgru_cell.cc47 const int n_output = state_shape.Dims(1); in GruCell() local
70 auto r = ru.block(0 * n_output, 0, n_output, n_batch); in GruCell()
71 auto u = ru.block(1 * n_output, 0, n_output, n_batch); in GruCell()
76 auto hr = xh.block(n_input, 0, n_output, n_batch); in GruCell()
88 memcpy(output_state, output, n_batch * n_output * sizeof(float)); in GruCell()
Dlstm_eval.cc80 int n_input, int n_aux_input, int n_output, in ComputeRowSums() argument
126 n_output); in ComputeRowSums()
130 n_output); in ComputeRowSums()
133 n_output); in ComputeRowSums()
136 n_output); in ComputeRowSums()
140 projection_weights_ptr, projection_weights_row_sums, n_output, n_cell); in ComputeRowSums()
188 const int n_output, const int n_cell, in CalculateLstmGateFloat() argument
222 n_output, n_batch, context); in CalculateLstmGateFloat()
302 void CalculateLstmOutputFloat(int n_batch, int n_cell, int n_output, in CalculateLstmOutputFloat() argument
320 tensor_utils::VectorBatchVectorAssign(projection_bias, n_output, n_batch, in CalculateLstmOutputFloat()
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Dunidirectional_sequence_gru.cc42 const int n_output = output->dims->data[2]; in GruImpl() local
44 const int n_batch_output = n_batch * n_output; in GruImpl()
58 const RuntimeShape output_shape = RuntimeShape({n_batch, n_output}); in GruImpl()
151 const int n_output = input_state->dims->data[1]; in Prepare() local
158 TF_LITE_ENSURE_EQ(context, gate_weight->dims->data[0], 2 * n_output); in Prepare()
159 TF_LITE_ENSURE_EQ(context, gate_weight->dims->data[1], n_input + n_output); in Prepare()
166 TF_LITE_ENSURE_EQ(context, gate_bias->dims->data[0], 2 * n_output); in Prepare()
173 TF_LITE_ENSURE_EQ(context, candidate_weight->dims->data[0], n_output); in Prepare()
175 n_input + n_output); in Prepare()
182 TF_LITE_ENSURE_EQ(context, candidate_bias->dims->data[0], n_output); in Prepare()
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Dlstm_test.cc39 LSTMOpModel(int n_batch, int n_input, int n_cell, int n_output, bool use_cifg, in LSTMOpModel() argument
45 n_output_(n_output), in LSTMOpModel()
62 recurrent_to_input_weights_ = AddInput({weight_type, {n_cell, n_output}}); in LSTMOpModel()
64 recurrent_to_forget_weights_ = AddInput({weight_type, {n_cell, n_output}}); in LSTMOpModel()
65 recurrent_to_cell_weights_ = AddInput({weight_type, {n_cell, n_output}}); in LSTMOpModel()
66 recurrent_to_output_weights_ = AddInput({weight_type, {n_cell, n_output}}); in LSTMOpModel()
92 projection_weights_ = AddInput({weight_type, {n_output, n_cell}}); in LSTMOpModel()
98 projection_bias_ = AddInput({TensorType_FLOAT32, {n_output}}); in LSTMOpModel()
104 AddVariableInput({TensorType_FLOAT32, {n_batch, n_output}}); in LSTMOpModel()
130 output_ = AddOutput({TensorType_FLOAT32, {n_batch, n_output}}); in LSTMOpModel()
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Doptional_tensor_test.cc31 LSTMOpModel(int n_batch, int n_input, int n_cell, int n_output, bool use_cifg, in LSTMOpModel() argument
38 n_output_(n_output) { in LSTMOpModel()
233 const int n_output = 4; in TEST() local
235 LSTMOpModel lstm(n_batch, n_input, n_cell, n_output, in TEST()
249 {n_cell, n_output}, // recurrent_to_forget_weight tensor in TEST()
250 {n_cell, n_output}, // recurrent_to_cell_weight tensor in TEST()
251 {n_cell, n_output}, // recurrent_to_output_weight tensor in TEST()
Dunidirectional_sequence_lstm_test_util.h30 UnidirectionalLSTMOpModel(int n_batch, int n_input, int n_cell, int n_output,
42 n_output_(n_output), in n_batch_()
Dunidirectional_sequence_lstm.cc419 int n_output, int n_cell, in CheckInputTensorDimensions() argument
461 n_output); in CheckInputTensorDimensions()
473 n_output); in CheckInputTensorDimensions()
483 n_output); in CheckInputTensorDimensions()
590 TF_LITE_ENSURE_EQ(context, projection_weights->dims->data[0], n_output); in CheckInputTensorDimensions()
