/external/tensorflow/tensorflow/core/framework/ |
H A D | allocator.h | 110 T* Allocate(size_t num_elements) { argument 111 return Allocate<T>(num_elements, AllocationAttributes()); 115 T* Allocate(size_t num_elements, argument 120 if (num_elements > (std::numeric_limits<size_t>::max() / sizeof(T))) { 124 void* p = AllocateRaw(kAllocatorAlignment, sizeof(T) * num_elements, 127 if (typed_p) RunCtor<T>(typed_p, num_elements); 132 void Deallocate(T* ptr, size_t num_elements) { argument 134 RunDtor<T>(ptr, num_elements);
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H A D | tensor_shape.cc | 60 int64 num_elements = 1; 65 num_elements = -1; 66 } else if (!kIsPartial || num_elements >= 0) { 67 num_elements = MultiplyWithoutOverflow(num_elements, d.size()); 68 if (num_elements < 0) return false; 86 int64 num_elements = 1; local 103 num_elements = -1; 104 } else if (!kIsPartial || num_elements >= 0) { 105 num_elements [all...] |
/external/libcxx/test/support/ |
H A D | unique_ptr_test_helper.h | 39 newValue(int num_elements) { argument 40 assert(num_elements == 1); 47 newValue(int num_elements) { argument 49 assert(num_elements >= 1); 50 return new VT[num_elements];
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/external/tensorflow/tensorflow/compiler/xla/ |
H A D | sparse_index_array.h | 128 int64 num_elements = index_count(); local 129 CHECK_EQ(values.size(), num_elements); 131 sort_order.reserve(num_elements); 132 for (int64 i = 0; i < num_elements; ++i) { 143 for (int64 i = 0; i < num_elements; ++i) {
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/external/tensorflow/tensorflow/core/util/ |
H A D | tensor_slice_set.cc | 57 result_shape.num_elements()}; 87 int64 total_size = target_shape.num_elements(); 99 overlap_size += inter_shape.num_elements(); 144 int64 total_size = target_shape.num_elements(); 156 overlap_size += inter_shape.num_elements();
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H A D | example_proto_fast_parsing.cc | 97 bool GetNumElementsInBytesList(int* num_elements) { argument 104 *num_elements = 0; 110 ++*num_elements; 451 LimitedArraySlice(T* begin, size_t num_elements) argument 452 : current_(begin), end_(begin + num_elements) {} 569 const std::size_t num_elements = config.dense[d].elements_per_stride; local 570 const std::size_t offset = example_index * num_elements; 584 LimitedArraySlice<int64> slice(out_p, num_elements); 587 return shape_error(num_elements - slice.EndDistance(), "int64"); 593 LimitedArraySlice<float> slice(out_p, num_elements); 615 const std::size_t num_elements = config.dense[d].elements_per_stride; local 738 const std::size_t num_elements = in.shape().num_elements(); local 823 FillAndCopyVarLen( const int d, const size_t num_elements, const size_t num_elements_per_minibatch, const Config& config, const std::vector<std::vector<SparseBuffer>>& varlen_dense_buffers, Tensor* values) argument 1256 const std::size_t num_elements = config.dense[d].elements_per_stride; local 1294 size_t num_elements; local [all...] |
H A D | tensor_slice_writer.cc | 179 Status TensorSliceWriter::SaveData(const string* data, int64 num_elements, argument 182 (num_elements * MaxBytesPerElement(DT_INT32)); 183 for (int64 i = 0; i < num_elements; ++i) { 191 Fill(data, num_elements, ss->mutable_data());
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/external/tensorflow/tensorflow/contrib/lite/kernels/ |
H A D | embedding_lookup_sparse.cc | 116 void FinalizeAggregation(TfLiteCombinerType combiner, int num_elements, argument 120 if (combiner != kTfLiteCombinerTypeSum && num_elements > 0) { 185 int num_elements = 0; local 208 FinalizeAggregation(params->combiner, num_elements, current_total_weight, 213 num_elements = 0; 220 ++num_elements; 232 FinalizeAggregation(params->combiner, num_elements, current_total_weight,
