From 780db4eb6a9e3dee565d14f36d772038cd3253da Mon Sep 17 00:00:00 2001 From: Michalis Spyrou Date: Thu, 23 Nov 2017 09:49:51 +0000 Subject: COMPMID-471 Implement Deconvolution on OpenCL Change-Id: Ie00c6b08a51d30c5ce2637d40ee3d165b8a68686 Reviewed-on: https://eu-gerrit-1.euhpc.arm.com/110311 Reviewed-by: Pablo Tello Reviewed-by: Georgios Pinitas Tested-by: Jenkins --- arm_compute/core/CL/CLKernels.h | 3 +- .../kernels/CLDeconvolutionLayerUpsampleKernel.h | 80 +++++++++ arm_compute/core/NEON/NEKernels.h | 3 +- .../kernels/NEDeconvolutionLayerUpsampleKernel.h | 72 -------- arm_compute/core/Utils.h | 28 ++- arm_compute/core/utils/misc/ShapeCalculator.h | 15 +- arm_compute/runtime/CL/CLFunctions.h | 4 +- .../runtime/CL/functions/CLDeconvolutionLayer.h | 103 +++++++++++ .../CL/functions/CLDeconvolutionLayerUpsample.h | 85 +++++++++ .../CL/functions/CLDirectConvolutionLayer.h | 3 +- arm_compute/runtime/NEON/NEFunctions.h | 3 +- .../runtime/NEON/functions/NEDeconvolutionLayer.h | 61 ++++--- .../NEON/functions/NEDeconvolutionLayerUpsample.h | 72 -------- src/core/CL/CLKernelLibrary.cpp | 7 +- src/core/CL/cl_kernels/deconvolution_layer.cl | 50 ++++++ .../kernels/CLDeconvolutionLayerUpsampleKernel.cpp | 117 +++++++++++++ .../kernels/NEDeconvolutionLayerUpsampleKernel.cpp | 165 ------------------ src/core/Utils.cpp | 32 ++-- src/runtime/CL/functions/CLDeconvolutionLayer.cpp | 132 ++++++++++++++ .../CL/functions/CLDeconvolutionLayerUpsample.cpp | 64 +++++++ .../NEON/functions/NEDeconvolutionLayer.cpp | 105 +++++------ .../functions/NEDeconvolutionLayerUpsample.cpp | 121 ------------- tests/datasets/ShapeDatasets.h | 4 +- tests/validation/CL/DeconvolutionLayer.cpp | 192 +++++++++++++++++++++ tests/validation/NEON/DeconvolutionLayer.cpp | 14 +- .../fixtures/DeconvolutionLayerFixture.h | 37 ++-- tests/validation/reference/DeconvolutionLayer.cpp | 72 ++++---- tests/validation/reference/DeconvolutionLayer.h | 4 +- 28 files changed, 1016 insertions(+), 632 deletions(-) create mode 100644 arm_compute/core/CL/kernels/CLDeconvolutionLayerUpsampleKernel.h delete mode 100644 arm_compute/core/NEON/kernels/NEDeconvolutionLayerUpsampleKernel.h create mode 100644 arm_compute/runtime/CL/functions/CLDeconvolutionLayer.h create mode 100644 arm_compute/runtime/CL/functions/CLDeconvolutionLayerUpsample.h delete mode 100644 arm_compute/runtime/NEON/functions/NEDeconvolutionLayerUpsample.h create mode 100644 src/core/CL/cl_kernels/deconvolution_layer.cl create mode 100644 src/core/CL/kernels/CLDeconvolutionLayerUpsampleKernel.cpp delete mode 100644 src/core/NEON/kernels/NEDeconvolutionLayerUpsampleKernel.cpp create mode 100644 src/runtime/CL/functions/CLDeconvolutionLayer.cpp create mode 100644 src/runtime/CL/functions/CLDeconvolutionLayerUpsample.cpp delete mode 100644 src/runtime/NEON/functions/NEDeconvolutionLayerUpsample.cpp create mode 100644 tests/validation/CL/DeconvolutionLayer.cpp diff --git a/arm_compute/core/CL/CLKernels.h b/arm_compute/core/CL/CLKernels.h index 9da0e5ab3a..64687fb26a 100644 --- a/arm_compute/core/CL/CLKernels.h +++ b/arm_compute/core/CL/CLKernels.h @@ -1,5 +1,5 @@ /* - * Copyright (c) 2016, 2017 ARM Limited. + * Copyright (c) 2016, 2018 ARM Limited. * * SPDX-License-Identifier: MIT * @@ -42,6 +42,7 @@ #include "arm_compute/core/CL/kernels/CLCol2ImKernel.h" #include "arm_compute/core/CL/kernels/CLColorConvertKernel.h" #include "arm_compute/core/CL/kernels/CLConvolutionKernel.h" +#include "arm_compute/core/CL/kernels/CLDeconvolutionLayerUpsampleKernel.h" #include "arm_compute/core/CL/kernels/CLDepthConcatenateLayerKernel.h" #include "arm_compute/core/CL/kernels/CLDepthConvertLayerKernel.h" #include "arm_compute/core/CL/kernels/CLDepthwiseConvolutionLayer3x3Kernel.h" diff --git a/arm_compute/core/CL/kernels/CLDeconvolutionLayerUpsampleKernel.h b/arm_compute/core/CL/kernels/CLDeconvolutionLayerUpsampleKernel.h new file mode 100644 index 0000000000..8867ca1c37 --- /dev/null +++ b/arm_compute/core/CL/kernels/CLDeconvolutionLayerUpsampleKernel.h @@ -0,0 +1,80 @@ +/* + * 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_CLDECONVOLUTIONLAYERUPSAMPLEKERNEL_H__ +#define __ARM_COMPUTE_CLDECONVOLUTIONLAYERUPSAMPLEKERNEL_H__ + +#include "arm_compute/core/CL/ICLKernel.h" + +namespace arm_compute +{ +class ICLTensor; + +/** Interface for the Deconvolution layer kernel on OpenCL. + */ +class CLDeconvolutionLayerUpsampleKernel : public ICLKernel +{ +public: + /** Constructor */ + CLDeconvolutionLayerUpsampleKernel(); + /** Prevent instances of this class from being copied (As this class contains pointers) */ + CLDeconvolutionLayerUpsampleKernel(const CLDeconvolutionLayerUpsampleKernel &) = delete; + /** Prevent instances of this class from being copied (As this class contains pointers) */ + CLDeconvolutionLayerUpsampleKernel &operator=(const CLDeconvolutionLayerUpsampleKernel &) = delete; + /** Default Move Constructor. */ + CLDeconvolutionLayerUpsampleKernel(CLDeconvolutionLayerUpsampleKernel &&) = default; + /** Default move assignment operator. */ + CLDeconvolutionLayerUpsampleKernel &operator=(CLDeconvolutionLayerUpsampleKernel &&) = default; + /** Default destructor */ + ~CLDeconvolutionLayerUpsampleKernel() = default; + + /** Initialise the kernel's input and output. + * + * @param[in] input Source tensor. Data types supported: F32. + * @param[out] output Destination tensor. Data types supported: F32. All but the lowest two dimensions must be the same size as in the input tensor, i.e. scaling is only performed within the XY-plane. + * @param[in] inner_border Top and right inner border sizes. These rows and columns will be filled with zero. + * @param[in] info Contains padding and stride information described in @ref PadStrideInfo. + */ + void configure(const ICLTensor *input, ICLTensor *output, const BorderSize &inner_border, const PadStrideInfo &info); + /** Static function to check if given info will lead to a valid configuration of @ref CLDeconvolutionLayerUpsample + * + * @param[in] input Source tensor info. Data types supported: F32. + * @param[in] output Destination tensor info. Data types supported: F32. All but the lowest two dimensions must be the same size as in the input tensor, i.e. scaling is only performed within the XY-plane. + * @param[in] inner_border Top and right inner border sizes. These rows and columns will be filled with zero. + * @param[in] info Contains padding and stride information described in @ref PadStrideInfo. + * + * @return a status + */ + static Status validate(const ITensorInfo *input, const ITensorInfo *output, const BorderSize &inner_border, const PadStrideInfo &info); + + // Inherited methods overridden: + void run(const Window &window, cl::CommandQueue &queue) override; + +private: + const ICLTensor *_input; + ICLTensor *_output; + BorderSize _inner_border; + PadStrideInfo _info; +}; +} // namespace arm_compute +#endif /*__ARM_COMPUTE_CLDECONVOLUTIONLAYERUPSAMPLEKERNEL_H__ */ diff --git a/arm_compute/core/NEON/NEKernels.h b/arm_compute/core/NEON/NEKernels.h index 8a4cf7abeb..d5c4c340ee 100644 --- a/arm_compute/core/NEON/NEKernels.h +++ b/arm_compute/core/NEON/NEKernels.h @@ -1,5 +1,5 @@ /* - * Copyright (c) 2016, 2017 ARM Limited. + * Copyright (c) 2016, 2018 ARM Limited. * * SPDX-License-Identifier: MIT * @@ -43,7 +43,6 @@ #include "arm_compute/core/NEON/kernels/NEColorConvertKernel.h" #include "arm_compute/core/NEON/kernels/NEConvolutionKernel.h" #include "arm_compute/core/NEON/kernels/NECumulativeDistributionKernel.h" -#include "arm_compute/core/NEON/kernels/NEDeconvolutionLayerUpsampleKernel.h" #include "arm_compute/core/NEON/kernels/NEDepthConcatenateLayerKernel.h" #include "arm_compute/core/NEON/kernels/NEDepthConvertLayerKernel.h" #include "arm_compute/core/NEON/kernels/NEDepthwiseConvolutionLayer3x3Kernel.h" diff --git a/arm_compute/core/NEON/kernels/NEDeconvolutionLayerUpsampleKernel.h b/arm_compute/core/NEON/kernels/NEDeconvolutionLayerUpsampleKernel.h deleted file mode 100644 index 707564683f..0000000000 --- a/arm_compute/core/NEON/kernels/NEDeconvolutionLayerUpsampleKernel.h +++ /dev/null @@ -1,72 +0,0 @@ -/* - * Copyright (c) 2017 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_NEDECONVOLUTIONLAYERKERNEL_H__ -#define __ARM_COMPUTE_NEDECONVOLUTIONLAYERKERNEL_H__ - -#include "arm_compute/core/NEON/INEKernel.h" -#include "arm_compute/core/Types.h" - -namespace arm_compute -{ -class ITensor; - -/** NEON kernel to perform scaling on a tensor */ -class NEDeconvolutionLayerUpsampleKernel : public INEKernel -{ -public: - /** Default constructor */ - NEDeconvolutionLayerUpsampleKernel(); - /** Prevent instances of this class from being copied (As this class contains pointers) */ - NEDeconvolutionLayerUpsampleKernel(const NEDeconvolutionLayerUpsampleKernel &) = delete; - /** Prevent instances of this class from being copied (As this class contains pointers) */ - NEDeconvolutionLayerUpsampleKernel &operator=(const NEDeconvolutionLayerUpsampleKernel &) = delete; - /** Allow instances of this class to be moved */ - NEDeconvolutionLayerUpsampleKernel(NEDeconvolutionLayerUpsampleKernel &&) = default; - /** Allow instances of this class to be moved */ - NEDeconvolutionLayerUpsampleKernel &operator=(NEDeconvolutionLayerUpsampleKernel &&) = default; - /** Default destructor */ - ~NEDeconvolutionLayerUpsampleKernel() = default; - - /** Initialise the kernel's inputs, output and interpolation policy - * - * @param[in] input Source tensor. Data types supported: F32. - * @param[in] offsets Offset to access the pixel with NEAREST interpolation or the top-left pixel with BILINEAR interpolation in the input tensor. Data type supported: S32. - * @param[out] output Destination tensor. Data types supported: F32. All but the lowest two dimensions must be the same size as in the input tensor, i.e. scaling is only performed within the XY-plane. - */ - void configure(const ITensor *input, const ITensor *offsets, ITensor *output); - - // Inherited methods overridden: - void run(const Window &window, const ThreadInfo &info) override; - BorderSize border_size() const override; - -private: - /** Function to perform scale using nearest interpolation on the given window */ - void scale_nearest(const Window &window); - - const ITensor *_offsets; - const ITensor *_input; - ITensor *_output; -}; -} // arm_compute -#endif /*__ARM_COMPUTE_NEDECONVOLUTIONLAYERKERNEL_H__ */ diff --git a/arm_compute/core/Utils.h b/arm_compute/core/Utils.h index f78add13f9..51967b1762 100644 --- a/arm_compute/core/Utils.h +++ b/arm_compute/core/Utils.h @@ -1,5 +1,5 @@ /* - * Copyright (c) 2016, 2017 ARM Limited. + * Copyright (c) 2016, 2017, 2018 ARM Limited. * * SPDX-License-Identifier: MIT * @@ -614,25 +614,23 @@ TensorShape