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new 884408a Parallelization for ROIpooling OP (#9958)
884408a is described below
commit 884408a065a7872fda3b22418a8ba35f89ff58e8
Author: XinyuChen <xinyu1.c...@intel.com>
AuthorDate: Fri Mar 9 09:56:39 2018 +0800
Parallelization for ROIpooling OP (#9958)
* parallelization for roipooling
* remove some useless computation
* remove useless muls
* add author and retriggering
* retrigger again
---
src/operator/roi_pooling.cc | 48 ++++++++++++++++++++++++++-------------------
1 file changed, 28 insertions(+), 20 deletions(-)
diff --git a/src/operator/roi_pooling.cc b/src/operator/roi_pooling.cc
index 10d1420..acff1f9 100644
--- a/src/operator/roi_pooling.cc
+++ b/src/operator/roi_pooling.cc
@@ -21,7 +21,7 @@
* Copyright (c) 2015 by Contributors
* \file roi_pooling.cc
* \brief roi pooling operator
- * \author Ross Girshick, Kye-Hyeon Kim, Jian Guo
+ * \author Ross Girshick, Kye-Hyeon Kim, Jian Guo, Xinyu Chen
*/
#include "./roi_pooling-inl.h"
#include <mshadow/base.h>
@@ -54,13 +54,22 @@ inline void ROIPoolForward(const Tensor<cpu, 4, Dtype> &out,
const int num_rois = bbox.size(0);
const int data_size = data.size(1) * data.size(2) * data.size(3);
+ const int data_size_c = data.size(2) * data.size(3);
+ const int out_size_c = out.size(2) * out.size(3);
+ const int out_size = channels_ * out_size_c;
+ const int max_idx_size_c = max_idx.size(2) * max_idx.size(3);
+ const int max_idx_size = channels_ * max_idx_size_c;
// For each ROI R = [batch_index x1 y1 x2 y2]: max pool over R
for (int n = 0; n < num_rois; ++n) {
- int roi_batch_ind = bottom_rois[0];
- int roi_start_w = round(bottom_rois[1] * spatial_scale_);
- int roi_start_h = round(bottom_rois[2] * spatial_scale_);
- int roi_end_w = round(bottom_rois[3] * spatial_scale_);
- int roi_end_h = round(bottom_rois[4] * spatial_scale_);
+ // Increment ROI data pointer
+ const Dtype *bottom_rois_n = bottom_rois + n * bbox.size(1);
+ Dtype *top_data_n = top_data + n * out_size;
+ Dtype *argmax_data_n = argmax_data + n * max_idx_size;
+ int roi_batch_ind = bottom_rois_n[0];
+ int roi_start_w = round(bottom_rois_n[1] * spatial_scale_);
+ int roi_start_h = round(bottom_rois_n[2] * spatial_scale_);
+ int roi_end_w = round(bottom_rois_n[3] * spatial_scale_);
+ int roi_end_h = round(bottom_rois_n[4] * spatial_scale_);
assert(roi_batch_ind >= 0);
assert(static_cast<index_t>(roi_batch_ind) < data.size(0) /* batch size
*/);
@@ -74,12 +83,18 @@ inline void ROIPoolForward(const Tensor<cpu, 4, Dtype> &out,
const Dtype* batch_data = bottom_data + data_size * roi_batch_ind;
+ #pragma omp parallel for
for (int c = 0; c < channels_; ++c) {
+ // Increment all data pointers
+ const Dtype* batch_data_c = batch_data + c * data_size_c;
+ Dtype* top_data_c = top_data_n + c * out_size_c;
+ Dtype* argmax_data_c = argmax_data_n + c * max_idx_size_c;
+
for (int ph = 0; ph < pooled_height_; ++ph) {
for (int pw = 0; pw < pooled_width_; ++pw) {
// Compute pooling region for this output unit:
- // start (included) = floor(ph * roi_height / pooled_height_)
- // end (excluded) = ceil((ph + 1) * roi_height / pooled_height_)
+ // start (included) = floor(ph * roi_height / pooled_height_)
+ // end (excluded) = ceil((ph + 1) * roi_height / pooled_height_)
int hstart = static_cast<int>(floor(static_cast<Dtype>(ph)
* bin_size_h));
int wstart = static_cast<int>(floor(static_cast<Dtype>(pw)
@@ -98,30 +113,23 @@ inline void ROIPoolForward(const Tensor<cpu, 4, Dtype>
&out,
const int pool_index = ph * pooled_width_ + pw;
if (is_empty) {
- top_data[pool_index] = 0;
- argmax_data[pool_index] = -1;
+ top_data_c[pool_index] = 0;
+ argmax_data_c[pool_index] = -1;
}
for (int h = hstart; h < hend; ++h) {
for (int w = wstart; w < wend; ++w) {
const int index = h * width_ + w;
- if (batch_data[index] > top_data[pool_index]) {
- top_data[pool_index] = batch_data[index];
- argmax_data[pool_index] = index;
+ if (batch_data_c[index] > top_data_c[pool_index]) {
+ top_data_c[pool_index] = batch_data_c[index];
+ argmax_data_c[pool_index] = index;
}
}
}
}
}
- // Increment all data pointers by one channel
- batch_data += data.size(2) * data.size(3);
- top_data += out.size(2) * out.size(3);
- argmax_data += max_idx.size(2) * max_idx.size(3);
}
- // Increment ROI data pointer
- bottom_rois += bbox.size(1);
}
-
return;
}
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