COMPMID-935 - Implementing Convolution with Winograd on OpenCL (part 4)
Implemented Winograd Output Transform (2x2,3x3) on OpenCL
Implemented CLWinogradConvolutionLayer on OpenCL
Change-Id: I6a113fc5f052ca07f878d2b800d2ab003f84af65
Reviewed-on: https://eu-gerrit-1.euhpc.arm.com/125148
Reviewed-by: Georgios Pinitas <georgios.pinitas@arm.com>
Tested-by: Jenkins <bsgcomp@arm.com>
diff --git a/arm_compute/core/CL/CLKernels.h b/arm_compute/core/CL/CLKernels.h
index ef629c2..6f5c615 100644
--- a/arm_compute/core/CL/CLKernels.h
+++ b/arm_compute/core/CL/CLKernels.h
@@ -111,5 +111,6 @@
#include "arm_compute/core/CL/kernels/CLWeightsReshapeKernel.h"
#include "arm_compute/core/CL/kernels/CLWinogradFilterTransformKernel.h"
#include "arm_compute/core/CL/kernels/CLWinogradInputTransformKernel.h"
+#include "arm_compute/core/CL/kernels/CLWinogradOutputTransformKernel.h"
#endif /* __ARM_COMPUTE_CLKERNELS_H__ */
diff --git a/arm_compute/core/CL/kernels/CLGEMMMatrixMultiplyKernel.h b/arm_compute/core/CL/kernels/CLGEMMMatrixMultiplyKernel.h
index 7260c4a..ee7e7c0 100644
--- a/arm_compute/core/CL/kernels/CLGEMMMatrixMultiplyKernel.h
+++ b/arm_compute/core/CL/kernels/CLGEMMMatrixMultiplyKernel.h
@@ -84,6 +84,7 @@
const ICLTensor *_input0;
const ICLTensor *_input1;
ICLTensor *_output;
+ bool _slide_matrix_b;
};
} // namespace arm_compute
#endif /* __ARM_COMPUTE_CLGEMMMATRIXMULTIPLYKERNEL_H__ */
diff --git a/arm_compute/core/CL/kernels/CLWinogradOutputTransformKernel.h b/arm_compute/core/CL/kernels/CLWinogradOutputTransformKernel.h
new file mode 100644
index 0000000..35117c6
--- /dev/null
+++ b/arm_compute/core/CL/kernels/CLWinogradOutputTransformKernel.h
@@ -0,0 +1,81 @@
+/*
+ * Copyright (c) 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_CLWINOGRADOUTPUTTRANSFORMKERNEL_H__
+#define __ARM_COMPUTE_CLWINOGRADOUTPUTTRANSFORMKERNEL_H__
+
+#include "arm_compute/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.
+ *
+ * @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
+ */
+ void configure(const ICLTensor *input, const ICLTensor *bias, ICLTensor *output, const Size2D &kernel_dims, const Size2D &output_convolved_dims, const Size2D &num_tiles);
+ /** 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
+ *
+ * @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);
+
+ // Inherited methods overridden:
+ void run(const Window &window, cl::CommandQueue &queue) override;
+
+private:
+ const ICLTensor *_input;
+ const ICLTensor *_bias;
+ ICLTensor *_output;
+};
+} // namespace arm_compute
+#endif /*__ARM_COMPUTE_CLWINOGRADOUTPUTTRANSFORMKERNEL_H__ */
diff --git a/arm_compute/core/utils/misc/ShapeCalculator.h b/arm_compute/core/utils/misc/ShapeCalculator.h
index 1e90927..5344ce7 100644
--- a/arm_compute/core/utils/misc/ShapeCalculator.h
+++ b/arm_compute/core/utils/misc/ShapeCalculator.h
@@ -28,6 +28,8 @@
#include "arm_compute/core/ITensorInfo.h"
#include "arm_compute/core/Utils.h"
+#include <cmath>
+
namespace arm_compute
{
namespace misc
@@ -233,19 +235,45 @@
return output_shape;
}
+
+inline TensorShape compute_winograd_output_transform_shape(const ITensorInfo &input, const Size2D &output_convolved_dims, DataLayout data_layout)
+{
+ TensorShape tensor_shape{ input.tensor_shape() };
+
+ // Output dimension
+ const unsigned int out_w = output_convolved_dims.width;
+ const unsigned int out_h = output_convolved_dims.height;
+ const unsigned int out_c = input.dimension(0);
+
+ tensor_shape.set(get_data_layout_dimension_index(data_layout, DataLayoutDimension::WIDTH), out_w);
+ tensor_shape.set(get_data_layout_dimension_index(data_layout, DataLayoutDimension::HEIGHT), out_h);
+ tensor_shape.set(get_data_layout_dimension_index(data_layout, DataLayoutDimension::CHANNEL), out_c);
+
+ return tensor_shape;
+}
+
inline TensorShape compute_deep_convolution_shape(const ITensorInfo &input, const ITensorInfo &weights, PadStrideInfo conv_info)
{
const TensorShape input_shape{ input.tensor_shape() };
const TensorShape weights_shape{ weights.tensor_shape() };
- unsigned int output_width = 0;
- unsigned int output_height = 0;
- std::tie(output_width, output_height) = scaled_dimensions(input_shape.x(), input_shape.y(), weights_shape.x(), weights_shape.y(), conv_info);
+ const size_t idx_width = get_data_layout_dimension_index(input.data_layout(), DataLayoutDimension::WIDTH);
+ const size_t idx_height = get_data_layout_dimension_index(input.data_layout(), DataLayoutDimension::HEIGHT);
