Port CLWinogradConvolutionLayer with ClWinogradConv2d

Port CLWinogradInputTransformKernel
Port CLWinogradFilterTransformKernel
Port CLWinogradOutputTransformKernel

Resolves: COMPMID-4504

Change-Id: I3177dda0b9c2f56b36cb317027e94abe8d47229e
Signed-off-by: Manuel Bottini <manuel.bottini@arm.com>
Reviewed-on: https://review.mlplatform.org/c/ml/ComputeLibrary/+/5680
Reviewed-by: Georgios Pinitas <georgios.pinitas@arm.com>
Tested-by: Arm Jenkins <bsgcomp@arm.com>
Comments-Addressed: Arm Jenkins <bsgcomp@arm.com>

10 files changed, 380 insertions, 498 deletions

diff --git a/src/core/CL/CLKernels.h b/src/core/CL/CLKernels.h
index c59eebacbb..5dc95dae27 100644
--- a/src/core/CL/CLKernels.h
+++ b/src/core/CL/CLKernels.h
@@ -80,8 +80,5 @@
 #include "src/core/CL/kernels/CLStridedSliceKernel.h"
 #include "src/core/CL/kernels/CLTileKernel.h"
 #include "src/core/CL/kernels/CLWeightsReshapeKernel.h"
-#include "src/core/CL/kernels/CLWinogradFilterTransformKernel.h"
-#include "src/core/CL/kernels/CLWinogradInputTransformKernel.h"
-#include "src/core/CL/kernels/CLWinogradOutputTransformKernel.h"
 