598 TF_LITE_ENSURE_EQ(context, projection_bias->dims->data[0], n_output); in CheckInputTensorDimensions()
915 const int n_output = recurrent_to_output_weights->dims->data[1]; in Prepare() local
919 context, CheckInputTensorDimensions(context, node, n_input, n_output, in Prepare()
937 TF_LITE_ENSURE_EQ(context, NumElements(output_state), n_batch * n_output); in Prepare()
942 output_size->data[input->dims->size - 1] = n_output; in Prepare()
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Dbidirectional_sequence_lstm.cc176 TfLiteContext* context, TfLiteNode* node, int n_input, int n_output, in CheckLstmTensorDimensionsAndTypes() argument
244 n_output); in CheckLstmTensorDimensionsAndTypes()
257 n_output); in CheckLstmTensorDimensionsAndTypes()
268 n_output); in CheckLstmTensorDimensionsAndTypes()
357 TF_LITE_ENSURE_EQ(context, projection_weights->dims->data[0], n_output); in CheckLstmTensorDimensionsAndTypes()
367 TF_LITE_ENSURE_EQ(context, projection_bias->dims->data[0], n_output); in CheckLstmTensorDimensionsAndTypes()
385 int n_output, int n_cell) { in CheckInputTensorDimensions() argument
389 context, node, n_input, n_output, n_cell, in CheckInputTensorDimensions()
403 context, node, n_input, n_output, n_cell, in CheckInputTensorDimensions()
/external/tensorflow/tensorflow/lite/delegates/gpu/cl/kernels/
Dlstm_full_test.cc35 LSTMOpModel(int n_batch, int n_input, int n_cell, int n_output, bool use_cifg, in LSTMOpModel() argument
62 n_output_(n_output), in LSTMOpModel()
79 AddConstInput({weight_type, {n_cell, n_output}}, in LSTMOpModel()
82 AddConstInput({weight_type, {n_cell, n_output}}, in LSTMOpModel()
84 AddConstInput({weight_type, {n_cell, n_output}}, recurrent_to_cell_weights); in LSTMOpModel()
85 AddConstInput({weight_type, {n_cell, n_output}}, in LSTMOpModel()
112 AddConstInput({weight_type, {n_output, n_cell}}, projection_weights); in LSTMOpModel()
118 AddConstInput({TensorType_FLOAT32, {n_output}}, projection_bias); in LSTMOpModel()
124 AddVariableInput({TensorType_FLOAT32, {n_batch, n_output}}); in LSTMOpModel()
150 output_ = AddOutput({TensorType_FLOAT32, {n_batch, n_output}}); in LSTMOpModel()
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/external/tensorflow/tensorflow/lite/tools/optimize/calibration/custom_logging_ops/
Dlstm.cc64 int n_aux_input, int n_output, int output_batch_leading_dim, in LstmStepWithAuxInput()
154 recurrent_to_input_weights_ptr, n_cell, n_output, output_state_ptr, in LstmStepWithAuxInput()
158 recurrent_to_forget_weights_ptr, n_cell, n_output, output_state_ptr, in LstmStepWithAuxInput()
161 recurrent_to_cell_weights_ptr, n_cell, n_output, output_state_ptr, in LstmStepWithAuxInput()
164 recurrent_to_output_weights_ptr, n_cell, n_output, output_state_ptr, in LstmStepWithAuxInput()
171 recurrent_to_input_weights_ptr, n_cell, n_output, output_state_ptr, in LstmStepWithAuxInput()
179 recurrent_to_forget_weights_ptr, n_cell, n_output, output_state_ptr, in LstmStepWithAuxInput()
187 recurrent_to_cell_weights_ptr, n_cell, n_output, output_state_ptr, in LstmStepWithAuxInput()
195 recurrent_to_output_weights_ptr, n_cell, n_output, output_state_ptr, in LstmStepWithAuxInput()
310 std::copy_n(projection_bias_ptr, n_output, in LstmStepWithAuxInput()
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/external/tensorflow/tensorflow/lite/tools/optimize/calibration/builtin_logging_ops/
Dlstm.cc47 const int n_output, const int n_cell, in CalculateLstmGateFloat() argument
77 recurrent_to_gate_weights, n_cell, n_output, output_state, n_batch, gate); in CalculateLstmGateFloat()
124 int n_batch, int n_cell, int n_output, const float* cell_state, in CalculateLstmOutputCalibration() argument
143 tensor_utils::VectorBatchVectorAssign(projection_bias, n_output, n_batch, in CalculateLstmOutputCalibration()
