/frameworks/ml/nn/common/operations/ |
D | LSTM.cpp | 246 const uint32_t n_batch = SizeOfDimension(input, 0); in Prepare() local 271 outputShape->dimensions = { n_batch, n_output }; in Prepare() 276 outputStateShape->dimensions = { n_batch, n_output }; in Prepare() 281 cellStateShape->dimensions = { n_batch, n_cell }; in Prepare() 290 scratchShape->dimensions = { n_batch, n_cell * 3 }; in Prepare() 293 scratchShape->dimensions = { n_batch, n_cell * 4 }; in Prepare() 303 const uint32_t n_batch = input_->shape().dimensions[0]; in Eval() local 321 forget_gate_scratch = cell_scratch + n_cell * n_batch; in Eval() 322 output_gate_scratch = cell_scratch + 2 * n_cell * n_batch; in Eval() 325 cell_scratch = input_gate_scratch + n_cell * n_batch; in Eval() [all …]
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D | LSTMTest.cpp | 76 LSTMOpModel(uint32_t n_batch, uint32_t n_input, in LSTMOpModel() argument 81 : n_batch_(n_batch), n_input_(n_input), in LSTMOpModel() 91 input_shapes.push_back({n_batch, n_output}); in LSTMOpModel() 92 input_shapes.push_back({n_batch, n_cell}); in LSTMOpModel() 114 {n_batch, n_cell * (use_cifg ? 3 : 4)}, in LSTMOpModel() 115 {n_batch, n_output}, in LSTMOpModel() 116 {n_batch, n_cell}, in LSTMOpModel() 117 {n_batch, n_output}, in LSTMOpModel() 134 Input_.insert(Input_.end(), n_batch * n_input, 0.f); in LSTMOpModel() 135 OutputStateIn_.insert(OutputStateIn_.end(), n_batch * n_output, 0.f); in LSTMOpModel() [all …]
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/frameworks/ml/nn/tools/test_generator/tests/P_lstm/ |
D | lstm.mod.py | 21 n_batch = 1 variable 27 input = Input("input", "TENSOR_FLOAT32", "{%d, %d}" % (n_batch, n_input)) 51 output_state_in = Input("output_state_in", "TENSOR_FLOAT32", "{%d, %d}" % (n_batch, n_output)) 52 cell_state_in = Input("cell_state_in", "TENSOR_FLOAT32", "{%d, %d}" % (n_batch, n_cell)) 58 scratch_buffer = IgnoredOutput("scratch_buffer", "TENSOR_FLOAT32", "{%d, %d}" % (n_batch, (n_cell *… 59 output_state_out = IgnoredOutput("output_state_out", "TENSOR_FLOAT32", "{%d, %d}" % (n_batch, n_out… 60 cell_state_out = IgnoredOutput("cell_state_out", "TENSOR_FLOAT32", "{%d, %d}" % (n_batch, n_cell)) 61 output = Output("output", "TENSOR_FLOAT32", "{%d, %d}" % (n_batch, n_output)) 153 scratch_buffer: [ 0 for x in range(n_batch * n_cell * 4) ], 154 cell_state_out: [ 0 for x in range(n_batch * n_cell) ], [all …]
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/frameworks/ml/nn/runtime/test/specs/ |
D | lstm2.mod.py | 21 n_batch = 1 variable 27 input = Input("input", "TENSOR_FLOAT32", "{%d, %d}" % (n_batch, n_input)) 51 output_state_in = Input("output_state_in", "TENSOR_FLOAT32", "{%d, %d}" % (n_batch, n_output)) 52 cell_state_in = Input("cell_state_in", "TENSOR_FLOAT32", "{%d, %d}" % (n_batch, n_cell)) 58 scratch_buffer = IgnoredOutput("scratch_buffer", "TENSOR_FLOAT32", "{%d, %d}" % (n_batch, n_cell * … 59 output_state_out = Output("output_state_out", "TENSOR_FLOAT32", "{%d, %d}" % (n_batch, n_output)) 60 cell_state_out = Output("cell_state_out", "TENSOR_FLOAT32", "{%d, %d}" % (n_batch, n_cell)) 61 output = Output("output", "TENSOR_FLOAT32", "{%d, %d}" % (n_batch, n_output)) 136 scratch_buffer: [ 0 for x in range(n_batch * n_cell * 4) ], 142 input0[output_state_in] = [ 0 for _ in range(n_batch * n_output) ] [all …]
