zero_copy_tensor.cc 6.9 KB
Newer Older
X
xiexionghang 已提交
1 2 3 4 5 6 7 8 9 10 11 12 13 14 15 16 17 18 19 20 21 22 23 24 25 26 27 28 29 30 31 32 33 34 35 36 37 38 39 40 41 42 43 44 45 46 47 48 49 50 51 52 53 54 55 56 57 58 59 60 61 62 63 64 65 66 67 68 69 70 71 72 73 74 75 76 77 78 79 80 81 82 83 84 85 86 87 88 89 90 91 92 93 94 95 96 97 98 99 100 101 102 103 104 105 106 107 108 109 110 111 112 113 114 115 116 117 118 119 120 121 122 123 124 125 126 127 128 129 130 131 132 133 134 135 136 137 138 139 140 141 142 143 144 145 146 147 148 149 150 151 152 153 154 155 156 157 158 159 160 161 162 163 164 165 166 167 168 169 170 171 172 173 174 175 176 177 178 179 180 181 182 183 184 185 186 187 188 189 190 191 192 193 194 195 196
// Copyright (c) 2018 PaddlePaddle Authors. All Rights Reserved.
//
// Licensed under the Apache License, Version 2.0 (the "License");
// you may not use this file except in compliance with the License.
// You may obtain a copy of the License at
//
//     http://www.apache.org/licenses/LICENSE-2.0
//
// Unless required by applicable law or agreed to in writing, software
// distributed under the License is distributed on an "AS IS" BASIS,
// WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
// See the License for the specific language governing permissions and
// limitations under the License.

#include "paddle/fluid/framework/lod_tensor.h"
#include "paddle/fluid/framework/scope.h"
#include "paddle/fluid/inference/api/paddle_inference_api.h"
#include "paddle/fluid/memory/memcpy.h"
#include "paddle/fluid/platform/enforce.h"

namespace paddle {

void ZeroCopyTensor::Reshape(const std::vector<int> &shape) {
  PADDLE_ENFORCE(!name_.empty(),
                 "Need to SetName first, so that the corresponding tensor can "
                 "be retrieved.");
  PADDLE_ENFORCE(input_or_output_,
                 "Can't reshape the output tensor, it is readonly");
  PADDLE_ENFORCE(scope_);
  auto *scope = static_cast<framework::Scope *>(scope_);
  auto *var = scope->FindVar(name_);
  PADDLE_ENFORCE(var, "No tensor called [%s] in the runtime scope", name_);
  auto *tensor = var->GetMutable<framework::LoDTensor>();
  tensor->Resize(framework::make_ddim(shape));
}

#define EAGER_GET_TENSOR    \
  if (!tensor_) {           \
    tensor_ = FindTensor(); \
  }                         \
  auto *tensor = static_cast<framework::LoDTensor *>(tensor_);

template <typename T>
T *ZeroCopyTensor::mutable_data(PaddlePlace place) {
  EAGER_GET_TENSOR;
  switch (static_cast<int>(place)) {
    case static_cast<int>(PaddlePlace::kCPU): {
      return tensor->mutable_data<T>(platform::CPUPlace());
    }
    case static_cast<int>(PaddlePlace::kGPU): {
      return tensor->mutable_data<T>(platform::CUDAPlace());
    }
    default:
      PADDLE_THROW("Unsupported place: %d", static_cast<int>(place));
      break;
  }
  return nullptr;
}

template <typename T>
T *ZeroCopyTensor::data(PaddlePlace *place, int *size) const {
  EAGER_GET_TENSOR;
  auto *res = tensor->data<T>();

  if (platform::is_cpu_place(tensor->place())) {
    *place = PaddlePlace::kCPU;
  } else if (platform::is_gpu_place(tensor->place())) {
    *place = PaddlePlace::kGPU;
  } else {
    *place = PaddlePlace::kUNK;
  }

  *size = tensor->numel();
  return res;
}

PaddleDType ZeroCopyTensor::type() const {
  EAGER_GET_TENSOR;
  auto type = tensor->type();
  if (type == framework::proto::VarType::FP32) {
    return PaddleDType::FLOAT32;
  } else if (type == framework::proto::VarType::INT64) {
    return PaddleDType::INT64;
  } else if (type == framework::proto::VarType::INT32) {
    return PaddleDType::INT32;
  } else {
    LOG(ERROR) << "unknown type, only support float32 and int64 now.";
  }
  return PaddleDType::FLOAT32;
}