146 std::fill_n(output_state, n_batch * n_output, 0.0f); in CalculateLstmOutputCalibration()
149 projection_weights, n_output, n_cell, scratch, n_batch, output_state); in CalculateLstmOutputCalibration()
151 tensor_utils::CwiseClipping(output_state, n_batch * n_output, proj_clip); in CalculateLstmOutputCalibration()
154 std::copy_n(scratch, n_batch * n_output, output_state); in CalculateLstmOutputCalibration()
182 int n_aux_input, int n_output, int output_batch_leading_dim, in LstmStepCalibration()
211 input_gate_bias_ptr, n_batch, n_input, n_aux_input, n_output, n_cell, in LstmStepCalibration()
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/external/executorch/backends/xnnpack/partition/config/
Dgemm_configs.py164 n_output = node_users[0]
166 n_output.op == "call_function"
167 and format_target_name(n_output.target.__name__) in self.fused_acts
169 gemm_deps.append(n_output)
170 fused_out_users = list(n_output.users.keys())
172 n_output = fused_out_users[0]
174 if not is_quant(n_output):
177 gemm_deps.append(n_output)
182 n_output = node_users[0]
184 n_output.op == "call_function"
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/external/tensorflow/tensorflow/lite/kernels/internal/reference/
Dportable_tensor_utils.h141 int32_t n_batch, int32_t n_input, int32_t n_output, int32_t output_zp, in MatrixBatchVectorMultiplyAccumulate() argument
145 n_output, output_zp, scratch, output, context); in MatrixBatchVectorMultiplyAccumulate()
151 int32_t n_batch, int32_t n_input, int32_t n_output, int32_t output_zp, in MatrixBatchVectorMultiplyAccumulate() argument
155 n_output, output_zp, scratch, output, context); in MatrixBatchVectorMultiplyAccumulate()
181 int32_t n_hidden, int32_t n_output, in MatrixBatchVectorMultiply() argument
186 n_hidden, n_output, output_zp, proj_output); in MatrixBatchVectorMultiply()
Dportable_tensor_utils.cc331 int32_t n_batch, int32_t n_input, int32_t n_output, int32_t output_zp, in PortableMatrixBatchVectorMultiplyAccumulateImpl() argument
336 for (int row = 0; row < n_output; ++row) { in PortableMatrixBatchVectorMultiplyAccumulateImpl()
345 acc += output[batch * n_output + row]; in PortableMatrixBatchVectorMultiplyAccumulateImpl()
352 output[batch * n_output + row] = static_cast<T>(acc); in PortableMatrixBatchVectorMultiplyAccumulateImpl()
360 int32_t n_batch, int32_t n_input, int32_t n_output, int32_t output_zp, in PortableMatrixBatchVectorMultiplyAccumulate() argument
364 n_output, output_zp, output); in PortableMatrixBatchVectorMultiplyAccumulate()
370 int32_t n_batch, int32_t n_input, int32_t n_output, int32_t output_zp, in PortableMatrixBatchVectorMultiplyAccumulate() argument
374 n_output, output_zp, output); in PortableMatrixBatchVectorMultiplyAccumulate()
413 int32_t n_output, int32_t output_zp, int8_t* proj_output) { in PortableMatrixBatchVectorMultiply() argument
417 for (int row = 0; row < n_output; ++row) { in PortableMatrixBatchVectorMultiply()
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Dportable_tensor_utils_impl.h120 int32_t n_batch, int32_t n_input, int32_t n_output, int32_t output_zp,
126 int32_t n_batch, int32_t n_input, int32_t n_output, int32_t output_zp,
142 int32_t n_output, int32_t output_zp, int8_t* proj_output);
/external/tensorflow/tensorflow/lite/kernels/internal/optimized/
Dneon_tensor_utils.h108 int32_t n_batch, int32_t n_input, int32_t n_output, int32_t output_zp, in MatrixBatchVectorMultiplyAccumulate() argument
112 n_output, output_zp, scratch, output, context); in MatrixBatchVectorMultiplyAccumulate()
118 int32_t n_batch, int32_t n_input, int32_t n_output, int32_t output_zp, in MatrixBatchVectorMultiplyAccumulate() argument
122 n_output, output_zp, scratch, output, context); in MatrixBatchVectorMultiplyAccumulate()
142 int32_t n_hidden, int32_t n_output, in MatrixBatchVectorMultiply() argument
147 n_hidden, n_output, output_zp, proj_output); in MatrixBatchVectorMultiply()
