From b7b31538eb9137e4d3e8de6d381dcbe9fc58df94 Mon Sep 17 00:00:00 2001 From: Michalis Spyrou Date: Thu, 23 Nov 2017 12:10:21 +0000 Subject: COMPMID-464 Implement Depthwise separable convolution on NEON Change-Id: Iccd686be18381e96bcf09b14c7017c6dda0f38d8 Reviewed-on: https://eu-gerrit-1.euhpc.arm.com/109824 Tested-by: BSG Visual Compute Jenkins server to access repositories on http://mpd-gerrit.cambridge.arm.com Reviewed-by: Pablo Tello --- arm_compute/core/NEON/NEKernels.h | 4 + .../core/NEON/kernels/NEDepthwiseIm2ColKernel.h | 74 +++++++++ .../NEON/kernels/NEDepthwiseVectorToTensorKernel.h | 71 +++++++++ .../NEON/kernels/NEDepthwiseWeightsReshapeKernel.h | 67 ++++++++ .../kernels/NEGEMMMatrixVectorMultiplyKernel.h | 63 ++++++++ .../kernels/convolution/NEDirectConvolution3x3.h | 172 +++++++++++++++++++++ .../NEON/functions/NEDepthwiseConvolution.h | 41 +++++ src/core/CL/kernels/CLDepthwiseIm2ColKernel.cpp | 1 + src/core/NEON/kernels/NEDepthwiseIm2ColKernel.cpp | 138 +++++++++++++++++ .../kernels/NEDepthwiseVectorToTensorKernel.cpp | 95 ++++++++++++ .../kernels/NEDepthwiseWeightsReshapeKernel.cpp | 112 ++++++++++++++ .../kernels/NEGEMMMatrixVectorMultiplyKernel.cpp | 131 ++++++++++++++++ .../NEON/functions/NEDepthwiseConvolution.cpp | 64 ++++++++ tests/validation/NEON/DepthwiseConvolution.cpp | 21 ++- 14 files changed, 1051 insertions(+), 3 deletions(-) create mode 100644 arm_compute/core/NEON/kernels/NEDepthwiseIm2ColKernel.h create mode 100644 arm_compute/core/NEON/kernels/NEDepthwiseVectorToTensorKernel.h create mode 100644 arm_compute/core/NEON/kernels/NEDepthwiseWeightsReshapeKernel.h create mode 100644 arm_compute/core/NEON/kernels/NEGEMMMatrixVectorMultiplyKernel.h create mode 100644 arm_compute/core/NEON/kernels/convolution/NEDirectConvolution3x3.h create mode 100644 src/core/NEON/kernels/NEDepthwiseIm2ColKernel.cpp create mode 100644 src/core/NEON/kernels/NEDepthwiseVectorToTensorKernel.cpp create mode 100644 src/core/NEON/kernels/NEDepthwiseWeightsReshapeKernel.cpp create mode 100644 src/core/NEON/kernels/NEGEMMMatrixVectorMultiplyKernel.cpp diff --git a/arm_compute/core/NEON/NEKernels.h b/arm_compute/core/NEON/NEKernels.h index ece3ad2c3a..3ad1931ed1 100644 --- a/arm_compute/core/NEON/NEKernels.h +++ b/arm_compute/core/NEON/NEKernels.h @@ -47,6 +47,9 @@ #include "arm_compute/core/NEON/kernels/NEDepthConcatenateKernel.h" #include "arm_compute/core/NEON/kernels/NEDepthConvertKernel.h" #include "arm_compute/core/NEON/kernels/NEDepthwiseConvolution3x3Kernel.h" +#include "arm_compute/core/NEON/kernels/NEDepthwiseIm2ColKernel.h" +#include "arm_compute/core/NEON/kernels/NEDepthwiseVectorToTensorKernel.h" +#include "arm_compute/core/NEON/kernels/NEDepthwiseWeightsReshapeKernel.h" #include "arm_compute/core/NEON/kernels/NEDequantizationLayerKernel.h" #include "arm_compute/core/NEON/kernels/NEDerivativeKernel.h" #include "arm_compute/core/NEON/kernels/NEDilateKernel.h" @@ -68,6 +71,7 @@ #include "arm_compute/core/NEON/kernels/NEGEMMMatrixAccumulateBiasesKernel.h" #include "arm_compute/core/NEON/kernels/NEGEMMMatrixAdditionKernel.h" #include "arm_compute/core/NEON/kernels/NEGEMMMatrixMultiplyKernel.h" +#include "arm_compute/core/NEON/kernels/NEGEMMMatrixVectorMultiplyKernel.h" #include "arm_compute/core/NEON/kernels/NEGEMMTranspose1xWKernel.h" #include "arm_compute/core/NEON/kernels/NEGaussian3x3Kernel.h" #include "arm_compute/core/NEON/kernels/NEGaussian5x5Kernel.h" diff --git a/arm_compute/core/NEON/kernels/NEDepthwiseIm2ColKernel.h b/arm_compute/core/NEON/kernels/NEDepthwiseIm2ColKernel.h new file mode 100644 index 0000000000..fde474d1f5 --- /dev/null +++ b/arm_compute/core/NEON/kernels/NEDepthwiseIm2ColKernel.h @@ -0,0 +1,74 @@ +/* + * 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_NEDEPTHWISEIM2COLKERNEL_H__ +#define __ARM_COMPUTE_NEDEPTHWISEIM2COLKERNEL_H__ + +#include "arm_compute/core/NEON/INEKernel.h" +#include "arm_compute/core/Size2D.h" + +namespace arm_compute +{ +class ITensor; + +/** Interface for the depthwise im2col reshape kernel. + * This kernel reshape the input low 3 dimensions to a new 3D shape where the output's first dimension is + * the linear patch size (FILTER_WIDTH * FILTER_HEIGHT) and second dimension is number of patches in per image and third dimension unchanged . + **/ +class NEDepthwiseIm2ColKernel : public INEKernel +{ +public: + /** Default constructor */ + NEDepthwiseIm2ColKernel(); + /** Prevent instances of this class from being copied (As this class contains pointers) */ + NEDepthwiseIm2ColKernel(const NEDepthwiseIm2ColKernel &) = delete; + /** Prevent instances of this class from being copied (As this class contains pointers) */ + NEDepthwiseIm2ColKernel &operator=(const NEDepthwiseIm2ColKernel &) = delete; + /** Allow instances of this class to be moved */ + NEDepthwiseIm2ColKernel(NEDepthwiseIm2ColKernel &&) = default; + /** Allow instances of this class to be moved */ + NEDepthwiseIm2ColKernel &operator=(NEDepthwiseIm2ColKernel &&) = default; + /** Set the input and output of the kernel. + * + * @param[in] input The input tensor to convert. 