deconvolution_output_shape(const std::pair deconvolution_output_dimensions(unsigned int in_width, unsigned int in_height, unsigned int kernel_width, unsigned int kernel_height, - unsigned int padx, unsigned int pady, unsigned int ax, unsigned int ay, - float upscalex, float upscaley, DimensionRoundingType round); + unsigned int padx, unsigned int pady, unsigned int inner_border_right, unsigned int inner_border_top, + unsigned int stride_x, unsigned int stride_y); /** Returns expected width and height of output scaled tensor depending on dimensions rounding mode. * diff --git a/arm_compute/core/utils/misc/ShapeCalculator.h b/arm_compute/core/utils/misc/ShapeCalculator.h index f31eb3d336..c7667f2c7b 100644 --- a/arm_compute/core/utils/misc/ShapeCalculator.h +++ b/arm_compute/core/utils/misc/ShapeCalculator.h @@ -1,5 +1,5 @@ /* - * Copyright (c) 2017 ARM Limited. + * Copyright (c) 2017, 2018 ARM Limited. * * SPDX-License-Identifier: MIT * @@ -106,7 +106,8 @@ inline TensorShape compute_depthwise_convolution_shape(const ITensorInfo &input, 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); + std::tie(output_width, output_height) = scaled_dimensions(input_shape.x(), input_shape.y(), weights_shape.x(), + weights_shape.y(), conv_info); TensorShape output_shape{ input_shape }; output_shape.set(0, output_width); @@ -114,6 +115,16 @@ inline TensorShape compute_depthwise_convolution_shape(const ITensorInfo &input, return output_shape; } +inline TensorShape compute_deconvolution_shape(const ITensorInfo &input, unsigned int sx, unsigned int sy, unsigned int inner_border_right, unsigned int inner_border_top, const PadStrideInfo &info) +{ + TensorShape scale_out_shape(input.tensor_shape()); + const unsigned int out_x = input.dimension(0) + (input.dimension(0) - 1) * (sx - 1) + inner_border_right + 2 * info.pad().first; + const unsigned int out_y = input.dimension(1) + (input.dimension(1) - 1) * (sy - 1) + inner_border_top + 2 * info.pad().second; + scale_out_shape.set(0, out_x); + scale_out_shape.set(1, out_y); + + return scale_out_shape; +} } // namespace shape_calculator } // namespace misc } // namespace arm_compute diff --git a/arm_compute/runtime/CL/CLFunctions.h b/arm_compute/runtime/CL/CLFunctions.h index f6ecef7a51..1154ab79aa 100644 --- a/arm_compute/runtime/CL/CLFunctions.h +++ b/arm_compute/runtime/CL/CLFunctions.h @@ -1,5 +1,5 @@ /* - * Copyright (c) 2016, 2017 ARM Limited. + * Copyright (c) 2016, 2018 ARM Limited. * * SPDX-License-Identifier: MIT * @@ -42,6 +42,8 @@ #include "arm_compute/runtime/CL/functions/CLColorConvert.h" #include "arm_compute/runtime/CL/functions/CLConvolution.h" #include "arm_compute/runtime/CL/functions/CLConvolutionLayer.h" +#include "arm_compute/runtime/CL/functions/CLDeconvolutionLayer.h" +#include "arm_compute/runtime/CL/functions/CLDeconvolutionLayerUpsample.h" #include "arm_compute/runtime/CL/functions/CLDepthConcatenateLayer.h" #include "arm_compute/runtime/CL/functions/CLDepthConvertLayer.h" #include "arm_compute/runtime/CL/functions/CLDepthwiseConvolutionLayer.h" diff --git a/arm_compute/runtime/CL/functions/CLDeconvolutionLayer.h b/arm_compute/runtime/CL/functions/CLDeconvolutionLayer.h new file mode 100644 index 0000000000..e98cc9b3d6 --- /dev/null +++ b/arm_compute/runtime/CL/functions/CLDeconvolutionLayer.h @@ -0,0 +1,103 @@ +/* + * 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_CLDECONVOLUTIONLAYER_H__ +#define __ARM_COMPUTE_CLDECONVOLUTIONLAYER_H__ + +#include "arm_compute/runtime/CL/functions/CLDeconvolutionLayerUpsample.h" +#include "arm_compute/runtime/CL/functions/CLDirectConvolutionLayer.h" + +#include "arm_compute/runtime/CL/CLMemoryGroup.h" +#include "arm_compute/runtime/CL/CLTensor.h" +#include "arm_compute/runtime/IFunction.h" +#include "arm_compute/runtime/IMemoryManager.h" + +#include + +namespace arm_compute +{ +class ICLTensor; +/** Function to run the deconvolution layer. + * + * Deconvolution Layer is the backward pass of Convolution Layer. First we transform the input depending on the stride and pad info and then perform a 1x1 + * convolution pass. Input stride defines how many zeroes we should put between each element of the input, pad is the amount of padding and finally a is a user + * specified value where a < stride - 1, that increases the padding top and right of the input image. + * + * The relation between input to output is as follows: + * width_output = round((width_input − 1) ∗ (stride_x - 1) − 2 ∗ padding_x + kernel_x + inner_border_right ) + * height_output = round((height_input − 1) ∗ (stride_y - 1) − 2 ∗ padding_y + kernel_y + inner_border_top ) + * + * where: + * width_input is the size of the first input dimension. + * height_input is the size of the second input dimension. + * width_output is the size of the first output dimension. + * height_output is the size of the second output dimension. + * kernel_x and kernel_y are the convolution sizes in x and y. + * inner_border_right and inner_border_top the number of zeros added to the right and top edges of the input. + * stride_x and stride_y is the input stride of the first and second dimension. + * + */ +class CLDeconvolutionLayer : public IFunction +{ +public: + /** Constructor */ + CLDeconvolutionLayer(std::shared_ptr memory_manager = nullptr); + /** Set the input, weights, biases and output tensors. + * + * @param[in,out] input Input tensor. 3 lower dimensions represent a single input, and an optional 4th dimension for batch of inputs. Data types supported: F32. + * @param[in] weights The 4d weights with dimensions [width, height, OFM, IFM]. Data type supported: Same as @p input. + * @param[in] bias (Optional) The biases have one dimension. Data type supported: Same as @p input. + * @param[out] output Output tensor. The output has the same number of dimensions as the @p input. + * @param[in] info Contains padding and policies to be used in the deconvolution, this is decribed in @ref PadStrideInfo. + * @param[in] inner_border_right The number of zeros added to right edge of the input. + * @param[in] inner_border_top The number of zeros added to top edge of the input. + * + */ + void configure(ICLTensor *input, const ICLTensor *weights, const ICLTensor *bias, ICLTensor *output, const PadStrideInfo &info, + unsigned int inner_border_right, unsigned int inner_border_top); + /** Static function to check if given info will lead to a valid configuration of @ref CLDeconvolutionLayer + * + * @param[in] input Input tensor info. 3 lower dimensions represent a single input, and an optional 4th dimension for batch of inputs. Data types supported: F32. + * @param[in] weights The 4d weights info with dimensions [width, height, OFM, IFM]. Data type supported: Same as @p input. + * @param[in] bias (Optional) The biases have one dimension. Data type supported: Same as @p input. + * @param[in] output Output tensor info. The output has the same number of dimensions as the @p input. + * @param[in] info Contains padding and policies to be used in the deconvolution, this is decribed in @ref PadStrideInfo. + * @param[in] inner_border_right The number of zeros added to right edge of the input. + * @param[in] inner_border_top The number of zeros added to top edge of the input. + * + * @return a status + */ + static Status validate(const ITensorInfo *input, const ITensorInfo *weights, const ITensorInfo *bias, ITensorInfo *output, const PadStrideInfo &info, + unsigned int inner_border_right, unsigned int inner_border_top); + + // Inherited methods overridden: + void run() override; + +private: + CLMemoryGroup _memory_group; + CLDeconvolutionLayerUpsample _scale_f; + CLDirectConvolutionLayer _conv_f; + CLTensor _scaled_output; +}; +} +#endif /* __ARM_COMPUTE_CLDECONVOLUTIONLAYER_H__ */ \ No newline at end of file diff --git a/arm_compute/runtime/CL/functions/CLDeconvolutionLayerUpsample.h b/arm_compute/runtime/CL/functions/CLDeconvolutionLayerUpsample.h new file mode 100644 index 0000000000..74ee4efb2c --- /dev/null +++ b/arm_compute/runtime/CL/functions/CLDeconvolutionLayerUpsample.h @@ -0,0 +1,85 @@ +/* + * 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_CLDECONVOLUTIONLAYERUPSAMPLE_H__ +#define __ARM_COMPUTE_CLDECONVOLUTIONLAYERUPSAMPLE_H__ + +#include "arm_compute/runtime/IFunction.h" + +#include "arm_compute/core/CL/kernels/CLDeconvolutionLayerUpsampleKernel.h" +#include "arm_compute/core/Types.h" +#include "arm_compute/runtime/CL/CLMemoryGroup.h" +#include "arm_compute/runtime/IFunction.h" +#include "arm_compute/runtime/IMemoryManager.h" + +namespace arm_compute +{ +class ICLTensor; + +/** Basic function to run @ref CLDeconvolutionLayerUpsampleKernel */ +class CLDeconvolutionLayerUpsample : public IFunction +{ +public: + /** Default constructor */ + CLDeconvolutionLayerUpsample(); + /** Prevent instances of this class from being copied (As this class contains pointers) */ + CLDeconvolutionLayerUpsample(const CLDeconvolutionLayerUpsample &) = delete; + /** Prevent instances of this class from being copied (As this class contains pointers) */ + CLDeconvolutionLayerUpsample &operator=(const CLDeconvolutionLayerUpsample &) = delete; + /** Allow instances of this class to be moved */ + CLDeconvolutionLayerUpsample(CLDeconvolutionLayerUpsample &&) = default; + /** Allow instances of this class to be moved */ + CLDeconvolutionLayerUpsample &operator=(CLDeconvolutionLayerUpsample &&) = default; + /** Default destructor */ + virtual ~CLDeconvolutionLayerUpsample() = default; + + /** Initialize the function's source, destination, interpolation type and border_mode. + * + * @param[in, out] input Source tensor. Data type supported: F32. + * @param[out] output Destination tensor. Data type supported: F32. + * @param[in] inner_border The number of zeros added to right and top edges of the input. + * @param[in] info Contains padding and policies to be used in the deconvolution. + */ + void configure(ICLTensor *input, ICLTensor *output, const BorderSize &inner_border, + const PadStrideInfo &info); + /** Static function to check if given info will lead to a valid configuration of @ref CLDeconvolutionLayerUpsample + * + * @param[in] input Source tensor info. Data type supported: F32. + * @param[in] output Destination tensor info. Data type supported: F32. + * @param[in] inner_border The number of zeros added to right and top edges of the input. + * @param[in] info Contains padding and policies to be used in the deconvolution. + * + * @return a status + */ + static Status validate(const ITensorInfo *input, const ITensorInfo *output, const BorderSize &inner_border, + const PadStrideInfo &info); + + // Inherited methods overridden: + void run() override; + +private: + CLDeconvolutionLayerUpsampleKernel _upsample; + ICLTensor *_output; +}; +} +#endif /* __ARM_COMPUTE_CLDECONVOLUTIONLAYERUPSAMPLE_H__ */ diff --git a/arm_compute/runtime/CL/functions/CLDirectConvolutionLayer.h b/arm_compute/runtime/CL/functions/CLDirectConvolutionLayer.h index f31a45be90..205c90c478 100644 --- a/arm_compute/runtime/CL/functions/CLDirectConvolutionLayer.h +++ b/arm_compute/runtime/CL/functions/CLDirectConvolutionLayer.h @@ -1,5 +1,5 @@ /* - * Copyright (c) 2017 ARM Limited. + * Copyright (c) 2017, 2018 ARM Limited. * * SPDX-License-Identifier: MIT * @@ -40,6 +40,7 @@ class ICLTensor; class CLDirectConvolutionLayer : public IFunction { public: + /** Default constructor */ CLDirectConvolutionLayer(); /** Set the input and output tensors. * diff --git a/arm_compute/runtime/NEON/NEFunctions.h b/arm_compute/runtime/NEON/NEFunctions.h index 08852cf368..d09fcb280c 100644 --- a/arm_compute/runtime/NEON/NEFunctions.h +++ b/arm_compute/runtime/NEON/NEFunctions.h @@ -1,5 +1,5 @@ /* - * Copyright (c) 2016, 2017 ARM Limited. + * Copyright (c) 2016, 2018 ARM Limited. * * SPDX-License-Identifier: MIT * @@ -44,7 +44,6 @@ #include "arm_compute/runtime/NEON/functions/NEConvolution.h" #include "arm_compute/runtime/NEON/functions/NEConvolutionLayer.h" #include "arm_compute/runtime/NEON/functions/NEDeconvolutionLayer.h" -#include "arm_compute/runtime/NEON/functions/NEDeconvolutionLayerUpsample.h" #include "arm_compute/runtime/NEON/functions/NEDepthConcatenateLayer.h" #include "arm_compute/runtime/NEON/functions/NEDepthConvertLayer.h" #include "arm_compute/runtime/NEON/functions/NEDepthwiseConvolutionLayer.h" diff --git a/arm_compute/runtime/NEON/functions/NEDeconvolutionLayer.h b/arm_compute/runtime/NEON/functions/NEDeconvolutionLayer.h index 8757bc63aa..091a928db6 100644 --- a/arm_compute/runtime/NEON/functions/NEDeconvolutionLayer.h +++ b/arm_compute/runtime/NEON/functions/NEDeconvolutionLayer.h @@ -1,5 +1,5 @@ /* - * Copyright (c) 2017 ARM Limited. + * Copyright (c) 2017, 2018 ARM Limited. * * SPDX-License-Identifier: MIT * @@ -24,7 +24,6 @@ #ifndef __ARM_COMPUTE_NEDECONVOLUTIONLAYER_H__ #define __ARM_COMPUTE_NEDECONVOLUTIONLAYER_H__ -#include "arm_compute/runtime/NEON/functions/NEDeconvolutionLayerUpsample.h" #include "arm_compute/runtime/NEON/functions/NEDirectConvolutionLayer.h" #include "arm_compute/core/Types.h" @@ -39,13 +38,13 @@ namespace arm_compute { /** Function to run the deconvolution layer. * - * The operation is similar to convolution but it's implemented by up-sampling the inputs with zeros insertions between the inputs and convolving - * the kernels on the up-sampled result. + * Deconvolution Layer is the backward pass of Convolution Layer. First we transform the input depending on the stride and pad info and then perfrom a 1x1 + * convolution pass. Input stride defines how many zeroes we should put between each element of the input, pad is the amount of padding and finaly a is a user + * specified value where a < stride - 1 that increases the padding top and right of the input image. * - * Before the Deconvolution is done, up-scaling the first 2D with zeros is performed. The relation between input to - * output is as follows: - * width_output = round((width_input − 1) ∗ upscale_x − 2 ∗ padding_x + kernel_x + a_x ) - * height_output = round((height_input − 1) ∗ upscale_y − 2 ∗ padding_y + kernel_y + a_y ) + * The relation between input to output is as follows: + * width_output = round((width_input − 1) ∗ (stride_x - 1) − 2 ∗ padding_x + kernel_x + inner_border_right ) + * height_output = round((height_input − 1) ∗ (stride_y - 1) − 2 ∗ padding_y + kernel_y + inner_border_top ) * * where * width is the size of the first input dimension. @@ -53,44 +52,54 @@ namespace arm_compute * width_output is the size of the first output dimension. * height_output is the size of the second output dimension. * kernel_x and kernel_y are the convolution sizes in x and y. - * ax and ay the number of zeros added to the top and right edges of the input. - * upscale_x and upscale_y how much to scale the X and Y axis. + * inner_border_right and inner_border_top the number of zeros added to the top and right edges of the input. + * stride_x and stride_y is the input stride of the first and second dimension. * * This function calls the following NEON kernels: * - * -# @ref NEDeconvolutionLayerUpsampleKernel * -# @ref NEDirectConvolutionLayer * */ class NEDeconvolutionLayer : public IFunction { public: - /** Constructor */ + /** Default constructor */ NEDeconvolutionLayer(std::shared_ptr memory_manager = nullptr); + + /** Prevent instances of this class from being copied (As this class contains pointers) */ + NEDeconvolutionLayer(const NEDeconvolutionLayer &) = delete; + /** Prevent instances of this class from being copied (As this class contains pointers) */ + NEDeconvolutionLayer &operator=(const NEDeconvolutionLayer &) = delete; + /** Allow instances of this class to be moved */ + NEDeconvolutionLayer(NEDeconvolutionLayer &&) = default; + /** Allow instances of this class to be moved */ + NEDeconvolutionLayer &operator=(NEDeconvolutionLayer &&) = default; + /** Default destructor */ + virtual ~NEDeconvolutionLayer() = default; /** Set the input, weights, biases and output tensors. * - * @param[in,out] input Input tensor. 3 lower dimensions represent a single input, and an optional 4th dimension for batch of inputs. Data types supported: F32. - * @param[in] weights The 4d weights with dimensions [width, height, OFM, IFM]. Data type supported: Same as @p input. - * @param[in] bias Optional, ignored if NULL. The biases have one dimension. Data type supported: Same as @p input. - * @param[out] output Output tensor. The output has the same number of dimensions as the @p input. - * @param[in] info Contains padding and policies to be used in the deconvolution, this is decribed in @ref PadStrideInfo. - * @param[in] ax The number of zeros added to right edge of the input. - * @param[in] ay The number of zeros added to top edge of the input. - * @param[in] upscalex How much to scale the X axis. - * @param[in] upscaley How much to scale the Y axis. + * @param[in,out] input Input tensor. 3 lower dimensions represent a single input, and an optional 4th dimension for batch of inputs. Data types supported: F32. + * @param[in] weights The 4d weights with dimensions [width, height, OFM, IFM]. Data type supported: Same as @p input. + * @param[in] bias Optional, ignored if NULL. The biases have one dimension. Data type supported: Same as @p input. + * @param[out] output Output tensor. The output has the same number of dimensions as the @p input. + * @param[in] info Contains padding and policies to be used in the deconvolution, this is decribed in @ref PadStrideInfo. + * @param[in] inner_border_right The number of zeros added to right edge of the input. + * @param[in] inner_border_top The number of zeros added to top edge of the input. * */ void configure(ITensor *input, const ITensor *weights, const ITensor *bias, ITensor *output, const PadStrideInfo &info, - unsigned int ax, unsigned int ay, float upscalex, float upscaley); + unsigned int inner_border_right, unsigned int inner_border_top); // Inherited methods overridden: void run() override; private: - MemoryGroup _memory_group; - NEDeconvolutionLayerUpsample _scale_f; - NEDirectConvolutionLayer _conv_f; - Tensor _scaled_output; + MemoryGroup _memory_group; + NEDirectConvolutionLayer _conv_f; + Tensor _scaled_output; + ITensor *_input; + PadStrideInfo _info; + std::pair _inner_border; }; } // arm_compute #endif /* __ARM_COMPUTE_NEDECONVOLUTIONLAYER_H__ */ diff --git a/arm_compute/runtime/NEON/functions/NEDeconvolutionLayerUpsample.h b/arm_compute/runtime/NEON/functions/NEDeconvolutionLayerUpsample.h deleted file mode 100644 index d2ac12a58a..0000000000 --- a/arm_compute/runtime/NEON/functions/NEDeconvolutionLayerUpsample.h +++ /dev/null @@ -1,72 +0,0 @@ -/* - * Copyright (c) 2016, 2017 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_NEDECONVOLUTIONUPSAMPLE_H__ -#define __ARM_COMPUTE_NEDECONVOLUTIONUPSAMPLE_H__ - -#include "arm_compute/core/NEON/kernels/NEDeconvolutionLayerUpsampleKernel.h" -#include "arm_compute/core/NEON/kernels/NEFillBorderKernel.h" -#include "arm_compute/core/Types.h" -#include "arm_compute/runtime/IFunction.h" -#include "arm_compute/runtime/IMemoryManager.h" -#include "arm_compute/runtime/MemoryGroup.h" -#include "arm_compute/runtime/Tensor.h" - -#include -#include - -namespace arm_compute -{ -class ITensor; - -/** Basic function to run @ref NEDeconvolutionLayerUpsampleKernel */ -class NEDeconvolutionLayerUpsample : public IFunction -{ -public: - /** Constructor - * - * Initialize NEDeconvolutionLayerUpsample - */ - NEDeconvolutionLayerUpsample(std::shared_ptr memory_manager = nullptr); - /** Initialize the function's source, destination, interpolation type and border_mode. - * - * @param[in, out] input Source tensor. Data type supported: F32. - * @param[out] output Destination tensor. Data type supported: F32. - * @param[in] a Top and right inner border sizes. These rows and columns will be filled with zero. - * @param[in] iz The number of zeros to be inserted between each input sample - * @param[in] info Contains padding and policies to be used in the deconvolution, this is decribed in @ref PadStrideInfo. - */ - void configure(ITensor *input, ITensor *output, const std::pair &a, - const std::pair &iz, const PadStrideInfo &info); - - // Inherited methods overridden: - void run() override; - -private: - MemoryGroup _memory_group; - Tensor _offsets; - NEFillBorderKernel _border_handler; - NEDeconvolutionLayerUpsampleKernel _upsample; -}; -} // arm_compute -#endif /*__ARM_COMPUTE_NEDECONVOLUTIONUPSAMPLE_H__ */ diff --git a/src/core/CL/CLKernelLibrary.cpp b/src/core/CL/CLKernelLibrary.cpp index de75518a05..352b89baa5 100644 --- a/src/core/CL/CLKernelLibrary.cpp +++ b/src/core/CL/CLKernelLibrary.cpp @@ -1,5 +1,5 @@ /* - * Copyright (c) 2016, 2017 ARM Limited. + * Copyright (c) 2016, 2018 ARM Limited. * * SPDX-License-Identifier: MIT * @@ -186,6 +186,7 @@ const std::map CLKernelLibrary::_kernel_program_map = { "copy_plane", "channel_extract.cl" }, { "copy_planes_3p", "channel_combine.cl" }, { "copy_to_keypoint", "fast_corners.cl" }, + { "deconvolution_upsample", "deconvolution_layer.cl" }, { "depthwise_convolution_3x3", "depthwise_convolution.cl" }, { "depthwise_convolution_3x3_quantized", "depthwise_convolution_quantized.cl" }, { "depthwise_im2col", "depthwise_convolution.cl" }, @@ -419,6 +420,10 @@ const std::map CLKernelLibrary::_program_source_map = { "convolution_rectangle.cl", #include "./cl_kernels/convolution_rectangle.clembed" + }, + { + "deconvolution_layer.cl", +#include "./cl_kernels/deconvolution_layer.clembed" }, { "depth_convert.cl", diff --git a/src/core/CL/cl_kernels/deconvolution_layer.cl b/src/core/CL/cl_kernels/deconvolution_layer.cl new file mode 100644 index 0000000000..2514ddc8cc --- /dev/null +++ b/src/core/CL/cl_kernels/deconvolution_layer.cl @@ -0,0 +1,50 @@ +/* + * 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. + */ +#include "helpers.h" + +/** This function applies upsample on an input image. + * + * @param[in] src_ptr Pointer to the source image. Supported data types: F32 + * @param[in] src_stride_x Stride of the source image in X dimension (in bytes) + * @param[in] src_step_x src_stride_x * number of elements along X processed per workitem(in bytes) + * @param[in] src_stride_y Stride of the source image in Y dimension (in bytes) + * @param[in] src_step_y src_stride_y * number of elements along Y processed per workitem(in bytes) + * @param[in] src_offset_first_element_in_bytes The offset of the first element in the source image + * @param[out] dst_ptr Pointer to the destination image. Supported data types: F32 + * @param[in] dst_stride_x Stride of the destination image in X dimension (in bytes) + * @param[in] dst_step_x dst_stride_x * number of elements along X processed per workitem(in bytes) + * @param[in] dst_stride_y Stride of the destination image in Y dimension (in bytes) + * @param[in] dst_step_y dst_stride_y * number of elements along Y processed per workitem(in bytes) + * @param[in] dst_offset_first_element_in_bytes The offset of the first element in the destination image + */ +__kernel void deconvolution_upsample( + IMAGE_DECLARATION(src), + IMAGE_DECLARATION(dst)) +{ + Image src = CONVERT_TO_IMAGE_STRUCT(src); + Image dst = CONVERT_TO_IMAGE_STRUCT(dst); + + // Store result + *((__global float *)dst.ptr) = *((__global float *)src.ptr); +} diff --git a/src/core/CL/kernels/CLDeconvolutionLayerUpsampleKernel.cpp b/src/core/CL/kernels/CLDeconvolutionLayerUpsampleKernel.cpp new file mode 100644 index 0000000000..5c08d5bee2 --- /dev/null +++ b/src/core/CL/kernels/CLDeconvolutionLayerUpsampleKernel.cpp @@ -0,0 +1,117 @@ +/* + * 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. + */ +#include "arm_compute/core/CL/kernels/CLDeconvolutionLayerUpsampleKernel.h" + +#include "arm_compute/core/CL/CLHelpers.h" +#include "arm_compute/core/CL/CLKernelLibrary.h" +#include "arm_compute/core/CL/ICLTensor.h" +#include "arm_compute/core/Error.h" +#include "arm_compute/core/Helpers.h" +#include "arm_compute/core/Validate.h" +#include "arm_compute/core/Window.h" + +using namespace arm_compute; + +CLDeconvolutionLayerUpsampleKernel::CLDeconvolutionLayerUpsampleKernel() + : _input(nullptr), _output(nullptr), _inner_border(), _info() +{ +} + +Status CLDeconvolutionLayerUpsampleKernel::validate(const ITensorInfo *input, const ITensorInfo *output, const BorderSize &inner_border, + const PadStrideInfo &info) +{ + ARM_COMPUTE_RETURN_ERROR_ON_NULLPTR(input, output); + ARM_COMPUTE_UNUSED(info); + + ARM_COMPUTE_RETURN_ERROR_ON_DATA_TYPE_CHANNEL_NOT_IN(input, 1, DataType::F32); + ARM_COMPUTE_RETURN_ERROR_ON_MISMATCHING_DATA_TYPES(input, output); + ARM_COMPUTE_RETURN_ERROR_ON(output->dimension(0) == 0); + ARM_COMPUTE_RETURN_ERROR_ON(output->dimension(1) == 0); + + for(size_t i = 2; i < Coordinates::num_max_dimensions; ++i) + { + ARM_COMPUTE_RETURN_ERROR_ON(input->dimension(i) != output->dimension(i)); + } + + ARM_COMPUTE_RETURN_ERROR_ON_MSG(inner_border.right > info.stride().first - 1, "inner_border_right must be smaller that stride_x"); + ARM_COMPUTE_RETURN_ERROR_ON_MSG(inner_border.top > info.stride().second - 1, "inner_border_top must be smaller that stride_y"); + + return Status{}; +} + +void CLDeconvolutionLayerUpsampleKernel::configure(const ICLTensor *input, ICLTensor *output, const BorderSize &inner_border, + const PadStrideInfo &info) +{ + ARM_COMPUTE_ERROR_ON_NULLPTR(input, output); + + _input = input; + _output = output; + _inner_border = inner_border; + _info = info; + + // Perform validation step + ARM_COMPUTE_ERROR_THROW_ON(CLDeconvolutionLayerUpsampleKernel::validate(input->info(), output->info(), inner_border, info)); + + // Create kernel + _kernel = static_cast(CLKernelLibrary::get().create_kernel("deconvolution_upsample")); + + constexpr unsigned int num_elems_processed_per_iteration = 1; + + // Configure kernel window + Window win = calculate_max_window(*output->info(), Steps(num_elems_processed_per_iteration)); + + AccessWindowHorizontal output_access(output->info(), 0, 0, num_elems_processed_per_iteration); + output_access.set_valid_region(win, ValidRegion(Coordinates(), output->info()->tensor_shape())); + + ICLKernel::configure(win); +} + +void CLDeconvolutionLayerUpsampleKernel::run(const Window &window, cl::CommandQueue &queue) +{ + ARM_COMPUTE_ERROR_ON_UNCONFIGURED_KERNEL(this); + ARM_COMPUTE_ERROR_ON_INVALID_SUBWINDOW(ICLKernel::window(), window); + + const int out_start_x = _info.pad().first; + const int out_end_x = _output->info()->dimension(0) - _inner_border.right - _info.pad().first + _info.stride().first - 1; + const int out_step_x = _info.stride().first; + + const int out_start_y = _inner_border.top + _info.pad().second; + const int out_end_y = _output->info()->dimension(1) - _info.pad().second + _info.stride().second - 1; + const int out_step_y = _info.stride().second; + + Window slice_out = window.first_slice_window_2D(); + slice_out.set(Window::DimX, Window::Dimension(out_start_x, out_end_x, out_step_x)); + slice_out.set(Window::DimY, Window::Dimension(out_start_y, out_end_y, out_step_y)); + + Window slice_in = window.first_slice_window_2D(); + + do + { + unsigned int idx = 0; + add_2D_tensor_argument(idx, _input, slice_in); + add_2D_tensor_argument(idx, _output, slice_out); + enqueue(queue, *this, slice_out); + } + while(window.slide_window_slice_2D(slice_in) && window.slide_window_slice_2D(slice_out)); +} diff --git a/src/core/NEON/kernels/NEDeconvolutionLayerUpsampleKernel.cpp b/src/core/NEON/kernels/NEDeconvolutionLayerUpsampleKernel.cpp deleted file mode 100644 index 71db2e9782..0000000000 --- a/src/core/NEON/kernels/NEDeconvolutionLayerUpsampleKernel.cpp +++ /dev/null @@ -1,165 +0,0 @@ -/* - * Copyright (c) 2016, 2017 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. - */ -#include "arm_compute/core/NEON/kernels/NEDeconvolutionLayerUpsampleKernel.h" - -#include "arm_compute/core/AccessWindowStatic.h" -#include "arm_compute/core/Coordinates.h" -#include "arm_compute/core/Error.h" -#include "arm_compute/core/Helpers.h" -#include "arm_compute/core/ITensor.h" -#include "arm_compute/core/TensorInfo.h" -#include "arm_compute/core/Validate.h" -#include "arm_compute/core/Window.h" - -#include -#include -#include - -using namespace arm_compute; - -NEDeconvolutionLayerUpsampleKernel::NEDeconvolutionLayerUpsampleKernel() - : _offsets(nullptr), _input(nullptr), _output(nullptr) -{ -} - -BorderSize NEDeconvolutionLayerUpsampleKernel::border_size() const -{ - return BorderSize(1); -} - -void NEDeconvolutionLayerUpsampleKernel::configure(const ITensor *input, const ITensor *offsets, ITensor *output) -{ - ARM_COMPUTE_ERROR_ON_DATA_TYPE_CHANNEL_NOT_IN(input, 1, DataType::F32); - ARM_COMPUTE_ERROR_ON_DATA_TYPE_CHANNEL_NOT_IN(output, 1, DataType::F32); - ARM_COMPUTE_ERROR_ON(output->info()->dimension(0) == 0); - ARM_COMPUTE_ERROR_ON(output->info()->dimension(1) == 0); - - for(size_t i = 2; i < Coordinates::num_max_dimensions; ++i) - { - ARM_COMPUTE_ERROR_ON(input->info()->dimension(i) != output->info()->dimension(i)); - } - - _input = input; - _output = output; - _offsets = offsets; - - constexpr unsigned int num_elems_processed_per_iteration = 16; - const int border_offset = border_size().left; - - // Configure kernel window - Window win = calculate_max_window(*output->info(), Steps(num_elems_processed_per_iteration)); - - AccessWindowRectangle input_access(input->info(), -border_offset, -border_offset, input->info()->dimension(0) + border_offset, input->info()->dimension(1) + border_offset); - AccessWindowHorizontal offsets_access(offsets->info(), 0, num_elems_processed_per_iteration); - AccessWindowHorizontal output_access(output->info(), 0, num_elems_processed_per_iteration); - - update_window_and_padding(win, input_access, offsets_access, output_access); - - output_access.set_valid_region(win, ValidRegion(Coordinates(), output->info()->tensor_shape())); - - INEKernel::configure(win); -} - -void NEDeconvolutionLayerUpsampleKernel::scale_nearest(const Window &window) -{ - const size_t input_stride = _input->info()->strides_in_bytes()[1]; - - // Compute the ratio between source height and destination height - const auto hr = static_cast(_input->info()->dimension(1)) / static_cast(_output->info()->dimension(1)); - - // Don't increment in X and Y direction for the input tensor - // A pointer to the start of this plane is needed as base for the precomputed offsets - Window win_in(window); - win_in.set(Window::DimX, Window::Dimension(0, 0, 0)); - win_in.set(Window::DimY, Window::Dimension(0, 0, 0)); - - Window win_off; - win_off.set(Window::DimX, window[Window::DimX]); - win_off.set(Window::DimY, window[Window::DimY]); - - for(size_t d = Window::DimZ; d < _offsets->info()->num_dimensions(); ++d) - { - win_off.set(d, Window::Dimension(0, 0, 0)); - } - - Iterator in(_input, win_in); - Iterator out(_output, window); - Iterator offsets(_offsets, win_off); - - switch(_input->info()->data_type()) - { - case DataType::F32: - { - float32x4x4_t tmp = - { - { - vdupq_n_f32(0), - vdupq_n_f32(0) - } - }; - execute_window_loop(window, [&](const Coordinates & id) - { - const auto offsets_ptr = reinterpret_cast(offsets.ptr()); - - const size_t in_yi = (id.y() + 0.5f) * hr; - const size_t offset_row = in_yi * input_stride; - - tmp.val[0] = vsetq_lane_f32(*reinterpret_cast(in.ptr() + offsets_ptr[0] + offset_row), tmp.val[0], 0); - tmp.val[0] = vsetq_lane_f32(*reinterpret_cast(in.ptr() + offsets_ptr[4] + offset_row), tmp.val[0], 1); - tmp.val[0] = vsetq_lane_f32(*reinterpret_cast(in.ptr() + offsets_ptr[8] + offset_row), tmp.val[0], 2); - tmp.val[0] = vsetq_lane_f32(*reinterpret_cast(in.ptr() + offsets_ptr[12] + offset_row), tmp.val[0], 3); - - tmp.val[1] = vsetq_lane_f32(*reinterpret_cast(in.ptr() + offsets_ptr[1] + offset_row), tmp.val[1], 0); - tmp.val[1] = vsetq_lane_f32(*reinterpret_cast(in.ptr() + offsets_ptr[5] + offset_row), tmp.val[1], 1); - tmp.val[1] = vsetq_lane_f32(*reinterpret_cast(in.ptr() + offsets_ptr[9] + offset_row), tmp.val[1], 2); - tmp.val[1] = vsetq_lane_f32(*reinterpret_cast(in.ptr() + offsets_ptr[13] + offset_row), tmp.val[1], 3); - - tmp.val[2] = vsetq_lane_f32(*reinterpret_cast(in.ptr() + offsets_ptr[2] + offset_row), tmp.val[2], 