fix auto padding calculation again

src/caffe/layers/spp_layer.cpp

@@ -23,18 +23,16 @@ LayerParameter SPPLayer<Dtype>::GetPoolingParam(const int pyramid_level,
   // performed across the entire image
   int kernel_h = ceil(bottom_h / static_cast<double>(num_bins));
   int pad_h = 0;
-  int remainder_h = kernel_h - bottom_h % num_bins + 1;
+  int remainder_h = kernel_h * num_bins - bottom_h;
   if (bottom_h % num_bins > 0) {
     pad_h = (remainder_h + 1) / 2;
-    kernel_h = (bottom_h + 2 * pad_h) / num_bins;
   }
 
   int kernel_w = ceil(bottom_w / static_cast<double>(num_bins));
   int pad_w = 0;
-  int remainder_w = kernel_w - bottom_w % num_bins + 1;
+  int remainder_w = kernel_w * num_bins - bottom_w;
   if (bottom_w % num_bins > 0) {
     pad_w = (remainder_w + 1) / 2;
-    kernel_w = (bottom_w + 2 * pad_w) / num_bins;
   }
 
   pooling_param.mutable_pooling_param()->set_pad_h(pad_h);

src/caffe/test/test_spp_layer.cpp

@@ -22,26 +22,31 @@ class SPPLayerTest : public MultiDeviceTest<TypeParam> {
   SPPLayerTest()
       : blob_bottom_(new Blob<Dtype>()),
         blob_bottom_2_(new Blob<Dtype>()),
+        blob_bottom_3_(new Blob<Dtype>()),
         blob_top_(new Blob<Dtype>()) {}
   virtual void SetUp() {
     Caffe::set_random_seed(1701);
     blob_bottom_->Reshape(2, 3, 9, 8);
     blob_bottom_2_->Reshape(4, 3, 1024, 765);
+    blob_bottom_3_->Reshape(10, 3, 7, 7);
     // fill the values
     FillerParameter filler_param;
     GaussianFiller<Dtype> filler(filler_param);
     filler.Fill(this->blob_bottom_);
     blob_bottom_vec_.push_back(blob_bottom_);
     blob_bottom_vec_2_.push_back(blob_bottom_2_);
+    blob_bottom_vec_3_.push_back(blob_bottom_3_);
     blob_top_vec_.push_back(blob_top_);
   }
   virtual ~SPPLayerTest() { delete blob_bottom_; delete blob_top_; }
 
   Blob<Dtype>* const blob_bottom_;
   Blob<Dtype>* const blob_bottom_2_;
+  Blob<Dtype>* const blob_bottom_3_;
   Blob<Dtype>* const blob_top_;
   vector<Blob<Dtype>*> blob_bottom_vec_;
   vector<Blob<Dtype>*> blob_bottom_vec_2_;
+  vector<Blob<Dtype>*> blob_bottom_vec_3_;
   vector<Blob<Dtype>*> blob_top_vec_;
 };
 
@@ -81,6 +86,23 @@ TYPED_TEST(SPPLayerTest, TestEqualOutputDims) {
   EXPECT_EQ(this->blob_top_->width(), 1);
 }
 
+TYPED_TEST(SPPLayerTest, TestEqualOutputDims2) {
+  typedef typename TypeParam::Dtype Dtype;
+  LayerParameter layer_param;
+  layer_param.mutable_spp_param()->set_pyramid_height(3);
+  SPPLayer<Dtype> layer(layer_param);
+  layer.SetUp(this->blob_bottom_vec_3_, this->blob_top_vec_);
+  // expected number of pool results is geometric sum
+  // (1 - r ** n)/(1 - r) where r = 4 and n = pyramid_height
+  // (1 - 4 ** 3)/(1 - 4) = 21
+  // multiply bottom num_channels * expected_pool_results
+  // to get expected num_channels (3 * 21 = 63)
+  EXPECT_EQ(this->blob_top_->num(), 10);
+  EXPECT_EQ(this->blob_top_->channels(), 63);
+  EXPECT_EQ(this->blob_top_->height(), 1);
+  EXPECT_EQ(this->blob_top_->width(), 1);
+}
+
 TYPED_TEST(SPPLayerTest, TestForwardBackward) {
   typedef typename TypeParam::Dtype Dtype;
   LayerParameter layer_param;