| /external/tensorflow/tensorflow/contrib/lite/kernels/ |
| unidirectional_sequence_lstm.cc | 36 // Input Tensors of size {max_time, n_batch, n_input}
234 const int n_batch = input->dims->data[1]; local
264 output_size->data[1] = n_batch;
270 output_state_size->data[0] = n_batch;
277 cell_size->data[0] = n_batch;
291 scratch_buffer_size->data[0] = n_batch;
298 scratch_buffer_size->data[0] = n_batch;
355 const int n_batch = input->dims->data[1]; local
374 forget_gate_scratch = scratch_buffer->data.f + n_cell * n_batch;
375 output_gate_scratch = scratch_buffer->data.f + 2 * n_cell * n_batch;
[all...] |
| lstm.cc | 36 // Input Tensors of size {n_batch, n_input}
233 const int n_batch = input->dims->data[0]; local
262 output_size->data[0] = n_batch;
268 output_state_size->data[0] = n_batch;
275 cell_size->data[0] = n_batch;
289 scratch_buffer_size->data[0] = n_batch;
296 scratch_buffer_size->data[0] = n_batch;
352 const int n_batch = input->dims->data[0]; local
371 forget_gate_scratch = scratch_buffer->data.f + n_cell * n_batch;
372 output_gate_scratch = scratch_buffer->data.f + 2 * n_cell * n_batch;
[all...] |
| optional_tensor_test.cc | 33 LSTMOpModel(int n_batch, int n_input, int n_cell, int n_output, bool use_cifg,
37 : n_batch_(n_batch),
247 const int n_batch = 1; local
253 LSTMOpModel lstm(n_batch, n_input, n_cell, n_output,
259 {n_batch, n_input}, // input tensor
|
| /frameworks/ml/nn/common/operations/ |
| LSTM.cpp | 246 const uint32_t n_batch = SizeOfDimension(input, 0); local
271 outputShape->dimensions = { n_batch, n_output };
276 outputStateShape->dimensions = { n_batch, n_output };
281 cellStateShape->dimensions = { n_batch, n_cell };
290 scratchShape->dimensions = { n_batch, n_cell * 3 };
293 scratchShape->dimensions = { n_batch, n_cell * 4 };
303 const uint32_t n_batch = input_->shape().dimensions[0]; local
321 forget_gate_scratch = cell_scratch + n_cell * n_batch;
322 output_gate_scratch = cell_scratch + 2 * n_cell * n_batch;
325 cell_scratch = input_gate_scratch + n_cell * n_batch;
333 n_cell, n_batch, input_gate_scratch); local
336 n_cell, n_batch, forget_gate_scratch); local
338 n_cell, n_batch, cell_scratch); local
340 n_cell, n_batch, output_gate_scratch); local
346 GetBuffer<float>(input_), n_batch, input_gate_scratch, \/*result_stride*\/1); local
350 GetBuffer<float>(input_), n_batch, forget_gate_scratch, \/*result_stride*\/1); local
353 GetBuffer<float>(input_), n_batch, cell_scratch, \/*result_stride*\/1); local
356 GetBuffer<float>(input_), n_batch, output_gate_scratch, \/*result_stride*\/1); local
362 GetBuffer<float>(output_state_in_), n_batch, input_gate_scratch, \/*result_stride*\/1); local
366 GetBuffer<float>(output_state_in_), n_batch, forget_gate_scratch, \/*result_stride*\/1); local
369 GetBuffer<float>(output_state_in_), n_batch, cell_scratch, \/*result_stride*\/1); local
372 GetBuffer<float>(output_state_in_), n_batch, output_gate_scratch, \/*result_stride*\/1); local
379 GetBuffer<float>(cell_state_in_), n_batch, input_gate_scratch); local
390 GetBuffer<float>(cell_state_in_), n_batch, forget_gate_scratch); local
423 GetBuffer<float>(cell_state_out_), n_batch, output_gate_scratch); local
442 n_batch, GetBuffer<float>(output_)); local
448 output_gate_scratch, n_batch, GetBuffer<float>(output_), local
[all...] |
| /frameworks/ml/nn/tools/test_generator/tests/P_lstm/ |
| 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 * 4)))
59 output_state_out = IgnoredOutput("output_state_out", "TENSOR_FLOAT32", "{%d, %d}" % (n_batch, n_output))
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...] |
| /external/tensorflow/tensorflow/contrib/lite/kernels/internal/optimized/ |
| neon_tensor_utils.h | 29 int n_batch, float* result,
32 vector, n_batch, result, result_stride);
49 int n_batch, float* result) {
51 batch_vector, n_batch, result);
61 int n_batch, float* result,
64 n_batch, result, result_stride);
67 void VectorBatchVectorAssign(const float* vector, int v_size, int n_batch,
69 PortableVectorBatchVectorAssign(vector, v_size, n_batch, batch_vector);
|
| tensor_utils_impl.h | 36 int n_batch, float* result,
