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authorIsabella Gottardi <isabella.gottardi@arm.com>2018-02-06 14:52:43 +0000
committerAnthony Barbier <anthony.barbier@arm.com>2018-11-02 16:47:18 +0000
commitf07d28d9ee8ae73a93fe433f72855b6dcf58ad90 (patch)
tree6ad19c89540f36e1ba5c6af7ff061bee773c43d6 /arm_compute/runtime/CL/functions/CLGEMMConvolutionLayer.h
parent21f67d6763c82d78278f6bca6c6f9e42bb5ee1b9 (diff)
downloadComputeLibrary-f07d28d9ee8ae73a93fe433f72855b6dcf58ad90.tar.gz
COMPMID-845: Create a ConvolutionLayer for CL
Change-Id: Ifcc406d2d0a99c911d6b6c875657b0e0028255d5 Reviewed-on: https://eu-gerrit-1.euhpc.arm.com/119148 Tested-by: Jenkins <bsgcomp@arm.com> Reviewed-by: Anthony Barbier <anthony.barbier@arm.com> Reviewed-by: Georgios Pinitas <georgios.pinitas@arm.com>
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+/*
+ * Copyright (c) 2017-2018 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_CLGEMMCONVOLUTIONLAYER_H__
+#define __ARM_COMPUTE_CLGEMMCONVOLUTIONLAYER_H__
+
+#include "arm_compute/runtime/IFunction.h"
+
+#include "arm_compute/core/CL/kernels/CLCol2ImKernel.h"
+#include "arm_compute/core/CL/kernels/CLFillBorderKernel.h"
+#include "arm_compute/core/CL/kernels/CLGEMMInterleave4x4Kernel.h"
+#include "arm_compute/core/CL/kernels/CLGEMMMatrixMultiplyKernel.h"
+#include "arm_compute/core/CL/kernels/CLGEMMTranspose1xWKernel.h"
+#include "arm_compute/core/CL/kernels/CLIm2ColKernel.h"
+#include "arm_compute/core/CL/kernels/CLWeightsReshapeKernel.h"
+#include "arm_compute/core/Types.h"
+#include "arm_compute/runtime/CL/CLMemoryGroup.h"
+#include "arm_compute/runtime/CL/CLTensor.h"
+#include "arm_compute/runtime/CL/functions/CLGEMM.h"
+#include "arm_compute/runtime/CL/functions/CLGEMMLowpMatrixMultiplyCore.h"
+#include "arm_compute/runtime/CL/functions/CLGEMMLowpOutputStage.h"
+#include "arm_compute/runtime/IMemoryManager.h"
+
+#include <memory>
+
+namespace arm_compute
+{
+class ICLTensor;
+
+/** Function to reshape and transpose the weights. This function calls the following kernels:
+ * -# @ref CLWeightsReshapeKernel
+ * -# @ref CLGEMMTranspose1xWKernel
+ */
+class CLConvolutionLayerReshapeWeights : public IFunction
+{
+public:
+ /** Constructor */
+ CLConvolutionLayerReshapeWeights(std::shared_ptr<IMemoryManager> memory_manager = nullptr);
+ /** Set the input and output tensors.
+ *
+ * @param[in] weights Weights tensor. Weights are 4D tensor with dimensions [kernel_x, kernel_y, IFM, OFM].
+ * Data type supported: QS8/QASYMM8/QS16/F16/F32.
+ * @param[in] biases Biases tensor. Shared biases supported. Biases are 1D tensor with dimensions [OFM]. Data type supported: Same as @p weights.
+ * @param[out] output Destination tensor. Data types supported: Same as @p weights.
+ * @param[in] transpose1xW True if the weights are to undergo a 1xW transposition after reshaping (in case of GEMM operation), false otherwise.
+ * Data types supported: Same as @p weights.
