| /external/tensorflow/tensorflow/lite/kernels/ |
| D | unidirectional_sequence_rnn_test.cc | 287 float* batch_start = rnn_input; in TEST() local
288 float* batch_end = batch_start + input_sequence_size; in TEST()
289 rnn.SetInput(0, batch_start, batch_end); in TEST()
290 rnn.SetInput(input_sequence_size, batch_start, batch_end); in TEST()
316 float* batch_start = rnn_input; in TEST_P() local
317 float* batch_end = batch_start + input_sequence_size; in TEST_P()
318 rnn.SetInput(0, batch_start, batch_end); in TEST_P()
319 rnn.SetInput(input_sequence_size, batch_start, batch_end); in TEST_P()
343 float* batch_start = rnn_input; in TEST_P() local
344 float* batch_end = batch_start + input_sequence_size; in TEST_P()
[all …]
|
| D | bidirectional_sequence_rnn_test.cc | 878 float* batch_start = rnn_input; in TEST_P() local
879 float* batch_end = batch_start + input_sequence_size; in TEST_P()
880 rnn.SetInput(0, batch_start, batch_end); in TEST_P()
881 rnn.SetInput(input_sequence_size, batch_start, batch_end); in TEST_P()
929 float* batch_start = rnn_input + i * rnn.input_size(); in TEST_P() local
930 float* batch_end = batch_start + rnn.input_size(); in TEST_P()
932 rnn.SetInput(2 * i * rnn.input_size(), batch_start, batch_end); in TEST_P()
933 rnn.SetInput((2 * i + 1) * rnn.input_size(), batch_start, batch_end); in TEST_P()
973 float* batch_start = rnn_input; in TEST_P() local
974 float* batch_end = batch_start + input_sequence_size; in TEST_P()
[all …]
|
| D | basic_rnn_test.cc | 269 float* batch_start = rnn_input + i * rnn.input_size(); in TEST() local
270 float* batch_end = batch_start + rnn.input_size(); in TEST()
271 rnn.SetInput(0, batch_start, batch_end); in TEST()
272 rnn.SetInput(rnn.input_size(), batch_start, batch_end); in TEST()
298 float* batch_start = rnn_input + i * rnn.input_size(); in TEST_P() local
299 float* batch_end = batch_start + rnn.input_size(); in TEST_P()
300 rnn.SetInput(0, batch_start, batch_end); in TEST_P()
301 rnn.SetInput(rnn.input_size(), batch_start, batch_end); in TEST_P()
326 float* batch_start = rnn_input + i * rnn.input_size(); in TEST_P() local
327 float* batch_end = batch_start + rnn.input_size(); in TEST_P()
[all …]
|
| D | svdf_test.cc | 247 float* batch_start = in VerifyGoldens() local
249 float* batch_end = batch_start + svdf_input_size * svdf_num_batches; in VerifyGoldens()
250 svdf->SetInput(0, batch_start, batch_end); in VerifyGoldens()
|
| D | lstm_test.cc | 359 const float* batch_start = lstm_input_[i][b].data(); in VerifyGoldens() local
360 const float* batch_end = batch_start + num_inputs; in VerifyGoldens()
361 lstm->SetInput(b * num_inputs, batch_start, batch_end); in VerifyGoldens()
370 const float* batch_start = lstm_golden_output_[i][b].data(); in VerifyGoldens() local
371 const float* batch_end = batch_start + num_outputs; in VerifyGoldens()
372 expected.insert(expected.end(), batch_start, batch_end); in VerifyGoldens()
2400 const float* batch_start = input[b].data() + i * num_inputs; in VerifyGoldens() local
2401 const float* batch_end = batch_start + num_inputs; in VerifyGoldens()
2404 b * sparse_layer_norm_lstm->num_inputs(), batch_start, batch_end); in VerifyGoldens()
|
| D | unidirectional_sequence_lstm_test.cc | 402 const float* batch_start = input[b].data() + i * num_inputs; in VerifyGoldens() local
403 const float* batch_end = batch_start + num_inputs; in VerifyGoldens()
405 lstm->SetInput(((i * num_batches) + b) * num_inputs, batch_start, in VerifyGoldens()
411 const float* batch_start = input[b].data(); in VerifyGoldens() local
412 const float* batch_end = batch_start + input_sequence_size * num_inputs; in VerifyGoldens()
414 lstm->SetInput(b * input_sequence_size * num_inputs, batch_start, in VerifyGoldens()
2524 const float* batch_start = input[b].data() + i * num_inputs; in VerifyGoldens() local
2525 const float* batch_end = batch_start + num_inputs; in VerifyGoldens()