3 lower dimensions represent a single input [width, height, IFM], + * while every optional dimension from 4 and above represent a batch of inputs. Data types supported: F32 + * @param[out] output The output tensor. First 3 lower dimensions represent a transform of each 3D input, + * while every dimension above 3 represents a batch. Data types supported: Same as @p input + * @param[in] kernel_dims The kernel dimensions (width and height). + * @param[in] conv_info Contains padding and stride information described in @ref PadStrideInfo. + * @param[in] has_bias Boolean that specifies if the depthwise convolution has bias. + */ + void configure(const ITensor *input, ITensor *output, const Size2D &kernel_dims, const PadStrideInfo &conv_info, bool has_bias = false); + + // Inherited methods overridden: + void run(const Window &window, const ThreadInfo &info) override; + +private: + const ITensor *_input; + ITensor *_output; + Size2D _kernel_dims; + PadStrideInfo _conv_info; + bool _has_bias; +}; +} // arm_compute +#endif /*__ARM_COMPUTE_NEDEPTHWISEIM2COLKERNEL_H__ */ diff --git a/arm_compute/core/NEON/kernels/NEDepthwiseVectorToTensorKernel.h b/arm_compute/core/NEON/kernels/NEDepthwiseVectorToTensorKernel.h new file mode 100644 index 0000000000..8b33fae6f3 --- /dev/null +++ b/arm_compute/core/NEON/kernels/NEDepthwiseVectorToTensorKernel.h @@ -0,0 +1,71 @@ +/* + * 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_NEDEPTHWISEVECTORTOTENSORKERNEL_H__ +#define __ARM_COMPUTE_NEDEPTHWISEVECTORTOTENSORKERNEL_H__ + +#include "arm_compute/core/NEON/INEKernel.h" + +namespace arm_compute +{ +class ITensor; + +/** Interface for the depthwise vector to tensor kernel. + * + * This kernel takes the 1D tensor that's been produced by the MatrixVectorMultiply + * kernel and reshapes it to given width and height (previously calculated, based + * on input/weights dimensions and convolution strides and padding). + * + **/ +class NEDepthwiseVectorToTensorKernel : public INEKernel +{ +public: + /** Default constructor */ + NEDepthwiseVectorToTensorKernel(); + /** Prevent instances of this class from being copied (As this class contains pointers) */ + NEDepthwiseVectorToTensorKernel(const NEDepthwiseVectorToTensorKernel &) = delete; + /** Prevent instances of this class from being copied (As this class contains pointers) */ + NEDepthwiseVectorToTensorKernel &operator=(const NEDepthwiseVectorToTensorKernel &) = delete; + /** Allow instances of this class to be moved */ + NEDepthwiseVectorToTensorKernel(NEDepthwiseVectorToTensorKernel &&) = default; + /** Allow instances of this class to be moved */ + NEDepthwiseVectorToTensorKernel &operator=(NEDepthwiseVectorToTensorKernel &&) = default; + /** Set the input and output of the kernel. + * + * @param[in] input The input vector to convert. Data type supported: F32. + * @param[out] output The output tensor. 3 lower dimensions represent a single input [width, height, IFM]. Data type supported: same as @p input. + * @param[in] conv_w The converted tensor's width. + * @param[in] conv_h The converted tensor's height. + */ + void configure(const ITensor *input, ITensor *output, size_t conv_w, size_t conv_h); + + // Inherited methods overridden: + void run(const Window &window, const ThreadInfo &info) override; + +private: + const ITensor *_input; + ITensor *_output; + std::pair _conv_dims; +}; +} // arm_compute +#endif /*__ARM_COMPUTE_NEDEPTHWISEVECTORTOTENSORKERNEL_H__ */ diff --git a/arm_compute/core/NEON/kernels/NEDepthwiseWeightsReshapeKernel.h b/arm_compute/core/NEON/kernels/NEDepthwiseWeightsReshapeKernel.h new file mode 100644 index 0000000000..2e986117df --- /dev/null +++ b/arm_compute/core/NEON/kernels/NEDepthwiseWeightsReshapeKernel.h @@ -0,0 +1,67 @@ +/* + * 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_NEDEPTHWISEWEIGHTSRESHAPEKERNEL_H__ +#define __ARM_COMPUTE_NEDEPTHWISEWEIGHTSRESHAPEKERNEL_H__ + +#include "arm_compute/core/NEON/INEKernel.h" + +namespace arm_compute +{ +class ITensor; + +/** Interface for the depthwise weights reshape kernel. + * This kernel reshape original weights' low 2D dimensions into a single col and + * have the second dimension as the original depth size. + **/ +class NEDepthwiseWeightsReshapeKernel : public INEKernel +{ +public: + /** Default constructor */ + NEDepthwiseWeightsReshapeKernel(); + /** Prevent instances of this class from being copied (As this class contains pointers) */ + NEDepthwiseWeightsReshapeKernel(const NEDepthwiseWeightsReshapeKernel &) = delete; + /** Prevent instances of this class from being copied (As this class contains pointers) */ + NEDepthwiseWeightsReshapeKernel &operator=(const NEDepthwiseWeightsReshapeKernel &) = delete; + /** Allow instances of this class to be moved */ + NEDepthwiseWeightsReshapeKernel(NEDepthwiseWeightsReshapeKernel &&) = default; + /** Allow instances of this class to be moved */ + NEDepthwiseWeightsReshapeKernel &operator=(NEDepthwiseWeightsReshapeKernel &&) = default; + /** Set the input and output of the kernel. + * + * @param[in] input The input tensor to convert. 