 #endif /* ARM_COMPUTE_CLKERNELS_H */
diff --git a/src/core/CL/kernels/CLWinogradFilterTransformKernel.h b/src/core/CL/kernels/CLWinogradFilterTransformKernel.h
deleted file mode 100644
index d22fedebcd..0000000000
--- a/src/core/CL/kernels/CLWinogradFilterTransformKernel.h
+++ /dev/null
@@ -1,115 +0,0 @@
-/*
- * Copyright (c) 2018-2020 Arm Limited.
- *
- * SPDX-License-Identifier: MIT
- *
- * Permission is hereby granted, free of charge, to any person obtaining a copy
- * of this software and associated documentation files (the "Software"), to
- * deal in the Software without restriction, including without limitation the
- * rights to use, copy, modify, merge, publish, distribute, sublicense, and/or
- * sell copies of the Software, and to permit persons to whom the Software is
- * furnished to do so, subject to the following conditions:
- *
- * The above copyright notice and this permission notice shall be included in all
- * copies or substantial portions of the Software.
- *
- * THE SOFTWARE IS PROVIDED "AS IS", WITHOUT WARRANTY OF ANY KIND, EXPRESS OR
- * IMPLIED, INCLUDING BUT NOT LIMITED TO THE WARRANTIES OF MERCHANTABILITY,
- * FITNESS FOR A PARTICULAR PURPOSE AND NONINFRINGEMENT. IN NO EVENT SHALL THE
- * AUTHORS OR COPYRIGHT HOLDERS BE LIABLE FOR ANY CLAIM, DAMAGES OR OTHER
- * LIABILITY, WHETHER IN AN ACTION OF CONTRACT, TORT OR OTHERWISE, ARISING FROM,
- * OUT OF OR IN CONNECTION WITH THE SOFTWARE OR THE USE OR OTHER DEALINGS IN THE
- * SOFTWARE.
- */
-#ifndef ARM_COMPUTE_CLWINOGRADFILTERTRANSFORMKERNEL_H
-#define ARM_COMPUTE_CLWINOGRADFILTERTRANSFORMKERNEL_H
-
-#include "src/core/CL/ICLKernel.h"
-
-namespace arm_compute
-{
-class ICLTensor;
-
-/** Interface for the Winograd filter transform kernel. */
-class CLWinogradFilterTransformKernel : public ICLKernel
-{
-public:
-    /** Default constructor */
-    CLWinogradFilterTransformKernel();
-    /** Prevent instances of this class from being copied (As this class contains pointers) */
-    CLWinogradFilterTransformKernel(const CLWinogradFilterTransformKernel &) = delete;
-    /** Prevent instances of this class from being copied (As this class contains pointers) */
-    CLWinogradFilterTransformKernel &operator=(const CLWinogradFilterTransformKernel &) = delete;
-    /** Allow instances of this class to be moved */
-    CLWinogradFilterTransformKernel(CLWinogradFilterTransformKernel &&) = default;
-    /** Allow instances of this class to be moved */
-    CLWinogradFilterTransformKernel &operator=(CLWinogradFilterTransformKernel &&) = default;
-    /** Default destructor */
-    ~CLWinogradFilterTransformKernel() = default;
-    /** Set the input and output tensor.
-     *
-     * @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), F(4x1, 5x1), F(1x4, 1x5)
-     *
-     *       Strides: only unit strides
-     *
-     * @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: F16/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
-     * @param[in]  winograd_info Contains Winograd's information described in @ref WinogradInfo
-     */
-    void configure(const ICLTensor *input, ICLTensor *output, const WinogradInfo &winograd_info);
-    /** Set the input and output tensor.
-     *
-     * @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), F(4x1, 5x1), F(1x4, 1x5)
-     *
-     *       Strides: only unit strides
-     *
-     * @param[in]  compile_context The compile context to be used.
-     * @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: F16/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
-     * @param[in]  winograd_info   Contains Winograd's information described in @ref WinogradInfo
-     */
-    void configure(const CLCompileContext &compile_context, 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 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), F(4x1, 5x1), F(1x4, 1x5)
-     *
-     *       Strides: only unit strides
-     *
-     * @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: F16/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
-     * @param[in]  winograd_info Contains Winograd's information described in @ref WinogradInfo
-     *
-     * @return a status
-     */
-    static Status validate(const ITensorInfo *input, const ITensorInfo *output, const WinogradInfo &winograd_info);
-
-    // Inherited methods overridden:
-    void run(const Window &window, cl::CommandQueue &queue) override;
-
-private:
-    const ICLTensor *_input;
-    ICLTensor       *_output;
-};
-} // namespace arm_compute
-#endif /*ARM_COMPUTE_CLWINOGRADFILTERTRANSFORMKERNEL_H */
diff --git a/src/core/CL/kernels/CLWinogradInputTransformKernel.h b/src/core/CL/kernels/CLWinogradInputTransformKernel.h
deleted file mode 100644
index 25301877e6..0000000000
--- a/src/core/CL/kernels/CLWinogradInputTransformKernel.h
+++ /dev/null
@@ -1,121 +0,0 @@
-/*
- * Copyright (c) 2018-2020 Arm Limited.
- *
- * SPDX-License-Identifier: MIT
- *
- * Permission is hereby granted, free of charge, to any person obtaining a copy
- * of this software and associated documentation files (the "Software"), to
- * deal in the Software without restriction, including without limitation the
- * rights to use, copy, modify, merge, publish, distribute, sublicense, and/or
- * sell copies of the Software, and to permit persons to whom the Software is
- * furnished to do so, subject to the following conditions:
- *
- * The above copyright notice and this permission notice shall be included in all
- * copies or substantial portions of the Software.
- *
- * THE SOFTWARE IS PROVIDED "AS IS", WITHOUT WARRANTY OF ANY KIND, EXPRESS OR
- * IMPLIED, INCLUDING BUT NOT LIMITED TO THE WARRANTIES OF MERCHANTABILITY,
- * FITNESS FOR A PARTICULAR PURPOSE AND NONINFRINGEMENT. IN NO EVENT SHALL THE
- * AUTHORS OR COPYRIGHT HOLDERS BE LIABLE FOR ANY CLAIM, DAMAGES OR OTHER
- * LIABILITY, WHETHER IN AN ACTION OF CONTRACT, TORT OR OTHERWISE, ARISING FROM,
- * OUT OF OR IN CONNECTION WITH THE SOFTWARE OR THE USE OR OTHER DEALINGS IN THE
- * SOFTWARE.
- */
-#ifndef ARM_COMPUTE_CLWINOGRADINPUTTRANSFORMKERNEL_H
-#define ARM_COMPUTE_CLWINOGRADINPUTTRANSFORMKERNEL_H
-
-#include "src/core/CL/ICLKernel.h"
-
-namespace arm_compute
-{
-class ICLTensor;
-
-/** OpenCL kernel to perform Winograd input transform.*/
-class CLWinogradInputTransformKernel : public ICLKernel
-{
-public:
-    /** Default constructor */
-    CLWinogradInputTransformKernel();
-    /** Prevent instances of this class from being copied (As this class contains pointers) */
-    CLWinogradInputTransformKernel(const CLWinogradInputTransformKernel &) = delete;
-    /** Prevent instances of this class from being copied (As this class contains pointers) */
-    CLWinogradInputTransformKernel &operator=(const CLWinogradInputTransformKernel &) = delete;
-    /** Allow instances of this class to be moved */
-    CLWinogradInputTransformKernel(CLWinogradInputTransformKernel &&) = default;
-    /** Allow instances of this class to be moved */
-    CLWinogradInputTransformKernel &operator=(CLWinogradInputTransformKernel &&) = default;
-    /** Set the input and output of the kernel.
-     *
-     * @note Winograd input 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 input 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), F(4x1, 5x1), F(1x4, 1x5)
-     *
-     *       Strides: only unit strides
-     *
-     * @param[in] input         The input tensor to transform. Data types supported: F16/F32
-     * @param[in] output        The output tensor. The shape for this tensor can be calculated using the utility function @p compute_winograd_input_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, ICLTensor *output, const WinogradInfo &winograd_info);
-    /** Set the input and output of the kernel.
-     *
-     * @note Winograd input 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 input 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), F(4x1, 5x1), F(1x4, 1x5)
-     *
-     *       Strides: only unit strides
-     *
-     * @param[in] compile_context The compile context to be used.
-     * @param[in] input           The input tensor to transform. Data types supported: F16/F32
-     * @param[in] output          The output tensor. The shape for this tensor can be calculated using the utility function @p compute_winograd_input_transform_shape. Data types supported: Same as @p input
-     * @param[in] winograd_info   Contains Winograd's information described in @ref WinogradInfo.
-     */
-    void configure(const CLCompileContext &compile_context, const ICLTensor *input, ICLTensor *output, const WinogradInfo &winograd_info);
-    /** Static function to check if given info will lead to a valid configuration of @ref CLWinogradInputTransformKernel
-     *
-     * @note Winograd input 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 input 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), F(4x1, 5x1), F(1x4, 1x5)
-     *
-     *       Strides: only unit strides
-     *
-     * @param[in] input         The input tensor to transform. Data types supported: F16/F32
-     * @param[in] output        The output tensor. The shape for this tensor can be calculated using the utility function @p compute_winograd_input_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 *output, const WinogradInfo &winograd_info);
-
-    // Inherited methods overridden:
-    void run(const Window &window, cl::CommandQueue &queue) override;
-    BorderSize border_size() const override;
-
-private:
-    using WinogradKey = std::pair<std::pair<int, int>, std::pair<int, int>>;
-
-    BorderSize       _border_size;
-    const ICLTensor *_input;
-    ICLTensor       *_output;
-    DataLayout       _data_layout;
-    int              _num_tiles_x;
-    int              _num_tiles_y;
-    unsigned int     _step_z;
-};
-} // arm_compute
-#endif /*ARM_COMPUTE_CLWINOGRADINPUTTRANSFORMKERNEL_H */
diff --git a/src/core/CL/kernels/CLWinogradOutputTransformKernel.h b/src/core/CL/kernels/CLWinogradOutputTransformKernel.h
deleted file mode 100644
index 632a5629d9..0000000000
--- a/src/core/CL/kernels/CLWinogradOutputTransformKernel.h
+++ /dev/null
@@ -1,127 +0,0 @@
-/*
- * Copyright (c) 2018-2020 Arm Limited.
- *
- * SPDX-License-Identifier: MIT
- *
- * Permission is hereby granted, free of charge, to any person obtaining a copy
- * of this software and associated documentation files (the "Software"), to
- * deal in the Software without restriction, including without limitation the
- * rights to use, copy, modify, merge, publish, distribute, sublicense, and/or
- * sell copies of the Software, and to permit persons to whom the Software is
- * furnished to do so, subject to the following conditions:
- *
- * The above copyright notice and this permission notice shall be included in all
- * copies or substantial portions of the Software.
- *
- * THE SOFTWARE IS PROVIDED "AS IS", WITHOUT WARRANTY OF ANY KIND, EXPRESS OR
- * IMPLIED, INCLUDING BUT NOT LIMITED TO THE WARRANTIES OF MERCHANTABILITY,
- * FITNESS FOR A PARTICULAR PURPOSE AND NONINFRINGEMENT. IN NO EVENT SHALL THE
- * AUTHORS OR COPYRIGHT HOLDERS BE LIABLE FOR ANY CLAIM, DAMAGES OR OTHER
- * LIABILITY, WHETHER IN AN ACTION OF CONTRACT, TORT OR OTHERWISE, ARISING FROM,
- * OUT OF OR IN CONNECTION WITH THE SOFTWARE OR THE USE OR OTHER DEALINGS IN THE
- * SOFTWARE.
- */
-#ifndef ARM_COMPUTE_CLWINOGRADOUTPUTTRANSFORMKERNEL_H
-#define ARM_COMPUTE_CLWINOGRADOUTPUTTRANSFORMKERNEL_H
-
-#include "src/core/CL/ICLKernel.h"
-
-namespace arm_compute
-{
-class ICLTensor;
-
-/** Interface for the Winograd output transform kernel. */
-class CLWinogradOutputTransformKernel : public ICLKernel
-{
-public:
-    /** Default constructor */
-    CLWinogradOutputTransformKernel();
-    /** Prevent instances of this class from being copied (As this class contains pointers) */
-    CLWinogradOutputTransformKernel(const CLWinogradOutputTransformKernel &) = delete;
-    /** Prevent instances of this class from being copied (As this class contains pointers) */
-    CLWinogradOutputTransformKernel &operator=(const CLWinogradOutputTransformKernel &) = delete;
-    /** Allow instances of this class to be moved */
-    CLWinogradOutputTransformKernel(CLWinogradOutputTransformKernel &&) = default;
-    /** Allow instances of this class to be moved */
-    CLWinogradOutputTransformKernel &operator=(CLWinogradOutputTransformKernel &&) = default;
-    /** Default destructor */
-    ~CLWinogradOutputTransformKernel() = default;
-    /** Set the input and output tensor.
-     *
-     * @note Winograd output 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 output 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), F(4x1, 5x1), F(1x4, 1x5)
-     *
-     *       Strides: only unit strides
-     *
-     * @param[in]  input         Source tensor with shape [C, N, K, batches]. Data types supported: F16/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
-     * @param[in]  act_info      (Optional) Activation layer information in case of a fused activation.
-     */
-    void configure(const ICLTensor *input, const ICLTensor *bias, ICLTensor *output, const WinogradInfo &winograd_info, const ActivationLayerInfo &act_info = ActivationLayerInfo());
-    /** Set the input and output tensor.
-     *
-     * @note Winograd output 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 output 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), F(4x1, 5x1), F(1x4, 1x5)
-     *
-     *       Strides: only unit strides
-     *
-     * @param[in]  compile_context The compile context to be used.
-     * @param[in]  input           Source tensor with shape [C, N, K, batches]. Data types supported: F16/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
-     * @param[in]  act_info        (Optional) Activation layer information in case of a fused activation.
-     */
-    void configure(const CLCompileContext &compile_context, const ICLTensor *input, const ICLTensor *bias, ICLTensor *output, const WinogradInfo &winograd_info,
-                   const ActivationLayerInfo &act_info = ActivationLayerInfo());
-
-    /** Static function to check if given info will lead to a valid configuration of @ref CLWinogradOutputTransformKernel
-     *
-     * @note Winograd output 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 output 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), F(4x1, 5x1), F(1x4, 1x5)
-     *
-     *       Strides: only unit strides
-     *
-     * @param[in]  input         Source tensor with shape [C, N, K, batches]. Data types supported: F16/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
-     * @param[in]  act_info      (Optional) Activation layer information in case of a fused activation @ref ActivationLayerInfo. Only RELU, BOUNDED_RELU, LU_BOUNDED_RELU, LEAKY_RELU and SOFT_RELU supported.
-     *
-     * @return a status
-     */
-    static Status validate(const ITensorInfo *input, const ITensorInfo *bias, const ITensorInfo *output, const WinogradInfo &winograd_info, const ActivationLayerInfo &act_info = ActivationLayerInfo());
-
-    // 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;
-    bool             _is_nhwc;
-};
-} // namespace arm_compute
-#endif /*ARM_COMPUTE_CLWINOGRADOUTPUTTRANSFORMKERNEL_H */
diff --git a/src/core/CL/kernels/CLWinogradFilterTransformKernel.cpp b/src/core/gpu/cl/kernels/ClWinogradFilterTransformKernel.cpp
index 138f4cf947..381b4bcae9 100644
--- a/src/core/CL/kernels/CLWinogradFilterTransformKernel.cpp
+++ b/src/core/gpu/cl/kernels/ClWinogradFilterTransformKernel.cpp
@@ -21,7 +21,7 @@
  * OUT OF OR IN CONNECTION WITH THE SOFTWARE OR THE USE OR OTHER DEALINGS IN THE
  * SOFTWARE.
  */
-#include "src/core/CL/kernels/CLWinogradFilterTransformKernel.h"
+#include "src/core/gpu/cl/kernels/ClWinogradFilterTransformKernel.h"
 
