Merge pull request #4154 from luotao1/avg_pool

refine avg-pooling, which is exclusive. refine related code.

Author: luotao1

paddle/cuda/include/hl_cuda_cudnn.h

@@ -22,10 +22,10 @@ limitations under the License. */
  */
 typedef enum {
  HL_POOLING_MAX = 0,
- // average includes padded values
- HL_POOLING_AVERAGE = 1,
  // average does not include padded values
- HL_POOLING_AVERAGE_EXCLUDE_PADDING = 2,
+ HL_POOLING_AVERAGE = 1,
+ // average includes padded values
+ HL_POOLING_AVERAGE_INCLUDE_PADDING = 2,
  HL_POOLING_END
 } hl_pooling_mode_t;
 

paddle/cuda/src/hl_cuda_cnn.cu

@@ -211,13 +211,11 @@ __global__ void KeAvgPoolForward(const int nthreads,
 
  int hstart = ph * strideH - padH;
  int wstart = pw * strideW - padW;
- int hend = min(hstart + sizeY, height + padH);
- int wend = min(wstart + sizeX, width + padW);
- int pool_size = (hend - hstart) * (wend - wstart);
+ int hend = min(hstart + sizeY, height);
+ int wend = min(wstart + sizeX, width);
  hstart = max(hstart, 0);
  wstart = max(wstart, 0);
- hend = min(hend, height);
- wend = min(wend, width);
+ int pool_size = (hend - hstart) * (wend - wstart);
 
  real aveval = 0;
  inputData += (frameNum * channels + c) * height * width;
@@ -299,12 +297,14 @@ __global__ void KeAvgPoolBackward(const int nthreads,
  outGrad += (frameNum * outStride + offsetC * pooledH * pooledW);
 
  for (int ph = phstart; ph < phend; ++ph) {
+ int hstart = ph * strideH - padH;
+ int hend = min(hstart + sizeY, height);
+ hstart = max(hstart, 0);
  for (int pw = pwstart; pw < pwend; ++pw) {
  // figure out the pooling size
- int hstart = ph * strideH - padH;
  int wstart = pw * strideW - padW;
- int hend = min(hstart + sizeY, height + padH);
- int wend = min(wstart + sizeX, width + padW);
+ int wend = min(wstart + sizeX, width);
+ wstart = max(wstart, 0);
  int poolsize = (hend - hstart) * (wend - wstart);
  gradient += outGrad[ph * pooledW + pw] / poolsize;
  }
@@ -600,16 +600,13 @@ __global__ void KeAvgPool3DForward(const int nthreads,
  int dstart = pd * strideD - padD;
  int hstart = ph * strideH - padH;
  int wstart = pw * strideW - padW;
- int dend = min(dstart + sizeZ, depth + padD);
- int hend = min(hstart + sizeY, height + padH);
- int wend = min(wstart + sizeX, width + padW);
- int pool_size = (dend - dstart) * (hend - hstart) * (wend - wstart);
+ int dend = min(dstart + sizeZ, depth);
+ int hend = min(hstart + sizeY, height);
+ int wend = min(wstart + sizeX, width);
  dstart = max(dstart, 0);
  hstart = max(hstart, 0);
  wstart = max(wstart, 0);
- dend = min(dend, depth);
- hend = min(hend, height);
- wend = min(wend, width);
+ int pool_size = (dend - dstart) * (hend - hstart) * (wend - wstart);
 
  real aveval = 0;
  inputData += (frameNum * channels + c) * depth * height * width;
@@ -712,15 +709,18 @@ __global__ void KeAvgPool3DBackward(const int nthreads,
  outGrad += (frameNum * channels + offsetC) * pooledD * pooledH * pooledW;
 
  for (int pd = pdstart; pd < pdend; ++pd) {
+ int dstart = pd * strideD - padD;
+ int dend = min(dstart + sizeZ, depth);
+ dstart = max(dstart, 0);
  for (int ph = phstart; ph < phend; ++ph) {
+ int hstart = ph * strideH - padH;
+ int hend = min(hstart + sizeY, height);
+ hstart = max(hstart, 0);
  for (int pw = pwstart; pw < pwend; ++pw) {
  // figure out the pooling size
- int dstart = pd * strideD - padD;
- int hstart = ph * strideH - padH;
  int wstart = pw * strideW - padW;
- int dend = min(dstart + sizeZ, depth + padD);
- int hend = min(hstart + sizeY, height + padH);
- int wend = min(wstart + sizeX, width + padW);
+ int wend = min(wstart + sizeX, width);
+ wstart = max(wstart, 0);
  int poolsize = (dend - dstart) * (hend - hstart) * (wend - wstart);
  gradient += outGrad[(pd * pooledH + ph) * pooledW + pw] / poolsize;
  }

paddle/cuda/src/hl_cuda_cudnn.cc

@@ -432,11 +432,11 @@ void hl_create_pooling_descriptor(hl_pooling_descriptor* pooling_desc,
  cudnn_mode = CUDNN_POOLING_MAX;
  break;
  case HL_POOLING_AVERAGE:
- cudnn_mode = CUDNN_POOLING_AVERAGE_COUNT_INCLUDE_PADDING;
- break;
- case HL_POOLING_AVERAGE_EXCLUDE_PADDING:
  cudnn_mode = CUDNN_POOLING_AVERAGE_COUNT_EXCLUDE_PADDING;
  break;
+ case HL_POOLING_AVERAGE_INCLUDE_PADDING:
+ cudnn_mode = CUDNN_POOLING_AVERAGE_COUNT_INCLUDE_PADDING;
+ break;
  default:
  LOG(FATAL) << "parameter mode error";
  }

paddle/gserver/layers/CudnnPoolLayer.cpp

@@ -29,9 +29,9 @@ bool CudnnPoolLayer::typeCheck(const std::string &poolType,
  if (mode) {
  *mode = HL_POOLING_AVERAGE;
  }
- } else if (poolType == "cudnn-avg-excl-pad-pool") {
+ } else if (poolType == "cudnn-avg-incl-pad-pool") {
  if (mode) {
- *mode = HL_POOLING_AVERAGE_EXCLUDE_PADDING;
+ *mode = HL_POOLING_AVERAGE_INCLUDE_PADDING;
  }
  } else {
  return false;