| /external/tensorflow/tensorflow/core/kernels/ |
| scan_ops_test.cc | 25 static Graph* LargeOneDCumsum(int num_x, bool reverse = false) {
27 Tensor data(DataTypeToEnum<T>::value, TensorShape({num_x}));
36 static Graph* ColCumsum(int num_x, int num_y, bool reverse = false) {
38 Tensor data(DT_FLOAT, TensorShape({num_x, num_y}));
47 static Graph* RowCumsum(int num_x, int num_y, bool reverse = false) {
49 Tensor data(DT_FLOAT, TensorShape({num_x, num_y}));
70 static void LargeOneDimensional(int iters, const string& device, int num_x,
72 testing::ItemsProcessed(static_cast<int64>(iters) * num_x);
73 testing::BytesProcessed(static_cast<int64>(iters) * num_x * sizeof(T));
74 test::Benchmark(device, LargeOneDCumsum<T>(num_x, reverse)).Run(iters)
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| reduction_ops_test.cc | 27 static Graph* ToScalar(const string& reduce, int num_x, int num_y) {
29 Tensor data(DataTypeToEnum<T>::value, TensorShape({num_x, num_y}));
39 static Graph* ColReduce(const string& reduce, int num_x, int num_y) {
41 Tensor data(DT_FLOAT, TensorShape({num_x, num_y}));
50 static Graph* RowReduce(const string& reduce, int num_x, int num_y) {
52 Tensor data(DT_FLOAT, TensorShape({num_x, num_y}));
88 const string& reduce, int num_x, int num_y) {
89 testing::ItemsProcessed(static_cast<int64>(iters) * num_x * num_y);
90 testing::BytesProcessed(static_cast<int64>(iters) * num_x * num_y *
92 test::Benchmark(device, ToScalar<T>(reduce, num_x, num_y)).Run(iters)
[all...] |
| /external/tensorflow/tensorflow/stream_executor/ |
| fft.h | 94 virtual std::unique_ptr<Plan> Create1dPlan(Stream *stream, uint64 num_x,
98 virtual std::unique_ptr<Plan> Create2dPlan(Stream *stream, uint64 num_x,
103 virtual std::unique_ptr<Plan> Create3dPlan(Stream *stream, uint64 num_x,
109 Stream *stream, uint64 num_x, Type type, bool in_place_fft,
114 Stream *stream, uint64 num_x, uint64 num_y, Type type, bool in_place_fft,
119 Stream *stream, uint64 num_x, uint64 num_y, uint64 num_z, Type type,
214 std::unique_ptr<fft::Plan> Create1dPlan(Stream *stream, uint64 num_x, \
217 std::unique_ptr<fft::Plan> Create2dPlan(Stream *stream, uint64 num_x, \
221 Stream *stream, uint64 num_x, uint64 num_y, uint64 num_z, \
224 Stream *stream, uint64 num_x, fft::Type type, bool in_place_fft,
[all...] |
| /external/tensorflow/tensorflow/stream_executor/cuda/ |
| cuda_fft.cc | 291 std::unique_ptr<fft::Plan> CUDAFft::Create1dPlan(Stream *stream, uint64 num_x,
295 uint64 elem_count[1] = {num_x};
301 LOG(ERROR) << "Plan Parameters: num_x: " << num_x;
309 Stream *stream, uint64 num_x, fft::Type type, bool in_place_fft,
312 uint64 elem_count[1] = {num_x};
316 LOG(ERROR) << "Plan Parameters: num_x: " << num_x;
324 std::unique_ptr<fft::Plan> CUDAFft::Create2dPlan(Stream *stream, uint64 num_x,
328 uint64 elem_count[2] = {num_x, num_y}
[all...] |
| /external/tensorflow/tensorflow/stream_executor/rocm/ |
| rocm_fft.cc | 372 std::unique_ptr<fft::Plan> ROCMFft::Create1dPlan(Stream *stream, uint64 num_x,
376 uint64 elem_count[1] = {num_x};
389 Stream *stream, uint64 num_x, fft::Type type, bool in_place_fft,
392 uint64 elem_count[1] = {num_x};
403 std::unique_ptr<fft::Plan> ROCMFft::Create2dPlan(Stream *stream, uint64 num_x,
407 uint64 elem_count[2] = {num_x, num_y};
418 Stream *stream, uint64 num_x, uint64 num_y, fft::Type type,
421 uint64 elem_count[2] = {num_x, num_y};
432 std::unique_ptr<fft::Plan> ROCMFft::Create3dPlan(Stream *stream, uint64 num_x,
437 uint64 elem_count[3] = {num_x, num_y, num_z}
[all...] |
| /external/tensorflow/tensorflow/core/graph/ |
| gradients.cc | 102 const int num_x = n->num_inputs(); local
110 // The gradient node should have num_x + num_y inputs.
111 std::vector<NodeOut> n_inputs(num_x);
125 CHECK_EQ(ndef.input_size(), num_x + num_y);
344 // "n" has num_x inputs and num_y outputs.
345 const int num_x = n->num_inputs(); local
372 // Adds a gradient node with num_x + num_y inputs and num_x
381 graph_->AddEdge(dy[i].node, dy[i].index, grad, num_x + i);
|
| /external/tensorflow/tensorflow/core/common_runtime/ |
| function.cc | 2044 const size_t num_x = fbody_->arg_nodes.size(); local
[all...] |