Dsse_tensor_utils.h122 int32_t n_batch, int32_t n_input, int32_t n_output, int32_t output_zp, in MatrixBatchVectorMultiplyAccumulate() argument
126 shift, n_batch, n_input, n_output, output_zp, scratch, output, context); in MatrixBatchVectorMultiplyAccumulate()
132 int32_t n_batch, int32_t n_input, int32_t n_output, int32_t output_zp, in MatrixBatchVectorMultiplyAccumulate() argument
136 shift, n_batch, n_input, n_output, output_zp, scratch, output, context); in MatrixBatchVectorMultiplyAccumulate()
156 int32_t n_hidden, int32_t n_output, in MatrixBatchVectorMultiply() argument
161 n_hidden, n_output, output_zp, proj_output); in MatrixBatchVectorMultiply()
Dneon_tensor_utils_impl.h93 int32_t n_batch, int32_t n_input, int32_t n_output, int32_t output_zp,
99 int32_t n_batch, int32_t n_input, int32_t n_output, int32_t output_zp,
Dneon_tensor_utils.cc770 int32_t n_output, int32_t output_zp, in NeonMatrixBatchVectorMultiplyImpl() argument
808 for (int row = 0; row < n_output; ++row) { in NeonMatrixBatchVectorMultiplyImpl()
868 scratch[batch * n_output + row] = dotprod; in NeonMatrixBatchVectorMultiplyImpl()
879 int32_t multiplier, int32_t shift, int32_t n_batch, int32_t n_output, in NeonMatrixBatchVectorAccumulateImpl() argument
882 const int total_size = n_batch * n_output; in NeonMatrixBatchVectorAccumulateImpl()
932 int32_t multiplier, int32_t shift, int32_t n_batch, int32_t n_output, in NeonMatrixBatchVectorAccumulateImpl() argument
935 const int total_size = n_batch * n_output; in NeonMatrixBatchVectorAccumulateImpl()
1007 int32_t n_input, int32_t n_output, int32_t output_zp, in NeonCpuBackendGemm() argument
1015 lhs_params.rows = n_output; in NeonCpuBackendGemm()
1026 dst_params.rows = n_output; in NeonCpuBackendGemm()
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/external/tensorflow/tensorflow/lite/delegates/nnapi/
Dnnapi_delegate_test.cc3169 LSTMOpModel(int n_batch, int n_input, int n_cell, int n_output, bool use_cifg, in LSTMOpModel() argument
3177 n_output_(n_output), in LSTMOpModel()
3536 const int n_output = 4; in TEST_F() local
3538 LSTMOpModel lstm(n_batch, n_input, n_cell, n_output, in TEST_F()
3551 {n_cell, n_output}, // recurrent_to_input_weight_tensor in TEST_F()
3552 {n_cell, n_output}, // recurrent_to_forget_weight_tensor in TEST_F()
3553 {n_cell, n_output}, // recurrent_to_cell_weight_tensor in TEST_F()
3554 {n_cell, n_output}, // recurrent_to_output_weight_tensor in TEST_F()
3568 {n_batch, n_output}, // activation_state tensor in TEST_F()
3600 const int n_output = 4; in TEST_F() local
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/external/tensorflow/tensorflow/lite/kernels/internal/
Dtensor_utils.h107 int32_t n_batch, int32_t n_input, int32_t n_output, int32_t output_zp,
138 int32_t n_batch, int32_t n_input, int32_t n_output, int32_t output_zp,
/external/armnn/src/backends/backendsCommon/
DWorkloadData.cpp2016 const uint32_t n_output = m_RecurrentToOutputWeights->GetShape()[1]; in Validate() local
2022 ValidateTensorNumDimNumElem(workloadInfo.m_InputTensorInfos[1], 2, (n_batch * n_output), in Validate()
2032 ValidateTensorNumDimNumElem(workloadInfo.m_OutputTensorInfos[1], 2, (n_batch * n_output), in Validate()
2038 ValidateTensorNumDimNumElem(workloadInfo.m_OutputTensorInfos[3], 2, (n_batch * n_output), in Validate()
2059 (n_cell * n_output), "RecurrentToInputWeights"); in Validate()
2064 (n_cell * n_output), "RecurrentToForgetWeights"); in Validate()
2068 (n_cell * n_output), "RecurrentToCellWeights"); in Validate()
2142 (n_cell * n_output), "ProjectionWeights"); in Validate()
2146 … ValidateTensorNumDimNumElem(m_ProjectionBias->GetTensorInfo(), 1, n_output, "ProjectionBias"); in Validate()
3882 const uint32_t n_output = m_RecurrentToOutputWeights->GetShape()[1]; in Validate() local
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