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D | lstm2_state2.mod.py | 21 n_batch = 1 variable 27 input = Input("input", "TENSOR_FLOAT32", "{%d, %d}" % (n_batch, n_input)) 51 output_state_in = Input("output_state_in", "TENSOR_FLOAT32", "{%d, %d}" % (n_batch, n_output)) 52 cell_state_in = Input("cell_state_in", "TENSOR_FLOAT32", "{%d, %d}" % (n_batch, n_cell)) 58 scratch_buffer = IgnoredOutput("scratch_buffer", "TENSOR_FLOAT32", "{%d, %d}" % (n_batch, n_cell * … 59 output_state_out = IgnoredOutput("output_state_out", "TENSOR_FLOAT32", "{%d, %d}" % (n_batch, n_out… 60 cell_state_out = IgnoredOutput("cell_state_out", "TENSOR_FLOAT32", "{%d, %d}" % (n_batch, n_cell)) 61 output = Output("output", "TENSOR_FLOAT32", "{%d, %d}" % (n_batch, n_output)) 136 scratch_buffer: [ 0 for x in range(n_batch * n_cell * 4) ], 137 cell_state_out: [ 0 for x in range(n_batch * n_cell) ], [all …]
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D | lstm_state2.mod.py | 21 n_batch = 1 variable 27 input = Input("input", "TENSOR_FLOAT32", "{%d, %d}" % (n_batch, n_input)) 51 output_state_in = Input("output_state_in", "TENSOR_FLOAT32", "{%d, %d}" % (n_batch, n_output)) 52 cell_state_in = Input("cell_state_in", "TENSOR_FLOAT32", "{%d, %d}" % (n_batch, n_cell)) 58 scratch_buffer = IgnoredOutput("scratch_buffer", "TENSOR_FLOAT32", "{%d, %d}" % (n_batch, (n_cell *… 59 output_state_out = IgnoredOutput("output_state_out", "TENSOR_FLOAT32", "{%d, %d}" % (n_batch, n_out… 60 cell_state_out = IgnoredOutput("cell_state_out", "TENSOR_FLOAT32", "{%d, %d}" % (n_batch, n_cell)) 61 output = Output("output", "TENSOR_FLOAT32", "{%d, %d}" % (n_batch, n_output)) 144 scratch_buffer: [ 0 for x in range(n_batch * n_cell * 4) ], 145 cell_state_out: [ 0 for x in range(n_batch * n_cell) ], [all …]
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D | lstm3_state3.mod.py | 21 n_batch = 2 variable 27 input = Input("input", "TENSOR_FLOAT32", "{%d, %d}" % (n_batch, n_input)) 51 output_state_in = Input("output_state_in", "TENSOR_FLOAT32", "{%d, %d}" % (n_batch, n_output)) 52 cell_state_in = Input("cell_state_in", "TENSOR_FLOAT32", "{%d, %d}" % (n_batch, n_cell)) 58 scratch_buffer = IgnoredOutput("scratch_buffer", "TENSOR_FLOAT32", "{%d, %d}" % (n_batch, (n_cell *… 59 output_state_out = IgnoredOutput("output_state_out", "TENSOR_FLOAT32", "{%d, %d}" % (n_batch, n_out… 60 cell_state_out = IgnoredOutput("cell_state_out", "TENSOR_FLOAT32", "{%d, %d}" % (n_batch, n_cell)) 61 output = Output("output", "TENSOR_FLOAT32", "{%d, %d}" % (n_batch, n_output)) 648 scratch_buffer: [ 0 for x in range(n_batch * n_cell * 4) ], 649 cell_state_out: [ 0 for x in range(n_batch * n_cell) ], [all …]
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D | lstm3.mod.py | 21 n_batch = 2 variable 27 input = Input("input", "TENSOR_FLOAT32", "{%d, %d}" % (n_batch, n_input)) 51 output_state_in = Input("output_state_in", "TENSOR_FLOAT32", "{%d, %d}" % (n_batch, n_output)) 52 cell_state_in = Input("cell_state_in", "TENSOR_FLOAT32", "{%d, %d}" % (n_batch, n_cell)) 58 scratch_buffer = IgnoredOutput("scratch_buffer", "TENSOR_FLOAT32", "{%d, %d}" % (n_batch, (n_cell *… 59 output_state_out = Output("output_state_out", "TENSOR_FLOAT32", "{%d, %d}" % (n_batch, n_output)) 60 cell_state_out = Output("cell_state_out", "TENSOR_FLOAT32", "{%d, %d}" % (n_batch, n_cell)) 61 output = Output("output", "TENSOR_FLOAT32", "{%d, %d}" % (n_batch, n_output)) 625 input0[cell_state_in] = [ 0 for _ in range(n_batch * n_cell) ] 626 input0[output_state_in] = [ 0 for _ in range(n_batch * n_output) ] [all …]