0); - tmp.val[2] = vsetq_lane_f32(*reinterpret_cast(in.ptr() + offsets_ptr[6] + offset_row), tmp.val[2], 1); - tmp.val[2] = vsetq_lane_f32(*reinterpret_cast(in.ptr() + offsets_ptr[10] + offset_row), tmp.val[2], 2); - tmp.val[2] = vsetq_lane_f32(*reinterpret_cast(in.ptr() + offsets_ptr[14] + offset_row), tmp.val[2], 3); - - tmp.val[3] = vsetq_lane_f32(*reinterpret_cast(in.ptr() + offsets_ptr[3] + offset_row), tmp.val[3], 0); - tmp.val[3] = vsetq_lane_f32(*reinterpret_cast(in.ptr() + offsets_ptr[7] + offset_row), tmp.val[3], 1); - tmp.val[3] = vsetq_lane_f32(*reinterpret_cast(in.ptr() + offsets_ptr[11] + offset_row), tmp.val[3], 2); - tmp.val[3] = vsetq_lane_f32(*reinterpret_cast(in.ptr() + offsets_ptr[15] + offset_row), tmp.val[3], 3); - - vst4q_f32(reinterpret_cast(out.ptr()), tmp); - }, - in, offsets, out); - break; - } - default: - ARM_COMPUTE_ERROR("Not supported"); - break; - } -} - -void NEDeconvolutionLayerUpsampleKernel::run(const Window &window, const ThreadInfo &info) -{ - ARM_COMPUTE_UNUSED(info); - ARM_COMPUTE_ERROR_ON_UNCONFIGURED_KERNEL(this); - ARM_COMPUTE_ERROR_ON_INVALID_SUBWINDOW(INEKernel::window(), window); - scale_nearest(window); -} diff --git a/src/core/Utils.cpp b/src/core/Utils.cpp index 76d0b0f059..a8249c4840 100644 --- a/src/core/Utils.cpp +++ b/src/core/Utils.cpp @@ -1,5 +1,5 @@ /* - * Copyright (c) 2016, 2017 ARM Limited. + * Copyright (c) 2016, 2017, 2018 ARM Limited. * * SPDX-License-Identifier: MIT * @@ -261,29 +261,17 @@ TensorShape arm_compute::deconvolution_output_shape(const std::pair arm_compute::deconvolution_output_dimensions( unsigned int in_width, unsigned int in_height, unsigned int kernel_width, unsigned int kernel_height, unsigned int padx, unsigned int pady, - unsigned int ax, unsigned int ay, float upscalex, float upscaley, DimensionRoundingType round) + unsigned int inner_border_right, unsigned int inner_border_top, unsigned int stride_x, unsigned int stride_y) { ARM_COMPUTE_ERROR_ON(in_width < 1 || in_height < 1); - ARM_COMPUTE_ERROR_ON(((in_width - 1) * upscalex + kernel_width + ax) < 2.f * padx); - ARM_COMPUTE_ERROR_ON(((in_height - 1) * upscaley + kernel_height + ay) < 2.f * pady); - const float fw = (in_width - 1) * upscalex - 2.f * padx + kernel_width + ax; - const float fh = (in_height - 1) * upscaley - 2.f * pady + kernel_height + ay; - int w = 0; - int h = 0; - switch(round) - { - case DimensionRoundingType::FLOOR: - w = std::floor(fw); - h = std::floor(fh); - break; - case DimensionRoundingType::CEIL: - w = std::ceil(fw); - h = std::ceil(fh); - break; - default: - ARM_COMPUTE_ERROR("Not supported"); - break; - } + ARM_COMPUTE_ERROR_ON(((in_width - 1) * stride_x + kernel_width + inner_border_right) < 2 * padx); + ARM_COMPUTE_ERROR_ON(((in_height - 1) * stride_y + kernel_height + inner_border_top) < 2 * pady); + const int padx_deconv = (kernel_width - padx - 1); + const int pady_deconv = (kernel_height - pady - 1); + ARM_COMPUTE_ERROR_ON(padx_deconv < 0); + ARM_COMPUTE_ERROR_ON(pady_deconv < 0); + const int w = stride_x * (in_width - 1) + kernel_width + inner_border_right - 2 * padx_deconv; + const int h = stride_y * (in_height - 1) + kernel_height + inner_border_top - 2 * pady_deconv; return std::make_pair(w, h); } diff --git a/src/runtime/CL/functions/CLDeconvolutionLayer.cpp b/src/runtime/CL/functions/CLDeconvolutionLayer.cpp new file mode 100644 index 0000000000..1c55722344 --- /dev/null +++ b/src/runtime/CL/functions/CLDeconvolutionLayer.cpp @@ -0,0 +1,132 @@ +/* + * 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. + */ +#include "arm_compute/runtime/CL/functions/CLDeconvolutionLayer.h" + +#include "arm_compute/core/Helpers.h" +#include "arm_compute/core/Utils.h" +#include "arm_compute/core/Validate.h" +#include "arm_compute/core/utils/misc/ShapeCalculator.h" + +#include +#include + +using namespace arm_compute; +using namespace arm_compute::misc::shape_calculator; + +CLDeconvolutionLayer::CLDeconvolutionLayer(std::shared_ptr memory_manager) // NOLINT + : _memory_group(std::move(memory_manager)), + _scale_f(), + _conv_f(), + _scaled_output() +{ +} + +Status CLDeconvolutionLayer::validate(const ITensorInfo *input, const ITensorInfo *weights, const ITensorInfo *bias, ITensorInfo *output, const PadStrideInfo &info, + unsigned int inner_border_right, unsigned int inner_border_top) +{ + ARM_COMPUTE_RETURN_ERROR_ON_NULLPTR(input, weights, output); + ARM_COMPUTE_RETURN_ERROR_ON_DATA_TYPE_CHANNEL_NOT_IN(input, 1, DataType::F32); + ARM_COMPUTE_RETURN_ERROR_ON(weights->dimension(0) != weights->dimension(1)); + ARM_COMPUTE_RETURN_ERROR_ON(weights->dimension(0) < 1); + + const unsigned int stride_x = info.stride().first; + const unsigned int stride_y = info.stride().second; + + ARM_COMPUTE_RETURN_ERROR_ON_MSG(inner_border_right > stride_x - 1, "inner_border_right must be smaller than stride_x"); + ARM_COMPUTE_RETURN_ERROR_ON_MSG(inner_border_top > stride_y - 1, "inner_border_top must be smaller than stride_y"); + + auto out_dims = deconvolution_output_dimensions(input->dimension(0), input->dimension(1), weights->dimension(0), weights->dimension(1), + info.pad().first, info.pad().second, inner_border_right, inner_border_top, stride_x, stride_y); + + const TensorShape output_shape = deconvolution_output_shape(out_dims, input->tensor_shape(), weights->tensor_shape()); + + ARM_COMPUTE_RETURN_ERROR_ON_MISMATCHING_DATA_TYPES(input, output, weights, bias); + ARM_COMPUTE_RETURN_ERROR_ON_MISMATCHING_FIXED_POINT(input, output, weights, bias); + + if(bias != nullptr) + { + ARM_COMPUTE_RETURN_ERROR_ON_MISMATCHING_DATA_TYPES(input, bias); + ARM_COMPUTE_RETURN_ERROR_ON_MISMATCHING_FIXED_POINT(input, bias); + } + + ARM_COMPUTE_RETURN_ERROR_ON_MSG(output->dimension(Window::DimX) != output_shape.x(), "Output's width is invalid."); + ARM_COMPUTE_RETURN_ERROR_ON_MSG(output->dimension(Window::DimY) != output_shape.y(), "Output's height is invalid."); + ARM_COMPUTE_RETURN_ERROR_ON_MSG(output->dimension(Window::DimZ) != output_shape.z(), "Output's depth is invalid."); + + TensorInfo scale_out_info(input->clone()->set_is_resizable(true).reset_padding().set_tensor_shape(compute_deconvolution_shape(*input, stride_x, stride_y, inner_border_right, inner_border_top, + info))); + const PadStrideInfo conv_info(1, 1, 0, 0, 0, 0, DimensionRoundingType::CEIL); + + ARM_COMPUTE_RETURN_ON_ERROR(CLDeconvolutionLayerUpsample::validate(input, &scale_out_info, BorderSize(inner_border_right, inner_border_top), info)); + ARM_COMPUTE_RETURN_ON_ERROR(CLDirectConvolutionLayer::validate(&scale_out_info, weights, bias, output, conv_info)); + + return Status{}; +} + +void CLDeconvolutionLayer::configure(ICLTensor *input, const ICLTensor *weights, const ICLTensor *bias, ICLTensor *output, const PadStrideInfo &info, + unsigned int inner_border_right, unsigned int inner_border_top) +{ + ARM_COMPUTE_ERROR_ON_NULLPTR(input, weights, output); + + const unsigned int stride_x = info.stride().first; + const unsigned int stride_y = info.stride().second; + + auto out_dims = deconvolution_output_dimensions(input->info()->dimension(0), input->info()->dimension(1), weights->info()->dimension(0), weights->info()->dimension(1), + info.pad().first, info.pad().second, inner_border_top, inner_border_right, stride_x, stride_y); + + const TensorShape output_shape = deconvolution_output_shape(out_dims, input->info()->tensor_shape(), weights->info()->tensor_shape()); + + // Output auto initialization if not yet initialized + auto_init_if_empty(*output->info(), output_shape, 1, input->info()->data_type(), input->info()->fixed_point_position()); + + // Perform validation step + ARM_COMPUTE_ERROR_THROW_ON(CLDeconvolutionLayer::validate(input->info(), weights->info(), bias == nullptr ? nullptr : bias->info(), output->info(), info, inner_border_right, inner_border_top)); + + _memory_group.manage(&_scaled_output); + + // configure scale function + // Init and allocate intermmidiate tensor for output, same size as input but the first two axis are the same as the output tensor + TensorShape scale_out_shape(input->info()->tensor_shape()); + const unsigned int out_x = input->info()->dimension(0) + (input->info()->dimension(0) - 1) * (stride_x - 1) + inner_border_right + 2 * info.pad().first; + const unsigned int out_y = input->info()->dimension(1) + (input->info()->dimension(1) - 1) * (stride_y - 1) + inner_border_top + 2 * info.pad().second; + scale_out_shape.set(0, out_x); + scale_out_shape.set(1, out_y); + TensorInfo scale_out_info(scale_out_shape, 1, input->info()->data_type(), input->info()->fixed_point_position()); + _scaled_output.allocator()->init(scale_out_info); + + _scale_f.configure(input, &_scaled_output, BorderSize(inner_border_top, inner_border_right), info); + + // setup the function to convolve the upscaled output + const PadStrideInfo conv_info(1, 1, 0, 0, 0, 0, DimensionRoundingType::CEIL); + _conv_f.configure(&_scaled_output, weights, bias, output, conv_info); + _scaled_output.allocator()->allocate(); +} + +void CLDeconvolutionLayer::run() +{ + _memory_group.acquire(); + _scale_f.run(); + _conv_f.run(); + _memory_group.release(); +} diff --git a/src/runtime/CL/functions/CLDeconvolutionLayerUpsample.cpp b/src/runtime/CL/functions/CLDeconvolutionLayerUpsample.cpp new file mode 100644 index 0000000000..13a24f8ba4 --- /dev/null +++ b/src/runtime/CL/functions/CLDeconvolutionLayerUpsample.cpp @@ -0,0 +1,64 @@ +/* + * 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. + */ +#include "arm_compute/runtime/CL/functions/CLDeconvolutionLayerUpsample.h" + +#include "arm_compute/core/CL/OpenCL.h" +#include "arm_compute/core/Utils.h" +#include "arm_compute/runtime/CL/CLScheduler.h" + +#include +#include +#include + +using namespace arm_compute; + +CLDeconvolutionLayerUpsample::CLDeconvolutionLayerUpsample() // NOLINT + : _upsample(), + _output(nullptr) +{ +} + +Status CLDeconvolutionLayerUpsample::validate(const ITensorInfo *input, const ITensorInfo *output, const BorderSize &inner_border, + const PadStrideInfo &info) +{ + return CLDeconvolutionLayerUpsampleKernel::validate(input, output, inner_border, info); +} + +void CLDeconvolutionLayerUpsample::configure(ICLTensor *input, ICLTensor *output, const BorderSize &inner_border, + const PadStrideInfo &info) +{ + ARM_COMPUTE_ERROR_ON_NULLPTR(input, output); + + _output = output; + _upsample.configure(input, _output, inner_border, info); +} + +void CLDeconvolutionLayerUpsample::run() +{ + _output->map(CLScheduler::get().queue(), true); + memset(_output->buffer(), 0, _output->info()->total_size()); + _output->unmap(CLScheduler::get().queue()); + + CLScheduler::get().enqueue(_upsample, false); +} diff --git a/src/runtime/NEON/functions/NEDeconvolutionLayer.cpp b/src/runtime/NEON/functions/NEDeconvolutionLayer.cpp index 