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author | Gian Marco Iodice <gianmarco.iodice@arm.com> | 2018-03-22 11:24:56 +0000 |
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committer | Anthony Barbier <anthony.barbier@arm.com> | 2018-11-02 16:49:16 +0000 |
commit | 247f52cfe337f7b2542b900e3d8cf122e9d4f11c (patch) | |
tree | bcbabb7f1eea588a5d37566829763506d328e7a9 /arm_compute/core/CL/kernels/CLWinogradOutputTransformKernel.h | |
parent | eb8a399ba655b85c6854676832eb11b0af4108fe (diff) | |
download | ComputeLibrary-247f52cfe337f7b2542b900e3d8cf122e9d4f11c.tar.gz |
COMPMID-1013 - Create WinogradInfo data structure
COMPMID-1014 - Refactoring Winograd's dataset
Change-Id: I6abdcbf9a90d663f4db666cd410afece9f1d034d
Reviewed-on: https://eu-gerrit-1.euhpc.arm.com/125899
Tested-by: Jenkins <bsgcomp@arm.com>
Reviewed-by: Anthony Barbier <anthony.barbier@arm.com>
Diffstat (limited to 'arm_compute/core/CL/kernels/CLWinogradOutputTransformKernel.h')
-rw-r--r-- | arm_compute/core/CL/kernels/CLWinogradOutputTransformKernel.h | 36 |
1 files changed, 22 insertions, 14 deletions
diff --git a/arm_compute/core/CL/kernels/CLWinogradOutputTransformKernel.h b/arm_compute/core/CL/kernels/CLWinogradOutputTransformKernel.h index 35117c65db..b0d0bbeeaa 100644 --- a/arm_compute/core/CL/kernels/CLWinogradOutputTransformKernel.h +++ b/arm_compute/core/CL/kernels/CLWinogradOutputTransformKernel.h @@ -48,31 +48,39 @@ public: ~CLWinogradOutputTransformKernel() = default; /** Set the input and output tensor. * - * @param[in] input Source tensor with shape [C, N, 16, batches]. Data types supported: F32. - * @param[in] bias Biases tensor. Shared biases supported. Biases are 1D tensor with dimensions [OFM]. It can be a nullptr. Data type supported: as @p input - * @param[out] output Destination tensor with shape [output_convolved_dims.width, output_convolved_dims.height, C, batches]. Data type supported: same as @p input - * @param[in] kernel_dims Kernel dimensions (Width and height). Currently only supported 3x3 kernels - * @param[in] output_convolved_dims Output dimensions after the convolution (Width and height) - * @param[in] num_tiles Number of tiles of size 2x2 in the output tensor along the X and Y direction + * @note Winograd output transform supports the following configurations: + * Output tile size: 2x2 + * Kernel size: 3x3 + * Strides: only unit strides + * + * @param[in] input Source tensor with shape [C, N, 16, batches]. Data types supported: F32. + * @param[in] bias Biases tensor. Shared biases supported. Biases are 1D tensor with dimensions [OFM]. It can be a nullptr. Data type supported: as @p input + * @param[out] output The output tensor. The shape for this tensor can be calculated using the utility function @p compute_winograd_output_transform_shape. Data types supported: Same as @p input + * @param[in] winograd_info Contains Winograd's information described in @ref WinogradInfo */ - void configure(const ICLTensor *input, const ICLTensor *bias, ICLTensor *output, const Size2D &kernel_dims, const Size2D &output_convolved_dims, const Size2D &num_tiles); + void configure(const ICLTensor *input, const ICLTensor *bias, ICLTensor *output, const WinogradInfo &winograd_info); /** Static function to check if given info will lead to a valid configuration of @ref CLWinogradOutputTransformKernel * - * @param[in] input Source tensor with shape [C, N, 16, batches]. Data types supported: F32. - * @param[in] bias Biases tensor. Shared biases supported. Biases are 1D tensor with dimensions [OFM]. It can be a nullptr. Data type supported: as @p input - * @param[out] output Destination tensor with shape [output_convolved_dims.width, output_convolved_dims.height, C, batches]. Data type supported: same as @p input - * @param[in] kernel_dims Kernel dimensions (Width and height). Currently only supported 3x3 kernels - * @param[in] output_convolved_dims Output dimensions after the convolution (Width and height) - * @param[in] num_tiles Number of tiles of size 2x2 in the output tensor along the X and Y direction + * @note Winograd output transform supports the following configurations: + * Output tile size: 2x2 + * Kernel size: 3x3 + * Strides: only unit strides + * + * @param[in] input Source tensor with shape [C, N, 16, batches]. Data types supported: F32. + * @param[in] bias Biases tensor. Shared biases supported. Biases are 1D tensor with dimensions [OFM]. It can be a nullptr. Data type supported: as @p input + * @param[out] output The output tensor. The shape for this tensor can be calculated using the utility function @p compute_winograd_output_transform_shape. Data types supported: Same as @p input + * @param[in] winograd_info Contains Winograd's information described in @ref WinogradInfo * * @return a status */ - static Status validate(const ITensorInfo *input, const ITensorInfo *bias, const ITensorInfo *output, const Size2D &kernel_dims, const Size2D &output_convolved_dims, const Size2D &num_tiles); + static Status validate(const ITensorInfo *input, const ITensorInfo *bias, const ITensorInfo *output, const WinogradInfo &winograd_info); // Inherited methods overridden: void run(const Window &window, cl::CommandQueue &queue) override; private: + using WinogradKey = std::pair<std::pair<int, int>, std::pair<int, int>>; + const ICLTensor *_input; const ICLTensor *_bias; ICLTensor *_output; |