 #include "arm_compute/core/CL/CLHelpers.h"
 #include "arm_compute/core/CL/CLKernelLibrary.h"
@@ -36,13 +36,17 @@
 #include "src/core/CL/CLValidate.h"
 #include "src/core/helpers/AutoConfiguration.h"
 #include "src/core/helpers/WindowHelpers.h"
-
+#include "support/Cast.h"
 #include "support/StringSupport.h"
 
 using namespace arm_compute::misc::shape_calculator;
 
 namespace arm_compute
 {
+namespace opencl
+{
+namespace kernels
+{
 namespace
 {
 Status validate_arguments(const ITensorInfo *input, const ITensorInfo *output, const WinogradInfo &winograd_info)
@@ -87,69 +91,61 @@ std::pair<Status, Window> validate_and_configure_window(ITensorInfo *input, ITen
 }
 } // namespace
 
-CLWinogradFilterTransformKernel::CLWinogradFilterTransformKernel()
-    : _input(nullptr), _output(nullptr)
-{
-}
-
-void CLWinogradFilterTransformKernel::configure(const ICLTensor *input, ICLTensor *output, const WinogradInfo &winograd_info)
+void ClWinogradFilterTransformKernel::configure(const ClCompileContext &compile_context, ITensorInfo *src, ITensorInfo *dst, const WinogradInfo &winograd_info)
 {
-    configure(CLKernelLibrary::get().get_compile_context(), input, output, winograd_info);
-}
-
-void CLWinogradFilterTransformKernel::configure(const CLCompileContext &compile_context, const ICLTensor *input, ICLTensor *output, const WinogradInfo &winograd_info)
-{
-    ARM_COMPUTE_ERROR_ON_NULLPTR(input, output);
+    ARM_COMPUTE_ERROR_ON_NULLPTR(src, dst);
 
     // Output auto initialization if not yet initialized
-    auto_init_if_empty(*output->info(), input->info()->clone()->set_tensor_shape(compute_winograd_filter_transform_shape(*input->info(), winograd_info)));
+    auto_init_if_empty(*dst, src->clone()->set_tensor_shape(compute_winograd_filter_transform_shape(*src, winograd_info)));
 
-    ARM_COMPUTE_ERROR_THROW_ON(validate_arguments(input->info(), output->info(), winograd_info));
-    auto padding_info = get_padding_info({ input, output });
+    ARM_COMPUTE_ERROR_THROW_ON(validate_arguments(src, dst, winograd_info));
+    auto padding_info = get_padding_info({ src, dst });
 
     // Set build options
     CLBuildOptions build_opts;
-    build_opts.add_option("-DSRC_DIM_Z=" + support::cpp11::to_string(input->info()->dimension(2)));
-    build_opts.add_option("-DDATA_TYPE=" + get_cl_type_from_data_type(input->info()->data_type()));
+    build_opts.add_option("-DSRC_DIM_Z=" + support::cpp11::to_string(src->dimension(2)));
+    build_opts.add_option("-DDATA_TYPE=" + get_cl_type_from_data_type(src->data_type()));
     build_opts.add_option_if(winograd_info.kernel_size.height == 1, "-DWINOGRAD_FILTER_TRANSFORM_HORIZONTAL");
     build_opts.add_option_if(winograd_info.kernel_size.width == 1, "-DWINOGRAD_FILTER_TRANSFORM_VERTICAL");
     const Size2D kernel_size      = winograd_info.kernel_size;
     const Size2D output_tile_size = winograd_info.output_tile_size;
 
     // Create kernel
-    std::string kernel_name = "winograd_filter_transform_" + output_tile_size.to_string() + "_" + kernel_size.to_string() + "_" + lower_string(string_from_data_layout(input->info()->data_layout()));
+    std::string kernel_name = "winograd_filter_transform_" + output_tile_size.to_string() + "_" + kernel_size.to_string() + "_" + lower_string(string_from_data_layout(src->data_layout()));
     _kernel                 = create_kernel(compile_context, kernel_name, build_opts.options());
 
-    _input  = input;
-    _output = output;
-
     // Configure kernel window
-    auto win_config = validate_and_configure_window(input->info(), output->info());
+    auto win_config = validate_and_configure_window(src, dst);
     ARM_COMPUTE_ERROR_THROW_ON(win_config.first);
-    ICLKernel::configure_internal(win_config.second);
+    IClKernel::configure_internal(win_config.second);
     ARM_COMPUTE_ERROR_ON(has_padding_changed(padding_info));
 }
 
-Status CLWinogradFilterTransformKernel::validate(const ITensorInfo *input, const ITensorInfo *output, const WinogradInfo &winograd_info)
+Status ClWinogradFilterTransformKernel::validate(const ITensorInfo *src, const ITensorInfo *dst, const WinogradInfo &winograd_info)
 {
-    ARM_COMPUTE_RETURN_ON_ERROR(validate_arguments(input, output, winograd_info));
-    ARM_COMPUTE_RETURN_ON_ERROR(validate_and_configure_window(input->clone().get(), output->clone().get()).first);
+    ARM_COMPUTE_RETURN_ON_ERROR(validate_arguments(src, dst, winograd_info));
+    ARM_COMPUTE_RETURN_ON_ERROR(validate_and_configure_window(src->clone().get(), dst->clone().get()).first);
 
     return Status{};
 }
 
-void CLWinogradFilterTransformKernel::run(const Window &window, cl::CommandQueue &queue)
+void ClWinogradFilterTransformKernel::run_op(ITensorPack &tensors, const Window &window, cl::CommandQueue &queue)
 {
     ARM_COMPUTE_ERROR_ON_UNCONFIGURED_KERNEL(this);
-    ARM_COMPUTE_ERROR_ON_INVALID_SUBWINDOW(ICLKernel::window(), window);
+    ARM_COMPUTE_ERROR_ON_INVALID_SUBWINDOW(IClKernel::window(), window);
+
+    auto src = utils::cast::polymorphic_downcast<const ICLTensor *>(tensors.get_const_tensor(TensorType::ACL_SRC));
+    auto dst = utils::cast::polymorphic_downcast<ICLTensor *>(tensors.get_tensor(TensorType::ACL_DST));
 
