diff options
-rw-r--r-- | Android.bp | 21 | ||||
-rw-r--r-- | arm_compute/runtime/NEON/functions/NECropResize.h | 3 | ||||
-rw-r--r-- | arm_compute/runtime/NEON/functions/NEScale.h | 30 | ||||
-rw-r--r-- | docs/00_introduction.dox | 10 | ||||
-rw-r--r-- | src/core/NEON/NEKernels.h | 1 | ||||
-rw-r--r-- | src/core/NEON/kernels/NEScaleKernel.h | 122 | ||||
-rw-r--r-- | src/core/cpu/kernels/CpuScaleKernel.cpp (renamed from src/core/NEON/kernels/NEScaleKernel.cpp) | 287 | ||||
-rw-r--r-- | src/core/cpu/kernels/CpuScaleKernel.h | 111 | ||||
-rw-r--r-- | src/core/cpu/kernels/scale/neon/fp16.cpp (renamed from src/core/NEON/kernels/scale/impl/NEON/fp16.cpp) | 0 | ||||
-rw-r--r-- | src/core/cpu/kernels/scale/neon/integer.cpp (renamed from src/core/NEON/kernels/scale/impl/NEON/integer.cpp) | 0 | ||||
-rw-r--r-- | src/core/cpu/kernels/scale/neon/list.h (renamed from src/core/NEON/kernels/scale/impl/NEON/list.h) | 0 | ||||
-rw-r--r-- | src/core/cpu/kernels/scale/neon/qasymm8.cpp (renamed from src/core/NEON/kernels/scale/impl/NEON/qasymm8.cpp) | 38 | ||||
-rw-r--r-- | src/core/cpu/kernels/scale/neon/qasymm8_signed.cpp (renamed from src/core/NEON/kernels/scale/impl/NEON/qasymm8_signed.cpp) | 38 | ||||
-rw-r--r-- | src/core/cpu/kernels/scale/sve/fp16.cpp (renamed from src/core/NEON/kernels/scale/impl/SVE/fp16.cpp) | 0 | ||||
-rw-r--r-- | src/core/cpu/kernels/scale/sve/fp32.cpp (renamed from src/core/NEON/kernels/scale/impl/SVE/fp32.cpp) | 0 | ||||
-rw-r--r-- | src/core/cpu/kernels/scale/sve/integer.cpp (renamed from src/core/NEON/kernels/scale/impl/SVE/integer.cpp) | 0 | ||||
-rw-r--r-- | src/core/cpu/kernels/scale/sve/list.h (renamed from src/core/NEON/kernels/scale/impl/SVE/list.h) | 0 | ||||
-rw-r--r-- | src/core/cpu/kernels/scale/sve/qasymm8.cpp (renamed from src/core/NEON/kernels/scale/impl/SVE/qasymm8.cpp) | 0 | ||||
-rw-r--r-- | src/core/cpu/kernels/scale/sve/qasymm8_signed.cpp (renamed from src/core/NEON/kernels/scale/impl/SVE/qasymm8_signed.cpp) | 0 | ||||
-rw-r--r-- | src/runtime/NEON/functions/NECropResize.cpp | 3 | ||||
-rw-r--r-- | src/runtime/NEON/functions/NEScale.cpp | 184 | ||||
-rw-r--r-- | src/runtime/cpu/operators/CpuScale.cpp | 254 | ||||
-rw-r--r-- | src/runtime/cpu/operators/CpuScale.h | 73 | ||||
-rw-r--r-- | tests/validation/NEON/Scale.cpp | 5 |
24 files changed, 712 insertions, 468 deletions
diff --git a/Android.bp b/Android.bp index 3468bd90a1..6dce0e40bc 100644 --- a/Android.bp +++ b/Android.bp @@ -232,7 +232,6 @@ cc_library_static { "src/core/NEON/kernels/NERemapKernel.cpp", "src/core/NEON/kernels/NEReorgLayerKernel.cpp", "src/core/NEON/kernels/NEReverseKernel.cpp", - "src/core/NEON/kernels/NEScaleKernel.cpp", "src/core/NEON/kernels/NESelectKernel.cpp", "src/core/NEON/kernels/NESpaceToBatchLayerKernel.cpp", "src/core/NEON/kernels/NESpaceToDepthLayerKernel.cpp", @@ -305,15 +304,6 @@ cc_library_static { "src/core/NEON/kernels/convolution/winograd/winograd_transforms/weights_4x4_3x3_fp16_fp16_integers.cpp", "src/core/NEON/kernels/convolution/winograd/winograd_transforms/weights_4x4_3x3_fp32_fp32_integers.cpp", "src/core/NEON/kernels/convolution/winograd/winograd_transforms/weights_6_3_fp32_fp32_integers.cpp", - "src/core/NEON/kernels/scale/impl/NEON/fp16.cpp", - "src/core/NEON/kernels/scale/impl/NEON/integer.cpp", - "src/core/NEON/kernels/scale/impl/NEON/qasymm8.cpp", - "src/core/NEON/kernels/scale/impl/NEON/qasymm8_signed.cpp", - "src/core/NEON/kernels/scale/impl/SVE/fp16.cpp", - "src/core/NEON/kernels/scale/impl/SVE/fp32.cpp", - "src/core/NEON/kernels/scale/impl/SVE/integer.cpp", - "src/core/NEON/kernels/scale/impl/SVE/qasymm8.cpp", - "src/core/NEON/kernels/scale/impl/SVE/qasymm8_signed.cpp", "src/core/PyramidInfo.cpp", "src/core/Rounding.cpp", "src/core/Size2D.cpp", @@ -339,6 +329,7 @@ cc_library_static { "src/core/cpu/kernels/CpuPoolingKernel.cpp", "src/core/cpu/kernels/CpuQuantizationKernel.cpp", "src/core/cpu/kernels/CpuReshapeKernel.cpp", + "src/core/cpu/kernels/CpuScaleKernel.cpp", "src/core/cpu/kernels/CpuSoftmaxKernel.cpp", "src/core/cpu/kernels/CpuSubKernel.cpp", "src/core/cpu/kernels/activation/NEON/fp16.cpp", @@ -366,6 +357,15 @@ cc_library_static { "src/core/cpu/kernels/pooling/neon/nchw/all.cpp", "src/core/cpu/kernels/pooling/neon/qasymm8.cpp", "src/core/cpu/kernels/pooling/neon/qasymm8_signed.cpp", + "src/core/cpu/kernels/scale/neon/fp16.cpp", + "src/core/cpu/kernels/scale/neon/integer.cpp", + "src/core/cpu/kernels/scale/neon/qasymm8.cpp", + "src/core/cpu/kernels/scale/neon/qasymm8_signed.cpp", + "src/core/cpu/kernels/scale/sve/fp16.cpp", + "src/core/cpu/kernels/scale/sve/fp32.cpp", + "src/core/cpu/kernels/scale/sve/integer.cpp", + "src/core/cpu/kernels/scale/sve/qasymm8.cpp", + "src/core/cpu/kernels/scale/sve/qasymm8_signed.cpp", "src/core/cpu/kernels/sub/neon/integer.cpp", "src/core/cpu/kernels/sub/neon/qasymm8.cpp", "src/core/cpu/kernels/sub/neon/qasymm8_signed.cpp", @@ -667,6 +667,7 @@ cc_library_static { "src/runtime/cpu/operators/CpuPoolingAssemblyDispatch.cpp", "src/runtime/cpu/operators/CpuQuantization.cpp", "src/runtime/cpu/operators/CpuReshape.cpp", + "src/runtime/cpu/operators/CpuScale.cpp", "src/runtime/cpu/operators/CpuSoftmax.cpp", "src/runtime/cpu/operators/CpuSub.cpp", "src/runtime/gpu/cl/operators/ClActivation.cpp", diff --git a/arm_compute/runtime/NEON/functions/NECropResize.h b/arm_compute/runtime/NEON/functions/NECropResize.h index 5c3733f8ee..7dcf925650 100644 --- a/arm_compute/runtime/NEON/functions/NECropResize.h +++ b/arm_compute/runtime/NEON/functions/NECropResize.h @@ -1,5 +1,5 @@ /* - * Copyright (c) 2019-2020 Arm Limited. + * Copyright (c) 2019-2021 Arm Limited. * * SPDX-License-Identifier: MIT * @@ -31,6 +31,7 @@ namespace arm_compute { // Forward Declarations +class Tensor; class ITensor; class NECropKernel; diff --git a/arm_compute/runtime/NEON/functions/NEScale.h b/arm_compute/runtime/NEON/functions/NEScale.h index fceda83510..45658a7cd3 100644 --- a/arm_compute/runtime/NEON/functions/NEScale.h +++ b/arm_compute/runtime/NEON/functions/NEScale.h @@ -1,5 +1,5 @@ /* - * Copyright (c) 2016-2020 Arm Limited. + * Copyright (c) 2016-2021 Arm Limited. * * SPDX-License-Identifier: MIT * @@ -24,24 +24,28 @@ #ifndef ARM_COMPUTE_NESCALEIMAGE_H #define ARM_COMPUTE_NESCALEIMAGE_H +#include "arm_compute/runtime/IFunction.h" + #include "arm_compute/core/KernelDescriptors.h" #include "arm_compute/core/Types.h" -#include "arm_compute/runtime/NEON/INESimpleFunctionNoBorder.h" -#include "arm_compute/runtime/Tensor.h" +#include "src/core/common/Macros.h" + +#include <memory> namespace arm_compute { class ITensor; +class ITensorInfo; -/** Basic function to run @ref NEScaleKernel */ -class NEScale : public INESimpleFunctionNoBorder +/** Basic function to compute Scale */ +class NEScale : public IFunction { public: - /** Constructor - * - * Initialize NEScale - */ + /** Default Constructor */ NEScale(); + /** Default Destructor */ + ~NEScale(); + ARM_COMPUTE_DISALLOW_COPY_ALLOW_MOVE(NEScale); /** Initialize the function's source, destination, interpolation type and border_mode. * * @param[in, out] input Source tensor. Data type supported: QASYMM8/QASYMM8_SIGNED/U8/S16/F16/F32. (Written to only for @p border_mode != UNDEFINED) @@ -59,10 +63,12 @@ public: */ static Status validate(const ITensorInfo *input, const ITensorInfo *output, const ScaleKernelInfo &info); + // Inherited methods overridden: + void run() override; + private: - Tensor _offsets; /**< Offset to access the element with NEAREST interpolation or the top-left element with BILINEAR interpolation in the input tensor */ - Tensor _dx; /**< Element's distance between the X real coordinate and the smallest X following integer */ - Tensor _dy; /**< Element's distance between the Y real coordinate and the smallest Y following integer */ + struct Impl; + std::unique_ptr<Impl> _impl; }; } // namespace arm_compute #endif /*ARM_COMPUTE_NESCALEIMAGE_H */ diff --git a/docs/00_introduction.dox b/docs/00_introduction.dox index 1bab6e57d1..d877236c66 100644 --- a/docs/00_introduction.dox +++ b/docs/00_introduction.dox @@ -180,7 +180,7 @@ v21.02 Public major release - Add macOS support - Add Armv8-R AArch64 architecture support - Add SVE/SVE2 support for: - - @ref NEScaleKernel + - NEScaleKernel - @ref NEActivationLayer - @ref NEArithmeticAddition - @ref NEBatchNormalizationLayerKernel @@ -260,7 +260,7 @@ v20.11 Public major release - @ref NERemapKernel - @ref NEGEMMInterleave4x4Kernel - @ref NEDirectConvolutionLayerKernel - - @ref NEScaleKernel + - NEScaleKernel - NELocallyConnectedMatrixMultiplyKernel - @ref NEGEMMLowpOffsetContributionKernel - @ref NEGEMMTranspose1xWKernel @@ -534,7 +534,7 @@ v20.08 Public major release - @ref NECropKernel - CLCropKernel - Added aligh_corner support for nearest neighbor interpolation in: - - @ref NEScaleKernel + - NEScaleKernel - CLScaleKernel - New OpenCL kernels / functions: - @ref CLMaxUnpoolingLayerKernel @@ -621,7 +621,7 @@ v20.05 Public major release - @ref CLReductionOperation - @ref CLReduceMean - @ref NEScale - - @ref NEScaleKernel + - NEScaleKernel - NEUpsampleLayer - @ref NECast - @ref NEReductionOperation @@ -1139,7 +1139,7 @@ v18.05 Public major release - Added support for the memory manager in the graph API. - Enabled Winograd Convolution method in the graph API. - Added support for grouped convolutions in the graph API. - - Replaced NEDeconvolutionLayerUpsampleKernel with @ref NEScaleKernel in @ref NEDeconvolutionLayer. + - Replaced NEDeconvolutionLayerUpsampleKernel with NEScaleKernel in @ref NEDeconvolutionLayer. - Added fast maths flag in @ref CLConvolutionLayer. - Added new tests and benchmarks in validation and benchmark frameworks - Merge Activation layer with Convolution Layer (Neon. CL, GLES) diff --git a/src/core/NEON/NEKernels.h b/src/core/NEON/NEKernels.h index 6a7e856d8b..973c0f2d31 100644 --- a/src/core/NEON/NEKernels.h +++ b/src/core/NEON/NEKernels.h @@ -82,7 +82,6 @@ #include "src/core/NEON/kernels/NERemapKernel.h" #include "src/core/NEON/kernels/NEReorgLayerKernel.h" #include "src/core/NEON/kernels/NEReverseKernel.h" -#include "src/core/NEON/kernels/NEScaleKernel.h" #include "src/core/NEON/kernels/NESelectKernel.h" #include "src/core/NEON/kernels/NESpaceToBatchLayerKernel.h" #include "src/core/NEON/kernels/NESpaceToDepthLayerKernel.h" diff --git a/src/core/NEON/kernels/NEScaleKernel.h b/src/core/NEON/kernels/NEScaleKernel.h deleted file mode 100644 index 32fa8d7fb2..0000000000 --- a/src/core/NEON/kernels/NEScaleKernel.h +++ /dev/null @@ -1,122 +0,0 @@ -/* - * Copyright (c) 2016-2021 Arm Limited. - * - * SPDX-License-Identifier: MIT - * - * Permission is hereby granted, free of charge, to any person obtaining a copy - * of this software and associated documentation files (the "Software"), to - * deal in the Software without restriction, including without limitation the - * rights to use, copy, modify, merge, publish, distribute, sublicense, and/or - * sell copies of the Software, and to permit persons to whom the Software is - * furnished to do so, subject to the following conditions: - * - * The above copyright notice and this