/packages/modules/NeuralNetworks/runtime/test/specs/V1_3/ |
D | bidirectional_sequence_lstm.mod.py | 22 n_batch, argument 88 "{{{}, {}, {}}}".format(max_time, n_batch, n_fw_input)) 181 "{{{}, {}}}".format(n_batch, n_output)) 183 "{{{}, {}}}".format(n_batch, n_cell)) 186 "{{{}, {}}}".format(n_batch, n_output)) 188 "{{{}, {}}}".format(n_batch, n_cell)) 191 "{{{}, {}, {}}}".format(max_time, n_batch, n_bw_input)) 230 "{{{}, {}, {}}}".format(max_time, n_batch, n_output)) 232 "{{{}, {}, {}}}".format(max_time, n_batch, n_output)) 237 "{{{}, {}, {}}}".format(max_time, n_batch, n_output)) [all …]
|
D | unidirectional_sequence_lstm_layer_norm_cifg_peephole_state_output.mod.py | 24 n_batch = 2 variable 31 "{%d, %d, %d}" % (max_time, n_batch, n_input)) 71 "{%d, %d}" % (n_batch, n_output)) 73 "{%d, %d}" % (n_batch, n_cell)) 90 "{%d, %d, %d}" % (max_time, n_batch, n_output)) 92 "{%d, %d}" % (n_batch, n_output)) 94 "{%d, %d}" % (n_batch, n_cell)) 181 golden_output[(max_time - 1) * (n_batch * n_output):], 189 input0[output_state_in] = [0 for _ in range(n_batch * n_output)] 190 input0[cell_state_in] = [0 for _ in range(n_batch * n_cell)]
|
D | bidirectional_sequence_lstm_state_output.mod.py | 20 n_batch = 1 variable 26 input = Input("input", "TENSOR_FLOAT32", "{{{}, {}, {}}}".format(max_time, n_batch, n_input)) 107 "fw_activatiom_state", "TENSOR_FLOAT32", "{{{}, {}}}".format(n_batch, n_output)) 109 "fw_cell_state", "TENSOR_FLOAT32", "{{{}, {}}}".format(n_batch, n_cell)) 112 "bw_activatiom_state", "TENSOR_FLOAT32", "{{{}, {}}}".format(n_batch, n_output)) 114 "bw_cell_state", "TENSOR_FLOAT32", "{{{}, {}}}".format(n_batch, n_cell)) 116 aux_input = Input("input", "TENSOR_FLOAT32", "{{{}, {}, {}}}".format(max_time, n_batch, n_input)) 146 fw_output=Output("fw_output", "TENSOR_FLOAT32", "{{{}, {}, {}}}".format(max_time, n_batch, n_output… 147 bw_output=Output("bw_output", "TENSOR_FLOAT32", "{{{}, {}, {}}}".format(max_time, n_batch, n_output… 151 "{{{}, {}}}".format(n_batch, n_output)) [all …]
|
/packages/modules/NeuralNetworks/runtime/test/specs/V1_2/ |
D | layer_norm_lstm.mod.py | 22 n_batch = 2 variable 27 input = Input("input", "TENSOR_FLOAT32", "{%d, %d}" % (n_batch, n_input)) 69 "{%d, %d}" % (n_batch, n_output)) 71 "{%d, %d}" % (n_batch, n_cell)) 87 "{%d, %d}" % (n_batch, (n_cell * 4))) 89 "{%d, %d}" % (n_batch, n_output)) 91 "{%d, %d}" % (n_batch, n_cell)) 92 output = Output("output", "TENSOR_FLOAT32", "{%d, %d}" % (n_batch, n_output)) 183 scratch_buffer: [0] * (n_batch * n_cell * 4), 194 n_batch = 2 variable [all …]
|
D | lstm2_state2_float16.mod.py | 21 n_batch = 1 variable 27 input = Input("input", "TENSOR_FLOAT16", "{%d, %d}" % (n_batch, n_input)) 51 output_state_in = Input("output_state_in", "TENSOR_FLOAT16", "{%d, %d}" % (n_batch, n_output)) 52 cell_state_in = Input("cell_state_in", "TENSOR_FLOAT16", "{%d, %d}" % (n_batch, n_cell)) 58 scratch_buffer = IgnoredOutput("scratch_buffer", "TENSOR_FLOAT16", "{%d, %d}" % (n_batch, n_cell * … 59 output_state_out = IgnoredOutput("output_state_out", "TENSOR_FLOAT16", "{%d, %d}" % (n_batch, n_out… 60 cell_state_out = IgnoredOutput("cell_state_out", "TENSOR_FLOAT16", "{%d, %d}" % (n_batch, n_cell)) 61 output = Output("output", "TENSOR_FLOAT16", "{%d, %d}" % (n_batch, n_output)) 132 scratch_buffer: [ 0 for x in range(n_batch * n_cell * 3) ], 133 cell_state_out: [ 0 for x in range(n_batch * n_cell) ], [all …]