2527 lstm->SetInput(((i * num_batches) + b) * num_inputs, batch_start, in VerifyGoldens()
|
| D | fully_connected_test.cc | 1165 float* batch_start = fully_connected_input + i * m.input_size(); in TEST_P() local
1166 float* batch_end = batch_start + m.input_size(); in TEST_P()
1167 m.SetInput(0, batch_start, batch_end); in TEST_P()
1168 m.SetInput(m.input_size(), batch_start, batch_end); in TEST_P()
|
| /external/tensorflow/tensorflow/python/keras/engine/ |
| D | training_utils_v1_test.py | 265 …def wrapped(batch_element, batch_start, batch_end, is_finished): # pylint: disable=unused-argument argument
315 batch_start = 0
320 batch_end = batch_start + batch.shape[0]
321 aggregator.aggregate(batch, batch_start, batch_end)
322 batch_start = batch_end
341 batch_start = 0
346 batch_end = batch_start + batch[0].shape[0]
347 aggregator.aggregate(batch, batch_start, batch_end)
348 batch_start = batch_end
|
| D | training_utils_v1.py | 105 def aggregate(self, batch_outs, batch_start=None, batch_end=None): argument
143 def aggregate(self, batch_outs, batch_start=None, batch_end=None): argument
148 self.results[0] += batch_outs[0] * (batch_end - batch_start)
286 def aggregate(self, batch_element, batch_start=None, batch_end=None): argument
377 def aggregate(self, batch_element, batch_start, batch_end): argument
383 if batch_end - batch_start == self.num_samples:
397 self.results[batch_start:batch_end] = batch_element
402 args=(batch_element, batch_start, batch_end, is_finished))
405 def _slice_assign(self, batch_element, batch_start, batch_end, is_finished): argument
408 self.results[batch_start:batch_end] = batch_element
[all …]
|
| D | training_arrays_v1.py | 353 for batch_index, (batch_start, batch_end) in enumerate(batches):
354 batch_ids = index_array[batch_start:batch_end]
391 aggregator.aggregate(batch_outs, batch_start, batch_end)
|
| D | training_generator_v1.py | 481 for (batch_start, batch_end) in batches:
482 batch_ids = index_array[batch_start:batch_end]
|
| /external/tensorflow/tensorflow/lite/delegates/gpu/cl/kernels/ |
| D | lstm_full_test.cc | 242 const float* batch_start = lstm_input_[i][b].data(); in VerifyGoldens() local
243 const float* batch_end = batch_start + num_inputs; in VerifyGoldens()
244 lstm->SetInput(b * num_inputs, batch_start, batch_end); in VerifyGoldens()
253 const float* batch_start = lstm_golden_output_[i][b].data(); in VerifyGoldens() local
254 const float* batch_end = batch_start + num_outputs; in VerifyGoldens()
255 expected.insert(expected.end(), batch_start, batch_end); in VerifyGoldens()
|
| /external/rust/crates/plotters-backend/src/rasterizer/ |
| D | line.rs | 94 let batch_start = (f64::from(from.1.min(size_limit.1 as i32 - 2).max(0) - from.1) / grad) in draw_line() localVariable
103 let mut y = f64::from(from.1) + f64::from(batch_start - from.0) * grad; in draw_line()
105 for x in batch_start..=batch_limit { in draw_line()
|
| /external/tensorflow/tensorflow/lite/kernels/internal/optimized/integer_ops/ |
| D | depthwise_conv_hybrid.h | 144 int batch_start = 0; in DepthwiseConvHybridGeneral() local
154 batch_start = thread_start; in DepthwiseConvHybridGeneral()
156 output_ptr_offset = batch_start * FlatSizeSkipDim(output_shape, 0); in DepthwiseConvHybridGeneral()
170 for (int b = batch_start; b < batch_end; ++b) { in DepthwiseConvHybridGeneral()
|
| D | depthwise_conv_hybrid_3x3_filter.h | 3126 int batch_start = 0;
3135 batch_start = thread_start;
3146 for (int32 b = batch_start; b < batch_end; ++b) {
|
| D | depthwise_conv_3x3_filter.h | 2968 int batch_start = 0;
2977 batch_start = thread_start;
2988 for (int32 b = batch_start; b < batch_end; ++b) {
|
| /external/XNNPACK/src/xnnpack/ |
| D | indirection.h | 75 size_t batch_start,
|
| D | compute.h | 893 size_t batch_start,
914 size_t batch_start,
|
| /external/libtextclassifier/native/annotator/ |
| D | annotator.cc | 2987 for (int batch_start = span_of_interest.first; in ModelClickContextScoreChunks() local