permission notice shall be included in all - * copies or substantial portions of the Software. - * - * THE SOFTWARE IS PROVIDED "AS IS", WITHOUT WARRANTY OF ANY KIND, EXPRESS OR - * IMPLIED, INCLUDING BUT NOT LIMITED TO THE WARRANTIES OF MERCHANTABILITY, - * FITNESS FOR A PARTICULAR PURPOSE AND NONINFRINGEMENT. IN NO EVENT SHALL THE - * AUTHORS OR COPYRIGHT HOLDERS BE LIABLE FOR ANY CLAIM, DAMAGES OR OTHER - * LIABILITY, WHETHER IN AN ACTION OF CONTRACT, TORT OR OTHERWISE, ARISING FROM, - * OUT OF OR IN CONNECTION WITH THE SOFTWARE OR THE USE OR OTHER DEALINGS IN THE - * SOFTWARE. - */ -#ifndef ARM_COMPUTE_NESCALEKERNEL_H -#define ARM_COMPUTE_NESCALEKERNEL_H - -#include "arm_compute/core/KernelDescriptors.h" -#include "src/core/NEON/INEKernel.h" - -namespace arm_compute -{ -class ITensor; - -/** Neon kernel to perform scaling on a tensor */ -class NEScaleKernel : public INEKernel -{ -public: - const char *name() const override - { - return "NEScaleKernel"; - } - /** Default constructor */ - NEScaleKernel(); - /** Prevent instances of this class from being copied (As this class contains pointers) */ - NEScaleKernel(const NEScaleKernel &) = delete; - /** Prevent instances of this class from being copied (As this class contains pointers) */ - NEScaleKernel &operator=(const NEScaleKernel &) = delete; - /** Allow instances of this class to be moved */ - NEScaleKernel(NEScaleKernel &&) = default; - /** Allow instances of this class to be moved */ - NEScaleKernel &operator=(NEScaleKernel &&) = default; - /** Default destructor */ - ~NEScaleKernel() = default; - - /** Initialise the kernel's inputs, output and interpolation policy - * - * @note dx, dy and offsets have the same dimensions (width and height) of the output tensor - * @note Using @p policy Area only supports data layout NCHW and input data type U8. - * - * @param[in] input Source tensor. Data types supported: QASYMM8/QASYMM8_SIGNED/U8/S16/F16/F32. - * @param[in] dx Pixel's distance between the X real coordinate and the smallest X following integer. Data type supported: F32 - * @param[in] dy Pixel's distance between the Y real coordinate and the smallest Y following integer. Data type 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: Same as @p input. 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] info @ref ScaleKernelInfo to use for configuration - */ - void configure(const ITensor *input, const ITensor *dx, const ITensor *dy, const ITensor *offsets, ITensor *output, - const ScaleKernelInfo &info); - /** Static function to check if given info will lead to a valid configuration of @ref NEScaleKernel - * - * @note dx, dy and offsets have the same dimensions (width and height) of the output tensor - * @note Using @p policy Area only supports data layout NCHW and input data type U8. - * - * @param[in] input Source tensor. Data types supported: QASYMM8/QASYMM8_SIGNED/U8/S16/F16/F32. - * @param[in] dx Pixel's distance between the X real coordinate and the smallest X following integer. Data type supported: F32 - * @param[in] dy Pixel's distance between the Y real coordinate and the smallest Y following integer. Data type 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[in] output Destination tensor. Data types supported: Same as @p input. 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] info @ref ScaleKernelInfo to use for validation - */ - static Status validate(const ITensorInfo *input, const ITensorInfo *dx, const ITensorInfo *dy, const ITensorInfo *offsets, ITensorInfo *output, - const ScaleKernelInfo &info); - - // Inherited methods overridden: - void run(const Window &window, const ThreadInfo &info) override; - -private: - /** function to perform scale using area interpolation on the given window - * - * @note Used only in case down-sampling. - */ - void scale_area_nchw_u8(const Window &window); - - /** function to perform scale using bilinear interpolation on the given window */ - template <typename T> - void scale_bilinear_nchw(const Window &window); - /** function to perform scale using bilinear interpolation on the given window */ - template <typename T> - void scale_bilinear_qasymm(const Window &window); - - /** function to perform scale using nearest neighbour on the given window */ - template <typename T> - void scale_nearest_nchw(const Window &window); - - /** Scale function to use for the particular function to use */ - using ScaleFunctionPtr = void (NEScaleKernel::*)(const Window &window); - - ScaleFunctionPtr _func; - const ITensor *_offsets; - const ITensor *_dx; - const ITensor *_dy; - const ITensor *_input; - ITensor *_output; - InterpolationPolicy _policy; - BorderMode _border_mode; - PixelValue _constant_border_value; - float _sampling_offset; - bool _align_corners; - DataLayout _data_layout; -}; -} // namespace arm_compute -#endif /*ARM_COMPUTE_NESCALEKERNEL_H */ diff --git a/src/core/NEON/kernels/NEScaleKernel.cpp b/src/core/cpu/kernels/CpuScaleKernel.cpp index 6b9aa51aaa..22d1332a55 100644 --- a/src/core/NEON/kernels/NEScaleKernel.cpp +++ b/src/core/cpu/kernels/CpuScaleKernel.cpp @@ -21,27 +21,32 @@ * OUT OF OR IN CONNECTION WITH THE SOFTWARE OR THE USE OR OTHER DEALINGS IN THE * SOFTWARE. */ -#include "src/core/NEON/kernels/NEScaleKernel.h" +#include "src/core/cpu/kernels/CpuScaleKernel.h" #include "arm_compute/core/Helpers.h" #include "arm_compute/core/Window.h" #include "arm_compute/core/utils/misc/Utility.h" #include "src/core/AccessWindowStatic.h" #include "src/core/CPP/Validate.h" -#include "src/core/NEON/kernels/scale/impl/NEON/list.h" -#include "src/core/NEON/kernels/scale/impl/SVE/list.h" #include "src/core/NEON/wrapper/wrapper.h" #include "src/core/common/Registrars.h" +#include "src/core/cpu/kernels/scale/neon/list.h" +#include "src/core/cpu/kernels/scale/sve/list.h" #include "src/core/helpers/AutoConfiguration.h" #include "src/core/helpers/ScaleHelpers.h" #include "src/core/helpers/WindowHelpers.h" #include "src/core/utils/ScaleUtils.h" #include "support/Rounding.h" + #include <arm_neon.h> #include <map> namespace arm_compute { +namespace cpu +{ +namespace kernels +{ namespace { struct ScaleSelectorData @@ -145,24 +150,24 @@ const ScaleKernel *get_implementation(const ScaleSelectorData &data) return nullptr; } -Status validate_arguments(const ITensorInfo *input, const ITensorInfo *dx, const ITensorInfo *dy, - const ITensorInfo *offsets, ITensorInfo *output, const ScaleKernelInfo &info) +Status validate_arguments(const ITensorInfo *src, const ITensorInfo *dx, const ITensorInfo *dy, + const ITensorInfo *offsets, ITensorInfo *dst, const ScaleKernelInfo &info) { - const auto *uk = get_implementation(ScaleSelectorData{ input->data_type() }); + const auto *uk = get_implementation(ScaleSelectorData{ src->data_type() }); ARM_COMPUTE_RETURN_ERROR_ON(uk == nullptr || uk->ukernel == nullptr); - ARM_COMPUTE_RETURN_ERROR_ON_NULLPTR(output); - ARM_COMPUTE_RETURN_ERROR_ON_MISMATCHING_DATA_TYPES(input, output); - ARM_COMPUTE_RETURN_ERROR_ON(output == input); + ARM_COMPUTE_RETURN_ERROR_ON_NULLPTR(dst); + ARM_COMPUTE_RETURN_ERROR_ON_MISMATCHING_DATA_TYPES(src, dst); + ARM_COMPUTE_RETURN_ERROR_ON(dst == src); ARM_COMPUTE_RETURN_ERROR_ON(info.sampling_policy != SamplingPolicy::CENTER && info.sampling_policy != SamplingPolicy::TOP_LEFT); ARM_COMPUTE_UNUSED(info.constant_border_value); ARM_COMPUTE_RETURN_ERROR_ON_MSG(info.use_padding, "Padding is not supported"); - const DataLayout data_layout = info.data_layout == DataLayout::UNKNOWN ? input->data_layout() : info.data_layout; + const DataLayout data_layout = info.data_layout == DataLayout::UNKNOWN ? src->data_layout() : info.data_layout; const auto width_index = get_data_layout_dimension_index(data_layout, DataLayoutDimension::WIDTH); const auto height_index = get_data_layout_dimension_index(data_layout, DataLayoutDimension::HEIGHT); - const auto output_width = output->dimension(width_index); - const auto output_height = output->dimension(height_index); + const auto output_width = dst->dimension(width_index); + const auto output_height = dst->dimension(height_index); ARM_COMPUTE_RETURN_ERROR_ON(output_width == 0); ARM_COMPUTE_RETURN_ERROR_ON(output_height == 0); @@ -183,41 +188,36 @@ Status validate_arguments(const ITensorInfo *input, const ITensorInfo *dx, const if(info.interpolation_policy == InterpolationPolicy::AREA) { ARM_COMPUTE_RETURN_ERROR_ON(data_layout != DataLayout::NCHW); - ARM_COMPUTE_RETURN_ERROR_ON_DATA_TYPE_CHANNEL_NOT_IN(input, 1, DataType::U8); + ARM_COMPUTE_RETURN_ERROR_ON_DATA_TYPE_CHANNEL_NOT_IN(src, 1, DataType::U8); } return Status{}; } } // namespace -NEScaleKernel::NEScaleKernel() - : _func(nullptr), _offsets(nullptr), _dx(nullptr), _dy(nullptr), _input(nullptr), _output(nullptr), _policy(), _border_mode(), _constant_border_value(PixelValue()), _sampling_offset(0), - _align_corners(false), _data_layout(DataLayout::UNKNOWN) +CpuScaleKernel::CpuScaleKernel() + : _func(nullptr), _policy(), _border_mode(), _constant_border_value(PixelValue()), _sampling_offset(0), _align_corners(false), _data_layout(DataLayout::UNKNOWN) { } -void NEScaleKernel::configure(const ITensor *input, const ITensor *dx, const ITensor *dy, const ITensor *offsets, - ITensor *output, const ScaleKernelInfo &info) +void CpuScaleKernel::configure(const ITensorInfo *src, const ITensorInfo *dx, const ITensorInfo *dy, const ITensorInfo *offsets, + ITensorInfo *dst, const ScaleKernelInfo &info) { - ARM_COMPUTE_ERROR_ON_NULLPTR(input, output); + ARM_COMPUTE_UNUSED(dx, dy, offsets); + ARM_COMPUTE_ERROR_ON_NULLPTR(src, dst); // Perform validation step - ARM_COMPUTE_ERROR_THROW_ON(validate_arguments(input->info(), - dx != nullptr ? dx->info() : nullptr, - dy != nullptr ? dy->info() : nullptr, - offsets != nullptr ? offsets->info() : nullptr, - output->info(), + ARM_COMPUTE_ERROR_THROW_ON(validate_arguments(src, + dx, + dy, + offsets, + dst, info)); // Get data layout and width/height indices - _data_layout = info.data_layout == DataLayout::UNKNOWN ? input->info()->data_layout() : info.data_layout; + _data_layout = info.data_layout == DataLayout::UNKNOWN ? src->data_layout() : info.data_layout; const int idx_width = get_data_layout_dimension_index(_data_layout, DataLayoutDimension::WIDTH); const int idx_height = get_data_layout_dimension_index(_data_layout, DataLayoutDimension::HEIGHT); - _input = input; - _output = output; - _offsets = offsets; - _dx = dx; - _dy = dy; _policy = info.interpolation_policy; _border_mode = info.border_mode; _constant_border_value = info.constant_border_value; @@ -229,8 +229,8 @@ void NEScaleKernel::configure(const ITensor *input, const ITensor *dx, const ITe } // Compute the ratio between source width/height and destination width/height - const auto wr = scale_utils::calculate_resize_ratio(input->info()->dimension(idx_width), output->info()->dimension(idx_width), _align_corners); - const auto hr = scale_utils::calculate_resize_ratio(input->info()->dimension(idx_height), output->info()->dimension(idx_height), _align_corners); + const auto wr = scale_utils::calculate_resize_ratio(src->dimension(idx_width), dst->dimension(idx_width), _align_corners); + const