|
D | lstm3_float16.mod.py | 21 n_batch = 2 variable 27 input = Input("input", "TENSOR_FLOAT16", "{%d, %d}" % (n_batch, n_input)) 51 output_state_in = Input("output_state_in", "TENSOR_FLOAT16", "{%d, %d}" % (n_batch, n_output)) 52 cell_state_in = Input("cell_state_in", "TENSOR_FLOAT16", "{%d, %d}" % (n_batch, n_cell)) 58 scratch_buffer = IgnoredOutput("scratch_buffer", "TENSOR_FLOAT16", "{%d, %d}" % (n_batch, (n_cell *… 59 output_state_out = Output("output_state_out", "TENSOR_FLOAT16", "{%d, %d}" % (n_batch, n_output)) 60 cell_state_out = Output("cell_state_out", "TENSOR_FLOAT16", "{%d, %d}" % (n_batch, n_cell)) 61 output = Output("output", "TENSOR_FLOAT16", "{%d, %d}" % (n_batch, n_output)) 620 input0[cell_state_in] = [ 0 for _ in range(n_batch * n_cell) ] 621 input0[output_state_in] = [ 0 for _ in range(n_batch * n_output) ] [all …]
|
D | lstm2_float16.mod.py | 21 n_batch = 1 variable 27 input = Input("input", "TENSOR_FLOAT16", "{%d, %d}" % (n_batch, n_input)) 51 output_state_in = Input("output_state_in", "TENSOR_FLOAT16", "{%d, %d}" % (n_batch, n_output)) 52 cell_state_in = Input("cell_state_in", "TENSOR_FLOAT16", "{%d, %d}" % (n_batch, n_cell)) 58 scratch_buffer = IgnoredOutput("scratch_buffer", "TENSOR_FLOAT16", "{%d, %d}" % (n_batch, n_cell * … 59 output_state_out = Output("output_state_out", "TENSOR_FLOAT16", "{%d, %d}" % (n_batch, n_output)) 60 cell_state_out = Output("cell_state_out", "TENSOR_FLOAT16", "{%d, %d}" % (n_batch, n_cell)) 61 output = Output("output", "TENSOR_FLOAT16", "{%d, %d}" % (n_batch, n_output)) 132 scratch_buffer: [ 0 for x in range(n_batch * n_cell * 3) ], 138 input0[output_state_in] = [ 0 for _ in range(n_batch * n_output) ] [all …]
|
D | lstm_state2_float16.mod.py | 21 n_batch = 1 variable 27 input = Input("input", "TENSOR_FLOAT16", "{%d, %d}" % (n_batch, n_input)) 51 output_state_in = Input("output_state_in", "TENSOR_FLOAT16", "{%d, %d}" % (n_batch, n_output)) 52 cell_state_in = Input("cell_state_in", "TENSOR_FLOAT16", "{%d, %d}" % (n_batch, n_cell)) 58 scratch_buffer = IgnoredOutput("scratch_buffer", "TENSOR_FLOAT16", "{%d, %d}" % (n_batch, (n_cell *… 59 output_state_out = IgnoredOutput("output_state_out", "TENSOR_FLOAT16", "{%d, %d}" % (n_batch, n_out… 60 cell_state_out = IgnoredOutput("cell_state_out", "TENSOR_FLOAT16", "{%d, %d}" % (n_batch, n_cell)) 61 output = Output("output", "TENSOR_FLOAT16", "{%d, %d}" % (n_batch, n_output)) 140 scratch_buffer: [ 0 for x in range(n_batch * n_cell * 4) ], 141 cell_state_out: [ 0 for x in range(n_batch * n_cell) ], [all …]
|
D | lstm3_state3_float16.mod.py | 21 n_batch = 2 variable 27 input = Input("input", "TENSOR_FLOAT16", "{%d, %d}" % (n_batch, n_input)) 51 output_state_in = Input("output_state_in", "TENSOR_FLOAT16", "{%d, %d}" % (n_batch, n_output)) 52 cell_state_in = Input("cell_state_in", "TENSOR_FLOAT16", "{%d, %d}" % (n_batch, n_cell)) 58 scratch_buffer = IgnoredOutput("scratch_buffer", "TENSOR_FLOAT16", "{%d, %d}" % (n_batch, (n_cell *… 59 output_state_out = IgnoredOutput("output_state_out", "TENSOR_FLOAT16", "{%d, %d}" % (n_batch, n_out… 60 cell_state_out = IgnoredOutput("cell_state_out", "TENSOR_FLOAT16", "{%d, %d}" % (n_batch, n_cell)) 61 output = Output("output", "TENSOR_FLOAT16", "{%d, %d}" % (n_batch, n_output)) 643 scratch_buffer: [ 0 for x in range(n_batch * n_cell * 4) ], 644 cell_state_out: [ 0 for x in range(n_batch * n_cell) ], [all …]