3 lower dimensions represent a single input [width, height, IFM]. Data type supported: F32. + * @param[out] output The output tensor. Data type supported: same as @p input. + * @param[in] biases (Optional) The input biases to add. Shape [IFM]. Data type supported: same as @p input. + */ + void configure(const ITensor *input, ITensor *output, const ITensor *biases); + + // Inherited methods overridden: + void run(const Window &window, const ThreadInfo &info) override; + +private: + const ITensor *_input; + ITensor *_output; + const ITensor *_biases; +}; +} // arm_compute +#endif /*__ARM_COMPUTE_NEDEPTHWISEWEIGHTSRESHAPEKERNEL_H__ */ diff --git a/arm_compute/core/NEON/kernels/NEGEMMMatrixVectorMultiplyKernel.h b/arm_compute/core/NEON/kernels/NEGEMMMatrixVectorMultiplyKernel.h new file mode 100644 index 0000000000..d844af5d54 --- /dev/null +++ b/arm_compute/core/NEON/kernels/NEGEMMMatrixVectorMultiplyKernel.h @@ -0,0 +1,63 @@ +/* + * 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_NEGEMMMATRIXVECTORMULTIPLYKERNEL_H_ +#define __ARM_COMPUTE_NEGEMMMATRIXVECTORMULTIPLYKERNEL_H_ + +#include "arm_compute/core/NEON/INESimpleKernel.h" + +namespace arm_compute +{ +class ITensor; + +class NEGEMMMatrixVectorMultiplyKernel : public INESimpleKernel +{ +public: + /** Default constructor */ + NEGEMMMatrixVectorMultiplyKernel(); + /** Prevent instances of this class from being copied (As this class contains pointers) */ + NEGEMMMatrixVectorMultiplyKernel(const NEGEMMMatrixVectorMultiplyKernel &) = delete; + /** Prevent instances of this class from being copied (As this class contains pointers) */ + NEGEMMMatrixVectorMultiplyKernel &operator=(const NEGEMMMatrixVectorMultiplyKernel &) = delete; + /** Allow instances of this class to be moved */ + NEGEMMMatrixVectorMultiplyKernel(NEGEMMMatrixVectorMultiplyKernel &&) = default; + /** Allow instances of this class to be moved */ + NEGEMMMatrixVectorMultiplyKernel &operator=(NEGEMMMatrixVectorMultiplyKernel &&) = default; + /** Initialise the kernel's input and output. + * + * @param[in] input0 First Input tensor. Data types supported: F16/F32 + * @param[in] input1 Second Input tensor. Data types supported: same as @p input. + * @param[out] output Output tensor which stores the interleaved matrix. Data type supported: same as @p input. + */ + void configure(const ITensor *input0, const ITensor *input1, ITensor *output); + + // Inherited methods overridden: + void run(const Window &window, const ThreadInfo &info) override; + +private: + const ITensor *_input0; + const ITensor *_input1; + ITensor *_output; +}; +} // namespace arm_compute +#endif /*__ARM_COMPUTE_NEGEMMMATRIXVECTORMULTIPLYKERNEL_H_*/ diff --git a/arm_compute/core/NEON/kernels/convolution/NEDirectConvolution3x3.h b/arm_compute/core/NEON/kernels/convolution/NEDirectConvolution3x3.h new file mode 100644 index 0000000000..7f39e5ee8d --- /dev/null +++ b/arm_compute/core/NEON/kernels/convolution/NEDirectConvolution3x3.h @@ -0,0 +1,172 @@ +/* + * 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_NECONVOLUTIONKERNEL3x3_H__ +#define __ARM_COMPUTE_NECONVOLUTIONKERNEL3x3_H__ + +#include + +namespace arm_compute +{ +namespace detail +{ +inline float32x4x3_t load_matrix_row(const float *ptr) +{ + const float32x4x3_t r = + { + { + vld1q_dup_f32(ptr), + vld1q_dup_f32(1 + ptr), + vld1q_dup_f32(2 + ptr) + } + }; + return r; +} + +template +float32x4x2_t convolve_3x3(const float *in_top, const float *in_mid, const float *in_low, const float32x4x3_t &m0, const float32x4x3_t &m1, const float32x4x3_t &m2, int fixed_point_position); + +template <> +inline float32x4x2_t convolve_3x3<1>(const float *in_top, const float *in_mid, const float *in_low, const float32x4x3_t &m0, const float32x4x3_t &m1, const float32x4x3_t &m2, int fixed_point_position) +{ + ARM_COMPUTE_UNUSED(fixed_point_position); + + const float32x4x3_t vtop = + { + { + vld1q_f32(in_top), + vld1q_f32(in_top + 4), + vld1q_f32(in_top + 8) + } + }; + const float32x4x3_t vmid = + { + { + vld1q_f32(in_mid), + vld1q_f32(in_mid + 4), + vld1q_f32(in_mid + 8) + } + }; + const float32x4x3_t vlow = + { + { + vld1q_f32(in_low), + vld1q_f32(in_low + 4), + vld1q_f32(in_low + 8) + } + }; + float32x4x2_t out = + { + { + vmulq_f32(vtop.val[0], m0.val[0]), + vmulq_f32(vtop.val[1], m0.val[0]) + } + }; + out.val[0] = vmlaq_f32(out.val[0], vextq_f32(vtop.val[0], vtop.val[1], 1), m0.val[1]); + out.val[0] = vmlaq_f32(out.val[0], vextq_f32(vtop.val[0], vtop.val[1], 2), m0.val[2]); + + out.val[0] = vmlaq_f32(out.val[0], vmid.val[0], m1.val[0]); + out.val[0] = vmlaq_f32(out.val[0], vextq_f32(vmid.val[0], vmid.val[1], 1), m1.val[1]); + out.val[0] = vmlaq_f32(out.val[0], vextq_f32(vmid.val[0], vmid.val[1], 2), m1.val[2]); + + out.val[0] = vmlaq_f32(out.val[0], vlow.val[0], m2.val[0]); + out.val[0] = vmlaq_f32(out.val[0], vextq_f32(vlow.val[0], vlow.val[1], 1), m2.val[1]); + out.val[0] = vmlaq_f32(out.val[0], vextq_f32(vlow.val[0], vlow.val[1], 2), m2.val[2]); + + out.val[1] = vmlaq_f32(out.val[1], vextq_f32(vtop.val[1], vtop.val[2], 1), m0.val[1]); + out.val[1] = vmlaq_f32(out.val[1], vextq_f32(vtop.val[1], vtop.val[2], 2), m0.val[2]); + + out.val[1] = vmlaq_f32(out.val[1], vmid.val[1], m1.val[0]); + out.val[1] = vmlaq_f32(out.val[1], vextq_f32(vmid.val[1], vmid.val[2], 1), m1.val[1]); + out.val[1] = vmlaq_f32(out.val[1], vextq_f32(vmid.val[1], vmid.val[2], 2), m1.val[2]); + + out.val[1] = vmlaq_f32(out.val[1], vlow.val[1], m2.val[0]); + out.val[1] = vmlaq_f32(out.val[1], vextq_f32(vlow.val[1], vlow.val[2], 