auto hr = scale_utils::calculate_resize_ratio(src->dimension(idx_height), dst->dimension(idx_height), _align_corners); // Area interpolation behaves as Nearest Neighbour in case of up-sampling _policy = (_policy == InterpolationPolicy::AREA && wr <= 1.f && hr <= 1.f) ? InterpolationPolicy::NEAREST_NEIGHBOR : _policy; @@ -241,37 +241,38 @@ void NEScaleKernel::configure(const ITensor *input, const ITensor *dx, const ITe _constant_border_value = PixelValue(); } +#ifdef ENABLE_NCHW_KERNELS // Configure scale function to run if(_data_layout == DataLayout::NCHW) { std::string function_to_call("scale_"); - function_to_call += string_from_data_type(_input->info()->data_type()) + "_"; + function_to_call += string_from_data_type(src->data_type()) + "_"; function_to_call += string_from_data_layout(_data_layout) + "_"; function_to_call += string_from_interpolation_policy(_policy); static std::map<std::string, ScaleFunctionPtr> map_function = { - { "scale_U8_NCHW_AREA_CONSTANT", &NEScaleKernel::scale_area_nchw_u8 }, + { "scale_U8_NCHW_AREA_CONSTANT", &CpuScaleKernel::scale_area_nchw_u8 }, - { "scale_U8_NCHW_BILINEAR", &NEScaleKernel::scale_bilinear_nchw<uint8_t> }, - { "scale_U8_NCHW_NEAREST_NEIGHBOUR", &NEScaleKernel::scale_nearest_nchw<uint8_t> }, + { "scale_U8_NCHW_BILINEAR", &CpuScaleKernel::scale_bilinear_nchw<uint8_t> }, + { "scale_U8_NCHW_NEAREST_NEIGHBOUR", &CpuScaleKernel::scale_nearest_nchw<uint8_t> }, - { "scale_QASYMM8_NCHW_BILINEAR", &NEScaleKernel::scale_bilinear_qasymm<uint8_t> }, - { "scale_QASYMM8_NCHW_NEAREST_NEIGHBOUR", &NEScaleKernel::scale_nearest_nchw<uint8_t> }, + { "scale_QASYMM8_NCHW_BILINEAR", &CpuScaleKernel::scale_bilinear_qasymm<uint8_t> }, + { "scale_QASYMM8_NCHW_NEAREST_NEIGHBOUR", &CpuScaleKernel::scale_nearest_nchw<uint8_t> }, - { "scale_QASYMM8_SIGNED_NCHW_BILINEAR", &NEScaleKernel::scale_bilinear_qasymm<int8_t> }, - { "scale_QASYMM8_SIGNED_NCHW_NEAREST_NEIGHBOUR", &NEScaleKernel::scale_nearest_nchw<int8_t> }, + { "scale_QASYMM8_SIGNED_NCHW_BILINEAR", &CpuScaleKernel::scale_bilinear_qasymm<int8_t> }, + { "scale_QASYMM8_SIGNED_NCHW_NEAREST_NEIGHBOUR", &CpuScaleKernel::scale_nearest_nchw<int8_t> }, - { "scale_S16_NCHW_BILINEAR", &NEScaleKernel::scale_bilinear_nchw<int16_t> }, - { "scale_S16_NCHW_NEAREST_NEIGHBOUR", &NEScaleKernel::scale_nearest_nchw<int16_t> }, + { "scale_S16_NCHW_BILINEAR", &CpuScaleKernel::scale_bilinear_nchw<int16_t> }, + { "scale_S16_NCHW_NEAREST_NEIGHBOUR", &CpuScaleKernel::scale_nearest_nchw<int16_t> }, #ifdef __ARM_FEATURE_FP16_VECTOR_ARITHMETIC - { "scale_F16_NCHW_BILINEAR", &NEScaleKernel::scale_bilinear_nchw<float16_t> }, - { "scale_F16_NCHW_NEAREST_NEIGHBOUR", &NEScaleKernel::scale_nearest_nchw<float16_t> }, + { "scale_F16_NCHW_BILINEAR", &CpuScaleKernel::scale_bilinear_nchw<float16_t> }, + { "scale_F16_NCHW_NEAREST_NEIGHBOUR", &CpuScaleKernel::scale_nearest_nchw<float16_t> }, #endif /* __ARM_FEATURE_FP16_VECTOR_ARITHMETIC */ - { "scale_F32_NCHW_BILINEAR", &NEScaleKernel::scale_bilinear_nchw<float> }, - { "scale_F32_NCHW_NEAREST_NEIGHBOUR", &NEScaleKernel::scale_nearest_nchw<float> }, + { "scale_F32_NCHW_BILINEAR", &CpuScaleKernel::scale_bilinear_nchw<float> }, + { "scale_F32_NCHW_NEAREST_NEIGHBOUR", &CpuScaleKernel::scale_nearest_nchw<float> }, }; auto it = map_function.find(function_to_call); if(it != map_function.end()) @@ -279,19 +280,22 @@ void NEScaleKernel::configure(const ITensor *input, const ITensor *dx, const ITe _func = it->second; } } +#endif // ENABLE_NCHW_KERNELS // Configure window - Window win = calculate_max_window(*output->info(), Steps()); - INEKernel::configure(win); + Window win = calculate_max_window(*dst, Steps()); + ICpuKernel::configure(win); } +#ifdef ENABLE_NCHW_KERNELS template <typename T> -void NEScaleKernel::scale_nearest_nchw(const Window &window) +void CpuScaleKernel::scale_nearest_nchw(const ITensor *src, ITensor *dst, const ITensor *dx, const ITensor *dy, const ITensor *offsets, const Window &window) { - const size_t in_stride_x = _input->info()->dimension(0) + _input->info()->padding().left + _input->info()->padding().right; + ARM_COMPUTE_UNUSED(dx, dy); + const size_t in_stride_x = src->info()->dimension(0) + src->info()->padding().left + src->info()->padding().right; // Compute the ratio between source height and destination height - const auto hr = scale_utils::calculate_resize_ratio(_input->info()->dimension(1), _output->info()->dimension(1), _align_corners); + const auto hr = scale_utils::calculate_resize_ratio(src->info()->dimension(1), dst->info()->dimension(1), _align_corners); // 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 @@ -303,30 +307,32 @@ void NEScaleKernel::scale_nearest_nchw(const Window &window) 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) + for(size_t d = Window::DimZ; d < offsets->info()->num_dimensions(); ++d) { win_off.set(d, Window::Dimension(0, 0, 0)); } // Create iterators - Iterator in(_input, win_in); - Iterator out(_output, window); - Iterator offsets(_offsets, win_off); + Iterator src_i(src, win_in); + Iterator dst_i(dst, window); + Iterator offsets_i(offsets, win_off); execute_window_loop(window, [&](const Coordinates & id) { - const auto offsets_ptr = reinterpret_cast<const int32_t *>(offsets.ptr()); - const auto in_yi = static_cast<int32_t>(_align_corners ? utils::rounding::round_half_away_from_zero((id.y() + _sampling_offset) * hr) : std::floor((id.y() + _sampling_offset) * hr)); - const int32_t offset_row = in_yi * in_stride_x; - *reinterpret_cast<T *>(out.ptr()) = *(reinterpret_cast<const T *>(in.ptr()) + offsets_ptr[0] + offset_row); + const auto offsets_ptr = reinterpret_cast<const int32_t *>(offsets_i.ptr()); + const auto in_yi = static_cast<int32_t>(_align_corners ? utils::rounding::round_half_away_from_zero((id.y() + _sampling_offset) * hr) : std::floor(( + id.y() + _sampling_offset) + * hr)); + const int32_t offset_row = in_yi * in_stride_x; + *reinterpret_cast<T *>(dst_i.ptr()) = *(reinterpret_cast<const T *>(src_i.ptr()) + offsets_ptr[0] + offset_row); }, - in, offsets, out); + src_i, offsets_i, dst_i); } template <typename T> -void NEScaleKernel::scale_bilinear_nchw(const Window &window) +void CpuScaleKernel::scale_bilinear_nchw(const ITensor *src, ITensor *dst, const ITensor *dx, const ITensor *dy, const ITensor *offsets, const Window &window) { // Compute the ratio between source height and destination height - const auto hr = scale_utils::calculate_resize_ratio(_input->info()->dimension(1), _output->info()->dimension(1), _align_corners); + const auto hr = scale_utils::calculate_resize_ratio(src->info()->dimension(1), dst->info()->dimension(1), _align_corners); Window win_off; win_off.set(Window::DimX, window.x()); win_off.set(Window::DimY, window.y()); @@ -337,20 +343,20 @@ void NEScaleKernel::scale_bilinear_nchw(const Window &window) win_in.set(Window::DimX, Window::Dimension(0, 0, 0)); win_in.set(Window::DimY, Window::Dimension(0, 0, 0)); - for(size_t d = Window::DimZ; d < _offsets->info()->num_dimensions(); ++d) + 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); - Iterator dx(_dx, win_off); - Iterator dy(_dy, win_off); + Iterator src_i(src, win_in); + Iterator dst_i(dst, window); + Iterator offsets_i(offsets, win_off); + Iterator dx_i(dx, win_off); + Iterator dy_i(dy, win_off); - const int32_t in_dim_w = _input->info()->dimension(0); - const int32_t in_dim_h = _input->info()->dimension(1); - const int32_t in_stride_w = in_dim_w + _input->info()->padding().left + _input->info()->padding().right; + const int32_t in_dim_w = src->info()->dimension(0); + const int32_t in_dim_h = src->info()->dimension(1); + const int32_t in_stride_w = in_dim_w + src->info()->padding().left + src->info()->padding().right; if(_border_mode == BorderMode::CONSTANT) { @@ -363,10 +369,10 @@ void NEScaleKernel::scale_bilinear_nchw(const Window &window) execute_window_loop(window, [&](const Coordinates & id) { const int32_t index_h = std::floor((id.y() + _sampling_offset) * hr - _sampling_offset); - const auto index_w = *(reinterpret_cast<const int32_t *>(offsets.ptr())); - const auto dx_val = *(reinterpret_cast<const float *>(dx.ptr())); - const auto dy_val = *(reinterpret_cast<const float *>(dy.ptr())); - const auto pixel_row_ptr = reinterpret_cast<const T *>(in.ptr()); + const auto index_w = *(reinterpret_cast<const int32_t *>(offsets_i.ptr())); + const auto dx_val = *(reinterpret_cast<const float *>(dx_i.ptr())); + const auto dy_val = *(reinterpret_cast<const float *>(dy_i.ptr())); + const auto pixel_row_ptr = reinterpret_cast<const T *>(src_i.ptr()); const auto a00 = (0 <= index_w && index_w < in_dim_w && 0 <= index_h && index_h < in_dim_h) ? (*(pixel_row_ptr + index_w + index_h * in_stride_w)) : const_border_value; const auto a01 = (-1 <= index_w && index_w < in_dim_w - 1 && 0 <= index_h && index_h < in_dim_h) ? (*(pixel_row_ptr + index_w + 1 + index_h * in_stride_w)) : const_border_value; @@ -379,19 +385,19 @@ void NEScaleKernel::scale_bilinear_nchw(const Window &window) (*(pixel_row_ptr + index_w + 1 + index_h * in_stride_w + in_stride_w)) : const_border_value; - *reinterpret_cast<T *>(out.ptr()) = static_cast<T>(scale_helpers::delta_bilinear(a00, a01, a10, a11, dx_val, dy_val)); + *reinterpret_cast<T *>(dst_i.ptr()) = static_cast<T>(scale_helpers::delta_bilinear(a00, a01, a10, a11, dx_val, dy_val)); }, - in, offsets, dx, dy, out); + src_i, offsets_i, dx_i, dy_i, dst_i); } else if(_border_mode == BorderMode::REPLICATE) { execute_window_loop(window, [&](const Coordinates & id) { const int index_h = std::floor((id.y() + _sampling_offset) * hr - _sampling_offset); - const auto index_w = *(reinterpret_cast<const int32_t *>(offsets.ptr())); - const auto dx_val = *(reinterpret_cast<const float *>(dx.ptr())); - const auto dy_val = *(reinterpret_cast<const float *>(dy.ptr())); - const auto pixel_row_ptr = reinterpret_cast<const T *>(in.ptr()); + const auto index_w = *(reinterpret_cast<const int32_t *>(offsets_i.ptr())); + const auto dx_val = *(reinterpret_cast<const float *>(dx_i.ptr())); + const auto dy_val = *(reinterpret_cast<const float *>(dy_i.ptr())); + const auto pixel_row_ptr = reinterpret_cast<const T *>(src_i.ptr()); auto clamped_x = utility::clamp<int>(index_w, 0, in_dim_w - 1); auto clamped_x1 = utility::clamp<int>(index_w + 1, 0, in_dim_w - 1); @@ -403,9 +409,9 @@ void NEScaleKernel::scale_bilinear_nchw(const Window &window) const auto a10 = *(pixel_row_ptr + clamped_x + clamped_y1 * in_stride_w); const auto a11 = *(pixel_row_ptr + clamped_x1 + clamped_y1 * in_stride_w); - *reinterpret_cast<T *>(out.ptr()) = static_cast<T>(scale_helpers::delta_bilinear(a00, a01, a10, a11, dx_val, dy_val)); + *reinterpret_cast<T *>(dst_i.ptr()) = static_cast<T>(scale_helpers::delta_bilinear(a00, a01, a10, a11, dx_val, dy_val)); }, - in, offsets, dx, dy, out); + src_i, offsets_i, dx_i, dy_i, dst_i); } else { @@ -413,11 +419,12 @@ void NEScaleKernel::scale_bilinear_nchw(const Window &window) } } -void NEScaleKernel::scale_area_nchw_u8(const Window &window) +void CpuScaleKernel::scale_area_nchw_u8(const ITensor *src, ITensor *dst, const ITensor *dx, const ITensor *dy, const ITensor *offsets, const Window &window) { + ARM_COMPUTE_UNUSED(dx, dy, offsets); using namespace scale_helpers; - ARM_COMPUTE_ERROR_ON_DATA_TYPE_CHANNEL_NOT_IN(_input, 1, DataType::U8); + ARM_COMPUTE_ERROR_ON_DATA_TYPE_CHANNEL_NOT_IN(src, 1, DataType::U8); // Don't increment in width/height/channels for the input tensor // A pointer to the start of this plane is needed as base for the precomputed offsets @@ -426,18 +433,18 @@ void NEScaleKernel::scale_area_nchw_u8(const Window &window) win_in.set(Window::DimY, Window::Dimension(0, 0, 0)); win_in.set(Window::DimZ, Window::Dimension(0, 0, 0)); - Iterator in(_input, win_in); - Iterator out(_output, window); + Iterator src_i(src, win_in); + Iterator dst_i(dst, window); - const auto wr = scale_utils::calculate_resize_ratio(_input->info()->dimension(0), _output->info()->dimension(0), _align_corners); - const auto hr = scale_utils::calculate_resize_ratio(_input->info()->dimension(1), _output->info()->dimension(1), _align_corners); - const auto w = _input->info()->dimension(0); - const auto h = _input->info()->dimension(1); - const size_t in_stride = _input->info()->strides_in_bytes()[1]; + const auto wr = scale_utils::calculate_resize_ratio(src->info()->dimension(0), dst->info()->dimension(0), _align_corners); + const auto hr = scale_utils::calculate_resize_ratio(src->info()->dimension(1), dst->info()->dimension(1), _align_corners); + const auto w = src->info()->dimension(0); + const auto h = src->info()->dimension(1); + const size_t in_stride = src->info()->strides_in_bytes()[1]; execute_window_loop(window, [&](const Coordinates & id) { - const auto in_ptr = reinterpret_cast<const uint8_t *>(in.ptr()); + const auto in_ptr = reinterpret_cast<const uint8_t *>(src_i.ptr()); uint8x8_t tmp0 = vdup_n_u8(0); tmp0 = vset_lane_u8(pixel_area_c1u8_clamp(in_ptr, in_stride, w, h, wr, hr, id.x(), id.y()), tmp0, 0); @@ -459,20 +466,20 @@ void NEScaleKernel::scale_area_nchw_u8(const Window &window) tmp1 = vset_lane_u8(pixel_area_c1u8_clamp(in_ptr, in_stride, w, h, wr, hr, id.x() + 14, id.y()), tmp1, 6); tmp1 = vset_lane_u8(pixel_area_c1u8_clamp(in_ptr, in_stride, w, h, wr, hr, id.x() + 15, id.y()), tmp1, 7); - vst1q_u8(out.ptr(), vcombine_u8(tmp0, tmp1)); + vst1q_u8(dst_i.ptr(), vcombine_u8(tmp0, tmp1)); }, - in, out); + src_i, dst_i); } template <typename T> -void NEScaleKernel::scale_bilinear_qasymm(const Window &window) +void CpuScaleKernel::scale_bilinear_qasymm(const ITensor *src, ITensor *dst, const ITensor *dx, const ITensor *dy, const ITensor *offsets, const Window &window) { // Get data layout and width/height indices const int idx_width = get_data_layout_dimension_index(_data_layout, DataLayoutDimension::WIDTH); const int idx_height = get_data_layout_dimension_index(_data_layout, DataLayoutDimension::HEIGHT); // Compute the ratio between source height and destination height - const auto hr = scale_utils::calculate_resize_ratio(_input->info()->dimension(idx_height), _output->info()->dimension(idx_height), _align_corners); + const auto hr = scale_utils::calculate_resize_ratio(src->info()->dimension(idx_height), dst->info()->dimension(idx_height), _align_corners); Window win_off; win_off.set(Window::DimX, Window::Dimension(0, 0, 0)); win_off.set(Window::DimY, Window::Dimension(0, 0, 0)); @@ -483,21 +490,21 @@ void NEScaleKernel::scale_bilinear_qasymm(const Window &window) win_in.set(idx_width, Window::Dimension(0, 0, 0)); win_in.set(idx_height, Window::Dimension(0, 0, 0)); - for(size_t d = Window::DimZ; d < _offsets->info()->num_dimensions(); ++d) + 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 src_i(src, win_in); + Iterator dst_i(dst, window); - const int32_t in_dim_w = _input->info()->dimension(idx_width); - const int32_t in_dim_h = _input->info()->dimension(idx_height); - const int32_t stride_w = _input->info()->strides_in_bytes()[idx_width]; - const int32_t stride_h = _input->info()->strides_in_bytes()[idx_height]; + const int32_t in_dim_w = src->info()->dimension(idx_width); + const int32_t in_dim_h = src->info()->dimension(idx_height); + const int32_t stride_w = src->info()->strides_in_bytes()[idx_width]; + const int32_t stride_h = src->info()->strides_in_bytes()[idx_height]; - const UniformQuantizationInfo iq_info = _input->info()->quantization_info().uniform(); - const UniformQuantizationInfo oq_info = _output->info()->quantization_info().uniform(); + const UniformQuantizationInfo iq_info = src->info()->quantization_info().uniform(); + const UniformQuantizationInfo oq_info = dst->info()->quantization_info().uniform(); if(_border_mode == BorderMode::CONSTANT) { @@ -510,10 +517,10 @@ void NEScaleKernel::scale_bilinear_qasymm(const Window &window) execute_window_loop(window, [&](const Coordinates & id) { const int32_t index_h = std::floor((id[idx_height] + _sampling_offset) * hr - _sampling_offset); - const int32_t index_w = *(reinterpret_cast<const int32_t *>(_offsets->ptr_to_element(Coordinates(id[idx_width], id[idx_height])))); - const auto dx_val = *(reinterpret_cast<const float *>(_dx->ptr_to_element(Coordinates(id[idx_width], id[idx_height])))); - const auto dy_val = *(reinterpret_cast<const float *>(_dy->ptr_to_element(Coordinates(id[idx_width], id[idx_height])))); - const auto pixel_row_ptr = reinterpret_cast<const T *>(in.ptr()); + const int32_t index_w = *(reinterpret_cast<const int32_t *>(offsets->ptr_to_element(Coordinates(id[idx_width], id[idx_height])))); + const auto dx_val = *(reinterpret_cast<const float *>(dx->ptr_to_element(Coordinates(id[idx_width], id[idx_height])))); + const auto dy_val = *(reinterpret_cast<const float *>(dy->ptr_to_element(Coordinates(id[idx_width], id[idx_height])))); + const auto pixel_row_ptr = reinterpret_cast<const T *>(src_i.ptr()); const auto a00 = (0 <= index_w && index_w < in_dim_w && 0 <= index_h && index_h < in_dim_h) ? (*(pixel_row_ptr + index_w * stride_w + index_h * stride_h)) : @@ -528,23 +535,23 @@ void NEScaleKernel::scale_bilinear_qasymm(const Window &window) (*(pixel_row_ptr + (index_w + 1) * stride_w + (index_h + 1) * stride_h)) : const_border_value; - const float inp00 = Qasymm8QuantizationHelper<T>::dequantize(a00, iq_info); - const float inp01 = Qasymm8QuantizationHelper<T>::dequantize(a01, iq_info); - const float inp10 = Qasymm8QuantizationHelper<T>::dequantize(a10, iq_info); - const float inp11 = Qasymm8QuantizationHelper<T>::dequantize(a11, iq_info); - *reinterpret_cast<T *>(out.ptr()) = Qasymm8QuantizationHelper<T>::quantize(scale_helpers::delta_bilinear(inp00, inp01, inp10, inp11, dx_val, dy_val), oq_info); + const float inp00 = Qasymm8QuantizationHelper<T>::dequantize(a00, iq_info); + const float inp01 = Qasymm8QuantizationHelper<T>::dequantize(a01, iq_info); + const float inp10 = Qasymm8QuantizationHelper<T>::dequantize(a10, iq_info); + const float inp11 = Qasymm8QuantizationHelper<T>::dequantize(a11, iq_info); + *reinterpret_cast<T *>(dst_i.ptr()) = Qasymm8QuantizationHelper<T>::quantize(scale_helpers::delta_bilinear(inp00, inp01, inp10, inp11, dx_val, dy_val), oq_info); }, - in, out); + src_i, dst_i); } else if(_border_mode == BorderMode::REPLICATE) { execute_window_loop(window, [&](const Coordinates & id) { const int index_h = std::floor((id[idx_height] + _sampling_offset) * hr - _sampling_offset); - const int32_t index_w = *(reinterpret_cast<const int32_t *>(_offsets->ptr_to_element(Coordinates(id[idx_width], id[idx_height])))); - const auto dx_val = *(reinterpret_cast<const float *>(_dx->ptr_to_element(Coordinates(id[idx_width], id[idx_height])))); - const auto dy_val = *(reinterpret_cast<const float *>(_dy->ptr_to_element(Coordinates(id[idx_width], id[idx_height])))); - const auto pixel_row_ptr = reinterpret_cast<const T *>(in.ptr()); + const int32_t index_w = *(reinterpret_cast<const int32_t *>(offsets->ptr_to_element(Coordinates(id[idx_width], id[idx_height])))); + const auto dx_val = *(reinterpret_cast<const float *>(dx->ptr_to_element(Coordinates(id[idx_width], id[idx_height])))); + const auto dy_val = *(reinterpret_cast<const float *>(dy->ptr_to_element(Coordinates(id[idx_width], id[idx_height])))); + const auto pixel_row_ptr = reinterpret_cast<const T *>(src_i.ptr()); auto clamped_w = utility::clamp<int>(index_w, 0, in_dim_w - 1); auto clamped_w1 = utility::clamp<int>(index_w + 1, 0, in_dim_w - 1); @@ -556,42 +563,56 @@ void NEScaleKernel::scale_bilinear_qasymm(const Window &window) const auto a10 = *(pixel_row_ptr + clamped_w * stride_w + clamped_h1 * stride_h); const auto a11 = *(pixel_row_ptr + clamped_w1 * stride_w + clamped_h1 * stride_h); - const float inp00 = Qasymm8QuantizationHelper<T>::dequantize(a00, iq_info); - const float inp01 = Qasymm8QuantizationHelper<T>::dequantize(a01, iq_info); - const float inp10 = Qasymm8QuantizationHelper<T>::dequantize(a10, iq_info); - const float inp11 = Qasymm8QuantizationHelper<T>::dequantize(a11, iq_info); - *reinterpret_cast<T *>(out.ptr()) = Qasymm8QuantizationHelper<T>::quantize(scale_helpers::delta_bilinear(inp00, inp01, inp10, inp11, dx_val, dy_val), oq_info); + const float inp00 = Qasymm8QuantizationHelper<T>::dequantize(a00, iq_info); + const float inp01 = Qasymm8QuantizationHelper<T>::dequantize(a01, iq_info); + const float inp10 = Qasymm8QuantizationHelper<T>::dequantize(a10, iq_info); + const float inp11 = Qasymm8QuantizationHelper<T>::dequantize(a11, iq_info); + *reinterpret_cast<T *>(dst_i.ptr()) = Qasymm8QuantizationHelper<T>::quantize(scale_helpers::delta_bilinear(inp00, inp01, inp10, inp11, dx_val, dy_val), oq_info); }, - in, out); + src_i, dst_i); } else { ARM_COMPUTE_ERROR("Not implemented"); } } +#endif // ENABLE_NCHW_KERNELS -Status NEScaleKernel::validate(const ITensorInfo *input, const ITensorInfo *dx, const ITensorInfo *dy, - const ITensorInfo *offsets, ITensorInfo *output, const ScaleKernelInfo &info) +Status CpuScaleKernel::validate(const ITensorInfo *input, const ITensorInfo *dx, const ITensorInfo *dy, + const ITensorInfo *offsets, ITensorInfo *output, const ScaleKernelInfo &info) { ARM_COMPUTE_RETURN_ON_ERROR(validate_arguments(input, dx, dy, offsets, output, info)); return Status{}; } -void NEScaleKernel::run(const Window &window, const ThreadInfo &info) +void CpuScaleKernel::run_op(ITensorPack &tensors, 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); + ARM_COMPUTE_ERROR_ON_INVALID_SUBWINDOW(ICpuKernel::window(), window); ARM_COMPUTE_ERROR_ON(_func == nullptr && _data_layout == DataLayout::NCHW); + const auto src = tensors.get_const_tensor(TensorType::ACL_SRC); + auto dst = tensors.get_tensor(TensorType::ACL_DST); + const auto dx = tensors.get_const_tensor(TensorType::ACL_INT_0); + const auto dy = tensors.get_const_tensor(TensorType::ACL_INT_1); + const auto offsets = tensors.get_const_tensor(TensorType::ACL_INT_2); + if(_data_layout == DataLayout::NCHW) { - (this->*_func)(window); + (this->*_func)(src, dst, dx, dy, offsets, window); } else { - const auto *uk = get_implementation(ScaleSelectorData{ _input->info()->data_type() }); - uk->ukernel(_input, _output, _offsets, _dx, _dy, _policy, _border_mode, _constant_border_value, _sampling_offset, _align_corners, window); + const