7b4e77b296..c4bca11d14 100644 --- a/src/runtime/NEON/functions/NEDeconvolutionLayer.cpp +++ b/src/runtime/NEON/functions/NEDeconvolutionLayer.cpp @@ -1,5 +1,5 @@ /* - * Copyright (c) 2017 ARM Limited. + * Copyright (c) 2017, 2018 ARM Limited. * * SPDX-License-Identifier: MIT * @@ -24,38 +24,41 @@ #include "arm_compute/runtime/NEON/functions/NEDeconvolutionLayer.h" #include "arm_compute/core/Helpers.h" -#include "arm_compute/core/PixelValue.h" #include "arm_compute/core/Utils.h" #include "arm_compute/core/Validate.h" +#include "arm_compute/core/utils/misc/ShapeCalculator.h" using namespace arm_compute; +using namespace arm_compute::misc::shape_calculator; NEDeconvolutionLayer::NEDeconvolutionLayer(std::shared_ptr memory_manager) // NOLINT : _memory_group(std::move(memory_manager)), - _scale_f(), _conv_f(), - _scaled_output() + _scaled_output(), + _input(nullptr), + _info(), + _inner_border() { } void NEDeconvolutionLayer::configure(ITensor *input, const ITensor *weights, const ITensor *bias, ITensor *output, const PadStrideInfo &info, - unsigned int ax, unsigned int ay, float upscalex, float upscaley) + unsigned int inner_border_right, unsigned int inner_border_top) { ARM_COMPUTE_ERROR_ON_NULLPTR(output); ARM_COMPUTE_ERROR_ON_DATA_TYPE_CHANNEL_NOT_IN(input, 1, DataType::F32); ARM_COMPUTE_ERROR_ON(weights->info()->dimension(0) != weights->info()->dimension(1)); - ARM_COMPUTE_ERROR_ON(weights->info()->dimension(0) < 1); + ARM_COMPUTE_ERROR_ON(weights->info()->dimension(0) != 1 && weights->info()->dimension(0) != 3 && weights->info()->dimension(0) != 5); - auto out_dims = deconvolution_output_dimensions(input->info()->dimension(0), input->info()->dimension(1), weights->info()->dimension(0), weights->info()->dimension(1), - info.pad().first, info.pad().second, ax, ay, upscalex, upscaley, info.round()); + _input = input; + _info = info; + _inner_border = std::make_pair(inner_border_right, inner_border_top); - const TensorShape output_shape = deconvolution_output_shape(out_dims, input->info()->tensor_shape(), weights->info()->tensor_shape()); - - // Output auto initialization if not yet initialized - auto_init_if_empty(*output->info(), output_shape, 1, input->info()->data_type(), input->info()->fixed_point_position()); + const unsigned int stride_x = info.stride().first; + const unsigned int stride_y = info.stride().second; + auto out_dims = deconvolution_output_dimensions(input->info()->dimension(0), input->info()->dimension(1), weights->info()->dimension(0), weights->info()->dimension(1), + info.pad().first, info.pad().second, inner_border_right, inner_border_top, stride_x, stride_y); - ARM_COMPUTE_ERROR_ON_MISMATCHING_DATA_TYPES(input, output, weights, bias); - ARM_COMPUTE_ERROR_ON_MISMATCHING_FIXED_POINT(input, output, weights, bias); + const TensorShape output_shape = deconvolution_output_shape(out_dims, input->info()->tensor_shape(), weights->info()->tensor_shape()); ARM_COMPUTE_ERROR_ON_MSG(output->info()->dimension(Window::DimX) != output_shape.x(), "Output's width is invalid."); ARM_COMPUTE_ERROR_ON_MSG(output->info()->dimension(Window::DimY) != output_shape.y(), "Output's height is invalid."); @@ -64,51 +67,51 @@ void NEDeconvolutionLayer::configure(ITensor *input, const ITensor *weights, con _memory_group.manage(&_scaled_output); // configure scale function - //Init and allocate intermmidiate tensor for output, same size as input but the first two axis are the same as the output tensor - TensorShape scale_out_shape(input->info()->tensor_shape()); - scale_out_shape.set(0, output->info()->dimension(0)); - scale_out_shape.set(1, output->info()->dimension(1)); - TensorInfo scale_out_info(scale_out_shape, 1, input->info()->data_type(), input->info()->fixed_point_position()); + // Init and allocate intermmidiate tensor for output, same size as input but the first two axis are the same as the output tensor + const TensorInfo scale_out_info(compute_deconvolution_shape(*input->info(), stride_x, stride_y, inner_border_right, inner_border_top, info), 1, input->info()->data_type(), + input->info()->fixed_point_position()); _scaled_output.allocator()->init(scale_out_info); - const unsigned int kernel_size = weights->info()->dimension(0); - // Padding for the upsampled image is calculated with the equiation: p' = k - p - 1, where k is kernel size and p is the input padding - ARM_COMPUTE_ERROR_ON(info.pad().first > (kernel_size - 1)); - const unsigned int tr_px = kernel_size - info.pad().first - 1; - const unsigned int tr_py = kernel_size - info.pad().second - 1; - const unsigned int tr_stride = 1; - const PadStrideInfo transposed_info(tr_stride, tr_stride, tr_px, tr_py); - _scale_f.configure(input, &_scaled_output, std::make_pair(ax, ay), std::make_pair(info.stride().first - 1u, info.stride().second - 1u), transposed_info); + // setup the function to convolve the upscaled output - switch(kernel_size) - { - case 1: - { - _conv_f.configure(&_scaled_output, weights, bias, output, PadStrideInfo(1, 1, 0, 0, DimensionRoundingType::CEIL)); - break; - } - case 3: - { - _conv_f.configure(&_scaled_output, weights, bias, output, PadStrideInfo(1, 1, 1, 1, DimensionRoundingType::CEIL)); - break; - } - case 5: - { - _conv_f.configure(&_scaled_output, weights, bias, output, PadStrideInfo(1, 1, 2, 2, DimensionRoundingType::CEIL)); - break; - } - default: - { - ARM_COMPUTE_ERROR("Not supported"); - break; - } - } + const PadStrideInfo conv_info(1, 1, 0, 0, 0, 0, DimensionRoundingType::CEIL); + _conv_f.configure(&_scaled_output, weights, bias, output, conv_info); _scaled_output.allocator()->allocate(); } void NEDeconvolutionLayer::run() { _memory_group.acquire(); - _scale_f.run(); + + // Initialize _scaled_output buffer + const int width_in = _input->info()->dimension(0); + const int height_in = _input->info()->dimension(1); + const int width_scaled = _scaled_output.info()->dimension(0); + const int height_scaled = _scaled_output.info()->dimension(1); + const int num_2d_slices = _input->info()->tensor_shape().total_size() / (width_in * height_in); + const int stride_x = _info.stride().first; + const int stride_y = _info.stride().second; + + std::fill_n(reinterpret_cast(_scaled_output.buffer()), _scaled_output.info()->tensor_shape().total_size(), 0.f); + + // scaled_output is the input for the forward convolution. We copy the input elements to scaled_output + // and insert rows and columns with zeroes depending on the stride values. + for(int slice = 0; slice < num_2d_slices; ++slice) + { + const int start_x = _info.pad().first; + const int start_y = _inner_border.second + _info.pad().second; + const int end_y = height_scaled - _info.pad().second; + const int end_x = width_scaled - _inner_border.first - _info.pad().first; + + for(int yi = start_y, in_y = 0; yi < end_y; yi += stride_y, in_y++) + { + for(int xi = start_x, in_x = 0; xi < end_x; xi += stride_x, in_x++) + { + const auto in = *(reinterpret_cast(_input->buffer() + _input->info()->offset_element_in_bytes(Coordinates(in_x, in_y, slice)))); + *(reinterpret_cast(_scaled_output.buffer() + _scaled_output.info()->offset_element_in_bytes(Coordinates(xi, yi, slice)))) = in; + } + } + } + _conv_f.run(); _memory_group.release(); } diff --git a/src/runtime/NEON/functions/NEDeconvolutionLayerUpsample.cpp b/src/runtime/NEON/functions/NEDeconvolutionLayerUpsample.cpp deleted file mode 100644 index 63f17bcb5a..0000000000 --- a/src/runtime/NEON/functions/NEDeconvolutionLayerUpsample.cpp +++ /dev/null @@ -1,121 +0,0 @@ -/* - * Copyright (c) 2016, 2017 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. - */ -#include "arm_compute/runtime/NEON/functions/NEDeconvolutionLayerUpsample.h" - -#include "arm_compute/core/Coordinates.h" -#include "arm_compute/core/Error.h" -#include "arm_compute/core/Helpers.h" -#include "arm_compute/core/ITensor.h" -#include "arm_compute/core/NEON/kernels/NEDeconvolutionLayerUpsampleKernel.h" -#include "arm_compute/core/PixelValue.h" -#include "arm_compute/core/TensorInfo.h" -#include "arm_compute/core/Window.h" -#include "arm_compute/runtime/NEON/NEScheduler.h" -#include "arm_compute/runtime/TensorAllocator.h" -#include "support/ToolchainSupport.h" - -#include -#include -#include - -using namespace arm_compute; - -namespace -{ -inline void precompute_offsets(ITensor *offsets, float wr, size_t input_element_size, const std::pair &a, - const std::pair &iz, const PadStrideInfo &info) -{ - ARM_COMPUTE_ERROR_ON(nullptr == offsets); - Window win; - const int padx = info.pad().first; - const int pady = info.pad().second; - const int ax = a.first; - const int ay = a.second; - const int offset_width = offsets->info()->dimension(0); - const int offset_height = offsets->info()->dimension(1); - // The values of ax and ay denote the number of ZEROS to be added on the top and right inner border of the image. - // Step value along the XY axis will depend on the number of zeros to be inserted between samples (number of zeros + 1). - // Pre-compute the X offset, Y's stride is unknown at this point so we can't precompute Y's offsets - for(int yi = ay; yi < (offset_height - pady); yi += (1 + iz.second)) - { - for(int xi = padx; xi < (offset_width - ax); xi += (1 + iz.first)) - { - int *ptr = reinterpret_cast(offsets->ptr_to_element(Coordinates(xi, yi))); - const size_t in_xi = (xi + 0.5f) * wr; - *reinterpret_cast(ptr) = in_xi * input_element_size; - } - } -} -} // namespace - -NEDeconvolutionLayerUpsample::NEDeconvolutionLayerUpsample(std::shared_ptr memory_manager) // NOLINT - : _memory_group(std::move(memory_manager)), - _offsets(), - _border_handler(), - _upsample() -{ -} - -void NEDeconvolutionLayerUpsample::configure(ITensor *input, ITensor *output, const std::pair &a, - const std::pair &iz, const PadStrideInfo &info) -{ - ARM_COMPUTE_ERROR_ON(nullptr == input); - ARM_COMPUTE_ERROR_ON(nullptr == output); - - for(size_t i = 2; i < Coordinates::num_max_dimensions; ++i) - { - ARM_COMPUTE_ERROR_ON(input->info()->dimension(i) != output->info()->dimension(i)); - } - - // Get the tensor shape - const TensorShape shape(output->info()->dimension(0), output->info()->dimension(1)); - - // Compute the ratio between source width/height and destination width/height - const auto wr = static_cast(input->info()->dimension(0)) / static_cast(output->info()->dimension(0)); - const auto hr = static_cast(input->info()->dimension(1)) / static_cast(output->info()->dimension(1)); - ARM_COMPUTE_UNUSED(hr); - // Get the element size of the input image - const size_t input_element_size = input->info()->element_size(); - - TensorInfo tensor_info_offsets(shape, Format::S32); - _offsets.allocator()->init(tensor_info_offsets); - - _upsample.configure(input, &_offsets, output); - - // Allocate once the configure