Allow wider test tolerances for:

1) Size of half numbers
2) Convolution weight/bias
3) BatchNormalization

1 files changed, 5 insertions, 5 deletions

diff --git a/lib/THCUNN/im2col.h b/lib/THCUNN/im2col.h
index 9cb5afe..ba57263 100644
--- a/lib/THCUNN/im2col.h
+++ b/lib/THCUNN/im2col.h
@@ -60,7 +60,7 @@ void im2col(cudaStream_t stream, const Dtype* data_im, const int channels,
   THCudaCheck(cudaGetLastError());
 }
 
-template <typename Dtype>
+template <typename Dtype, typename Acctype>
 __global__ void col2im_kernel(const int n, const Dtype* data_col,
                                   const int height, const int width, const int channels,
                                   const int kernel_h, const int kernel_w,
@@ -70,7 +70,7 @@ __global__ void col2im_kernel(const int n, const Dtype* data_col,
                                   const int height_col, const int width_col,
                                   Dtype* data_im) {
   CUDA_KERNEL_LOOP(index, n) {
-    Dtype val = ScalarConvert<int, Dtype>::to(0);
+    Acctype val = Acctype(0);
     const int w_im = index % width + pad_w;
     const int h_im = (index / width) % height + pad_h;
     const int c_im = index / (width * height);
@@ -97,11 +97,11 @@ __global__ void col2im_kernel(const int n, const Dtype* data_col,
         }
       }
     }
-    data_im[index] = val;
+    data_im[index] = ScalarConvert<Acctype, Dtype>::to(val);
   }
 }
 
-template <typename Dtype>
+template <typename Dtype, typename Acctype>
 void col2im(cudaStream_t stream, const Dtype* data_col, const int channels,
             const int height, const int width,
             const int patch_h, const int patch_w, const int pad_h,
@@ -114,7 +114,7 @@ void col2im(cudaStream_t stream, const Dtype* data_col, const int channels,
   int num_kernels = channels * height * width;
   // To avoid involving atomic operations, we will launch one kernel per
   // bottom dimension, and then in the kernel add up the top dimensions.
-  col2im_kernel <<<GET_BLOCKS(num_kernels), CUDA_NUM_THREADS, 0, stream>>> (
+  col2im_kernel<Dtype, Acctype> <<<GET_BLOCKS(num_kernels), CUDA_NUM_THREADS, 0, stream>>> (
       num_kernels, data_col, height, width, channels,
       patch_h, patch_w, pad_h, pad_w, stride_h, stride_w,
       dilation_h, dilation_w,