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<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 = [¶ms, &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 = [¶ms, &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 Status::OK(); \ 103 } 104 105 INSTANTIATE_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); 119 INSTANTIATE_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