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+/*
+ * 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_WINOGRADCONV2D_H
+#define ARM_COMPUTE_CL_WINOGRADCONV2D_H
+
+#include "arm_compute/runtime/CL/CLTensor.h"
+
+#include "src/core/CL/kernels/CLFillBorderKernel.h"
+#include "src/gpu/cl/ClCompileContext.h"
+#include "src/gpu/cl/IClOperator.h"
+#include "src/gpu/cl/operators/ClGemm.h"
+
+namespace arm_compute
+{
+class CLCompileContext;
+class ITensorInfo;
+namespace opencl
+{
+namespace kernels
+{
+class ClWinogradInputTransformKernel;
+class ClWinogradFilterTransformKernel;
+class ClWinogradOutputTransformKernel;
+} // namespace kernels
+/** Basic function to execute Winograd-based convolution on OpenCL. This function calls the following OpenCL functions/kernels:
+ *
+ * -# @ref kernels::ClWinogradInputTransformKernel
+ * -# @ref kernels::ClWinogradFilterTransformKernel (only once)
+ * -# @ref ClGemm
+ * -# @ref kernels::ClWinogradOutputTransformKernel
+ *
+ */
+class ClWinogradConv2d : public IClOperator
+{
+public:
+ /** Default constructor */
+ ClWinogradConv2d();
+ /** Default destructor */
+ ~ClWinogradConv2d();
+ /** Prevent instances of this class from being copied (As this class contains pointers) */
+ ClWinogradConv2d(const ClWinogradConv2d &) = delete;
+ /** Default move constructor */
+ ClWinogradConv2d(ClWinogradConv2d &&) = default;
+ /** Prevent instances of this class from being copied (As this class contains pointers) */
+ ClWinogradConv2d &operator=(const ClWinogradConv2d &) = delete;
+ /** Default move assignment operator */
+ ClWinogradConv2d &operator=(ClWinogradConv2d &&) = default;
+ /** Set the input and output tensors.
+ *
+ * Valid data layouts:
+ * - NHWC
+ * - NCHW
+ *
+ * Valid data type configurations:
+ * |src0 |src1 |src2 |dst |
+ * |:--------------|:--------------|:------|:--------------|
+ * |F16 |F16 |F16 |F16 |
+ * |F32 |F32 |F32 |F32 |
+ *
+ * @note: This function only works with 3x3,3x1,1x3,5x5,5x1,1x5,7x1 and 1x7 kernels along with unit strides for both NCHW and NHWC data layout
+ * @note Some Winograd configurations (i.e. F(4x4, 5x5)) are supported only with enable_fast_math = true
+ *
+ * @param[in] compile_context The compile context to be used.
+ * @param[in] src Source tensor info. 3 lower dimensions represent a single input [width, height, IFM],
+ * while every optional dimension from 4 and above represent a batch of inputs.
+ * Data types supported: F16/F32.
+ * @param[in] weights Weights tensor info. Weights are 4D tensor with dimensions [kernel_x, kernel_y, IFM, OFM]. Data type supported:Same as @p src.
+ * @param[in] biases Biases tensor info. Shared biases supported. Biases are 1D tensor with dimensions [OFM].Data type supported: Same as @p src
+ * @param[out] dst Destination tensor info. 3 lower dimensions represent a single output [width, height, OFM], while the rest represent batch of outputs.
+ * Data types supported: Same as @p src.
+ * @param[in] conv_info Contains padding and stride information described in @ref PadStrideInfo.
+ * @param[in] act_info (Optional) Activation layer information in case of a fused activation.
+ * @param[in] enable_fast_math (Optional) Enable fast math computation. In case this flag were set, the function could dispatch the fastest implementation
+ * available which may introduce a drop of accuracy as well. Default is false
+ */
+ void configure(const ClCompileContext &compile_context,
+ ITensorInfo *src,
+ ITensorInfo *weights,
+ ITensorInfo *biases,
+ ITensorInfo *dst,
+ const PadStrideInfo &conv_info,
+ const ActivationLayerInfo &act_info = ActivationLayerInfo(),
+ bool enable_fast_math = false);
+ /** Static function to check if given info will lead to a valid configuration
+ *
+ * Similar to ClWinogradConv2d::configure()
+ *
+ * @return a status
+ */
+ static Status validate(const ITensorInfo *src,
+ const ITensorInfo *weights,
+ const ITensorInfo *biases,
+ const ITensorInfo *dst,
+ const PadStrideInfo &conv_info,
+ const ActivationLayerInfo &act_info = ActivationLayerInfo(),
+ bool enable_fast_math = false);
+
+ // Inherited method overridden
+ void run(ITensorPack &tensors) override;
+ void prepare(ITensorPack &tensors) override;
+ experimental::MemoryRequirements workspace() const override;
+
+private:
+ ClGemm _batched_mm;
+ std::unique_ptr<kernels::ClWinogradInputTransformKernel> _input_transform;
+ std::unique_ptr<kernels::ClWinogradFilterTransformKernel> _filter_transform;
+ std::unique_ptr<kernels::ClWinogradOutputTransformKernel> _output_transform;
+ CLFillBorderKernel _border_handler;
+ TensorInfo _input0;
+ TensorInfo _input1;
+ TensorInfo _batched_mm_output;
+ bool _is_prepared;
+ experimental::MemoryRequirements _aux_mem{};
+};
+} // namespace opencl
+} // namespace arm_compute
+#endif /* ARM_COMPUTE_CL_WINOGRADCONV2D_H */