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/external/tensorflow/tensorflow/compiler/tf2xla/kernels/ |
H A D | scatter_nd_op.cc | 96 buffer_shape.num_elements() > 0 || (indices_shape.num_elements() == 0 && 97 updates_shape.num_elements() == 0),
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H A D | transpose_op.cc | 47 OP_REQUIRES(ctx, dims == perm_tensor_shape.num_elements(), 51 perm_tensor_shape.num_elements())); 109 FastBoundsCheck(ctx->InputShape(0).num_elements(),
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H A D | select_op.cc | 60 OP_REQUIRES(ctx, then_shape.dim_size(0) == cond_shape.num_elements(), 64 cond_shape.num_elements()));
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/external/tensorflow/tensorflow/core/kernels/data/ |
H A D | map_and_batch_dataset_op.cc | 134 int64 num_elements; variable 135 WaitForBatch(batch_index, &num_elements).IgnoreError(); 169 int64 num_elements = 0; variable 170 Status status = WaitForBatch(current_batch_index_, &num_elements); 171 if (num_elements == 0) { 179 if (num_elements < dataset()->batch_size_) { 185 component_shape.set_dim(0, num_elements); 189 CopyPartialBatch(&component, output[i], num_elements)); 225 int64 num_elements) { 231 for (size_t i = 0; i < num_elements; 224 CopyPartialBatch(Tensor* output, const Tensor& value, int64 num_elements) argument [all...] |
/external/mesa3d/src/util/ |
H A D | slab.h | 53 unsigned num_elements; member in struct:slab_parent_pool
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H A D | slab.c | 114 parent->num_elements = num_items; 148 p_atomic_set(&page->u.num_remaining, pool->parent->num_elements); 150 for (unsigned i = 0; i < pool->parent->num_elements; ++i) { 178 pool->parent->num_elements * pool->parent->element_size); 183 for (unsigned i = 0; i < pool->parent->num_elements; ++i) {
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/external/tensorflow/tensorflow/contrib/boosted_trees/kernels/ |
H A D | split_handler_ops.cc | 159 int32 num_elements = partition_boundaries.size() - 1; variable 163 num_elements = 0; 169 TensorShape({num_elements}), 177 context, context->allocate_output("gains", TensorShape({num_elements}), 184 "split_infos", TensorShape({num_elements}), 188 for (int root_idx = 0; root_idx < num_elements; ++root_idx) { 334 int num_elements = non_empty_partitions.size(); variable 338 TensorShape({num_elements}), 346 context, context->allocate_output("gains", TensorShape({num_elements}), 353 "split_infos", TensorShape({num_elements}), 578 int num_elements = non_empty_partitions.size(); variable [all...] |
/external/tensorflow/tensorflow/core/kernels/ |
H A D | dequantize_op.cc | 82 const int64 num_elements = input.NumElements(); variable 83 for (int i = 0; i < num_elements; ++i) { 118 const int64 num_elements = input.NumElements(); variable 119 for (int i = 0; i < num_elements; ++i) {
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H A D | quantized_reshape_op_test.cc | 54 for (int i = 0; i < input.shape().num_elements(); ++i) {
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H A D | assign_op.h | 90 old_lhs.shape().num_elements() == rhs.shape().num_elements()) {