     // Setup output window
     Window window_out;
-    window_out.use_tensor_dimensions(_output->info()->tensor_shape(), 0);
+    window_out.use_tensor_dimensions(dst->info()->tensor_shape(), 0);
 
     unsigned int idx = 0;
-    add_4D_tensor_argument(idx, _input, window);
-    add_3D_tensor_argument(idx, _output, window_out);
+    add_4D_tensor_argument(idx, src, window);
+    add_3D_tensor_argument(idx, dst, window_out);
     enqueue(queue, *this, window, lws_hint());
 }
+} // namespace kernels
+} // namespace opencl
 } // namespace arm_compute
\ No newline at end of file
diff --git a/src/core/gpu/cl/kernels/ClWinogradFilterTransformKernel.h b/src/core/gpu/cl/kernels/ClWinogradFilterTransformKernel.h
new file mode 100644
index 0000000000..2bc2ceb36e
--- /dev/null
+++ b/src/core/gpu/cl/kernels/ClWinogradFilterTransformKernel.h
@@ -0,0 +1,78 @@
+/*
+ * Copyright (c) 2018-2021 Arm Limited.
+ *
+ * SPDX-License-Identifier: MIT
+ *
+ * Permission is hereby granted, free of charge, to any person obtaining a copy
+ * of this software and associated documentation files (the "Software"), to
+ * deal in the Software without restriction, including without limitation the
+ * rights to use, copy, modify, merge, publish, distribute, sublicense, and/or
+ * sell copies of the Software, and to permit persons to whom the Software is
+ * furnished to do so, subject to the following conditions:
+ *
+ * The above copyright notice and this permission notice shall be included in all
+ * copies or substantial portions of the Software.
+ *
+ * THE SOFTWARE IS PROVIDED "AS IS", WITHOUT WARRANTY OF ANY KIND, EXPRESS OR
+ * IMPLIED, INCLUDING BUT NOT LIMITED TO THE WARRANTIES OF MERCHANTABILITY,
+ * FITNESS FOR A PARTICULAR PURPOSE AND NONINFRINGEMENT. IN NO EVENT SHALL THE
+ * AUTHORS OR COPYRIGHT HOLDERS BE LIABLE FOR ANY CLAIM, DAMAGES OR OTHER
+ * LIABILITY, WHETHER IN AN ACTION OF CONTRACT, TORT OR OTHERWISE, ARISING FROM,
+ * OUT OF OR IN CONNECTION WITH THE SOFTWARE OR THE USE OR OTHER DEALINGS IN THE
+ * SOFTWARE.
+ */
+#ifndef ARM_COMPUTE_CL_WINOGRAD_FILTER_TRANSFORM_KERNEL_H
+#define ARM_COMPUTE_CL_WINOGRAD_FILTER_TRANSFORM_KERNEL_H
+
+#include "arm_compute/core/KernelDescriptors.h"
+#include "src/core/common/Macros.h"
+#include "src/core/gpu/cl/ClCompileContext.h"
+#include "src/core/gpu/cl/IClKernel.h"
+
+namespace arm_compute
+{
+namespace opencl
+{
+namespace kernels
+{
+/** Interface for the Winograd filter transform kernel. */
+class ClWinogradFilterTransformKernel : public IClKernel
+{
+public:
+    /** Default constructor */
+    ClWinogradFilterTransformKernel() = default;
+    ARM_COMPUTE_DISALLOW_COPY_ALLOW_MOVE(ClWinogradFilterTransformKernel);
+    /** Set the input and output tensor.
+     *
+     * @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), F(4x1, 5x1), F(1x4, 1x5)
+     *
+     *       Strides: only unit strides
+     *
+     * @param[in]  compile_context The compile context to be used.
+     * @param[in]  src             Source tensor info. 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: F16/F32.
+     * @param[out] dst             The output tensor info. 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
+     * @param[in]  winograd_info   Contains Winograd's information described in @ref WinogradInfo
+     */
+    void configure(const ClCompileContext &compile_context, ITensorInfo *src, ITensorInfo *dst, const WinogradInfo &winograd_info);
+    /** Static function to check if given info will lead to a valid configuration
+     *
+     * Similar to ClWinogradFilterTransformKernel::configure()
+     *
+     * @return a status
+     */
+    static Status validate(const ITensorInfo *src, const ITensorInfo *dst, const WinogradInfo &winograd_info);
+
+    // Inherited methods overridden:
+    void run_op(ITensorPack &tensors, const Window &window, cl::CommandQueue &queue) override;
+};
+} // namespace kernels
+} // namespace opencl
+} // namespace arm_compute
+#endif /*ARM_COMPUTE_CL_WINOGRAD_FILTER_TRANSFORM_KERNEL_H */
diff --git a/src/core/CL/kernels/CLWinogradInputTransformKernel.cpp b/src/core/gpu/cl/kernels/ClWinogradInputTransformKernel.cpp
index 3399f47d5f..17f0eb9e2c 100644
--- a/src/core/CL/kernels/CLWinogradInputTransformKernel.cpp
+++ b/src/core/gpu/cl/kernels/ClWinogradInputTransformKernel.cpp
@@ -21,7 +21,7 @@
  * OUT OF OR IN CONNECTION WITH THE SOFTWARE OR THE USE OR OTHER DEALINGS IN THE
  * SOFTWARE.
  */
-#include "src/core/CL/kernels/CLWinogradInputTransformKernel.h"
+#include "src/core/gpu/cl/kernels/ClWinogradInputTransformKernel.h"
 
 #include "arm_compute/core/CL/CLHelpers.h"
 #include "arm_compute/core/CL/CLKernelLibrary.h"
@@ -36,10 +36,15 @@
 #include "src/core/CL/CLValidate.h"
 #include "src/core/helpers/AutoConfiguration.h"
 #include "src/core/helpers/WindowHelpers.h"
+#include "support/Cast.h"
 #include "support/StringSupport.h"
 
-using namespace arm_compute;
-
+namespace arm_compute
+{
+namespace opencl
+{
+namespace kernels
+{
 namespace
 {
 Status validate_arguments(const ITensorInfo *input, const ITensorInfo *output, const WinogradInfo &winograd_info)
@@ -95,69 +100,62 @@ std::pair<Status, Window> validate_and_configure_window(ITensorInfo *input, ITen
 }
 } // namespace
 
-CLWinogradInputTransformKernel::CLWinogradInputTransformKernel()
-    : _border_size(0), _input(nullptr), _output(nullptr), _data_layout(DataLayout::UNKNOWN), _num_tiles_x(0), _num_tiles_y(0), _step_z(1)
+ClWinogradInputTransformKernel::ClWinogradInputTransformKernel()
+    : _border_size(0), _data_layout(DataLayout::UNKNOWN), _num_tiles_x(0), _num_tiles_y(0), _step_z(1)
 {
 }
 
-BorderSize CLWinogradInputTransformKernel::border_size() const
+BorderSize ClWinogradInputTransformKernel::border_size() const
 {
     return _border_size;
 }
 
-void CLWinogradInputTransformKernel::configure(const ICLTensor *input, ICLTensor *output, const WinogradInfo &winograd_info)
-{
-    configure(CLKernelLibrary::get().get_compile_context(), input, output, winograd_info);
-}
-
-void CLWinogradInputTransformKernel::configure(const CLCompileContext &compile_context, const ICLTensor *input, ICLTensor *output, const WinogradInfo &winograd_info)
+void ClWinogradInputTransformKernel::configure(const ClCompileContext &compile_context, ITensorInfo *src, ITensorInfo *dst, const WinogradInfo &winograd_info)
 {
-    ARM_COMPUTE_ERROR_ON_NULLPTR(input, output);
-    ARM_COMPUTE_ERROR_THROW_ON(validate_arguments(input->info(), output->info(), winograd_info));
+    ARM_COMPUTE_ERROR_ON_NULLPTR(src, dst);
+    ARM_COMPUTE_ERROR_THROW_ON(validate_arguments(src, dst, winograd_info));
 
-    auto padding_info = get_padding_info({ input, output });
+    auto padding_info = get_padding_info({ src, dst });
 
     const PadStrideInfo conv_info        = winograd_info.convolution_info;
     const Size2D        output_tile_size = winograd_info.output_tile_size;
     const Size2D        kernel_size      = winograd_info.kernel_size;
 
-    _data_layout = input->info()->data_layout();
+    _data_layout = src->data_layout();
 
     const size_t idx_w = get_data_layout_dimension_index(_data_layout, DataLayoutDimension::WIDTH);
     const size_t idx_h = get_data_layout_dimension_index(_data_layout, DataLayoutDimension::HEIGHT);
 
     // Compute the number of output tiles along the x and y direction of size "output_tile_size"
-    const Size2D num_tiles = compute_winograd_convolution_tiles(Size2D(input->info()->dimension(idx_w), input->info()->dimension(idx_h)),
+    const Size2D num_tiles = compute_winograd_convolution_tiles(Size2D(src->dimension(idx_w), src->dimension(idx_h)),
                                                                 kernel_size,
                                                                 output_tile_size,
                                                                 conv_info);
 
-    _input       = input;
-    _output      = output;
     _num_tiles_x = num_tiles.width;
     _num_tiles_y = num_tiles.height;
 