|
D | lstm2_state_float16.mod.py | 21 n_batch = 1 variable 27 input = Input("input", "TENSOR_FLOAT16", "{%d, %d}" % (n_batch, n_input)) 51 output_state_in = Input("output_state_in", "TENSOR_FLOAT16", "{%d, %d}" % (n_batch, n_output)) 52 cell_state_in = Input("cell_state_in", "TENSOR_FLOAT16", "{%d, %d}" % (n_batch, n_cell)) 58 scratch_buffer = IgnoredOutput("scratch_buffer", "TENSOR_FLOAT16", "{%d, %d}" % (n_batch, n_cell * … 59 output_state_out = Output("output_state_out", "TENSOR_FLOAT16", "{%d, %d}" % (n_batch, n_output)) 60 cell_state_out = Output("cell_state_out", "TENSOR_FLOAT16", "{%d, %d}" % (n_batch, n_cell)) 61 output = Output("output", "TENSOR_FLOAT16", "{%d, %d}" % (n_batch, n_output)) 132 scratch_buffer: [ 0 for x in range(n_batch * n_cell * 3) ],
|
D | lstm3_state2_float16.mod.py | 21 n_batch = 2 variable 27 input = Input("input", "TENSOR_FLOAT16", "{%d, %d}" % (n_batch, n_input)) 51 output_state_in = Input("output_state_in", "TENSOR_FLOAT16", "{%d, %d}" % (n_batch, n_output)) 52 cell_state_in = Input("cell_state_in", "TENSOR_FLOAT16", "{%d, %d}" % (n_batch, n_cell)) 58 scratch_buffer = IgnoredOutput("scratch_buffer", "TENSOR_FLOAT16", "{%d, %d}" % (n_batch, (n_cell *… 59 output_state_out = Output("output_state_out", "TENSOR_FLOAT16", "{%d, %d}" % (n_batch, n_output)) 60 cell_state_out = Output("cell_state_out", "TENSOR_FLOAT16", "{%d, %d}" % (n_batch, n_cell)) 61 output = Output("output", "TENSOR_FLOAT16", "{%d, %d}" % (n_batch, n_output)) 643 scratch_buffer: [ 0 for x in range(n_batch * n_cell * 4) ],
|
/packages/modules/NeuralNetworks/common/cpu_operations/ |
D | LSTM.cpp | 348 const uint32_t n_batch = SizeOfDimension(input_, 0); in Prepare() local 376 outputShape->dimensions = {n_batch, n_output}; in Prepare() 381 outputStateShape->dimensions = {n_batch, n_output}; in Prepare() 386 cellStateShape->dimensions = {n_batch, n_cell}; in Prepare() 392 scratchShape->dimensions = {n_batch, n_cell * 3}; in Prepare() 395 scratchShape->dimensions = {n_batch, n_cell * 4}; in Prepare() 788 const uint32_t n_batch = input_shape.dimensions[0]; in LSTMStep() local 802 forget_gate_scratch = cell_scratch + n_cell * n_batch; in LSTMStep() 803 output_gate_scratch = cell_scratch + 2 * n_cell * n_batch; in LSTMStep() 806 cell_scratch = input_gate_scratch + n_cell * n_batch; in LSTMStep() [all …]
|
/packages/modules/NeuralNetworks/runtime/test/specs/V1_0/ |
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)) 132 scratch_buffer: [ 0 for x in range(n_batch * n_cell * 3) ], 133 cell_state_out: [ 0 for x in range(n_batch * n_cell) ], [all …]
|
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)) 132 scratch_buffer: [ 0 for x in range(n_batch * n_cell * 3) ], 138 input0[output_state_in] = [ 0 for _ in range(n_batch * n_output) ] [all …]
|
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)) 140 scratch_buffer: [ 0 for x in range(n_batch * n_cell * 4) ], 141 cell_state_out: [ 0 for x in range(n_batch * n_cell) ], [all …]
|
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)) 620 input0[cell_state_in] = [ 0 for _ in range(n_batch * n_cell) ] 621 input0[output_state_in] = [ 0 for _ in range(n_batch * n_output) ] [all …]