auto *uk = get_implementation(ScaleSelectorData{ src->info()->data_type() }); + uk->ukernel(src, dst, offsets, dx, dy, _policy, _border_mode, _constant_border_value, _sampling_offset, _align_corners, window); } } + +const char *CpuScaleKernel::name() const +{ + return "CpuScaleKernel"; +} +} // namespace kernels +} // namespace cpu } // namespace arm_compute diff --git a/src/core/cpu/kernels/CpuScaleKernel.h b/src/core/cpu/kernels/CpuScaleKernel.h new file mode 100644 index 0000000000..c1de8e0736 --- /dev/null +++ b/src/core/cpu/kernels/CpuScaleKernel.h @@ -0,0 +1,111 @@ +/* + * Copyright (c) 2021 Arm Limited. + * + * SPDX-License-Identifier: MIT + * + * Permission is hereby granted, free of charge, to any person obtaining a copy + * of this software and associated documentation files (the "Software"), to + * deal in the Software without restriction, including without limitation the + * rights to use, copy, modify, merge, publish, distribute, sublicense, and/or + * sell copies of the Software, and to permit persons to whom the Software is + * furnished to do so, subject to the following conditions: + * + * The above copyright notice and this permission notice shall be included in all + * copies or substantial portions of the Software. + * + * THE SOFTWARE IS PROVIDED "AS IS", WITHOUT WARRANTY OF ANY KIND, EXPRESS OR + * IMPLIED, INCLUDING BUT NOT LIMITED TO THE WARRANTIES OF MERCHANTABILITY, + * FITNESS FOR A PARTICULAR PURPOSE AND NONINFRINGEMENT. IN NO EVENT SHALL THE + * AUTHORS OR COPYRIGHT HOLDERS BE LIABLE FOR ANY CLAIM, DAMAGES OR OTHER + * LIABILITY, WHETHER IN AN ACTION OF CONTRACT, TORT OR OTHERWISE, ARISING FROM, + * OUT OF OR IN CONNECTION WITH THE SOFTWARE OR THE USE OR OTHER DEALINGS IN THE + * SOFTWARE. + */ +#ifndef ARM_COMPUTE_CPU_SCALEKERNEL_H +#define ARM_COMPUTE_CPU_SCALEKERNEL_H + +#include "arm_compute/core/KernelDescriptors.h" +#include "src/core/common/Macros.h" +#include "src/core/cpu/ICpuKernel.h" + +namespace arm_compute +{ +namespace cpu +{ +namespace kernels +{ +/** Arm(R) Neon(TM) kernel to perform scaling on a tensor */ +class CpuScaleKernel : public ICpuKernel +{ +public: + /** Default constructor */ + CpuScaleKernel(); + ARM_COMPUTE_DISALLOW_COPY_ALLOW_MOVE(CpuScaleKernel); + /** Initialise the kernel's inputs, output and interpolation policy + * + * @note dx, dy and offsets have the same dimensions (width and height) of the output tensor + * @note Using @p policy Area only supports data layout NCHW and input data type U8. + * + * @param[in] src Source tensor info. Data types supported: QASYMM8/QASYMM8_SIGNED/U8/S16/F16/F32. + * @param[in] dx Distance x tensor info. Pixel's distance between the X real coordinate and the smallest X following integer. Data type supported: F32 + * @param[in] dy Distance y tensor info. Pixel's distance between the Y real coordinate and the smallest Y following integer. Data type supported: F32 + * @param[in] offsets Offset tensor info. 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] dst Destination tensor info. Data types supported: Same as @p input. 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] info @ref ScaleKernelInfo to use for configuration + */ + void configure(const ITensorInfo *src, const ITensorInfo *dx, const ITensorInfo *dy, const ITensorInfo *offsets, ITensorInfo *dst, + const ScaleKernelInfo &info); + /** Static function to check if given info will lead to a valid configuration of @ref CpuScaleKernel + * + * @note dx, dy and offsets have the same dimensions (width and height) of the output tensor + * @note Using @p policy Area only supports data layout NCHW and input data type U8. + * + * @param[in] src Source tensor. Data types supported: QASYMM8/QASYMM8_SIGNED/U8/S16/F16/F32. + * @param[in] dx Distance x tensor info. Pixel's distance between the X real coordinate and the smallest X following integer. Data type supported: F32 + * @param[in] dy Distance y tensor info. Pixel's distance between the Y real coordinate and the smallest Y following integer. Data type supported: F32 + * @param[in] offsets Offset tensor info. 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[in] dst Destination tensor info. Data types supported: Same as @p input. 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] info @ref ScaleKernelInfo to use for validation + */ + static Status validate(const ITensorInfo *src, const ITensorInfo *dx, const ITensorInfo *dy, const ITensorInfo *offsets, ITensorInfo *dst, + const ScaleKernelInfo &info); + + // Inherited methods overridden: + void run_op(ITensorPack &tensors, const Window &window, const ThreadInfo &info) override; + const char *name() const override; + +private: +#ifdef ENABLE_NCHW_KERNELS + /** function to perform scale using area interpolation on the given window + * + * @note Used only in case down-sampling. + */ + void scale_area_nchw_u8(const ITensor *src, ITensor *dst, const ITensor *dx, const ITensor *dy, const ITensor *offsets, const Window &window); + + /** function to perform scale using bilinear interpolation on the given window */ + template <typename T> + void scale_bilinear_nchw(const ITensor *src, ITensor *dst, const ITensor *dx, const ITensor *dy, const ITensor *offsets, const Window &window); + /** function to perform scale using bilinear interpolation on the given window */ + template <typename T> + void scale_bilinear_qasymm(const ITensor *src, ITensor *dst, const ITensor *dx, const ITensor *dy, const ITensor *offsets, const Window &window); + + /** function to perform scale using nearest neighbour on the given window */ + template <typename T> + void scale_nearest_nchw(const ITensor *src, ITensor *dst, const ITensor *dx, const ITensor *dy, const ITensor *offsets, const Window &window); +#endif // ENABLE_NCHW_KERNELS + + /** Scale function to use for the particular function to use */ + using ScaleFunctionPtr = void (CpuScaleKernel::*)(const ITensor *, ITensor *, const ITensor *, const ITensor *, const ITensor *, const Window &window); + + ScaleFunctionPtr _func; + InterpolationPolicy _policy; + BorderMode _border_mode; + PixelValue _constant_border_value; + float _sampling_offset; + bool _align_corners; + DataLayout _data_layout; +}; +} // namespace kernels +} // namespace cpu +} // namespace arm_compute +#endif /*ARM_COMPUTE_CPU_SCALEKERNEL_H */ diff --git a/src/core/NEON/kernels/scale/impl/NEON/fp16.cpp b/src/core/cpu/kernels/scale/neon/fp16.cpp index 0ad66cab1c..0ad66cab1c 100644 --- a/src/core/NEON/kernels/scale/impl/NEON/fp16.cpp +++ b/src/core/cpu/kernels/scale/neon/fp16.cpp diff --git a/src/core/NEON/kernels/scale/impl/NEON/integer.cpp b/src/core/cpu/kernels/scale/neon/integer.cpp index a2359aac94..a2359aac94 100644 --- a/src/core/NEON/kernels/scale/impl/NEON/integer.cpp +++ b/src/core/cpu/kernels/scale/neon/integer.cpp diff --git a/src/core/NEON/kernels/scale/impl/NEON/list.h b/src/core/cpu/kernels/scale/neon/list.h index c91242f5b2..c91242f5b2 100644 --- a/src/core/NEON/kernels/scale/impl/NEON/list.h +++ b/src/core/cpu/kernels/scale/neon/list.h diff --git a/src/core/NEON/kernels/scale/impl/NEON/qasymm8.cpp b/src/core/cpu/kernels/scale/neon/qasymm8.cpp index 536ad2cd17..90302ce889 100644 --- a/src/core/NEON/kernels/scale/impl/NEON/qasymm8.cpp +++ b/src/core/cpu/kernels/scale/neon/qasymm8.cpp @@ -21,7 +21,7 @@ * OUT OF OR IN CONNECTION WITH THE SOFTWARE OR THE USE OR OTHER DEALINGS IN THE * SOFTWARE. */ -#include "src/core/NEON/kernels/scale/impl/NEON/list.h" +#include "src/core/cpu/kernels/scale/neon/list.h" namespace arm_compute { @@ -31,13 +31,9 @@ void qasymm8_neon_scale_bilinear(const ITensor *src, ITensor *dst, const ITensor BorderMode border_mode, PixelValue constant_border_value, float sampling_offset, bool align_corners, const Window &window) { - // Get data layout and width/height indices - const DataLayout data_layout = src->info()->data_layout(); - const int idx_width = get_data_layout_dimension_index(data_layout, DataLayoutDimension::WIDTH); - const int idx_height = get_data_layout_dimension_index(data_layout, DataLayoutDimension::HEIGHT); - + // Data layout is NHWC // Compute the ratio between source height and destination height - const auto hr = scale_utils::calculate_resize_ratio(src->info()->dimension(idx_height), dst->info()->dimension(idx_height), align_corners); + const auto hr = scale_utils::calculate_resize_ratio(src->info()->dimension(2), dst->info()->dimension(2), align_corners); Window win_off; win_off.set(Window::DimX, Window::Dimension(0, 0, 0)); win_off.set(Window::DimY, Window::Dimension(0, 0, 0)); @@ -45,8 +41,8 @@ void qasymm8_neon_scale_bilinear(const ITensor *src, ITensor *dst, const ITensor // 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(idx_width, Window::Dimension(0, 0, 0)); - win_in.set(idx_height, Window::Dimension(0, 0, 0)); + win_in.set(1, Window::Dimension(0, 0, 0)); + win_in.set(2, Window::Dimension(0, 0, 0)); for(size_t d = Window::DimZ; d < offsets->info()->num_dimensions(); ++d) { @@ -56,10 +52,10 @@ void qasymm8_neon_scale_bilinear(const ITensor *src, ITensor *dst, const ITensor Iterator in(src, win_in); Iterator out(dst, window); - const int32_t in_dim_w = src->info()->dimension(idx_width); - const int32_t in_dim_h = src->info()->dimension(idx_height); - const int32_t stride_w = src->info()->strides_in_bytes()[idx_width]; - const int32_t stride_h = src->info()->strides_in_bytes()[idx_height]; + const int32_t in_dim_w = src->info()->dimension(1); + const int32_t in_dim_h = src->info()->dimension(2); + const int32_t stride_w = src->info()->strides_in_bytes()[1]; + const int32_t stride_h = src->info()->strides_in_bytes()[2]; const UniformQuantizationInfo iq_info = src->info()->quantization_info().uniform(); const UniformQuantizationInfo oq_info = dst->info()->quantization_info().uniform(); @@ -69,10 +65,10 @@ void qasymm8_neon_scale_bilinear(const ITensor *src, ITensor *dst, const ITensor const uint8_t const_border_value = static_cast<uint8_t>(constant_border_value.get<uint8_t>()); execute_window_loop(window, [&](const Coordinates & id) { - const int32_t index_h = std::floor((id[idx_height] + sampling_offset) * hr - sampling_offset); - const int32_t index_w = *(reinterpret_cast<const int32_t *>(offsets->ptr_to_element(Coordinates(id[idx_width], id[idx_height])))); - const auto dx_val = *(reinterpret_cast<const float *>(dx->ptr_to_element(Coordinates(id[idx_width], id[idx_height])))); - const auto dy_val = *(reinterpret_cast<const float *>(dy->ptr_to_element(Coordinates(id[idx_width], id[idx_height])))); + const int32_t index_h = std::floor((id[2] + sampling_offset) * hr - sampling_offset); + const int32_t index_w = *(reinterpret_cast<const int32_t *>(offsets->ptr_to_element(Coordinates(id[1], id[2])))); + const auto dx_val = *(reinterpret_cast<const float *>(dx->ptr_to_element(Coordinates(id[1], id[2])))); + const auto dy_val = *(reinterpret_cast<const float *>(dy->ptr_to_element(Coordinates(id[1], id[2])))); const auto pixel_row_ptr = reinterpret_cast<const uint8_t *>(in.ptr()); const auto a00 = (0 <= index_w && index_w < in_dim_w && 0 <= index_h && index_h < in_dim_h) ? @@ -100,10 +96,10 @@ void qasymm8_neon_scale_bilinear(const ITensor *src, ITensor *dst, const ITensor { execute_window_loop(window, [&](const Coordinates & id) { - const int index_h = std::floor((id[idx_height] + sampling_offset) * hr - sampling_offset); - const int32_t index_w = *(reinterpret_cast<const int32_t *>(offsets->ptr_to_element(Coordinates(id[idx_width], id[idx_height])))); - const auto dx_val = *(reinterpret_cast<const float *>(dx->ptr_to_element(Coordinates(id[idx_width], id[idx_height])))); - const auto dy_val = *(reinterpret_cast<const float *>(dy->ptr_to_element(Coordinates(id[idx_width], id[idx_height])))); + const int index_h = std::floor((id[2] + sampling_offset) * hr - sampling_offset); + const int32_t index_w = *(reinterpret_cast<const int32_t *>(offsets->ptr_to_element(Coordinates(id[1], id[2])))); + const auto dx_val = *(reinterpret_cast<const float *>(dx->ptr_to_element(Coordinates(id[1], id[2])))); + const auto dy_val = *(reinterpret_cast<const float *>(dy->ptr_to_element(Coordinates(id[1], id[2])))); const auto pixel_row_ptr = reinterpret_cast<const uint8_t *>(in.ptr()); auto clamped_w = utility::clamp<int>(index_w, 0, in_dim_w - 1); diff --git a/src/core/NEON/kernels/scale/impl/NEON/qasymm8_signed.cpp b/src/core/cpu/kernels/scale/neon/qasymm8_signed.cpp index 149cdf478f..07d6c6ef03 100644 --- a/src/core/NEON/kernels/scale/impl/NEON/qasymm8_signed.cpp +++ b/src/core/cpu/kernels/scale/neon/qasymm8_signed.cpp @@ -21,7 +21,7 @@ * OUT OF OR IN CONNECTION WITH THE SOFTWARE OR THE USE OR OTHER DEALINGS IN THE * SOFTWARE. */ -#include "src/core/NEON/kernels/scale/impl/NEON/list.h" +#include "src/core/cpu/kernels/scale/neon/list.h" namespace arm_compute { @@ -31,13 +31,9 @@ void qasymm8_signed_neon_scale_bilinear(const ITensor *src, ITensor *dst, const BorderMode border_mode, PixelValue constant_border_value, float sampling_offset, bool align_corners, const Window &window) { - // Get data layout and width/height indices - const DataLayout data_layout = src->info()->data_layout(); - const int idx_width = get_data_layout_dimension_index(data_layout, DataLayoutDimension::WIDTH); - const int idx_height = get_data_layout_dimension_index(data_layout, DataLayoutDimension::HEIGHT); - + // Data layout is NHWC // Compute the ratio between source height and destination height - const auto hr = scale_utils::calculate_resize_ratio(src->info()->dimension(idx_height), dst->info()->dimension(idx_height), align_corners); + const auto hr = scale_utils::calculate_resize_ratio(src->info()->dimension(2), dst->info()->dimension(2), align_corners); Window win_off; win_off.set(Window::DimX, Window::Dimension(0, 0, 0)); win_off.set(Window::DimY, Window::Dimension(0, 0, 0)); @@ -45,8 +41,8 @@ void qasymm8_signed_neon_scale_bilinear(const ITensor *src, ITensor *dst, const // 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(idx_width, Window::Dimension(0, 0, 0)); - win_in.set(idx_height, Window::Dimension(0, 0, 0)); + win_in.set(1, Window::Dimension(0, 0, 0)); + win_in.set(2, Window::Dimension(0, 0, 0)); for(size_t d = Window::DimZ; d < offsets->info()->num_dimensions(); ++d) { @@ -56,10 +52,10 @@ void qasymm8_signed_neon_scale_bilinear(const ITensor *src, ITensor *dst, const Iterator in(src, win_in); Iterator out(dst, window); - const int32_t in_dim_w = src->info()->dimension(idx_width); - const int32_t in_dim_h = src->info()->dimension(idx_height); - const int32_t stride_w = src->info()->strides_in_bytes()[idx_width]; - const int32_t stride_h = src->info()->strides_in_bytes()[idx_height]; + const int32_t in_dim_w = src->info()->dimension(1); + const int32_t in_dim_h = src->info()->dimension(2); + const int32_t stride_w = src->info()->strides_in_bytes()[1]; + const int32_t stride_h = src->info()->strides_in_bytes()[2]; const UniformQuantizationInfo iq_info = src->info()->quantization_info().uniform(); const UniformQuantizationInfo oq_info = dst->info()->quantization_info().uniform(); @@ -69,10 +65,10 @@ void qasymm8_signed_neon_scale_bilinear(const ITensor *src, ITensor *dst, const const int8_t const_border_value = static_cast<int8_t>(constant_border_value.get<int8_t>()); execute_window_loop(window, [&](const Coordinates & id) { - const int32_t index_h = std::floor((id[idx_height] + sampling_offset) * hr - sampling_offset); - const int32_t index_w = *(reinterpret_cast<const int32_t *>(offsets->ptr_to_element(Coordinates(id[idx_width], id[idx_height])))); - const auto dx_val = *(reinterpret_cast<const float *>(dx->ptr_to_element(Coordinates(id[idx_width], id[idx_height])))); - const auto dy_val = *(reinterpret_cast<const float *>(dy->ptr_to_element(Coordinates(id[idx_width], id[idx_height])))); + const int32_t index_h = std::floor((id[2] + sampling_offset) * hr - sampling_offset); + const int32_t index_w = *(reinterpret_cast<const int32_t *>(offsets->ptr_to_element(Coordinates(id[1], id[2])))); + const auto dx_val = *(reinterpret_cast<const float *>(dx->ptr_to_element(Coordinates(id[1], id[2])))); + const auto dy_val = *(reinterpret_cast<const float *>(dy->ptr_to_element(Coordinates(id[1], id[2])))); const auto pixel_row_ptr = reinterpret_cast<const int8_t *>(in.ptr()); const auto a00 = (0 <= index_w && index_w < in_dim_w && 0 <= index_h && index_h < in_dim_h) ? @@ -100,10 +96,10 @@ void qasymm8_signed_neon_scale_bilinear(const ITensor *src, ITensor *dst, const { execute_window_loop(window, [&](const Coordinates & id) { - const int index_h = std::floor((id[idx_height] + sampling_offset) * hr - sampling_offset); - const int32_t index_w = *(reinterpret_cast<const int32_t *>(offsets->ptr_to_element(Coordinates(id[idx_width], id[idx_height])))); - const auto dx_val = *(reinterpret_cast<const float *>(dx->ptr_to_element(Coordinates(id[idx_width], id[idx_height])))); - const auto dy_val = *(reinterpret_cast<const float *>(dy->ptr_to_element(Coordinates(id[idx_width], id[idx_height])))); + const int index_h = std::floor((id[2] + sampling_offset) * hr - sampling_offset); + const int32_t index_w = *(reinterpret_cast<const int32_t *>(offsets->ptr_to_element(Coordinates(id[1], id[2])))); + const auto dx_val = *(reinterpret_cast<const float *>(dx->ptr_to_element(Coordinates(id[1], id[2])))); + const auto dy_val = *(reinterpret_cast<const float *>(dy->ptr_to_element(Coordinates(id[1], id[2])))); const auto pixel_row_ptr = reinterpret_cast<const int8_t *>(in.ptr()); auto clamped_w = utility::clamp<int>(index_w, 0, in_dim_w - 1); diff --git a/src/core/NEON/kernels/scale/impl/SVE/fp16.cpp b/src/core/cpu/kernels/scale/sve/fp16.cpp index 99f08dbdf9..99f08dbdf9 100644 --- a/src/core/NEON/kernels/scale/impl/SVE/fp16.cpp +++ b/src/core/cpu/kernels/scale/sve/fp16.cpp diff --git a/src/core/NEON/kernels/scale/impl/SVE/fp32.cpp b/src/core/cpu/kernels/scale/sve/fp32.cpp index 94055ae953..94055ae953 100644 --- a/src/core/NEON/kernels/scale/impl/SVE/fp32.cpp +++ b/src/core/cpu/kernels/scale/sve/fp32.cpp diff --git a/src/core/NEON/kernels/scale/impl/SVE/integer.cpp b/src/core/cpu/kernels/scale/sve/integer.cpp index 2a724ece31..2a724ece31 100644 --- a/src/core/NEON/kernels/scale/impl/SVE/integer.cpp +++ b/src/core/cpu/kernels/scale/sve/integer.cpp diff --git a/src/core/NEON/kernels/scale/impl/SVE/list.h b/src/core/cpu/kernels/scale/sve/list.h index b9c3a10a78..b9c3a10a78 100644 --- a/src/core/NEON/kernels/scale/impl/SVE/list.h +++ b/src/core/cpu/kernels/scale/sve/list.h diff --git a/src/core/NEON/kernels/scale/impl/SVE/qasymm8.cpp b/src/core/cpu/kernels/scale/sve/qasymm8.cpp index c475ad615c..c475ad615c 100644 --- a/src/core/NEON/kernels/scale/impl/SVE/qasymm8.cpp +++ b/src/core/cpu/kernels/scale/sve/qasymm8.cpp diff --git a/src/core/NEON/kernels/scale/impl/SVE/qasymm8_signed.cpp b/src/core/cpu/kernels/scale/sve/qasymm8_signed.cpp index b39b75abba..b39b75abba 100644 --- a/src/core/NEON/kernels/scale/impl/SVE/qasymm8_signed.cpp +++ b/src/core/cpu/kernels/scale/sve/qasymm8_signed.cpp diff --git a/src/runtime/NEON/functions/NECropResize.cpp b/src/runtime/NEON/functions/NECropResize.cpp index af85cac7da..1e1070d961 100644 --- a/src/runtime/NEON/functions/NECropResize.cpp +++ b/src/runtime/NEON/functions/NECropResize.cpp @@ -1,5 +1,5 @@ /* - * Copyright (c) 2019-2020 Arm Limited. + * Copyright (c) 2019-2021 Arm Limited. * * SPDX-License-Identifier: MIT * @@ -24,6 +24,7 @@ #include "arm_compute/runtime/NEON/NEScheduler.h" #include "arm_compute/runtime/NEON/functions/NECropResize.h" +#include "arm_compute/runtime/Tensor.h" #include "src/core/NEON/kernels/NECropKernel.h" #include <cstddef> diff --git a/src/runtime/NEON/functions/NEScale.cpp b/src/runtime/NEON/functions/NEScale.cpp index f91de32191..0fbad07d0f 100644 --- a/src/runtime/NEON/functions/NEScale.cpp +++ b/src/runtime/NEON/functions/NEScale.cpp @@ -23,191 +23,99 @@ */ #include "arm_compute/runtime/NEON/functions/NEScale.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/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 "src/core/NEON/kernels/NEScaleKernel.h" - +#include "arm_compute/core/Validate.h" +#include "arm_compute/runtime/Tensor.h" #include "src/core/utils/ScaleUtils.h" - +#include "src/runtime/cpu/operators/CpuScale.h" #include "support/Rounding.h" -#include <cmath> -#include <cstddef> -#include <utility> - namespace arm_compute { -namespace -{ -void precompute_dx_dy_offsets(ITensor *dx, ITensor *dy, ITensor *offsets, float wr, float hr, SamplingPolicy sampling_policy, bool align_corners) +struct NEScale::Impl { - ARM_COMPUTE_ERROR_ON(nullptr == offsets); - ARM_COMPUTE_UNUSED(sampling_policy); - float sampling_offset = 0.0f; - if(sampling_policy == SamplingPolicy::CENTER) - { - sampling_offset = 0.5f; - } - - Window win; - win.set(Window::DimX, Window::Dimension(0, offsets->info()->dimension(0), 1)); - win.set(Window::DimY, Window::Dimension(0, offsets->info()->dimension(1), 1)); - - if(dx != nullptr && dy != nullptr) - { - // Pre-compute the offset and pixel's distance for BILINEAR interpolation - Iterator offsets_it(offsets, win); - Iterator dx_it(dx, win); - Iterator dy_it(dy, win); - - execute_window_loop(win, [&](const Coordinates & id) - { - const float in_x = (id.x() + sampling_offset) * wr - sampling_offset; - const float in_y = (id.y() + sampling_offset) * hr - sampling_offset; - const int in_xi = std::floor(in_x); - const int in_yi = std::floor(in_y); - - *reinterpret_cast<int32_t *>(offsets_it.ptr()) = in_xi; - *reinterpret_cast<float *>(dx_it.ptr()) = in_x - in_xi; - *reinterpret_cast<float *>(dy_it.ptr()) = in_y - in_yi; - }, - offsets_it, dx_it, dy_it); - } - else - { - // Pre-compute the offset for NEAREST interpolation - Iterator offsets_it(offsets, win); - - execute_window_loop(win, [&](const Coordinates & id) - { - const float float_in_xi = (id.x() + sampling_offset) * wr; - const auto in_xi = static_cast<size_t>(align_corners ? arm_compute::utils::rounding::round_half_away_from_zero(float_in_xi) : std::floor(float_in_xi)); - *reinterpret_cast<int32_t *>(offsets_it.ptr()) = in_xi; - }, - offsets_it); - } -} -} // namespace + const ITensor *src{ nullptr }; + ITensor *dst{ nullptr }; + Tensor dx{ nullptr }; /**< Element's distance between the X real coordinate and the smallest X following integer */ + Tensor dy{ nullptr }; /**< Element's distance between the Y real coordinate and the smallest Y following integer */ + Tensor offsets{ nullptr }; /**< Offset to access the element with NEAREST interpolation or the top-left element with BILINEAR interpolation in the input tensor */ + std::unique_ptr<cpu::CpuScale> op{ nullptr }; +}; NEScale::NEScale() - : _offsets(), _dx(), _dy() + : _impl(std::make_unique<Impl>()) { } +NEScale::~NEScale() = default; void NEScale::configure(ITensor *input, ITensor *output, const ScaleKernelInfo &info) { - ARM_COMPUTE_ERROR_ON_NULLPTR(input, output); - ARM_COMPUTE_ERROR_THROW_ON(NEScale::validate(input->info(), output->info(), info)); - - const bool is_align_corners_used = info.align_corners && arm_compute::scale_utils::is_align_corners_allowed_sampling_policy(info.sampling_policy); + _impl->src = input; + _impl->dst = output; + _impl->op = std::make_unique<cpu::CpuScale>(); + _impl->op->configure(input->info(), output->info(), info); + // Configure for size of allocation of internal tensors // Get data layout and width/height indices const DataLayout data_layout = info.data_layout == DataLayout::UNKNOWN ? input->info()->data_layout() : info.data_layout; const int idx_width = get_data_layout_dimension_index(data_layout, DataLayoutDimension::WIDTH); const int idx_height = get_data_layout_dimension_index(data_layout, DataLayoutDimension::HEIGHT); + // Compute the ratio between source width/height and destination width/height + const bool is_align_corners_used = info.align_corners && arm_compute::scale_utils::is_align_corners_allowed_sampling_policy(info.sampling_policy); + const auto wr = arm_compute::scale_utils::calculate_resize_ratio(input->info()->dimension(idx_width), output->info()->dimension(idx_width), is_align_corners_used); + const auto hr = arm_compute::scale_utils::calculate_resize_ratio(input->info()->dimension(idx_height), output->info()->dimension(idx_height), is_align_corners_used); + + // Area interpolation behaves as Nearest Neighbour in case of up-sampling + InterpolationPolicy policy_to_use = (info.interpolation_policy == InterpolationPolicy::AREA && wr <= 1.f && hr <= 1.f) ? InterpolationPolicy::NEAREST_NEIGHBOR : info.interpolation_policy; + // Get the tensor shape TensorShape shape(output->info()->dimension(idx_width)); shape.set(1, output->info()->dimension(idx_height), false); - // Compute the ratio between source width/height and destination width/height - const auto wr = arm_compute::scale_utils::calculate_resize_ratio(input->info()->dimension(idx_width), output->info()->dimension(idx_width), is_align_corners_used); - const auto hr = arm_compute::scale_utils::calculate_resize_ratio(input->info()->dimension(idx_height), output->info()->dimension(idx_height), is_align_corners_used); + const TensorInfo tensor_info_dxdy(shape, Format::F32); + const TensorInfo tensor_info_offsets(shape, Format::S32); - // Area interpolation behaves as Nearest Neighbour in case of up-sampling - const auto policy_to_use = (info.interpolation_policy == InterpolationPolicy::AREA && wr <= 1.f && hr <= 1.f) ? InterpolationPolicy::NEAREST_NEIGHBOR : info.interpolation_policy; - - auto scale_kernel = std::make_unique<NEScaleKernel>(); + _impl->dx.allocator()->init(tensor_info_dxdy); + _impl->dy.allocator()->init(tensor_info_dxdy); + _impl->offsets.allocator()->init(tensor_info_offsets); switch(policy_to_use) { case InterpolationPolicy::NEAREST_NEIGHBOR: { - TensorInfo tensor_info_offsets(shape, Format::S32); - _offsets.allocator()->init(tensor_info_offsets); - - scale_kernel->configure(input, nullptr, nullptr, &_offsets, output, info); - // Allocate once the configure methods have been called - _offsets.allocator()->allocate(); - - // Pre-compute offsets for nearest interpolation - precompute_dx_dy_offsets(nullptr, nullptr, &_offsets, wr, hr, info.sampling_policy, is_align_corners_used); + _impl->offsets.allocator()->allocate(); break; } case InterpolationPolicy::BILINEAR: { - TensorInfo tensor_info_offsets(shape, Format::S32); - TensorInfo tensor_info_dxdy(shape, Format::F32); - - _offsets.allocator()->init(tensor_info_offsets); - _dx.allocator()->init(tensor_info_dxdy); - _dy.allocator()->init(tensor_info_dxdy); - - scale_kernel->configure(input, &_dx, &_dy, &_offsets, output, info); - // Allocate once the configure methods have been called - _offsets.allocator()->allocate(); - _dx.allocator()->allocate(); - _dy.allocator()->allocate(); - - // Pre-compute dx, dy and offsets for bilinear interpolation - precompute_dx_dy_offsets(&_dx, &_dy, &_offsets, wr, hr, info.sampling_policy, is_align_corners_used); + _impl->dx.allocator()->allocate(); + _impl->dy.allocator()->allocate(); + _impl->offsets.allocator()->allocate(); break; } case InterpolationPolicy::AREA: { - scale_kernel->configure(input, nullptr, nullptr, nullptr, output, info); break; } default: ARM_COMPUTE_ERROR("Unsupported interpolation mode"); } - _kernel = std::move(scale_kernel); } Status NEScale::validate(const ITensorInfo *input, const ITensorInfo *output, const ScaleKernelInfo &info) { - ARM_COMPUTE_RETURN_ERROR_ON_NULLPTR(input, output); - ARM_COMPUTE_RETURN_ERROR_ON(info.sampling_policy != SamplingPolicy::CENTER && info.sampling_policy != SamplingPolicy::TOP_LEFT); - - ITensorInfo *offsets = nullptr; - ITensorInfo *dx = nullptr; - ITensorInfo *dy = nullptr; - - // Get data layout and width/height indices - const DataLayout data_layout = info.data_layout == DataLayout::UNKNOWN ? input->data_layout() : info.data_layout; - const int idx_width = get_data_layout_dimension_index(data_layout, DataLayoutDimension::WIDTH); - const int idx_height = get_data_layout_dimension_index(data_layout, DataLayoutDimension::HEIGHT); - - // Get the tensor shape of auxilary buffers - const TensorShape shape(output->dimension(idx_width), output->dimension(idx_height)); - - TensorInfo tensor_info_offsets(shape, Format::S32); - TensorInfo tensor_info_dx(shape, Format::F32); - TensorInfo tensor_info_dy(shape, Format::F32); - - switch(info.interpolation_policy) - { - case InterpolationPolicy::NEAREST_NEIGHBOR: - offsets = &tensor_info_offsets; - break; - case InterpolationPolicy::BILINEAR: - offsets = &tensor_info_offsets; - dx = &tensor_info_dx; - dy = &tensor_info_dy; - break; - default: - break; - } + return cpu::CpuScale::validate(input, output, info); +} - ARM_COMPUTE_RETURN_ON_ERROR(NEScaleKernel::validate(input->clone().get(), dx, dy, offsets, output->clone().get(), info)); - return Status{}; +void NEScale::run() +{ + ITensorPack pack; + pack.add_tensor(TensorType::ACL_SRC, _impl->src); + pack.add_tensor(TensorType::ACL_DST, _impl->dst); + pack.add_tensor(TensorType::ACL_INT_0, &_impl->dx); + pack.add_tensor(TensorType::ACL_INT_1, &_impl->dy); + pack.add_tensor(TensorType::ACL_INT_2, &_impl->offsets); + _impl->op->run(pack); } } // namespace arm_compute diff --git a/src/runtime/cpu/operators/CpuScale.cpp b/src/runtime/cpu/operators/CpuScale.cpp new file mode 100644 index 0000000000..681a15e26c --- /dev/null +++ b/src/runtime/cpu/operators/CpuScale.cpp @@ -0,0 +1,254 @@ +/* + * Copyright (c) 2021 Arm Limited. + * + * SPDX-License-Identifier: MIT + * + * Permission is hereby granted, free of charge, to any person obtaining a copy + * of this software and associated documentation files (the "Software"), to + * deal in the Software without restriction, including without limitation the + * rights to use, copy, modify, merge, publish, distribute, sublicense, and/or + * sell copies of the Software, and to permit persons to whom the Software is + * furnished to do so, subject to the following conditions: + * + * The above copyright notice and this permission notice shall be included in all + * copies or substantial portions of the Software. + * + * THE SOFTWARE IS PROVIDED "AS IS", WITHOUT WARRANTY OF ANY KIND, EXPRESS OR + * IMPLIED, INCLUDING BUT NOT LIMITED TO THE WARRANTIES OF MERCHANTABILITY, + * FITNESS FOR A PARTICULAR PURPOSE AND NONINFRINGEMENT. IN NO EVENT SHALL THE + * AUTHORS OR COPYRIGHT HOLDERS BE LIABLE FOR ANY CLAIM, DAMAGES OR OTHER + * LIABILITY, WHETHER IN AN ACTION OF CONTRACT, TORT OR OTHERWISE, ARISING FROM, + * OUT OF OR IN CONNECTION WITH THE SOFTWARE OR THE USE OR OTHER DEALINGS IN THE + * SOFTWARE. + */ +#include "src/runtime/cpu/operators/CpuScale.h" + +#include "arm_compute/core/Helpers.h" +#include "arm_compute/core/TensorInfo.h" +#include "arm_compute/core/Validate.h" +#include "arm_compute/runtime/NEON/NEScheduler.h" +#include "src/core/cpu/kernels/CpuScaleKernel.h" +#include "src/core/utils/ScaleUtils.h" +#include "support/Rounding.h" + +namespace arm_compute +{ +namespace cpu +{ +namespace +{ +void precompute_dx_dy_offsets(ITensor *dx, ITensor *dy, ITensor *offsets, float wr, float hr, SamplingPolicy sampling_policy, bool align_corners) +{ + ARM_COMPUTE_ERROR_ON(offsets == nullptr); + float sampling_offset = 0.0f; + if(sampling_policy == SamplingPolicy::CENTER) + { + sampling_offset = 0.5f; + } + + Window win; + win.set(Window::DimX, Window::Dimension(0, offsets->info()->dimension(0), 1)); + win.set(Window::DimY, Window::Dimension(0, offsets->info()->dimension(1), 1)); + + if(dx != nullptr && dy != nullptr) + { + // Pre-compute the offset and pixel's distance for BILINEAR interpolation + Iterator offsets_it(offsets, win); + Iterator dx_it(dx, win); + Iterator dy_it(dy, win); + + execute_window_loop(win, [&](const Coordinates & id) + { + const float in_x = (id.x() + sampling_offset) * wr - sampling_offset; + const float in_y = (id.y() + sampling_offset) * hr - sampling_offset; + const int in_xi = std::floor(in_x); + const int in_yi = std::floor(in_y); + + *reinterpret_cast<int32_t *>(offsets_it.ptr()) = in_xi; + *reinterpret_cast<float *>(dx_it.ptr()) = in_x - in_xi; + *reinterpret_cast<float *>(dy_it.ptr()) = in_y - in_yi; + }, + offsets_it, dx_it, dy_it); + } + else + { + // Pre-compute the offset for NEAREST interpolation + Iterator offsets_it(offsets, win); + + execute_window_loop(win, [&](const Coordinates & id) + { + const float float_in_xi = (id.x() + sampling_offset) * wr; + const auto in_xi = static_cast<size_t>(align_corners ? arm_compute::utils::rounding::round_half_away_from_zero(float_in_xi) : std::floor(float_in_xi)); + *reinterpret_cast<int32_t *>(offsets_it.ptr()) = in_xi; + }, + offsets_it); + } +} +} // namespace + +CpuScale::CpuScale() + : _scale_info(InterpolationPolicy::NEAREST_NEIGHBOR, BorderMode::UNDEFINED), _data_layout(DataLayout::UNKNOWN), _is_prepared(false) +{ +} + +void CpuScale::configure(ITensorInfo *src, ITensorInfo *dst, const ScaleKernelInfo &info) +{ + ARM_COMPUTE_ERROR_ON_NULLPTR(src, dst); + ARM_COMPUTE_ERROR_THROW_ON(CpuScale::validate(src, dst, info)); + + _scale_info = info; + + // Get data layout and width/height indices + _data_layout = _scale_info.data_layout == DataLayout::UNKNOWN ? src->data_layout() : _scale_info.data_layout; + const int idx_width = get_data_layout_dimension_index(_data_layout, DataLayoutDimension::WIDTH); + const int idx_height = get_data_layout_dimension_index(_data_layout, DataLayoutDimension::HEIGHT); + + // Compute the ratio between source width/height and destination width/height + const bool is_align_corners_used = _scale_info.align_corners && arm_compute::scale_utils::is_align_corners_allowed_sampling_policy(_scale_info.sampling_policy); + const auto wr = arm_compute::scale_utils::calculate_resize_ratio(src->dimension(idx_width), dst->dimension(idx_width), is_align_corners_used); + const auto hr = arm_compute::scale_utils::calculate_resize_ratio(src->dimension(idx_height), dst->dimension(idx_height), is_align_corners_used); + + // Area interpolation behaves as Nearest Neighbour in case of up-sampling + InterpolationPolicy policy_to_use = (_scale_info.interpolation_policy == InterpolationPolicy::AREA && wr <= 1.f + && hr <= 1.f) ? + InterpolationPolicy::NEAREST_NEIGHBOR : + _scale_info.interpolation_policy; + + // Get the tensor shape + TensorShape shape(dst->dimension(idx_width)); + shape.set(1, dst->dimension(idx_height), false); + + TensorInfo tensor_info_offsets(shape, Format::S32); + TensorInfo tensor_info_dxdy(shape, Format::F32); + + auto dx = std::make_unique<TensorInfo>(tensor_info_dxdy); + auto dy = std::make_unique<TensorInfo>(tensor_info_dxdy); + auto offsets = std::make_unique<TensorInfo>(tensor_info_offsets); + auto scale_kernel = std::make_unique<kernels::CpuScaleKernel>(); + switch(policy_to_use) + { + case InterpolationPolicy::NEAREST_NEIGHBOR: + { + scale_kernel->configure(src, nullptr, nullptr, offsets.get(), dst, info); + break; + } + case InterpolationPolicy::BILINEAR: + { + scale_kernel->configure(src, dx.get(), dy.get(), offsets.get(), dst, info); + break; + } + case InterpolationPolicy::AREA: + { + scale_kernel->configure(src, nullptr, nullptr, nullptr, dst, info); + break; + } + default: + ARM_COMPUTE_ERROR("Unsupported interpolation mode"); + } + _kernel = std::move(scale_kernel); +} + +Status CpuScale::validate(const ITensorInfo *src, const ITensorInfo *dst, const ScaleKernelInfo &info) +{ + ARM_COMPUTE_RETURN_ERROR_ON_NULLPTR(src, dst); + ARM_COMPUTE_RETURN_ERROR_ON(info.sampling_policy != SamplingPolicy::CENTER && info.sampling_policy != SamplingPolicy::TOP_LEFT); + + ITensorInfo *offsets = nullptr; + ITensorInfo *dx = nullptr; + ITensorInfo *dy = nullptr; + + // Get data layout and width/height indices + const DataLayout data_layout = info.data_layout == DataLayout::UNKNOWN ? src->data_layout() : info.data_layout; + const int idx_width = get_data_layout_dimension_index(data_layout, DataLayoutDimension::WIDTH); + const int idx_height = get_data_layout_dimension_index(data_layout, DataLayoutDimension::HEIGHT); + + // Compute the ratio between source width/height and destination width/height + const bool is_align_corners_used = info.align_corners && arm_compute::scale_utils::is_align_corners_allowed_sampling_policy(info.sampling_policy); + const auto wr = arm_compute::scale_utils::calculate_resize_ratio(src->dimension(idx_width), dst->dimension(idx_width), is_align_corners_used); + const auto hr = arm_compute::scale_utils::calculate_resize_ratio(src->dimension(idx_height), dst->dimension(idx_height), is_align_corners_used); + + // Area interpolation behaves as Nearest Neighbour in case of up-sampling + InterpolationPolicy policy_to_use = (info.interpolation_policy == InterpolationPolicy::AREA && wr <= 1.f && hr <= 1.f) ? InterpolationPolicy::NEAREST_NEIGHBOR : info.interpolation_policy; + + // Get the tensor shape of auxilary buffers + const TensorShape shape(dst->dimension(idx_width), dst->dimension(idx_height)); + TensorInfo tensor_info_offsets(shape, Format::S32); + TensorInfo tensor_info_dx(shape, Format::F32); + TensorInfo tensor_info_dy(shape, Format::F32); + switch(policy_to_use) + { + case InterpolationPolicy::NEAREST_NEIGHBOR: + offsets = &tensor_info_offsets; + break; + case InterpolationPolicy::BILINEAR: + offsets = &tensor_info_offsets; + dx = &tensor_info_dx; + dy = &tensor_info_dy; + break; + default: + break; + } + + ARM_COMPUTE_RETURN_ON_ERROR(kernels::CpuScaleKernel::validate(src->clone().get(), dx, dy, offsets, dst->clone().get(), info)); + return Status{}; +} + +void CpuScale::prepare(ITensorPack &tensors) +{ + if(!_is_prepared) + { + _is_prepared = true; + const auto src = tensors.get_const_tensor(TensorType::ACL_SRC); + auto dst = tensors.get_tensor(TensorType::ACL_DST); + auto dx = tensors.get_tensor(TensorType::ACL_INT_0); + auto dy = tensors.get_tensor(TensorType::ACL_INT_1); + auto offsets = tensors.get_tensor(TensorType::ACL_INT_2); + + // Get data layout and width/height indices + const int idx_width = get_data_layout_dimension_index(_data_layout, DataLayoutDimension::WIDTH); + const int idx_height = get_data_layout_dimension_index(_data_layout, DataLayoutDimension::HEIGHT); + + // Compute the ratio between source width/height and destination width/height + const bool is_align_corners_used = _scale_info.align_corners && arm_compute::scale_utils::is_align_corners_allowed_sampling_policy(_scale_info.sampling_policy); + const auto wr = arm_compute::scale_utils::calculate_resize_ratio(src->info()->dimension(idx_width), dst->info()->dimension(idx_width), is_align_corners_used); + const auto hr = arm_compute::scale_utils::calculate_resize_ratio(src->info()->dimension(idx_height), dst->info()->dimension(idx_height), is_align_corners_used); + + // Area interpolation behaves as Nearest Neighbour in case of up-sampling + InterpolationPolicy policy_to_use = (_scale_info.interpolation_policy == InterpolationPolicy::AREA && wr <= 1.f + && hr <= 1.f) ? + InterpolationPolicy::NEAREST_NEIGHBOR : + _scale_info.interpolation_policy; + const SamplingPolicy sampling_policy = _scale_info.sampling_policy; + + switch(policy_to_use) + { + case InterpolationPolicy::NEAREST_NEIGHBOR: + { + // Pre-compute offsets for nearest interpolation + precompute_dx_dy_offsets(nullptr, nullptr, offsets, wr, hr, sampling_policy, is_align_corners_used); + break; + } + case InterpolationPolicy::BILINEAR: + { + // Pre-compute dx, dy and offsets for bilinear interpolation + precompute_dx_dy_offsets(dx, dy, offsets, wr, hr, sampling_policy, is_align_corners_used); + break; + } + case InterpolationPolicy::AREA: + { + break; + } + default: + ARM_COMPUTE_ERROR("Unsupported interpolation mode"); + } + } +} + +void CpuScale::run(ITensorPack &tensors) +{ + ARM_COMPUTE_ERROR_ON_MSG(tensors.empty(), "No inputs provided"); + prepare(tensors); + NEScheduler::get().schedule_op(_kernel.get(), Window::DimY, _kernel->window(), tensors); +} +} // namespace cpu +} // namespace arm_compute diff --git a/src/runtime/cpu/operators/CpuScale.h b/src/runtime/cpu/operators/CpuScale.h new file mode 100644 index 0000000000..90248a8d59 --- /dev/null +++ b/src/runtime/cpu/operators/CpuScale.h @@ -0,0 +1,73 @@ +/* + * Copyright (c) 2021 Arm Limited. + * + * SPDX-License-Identifier: MIT + * + * Permission is hereby granted, free of charge, to any person obtaining a copy + * of this software and associated documentation files (the "Software"), to + * deal in the Software without restriction, including without limitation the + * rights to use, copy, modify, merge, publish, distribute, sublicense, and/or + * sell copies of the Software, and to permit persons to whom the Software is + * furnished to do so, subject to the following conditions: + * + * The above copyright notice and this permission notice shall be included in all + * copies or substantial portions of the Software. + * + * THE SOFTWARE IS PROVIDED "AS IS", WITHOUT WARRANTY OF ANY KIND, EXPRESS OR + * IMPLIED, INCLUDING BUT NOT LIMITED TO THE WARRANTIES OF MERCHANTABILITY, + * FITNESS FOR A PARTICULAR PURPOSE AND NONINFRINGEMENT. IN NO EVENT SHALL THE + * AUTHORS OR COPYRIGHT HOLDERS BE LIABLE FOR ANY CLAIM, DAMAGES OR OTHER + * LIABILITY, WHETHER IN AN ACTION OF CONTRACT, TORT OR OTHERWISE, ARISING FROM, + * OUT OF OR IN CONNECTION WITH THE SOFTWARE OR THE USE OR OTHER DEALINGS IN THE + * SOFTWARE. + */ +#ifndef ARM_COMPUTE_CPU_SCALE_H +#define ARM_COMPUTE_CPU_SCALE_H + +#include "arm_compute/core/ITensorInfo.h" +#include "arm_compute/core/KernelDescriptors.h" +#include "arm_compute/core/experimental/Types.h" +#include "src/core/cpu/ICpuKernel.h" +#include "src/runtime/cpu/ICpuOperator.h" + +#include <memory> + +namespace arm_compute +{ +namespace cpu +{ +/** Basic function to compute Scale */ +class CpuScale : public ICpuOperator +{ +public: + /** Default Constructor */ + CpuScale(); + /** Initialize the function's source, destination, interpolation type and border_mode. + * + * @param[in, out] src Source tensor info. Data type supported: QASYMM8/QASYMM8_SIGNED/U8/S16/F16/F32. (Written to only for @p border_mode != UNDEFINED) + * @param[out] dst Destination tensor info. Data type supported: Same as @p src. 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] info @ref ScaleKernelInfo to be used for configuration + */ + void configure(ITensorInfo *src, ITensorInfo *dst, const ScaleKernelInfo &info); + /** Static function to check if given info will lead to a valid configuration of @ref NEScale + * + * @param[in] src Source tensor info. Data type supported: QASYMM8/QASYMM8_SIGNED/U8/S16/F16/F32. (Written to only for @p border_mode != UNDEFINED) + * @param[in] dst Destination tensor info. Data type supported: Same as @p src. 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] info @ref ScaleKernelInfo to be used for validation + * + * @return a status + */ + static Status validate(const ITensorInfo *src, const ITensorInfo *dst, const ScaleKernelInfo &info); + + // Inherited methods overridden: + void prepare(ITensorPack &tensors) override; + void run(ITensorPack &tensors) override; + +private: + ScaleKernelInfo _scale_info; + DataLayout _data_layout; + bool _is_prepared; +}; +} // namespace cpu +} // namespace arm_compute +#endif /*ARM_COMPUTE_CPU_SCALE_H */ diff --git a/tests/validation/NEON/Scale.cpp b/tests/validation/NEON/Scale.cpp index bb1ab936d1..eab241cb88 100644 --- a/tests/validation/NEON/Scale.cpp +++ b/tests/validation/NEON/Scale.cpp @@ -50,7 +50,7 @@ using datasets::ScaleSamplingPolicySet; using datasets::ScaleAlignCornersSamplingPolicySet; /** We consider vector size in byte 64 since the maximum size of - * a vector used by @ref NEScaleKernel is currently 64-byte (float32x4x4). + * a vector used by the kernel is currently 64-byte (float32x4x4). * There are possibility to reduce test time further by using * smaller vector sizes for different data types where applicable. */ @@ -94,9 +94,8 @@ TEST_SUITE(Validate) /** Validate test suite is to test ARM_COMPUTE_RETURN_ON_* macros * we use to check the validity of given arguments in @ref NEScale - * and subsequent call to @ref NEScaleKernel. * Since this is using validate() of @ref NEScale, which pre-adjust - * arguments for @ref NEScaleKernel, the following conditions in + * arguments for the kernel, the following conditions in * the kernel are not currently tested. * - The same input and output * - Data type of offset, dx and dy |