-    const TensorShape output_shape = misc::shape_calculator::compute_winograd_input_transform_shape(*input->info(), winograd_info);
+    const TensorShape output_shape = misc::shape_calculator::compute_winograd_input_transform_shape(*src, winograd_info);
 
     // Output auto initialization if not yet initialized
-    auto_init_if_empty(*output->info(), input->info()->clone()->set_tensor_shape(output_shape));
+    auto_init_if_empty(*dst, src->clone()->set_tensor_shape(output_shape));
 
-    ARM_COMPUTE_ERROR_ON(_num_tiles_x * _num_tiles_y != static_cast<int>(output->info()->dimension(1)));
-    const size_t total_batches = input->info()->tensor_shape().total_size_upper(3);
+    ARM_COMPUTE_ERROR_ON(_num_tiles_x * _num_tiles_y != static_cast<int>(dst->dimension(1)));
+    const size_t total_batches = src->tensor_shape().total_size_upper(3);
 
     CLBuildOptions build_opts;
     if(_data_layout == DataLayout::NHWC)
     {
         build_opts.add_option("-DNHWC");
-        build_opts.add_option("-DSRC_WIDTH=" + support::cpp11::to_string(input->info()->dimension(idx_w)));
-        build_opts.add_option("-DSRC_HEIGHT=" + support::cpp11::to_string(input->info()->dimension(idx_h)));
+        build_opts.add_option("-DSRC_WIDTH=" + support::cpp11::to_string(src->dimension(idx_w)));
+        build_opts.add_option("-DSRC_HEIGHT=" + support::cpp11::to_string(src->dimension(idx_h)));
         build_opts.add_option("-DNUM_TILES_X=" + support::cpp11::to_string(_num_tiles_x));
         build_opts.add_option("-DNUM_TILES_Y=" + support::cpp11::to_string(_num_tiles_y));
         build_opts.add_option("-DPAD_LEFT=" + support::cpp11::to_string(conv_info.pad_left()));
         build_opts.add_option("-DPAD_TOP=" + support::cpp11::to_string(conv_info.pad_top()));
         build_opts.add_option("-DOUTPUT_TILE_W=" + support::cpp11::to_string(output_tile_size.width));
         build_opts.add_option("-DOUTPUT_TILE_H=" + support::cpp11::to_string(output_tile_size.height));
-        build_opts.add_option("-DDATA_TYPE=" + get_cl_type_from_data_type(input->info()->data_type()));
+        build_opts.add_option("-DDATA_TYPE=" + get_cl_type_from_data_type(src->data_type()));
         build_opts.add_option_if(winograd_info.kernel_size.height == 1, "-DWINOGRAD_INPUT_TRANSFORM_HORIZONTAL");
         build_opts.add_option_if(winograd_info.kernel_size.width == 1, "-DWINOGRAD_INPUT_TRANSFORM_VERTICAL");
     }
@@ -168,10 +166,10 @@ void CLWinogradInputTransformKernel::configure(const CLCompileContext &compile_c
         build_opts.add_option("-DPAD_TOP=" + support::cpp11::to_string(conv_info.pad_top()));
         build_opts.add_option("-DOUTPUT_TILE_W=" + support::cpp11::to_string(output_tile_size.width));
         build_opts.add_option("-DOUTPUT_TILE_H=" + support::cpp11::to_string(output_tile_size.height));
-        build_opts.add_option("-DDATA_TYPE=" + get_cl_type_from_data_type(input->info()->data_type()));
+        build_opts.add_option("-DDATA_TYPE=" + get_cl_type_from_data_type(src->data_type()));
         build_opts.add_option_if(winograd_info.kernel_size.height == 1, "-DWINOGRAD_INPUT_TRANSFORM_HORIZONTAL");
         build_opts.add_option_if(winograd_info.kernel_size.width == 1, "-DWINOGRAD_INPUT_TRANSFORM_VERTICAL");
-        build_opts.add_option_if(total_batches > 1, "-DSRC_DEPTH=" + support::cpp11::to_string(_input->info()->dimension(2)));
+        build_opts.add_option_if(total_batches > 1, "-DSRC_DEPTH=" + support::cpp11::to_string(src->dimension(2)));
     }
 
     // Create kernel
@@ -183,7 +181,7 @@ void CLWinogradInputTransformKernel::configure(const CLCompileContext &compile_c
     // Check optimized kernel if output_dims == 2x2
     if((tile_max_dim == 2) && (_data_layout == DataLayout::NCHW))
     {
-        _step_z = (_input->info()->dimension(2) % 2) != 0 ? 1 : 2;
+        _step_z = (src->dimension(2) % 2) != 0 ? 1 : 2;
     }
 
     // Append stepz and data layout
@@ -194,20 +192,20 @@ void CLWinogradInputTransformKernel::configure(const CLCompileContext &compile_c
     _kernel = create_kernel(compile_context, kernel_name, build_opts.options());
 
     // Create window and update padding
-    auto win_config = validate_and_configure_window(input->info(), output->info(), winograd_info);
+    auto win_config = validate_and_configure_window(src, dst, winograd_info);
     ARM_COMPUTE_ERROR_THROW_ON(win_config.first);
-    ICLKernel::configure_internal(win_config.second, cl::NDRange(1, 1, 8));
+    IClKernel::configure_internal(win_config.second, cl::NDRange(1, 1, 8));
 
-    _border_size = BorderSize(_input->info()->padding());
+    _border_size = BorderSize(src->padding());
 
-    ARM_COMPUTE_ERROR_ON((input->info()->data_layout() == DataLayout::NHWC) && has_padding_changed(padding_info));
+    ARM_COMPUTE_ERROR_ON((src->data_layout() == DataLayout::NHWC) && has_padding_changed(padding_info));
 
     _config_id = kernel_name;
-    _config_id += support::cpp11::to_string(input->info()->dimension(0));
+    _config_id += support::cpp11::to_string(src->dimension(0));
     _config_id += "_";
-    _config_id += support::cpp11::to_string(input->info()->dimension(1));
+    _config_id += support::cpp11::to_string(src->dimension(1));
     _config_id += "_";
-    _config_id += support::cpp11::to_string(input->info()->dimension(2));
+    _config_id += support::cpp11::to_string(src->dimension(2));
     _config_id += "_";
     _config_id += support::cpp11::to_string(conv_info.pad_left());
     _config_id += "_";
@@ -216,27 +214,29 @@ void CLWinogradInputTransformKernel::configure(const CLCompileContext &compile_c
     _config_id += lower_string(string_from_data_layout(_data_layout));
 }
 
-Status CLWinogradInputTransformKernel::validate(const ITensorInfo *input, const ITensorInfo *output, const WinogradInfo &winograd_info)
+Status ClWinogradInputTransformKernel::validate(const ITensorInfo *src, const ITensorInfo *dst, const WinogradInfo &winograd_info)
 {
-    ARM_COMPUTE_RETURN_ERROR_ON_NULLPTR(input, output);
-    ARM_COMPUTE_RETURN_ON_ERROR(validate_arguments(input, output, winograd_info));
-    ARM_COMPUTE_RETURN_ON_ERROR(validate_and_configure_window(input->clone().get(), output->clone().get(), winograd_info).first);
-
+    ARM_COMPUTE_RETURN_ERROR_ON_NULLPTR(src, dst);
+    ARM_COMPUTE_RETURN_ON_ERROR(validate_arguments(src, dst, winograd_info));
+    ARM_COMPUTE_RETURN_ON_ERROR(validate_and_configure_window(src->clone().get(), dst->clone().get(), winograd_info).first);
     return Status{};
 }
 
-void CLWinogradInputTransformKernel::run(const Window &window, cl::CommandQueue &queue)
+void ClWinogradInputTransformKernel::run_op(ITensorPack &tensors, const Window &window, cl::CommandQueue &queue)
 {
     ARM_COMPUTE_ERROR_ON_UNCONFIGURED_KERNEL(this);
     ARM_COMPUTE_ERROR_ON_INVALID_SUBWINDOW(IKernel::window(), window);
 
+    auto src = utils::cast::polymorphic_downcast<const ICLTensor *>(tensors.get_const_tensor(TensorType::ACL_SRC));
+    auto dst = utils::cast::polymorphic_downcast<ICLTensor *>(tensors.get_tensor(TensorType::ACL_DST));
+
     const size_t idx_w         = get_data_layout_dimension_index(_data_layout, DataLayoutDimension::WIDTH);
     const size_t idx_h         = get_data_layout_dimension_index(_data_layout, DataLayoutDimension::HEIGHT);
     const size_t idx_c         = get_data_layout_dimension_index(_data_layout, DataLayoutDimension::CHANNEL);
     const size_t total_batches = window.shape().total_size_upper(3);
 
