From 27400b90a9cb3fe028c5b724b58ce0e82d89b5e8 Mon Sep 17 00:00:00 2001 From: Michele Di Giorgio Date: Thu, 1 Nov 2018 13:44:05 +0000 Subject: COMPMID-1707: Create 3 special CLWidthConcatenate kernel to concatenate 2/4 and 8 tensors (Part 1) Creating special cases for concatening 2 and 4 tensors. Change-Id: I6a739a494ae45011acb65369e353f9ef96970b90 --- arm_compute/core/CL/CLKernels.h | 2 + .../CL/kernels/CLWidthConcatenate2TensorsKernel.h | 79 ++++++++ .../CL/kernels/CLWidthConcatenate4TensorsKernel.h | 85 +++++++++ .../runtime/CL/functions/CLWidthConcatenateLayer.h | 8 +- src/core/CL/CLKernelLibrary.cpp | 2 + src/core/CL/cl_kernels/concatenate.cl | 208 ++++++++++++++++++++- .../kernels/CLWidthConcatenate2TensorsKernel.cpp | 151 +++++++++++++++ .../kernels/CLWidthConcatenate4TensorsKernel.cpp | 171 +++++++++++++++++ .../CL/functions/CLWidthConcatenateLayer.cpp | 75 ++++++-- .../fixtures/WidthConcatenateLayerFixture.h | 2 +- 10 files changed, 764 insertions(+), 19 deletions(-) create mode 100644 arm_compute/core/CL/kernels/CLWidthConcatenate2TensorsKernel.h create mode 100644 arm_compute/core/CL/kernels/CLWidthConcatenate4TensorsKernel.h create mode 100644 src/core/CL/kernels/CLWidthConcatenate2TensorsKernel.cpp create mode 100644 src/core/CL/kernels/CLWidthConcatenate4TensorsKernel.cpp diff --git a/arm_compute/core/CL/CLKernels.h b/arm_compute/core/CL/CLKernels.h index 36abb7bd78..df76366a4b 100644 --- a/arm_compute/core/CL/CLKernels.h +++ b/arm_compute/core/CL/CLKernels.h @@ -127,6 +127,8 @@ #include "arm_compute/core/CL/kernels/CLWarpAffineKernel.h" #include "arm_compute/core/CL/kernels/CLWarpPerspectiveKernel.h" #include "arm_compute/core/CL/kernels/CLWeightsReshapeKernel.h" +#include "arm_compute/core/CL/kernels/CLWidthConcatenate2TensorsKernel.h" +#include "arm_compute/core/CL/kernels/CLWidthConcatenate4TensorsKernel.h" #include "arm_compute/core/CL/kernels/CLWidthConcatenateLayerKernel.h" #include "arm_compute/core/CL/kernels/CLWinogradFilterTransformKernel.h" #include "arm_compute/core/CL/kernels/CLWinogradInputTransformKernel.h" diff --git a/arm_compute/core/CL/kernels/CLWidthConcatenate2TensorsKernel.h b/arm_compute/core/CL/kernels/CLWidthConcatenate2TensorsKernel.h new file mode 100644 index 0000000000..cc2eaa25f2 --- /dev/null +++ b/arm_compute/core/CL/kernels/CLWidthConcatenate2TensorsKernel.h @@ -0,0 +1,79 @@ +/* + * Copyright (c) 2018 ARM Limited. + * + * SPDX-License-Identifier: MIT + * + * Permission is hereby granted, free of charge, to any person obtaining a copy + * of this software and associated documentation files (the "Software"), to + * deal in the Software without restriction, including without limitation the + * rights to use, copy, modify, merge, publish, distribute, sublicense, and/or + * sell copies of the Software, and to permit persons to whom the Software is + * furnished to do so, subject to the following conditions: + * + * The above copyright notice and this permission notice shall be included in all + * copies or substantial portions of the Software. + * + * THE SOFTWARE IS PROVIDED "AS IS", WITHOUT WARRANTY OF ANY KIND, EXPRESS OR + * IMPLIED, INCLUDING BUT NOT LIMITED TO THE WARRANTIES OF MERCHANTABILITY, + * FITNESS FOR A PARTICULAR PURPOSE AND NONINFRINGEMENT. IN NO EVENT SHALL THE + * AUTHORS OR COPYRIGHT HOLDERS BE LIABLE FOR ANY CLAIM, DAMAGES OR OTHER + * LIABILITY, WHETHER IN AN ACTION OF CONTRACT, TORT OR OTHERWISE, ARISING FROM, + * OUT OF OR IN CONNECTION WITH THE SOFTWARE OR THE USE OR OTHER DEALINGS IN THE + * SOFTWARE. + */ + +#ifndef __ARM_COMPUTE_CLWIDTHCONCATENATE_2TENSORS_KERNEL_H__ +#define __ARM_COMPUTE_CLWIDTHCONCATENATE_2TENSORS_KERNEL_H__ + +#include "arm_compute/core/CL/ICLKernel.h" +#include "arm_compute/core/Types.h" + +namespace arm_compute +{ +class ICLTensor; + +/** Interface for the width concatenate kernel of 2 tensors. + * The input1 and input2 tensors will be concatenated into the output tensor. + */ +class CLWidthConcatenate2TensorsKernel : public ICLKernel +{ +public: + /** Default constructor */ + CLWidthConcatenate2TensorsKernel(); + /** Prevent instances of this class from being copied (As this class contains pointers) */ + CLWidthConcatenate2TensorsKernel(const CLWidthConcatenate2TensorsKernel &) = delete; + /** Prevent instances of this class from being copied (As this class contains pointers) */ + CLWidthConcatenate2TensorsKernel &operator=(const CLWidthConcatenate2TensorsKernel &) = delete; + /** Allow instances of this class to be moved */ + CLWidthConcatenate2TensorsKernel(CLWidthConcatenate2TensorsKernel &&) = default; + /** Allow instances of this class to be moved */ + CLWidthConcatenate2TensorsKernel &operator=(CLWidthConcatenate2TensorsKernel &&) = default; + /** Default destructor */ + ~CLWidthConcatenate2TensorsKernel() = default; + /** Initialise the kernel's input1s and output + * + * @param[in] input1 First input tensor. Data types supported: U8/S8/QASYMM8/U16/S16/F16/U32/S32/F32 + * @param[in] input2 Second input tensor. Data types supported: same as @p input1 + * @param[out] output Output tensor. Data types supported: Same as @p input1. + */ + void configure(const ICLTensor *input1, const ICLTensor *input2, ICLTensor *output); + /** Static function to check if given info will lead to a valid configuration of @ref CLWidthConcatenate2TensorsKernel + * + * @param[in] input1 First tensor info. Data types supported: U8/S8/QASYMM8/U16/S16/F16/U32/S32/F32 + * @param[in] input2 Second tensor info. Data types supported: same as @p input1 + * @param[in] output Output tensor info. Data types supported: Same as @p input1. + * + * @return a status + */ + static Status validate(const ITensorInfo *input1, const ITensorInfo *input2, const ITensorInfo *output); + + // Inherited methods overridden: + void run(const Window &window, cl::CommandQueue &queue) override; + +private: + const ICLTensor *_input1; + const ICLTensor *_input2; + ICLTensor *_output; +}; +} // namespace arm_compute +#endif /* __ARM_COMPUTE_CLWIDTHCONCATENATE_2TENSORS_KERNEL_H__ */ diff --git a/arm_compute/core/CL/kernels/CLWidthConcatenate4TensorsKernel.h b/arm_compute/core/CL/kernels/CLWidthConcatenate4TensorsKernel.h new file mode 100644 index 0000000000..952fd99beb --- /dev/null +++ b/arm_compute/core/CL/kernels/CLWidthConcatenate4TensorsKernel.h @@ -0,0 +1,85 @@ +/* + * Copyright (c) 2018 ARM Limited. + * + * SPDX-License-Identifier: MIT + * + * Permission is hereby granted, free of charge, to any person obtaining a copy + * of this software and associated documentation files (the "Software"), to + * deal in the Software without restriction, including without limitation the + * rights to use, copy, modify, merge, publish, distribute, sublicense, and/or + * sell copies of the Software, and to permit persons to whom the Software is + * furnished to do so, subject to the following conditions: + * + * The above copyright notice and this permission notice shall be included in all + * copies or substantial portions of the Software. + * + * THE SOFTWARE IS PROVIDED "AS IS", WITHOUT WARRANTY OF ANY KIND, EXPRESS OR + * IMPLIED, INCLUDING BUT NOT LIMITED TO THE WARRANTIES OF MERCHANTABILITY, + * FITNESS