ScaleSubRegionOp.cpp 5.2 KB
Newer Older
1
/* Copyright (c) 2016 PaddlePaddle Authors. All Rights Reserved.
Y
yangyaming 已提交
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

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 "ScaleSubRegionOp.h"
#include "paddle/function/TensorShape.h"

namespace paddle {

template <>
void ScaleSubRegion<DEVICE_TYPE_CPU>(real* outputs,
                                     const real* inputs,
                                     const real* indices,
                                     const TensorShape shape,
                                     const FuncConfig& conf) {
  real value = conf.get<real>("value");

  int number = shape[0];
  int channel = shape[1];
  int height = shape[2];
  int width = shape[3];

  memcpy(outputs, inputs, number * channel * height * width * sizeof(real));

  for (int n = 0; n < number; ++n) {
    // indices start from 1
    int offset = n * 6;
    for (int c = indices[offset] - 1; c < indices[offset + 1]; ++c) {
      for (int h = indices[offset + 2] - 1; h < indices[offset + 3]; ++h) {
        for (int w = indices[offset + 4] - 1; w < indices[offset + 5]; ++w) {
          int idx = ((n * channel + c) * height + h) * width + w;
          outputs[idx] *= value;
        }
      }
    }
  }
}

template <>
void ScaleSubRegionGrad<DEVICE_TYPE_CPU>(const real* inGrad,
                                         real* outGrad,
                                         const real* indices,
                                         const TensorShape shape,
                                         const FuncConfig& conf) {
  real value = conf.get<real>("value");

  int number = shape[0];
  int channel = shape[1];
  int height = shape[2];
  int width = shape[3];

  for (int n = 0; n < number; ++n) {
    for (int c = 0; c < channel; ++c) {
      for (int h = 0; h < height; ++h) {
        for (int w = 0; w < width; ++w) {
          int idx = ((n * channel + c) * height + h) * width + w;
          int offset = n * 6;
          if (c >= (indices[offset] - 1) && c <= (indices[offset + 1] - 1) &&
              h >= (indices[offset + 2] - 1) &&
              h <= (indices[offset + 3] - 1) &&
              w >= (indices[offset + 4] - 1) &&
              w <= (indices[offset + 5] - 1)) {
            outGrad[idx] += inGrad[idx] * value;
          } else {
            outGrad[idx] += inGrad[idx];
          }
        }
      }
    }
  }
}

/**
 * \brief For each instance, ScaleSubRegion can be used to multiply a value to
 *        a specified sub continuous region. By providing start index and end
 *        index for C/H/W, you can specify the location and shape of the region.
 *
 * Argument in this Function:
 * \param inputs    A 4-D tensor with shape [N, C, H, W], only one input.
 * \param indices   A 2-D tensor with shape [N, 6], indicates the sub region.
 * \param outputs   A 4-D tensor with same shape as inputs, output value.
 */
template <DeviceType Device>
class ScaleSubRegionFunc : public FunctionBase {
W
Wu Yi 已提交
95
 public:
Y
yangyaming 已提交
96 97 98 99 100 101 102 103 104 105 106 107 108 109 110 111
  void init(const FuncConfig& config) override { conf_ = config; }

  void calc(const BufferArgs& inputs, const BufferArgs& outputs) override {
    CHECK_EQ(2UL, inputs.size());
    CHECK_EQ(1UL, outputs.size());
    CHECK_EQ(outputs[0].getArgType(), ASSIGN_TO);

    TensorShape shape = inputs[0].shape();

    ScaleSubRegion<Device>(outputs[0].data<real>(),
                           inputs[0].data<real>(),
                           inputs[1].data<real>(),
                           shape,
                           conf_);
  }

W
Wu Yi 已提交
112
 private:
Y
yangyaming 已提交
113 114 115 116 117 118 119 120 121 122 123 124 125 126
  FuncConfig conf_;
};

/**
 * \brief The backward propagation of ScaleSubRegion Function.
 *
 * Argument in this Function:
 * \param inputs  A 4-D tensor with shape [N, C, H, W], output gradient.
 * \param indices A 2-D tensor with shape [N, 6], indicates the sub region.
 * \param outputs A 4-D tensor with shape [N, C, H, W], gradient of input value.
 */

template <DeviceType Device>
class ScaleSubRegionGradFunc : public FunctionBase {
W
Wu Yi 已提交
127
 public:
Y
yangyaming 已提交
128 129 130 131 132 133 134 135 136 137 138 139 140 141 142 143
  void init(const FuncConfig& config) override { conf_ = config; }

  void calc(const BufferArgs& inputs, const BufferArgs& outputs) override {
    CHECK_EQ(2UL, inputs.size());
    CHECK_EQ(1UL, outputs.size());
    CHECK_EQ(outputs[0].getArgType(), ADD_TO);

    TensorShape shape = inputs[0].shape();

    ScaleSubRegionGrad<Device>(inputs[0].data<real>(),
                               outputs[0].data<real>(),
                               inputs[1].data<real>(),
                               shape,
                               conf_);
  }

W
Wu Yi 已提交
144
 private:
Y
yangyaming 已提交
145 146 147 148 149 150 151 152 153 154 155
  FuncConfig conf_;
};

REGISTER_TYPED_FUNC(ScaleSubRegion, CPU, ScaleSubRegionFunc);
REGISTER_TYPED_FUNC(ScaleSubRegionGrad, CPU, ScaleSubRegionGradFunc);
#ifdef PADDLE_WITH_CUDA
REGISTER_TYPED_FUNC(ScaleSubRegion, GPU, ScaleSubRegionFunc);
REGISTER_TYPED_FUNC(ScaleSubRegionGrad, GPU, ScaleSubRegionGradFunc);
#endif

}  // namespace paddle