diff options
Diffstat (limited to 'src/core/cpu/kernels/CpuWinogradConv2dKernel.cpp')
| -rw-r--r-- | src/core/cpu/kernels/CpuWinogradConv2dKernel.cpp | 10 |
1 files changed, 6 insertions, 4 deletions
diff --git a/src/core/cpu/kernels/CpuWinogradConv2dKernel.cpp b/src/core/cpu/kernels/CpuWinogradConv2dKernel.cpp index 5620d36e2c..9456f96354 100644 --- a/src/core/cpu/kernels/CpuWinogradConv2dKernel.cpp +++ b/src/core/cpu/kernels/CpuWinogradConv2dKernel.cpp @@ -194,8 +194,8 @@ template <typename T, int OutputTileRows, int OutputTileCols, int KernelRows, in unsigned int CpuWinogradConv2dTransformWeightsKernel<T, OutputTileRows, OutputTileCols, KernelRows, KernelCols>::get_weight_storage_size(int num_output_channels, int num_input_channels) const { const KernelShape shape(num_output_channels, KernelRows, KernelCols, num_input_channels); - return static_cast<unsigned int>( - WinogradConv::get_kernel_storage_size(num_input_channels, num_output_channels)); + // WinogradConv returns the size in bytes, we divide by `sizeof(T)` to express that in units of T + return static_cast<unsigned int>(WinogradConv::get_kernel_storage_size(num_input_channels, num_output_channels) / sizeof(T)); } template <typename T, int OutputTileRows, int OutputTileCols, int KernelRows, int KernelCols> @@ -297,7 +297,8 @@ unsigned int CpuWinogradConv2dTransformInputKernel<T, OutputTileRows, OutputTile // Construct shapes for the input and kernel tensors. const Tensor4DShape input_shape(num_batches, num_rows, num_cols, num_channels); const KernelShape kern_shape(1, KernelRows, KernelCols, num_channels); - return static_cast<unsigned int>(WinogradConv::get_input_storage_size(num_batches, num_rows, num_cols, num_channels, same_padding)); + // Return the size, converted into units of TIn + return static_cast<unsigned int>(WinogradConv::get_input_storage_size(num_batches, num_rows, num_cols, num_channels, same_padding) / sizeof(T)); } template <typename T, int OutputTileRows, int OutputTileCols, int KernelRows, int KernelCols> @@ -432,8 +433,9 @@ unsigned int CpuWinogradConv2dTransformOutputKernel<T, OutputTileRows, OutputTil // Construct shapes for the input and kernel tensors. const Tensor4DShape input_shape(num_batches, num_rows, num_cols, 1); const KernelShape kern_shape(num_output_channels, KernelRows, KernelCols, 1); + // Return the size, converted into units of TOut return static_cast<unsigned int>( - WinogradConv::get_output_storage_size(num_batches, num_rows, num_cols, num_output_channels)); + WinogradConv::get_output_storage_size(num_batches, num_rows, num_cols, num_output_channels) / sizeof(T)); } template <typename T, int OutputTileRows, int OutputTileCols, int KernelRows, int KernelCols> |