1), m2.val[1]); + out.val[1] = vmlaq_f32(out.val[1], vextq_f32(vlow.val[1], vlow.val[2], 2), m2.val[2]); + return out; +} + +template <> +inline float32x4x2_t convolve_3x3<2>(const float *in_top, const float *in_mid, const float *in_low, const float32x4x3_t &m0, const float32x4x3_t &m1, const float32x4x3_t &m2, int fixed_point_position) +{ + float32x4x2_t out = convolve_3x3<1>(in_top, in_mid, in_low, m0, m1, m2, fixed_point_position); + out.val[0] = vsetq_lane_f32(vgetq_lane_f32(out.val[0], 2), out.val[0], 1); + out.val[0] = vsetq_lane_f32(vgetq_lane_f32(out.val[1], 0), out.val[0], 2); + out.val[0] = vsetq_lane_f32(vgetq_lane_f32(out.val[1], 2), out.val[0], 3); + return out; +} + +template <> +inline float32x4x2_t convolve_3x3<3>(const float *in_top, const float *in_mid, const float *in_low, const float32x4x3_t &m0, const float32x4x3_t &m1, const float32x4x3_t &m2, int fixed_point_position) +{ + float32x4x2_t out = convolve_3x3<1>(in_top, in_mid, in_low, m0, m1, m2, fixed_point_position); + out.val[0] = vsetq_lane_f32(vgetq_lane_f32(out.val[0], 3), out.val[0], 1); + return out; +} + +template +void store_results(float *buffer, const float32x4x2_t &values); + +template <> +void store_results<1>(float *buffer, const float32x4x2_t &values) +{ + vst1q_f32(buffer, values.val[0]); + vst1q_f32(buffer + 4, values.val[1]); +} + +template <> +void store_results<2>(float *buffer, const float32x4x2_t &values) +{ + vst1q_f32(buffer, values.val[0]); +} + +template <> +void store_results<3>(float *buffer, const float32x4x2_t &values) +{ + vst1_f32(buffer, vget_low_f32(values.val[0])); +} + +template +int get_input_num_elems_processed(unsigned int num_elems_written_per_iteration); + +template <> +int get_input_num_elems_processed<1>(unsigned int num_elems_written_per_iteration) +{ + return num_elems_written_per_iteration; +} + +template <> +int get_input_num_elems_processed<2>(unsigned int num_elems_written_per_iteration) +{ + return num_elems_written_per_iteration << 1; +} + +template <> +int get_input_num_elems_processed<3>(unsigned int num_elems_written_per_iteration) +{ + return num_elems_written_per_iteration * 3; +} +} +} // namespace arm_compute +#endif /* __ARM_COMPUTE_NECONVOLUTIONKERNEL3x3_H__ */ \ No newline at end of file diff --git a/arm_compute/runtime/NEON/functions/NEDepthwiseConvolution.h b/arm_compute/runtime/NEON/functions/NEDepthwiseConvolution.h index acf66f8dd4..f2c209cd80 100644 --- a/arm_compute/runtime/NEON/functions/NEDepthwiseConvolution.h +++ b/arm_compute/runtime/NEON/functions/NEDepthwiseConvolution.h @@ -25,8 +25,12 @@ #define __ARM_COMPUTE_NEDEPTHWISECONVOLUTION_H__ #include "arm_compute/core/NEON/kernels/NEDepthwiseConvolution3x3Kernel.h" +#include "arm_compute/core/NEON/kernels/NEDepthwiseIm2ColKernel.h" +#include "arm_compute/core/NEON/kernels/NEDepthwiseVectorToTensorKernel.h" +#include "arm_compute/core/NEON/kernels/NEDepthwiseWeightsReshapeKernel.h" #include "arm_compute/core/NEON/kernels/NEDirectConvolutionLayerBiasAccumulateKernel.h" #include "arm_compute/core/NEON/kernels/NEFillBorderKernel.h" +#include "arm_compute/core/NEON/kernels/NEGEMMMatrixVectorMultiplyKernel.h" #include "arm_compute/core/Types.h" #include "arm_compute/runtime/IFunction.h" #include "arm_compute/runtime/IMemoryManager.h" @@ -68,5 +72,42 @@ private: NEFillBorderKernel _border_handler; bool _has_bias; }; + +/** Basic function to execute a generic depthwise convolution. This function calls the following OpenCL kernels: + * + * -# @ref NEDepthwiseIm2ColKernel + * -# @ref NEDepthwiseWeightsReshapeKernel + * -# @ref NEGEMMMatrixVectorMultiplyKernel + * -# @ref NEFillBorderKernel (if pad_x or pad_y > 0) + * + */ +class NEDepthwiseConvolution : public IFunction +{ +public: + /** Default constructor */ + NEDepthwiseConvolution(); + /** Initialize the function's source, destination, weights and convolution information. + * + * @param[in, out] input Source tensor. Data type supported: F32. (Written to only for border filling). + * @param[out] output Destination tensor. Data type supported: same as @p input. + * @param[in] weights Weights tensor. These are 3D tensors with shape [kernel_x, kernel_y, IFM]. Data type supported: Same as @p input. + * @param[in] biases (Optional) Biases tensor. A 1D tensor with shape [IFM]. Must be nullptr if not needed. + * Data type supported: Same as @p input. + * @param[in] conv_info Padding and stride information to use for the convolution. + */ + void configure(ITensor *input, const ITensor *weights, const ITensor *biases, ITensor *output, const PadStrideInfo &conv_info); + + // Inherited methods overriden: + void run() override; + +private: + NEDepthwiseIm2ColKernel _im2col_kernel; + NEDepthwiseWeightsReshapeKernel _weights_reshape_kernel; + NEGEMMMatrixVectorMultiplyKernel _v2mm_kernel; + NEDepthwiseVectorToTensorKernel _vector_to_tensor_kernel; + Tensor _input_reshaped; + Tensor _weights_reshaped; + Tensor _v2mm_output; +}; } #endif /* __ARM_COMPUTE_NEDEPTHWISECONVOLUTION_H__ */ \ No newline at end of file diff --git a/src/core/CL/kernels/CLDepthwiseIm2ColKernel.cpp b/src/core/CL/kernels/CLDepthwiseIm2ColKernel.cpp index 743cd4a38f..c23941426e 100644 --- a/src/core/CL/kernels/CLDepthwiseIm2ColKernel.cpp +++ b/src/core/CL/kernels/CLDepthwiseIm2ColKernel.cpp @@ -32,6 +32,7 @@ #include "arm_compute/core/Types.h" #include "support/ToolchainSupport.h" +#include "arm_compute/runtime/CL/CLScheduler.h" #include using namespace arm_compute; diff --git a/src/core/NEON/kernels/NEDepthwiseIm2ColKernel.cpp b/src/core/NEON/kernels/NEDepthwiseIm2ColKernel.cpp new file mode 100644 index 0000000000..2ceb39d217 --- /dev/null +++ b/src/core/NEON/kernels/NEDepthwiseIm2ColKernel.cpp @@ -0,0 +1,138 @@ +/* + * 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. + */ +#include "arm_compute/core/NEON/kernels/NEDepthwiseIm2ColKernel.h" + +#include "arm_compute/core/AccessWindowTranspose.