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D | lstm2_state.mod.py | 21 n_batch = 1 variable 27 input = Input("input", "TENSOR_FLOAT32", "{%d, %d}" % (n_batch, n_input)) 51 output_state_in = Input("output_state_in", "TENSOR_FLOAT32", "{%d, %d}" % (n_batch, n_output)) 52 cell_state_in = Input("cell_state_in", "TENSOR_FLOAT32", "{%d, %d}" % (n_batch, n_cell)) 58 scratch_buffer = IgnoredOutput("scratch_buffer", "TENSOR_FLOAT32", "{%d, %d}" % (n_batch, n_cell * … 59 output_state_out = Output("output_state_out", "TENSOR_FLOAT32", "{%d, %d}" % (n_batch, n_output)) 60 cell_state_out = Output("cell_state_out", "TENSOR_FLOAT32", "{%d, %d}" % (n_batch, n_cell)) 61 output = Output("output", "TENSOR_FLOAT32", "{%d, %d}" % (n_batch, n_output)) 136 scratch_buffer: [ 0 for x in range(n_batch * n_cell * 4) ],
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D | lstm.mod.py | 21 n_batch = 1 variable 27 input = Input("input", "TENSOR_FLOAT32", "{%d, %d}" % (n_batch, n_input)) 51 output_state_in = Input("output_state_in", "TENSOR_FLOAT32", "{%d, %d}" % (n_batch, n_output)) 52 cell_state_in = Input("cell_state_in", "TENSOR_FLOAT32", "{%d, %d}" % (n_batch, n_cell)) 58 scratch_buffer = IgnoredOutput("scratch_buffer", "TENSOR_FLOAT32", "{%d, %d}" % (n_batch, (n_cell *… 59 output_state_out = Output("output_state_out", "TENSOR_FLOAT32", "{%d, %d}" % (n_batch, n_output)) 60 cell_state_out = Output("cell_state_out", "TENSOR_FLOAT32", "{%d, %d}" % (n_batch, n_cell)) 61 output = Output("output", "TENSOR_FLOAT32", "{%d, %d}" % (n_batch, n_output)) 144 scratch_buffer: [ 0 for x in range(n_batch * n_cell * 4) ],
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D | lstm3_state2.mod.py | 21 n_batch = 2 variable 27 input = Input("input", "TENSOR_FLOAT32", "{%d, %d}" % (n_batch, n_input)) 51 output_state_in = Input("output_state_in", "TENSOR_FLOAT32", "{%d, %d}" % (n_batch, n_output)) 52 cell_state_in = Input("cell_state_in", "TENSOR_FLOAT32", "{%d, %d}" % (n_batch, n_cell)) 58 scratch_buffer = IgnoredOutput("scratch_buffer", "TENSOR_FLOAT32", "{%d, %d}" % (n_batch, (n_cell *… 59 output_state_out = Output("output_state_out", "TENSOR_FLOAT32", "{%d, %d}" % (n_batch, n_output)) 60 cell_state_out = Output("cell_state_out", "TENSOR_FLOAT32", "{%d, %d}" % (n_batch, n_cell)) 61 output = Output("output", "TENSOR_FLOAT32", "{%d, %d}" % (n_batch, n_output)) 648 scratch_buffer: [ 0 for x in range(n_batch * n_cell * 4) ],
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D | lstm3_state.mod.py | 21 n_batch = 2 variable 27 input = Input("input", "TENSOR_FLOAT32", "{%d, %d}" % (n_batch, n_input)) 51 output_state_in = Input("output_state_in", "TENSOR_FLOAT32", "{%d, %d}" % (n_batch, n_output)) 52 cell_state_in = Input("cell_state_in", "TENSOR_FLOAT32", "{%d, %d}" % (n_batch, n_cell)) 58 scratch_buffer = IgnoredOutput("scratch_buffer", "TENSOR_FLOAT32", "{%d, %d}" % (n_batch, (n_cell *… 59 output_state_out = Output("output_state_out", "TENSOR_FLOAT32", "{%d, %d}" % (n_batch, n_output)) 60 cell_state_out = Output("cell_state_out", "TENSOR_FLOAT32", "{%d, %d}" % (n_batch, n_cell)) 61 output = Output("output", "TENSOR_FLOAT32", "{%d, %d}" % (n_batch, n_output)) 648 scratch_buffer: [ 0 for x in range(n_batch * n_cell * 4) ],
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D | lstm_state.mod.py | 21 n_batch = 1 variable 27 input = Input("input", "TENSOR_FLOAT32", "{%d, %d}" % (n_batch, n_input)) 51 output_state_in = Input("output_state_in", "TENSOR_FLOAT32", "{%d, %d}" % (n_batch, n_output)) 52 cell_state_in = Input("cell_state_in", "TENSOR_FLOAT32", "{%d, %d}" % (n_batch, n_cell)) 58 scratch_buffer = IgnoredOutput("scratch_buffer", "TENSOR_FLOAT32", "{%d, %d}" % (n_batch, (n_cell *… 59 output_state_out = Output("output_state_out", "TENSOR_FLOAT32", "{%d, %d}" % (n_batch, n_output)) 60 cell_state_out = Output("cell_state_out", "TENSOR_FLOAT32", "{%d, %d}" % (n_batch, n_cell)) 61 output = Output("output", "TENSOR_FLOAT32", "{%d, %d}" % (n_batch, n_output)) 144 scratch_buffer: [ 0 for x in range(n_batch * n_cell * 4) ],