40 int n_batch, float* result,
68 int n_batch, float* result,
72 int n_batch, float* result,
81 int n_batch,
86 int n_batch, float* result);
100 int n_batch, float* batch_vector);
|
| /external/tensorflow/tensorflow/contrib/lite/kernels/internal/reference/ |
| portable_tensor_utils.h | 33 int n_batch, float* result,
54 int n_batch, float* result,
63 int n_batch,
68 int n_batch, float* batch_vector);
108 int n_batch, float* result,
111 n_batch, result, result_stride);
127 int n_batch, float* result) {
129 n_batch, result);
139 int n_batch, float* result,
141 PortableBatchVectorBatchVectorDotProduct(vector1, vector2, v_size, n_batch,
[all...] |
| portable_tensor_utils.cc | 33 int n_batch, float* result,
36 for (int b = 0; b < n_batch; b++) {
67 int n_batch, float* result,
72 for (int b = 0; b < n_batch; b++) {
92 int n_batch,
94 for (int b = 0; b < n_batch; b++) {
102 int n_batch, float* batch_vector) {
103 for (int b = 0; b < n_batch; b++) {
|
| /frameworks/ml/nn/runtime/test/specs/V1_0/ |
| 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 * 3))
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...] |
| 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 * 3))
59 output_state_out = IgnoredOutput("output_state_out", "TENSOR_FLOAT32", "{%d, %d}" % (n_batch, n_output))
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...] |
| 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 * 4)))
59 output_state_out = IgnoredOutput("output_state_out", "TENSOR_FLOAT32", "{%d, %d}" % (n_batch, n_output))
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...] |
| 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 * 4)))
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))
140 scratch_buffer: [ 0 for x in range(n_batch * n_cell * 4) ],
|
| 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 * 3))
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) ],
|
| 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 * 4)))
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))
140 scratch_buffer: [ 0 for x in range(n_batch * n_cell * 4) ],
|
| 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 * 4)))
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))
[all...] |
| 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 * 4)))
59 output_state_out = IgnoredOutput("output_state_out", "TENSOR_FLOAT32", "{%d, %d}" % (n_batch, n_output))
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))
[all...] |
| /frameworks/ml/nn/runtime/test/specs/V1_1/ |
| 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 * 3))
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...] |
| 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 * 3))
59 output_state_out = IgnoredOutput("output_state_out", "TENSOR_FLOAT32", "{%d, %d}" % (n_batch, n_output))
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...] |
| 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 * 4)))
59 output_state_out = IgnoredOutput("output_state_out", "TENSOR_FLOAT32", "{%d, %d}" % (n_batch, n_output))
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...] |
| lstm2_state_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 * 3))
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) ],
|
| lstm_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 * 4)))
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))
141 scratch_buffer: [ 0 for x in range(n_batch * n_cell * 4) ],
|
| lstm_state_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 * 4)))
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))
141 scratch_buffer: [ 0 for x in range(n_batch * n_cell * 4) ],
|
| 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 * 4)))
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))
[all...] |
| /external/tensorflow/tensorflow/contrib/lite/kernels/internal/ |
| tensor_utils.h | 34 int n_batch, float* result,
51 // Dot product of two batch vectors of size n_batch * v_size:
60 // Then result will be a vector of n_batch size which will be saved with a
68 int n_batch, float* result,
76 int n_batch, float* result);
79 void VectorBatchVectorAssign(const float* vector, int v_size, int n_batch,
|