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/INEKernel.h" +#include "arm_compute/core/TensorInfo.h" +#include "arm_compute/core/TensorShape.h" +#include "arm_compute/core/Types.h" +#include "arm_compute/core/Validate.h" +#include "arm_compute/core/Window.h" + +using namespace arm_compute; + +NEDepthwiseIm2ColKernel::NEDepthwiseIm2ColKernel() + : _input(nullptr), _output(nullptr), _kernel_dims(), _conv_info(), _has_bias() +{ +} + +void NEDepthwiseIm2ColKernel::configure(const ITensor *input, ITensor *output, const Size2D &kernel_dims, const PadStrideInfo &conv_info, bool has_bias) +{ + ARM_COMPUTE_ERROR_ON_DATA_TYPE_CHANNEL_NOT_IN(input, 1, DataType::F16, DataType::F32); + ARM_COMPUTE_ERROR_ON_MISMATCHING_DATA_TYPES(input, output); + ARM_COMPUTE_ERROR_ON_MISMATCHING_FIXED_POINT(input, output); + ARM_COMPUTE_ERROR_ON(input->info()->dimension(2) != output->info()->dimension(2)); + ARM_COMPUTE_ERROR_ON(output->info()->dimension(0) != (kernel_dims.width * kernel_dims.height + ((has_bias) ? 1 : 0))); + + _input = input; + _output = output; + _kernel_dims = kernel_dims; + _conv_info = conv_info; + _has_bias = has_bias; + + // Configure kernel window + Window win = calculate_max_window(*input->info(), Steps()); + + // The NEDepthwiseIm2ColKernel doesn't need padding so update_window_and_padding() can be skipped + output->info()->set_valid_region(ValidRegion(Coordinates(), output->info()->tensor_shape())); + + INEKernel::configure(win); +} + +void NEDepthwiseIm2ColKernel::run(const Window &window, const ThreadInfo &info) +{ + ARM_COMPUTE_UNUSED(info); + ARM_COMPUTE_ERROR_ON_UNCONFIGURED_KERNEL(this); + + //const int kernel_depth = _input->info()->dimension(2); + const int input_w = _input->info()->dimension(0); + const int input_h = _input->info()->dimension(1); + const int input_stride_x = _input->info()->strides_in_bytes().x(); + const int input_stride_y = _input->info()->strides_in_bytes().y(); + const int input_stride_z = _input->info()->strides_in_bytes().z(); + const int stride_x = _conv_info.stride().first; + const int stride_y = _conv_info.stride().second; + + const int pad_left = _conv_info.pad_left(); + const int pad_right = _conv_info.pad_right(); + const int pad_top = _conv_info.pad_top(); + + Window window_in(window); + // The first three dimensions of the input are increased by the inner loops + window_in.set(Window::DimX, Window::Dimension(0, 0, 0)); + window_in.set(Window::DimY, Window::Dimension(0, 0, 0)); + window_in.set(Window::DimZ, Window::Dimension(0, 0, 0)); + + // Setup output window + Window window_out(window); + window_out.set(Window::DimX, Window::Dimension(0, _output->info()->dimension(0), _output->info()->dimension(0))); + window_out.set(Window::DimY, Window::Dimension(0, _output->info()->dimension(1), 1)); + window_out.set(Window::DimZ, Window::Dimension(0, _output->info()->dimension(2), 1)); + + Iterator in(_input, window_in); + Iterator out(_output, window_out); + + const int full_length = input_w + pad_left + pad_right; + const int max_initial_x = stride_x * (((full_length - _kernel_dims.width) / stride_x) + 1); + + execute_window_loop(window_out, [&](const Coordinates & id) + { + const int src_pixel_linear = id.y() * stride_x; + + const int src_x = -pad_left + src_pixel_linear % max_initial_x; + const int src_y = -pad_top + src_pixel_linear / max_initial_x * stride_y; + + // Get pointers + const uint8_t *const input_ptr = in.ptr() + id.z() * input_stride_z; + auto output_ptr = reinterpret_cast(out.ptr()); + const int height = src_y + _kernel_dims.height; + const int width = src_x + _kernel_dims.width; + + for(int y = src_y; y < height; ++y) + { + for(int x = src_x; x < width; ++x, ++output_ptr) + { + if(x < 0 || x >= input_w || y < 0 || y >= input_h) + { + *output_ptr = 0; + } + else + { + *output_ptr = *(reinterpret_cast(input_ptr + x * input_stride_x + y * input_stride_y)); + } + } + } + + if(_has_bias) + { + *output_ptr = static_cast(1); + } + }, + in, out); +} diff --git a/src/core/NEON/kernels/NEDepthwiseVectorToTensorKernel.cpp b/src/core/NEON/kernels/NEDepthwiseVectorToTensorKernel.cpp new file mode 100644 index 0000000000..6deda506ab --- /dev/null +++ b/src/core/NEON/kernels/NEDepthwiseVectorToTensorKernel.cpp @@ -0,0 +1,95 @@ +/* + * 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. + */ +#include "arm_compute/core/NEON/kernels/NEDepthwiseVectorToTensorKernel.h" + +#include "arm_compute/core/AccessWindowTranspose.