| /external/tensorflow/tensorflow/compiler/jit/kernels/ |
| xla_launch_op.cc | 66 // compute stream to enforce a happens-before relationship between a memory
216 void XlaLocalLaunchOp::Compute(OpKernelContext* ctx) {
217 VLOG(1) << "XlaLocalLaunchOp::Compute "
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| /external/tensorflow/tensorflow/compiler/tf2xla/ |
| xla_op_kernel.cc | 482 void XlaOpKernel::Compute(OpKernelContext* context) {
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| /external/tensorflow/tensorflow/core/framework/ |
| dataset.cc | 241 void DatasetOpKernel::Compute(OpKernelContext* ctx) {
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| resource_mgr.h | 315 void Compute(OpKernelContext* ctx) override;
337 void Compute(OpKernelContext* ctx) override;
491 void IsResourceInitialized<T>::Compute(OpKernelContext* ctx) {
514 void ResourceHandleOp<T>::Compute(OpKernelContext* ctx) {
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| op_kernel.cc | 162 void AsyncOpKernel::Compute(OpKernelContext* context) {
[all...] |
| /external/tensorflow/tensorflow/core/graph/ |
| gradients.cc | 131 Status Compute();
305 Status SymbolicGradientBuilder::Compute() {
378 return builder.Compute();
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| /external/tensorflow/tensorflow/core/kernels/ |
| sparse_tensor_dense_matmul_op.cc | 41 void Compute(OpKernelContext* ctx) override {
139 ADJ_B>::Compute(ctx->eigen_device<Device>(), out->matrix<T>(), \
184 ADJ_B>::Compute(const GPUDevice& d, typename TTypes<T>::Matrix out, \
247 static Status Compute(const CPUDevice& d, typename TTypes<T>::Matrix out,
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| where_op_gpu.cu.h | 135 EIGEN_ALWAYS_INLINE static Status Compute(
257 EIGEN_ALWAYS_INLINE static Status Compute(
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| example_parsing_ops.cc | 43 void Compute(OpKernelContext* ctx) override {
177 void Compute(OpKernelContext* ctx) override {
274 void Compute(OpKernelContext* ctx) override {
673 void Compute(OpKernelContext* ctx) {
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| matmul_op.cc | 163 static void Compute(
200 void LaunchBlasGemv<Eigen::half>::Compute(
311 // We want the output to be in row-major, so we can compute
348 LaunchBlasGemv<T>::Compute(ctx, stream, !transpose_a,
390 // 2) compute type does not support autotune;
404 // This is a matrix*vector multiply so use GEMV to compute A * b.
409 LaunchBlasGemv<T>::Compute(ctx, stream, !transpose_a,
456 void Compute(OpKernelContext* ctx) override {
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| resize_bicubic_op.cc | 103 // Compute the 1D interpolation for a given X index using the y_weights
104 static float Compute(float values_[4], const float xw_0, const float xw_1,
110 // In order to compute a single output value, we look at a 4x4 patch in the
114 // This class helps compute the number of values to copy from the previous
325 Compute(cached_value_0, x_wai.weight_0, x_wai.weight_1,
328 Compute(cached_value_1, x_wai.weight_0, x_wai.weight_1,
331 Compute(cached_value_2, x_wai.weight_0, x_wai.weight_1,
389 Compute(&cached_value[4 * c], x_wai.weight_0, x_wai.weight_1,
476 void Compute(OpKernelContext* context) override {
501 void Compute(OpKernelContext* context) override
[all...] |
| mkl_concat_op.cc | 61 // Although, we modify Compute for this call to accept one extra param,
62 // we need to have empty Compute because Compute is pure virtual function.
63 void Compute(OpKernelContext* c) {}
67 void Compute(OpKernelContext* c, const std::vector<Tensor>& values) {
81 // Instead of accessing values from context, we use input to Compute.
154 void Compute(OpKernelContext* c, const std::vector<Tensor>& values,
169 // Instead of accessing values from context, we use input to Compute.
