experiments/STT-tensorflow
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Fix ODR violation by splitting a duplicate definition of a function template into separate overloads.

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PiperOrigin-RevId: 239293552
This commit is contained in:
A. Unique TensorFlower 2019-03-19 16:26:42 -07:00 committed by TensorFlower Gardener
parent 14fbe25f3e
commit 6ec89893ce
3 changed files with 36 additions and 10 deletions
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20
tensorflow/core/kernels/tile_functor.h
View File

@ -26,9 +26,21 @@ namespace tensorflow {
namespace internal {
// Device-specific naive implementation for tile.
template <typename Device, typename T>
void TileSimple(const Device& d, Tensor* out, const Tensor& in);
// Device-specific naive implementation for Tile.
template <typename T>
void TileSimple(const Eigen::ThreadPoolDevice& d, Tensor* out,
const Tensor& in);
#if GOOGLE_CUDA
template <typename T>
void TileSimple(const Eigen::GpuDevice& d, Tensor* out, const Tensor& in);
#endif // GOOGLE_CUDA
#ifdef TENSORFLOW_USE_SYCL
template <typename T>
void TileSimple(const Eigen::SyclDevice& d, Tensor* out, const Tensor& in);
#endif
template <typename Device, typename T, typename Tmultiples, int NDIM>
void TileUsingEigen(const Device& d, Tensor* out, const Tensor& in,
@ -99,7 +111,7 @@ struct Tile {
broadcast_array);
break;
default:
internal::TileSimple<Device, T>(d, out, in);
internal::TileSimple<T>(d, out, in);
break;
}
}

20
tensorflow/core/kernels/tile_functor_cpu.cc
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@ -21,11 +21,11 @@ limitations under the License.
#include "tensorflow/core/kernels/tile_functor.h"
namespace tensorflow {
namespace internal {
namespace {
template <typename Device, typename T>
void TileSimple(const Device& d, Tensor* out, const Tensor& in) {
void TileSimpleImpl(const Device& d, Tensor* out, const Tensor& in) {
const int ndims = in.dims();
const int64 nelem = out->NumElements();
gtl::InlinedVector<int64, 8> in_strides = ComputeStride<int64>(in.shape());
@ -44,7 +44,21 @@ void TileSimple(const Device& d, Tensor* out, const Tensor& in) {
}
}
} // end namespace internal
} // namespace
template <typename T>
void TileSimple(const Eigen::ThreadPoolDevice& d, Tensor* out,
const Tensor& in) {
return TileSimpleImpl<Eigen::ThreadPoolDevice, T>(d, out, in);
}
#ifdef TENSORFLOW_USE_SYCL
template <typename T>
void TileSimple(const Eigen::SyclDevice& d, Tensor* out, const Tensor& in) {
return TileSimpleImpl<Eigen::SyclDevice, T>(d, out, in);
}
#endif
} // namespace internal
namespace functor {

6
tensorflow/core/kernels/tile_functor_gpu.h
View File

@ -21,7 +21,6 @@ limitations under the License.
#define EIGEN_USE_GPU
#include "third_party/eigen3/unsupported/Eigen/CXX11/Tensor"
#include "tensorflow/core/framework/register_types.h"
#include "tensorflow/core/kernels/ops_util.h"
#include "tensorflow/core/kernels/tile_functor.h"
@ -47,8 +46,8 @@ __global__ void TileKernel(int nthreads, const T* src, const int32* buf,
}
}
template <typename Device, typename T>
void TileSimple(const Device& d, Tensor* out, const Tensor& in) {
template <typename T>
void TileSimple(const Eigen::GpuDevice& d, Tensor* out, const Tensor& in) {
// Ensures we can use 32-bit index.
const int64 in_nelem = in.NumElements();
CHECK_LT(in_nelem, kint32max) << "Tensor too large to transpose on GPU";
@ -85,6 +84,7 @@ void TileSimple(const Device& d, Tensor* out, const Tensor& in) {
} // end namespace internal
} // namespace tensorflow
#endif // GOOGLE_CUDA
#endif // TENSORFLOW_CORE_KERNELS_TILE_FUNCTOR_GPU_H_