     // Collapse window
-    Window window_collapsed = window.collapse_if_possible(ICLKernel::window(), Window::DimZ);
+    Window window_collapsed = window.collapse_if_possible(IClKernel::window(), Window::DimZ);
 
     if(_data_layout == DataLayout::NHWC)
     {
@@ -245,8 +245,8 @@ void CLWinogradInputTransformKernel::run(const Window &window, cl::CommandQueue
         slice.set(2, Window::Dimension(0, total_batches, 1));
 
         unsigned int idx = 0;
-        add_4D_tensor_argument(idx, _input, slice);
-        add_4D_tensor_argument(idx, _output, slice);
+        add_4D_tensor_argument(idx, src, slice);
+        add_4D_tensor_argument(idx, dst, slice);
         enqueue(queue, *this, slice, lws_hint());
     }
     else
@@ -259,17 +259,20 @@ void CLWinogradInputTransformKernel::run(const Window &window, cl::CommandQueue
         slice.set(idx_c, Window::Dimension(slice[idx_c].start(), slice[idx_c].end(), _step_z));
 
         unsigned int idx = 2 * num_arguments_per_3D_tensor();
-        _kernel.setArg<cl_uint>(idx++, static_cast<unsigned int>(_input->info()->strides_in_bytes()[3]));
-        _kernel.setArg<cl_uint>(idx++, static_cast<unsigned int>(_output->info()->strides_in_bytes()[3]));
+        _kernel.setArg<cl_uint>(idx++, static_cast<unsigned int>(src->info()->strides_in_bytes()[3]));
+        _kernel.setArg<cl_uint>(idx++, static_cast<unsigned int>(dst->info()->strides_in_bytes()[3]));
 
         do
         {
             unsigned int idx = 0;
-            add_3D_tensor_argument(idx, _input, slice);
-            add_3D_tensor_argument(idx, _output, slice);
+            add_3D_tensor_argument(idx, src, slice);
+            add_3D_tensor_argument(idx, dst, slice);
 
             enqueue(queue, *this, slice, lws_hint());
         }
         while(window_collapsed.slide_window_slice_3D(slice));
     }
 }
+} // namespace kernels
+} // namespace opencl
+} // namespace arm_compute
\ No newline at end of file
diff --git a/src/core/gpu/cl/kernels/ClWinogradInputTransformKernel.h b/src/core/gpu/cl/kernels/ClWinogradInputTransformKernel.h
new file mode 100644
index 0000000000..76b45279a4
--- /dev/null
+++ b/src/core/gpu/cl/kernels/ClWinogradInputTransformKernel.h
@@ -0,0 +1,88 @@
+/*
+ * Copyright (c) 2018-2021 Arm Limited.
+ *
+ * SPDX-License-Identifier: MIT
+ *
+ * Permission is hereby granted, free of charge, to any person obtaining a copy
+ * of this software and associated documentation files (the "Software"), to
+ * deal in the Software without restriction, including without limitation the
+ * rights to use, copy, modify, merge, publish, distribute, sublicense, and/or
+ * sell copies of the Software, and to permit persons to whom the Software is
+ * furnished to do so, subject to the following conditions:
+ *
+ * The above copyright notice and this permission notice shall be included in all
+ * copies or substantial portions of the Software.
+ *
+ * THE SOFTWARE IS PROVIDED "AS IS", WITHOUT WARRANTY OF ANY KIND, EXPRESS OR
+ * IMPLIED, INCLUDING BUT NOT LIMITED TO THE WARRANTIES OF MERCHANTABILITY,
+ * FITNESS FOR A PARTICULAR PURPOSE AND NONINFRINGEMENT. IN NO EVENT SHALL THE
+ * AUTHORS OR COPYRIGHT HOLDERS BE LIABLE FOR ANY CLAIM, DAMAGES OR OTHER
+ * LIABILITY, WHETHER IN AN ACTION OF CONTRACT, TORT OR OTHERWISE, ARISING FROM,
+ * OUT OF OR IN CONNECTION WITH THE SOFTWARE OR THE USE OR OTHER DEALINGS IN THE
+ * SOFTWARE.
+ */
+#ifndef ARM_COMPUTE_CL_WINOGRAD_INPUT_TRANSFORM_KERNEL_H
+#define ARM_COMPUTE_CL_WINOGRAD_INPUT_TRANSFORM_KERNEL_H
+
+#include "arm_compute/core/KernelDescriptors.h"
+#include "src/core/common/Macros.h"
+#include "src/core/gpu/cl/ClCompileContext.h"
+#include "src/core/gpu/cl/IClKernel.h"
+
+namespace arm_compute
+{
+namespace opencl
+{
+namespace kernels
+{
+/** OpenCL kernel to perform Winograd input transform.*/
+class ClWinogradInputTransformKernel : public IClKernel
+{
+public:
+    /** Default constructor */
+    ClWinogradInputTransformKernel();
+    ARM_COMPUTE_DISALLOW_COPY_ALLOW_MOVE(ClWinogradInputTransformKernel);
+    /** Set the input and output of the kernel.
+     *
+     * @note Winograd input 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 input 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), F(4x1, 5x1), F(1x4, 1x5)
+     *
+     *       Strides: only unit strides
+     *
+     * @param[in] compile_context The compile context to be used.
+     * @param[in] src             The input tensor info to transform. Data types supported: F16/F32
+     * @param[in] dst             The output tensor info. The shape for this tensor can be calculated using the utility function @p compute_winograd_input_transform_shape. Data types supported: Same as @p input
+     * @param[in] winograd_info   Contains Winograd's information described in @ref WinogradInfo.
+     */
+    void configure(const ClCompileContext &compile_context, ITensorInfo *src, ITensorInfo *dst, const WinogradInfo &winograd_info);
+    /** Static function to check if given info will lead to a valid configuration
+     *
+     * Similar to ClWinogradInputTransformKernel::configure()
+     *
+     * @return a status
+     */
+    static Status validate(const ITensorInfo *src, const ITensorInfo *dst, const WinogradInfo &winograd_info);
+
+    // Inherited methods overridden:
+    void run_op(ITensorPack &tensors, const Window &window, cl::CommandQueue &queue) override;
+    BorderSize border_size() const override;
+
+private:
+    using WinogradKey = std::pair<std::pair<int, int>, std::pair<int, int>>;
+
+    BorderSize   _border_size;
+    DataLayout   _data_layout;
+    int          _num_tiles_x;
+    int          _num_tiles_y;
+    unsigned int _step_z;
+};
+} // namespace kernels
+} // namespace opencl
+} // namespace arm_compute
+#endif /*ARM_COMPUTE_CL_WINOGRAD_INPUT_TRANSFORM_KERNEL_H */
diff --git a/src/core/CL/kernels/CLWinogradOutputTransformKernel.cpp b/src/core/gpu/cl/kernels/ClWinogradOutputTransformKernel.cpp
index 965bf9df77..a6c05420ed 100644
--- a/src/core/CL/kernels/CLWinogradOutputTransformKernel.cpp
+++ b/src/core/gpu/cl/kernels/ClWinogradOutputTransformKernel.cpp
@@ -21,7 +21,7 @@
  * OUT OF OR IN CONNECTION WITH THE SOFTWARE OR THE USE OR OTHER DEALINGS IN THE
  * SOFTWARE.
  */
-#include "src/core/CL/kernels/CLWinogradOutputTransformKernel.h"
+#include "src/core/gpu/cl/kernels/ClWinogradOutputTransformKernel.h"
 
 #include "arm_compute/core/CL/CLHelpers.h"
 #include "arm_compute/core/CL/CLKernelLibrary.h"
@@ -38,15 +38,19 @@
 #include "src/core/CL/CLValidate.h"
 #include "src/core/helpers/AutoConfiguration.h"
 #include "src/core/helpers/WindowHelpers.h"
-
+#include "support/Cast.h"
 #include "support/StringSupport.h"
 
 #include <cmath>
 
-namespace arm_compute
-{
 using namespace arm_compute::misc::shape_calculator;
 
