1/* Copyright 2015 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
16#define EIGEN_USE_THREADS
17
18#include "tensorflow/core/kernels/dense_update_functor.h"
19
20#include "tensorflow/core/framework/register_types.h"
21#include "tensorflow/core/framework/variant_op_registry.h"
22#include "tensorflow/core/lib/core/errors.h"
23#include "tensorflow/core/platform/mutex.h"
24#include "tensorflow/core/platform/types.h"
25
26namespace tensorflow {
27
28typedef Eigen::ThreadPoolDevice CPUDevice;
29typedef Eigen::GpuDevice GPUDevice;
30
31namespace functor {
32
33template <>
34struct DenseUpdate<CPUDevice, string, ASSIGN> {
35 void operator()(const CPUDevice& d, typename TTypes<tstring>::Flat params,
36 typename TTypes<tstring>::ConstFlat update) {
37 if (params.dimension(0) == 1) {
38 params.data()->resize(update.data()->size());
39 auto work = [&params, &update](int64_t start, int64_t end) {
40 memmove(const_cast<char*>(params.data()->data()) + start,
41 update.data()->data() + start, end - start);
42 };
43 d.parallelFor(update.data()->size(),
44 Eigen::TensorOpCost(.1, // chosen to force large chunks
45 .1, 0),
46 work);
47 } else {
48 auto work = [&params, &update](int64_t start, int64_t end) {
49 for (int i = start; i < end; ++i) {
50 params.data()[i].resize(update.data()[i].size());
51 memmove(const_cast<char*>(params.data()[i].data()),
52 update.data()[i].data(), update.data()[i].size());
53 }
54 };
55 int64_t estimated_string_size;
56 if (update.size() > 0) {
57 // first element of the tensor seems as good a guess as any of the sizes
58 // of the strings contained within...
59 estimated_string_size =
60 std::max(update.data()[0].size(), sizeof(tstring));
61 } else {
62 estimated_string_size = sizeof(tstring);
63 }
64 d.parallelFor(
65 params.dimension(0),
66 Eigen::TensorOpCost(estimated_string_size, estimated_string_size, 0),
67 work);
68 }
69 }
70};
71
72} // namespace functor
73
74#define CPU_DENSE_COPY(T) \
75 case DataTypeToEnum<T>::value: { \
76 functor::DenseUpdate<CPUDevice, T, ASSIGN> copy_functor_; \
77 copy_functor_(context->eigen_device<CPUDevice>(), tensor.flat<T>(), \
78 from.flat<T>()); \
79 break; \
80 }
81
82#define INSTANTIATE_GET_VARIANT_COPY_FN(DEVICE, TYPE_CALLER, TYPE_DENSE_COPY) \
83 template <> \
84 Status VariantCopyFn<DEVICE>(OpKernelContext * context, const Tensor& from, \
85 Tensor* to) { \
86 Tensor tensor; \
87 AllocatorAttributes attr; \
88 attr.set_gpu_compatible(true); \
89 attr.set_nic_compatible(true); \
90 TF_RETURN_IF_ERROR( \
91 context->allocate_temp(from.dtype(), from.shape(), &tensor, attr)); \
92 switch (from.dtype()) { \
93 TYPE_CALLER(TYPE_DENSE_COPY); \
94 default: \
95 return errors::InvalidArgument( \
96 "VariantCopyFn: Could not perform a deep copy of variant " \
97 "element of type: ", \
98 DataTypeString(from.dtype()), \
99 " using device: ", context->device()->name()); \
100 } \
101 *to = tensor; \
102 return OkStatus(); \
103 }
104
105INSTANTIATE_GET_VARIANT_COPY_FN(CPUDevice, TF_CALL_ALL_TYPES, CPU_DENSE_COPY);
106
107#if GOOGLE_CUDA || TENSORFLOW_USE_ROCM
108#define GPU_DENSE_COPY(T) \
109 case DataTypeToEnum<T>::value: { \
110 functor::DenseUpdate<GPUDevice, T, ASSIGN> copy_functor_; \
111 copy_functor_(context->eigen_device<GPUDevice>(), tensor.flat<T>(), \
112 from.flat<T>()); \
113 break; \
114 }
115#define TF_CALL_GPU_AND_ADDITIONAL_TYPES(T) \
116 TF_CALL_GPU_ALL_TYPES(T); \
117 TF_CALL_int32(T); \
118 TF_CALL_int64(T);
119INSTANTIATE_GET_VARIANT_COPY_FN(GPUDevice, TF_CALL_GPU_AND_ADDITIONAL_TYPES,
120 GPU_DENSE_COPY);
121#undef TF_CALL_GPU_AND_ADDITIONAL_TYPES
122#undef GPU_DENSE_COPY
123#endif // GOOGLE_CUDA || TENSORFLOW_USE_ROCM
124
125#undef CPU_DENSE_COPY
126#undef INSTANTIATE_GET_VARIANT_COPY_FN
127
128} // namespace tensorflow
129