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/INEKernel.h" +#include "arm_compute/core/TensorInfo.h" +#include "arm_compute/core/TensorShape.h" +#include "arm_compute/core/Types.h" +#include "arm_compute/core/Validate.h" +#include "arm_compute/core/Window.h" + +using namespace arm_compute; + +NEDepthwiseVectorToTensorKernel::NEDepthwiseVectorToTensorKernel() + : _input(nullptr), _output(nullptr), _conv_dims() +{ +} + +void NEDepthwiseVectorToTensorKernel::configure(const ITensor *input, ITensor *output, size_t conv_w, size_t conv_h) +{ + ARM_COMPUTE_ERROR_ON_DATA_TYPE_CHANNEL_NOT_IN(input, 1, DataType::F16, DataType::F32); + ARM_COMPUTE_ERROR_ON_MISMATCHING_DATA_TYPES(input, output); + ARM_COMPUTE_ERROR_ON_MISMATCHING_FIXED_POINT(input, output); + + _input = input; + _output = output; + _conv_dims = std::pair(conv_w, conv_h); + + // Configure kernel window + Window win = calculate_max_window(*input->info(), Steps()); + // The NEDepthwisevectorToTensorKernel doesn't need padding so update_window_and_padding() can be skipped + output->info()->set_valid_region(ValidRegion(Coordinates(), output->info()->tensor_shape())); + + INEKernel::configure(win); +} + +void NEDepthwiseVectorToTensorKernel::run(const Window &window, const ThreadInfo &info) +{ + ARM_COMPUTE_UNUSED(info); + ARM_COMPUTE_ERROR_ON_UNCONFIGURED_KERNEL(this); + + // const int input_w = _input->info()->dimension(0); + const int output_stride_x = _output->info()->strides_in_bytes().x(); + const int output_stride_y = _output->info()->strides_in_bytes().y(); + const int output_stride_z = _output->info()->strides_in_bytes().z(); + + // Setup output window + Window window_out(window); + window_out.set(Window::DimX, Window::Dimension(0, 0, 0)); + window_out.set(Window::DimY, Window::Dimension(0, 0, 0)); + window_out.set(Window::DimZ, Window::Dimension(0, 0, 0)); + + Iterator in(_input, window); + Iterator out(_output, window_out); + + const int patch_size = _conv_dims.first * _conv_dims.second; + + execute_window_loop(window, [&](const Coordinates & id) + { + const int z = id.x() / patch_size; + const int index2D = id.x() - z * patch_size; + + auto input_ptr = reinterpret_cast(in.ptr()); + auto output_ptr = reinterpret_cast(out.ptr() + index2D % _conv_dims.first * output_stride_x + index2D / _conv_dims.first * output_stride_y + z * output_stride_z); + + *output_ptr = *input_ptr; + }, + in, out); +} diff --git a/src/core/NEON/kernels/NEDepthwiseWeightsReshapeKernel.cpp b/src/core/NEON/kernels/NEDepthwiseWeightsReshapeKernel.cpp new file mode 100644 index 0000000000..6585fdb8b8 --- /dev/null +++ b/src/core/NEON/kernels/NEDepthwiseWeightsReshapeKernel.cpp @@ -0,0 +1,112 @@ +/* + * 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. + */ +#include "arm_compute/core/NEON/kernels/NEDepthwiseWeightsReshapeKernel.h" + +#include "arm_compute/core/AccessWindowTranspose.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/INEKernel.h" +#include "arm_compute/core/TensorInfo.h" +#include "arm_compute/core/TensorShape.h" +#include "arm_compute/core/Types.h" +#include "arm_compute/core/Validate.h" +#include "arm_compute/core/Window.h" + +using namespace arm_compute; + +NEDepthwiseWeightsReshapeKernel::NEDepthwiseWeightsReshapeKernel() + : _input(nullptr), _output(nullptr), _biases(nullptr) +{ +} + +void NEDepthwiseWeightsReshapeKernel::configure(const ITensor *input, ITensor *output, const ITensor *biases) +{ + ARM_COMPUTE_ERROR_ON_DATA_TYPE_CHANNEL_NOT_IN(input, 1, DataType::F16, DataType::F32); + ARM_COMPUTE_ERROR_ON_MISMATCHING_DATA_TYPES(input, output); + ARM_COMPUTE_ERROR_ON_MISMATCHING_FIXED_POINT(input, output); + ARM_COMPUTE_ERROR_ON(input->info()->dimension(2) != output->info()->dimension(1)); + ARM_COMPUTE_ERROR_ON(output->info()->dimension(0) != (input->info()->dimension(0) * input->info()->dimension(1) + ((biases != nullptr) ? 1 : 0))); + + if(biases != nullptr) + { + ARM_COMPUTE_ERROR_ON_MISMATCHING_DATA_TYPES(input, biases); + ARM_COMPUTE_ERROR_ON_MISMATCHING_FIXED_POINT(input, biases); + ARM_COMPUTE_ERROR_ON(biases->info()->dimension(0) != input->info()->dimension(2)); + ARM_COMPUTE_ERROR_ON(biases->info()->num_dimensions() > 1); + } + + _input = input; + _output = output; + _biases = biases; + + // Configure kernel window + Window win = calculate_max_window(*input->info(), Steps()); + // The NEDepthwiseWeightsReshapeKernel doesn't need padding so update_window_and_padding() can be skipped + output->info()->set_valid_region(ValidRegion(Coordinates(), output->info()->tensor_shape())); + + INEKernel::configure(win); +} + +void NEDepthwiseWeightsReshapeKernel::run(const Window &window, const ThreadInfo &info) +{ + ARM_COMPUTE_UNUSED(info); + ARM_COMPUTE_ERROR_ON_UNCONFIGURED_KERNEL(this); + + const int input_w = _input->info()->dimension(0); + const int output_stride_x = _output->info()->strides_in_bytes().x(); + const int output_stride_y = _output->info()->strides_in_bytes().y(); + + Window window_in(window); + // The first three dimensions of the input are increased by the inner loops + window_in.set(Window::DimX, Window::Dimension(0, _input->info()->dimension(0), _input->info()->dimension(0))); + window_in.set(Window::DimY, Window::Dimension(0, _input->info()->dimension(1), 