+namespace arm_compute
+{
+namespace opencl
+{
+namespace kernels
+{
 namespace
 {
 Status validate_arguments(const ITensorInfo *input, const ITensorInfo *bias, const ITensorInfo *output, const WinogradInfo &winograd_info, const ActivationLayerInfo &act_info)
@@ -118,36 +122,23 @@ std::pair<Status, Window> validate_and_configure_window(ITensorInfo *input, ITen
 }
 } // namespace
 
-CLWinogradOutputTransformKernel::CLWinogradOutputTransformKernel()
-    : _input(nullptr), _bias(nullptr), _output(nullptr), _is_nhwc(false)
-{
-}
-
-void CLWinogradOutputTransformKernel::configure(const ICLTensor *input, const ICLTensor *bias, ICLTensor *output, const WinogradInfo &winograd_info, const ActivationLayerInfo &act_info)
-{
-    configure(CLKernelLibrary::get().get_compile_context(), input, bias, output, winograd_info, act_info);
-}
-
-void CLWinogradOutputTransformKernel::configure(const CLCompileContext &compile_context, const ICLTensor *input, const ICLTensor *bias, ICLTensor *output, const WinogradInfo &winograd_info,
+void ClWinogradOutputTransformKernel::configure(const ClCompileContext &compile_context, ITensorInfo *src, ITensorInfo *bias, ITensorInfo *dst, const WinogradInfo &winograd_info,
                                                 const ActivationLayerInfo &act_info)
 {
-    ARM_COMPUTE_ERROR_ON_NULLPTR(input, output);
+    ARM_COMPUTE_ERROR_ON_NULLPTR(src, dst);
 
     // Output tensor auto initialization if not yet initialized
-    auto_init_if_empty(*output->info(), input->info()->clone()->set_tensor_shape(compute_winograd_output_transform_shape(*input->info(), winograd_info)));
+    auto_init_if_empty(*dst, src->clone()->set_tensor_shape(compute_winograd_output_transform_shape(*src, winograd_info)));
 
-    ARM_COMPUTE_ERROR_THROW_ON(validate_arguments(input->info(), (bias != nullptr ? bias->info() : nullptr), output->info(), winograd_info, act_info));
+    ARM_COMPUTE_ERROR_THROW_ON(validate_arguments(src, bias, dst, winograd_info, act_info));
 
     // Configure kernel window
-    auto win_config = validate_and_configure_window(input->info(), (bias != nullptr ? bias->info() : nullptr), output->info(), winograd_info.output_tile_size);
+    auto win_config = validate_and_configure_window(src, bias, dst, winograd_info.output_tile_size);
     ARM_COMPUTE_ERROR_THROW_ON(win_config.first);
-    ICLKernel::configure_internal(win_config.second);
+    IClKernel::configure_internal(win_config.second);
 
-    auto padding_info = get_padding_info({ input, bias, output });
+    auto padding_info = get_padding_info({ src, bias, dst });
 
-    _input   = input;
-    _bias    = bias;
-    _output  = output;
     _is_nhwc = winograd_info.output_data_layout == DataLayout::NHWC;
 
     // Compute num_tiles_x
@@ -163,7 +154,7 @@ void CLWinogradOutputTransformKernel::configure(const CLCompileContext &compile_
                                                                 kernel_size,
                                                                 output_tile_size,
                                                                 conv_info);
-    const size_t total_batches = output->info()->tensor_shape().total_size_upper(3);
+    const size_t total_batches = dst->tensor_shape().total_size_upper(3);
 
     // Set build options
     CLBuildOptions build_opts;
@@ -180,17 +171,17 @@ void CLWinogradOutputTransformKernel::configure(const CLCompileContext &compile_
         build_opts.add_option("-DVEC_SIZE=4");
     }
 
-    build_opts.add_option_if(_bias != nullptr, std::string("-DHAS_BIAS"));
+    build_opts.add_option_if(bias != nullptr, std::string("-DHAS_BIAS"));
     build_opts.add_option("-cl-fast-relaxed-math");
     build_opts.add_option("-DN0=" + support::cpp11::to_string(win_config.second.x().step()));
     build_opts.add_option("-DNUM_TILES_X=" + support::cpp11::to_string(num_tiles.width));
     build_opts.add_option("-DOUTPUT_TILE_W=" + support::cpp11::to_string(output_tile_size.width));
     build_opts.add_option("-DOUTPUT_TILE_H=" + support::cpp11::to_string(output_tile_size.height));
-    build_opts.add_option("-DDATA_TYPE=" + get_cl_type_from_data_type(input->info()->data_type()));
-    build_opts.add_option("-DSRC_HEIGHT=" + support::cpp11::to_string(_input->info()->dimension(1)));
-    build_opts.add_option("-DDST_WIDTH=" + support::cpp11::to_string(_output->info()->dimension(idx_width)));
-    build_opts.add_option("-DDST_HEIGHT=" + support::cpp11::to_string(_output->info()->dimension(idx_height)));
-    build_opts.add_option_if(total_batches > 1, "-DSRC_DEPTH=" + support::cpp11::to_string(_input->info()->dimension(2)));
+    build_opts.add_option("-DDATA_TYPE=" + get_cl_type_from_data_type(src->data_type()));
+    build_opts.add_option("-DSRC_HEIGHT=" + support::cpp11::to_string(src->dimension(1)));
+    build_opts.add_option("-DDST_WIDTH=" + support::cpp11::to_string(dst->dimension(idx_width)));
+    build_opts.add_option("-DDST_HEIGHT=" + support::cpp11::to_string(dst->dimension(idx_height)));
+    build_opts.add_option_if(total_batches > 1, "-DSRC_DEPTH=" + support::cpp11::to_string(src->dimension(2)));
     build_opts.add_option_if(winograd_info.kernel_size.height == 1, "-DWINOGRAD_OUTPUT_TRANSFORM_HORIZONTAL");
     build_opts.add_option_if(winograd_info.kernel_size.width == 1, "-DWINOGRAD_OUTPUT_TRANSFORM_VERTICAL");
 
@@ -201,36 +192,39 @@ void CLWinogradOutputTransformKernel::configure(const CLCompileContext &compile_
     // Set config_id for enabling LWS tuning
     _config_id = kernel_name;
     _config_id += "_";
-    _config_id += lower_string(string_from_data_type(input->info()->data_type()));
+    _config_id += lower_string(string_from_data_type(src->data_type()));
     _config_id += "_";
-    _config_id += support::cpp11::to_string(input->info()->dimension(0));
+    _config_id += support::cpp11::to_string(src->dimension(0));
     _config_id += "_";
-    _config_id += support::cpp11::to_string(input->info()->dimension(1));
+    _config_id += support::cpp11::to_string(src->dimension(1));
     _config_id += "_";
-    _config_id += support::cpp11::to_string(output->info()->dimension(0));
+    _config_id += support::cpp11::to_string(dst->dimension(0));
     _config_id += "_";
-    _config_id += support::cpp11::to_string(output->info()->dimension(1));
+    _config_id += support::cpp11::to_string(dst->dimension(1));
     _config_id += "_";
     _config_id += lower_string(string_from_data_layout(winograd_info.output_data_layout));
 
     ARM_COMPUTE_ERROR_ON(has_padding_changed(padding_info) && _is_nhwc);
 }
 
-Status CLWinogradOutputTransformKernel::validate(const ITensorInfo *input, const ITensorInfo *bias, const ITensorInfo *output, const WinogradInfo &winograd_info, const ActivationLayerInfo &act_info)
+Status ClWinogradOutputTransformKernel::validate(const ITensorInfo *src, const ITensorInfo *bias, const ITensorInfo *dst, const WinogradInfo &winograd_info, const ActivationLayerInfo &act_info)
 {
-    ARM_COMPUTE_RETURN_ON_ERROR(validate_arguments(input, (bias != nullptr ? bias->clone().get() : nullptr), output, winograd_info, act_info));
-    ARM_COMPUTE_RETURN_ON_ERROR(validate_and_configure_window(input->clone().get(), (bias != nullptr ? bias->clone().get() : nullptr), output->clone().get(), winograd_info.output_tile_size).first);
-
+    ARM_COMPUTE_RETURN_ON_ERROR(validate_arguments(src, (bias != nullptr ? bias->clone().get() : nullptr), dst, winograd_info, act_info));
+    ARM_COMPUTE_RETURN_ON_ERROR(validate_and_configure_window(src->clone().get(), (bias != nullptr ? bias->clone().get() : nullptr), dst->clone().get(), winograd_info.output_tile_size).first);
     return Status{};
 }
 