+ const size_t idx_channel = get_data_layout_dimension_index(input.data_layout(), DataLayoutDimension::CHANNEL);
+
+ const unsigned int input_width = input_shape[idx_width];
+ const unsigned int input_height = input_shape[idx_height];
+ const unsigned int weights_width = weights_shape[idx_width];
+ const unsigned int weights_height = weights_shape[idx_height];
+ const unsigned int weights_channel = weights_shape[idx_channel];
+ unsigned int output_width = 0;
+ unsigned int output_height = 0;
+ std::tie(output_width, output_height) = scaled_dimensions(input_width, input_height, weights_width, weights_height, conv_info);
TensorShape output_shape{ input_shape };
- output_shape.set(0, output_width);
- output_shape.set(1, output_height);
- output_shape.set(2, weights_shape[3]);
+ output_shape.set(idx_width, output_width);
+ output_shape.set(idx_height, output_height);
+ output_shape.set(idx_channel, weights_channel);
return output_shape;
}
diff --git a/arm_compute/runtime/CL/CLFunctions.h b/arm_compute/runtime/CL/CLFunctions.h
index 7c2377a..adf240e 100644
--- a/arm_compute/runtime/CL/CLFunctions.h
+++ b/arm_compute/runtime/CL/CLFunctions.h
@@ -107,6 +107,7 @@
#include "arm_compute/runtime/CL/functions/CLTranspose.h"
#include "arm_compute/runtime/CL/functions/CLWarpAffine.h"
#include "arm_compute/runtime/CL/functions/CLWarpPerspective.h"
+#include "arm_compute/runtime/CL/functions/CLWinogradConvolutionLayer.h"
#include "arm_compute/runtime/CL/functions/CLWinogradInputTransform.h"
#endif /* __ARM_COMPUTE_CLFUNCTIONS_H__ */
diff --git a/arm_compute/runtime/CL/functions/CLWinogradConvolutionLayer.h b/arm_compute/runtime/CL/functions/CLWinogradConvolutionLayer.h
new file mode 100644
index 0000000..14de169
--- /dev/null
+++ b/arm_compute/runtime/CL/functions/CLWinogradConvolutionLayer.h
@@ -0,0 +1,97 @@
+/*
+ * Copyright (c) 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_CLWINOGRADCONVOLUTIONLAYER_H__
+#define __ARM_COMPUTE_CLWINOGRADCONVOLUTIONLAYER_H__
+
+#include "arm_compute/core/CL/kernels/CLWinogradFilterTransformKernel.h"
+#include "arm_compute/core/CL/kernels/CLWinogradOutputTransformKernel.h"
+#include "arm_compute/core/Types.h"
+#include "arm_compute/runtime/CL/functions/CLGEMM.h"
+#include "arm_compute/runtime/CL/functions/CLWinogradInputTransform.h"
+#include "arm_compute/runtime/IFunction.h"
+
+namespace arm_compute
+{
+class ICLTensor;
+
+/** Basic function to execute Winograd-based convolution on OpenCL. This function calls the following OpenCL functions/kernels:
+ *
+ * -# @ref CLWinogradInputTransform
+ * -# @ref CLWinogradFilterTransformKernel (only once)
+ * -# @ref CLGEMM
+ * -# @ref CLWinogradOutputTransformKernel
+ *
+ */
+class CLWinogradConvolutionLayer : public IFunction
+{
+public:
+ /** Default constructor */
+ CLWinogradConvolutionLayer(std::shared_ptr<IMemoryManager> memory_manager = nullptr);
+ /** Set the input and output tensors.
+ *
+ * @note: This function only works with 3x3 kernels and unit strides
+ *
+ * @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: 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: Same as @p input
+ * @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.
+ */
+ void configure(ICLTensor *input, const ICLTensor *weights, const ICLTensor *biases, ICLTensor *output, const PadStrideInfo &conv_info);
+ /** Static function to check if given info will lead to a valid configuration of @ref CLWinogradConvolutionLayer
+ *
+ * @note: This function only works with 3x3 kernels and unit strides
+ *
+ * @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: 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: Same as @p input
+ * @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.
+ *
+ * @return a status
+ */
+ static Status validate(const ITensorInfo *input, const ITensorInfo *weights, const ITensorInfo *biases, const ITensorInfo *output, const PadStrideInfo &conv_info);
+
+ // Inherited methods overridden:
+ void run() override;
+
+private:
+ CLMemoryGroup _memory_group;
+ CLGEMM _batched_mm;
+ CLWinogradInputTransform _input_transform;
+ CLWinogradFilterTransformKernel _filter_transform;
+ CLWinogradOutputTransformKernel _output_transform;
+ CLTensor _input0;
+ CLTensor _input1;
+ CLTensor _batched_mm_output;
+ bool _is_first_run;
+};
+}
+#endif /* __ARM_COMPUTE_CLWINOGRADCONVOLUTIONLAYER_H__ */