methods have been called - _offsets.allocator()->allocate(); - // Pre-compute offsets for nearest interpolation - std::fill_n(reinterpret_cast(_offsets.buffer()), _offsets.info()->total_size() / sizeof(int32_t), -1 * input_element_size); - precompute_offsets(&_offsets, wr, input_element_size, a, iz, info); - - _border_handler.configure(input, _upsample.border_size(), BorderMode::CONSTANT, PixelValue(0)); -} - -void NEDeconvolutionLayerUpsample::run() -{ - NEScheduler::get().schedule(&_border_handler, Window::DimZ); - _memory_group.acquire(); - NEScheduler::get().schedule(&_upsample, Window::DimY); - _memory_group.release(); -} diff --git a/tests/datasets/ShapeDatasets.h b/tests/datasets/ShapeDatasets.h index 58fba07bf8..a5e03c737f 100644 --- a/tests/datasets/ShapeDatasets.h +++ b/tests/datasets/ShapeDatasets.h @@ -1,5 +1,5 @@ /* - * Copyright (c) 2017 ARM Limited. + * Copyright (c) 2017, 2018 ARM Limited. * * SPDX-License-Identifier: MIT * @@ -239,7 +239,7 @@ public: SmallDeconvolutionShapes() : ShapeDataset("InputShape", { - TensorShape{ 2U, 3U, 3U, 2U }, + TensorShape{ 4U, 3U, 3U, 2U }, TensorShape{ 5U, 5U, 3U }, TensorShape{ 11U, 13U, 4U, 3U } }) diff --git a/tests/validation/CL/DeconvolutionLayer.cpp b/tests/validation/CL/DeconvolutionLayer.cpp new file mode 100644 index 0000000000..59e85537e5 --- /dev/null +++ b/tests/validation/CL/DeconvolutionLayer.cpp @@ -0,0 +1,192 @@ +/* + * 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. + */ +#include "arm_compute/core/CL/kernels/CLFillBorderKernel.h" +#include "arm_compute/core/Types.h" +#include "arm_compute/runtime/CL/CLTensor.h" +#include "arm_compute/runtime/CL/CLTensorAllocator.h" +#include "arm_compute/runtime/CL/functions/CLDeconvolutionLayer.h" +#include "tests/CL/CLAccessor.h" +#include "tests/PaddingCalculator.h" +#include "tests/datasets/ShapeDatasets.h" +#include "tests/framework/Asserts.h" +#include "tests/framework/Macros.h" +#include "tests/framework/datasets/Datasets.h" +#include "tests/validation/Validation.h" +#include "tests/validation/fixtures/DeconvolutionLayerFixture.h" + +namespace arm_compute +{ +namespace test +{ +namespace validation +{ +namespace +{ +constexpr AbsoluteTolerance tolerance_fp32(0.001f); /**< Tolerance for floating point tests */ + +const auto data3x3 = datasets::SmallDeconvolutionShapes() * framework::dataset::make("StrideX", 1, 4) * framework::dataset::make("StrideY", 1, 4) * framework::dataset::make("PadX", 0, 2) + * framework::dataset::make("PadY", 0, 2) * framework::dataset::make("ax", 0) * framework::dataset::make("ay", 0) * framework::dataset::make("NumKernels", { 1, 3 }); + +const auto data1x1 = datasets::SmallDeconvolutionShapes() * framework::dataset::make("StrideX", 1, 4) * framework::dataset::make("StrideY", 1, 4) * framework::dataset::make("PadX", 0, 1) + * framework::dataset::make("PadY", 0, 1) * framework::dataset::make("ax", 0) * framework::dataset::make("ay", 0) * framework::dataset::make("NumKernels", { 1, 3 }); + +} // namespace + +TEST_SUITE(CL) +TEST_SUITE(DeconvolutionLayer) + +DATA_TEST_CASE(Configuration, framework::DatasetMode::ALL, (combine(datasets::SmallDeconvolutionShapes(), framework::dataset::make("DataType", DataType::F32))), + input_shape, data_type) +{ + // Create shapes + const unsigned int kernel_size_x = 3; + const unsigned int kernel_size_y = 3; + const unsigned int num_kernels = 1; + const TensorShape weights_shape(kernel_size_x, kernel_size_y, input_shape.z(), num_kernels); + const TensorShape bias_shape(num_kernels); + auto out_dim = deconvolution_output_dimensions(input_shape.x(), input_shape.y(), kernel_size_x, kernel_size_y, 1, 1, 0, 0, 1, 1); + TensorShape output_shape = deconvolution_output_shape(out_dim, input_shape, weights_shape); + + // Create tensors + CLTensor src = create_tensor(input_shape, data_type, 1); + CLTensor weights = create_tensor(weights_shape, data_type, 1); + CLTensor bias = create_tensor(bias_shape, data_type, 1); + CLTensor dst = create_tensor(output_shape, data_type, 1); + + ARM_COMPUTE_EXPECT(src.info()->is_resizable(), framework::LogLevel::ERRORS); + ARM_COMPUTE_EXPECT(weights.info()->is_resizable(), framework::LogLevel::ERRORS); + ARM_COMPUTE_EXPECT(bias.info()->is_resizable(), framework::LogLevel::ERRORS); + ARM_COMPUTE_EXPECT(dst.info()->is_resizable(), framework::LogLevel::ERRORS); + + // Create and configure function + CLDeconvolutionLayer deconv; + deconv.configure(&src, &weights, &bias, &dst, PadStrideInfo(1, 1, 1, 1, DimensionRoundingType::CEIL), 0, 0); + + // Validate valid region + const ValidRegion src_valid_region = shape_to_valid_region(input_shape); + const ValidRegion weights_valid_region = shape_to_valid_region(weights_shape); + const ValidRegion bias_valid_region = shape_to_valid_region(bias_shape); + const ValidRegion dst_valid_region = shape_to_valid_region(output_shape); + + validate(src.info()->valid_region(), src_valid_region); + validate(weights.info()->valid_region(), weights_valid_region); + validate(bias.info()->valid_region(), bias_valid_region); + validate(dst.info()->valid_region(), dst_valid_region); +} + +// *INDENT-OFF* +// clang-format off +DATA_TEST_CASE(Validate, framework::DatasetMode::ALL, zip(zip(zip(zip(zip(zip(zip( + framework::dataset::make("InputInfo", { TensorInfo(TensorShape(27U, 13U, 2U), 1, DataType::F32, 0), // Mismatching data type + TensorInfo(TensorShape(27U, 13U, 2U), 1, DataType::F32, 0), // Invalid weights shape + TensorInfo(TensorShape(27U, 13U, 2U), 1, DataType::QS8, 4), // Non supported data type + TensorInfo(TensorShape(27U, 13U, 2U), 1, DataType::F32, 11), // Invalid bias shape + TensorInfo(TensorShape(13U, 11U, 4U, 3U), 1, DataType::F32, 0), // Window shrink + TensorInfo(TensorShape(32U, 16U, 2U), 1, DataType::F32, 0), + }), + framework::dataset::make("WeightsInfo", { TensorInfo(TensorShape(3U, 3U, 2U, 2U), 1, DataType::F16, 0), + TensorInfo(TensorShape(3U, 3U, 2U, 4U), 1, DataType::F32, 0), + TensorInfo(TensorShape(3U, 3U, 2U, 2U), 1, DataType::QS8, 5), + TensorInfo(TensorShape(3U, 2U, 2U, 2U), 1, DataType::F32, 11), + TensorInfo(TensorShape(3U, 3U, 4U), 1, DataType::F32, 0), + TensorInfo(TensorShape(1U, 1U, 2U, 4U), 1, DataType::F32, 0), + })), + framework::dataset::make("BiasInfo", { TensorInfo(TensorShape(1U), 1, DataType::F16, 0), + TensorInfo(TensorShape(1U), 1, DataType::F32, 0), + TensorInfo(TensorShape(1U), 1, DataType::F32, 5), + TensorInfo(TensorShape(25U, 11U), 1, DataType::F32, 11), + TensorInfo(TensorShape(1U), 1, DataType::F32, 0), + TensorInfo(TensorShape(4U), 1, DataType::F32, 0), + })), + framework::dataset::make("OutputInfo",{ TensorInfo(TensorShape(25U, 11U, 2U), 1, DataType::F16, 0), + TensorInfo(TensorShape(25U, 10U, 2U), 1, DataType::F32, 0), + TensorInfo(TensorShape(25U, 11U, 2U), 1, DataType::F32, 5), + TensorInfo(TensorShape(13U, 13U, 2U), 1, DataType::F32, 0), + TensorInfo(TensorShape(11U, 9U, 1U, 3U), 1, DataType::F32, 0), + TensorInfo(TensorShape(32U, 16U, 4U), 1, DataType::F32, 0), + })), + framework::dataset::make("PadStrideInfo", { PadStrideInfo(1, 1, 0, 0), + PadStrideInfo(1, 1, 0, 0), + PadStrideInfo(1, 1, 0, 0), + PadStrideInfo(1, 1, 0, 0), + PadStrideInfo(1, 1, 1, 1), + PadStrideInfo(1, 1, 0, 0), + })), + framework::dataset::make("ax", { 1U, + 1U, + 1U, + 1U, + 0U, + 0U, + })), + framework::dataset::make("ay", { 1U, + 1U, + 1U, + 1U, + 0U, + 0U, + })), + framework::dataset::make("Expected", { false, false, false, false, false, true })), + input_info, weights_info, bias_info, output_info, pad_info, ax, ay, expected) +{ + bool is_valid = bool(CLDeconvolutionLayer::validate(&input_info.clone()->set_is_resizable(false), &weights_info.clone()->set_is_resizable(false), &bias_info.clone()->set_is_resizable(false), &output_info.clone()->set_is_resizable(false), pad_info, ax, ay)); + ARM_COMPUTE_EXPECT(is_valid == expected, framework::LogLevel::ERRORS); +} +// clang-format on +// *INDENT-ON* + +template +using CLDeconvolutionLayerFixture3x3 = DeconvolutionValidationFixture; + +template +using CLDeconvolutionLayerFixture1x1 = DeconvolutionValidationFixture; + +TEST_SUITE(Float) + +TEST_SUITE(FP32) +TEST_SUITE(W3x3) + +FIXTURE_DATA_TEST_CASE(Run, CLDeconvolutionLayerFixture3x3, framework::DatasetMode::ALL, combine(data3x3, framework::dataset::make("DataType", DataType::F32))) +{ + // Validate output + validate(CLAccessor(_target), _reference, tolerance_fp32); +} +TEST_SUITE_END() + +TEST_SUITE(W1x1) +FIXTURE_DATA_TEST_CASE(Run, CLDeconvolutionLayerFixture1x1, framework::DatasetMode::ALL, combine(data1x1, framework::dataset::make("DataType", DataType::F32))) +{ + // Validate output + validate(CLAccessor(_target), _reference, tolerance_fp32); +} +TEST_SUITE_END() + +TEST_SUITE_END() +TEST_SUITE_END() + +TEST_SUITE_END() +TEST_SUITE_END() +} // namespace validation +} // namespace test +} // namespace arm_compute diff --git a/tests/validation/NEON/DeconvolutionLayer.cpp b/tests/validation/NEON/DeconvolutionLayer.cpp index 751a96558a..9573784d86 100644 --- a/tests/validation/NEON/DeconvolutionLayer.cpp +++ b/tests/validation/NEON/DeconvolutionLayer.cpp @@ -1,5 +1,5 @@ /* - * Copyright (c) 2017 ARM Limited. + * Copyright (c) 2017, 2018 ARM Limited. * * SPDX-License-Identifier: MIT * @@ -44,15 +44,11 @@ namespace { constexpr AbsoluteTolerance tolerance_fp32(0.001f); /**< Tolerance for floating point tests */ -const auto data3x3 = datasets::SmallDeconvolutionShapes() * framework::dataset::make("StrideX", 1, 4) * framework::dataset::make("StrideY", 1, 4) * framework::dataset::make("PadX", 0, - 2) - * framework::dataset::make("PadY", 0, 2) * framework::dataset::make("ax", 1, 3) * framework::dataset::make("ay", 1, 3) * framework::dataset::make("NumKernels", { 1, 3 }) - *framework::dataset::make("ux", 1, 4) *framework::dataset::make("uy", 1, 4); +const auto data3x3 = datasets::SmallDeconvolutionShapes() * framework::dataset::make("StrideX", 1, 4) * framework::dataset::make("StrideY", 1, 4) * framework::dataset::make("PadX", 0, 2) + * framework::dataset::make("PadY", 0, 2) * framework::dataset::make("ax", 0) * framework::dataset::make("ay", 0) * framework::dataset::make("NumKernels", { 1, 3 }); -const auto data1x1 = datasets::SmallDeconvolutionShapes() * framework::dataset::make("StrideX", 1, 4) * framework::dataset::make("StrideY", 1, 4) * framework::dataset::make("PadX", 0, - 1) - * framework::dataset::make("PadY", 0, 1) * framework::dataset::make("ax", 1, 3) * framework::dataset::make("ay", 1, 3) * framework::dataset::make("NumKernels", { 1, 3 }) - *framework::dataset::make("ux", 1, 4) *framework::dataset::make("uy", 1, 4); +const auto data1x1 = datasets::SmallDeconvolutionShapes() * framework::dataset::make("StrideX", 1, 4) * framework::dataset::make("StrideY", 1, 