-void CLWinogradOutputTransformKernel::run(const Window &window, cl::CommandQueue &queue)
+void ClWinogradOutputTransformKernel::run_op(ITensorPack &tensors, const Window &window, cl::CommandQueue &queue)
 {
     ARM_COMPUTE_ERROR_ON_UNCONFIGURED_KERNEL(this);
-    ARM_COMPUTE_ERROR_ON_INVALID_SUBWINDOW(ICLKernel::window(), window);
+    ARM_COMPUTE_ERROR_ON_INVALID_SUBWINDOW(IClKernel::window(), window);
+
+    auto src  = utils::cast::polymorphic_downcast<const ICLTensor *>(tensors.get_const_tensor(TensorType::ACL_SRC_0));
+    auto bias = utils::cast::polymorphic_downcast<const ICLTensor *>(tensors.get_const_tensor(TensorType::ACL_SRC_1));
+    auto dst  = utils::cast::polymorphic_downcast<ICLTensor *>(tensors.get_tensor(TensorType::ACL_DST));
 
     // Collapse window
-    Window window_collapsed = window.collapse_if_possible(ICLKernel::window(), Window::DimZ);
+    Window window_collapsed = window.collapse_if_possible(IClKernel::window(), Window::DimZ);
 
     // Get initial windows
     Window slice = window_collapsed.first_slice_window_4D();
@@ -241,27 +235,29 @@ void CLWinogradOutputTransformKernel::run(const Window &window, cl::CommandQueue
     slice_out.set(Window::DimX, Window::Dimension(0, 0, 0));
     slice_out.set(Window::DimY, Window::Dimension(0, 0, 0));
 
-    if(_bias != nullptr)
+    if(bias != nullptr)
     {
         unsigned int idx1 = 2 * num_arguments_per_4D_tensor();
         Window       slice_biases;
-        slice_biases.use_tensor_dimensions(_bias->info()->tensor_shape());
-        add_1D_tensor_argument(idx1, _bias, slice_biases);
+        slice_biases.use_tensor_dimensions(bias->info()->tensor_shape());
+        add_1D_tensor_argument(idx1, bias, slice_biases);
     }
 
     if(_is_nhwc)
     {
-        unsigned int idx2 = 2 * num_arguments_per_4D_tensor() + ((_bias != nullptr) ? num_arguments_per_1D_tensor() : 0);
-        _kernel.setArg(idx2, static_cast<int>(_output->info()->total_size() - _output->info()->strides_in_bytes().y()));
+        unsigned int idx2 = 2 * num_arguments_per_4D_tensor() + ((bias != nullptr) ? num_arguments_per_1D_tensor() : 0);
+        _kernel.setArg(idx2, static_cast<int>(dst->info()->total_size() - dst->info()->strides_in_bytes().y()));
     }
 
     do
     {
         unsigned int idx = 0;
-        add_4D_tensor_argument(idx, _input, slice);
-        add_4D_tensor_argument(idx, _output, slice_out);
+        add_4D_tensor_argument(idx, src, slice);
+        add_4D_tensor_argument(idx, dst, slice_out);
         enqueue(queue, *this, slice, lws_hint());
     }
     while(window.slide_window_slice_3D(slice) && window.slide_window_slice_3D(slice_out));
 }
+} // namespace kernels
+} // namespace opencl
 } // namespace arm_compute
diff --git a/src/core/gpu/cl/kernels/ClWinogradOutputTransformKernel.h b/src/core/gpu/cl/kernels/ClWinogradOutputTransformKernel.h
new file mode 100644
index 0000000000..48b27e658c
--- /dev/null
+++ b/src/core/gpu/cl/kernels/ClWinogradOutputTransformKernel.h
@@ -0,0 +1,87 @@
+/*
+ * Copyright (c) 2018-2021 Arm Limited.
+ *
+ * SPDX-License-Identifier: MIT
+ *
+ * Permission is hereby granted, free of charge, to any person obtaining a copy
+ * of this software and associated documentation files (the "Software"), to
+ * deal in the Software without restriction, including without limitation the
+ * rights to use, copy, modify, merge, publish, distribute, sublicense, and/or
+ * sell copies of the Software, and to permit persons to whom the Software is
+ * furnished to do so, subject to the following conditions:
+ *
+ * The above copyright notice and this permission notice shall be included in all
+ * copies or substantial portions of the Software.
+ *
+ * THE SOFTWARE IS PROVIDED "AS IS", WITHOUT WARRANTY OF ANY KIND, EXPRESS OR
+ * IMPLIED, INCLUDING BUT NOT LIMITED TO THE WARRANTIES OF MERCHANTABILITY,
+ * FITNESS FOR A PARTICULAR PURPOSE AND NONINFRINGEMENT. IN NO EVENT SHALL THE
+ * AUTHORS OR COPYRIGHT HOLDERS BE LIABLE FOR ANY CLAIM, DAMAGES OR OTHER
+ * LIABILITY, WHETHER IN AN ACTION OF CONTRACT, TORT OR OTHERWISE, ARISING FROM,
+ * OUT OF OR IN CONNECTION WITH THE SOFTWARE OR THE USE OR OTHER DEALINGS IN THE
+ * SOFTWARE.
+ */
+#ifndef ARM_COMPUTE_CL_WINOGRAD_OUTPUT_TRANSFORM_KERNEL_H
+#define ARM_COMPUTE_CL_WINOGRAD_OUTPUT_TRANSFORM_KERNEL_H
+
+#include "arm_compute/core/KernelDescriptors.h"
+#include "src/core/common/Macros.h"
+#include "src/core/gpu/cl/ClCompileContext.h"
+#include "src/core/gpu/cl/IClKernel.h"
+
+namespace arm_compute
+{
+namespace opencl
+{
+namespace kernels
+{
+/** Interface for the Winograd output transform kernel. */
+class ClWinogradOutputTransformKernel : public IClKernel
+{
+public:
+    /** Default constructor */
+    ClWinogradOutputTransformKernel() = default;
+    ARM_COMPUTE_DISALLOW_COPY_ALLOW_MOVE(ClWinogradOutputTransformKernel);
+    /** Set the input and output tensor.
+     *
+     * @note Winograd output 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 output 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), F(4x1, 5x1), F(1x4, 1x5)
+     *
+     *       Strides: only unit strides
+     *
+     * @param[in]  compile_context The compile context to be used.
+     * @param[in]  src             Source tensor info with shape [C, N, K, batches]. Data types supported: F16/F32.
+     * @param[in]  bias            Biases tensor info. Shared biases supported. Biases are 1D tensor with dimensions [OFM]. It can be a nullptr. Data type supported: as @p src
+     * @param[out] dst             The output tensor info. The shape for this tensor can be calculated using the utility function @p compute_winograd_output_transform_shape. Data types supported: Same as @p src
+     * @param[in]  winograd_info   Contains Winograd's information described in @ref WinogradInfo
+     * @param[in]  act_info        (Optional) Activation layer information in case of a fused activation.
+     */
+    void configure(const ClCompileContext &compile_context, ITensorInfo *src, ITensorInfo *bias, ITensorInfo *dst, const WinogradInfo &winograd_info,
+                   const ActivationLayerInfo &act_info = ActivationLayerInfo());
+
+    /** Static function to check if given info will lead to a valid configuration
+     *
+     * Similar to ClWinogradOutputTransformKernel::configure()
+     *
+     * @return a status
+     */
+    static Status validate(const ITensorInfo *src, const ITensorInfo *bias, const ITensorInfo *dst, const WinogradInfo &winograd_info, const ActivationLayerInfo &act_info = ActivationLayerInfo());
+
+    // Inherited methods overridden:
+    void run_op(ITensorPack &tensors, const Window &window, cl::CommandQueue &queue) override;
+
+private:
+    using WinogradKey = std::pair<std::pair<int, int>, std::pair<int, int>>;
+
+    bool _is_nhwc{ false };
+};
+} // namespace kernels
+} // namespace opencl
+} // namespace arm_compute
+#endif /*ARM_COMPUTE_CL_WINOGRAD_OUTPUT_TRANSFORM_KERNEL_H */