1/* Copyright 2016 The TensorFlow Authors. All Rights Reserved.
2
3Licensed under the Apache License, Version 2.0 (the "License");
4you may not use this file except in compliance with the License.
5You may obtain a copy of the License at
6
7 http://www.apache.org/licenses/LICENSE-2.0
8
9Unless required by applicable law or agreed to in writing, software
10distributed under the License is distributed on an "AS IS" BASIS,
11WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
12See the License for the specific language governing permissions and
13limitations under the License.
14==============================================================================*/
15#ifndef TENSORFLOW_CORE_KERNELS_TILE_FUNCTOR_CPU_H_
16#define TENSORFLOW_CORE_KERNELS_TILE_FUNCTOR_CPU_H_
17
18#define EIGEN_USE_THREADS
19
20#include "tensorflow/core/kernels/ops_util.h"
21#include "tensorflow/core/kernels/tile_functor.h"
22
23namespace tensorflow {
24namespace internal {
25
26template <typename Device, typename T>
27void TileSimpleImpl(const Device& d, Tensor* out, const Tensor& in) {
28 const int ndims = in.dims();
29 const int64_t nelem = out->NumElements();
30 gtl::InlinedVector<int64_t, 8> in_strides =
31 ComputeStride<int64_t>(in.shape());
32 gtl::InlinedVector<int64_t, 8> out_strides =
33 ComputeStride<int64_t>(out->shape());
34 const T* p = in.flat<T>().data();
35 T* q = out->flat<T>().data();
36
37 for (int64_t o_idx = 0; o_idx < nelem; ++o_idx) {
38 int64_t i_idx = 0;
39 int64_t t = o_idx;
40 for (int i = 0; i < ndims; ++i) {
41 i_idx += t / out_strides[i] % in.dim_size(i) * in_strides[i];
42 t %= out_strides[i];
43 }
44 q[o_idx] = p[i_idx];
45 }
46}
47
48template <typename T>
49void TileSimple(const Eigen::ThreadPoolDevice& d, Tensor* out,
50 const Tensor& in) {
51 return TileSimpleImpl<Eigen::ThreadPoolDevice, T>(d, out, in);
52}
53
54} // namespace internal
55} // end namespace tensorflow
56
57#endif // TENSORFLOW_CORE_KERNELS_TILE_FUNCTOR_CPU_H_
58