         int h = h_in + i;
         int w = w_in + j;
         *data_col = (h >= 0 && w >= 0 && h < height && w < width) ?
-                                             data_im[i * width + j] : 0;
+          data_im[i * width + j] : 0;
         data_col += height_col * width_col;
       }
     }


  // Resize temporary columns
  THCudaTensor_resize2d(gradColumns, nInputPlane*kW*kH, outputHeight*outputWidth);
      
  // Helpers
  THCudaTensor *input_n = THCudaTensor_new();
  THCudaTensor *gradInput_n = THCudaTensor_new();


    // Do GEMM (note: this is a bit confusing because gemm assumes column-major matrices)
    THCudaBlas_gemm(
        't', 'n',
        n, m, k,
        scale,
        THCudaTensor_data(columns), k,
        THCudaTensor_data(gradOutput_n), k,
        1,
        THCudaTensor_data(gradWeight), n
    );

    // Do Bias:
    // M,N,K are dims of matrix A and B
    // (see http://docs.nvidia.com/cuda/cublas/#cublas-lt-t-gt-gemm)
    long m_ = nOutputPlane;