|
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)) 643 scratch_buffer: [ 0 for x in range(n_batch * n_cell * 4) ], 644 cell_state_out: [ 0 for x in range(n_batch * n_cell) ], [all …]
|
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)) 132 scratch_buffer: [ 0 for x in range(n_batch * n_cell * 3) ],
|
/packages/modules/NeuralNetworks/runtime/test/specs/V1_1/ |
D | lstm_state2_relaxed.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)) 141 scratch_buffer: [ 0 for x in range(n_batch * n_cell * 4) ], 142 cell_state_out: [ 0 for x in range(n_batch * n_cell) ], [all …]
|
D | lstm2_relaxed.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)) 133 scratch_buffer: [ 0 for x in range(n_batch * n_cell * 3) ], 139 input0[output_state_in] = [ 0 for _ in range(n_batch * n_output) ] [all …]
|
D | lstm2_state2_relaxed.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)) 133 scratch_buffer: [ 0 for x in range(n_batch * n_cell * 3) ], 134 cell_state_out: [ 0 for x in range(n_batch * n_cell) ], [all …]
|
D | lstm3_relaxed.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)) 621 input0[cell_state_in] = [ 0 for _ in range(n_batch * n_cell) ] 622 input0[output_state_in] = [ 0 for _ in range(n_batch * n_output) ] [all …]
|
D | lstm3_state3_relaxed.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)) 644 scratch_buffer: [ 0 for x in range(n_batch * n_cell * 4) ], 645 cell_state_out: [ 0 for x in range(n_batch * n_cell) ], [all …]
|
/packages/modules/NeuralNetworks/common/ |
D | QuantUtils.cpp | 12 int n_batch, int n_input, int16_t* output) { in ApplyLayerNorm() argument 14 for (int i = 0; i < n_batch; ++i) { in ApplyLayerNorm() 86 void ApplySigmoid(const int16_t* input, int32_t n_batch, int32_t n_input, int16_t* output) { in ApplySigmoid() argument 87 for (int batch = 0; batch < n_batch; ++batch) { in ApplySigmoid() 99 void CwiseMul(const int16_t* input_1, const int16_t* input_2, int n_batch, int n_input, int shift, in CwiseMul() argument 101 for (int batch = 0; batch < n_batch; ++batch) { in CwiseMul() 113 int32_t n_batch, int32_t n_input, int32_t output_zp, int8_t* output) { in CwiseMul() argument 114 for (int batch = 0; batch < n_batch; ++batch) { in CwiseMul() 138 void CwiseAdd(const int16_t* input_1, const int16_t* input_2, int n_batch, int n_input, in CwiseAdd() argument 140 for (int batch = 0; batch < n_batch; ++batch) { in CwiseAdd() [all …]
|
/packages/modules/NeuralNetworks/tools/test_generator/tests/P_vts_backward_compatibility_float/ |
D | lstm_float.mod.py | 17 n_batch = 1 variable 23 input = Input("input", "TENSOR_FLOAT32", "{%d, %d}" % (n_batch, n_input)) 47 output_state_in = Input("output_state_in", "TENSOR_FLOAT32", "{%d, %d}" % (n_batch, n_output)) 48 cell_state_in = Input("cell_state_in", "TENSOR_FLOAT32", "{%d, %d}" % (n_batch, n_cell)) 54 scratch_buffer = IgnoredOutput("scratch_buffer", "TENSOR_FLOAT32", "{%d, %d}" % (n_batch, (n_cell *… 55 output_state_out = Output("output_state_out", "TENSOR_FLOAT32", "{%d, %d}" % (n_batch, n_output)) 56 cell_state_out = Output("cell_state_out", "TENSOR_FLOAT32", "{%d, %d}" % (n_batch, n_cell)) 57 output = Output("output", "TENSOR_FLOAT32", "{%d, %d}" % (n_batch, n_output)) 137 scratch_buffer: [ 0 for x in range(n_batch * n_cell * 4) ],
|