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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 #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 
26 namespace tensorflow {
27 
28 typedef Eigen::ThreadPoolDevice CPUDevice;
29 typedef Eigen::GpuDevice GPUDevice;
30 
31 namespace functor {
32 
33 template <>
34 struct DenseUpdate<CPUDevice, string, ASSIGN> {
operator ()tensorflow::functor::DenseUpdate35   void operator()(const CPUDevice& d, typename TTypes<string>::Flat params,
36                   typename TTypes<string>::ConstFlat update) {
37     if (params.dimension(0) == 1) {
38       params.data()->resize(update.data()->size());
39       auto work = [&params, &update](int64 start, int64 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 start, int64 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 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(string));
61       } else {
62         estimated_string_size = sizeof(string);
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     PersistentTensor tmp;                                                     \
87     Tensor* tensor;                                                           \
88     AllocatorAttributes attr;                                                 \
89     attr.set_gpu_compatible(true);                                            \
90     attr.set_nic_compatible(true);                                            \
91     TF_RETURN_IF_ERROR(context->allocate_persistent(                          \
92         from.dtype(), from.shape(), &tmp, &tensor, attr));                    \
93     switch (from.dtype()) {                                                   \
94       TYPE_CALLER(TYPE_DENSE_COPY);                                           \
95       default:                                                                \
96         return errors::InvalidArgument(                                       \
97             "VariantCopyFn: Could not perform a deep copy of variant "        \
98             "element of type: ",                                              \
99             DataTypeString(from.dtype()),                                     \
100             " using device: ", context->device()->name());                    \
101     }                                                                         \
102     *to = *tensor;                                                            \
103     return Status::OK();                                                      \
104   }
105 
106 INSTANTIATE_GET_VARIANT_COPY_FN(CPUDevice, TF_CALL_ALL_TYPES, CPU_DENSE_COPY);
107 
108 #if GOOGLE_CUDA
109 #define GPU_DENSE_COPY(T)                                                \
110   case DataTypeToEnum<T>::value: {                                       \
111     functor::DenseUpdate<GPUDevice, T, ASSIGN> copy_functor_;            \
112     copy_functor_(context->eigen_device<GPUDevice>(), tensor->flat<T>(), \
113                   from.flat<T>());                                       \
114     break;                                                               \
115   }
116 #define TF_CALL_GPU_AND_ADDITIONAL_TYPES(T) \
117   TF_CALL_GPU_ALL_TYPES(T);                 \
118   TF_CALL_int32(T);                         \
119   TF_CALL_int64(T);
120 INSTANTIATE_GET_VARIANT_COPY_FN(GPUDevice, TF_CALL_GPU_AND_ADDITIONAL_TYPES,
121                                 GPU_DENSE_COPY);
122 #undef TF_CALL_GPU_AND_ADDITIONAL_TYPES
123 #undef GPU_DENSE_COPY
124 #endif  // GOOGLE_CUDA
125 
126 #undef CPU_DENSE_COPY
127 #undef INSTANTIATE_GET_VARIANT_COPY_FN
128 
129 }  // namespace tensorflow
130