diff options
Diffstat (limited to 'arm_compute/core/CL/kernels/CLWinogradFilterTransformKernel.h')
| -rw-r--r-- | arm_compute/core/CL/kernels/CLWinogradFilterTransformKernel.h | 22 |
1 files changed, 16 insertions, 6 deletions
diff --git a/arm_compute/core/CL/kernels/CLWinogradFilterTransformKernel.h b/arm_compute/core/CL/kernels/CLWinogradFilterTransformKernel.h index 5e3d815d8c..9d0833d695 100644 --- a/arm_compute/core/CL/kernels/CLWinogradFilterTransformKernel.h +++ b/arm_compute/core/CL/kernels/CLWinogradFilterTransformKernel.h @@ -48,10 +48,15 @@ public: ~CLWinogradFilterTransformKernel() = default; /** Set the input and output tensor. * - * @note Winograd filter transform supports the following configurations: - * F(output tile, kernel size):F(2x2, 3x3), F(4x4, 3x3), F(4x4, 5x5) + * @note Winograd filter transform supports the following configurations for NCWH data layout + * F(output tile, kernel size):F(2x2, 3x3), F(2x1, 3x1), F(1x2, 1x3), + * F(4x4, 3x3), F(4x1, 3x1), F(1x4, 1x3), + * F(4x4, 5x5), F(4x1, 5x1), F(1x4, 1x5) + * + * @note Winograd filter transform supports the following configurations for NHWC data layout + * F(output tile, kernel size):F(4x4, 3x3), F(4x1, 3x1), F(1x4, 1x3) + * F(4x4, 5x5) * Strides: only unit strides - * Data Layout: NCHW for all configurations, NHWC for F(4x4, 3x3) and F(4x4, 5x5) * * @param[in] input Source tensor. The input is a 4D tensor with dimensions [kernel_x, kernel_y, IFM, OFM] (NCHW data layout) or [IFM, kernel_x, kernel_y, OFM] (NHWC data layout). Data types supported: F32. * @param[out] output The output tensor. The shape for this tensor can be calculated using the utility function @p compute_winograd_filter_transform_shape. Data types supported: Same as @p input @@ -60,10 +65,15 @@ public: void configure(const ICLTensor *input, ICLTensor *output, const WinogradInfo &winograd_info); /** Static function to check if given info will lead to a valid configuration of @ref CLWinogradFilterTransformKernel * - * @note Winograd filter transform supports the following configurations: - * F(output tile, kernel size):F(2x2, 3x3), F(4x4, 3x3), F(4x4, 5x5) + * @note Winograd filter transform supports the following configurations for NCWH data layout + * F(output tile, kernel size):F(2x2, 3x3), F(2x1, 3x1), F(1x2, 1x3), + * F(4x4, 3x3), F(4x1, 3x1), F(1x4, 1x3), + * F(4x4, 5x5), F(4x1, 5x1), F(1x4, 1x5) + * + * @note Winograd filter transform supports the following configurations for NHWC data layout + * F(output tile, kernel size):F(4x4, 3x3), + * F(4x4, 5x5) * Strides: only unit strides - * Data Layout: NCHW for all configurations, NHWC for F(4x4, 3x3) and F(4x4, 5x5) * * @param[in] input Source tensor. The input is a 4D tensor with dimensions [kernel_x, kernel_y, IFM, OFM] (NCHW data layout) or [IFM, kernel_x, kernel_y, OFM] (NHWC data layout). Data types supported: F32. * @param[out] output The output tensor. The shape for this tensor can be calculated using the utility function @p compute_winograd_filter_transform_shape. Data types supported: Same as @p input |