1)); + window_in.set(Window::DimZ, Window::Dimension(0, _input->info()->dimension(2), 1)); + + // Setup output window + Window window_out; + window_out.set(Window::DimX, Window::Dimension(0, 0, 0)); + window_out.set(Window::DimY, Window::Dimension(0, 0, 0)); + + Iterator in(_input, window_in); + Iterator out(_output, window_out); + + execute_window_loop(window_in, [&](const Coordinates & id) + { + auto input_ptr = reinterpret_cast(in.ptr()); + auto output_ptr = reinterpret_cast(out.ptr() + id.y() * input_w * output_stride_x + id.z() * output_stride_y); + + for(int i = 0; i < input_w; ++i, ++input_ptr) + { + *(output_ptr + i) = *input_ptr; + } + + if(_biases != nullptr) + { + *(output_ptr + input_w) = *(reinterpret_cast(_biases->ptr_to_element(Coordinates(id.z())))); + } + }, + in, out); +} diff --git a/src/core/NEON/kernels/NEGEMMMatrixVectorMultiplyKernel.cpp b/src/core/NEON/kernels/NEGEMMMatrixVectorMultiplyKernel.cpp new file mode 100644 index 0000000000..c28dcf7463 --- /dev/null +++ b/src/core/NEON/kernels/NEGEMMMatrixVectorMultiplyKernel.cpp @@ -0,0 +1,131 @@ +/* + * 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/NEGEMMMatrixVectorMultiplyKernel.h" + +#include "arm_compute/core/AccessWindowStatic.h" +#include "arm_compute/core/Error.h" +#include "arm_compute/core/Helpers.h" +#include "arm_compute/core/ITensor.h" +#include "arm_compute/core/NEON/INEKernel.h" +#include "arm_compute/core/Types.h" +#include "arm_compute/core/Validate.h" +#include "arm_compute/core/Window.h" + +#include +#include +#include +#include + +using namespace arm_compute; + +NEGEMMMatrixVectorMultiplyKernel::NEGEMMMatrixVectorMultiplyKernel() + : _input0(nullptr), _input1(nullptr), _output(nullptr) +{ +} + +void NEGEMMMatrixVectorMultiplyKernel::configure(const ITensor *input0, const ITensor *input1, ITensor *output) +{ + ARM_COMPUTE_ERROR_ON_DATA_TYPE_CHANNEL_NOT_IN(input0, 1, DataType::F16, DataType::F32); + ARM_COMPUTE_ERROR_ON_MISMATCHING_DATA_TYPES(input0, input1, output); + ARM_COMPUTE_ERROR_ON_MISMATCHING_FIXED_POINT(input0, input1, output); + ARM_COMPUTE_ERROR_ON(input0->info()->dimension(2) != input1->info()->dimension(1)); + + _input0 = input0; + _input1 = input1; + _output = output; + + // Configure kernel window + const unsigned int num_elems_read_per_iteration = 4; + + Window win = calculate_max_window(*input0->info(), Steps(num_elems_read_per_iteration)); + + AccessWindowHorizontal input0_access(input0->info(), 0, num_elems_read_per_iteration); + AccessWindowHorizontal input1_access(input1->info(), 0, num_elems_read_per_iteration); + AccessWindowHorizontal output_access(output->info(), 0, 1); + + update_window_and_padding(win, input0_access, input1_access, output_access); + + _output->info()->set_valid_region(ValidRegion(Coordinates(), _output->info()->tensor_shape())); + + INEKernel::configure(win); +} + +void NEGEMMMatrixVectorMultiplyKernel::run(const Window &window, const ThreadInfo &info) +{ + ARM_COMPUTE_UNUSED(info); + ARM_COMPUTE_ERROR_ON_UNCONFIGURED_KERNEL(this); + + Window window_slice = window.first_slice_window_3D(); + + Window window_in(window); + Window window_weights(window_slice); + Window window_out(window); + + // Setup input0 slice + window_in.set(Window::DimX, Window::Dimension(0, _input0->info()->dimension(0), _input0->info()->dimension(0))); + window_in.set(Window::DimY, Window::Dimension(0, _input0->info()->dimension(1), 1)); + window_in.set(Window::DimZ, Window::Dimension(0, _input0->info()->dimension(2), 1)); + + // Setup input1 and output slice. Their dimensions are increased in the kernel. + window_weights.set(Window::DimX, Window::Dimension(0, 0, 0)); + window_weights.set(Window::DimY, Window::Dimension(0, 0, 0)); + window_weights.set(Window::DimZ, Window::Dimension(0, 0, 0)); + + window_out.set(Window::DimX, Window::Dimension(0, 0, 0)); + window_out.set(Window::DimY, Window::Dimension(0, 0, 0)); + window_out.set(Window::DimZ, Window::Dimension(0, 0, 0)); + + Iterator in(_input0, window_in); + Iterator in2(_input1, window_weights); + Iterator out(_output, window_out); + + const int input_w = _input0->info()->dimension(0); + const int input_h = _input0->info()->dimension(1); + const int input_stride_x = _input0->info()->strides_in_bytes().x(); + const int weights_stride_x = _input1->info()->strides_in_bytes().x(); + const int weights_stride_y = _input1->info()->strides_in_bytes().y(); + const int output_stride_x = _output->info()->strides_in_bytes().x(); + + execute_window_loop(window_in, [&](const Coordinates & id) + { + // Get pointers + const uint8_t *const input_ptr = in.ptr(); + const uint8_t *const weights_ptr = in2.ptr() + id.z() * weights_stride_y; + auto output_ptr = reinterpret_cast(out.ptr() + (id.y() + id.z() * input_h) * output_stride_x); + + float32x4_t row_dot = vdupq_n_f32(0.f); + for(int i = 0; i < input_w; i += 4) + { + const auto input = vld1q_f32(reinterpret_cast(input_ptr + i * input_stride_x)); + const auto weights = vld1q_f32(reinterpret_cast(weights_ptr + i * weights_stride_x)); + row_dot = vaddq_f32(row_dot, vmulq_f32(input, weights)); + } + + auto temp = vadd_f32(vget_high_f32(row_dot), vget_low_f32(row_dot)); + temp = vpadd_f32(temp, temp); + + *output_ptr = vget_lane_f32(temp, 0); + }, + in, in2, out); +} diff --git a/src/runtime/NEON/functions/NEDepthwiseConvolution.cpp b/src/runtime/NEON/functions/NEDepthwiseConvolution.cpp index fd8d419fa1..e12bc07464 100644 --- a/src/runtime/NEON/functions/NEDepthwiseConvolution.cpp +++ b/src/runtime/NEON/functions/NEDepthwiseConvolution.cpp @@ -59,4 +59,68 @@ void NEDepthwiseConvolution3x3::run() { NEScheduler::get().schedule(&_bias_kernel, Window::DimX); } +} + +NEDepthwiseConvolution::NEDepthwiseConvolution() + : _im2col_kernel(), _weights_reshape_kernel(), _v2mm_kernel(), _vector_to_tensor_kernel(), _input_reshaped(), _weights_reshaped(), _v2mm_output() +{ +} + +void NEDepthwiseConvolution::configure(ITensor *input, const ITensor *weights, const ITensor *biases, ITensor *output, const PadStrideInfo &conv_info) +{ + ARM_COMPUTE_ERROR_ON_DATA_TYPE_CHANNEL_NOT_IN(input, 1, DataType::F32); + ARM_COMPUTE_ERROR_ON_MISMATCHING_DATA_TYPES(input, weights); + ARM_COMPUTE_ERROR_ON(input->info()->dimension(2) != weights->info()->dimension(2)); + + const size_t weights_w = weights->info()->dimension(0); + const size_t weights_h = weights->info()->dimension(1); + const size_t weights_z = weights->info()->dimension(2); + + bool has_bias = (biases != nullptr); + + unsigned int conv_w = 0; + unsigned int conv_h = 0; + std::tie(conv_w, conv_h) = scaled_dimensions(input->info()->dimension(0), input->info()->dimension(1), weights_w, weights_h, conv_info); + + // Set up intermediate tensors + const size_t patch_size = weights_w * weights_h + ((has_bias) ? 1 : 0); + const size_t conv_size = conv_w * conv_h; + + // Im2Col configuration + TensorShape shape_im2col = input->info()->tensor_shape(); + shape_im2col.set(0, patch_size); + shape_im2col.set(1, conv_size); + shape_im2col.set(2, weights_z); + const TensorInfo info_im2col(shape_im2col, 1, input->info()->data_type(), input->info()->fixed_point_position()); + _input_reshaped.allocator()->init(info_im2col); + _im2col_kernel.configure(input, &_input_reshaped, Size2D(weights_w, weights_h), conv_info, has_bias); + + // Weights reshape configuration + const TensorShape shape_weights_reshape(patch_size, weights_z); + const TensorInfo info_weights_reshape(shape_weights_reshape, 1, weights->info()->data_type(), weights->info()->fixed_point_position()); + _weights_reshaped.allocator()->init(info_weights_reshape); + _weights_reshape_kernel.configure(weights, &_weights_reshaped, biases); + + // GEMV configuration + TensorShape shape_v2mm_out = input->info()->tensor_shape(); + shape_v2mm_out.set(0, conv_size * weights_z); + shape_v2mm_out.set(1, 1); + shape_v2mm_out.set(2, 1); + const TensorInfo info_v2mm_out(shape_v2mm_out, 1, input->info()->data_type(), input->info()->fixed_point_position()); + _v2mm_output.allocator()->init(info_v2mm_out); + _v2mm_kernel.configure(&_input_reshaped, &_weights_reshaped, &_v2mm_output); + _vector_to_tensor_kernel.configure(&_v2mm_output, output, conv_w, conv_h); + + // Allocate intermediate tensors + _input_reshaped.allocator()->allocate(); + _weights_reshaped.allocator()->allocate(); + _v2mm_output.allocator()->allocate(); +} + +void NEDepthwiseConvolution::run() +{ + NEScheduler::get().schedule(&_im2col_kernel, Window::DimX); + NEScheduler::get().schedule(&_weights_reshape_kernel, Window::DimX); + NEScheduler::get().schedule(&_v2mm_kernel, Window::DimX); + NEScheduler::get().schedule(&_vector_to_tensor_kernel, Window::DimX); } \ No newline at end of file diff --git a/tests/validation/NEON/DepthwiseConvolution.cpp b/tests/validation/NEON/DepthwiseConvolution.cpp index b6719b58e8..3a4b7aa2e9 100644 --- a/tests/validation/NEON/DepthwiseConvolution.cpp +++ b/tests/validation/NEON/DepthwiseConvolution.cpp @@ -84,12 +84,26 @@ DATA_TEST_CASE(Configuration, framework::DatasetMode::ALL, combine(framework::da validate(dst.info()->padding(), padding); } -template -using NEDepthwiseConvolutionFixture3x3 = DepthwiseConvolutionValidationFixture; - TEST_SUITE(Float) TEST_SUITE(F32) +TEST_SUITE(Generic) +template +using NEDepthwiseConvolutionFixture = DepthwiseConvolutionValidationFixture; +FIXTURE_DATA_TEST_CASE(RunSmall, NEDepthwiseConvolutionFixture, framework::DatasetMode::PRECOMMIT, combine(datasets::SmallDepthwiseConvolutionDataset(), framework::dataset::make("DataType", + DataType::F32))) +{ + validate(Accessor(_target), _reference, tolerance_f32); +} +FIXTURE_DATA_TEST_CASE(RunLarge, NEDepthwiseConvolutionFixture, framework::DatasetMode::NIGHTLY, combine(datasets::LargeDepthwiseConvolutionDataset(), framework::dataset::make("DataType", + DataType::F32))) +{ + validate(Accessor(_target), _reference, tolerance_f32); +} +TEST_SUITE_END() + TEST_SUITE(W3x3) +template +using NEDepthwiseConvolutionFixture3x3 = DepthwiseConvolutionValidationFixture; FIXTURE_DATA_TEST_CASE(RunSmall, NEDepthwiseConvolutionFixture3x3, framework::DatasetMode::ALL, combine(datasets::SmallDepthwiseConvolutionDataset3x3(), framework::dataset::make("DataType", DataType::F32))) { @@ -101,6 +115,7 @@ FIXTURE_DATA_TEST_CASE(RunLarge, NEDepthwiseConvolutionFixture3x3, framew validate(Accessor(_target), _reference, tolerance_f32); } TEST_SUITE_END() + TEST_SUITE_END() TEST_SUITE_END() -- cgit v1.2.1