+ */
+ void configure(const ICLTensor *weights, const ICLTensor *biases, ICLTensor *output, bool transpose1xW);
+ // Inherited methods overridden:
+ void run() override;
+
+private:
+ CLMemoryGroup _memory_group;
+ CLWeightsReshapeKernel _weights_reshape_kernel;
+ CLGEMMTranspose1xWKernel _weights_transposed_kernel;
+ CLTensor _weights_reshaped;
+ bool _transpose1xW;
+};
+
+/** Basic function to compute the convolution layer. This function calls the following OpenCL kernels/functions:
+ *
+ * Note: weights already reshaped for quantized asymmetric is not supported
+ *
+ * -# @ref CLIm2ColKernel
+ * -# @ref CLGEMMLowpMatrixMultiplyCore (if quantized asymmetric)
+ * -# @ref CLGEMMLowpQuantizeDownInt32ToUint8Scale (if quantized asymmetric)
+ * -# @ref CLCol2ImKernel
+ *
+ * if the weights are already reshaped:
+ * -# @ref CLGEMMInterleave4x4Kernel
+ * -# @ref CLGEMMMatrixMultiplyKernel
+ * else
+ * -# @ref CLGEMM
+ */
+class CLGEMMConvolutionLayer : public IFunction
+{
+public:
+ /** Default constructor */
+ CLGEMMConvolutionLayer(std::shared_ptr<IMemoryManager> memory_manager = nullptr);
+ /** Set the input and output tensors.
+ *
+ * @param[in] input Source tensor. 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: QS8/QASYMM8/QS16/F16/F32.
+ * @param[in] weights Weights tensor. Weights are 4D tensor with dimensions [kernel_x, kernel_y, IFM, OFM]. Data type supported: Same as @p input.
+ * @param[in] biases Biases tensor. Shared biases supported. Biases are 1D tensor with dimensions [OFM].
+ * Data type supported: Should match @p input data type, except for input of QASYMM8 type where biases should be of S32 type.
+ * @param[out] output Destination tensor. 3 lower dimensions represent a single output [width, height, OFM], while the rest represent batch of outputs.
+ * Data types supported: Same as @p input.
+ * @param[in] conv_info Contains padding and stride information described in @ref PadStrideInfo.
+ * @param[in] weights_info Specifies if the weights tensor has been reshaped with CLWeightsReshapeKernel. If this is not part of the fully connected layer the weights
+ * tensor has also been transposed with CLGEMMTranspose1xWKernel. Data type supported: Same as @p input.
+ */
+ void configure(const ICLTensor *input, const ICLTensor *weights, const ICLTensor *biases, ICLTensor *output, const PadStrideInfo &conv_info, const WeightsInfo &weights_info = WeightsInfo());
+
+ // Inherited methods overridden:
+ void run() override;
+
+private:
+ /** Configures the appropriate matrix multiply routine
+ *
+ * @param input Input tensor. Data types supported: QS8/QASYMM8/QS16/F16/F32.
+ * @param weights Weights tensor. Data type supported: Same as @p input.
+ * @param output Output tensor. Data types supported: Same as @p input,
+ * except for input of QASYMM8 type where output should be of S32 type.
+ * @param is_interleaved_transposed Flag that signals if matrix is interleaved transposed
+ */
+ void configure_mm(const ICLTensor *input, const ICLTensor *weights, ICLTensor *output, bool is_interleaved_transposed, bool are_weights_reshaped);
+
+private:
+ CLMemoryGroup _memory_group;
+ CLConvolutionLayerReshapeWeights _reshape_weights;
+ CLIm2ColKernel _im2col_kernel;
+ CLGEMMInterleave4x4Kernel _interleave_kernel;
+ CLGEMMMatrixMultiplyKernel _mm_kernel;
+ CLGEMM _mm_gemm;
+ CLGEMMLowpMatrixMultiplyCore _mm_gemmlowp;
+ CLGEMMLowpQuantizeDownInt32ToUint8ScaleByFixedPoint _gemmlowp_output_stage;
+ CLCol2ImKernel _col2im_kernel;
+
+ CLTensor _im2col_output;
+ CLTensor _interleave_output;
+ CLTensor _weights_reshaped;
+ CLTensor _weights_transposed;
+ CLTensor _gemm_output;
+ CLTensor _tmp_output;
+
+ bool _are_weights_reshaped;
+ bool _is_quantized;
+ bool _is_interleaved_transposed;
+};
+}
+#endif /* __ARM_COMPUTE_CLGEMMCONVOLUTIONLAYER_H__ */