2988 batch_start < span_of_interest.second; batch_start += max_batch_size) { in ModelClickContextScoreChunks()
2990 std::min(batch_start + max_batch_size, span_of_interest.second); in ModelClickContextScoreChunks()
2995 for (int click_pos = batch_start; click_pos < batch_end; ++click_pos) { in ModelClickContextScoreChunks()
3001 const int batch_size = batch_end - batch_start; in ModelClickContextScoreChunks()
3018 for (int click_pos = batch_start; click_pos < batch_end; ++click_pos) { in ModelClickContextScoreChunks()
3020 logits.data() + logits.dim(1) * (click_pos - batch_start), in ModelClickContextScoreChunks()
3096 for (int batch_start = 0; batch_start < candidate_spans.size(); in ModelBoundsSensitiveScoreChunks() local
3097 batch_start += max_batch_size) { in ModelBoundsSensitiveScoreChunks()
3098 const int batch_end = std::min(batch_start + max_batch_size, in ModelBoundsSensitiveScoreChunks()
[all …]
|
| /external/igt-gpu-tools/benchmarks/ |
| D | gem_wsim.c | 1118 unsigned long batch_start = w->bb_sz; in terminate_bb() local
1124 batch_start -= sizeof(uint32_t); /* bbend */ in terminate_bb()
1126 batch_start -= 4 * sizeof(uint32_t); in terminate_bb()
1128 batch_start -= 12 * sizeof(uint32_t); in terminate_bb()
1131 batch_start -= 4 * sizeof(uint32_t); /* MI_ARB_CHK + MI_BATCH_BUFFER_START */ in terminate_bb()
1133 mmap_start = rounddown(batch_start, PAGE_SIZE); in terminate_bb()
1140 cs = (uint32_t *)((char *)ptr + batch_start - mmap_start); in terminate_bb()
1143 w->reloc[r++].offset = batch_start + 2 * sizeof(uint32_t); in terminate_bb()
1144 batch_start += 4 * sizeof(uint32_t); in terminate_bb()
1154 w->reloc[r++].offset = batch_start + sizeof(uint32_t); in terminate_bb()
[all …]
|
| /external/XNNPACK/src/ |
| D | operator-run.c | 721 size_t batch_start, in xnn_compute_prelu() argument
726 const void* x = (const void*) ((uintptr_t) context->x + x_stride * batch_start); in xnn_compute_prelu()
727 void* y = (void*) ((uintptr_t) context->y + y_stride * batch_start); in xnn_compute_prelu()
880 size_t batch_start, in xnn_compute_vmulcaddc() argument
886 const void* x = (const void*) ((uintptr_t) context->x + x_stride * batch_start); in xnn_compute_vmulcaddc()
887 void* y = (void*) ((uintptr_t) context->y + y_stride * batch_start); in xnn_compute_vmulcaddc()
|
| D | indirection.c | 524 size_t batch_start, in xnn_indirection_init_unpool2d() argument
540 for (size_t image = batch_start; image < batch_size; image++) { in xnn_indirection_init_unpool2d()
|
| /external/tensorflow/tensorflow/lite/kernels/internal/optimized/ |
| D | depthwiseconv_float.h | 1003 int batch_start = 0;
1014 batch_start = thread_start;
1016 output_ptr_offset = batch_start * FlatSizeSkipDim(output_shape, 0);
1032 for (int b = batch_start; b < batch_end; ++b) {
|
| /external/tensorflow/tensorflow/lite/delegates/nnapi/ |
| D | nnapi_delegate_test.cc | 2804 float* batch_start = rnn_input + i * rnn.input_size(); in TEST() local
2805 float* batch_end = batch_start + rnn.input_size(); in TEST()
2806 rnn.SetInput(0, batch_start, batch_end); in TEST()
2807 rnn.SetInput(rnn.input_size(), batch_start, batch_end); in TEST()
3007 float* batch_start = in VerifyGoldens() local
3009 float* batch_end = batch_start + svdf_input_size * svdf_num_batches; in VerifyGoldens()
3010 svdf->SetInput(0, batch_start, batch_end); in VerifyGoldens()
3384 const float* batch_start = input[b].data() + i * num_inputs; in VerifyGoldens() local
3385 const float* batch_end = batch_start + num_inputs; in VerifyGoldens()
3387 lstm->SetInput(b * lstm->num_inputs(), batch_start, batch_end); in VerifyGoldens()
|
| /external/tensorflow/tensorflow/python/ops/numpy_ops/ |
| D | np_array_ops.py | 1714 batch_start = dims[0]
1715 if batch_start < 0:
1716 batch_start += len(dims) - batch_size
1719 updates = moveaxis(updates, range_(batch_start, batch_size),
|