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/frameworks/ml/nn/common/operations/internal/reference/ |
D | portable_tensor_utils.h | 34 int n_batch, float* result, 55 int n_batch, float* result, 64 int n_batch, 69 int n_batch, float* batch_vector); 111 int n_batch, float* result, in MatrixBatchVectorMultiplyAccumulate() argument 114 n_batch, result, result_stride); in MatrixBatchVectorMultiplyAccumulate() 130 int n_batch, float* result) { in VectorBatchVectorCwiseProductAccumulate() argument 132 n_batch, result); in VectorBatchVectorCwiseProductAccumulate() 142 int n_batch, float* result, in BatchVectorBatchVectorDotProduct() argument 144 PortableBatchVectorBatchVectorDotProduct(vector1, vector2, v_size, n_batch, in BatchVectorBatchVectorDotProduct() [all …]
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D | portable_tensor_utils.cc | 33 int n_batch, float* result, in PortableMatrixBatchVectorMultiplyAccumulate() argument 36 for (int b = 0; b < n_batch; b++) { in PortableMatrixBatchVectorMultiplyAccumulate() 67 int n_batch, float* result, in PortableBatchVectorBatchVectorDotProduct() argument 72 for (int b = 0; b < n_batch; b++) { in PortableBatchVectorBatchVectorDotProduct() 92 int n_batch, in PortableVectorBatchVectorCwiseProductAccumulate() argument 94 for (int b = 0; b < n_batch; b++) { in PortableVectorBatchVectorCwiseProductAccumulate() 102 int n_batch, float* batch_vector) { in PortableVectorBatchVectorAssign() argument 103 for (int b = 0; b < n_batch; b++) { in PortableVectorBatchVectorAssign()
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/frameworks/ml/nn/common/operations/internal/optimized/ |
D | neon_tensor_utils.h | 30 int n_batch, float* result, in MatrixBatchVectorMultiplyAccumulate() argument 33 vector, n_batch, result, result_stride); in MatrixBatchVectorMultiplyAccumulate() 50 int n_batch, float* result) { in VectorBatchVectorCwiseProductAccumulate() argument 52 batch_vector, n_batch, result); in VectorBatchVectorCwiseProductAccumulate() 62 int n_batch, float* result, in BatchVectorBatchVectorDotProduct() argument 64 PortableBatchVectorBatchVectorDotProduct(vector1, vector2, v_size, n_batch, in BatchVectorBatchVectorDotProduct() 68 void VectorBatchVectorAssign(const float* vector, int v_size, int n_batch, in VectorBatchVectorAssign() argument 70 PortableVectorBatchVectorAssign(vector, v_size, n_batch, batch_vector); in VectorBatchVectorAssign()
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D | tensor_utils_impl.h | 37 int n_batch, float* result, 41 int n_batch, float* result, 67 int n_batch, float* result, 76 int n_batch, 81 int n_batch, float* result); 95 int n_batch, float* batch_vector);
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D | neon_tensor_utils.cc | 33 int n_batch, float* result, in NeonMatrixBatchVectorMultiplyAccumulate() argument 46 for (int b = 0; b < n_batch; b++) { in NeonMatrixBatchVectorMultiplyAccumulate() 124 int n_batch, float* result) { in NeonVectorBatchVectorCwiseProductAccumulate() argument 141 for (int b = 0; b < n_batch; b++) { in NeonVectorBatchVectorCwiseProductAccumulate()
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/frameworks/ml/nn/common/operations/internal/ |
D | tensor_utils.h | 37 int n_batch, float* result, 71 int n_batch, float* result, 79 int n_batch, float* result); 82 void VectorBatchVectorAssign(const float* vector, int v_size, int n_batch,
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