4) * framework::dataset::make("PadX", 0, 1) + * framework::dataset::make("PadY", 0, 1) * framework::dataset::make("ax", 0) * framework::dataset::make("ay", 0) * framework::dataset::make("NumKernels", { 1, 3 }); } // namespace diff --git a/tests/validation/fixtures/DeconvolutionLayerFixture.h b/tests/validation/fixtures/DeconvolutionLayerFixture.h index e98f5e93c0..f2455f31ac 100644 --- a/tests/validation/fixtures/DeconvolutionLayerFixture.h +++ b/tests/validation/fixtures/DeconvolutionLayerFixture.h @@ -1,5 +1,5 @@ /* - * Copyright (c) 2017 ARM Limited. + * Copyright (c) 2017, 2018 ARM Limited. * * SPDX-License-Identifier: MIT * @@ -43,20 +43,15 @@ template void setup(TensorShape input_shape, TensorShape weights_shape, TensorShape bias_shape, TensorShape output_shape, PadStrideInfo info, - const std::pair &a, const std::pair &u, DataType data_type, int fractional_bits) + const std::pair &inner_border, DataType data_type, int fractional_bits) { _fractional_bits = fractional_bits; _data_type = data_type; - _target = compute_target(input_shape, weights_shape, bias_shape, output_shape, info, a, u, data_type, fractional_bits); - _reference = compute_reference(input_shape, weights_shape, bias_shape, output_shape, info, a, data_type, fractional_bits); + _target = compute_target(input_shape, weights_shape, bias_shape, output_shape, info, inner_border, data_type, fractional_bits); + _reference = compute_reference(input_shape, weights_shape, bias_shape, output_shape, info, inner_border, data_type, fractional_bits); } protected: @@ -75,13 +70,9 @@ protected: library->fill_tensor_uniform(tensor, i); } } - /* - * - * @param[in] a The number of zeros added to right and bottom edges of the input. - * @param[in] u How much to scale the X and Y axis. - */ + TensorType compute_target(const TensorShape &input_shape, const TensorShape &weights_shape, const TensorShape &bias_shape, const TensorShape &output_shape, - const PadStrideInfo &info, const std::pair &a, const std::pair &u, DataType data_type, int fixed_point_position) + const PadStrideInfo &info, const std::pair &inner_border, DataType data_type, int fixed_point_position) { // Create tensors TensorType src = create_tensor(input_shape, data_type, 1, fixed_point_position); @@ -91,7 +82,7 @@ protected: // Create and configure function FunctionType conv; - conv.configure(&src, &weights, &bias, &dst, info, a.first, a.second, u.first, u.second); + conv.configure(&src, &weights, &bias, &dst, info, inner_border.first, inner_border.second); ARM_COMPUTE_EXPECT(src.info()->is_resizable(), framework::LogLevel::ERRORS); ARM_COMPUTE_EXPECT(weights.info()->is_resizable(), framework::LogLevel::ERRORS); @@ -121,7 +112,7 @@ protected: } SimpleTensor compute_reference(const TensorShape &input_shape, const TensorShape &weights_shape, const TensorShape &bias_shape, const TensorShape &output_shape, - const PadStrideInfo &info, const std::pair a, DataType data_type, int fixed_point_position) + const PadStrideInfo &info, const std::pair inner_border, DataType data_type, int fixed_point_position) { // Create reference SimpleTensor src{ input_shape, data_type, 1, fixed_point_position }; @@ -133,7 +124,7 @@ protected: fill(weights, 1); fill(bias, 2); - return reference::deconvolution_layer(src, weights, bias, output_shape, info, a); + return reference::deconvolution_layer(src, weights, bias, output_shape, info, inner_border); } TensorType _target{}; @@ -148,18 +139,16 @@ class DeconvolutionValidationFixture : public DeconvolutionLayerFixtureBase void setup(TensorShape input_shape, unsigned int sx, unsigned int sy, unsigned int padx, unsigned int pady, - unsigned int ax, unsigned int ay, unsigned int ux, unsigned int uy, unsigned int num_kernels, DataType data_type) + unsigned int inner_border_right, unsigned int inner_border_top, unsigned int num_kernels, DataType data_type) { ARM_COMPUTE_ERROR_ON_MSG(kernel_size_x != kernel_size_y, "Only square kernels supported"); const TensorShape weights_shape(kernel_size_x, kernel_size_y, input_shape.z(), num_kernels); const TensorShape bias_shape(num_kernels); const PadStrideInfo info(sx, sy, padx, pady, DimensionRoundingType::CEIL); - const std::pair a(ax, ay); - const std::pair u(ux, uy); - auto out_dim = deconvolution_output_dimensions(input_shape.x(), input_shape.y(), kernel_size_x, kernel_size_y, padx, pady, a.first, a.second, u.first, u.second, - DimensionRoundingType::CEIL); + const std::pair inner_border(inner_border_right, inner_border_top); + auto out_dim = deconvolution_output_dimensions(input_shape.x(), input_shape.y(), kernel_size_x, kernel_size_y, padx, pady, inner_border.first, inner_border.second, sx, sy); TensorShape output_shape = deconvolution_output_shape(out_dim, input_shape, weights_shape); - DeconvolutionLayerFixtureBase::setup(input_shape, weights_shape, bias_shape, output_shape, info, a, u, data_type, 0); + DeconvolutionLayerFixtureBase::setup(input_shape, weights_shape, bias_shape, output_shape, info, inner_border, data_type, 0); } }; diff --git a/tests/validation/reference/DeconvolutionLayer.cpp b/tests/validation/reference/DeconvolutionLayer.cpp index 82c2188ade..0cf1087346 100644 --- a/tests/validation/reference/DeconvolutionLayer.cpp +++ b/tests/validation/reference/DeconvolutionLayer.cpp @@ -1,5 +1,5 @@ /* - * Copyright (c) 2017 ARM Limited. + * Copyright (c) 2017, 2018 ARM Limited. * * SPDX-License-Identifier: MIT * @@ -39,26 +39,27 @@ SimpleTensor deconvolution_layer(const SimpleTensor &src, const SimpleTens const PadStrideInfo &info, const std::pair &a) { // Create reference + const int stride_x = info.stride().first; + const int stride_y = info.stride().second; TensorShape scaled_shape = src.shape(); - scaled_shape.set(0, output_shape.x()); - scaled_shape.set(1, output_shape.y()); + int out_x = src.shape().x() + (src.shape().x() - 1) * (stride_x - 1) + a.first + 2 * info.pad().first; + int out_y = src.shape().y() + (src.shape().y() - 1) * (stride_y - 1) + a.second + 2 * info.pad().second; + scaled_shape.set(0, out_x); + scaled_shape.set(1, out_y); SimpleTensor scaled{ scaled_shape, src.data_type(), 1, src.fixed_point_position() }; - const int width_in = src.shape().x(); - const int height_in = src.shape().y(); - const int width_scaled = scaled.shape().x(); - const int height_scaled = scaled.shape().y(); - const int num_2d_slices = src.shape().total_size() / (width_in * height_in); - const float width_ratio = static_cast(width_in) / static_cast(width_scaled); - const float height_ratio = static_cast(height_in) / static_cast(height_scaled); - const int ax = a.first; // The number of zeros added to right edge of the input. - const int ay = a.second; // The number of zeros added to bottom edge of the input. - const unsigned int kernel_size = weights.shape().x(); - ARM_COMPUTE_ERROR_ON(info.pad().first > (kernel_size - 1)); - const int transposed_convolution_padx = kernel_size - info.pad().first - 1; - const int transposed_convolution_pady = kernel_size - info.pad().second - 1; - const int stridex = info.stride().first; - const int stridey = info.stride().second; + const int width_in = src.shape().x(); + const int height_in = src.shape().y(); + const int width_scaled = scaled.shape().x(); + const int height_scaled = scaled.shape().y(); + const int num_2d_slices = src.shape().total_size() / (width_in * height_in); + const int ax = a.first; // The number of zeros added to right edge of the input. + const int ay = a.second; // The number of zeros added to top edge of the input. + ARM_COMPUTE_ERROR_ON(info.pad().first > (weights.shape().x() - 1)); + + ARM_COMPUTE_ERROR_ON_MSG(ax > stride_x - 1, "ax must be smaller than stride_x"); + ARM_COMPUTE_ERROR_ON_MSG(ay > stride_y - 1, "ay must be smaller than stride_y"); + for(int j = 0; j < scaled.num_elements(); ++j) { scaled[j] = T(0); @@ -68,34 +69,23 @@ SimpleTensor deconvolution_layer(const SimpleTensor &src, const SimpleTens { const int offset_slice_in = slice * width_in * height_in; const int offset_slice_out = slice * width_scaled * height_scaled; - for(int yi = ay; yi < height_scaled; yi += stridey) + const int start_x = info.pad().first; + const int start_y = ay + info.pad().second; + const int end_y = height_scaled - info.pad().second; + const int end_x = width_scaled - ax - info.pad().first; + + for(int yi = start_y, in_y = 0; yi < end_y; yi += stride_y, in_y++) { - for(int xi = transposed_convolution_padx; xi < width_scaled; xi += stridex) + for(int xi = start_x, in_x = 0; xi < end_x; xi += stride_x, in_x++) { - const float x_src = (xi + 0.5f) * width_ratio - 0.5f; - const float y_src = (yi + 0.5f) * height_ratio - 0.5f; - T *out = scaled.data() + offset_slice_out + xi + yi * width_scaled; - const bool in_bounds = x_src > -1 && y_src > -1 && x_src < width_in && y_src < height_in; - const bool in_axy = xi < transposed_convolution_padx || xi >= (width_scaled - ax) // this is checking if the x coordinate is in the padded left/right area - || yi < ay || yi >= (height_scaled - transposed_convolution_pady); // like above but top and bottom padding in the upscaled XY plane - if(!in_axy) - { - if(in_bounds) - { - const int in_scaled_x = (x_src < 0.f) ? static_cast(x_src - 0.5f) : static_cast(x_src + 0.5f); - const int in_scaled_y = (y_src < 0.f) ? static_cast(y_src - 0.5f) : static_cast(y_src + 0.5f); - const T *in = src.data() + offset_slice_in + in_scaled_x + in_scaled_y * width_in; - *out = *in; - } - else - { - *out = T(0); - } - } + const T *in = src.data() + offset_slice_in + in_y * width_in + in_x; + T *out = scaled.data() + offset_slice_out + xi + yi * width_scaled; + *out = *in; } } } - const PadStrideInfo conv_info(1, 1, 1, 1, DimensionRoundingType::CEIL); + + const PadStrideInfo conv_info(1, 1, 0, 0, 0, 0, DimensionRoundingType::CEIL); return convolution_layer(scaled, weights, bias, output_shape, conv_info); } diff --git a/tests/validation/reference/DeconvolutionLayer.h b/tests/validation/reference/DeconvolutionLayer.h index 8222e32027..c0bc1fa928 100644 --- a/tests/validation/reference/DeconvolutionLayer.h +++ b/tests/validation/reference/DeconvolutionLayer.h @@ -1,5 +1,5 @@ /* - * Copyright (c) 2017 ARM Limited. + * Copyright (c) 2017, 2018 ARM Limited. * * SPDX-License-Identifier: MIT * @@ -42,7 +42,7 @@ namespace reference * bias Optional, ignored if NULL. The biases have one dimension. Data type supported: Same as @p input. * output_shape Output tensor shape. The output has the same number of dimensions as the @p input. * info Contains padding and policies to be used in the deconvolution, this is decribed in @ref PadStrideInfo. - * a The number of zeros added to right edge of the input. + * a The number of zeros added to right and top edges of the input. * */ template -- cgit v1.2.1