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H A D | quantized_mul_op.cc | 38 int32 full_input_offset, int64 num_elements, T scalar_input, 42 for (int i = 0; i < num_elements; ++i) { 53 int32 full_input_offset, int64 num_elements, 62 for (i = 0; i < (num_elements - 15); i += 16) { 106 for (; i < num_elements; ++i) { 115 const T* y_data, int32 offset_y, int64 num_elements, 117 for (int i = 0; i < num_elements; ++i) { 128 int64 num_elements, qint32* output) { 133 for (i = 0; i < (num_elements - 15); i += 16) { 182 for (; i < num_elements; 37 ScalarMultiply(OpKernelContext* context, const T* full_input, int32 full_input_offset, int64 num_elements, T scalar_input, int32 scalar_input_offset, Toutput* output) argument 51 ScalarMultiply(OpKernelContext* context, const quint8* full_input, int32 full_input_offset, int64 num_elements, quint8 scalar_input, int32 scalar_input_offset, qint32* output) argument 114 VectorMultiply(OpKernelContext* context, const T* x_data, int32 offset_x, const T* y_data, int32 offset_y, int64 num_elements, Toutput* output) argument 125 VectorMultiply(OpKernelContext* context, const quint8* x_data, int32 offset_x, const quint8* y_data, int32 offset_y, int64 num_elements, qint32* output) argument [all...] |
H A D | lookup_table_op.cc | 329 empty_key_input->template shaped<K, 2>({1, key_shape_.num_elements()}), 345 const int64 num_elements = key.dim_size(0); local 346 const int64 key_size = key_shape_.num_elements(); 347 const int64 value_size = value_shape_.num_elements(); 348 if (key.NumElements() != num_elements * key_size) { 349 TensorShape expected_shape({num_elements}); 355 const auto key_matrix = key.shaped<K, 2>({num_elements, key_size}); 356 auto value_matrix = value->shaped<V, 2>({num_elements, value_size}); 368 for (int64 i = 0; i < num_elements; ++i) { 408 if (key.NumElements() != key.dim_size(0) * key_shape_.num_elements()) { 505 const int64 num_elements = key.dim_size(0); local [all...] |
H A D | roll_op.cc | 38 void DoRoll(OpKernelContext* context, const int64 num_elements, argument 88 Shard(worker_threads->num_threads, worker_threads->workers, num_elements, 101 void DoRollWithMemcpy(OpKernelContext* context, const int64 num_elements, argument 215 const int total_work = 2 * num_elements / std::max<int>(dim_range[isd], 1); 249 const int64 num_elements = input.NumElements(); variable 294 DoRollWithMemcpy<T>(context, num_elements, num_dims, dim_size, 298 DoRoll<T>(context, num_elements, num_dims, dim_size, input_flat,
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H A D | parameterized_truncated_normal_op_gpu.cu.cc | 52 int64 samples_per_batch, int64 num_elements, 74 CUDA_1D_KERNEL_LOOP(offset, num_elements) { 196 int64 samples_per_batch, int64 num_elements, 203 const auto config = GetCudaLaunchConfig(num_elements, d); 207 gen, output.data(), num_batches, samples_per_batch, num_elements, 51 TruncatedNormalKernel(random::PhiloxRandom gen, T* data, int64 num_batches, int64 samples_per_batch, int64 num_elements, const T* means, bool single_mean, const T* stddevs, bool single_stddev, const T* minvals, bool single_minval, const T* maxvals, bool single_maxval, int64 kMaxIterations) argument
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/external/tensorflow/tensorflow/contrib/data/python/kernel_tests/ |
H A D | unique_dataset_op_test.py | 87 def build_dataset(num_elements, unique_elem_range): 88 return dataset_ops.Dataset.range(num_elements).map(
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/external/mesa3d/src/gallium/drivers/svga/ |
H A D | svga_state_vs.c | 262 unsigned num_elements; local 283 num_elements = 1; 298 dst[num_elements] = ureg_DECL_output(ureg, 301 src[num_elements] = ureg_DECL_vs_input(ureg, num_elements); 302 num_elements++; 309 for (i = 0; i < num_elements; i++) {
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/external/mesa3d/src/gallium/state_trackers/va/ |
H A D | picture_vc1.c | 34 assert(buf->size >= sizeof(VAPictureParameterBufferVC1) && buf->num_elements == 1); 72 assert(buf->size >= sizeof(VASliceParameterBufferVC1) && buf->num_elements == 1); 73 context->desc.vc1.slice_count += buf->num_elements;
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