template <typename T>
void ZeroCopyTensor::copy_from_cpu(const T *data) {
  EAGER_GET_TENSOR;
  PADDLE_ENFORCE_GE(
      tensor->numel(), 0,
      "You should call ZeroCopyTensor::Reshape(const std::vector<int> &shape)"
      "function before copy data from cpu.");
  size_t ele_size = tensor->numel() * sizeof(T);

  if (place_ == PaddlePlace::kCPU) {
    auto *t_data = tensor->mutable_data<T>(platform::CPUPlace());
    std::memcpy(static_cast<void *>(t_data), data, ele_size);
  } else {
#ifdef PADDLE_WITH_CUDA
    platform::DeviceContextPool &pool = platform::DeviceContextPool::Instance();
    platform::CUDAPlace gpu_place(device_);
    auto *t_data = tensor->mutable_data<T>(gpu_place);
    auto *dev_ctx =
        static_cast<const platform::CUDADeviceContext *>(pool.Get(gpu_place));

    memory::Copy(gpu_place, static_cast<void *>(t_data), platform::CPUPlace(),
                 data, ele_size, dev_ctx->stream());
#else
    PADDLE_THROW("Not compile with CUDA, should not reach here.");
#endif
  }
}

template <typename T>
void ZeroCopyTensor::copy_to_cpu(T *data) {
  EAGER_GET_TENSOR;
  auto ele_num = tensor->numel();
  auto *t_data = tensor->data<T>();
  auto t_place = tensor->place();

  if (platform::is_cpu_place(t_place)) {
    std::memcpy(static_cast<void *>(data), t_data, ele_num * sizeof(T));
  } else {
#ifdef PADDLE_WITH_CUDA
    platform::DeviceContextPool &pool = platform::DeviceContextPool::Instance();
    auto gpu_place = boost::get<platform::CUDAPlace>(t_place);
    auto *dev_ctx =
        static_cast<const platform::CUDADeviceContext *>(pool.Get(gpu_place));
    memory::Copy(platform::CPUPlace(), static_cast<void *>(data), gpu_place,
                 t_data, ele_num * sizeof(T), dev_ctx->stream());
    cudaDeviceSynchronize();
#else
    PADDLE_THROW("Not compile with CUDA, should not reach here.");
#endif
  }
}
template void ZeroCopyTensor::copy_from_cpu<float>(const float *data);
template void ZeroCopyTensor::copy_from_cpu<int64_t>(const int64_t *data);
template void ZeroCopyTensor::copy_from_cpu<int32_t>(const int32_t *data);
template void ZeroCopyTensor::copy_to_cpu<float>(float *data);
template void ZeroCopyTensor::copy_to_cpu<int64_t>(int64_t *data);
template void ZeroCopyTensor::copy_to_cpu<int32_t>(int32_t *data);

template float *ZeroCopyTensor::data<float>(PaddlePlace *place,
                                            int *size) const;
template int64_t *ZeroCopyTensor::data<int64_t>(PaddlePlace *place,
                                                int *size) const;
template int32_t *ZeroCopyTensor::data<int32_t>(PaddlePlace *place,
                                                int *size) const;
template float *ZeroCopyTensor::mutable_data<float>(PaddlePlace place);
template int64_t *ZeroCopyTensor::mutable_data<int64_t>(PaddlePlace place);
template int32_t *ZeroCopyTensor::mutable_data<int32_t>(PaddlePlace place);

void *ZeroCopyTensor::FindTensor() const {
  PADDLE_ENFORCE(!name_.empty(),
                 "Need to SetName first, so that the corresponding tensor can "
                 "be retrieved.");
  PADDLE_ENFORCE(scope_);
  auto *scope = static_cast<framework::Scope *>(scope_);
  auto *var = scope->FindVar(name_);
  PADDLE_ENFORCE(var, "No tensor called [%s] in the runtime scope", name_);
  auto *tensor = var->GetMutable<framework::LoDTensor>();
  return tensor;
}

std::vector<int> ZeroCopyTensor::shape() const {
  EAGER_GET_TENSOR;
  PADDLE_ENFORCE(tensor_, "not found tensor called %s in the scope", name_);
  return framework::vectorize2int(tensor->dims());
}

void ZeroCopyTensor::SetLoD(const std::vector<std::vector<size_t>> &x) {
  EAGER_GET_TENSOR;
  framework::LoD lod;
  for (auto &level : x) {
    lod.emplace_back(level);
  }
  tensor->set_lod(lod);
}

std::vector<std::vector<size_t>> ZeroCopyTensor::lod() const {
  EAGER_GET_TENSOR;
  std::vector<std::vector<size_t>> res;
  for (auto &level : tensor->lod()) {
    res.emplace_back(level);
  }
  return res;
}

}  // namespace paddle