1 /* Copyright 2015 The TensorFlow Authors. All Rights Reserved.
2
3 Licensed under the Apache License, Version 2.0 (the "License");
4 you may not use this file except in compliance with the License.
5 You may obtain a copy of the License at
6
7 http://www.apache.org/licenses/LICENSE-2.0
8
9 Unless required by applicable law or agreed to in writing, software
10 distributed under the License is distributed on an "AS IS" BASIS,
11 WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
12 See the License for the specific language governing permissions and
13 limitations under the License.
14 ==============================================================================*/
15
16 // See docs in ../ops/array_ops.cc.
17
18 #include <vector>
19
20 #include "third_party/eigen3/unsupported/Eigen/CXX11/Tensor"
21 #include "tensorflow/core/framework/op_kernel.h"
22 #include "tensorflow/core/framework/register_types.h"
23 #include "tensorflow/core/framework/tensor.h"
24 #include "tensorflow/core/framework/tensor_types.h"
25 #include "tensorflow/core/framework/types.h"
26
27 #if GOOGLE_CUDA || TENSORFLOW_USE_ROCM
28
29 #include "tensorflow/core/kernels/concat_lib_gpu.h"
30 #include "tensorflow/core/kernels/gpu_device_array.h"
31
32 namespace tensorflow {
33 namespace {
34
35 template <typename T, typename IntType>
ConcatGPUCall(OpKernelContext * c,const std::vector<std::unique_ptr<typename TTypes<T,2>::ConstMatrix>> & inputs_flat,typename TTypes<T,2>::Tensor * output_flat)36 void ConcatGPUCall(
37 OpKernelContext* c,
38 const std::vector<std::unique_ptr<typename TTypes<T, 2>::ConstMatrix>>&
39 inputs_flat,
40 typename TTypes<T, 2>::Tensor* output_flat) {
41 GpuDeviceArrayOnHost<const T*> input_ptrs(c, inputs_flat.size());
42 OP_REQUIRES_OK(c, input_ptrs.Init());
43 for (int i = 0; i < inputs_flat.size(); ++i) {
44 input_ptrs.Set(i, inputs_flat[i]->data());
45 }
46 OP_REQUIRES_OK(c, input_ptrs.Finalize());
47
48 GpuDeviceArrayOnHost<IntType> output_scan(c, inputs_flat.size() + 1);
49 OP_REQUIRES_OK(c, output_scan.Init());
50 IntType scan = 0;
51 output_scan.Set(0, scan);
52 bool one_size_input = true;
53 for (int i = 0; i < inputs_flat.size(); ++i) {
54 if (one_size_input && i < inputs_flat.size() - 1 &&
55 inputs_flat[i]->dimension(1) != inputs_flat[i + 1]->dimension(1)) {
56 one_size_input = false;
57 }
58 scan += inputs_flat[i]->dimension(1);
59 output_scan.Set(i + 1, scan);
60 }
61 if (!one_size_input) OP_REQUIRES_OK(c, output_scan.Finalize());
62
63 ConcatGPUImpl<T, IntType>(c->eigen_gpu_device(), input_ptrs.data(),
64 output_scan.data(), one_size_input,
65 inputs_flat[0]->dimension(1), output_flat);
66 }
67
68 } // end namespace
69
70 template <typename T>
ConcatGPU(OpKernelContext * c,const std::vector<std::unique_ptr<typename TTypes<T,2>::ConstMatrix>> & inputs_flat,Tensor * output,typename TTypes<T,2>::Tensor * output_flat)71 void ConcatGPU(
72 OpKernelContext* c,
73 const std::vector<std::unique_ptr<typename TTypes<T, 2>::ConstMatrix>>&
74 inputs_flat,
75 Tensor* output, typename TTypes<T, 2>::Tensor* output_flat) {
76 if (inputs_flat.size() < 16) {
77 if (output->NumElements() < std::numeric_limits<int32>::max()) {
78 ConcatGPUSlice<T, int32>(c->eigen_gpu_device(), inputs_flat, output_flat);
79 } else {
80 ConcatGPUSlice<T, int64>(c->eigen_gpu_device(), inputs_flat, output_flat);
81 }
82 } else {
83 // Switching indexing to int64 might cause performance issues.
84 // Hence, we keep int32 indexing in the GPU kernel unless we need to
85 // switch to int64.
86 if (output->NumElements() < std::numeric_limits<int32>::max()) {
87 ConcatGPUCall<T, int32>(c, inputs_flat, output_flat);
88 } else {
89 ConcatGPUCall<T, int64>(c, inputs_flat, output_flat);
90 }
91 }
92 }
93
94 #define REGISTER(T) \
95 template void ConcatGPU<T>( \
96 OpKernelContext * c, \
97 const std::vector<std::unique_ptr<typename TTypes<T, 2>::ConstMatrix>>& \
98 inputs_flat, \
99 Tensor* output, typename TTypes<T, 2>::Tensor* output_flat);
100
101 TF_CALL_INTEGRAL_TYPES(REGISTER); // int32 Needed for TensorLists.
102 TF_CALL_bfloat16(REGISTER);
103 TF_CALL_GPU_ALL_TYPES(REGISTER);
104
105 #undef REGISTER
106
107 } // namespace tensorflow
108
109 #endif // GOOGLE_CUDA || TENSORFLOW_USE_ROCM
110