252 void Compute(OpKernelContext* context) override {
510 eigen_concat_op_.Compute(context, converted_values)
[all...] |
| set_kernels.cc | 248 void Compute(OpKernelContext* ctx) override;
255 void SetSizeOp<T>::Compute(OpKernelContext* ctx) {
345 void Compute(OpKernelContext* ctx) override;
683 void SetOperationOp<T>::Compute(OpKernelContext* ctx) {
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| batch_kernels.cc | 606 Status Compute(OpKernelContext* context, AsyncOpKernel::DoneCallback done) {
801 auto status = ubr->Compute(c, done);
858 Status Compute(OpKernelContext* context,
[all...] |
| deep_conv2d.cc | 213 // Compute transform of 'num_filters' by 'transform_matrix'.
263 // Calls ComputeFilterRangeTransform to compute filter transform of data
295 // Compute number of filter shards.
304 // Compute strides to be used for input and output IO.
357 // Compute filter transform of data in 'filter_buf' by 'transform_matrix'.
602 void Compute() {
761 // Compute output transform.
[all...] |
| mkl_relu_op.cc | 70 void Compute(OpKernelContext* context) override {
190 void Compute(OpKernelContext* context) override;
266 void MklReluGradOp<Device, T>::Compute(OpKernelContext* context) {
382 void Compute(OpKernelContext* context) override {
472 void Compute(OpKernelContext* context) {
[all...] |
| sparse_matmul_op.cc | 81 // TODO(agarwal): compute these sizes based on cache sizes.
620 // Pre-compute pointers for output matrix.
634 // Pre-compute pointers for right matrix
786 static inline void Compute(TensorInfoCache* cache,
835 // Heuristics to compute various block sizes.
[all...] |
| /build/make/tools/releasetools/ |
| ota_from_target_files | 54 be used to compute fingerprint, while the rest will be used to assert
134 Specifies the threshold that will be used to compute the maximum
[all...] |
| ota_from_target_files.py | 54 be used to compute fingerprint, while the rest will be used to assert
134 Specifies the threshold that will be used to compute the maximum
[all...] |
| /prebuilts/ndk/r16/sources/third_party/shaderc/libshaderc_util/include/libshaderc_util/ |
| compiler.h | 158 Compute,
160 enum { kNumStages = int(Stage::Compute) + 1 };
166 Stage::Fragment, Stage::Compute}};
470 return Compiler::Stage::Compute;
475 return Compiler::Stage::Compute;
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| /external/toolchain-utils/cros_utils/ |
| tabulator.py | 251 def Compute(self, cell, values, baseline_values):
252 """Compute the result given a list of values and baseline values.
295 def Compute(self, cell, values, baseline_values):
308 def Compute(self, cell, values, baseline_values):
328 f.Compute(tmp_cell)
557 def Compute(self, cell):
815 column.result.Compute(cell, values, baseline)
816 column.fmt.Compute(cell)
821 column.result.Compute(cell, values, baseline)
822 column.fmt.Compute(cell
[all...] |
| /external/deqp/external/openglcts/modules/glesext/texture_cube_map_array/ |
| esextcTextureCubeMapArraySampling.hpp | 61 * * a compute shader.
191 Compute = 0,
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| /external/tensorflow/tensorflow/core/common_runtime/ |
| function.cc | [all...] |
| /external/tensorflow/tensorflow/core/common_runtime/gpu/ |
| gpu_device.cc | 76 // during OpKernel::Compute(). The recommended way of allocating such
207 if (!group->compute) {
208 group->compute = new gpu::Stream(executor);
209 group->compute->Init();
211 << "] = " << group->compute;
312 i, streams_.back()->compute, streams_.back()->host_to_device,
316 gpu_device_info_->stream = streams_[0]->compute;
327 // * global: GPU uses threads shared with CPU in the main compute
337 // Default to two threads. One for device compute and another for memory
407 void BaseGPUDevice::Compute(OpKernel* op_kernel, OpKernelContext* context)
[all...] |
| /external/googletest/googlemock/test/ |
| gmock-matchers_test.cc | [all...] |