FOR A PARTICULAR PURPOSE AND NONINFRINGEMENT. IN NO EVENT SHALL THE + * AUTHORS OR COPYRIGHT HOLDERS BE LIABLE FOR ANY CLAIM, DAMAGES OR OTHER + * LIABILITY, WHETHER IN AN ACTION OF CONTRACT, TORT OR OTHERWISE, ARISING FROM, + * OUT OF OR IN CONNECTION WITH THE SOFTWARE OR THE USE OR OTHER DEALINGS IN THE + * SOFTWARE. + */ + +#ifndef __ARM_COMPUTE_CLWIDTHCONCATENATE_4TENSORS_KERNEL_H__ +#define __ARM_COMPUTE_CLWIDTHCONCATENATE_4TENSORS_KERNEL_H__ + +#include "arm_compute/core/CL/ICLKernel.h" +#include "arm_compute/core/Types.h" + +namespace arm_compute +{ +class ICLTensor; + +/** Interface for the width concatenate kernel of 4 tensors. + * All input tensors will be concatenated into the output tensor. + */ +class CLWidthConcatenate4TensorsKernel : public ICLKernel +{ +public: + /** Default constructor */ + CLWidthConcatenate4TensorsKernel(); + /** Prevent instances of this class from being copied (As this class contains pointers) */ + CLWidthConcatenate4TensorsKernel(const CLWidthConcatenate4TensorsKernel &) = delete; + /** Prevent instances of this class from being copied (As this class contains pointers) */ + CLWidthConcatenate4TensorsKernel &operator=(const CLWidthConcatenate4TensorsKernel &) = delete; + /** Allow instances of this class to be moved */ + CLWidthConcatenate4TensorsKernel(CLWidthConcatenate4TensorsKernel &&) = default; + /** Allow instances of this class to be moved */ + CLWidthConcatenate4TensorsKernel &operator=(CLWidthConcatenate4TensorsKernel &&) = default; + /** Default destructor */ + ~CLWidthConcatenate4TensorsKernel() = default; + /** Initialise the kernel's input1s and output + * + * @param[in] input1 First input tensor. Data types supported: U8/S8/QASYMM8/U16/S16/F16/U32/S32/F32 + * @param[in] input2 Second input tensor. Data types supported: same as @p input1 + * @param[in] input3 Third input tensor. Data types supported: same as @p input1 + * @param[in] input4 Fourth input tensor. Data types supported: same as @p input1 + * @param[out] output Output tensor. Data types supported: Same as @p input1. + */ + void configure(const ICLTensor *input1, const ICLTensor *input2, const ICLTensor *input3, const ICLTensor *input4, ICLTensor *output); + /** Static function to check if given info will lead to a valid configuration of @ref CLWidthConcatenate4TensorsKernel + * + * @param[in] input1 First tensor info. Data types supported: U8/S8/QASYMM8/U16/S16/F16/U32/S32/F32 + * @param[in] input2 Second tensor info. Data types supported: same as @p input1 + * @param[in] input3 Third tensor info. Data types supported: same as @p input1 + * @param[in] input4 Fourth tensor info. Data types supported: same as @p input1 + * @param[in] output Output tensor info. Data types supported: Same as @p input1. + * + * @return a status + */ + static Status validate(const ITensorInfo *input1, const ITensorInfo *input2, const ITensorInfo *input3, const ITensorInfo *input4, const ITensorInfo *output); + + // Inherited methods overridden: + void run(const Window &window, cl::CommandQueue &queue) override; + +private: + const ICLTensor *_input1; + const ICLTensor *_input2; + const ICLTensor *_input3; + const ICLTensor *_input4; + ICLTensor *_output; +}; +} // namespace arm_compute +#endif /* __ARM_COMPUTE_CLWIDTHCONCATENATE_4TENSORS_KERNEL_H__ */ diff --git a/arm_compute/runtime/CL/functions/CLWidthConcatenateLayer.h b/arm_compute/runtime/CL/functions/CLWidthConcatenateLayer.h index 44462b02b2..55b65dadc4 100644 --- a/arm_compute/runtime/CL/functions/CLWidthConcatenateLayer.h +++ b/arm_compute/runtime/CL/functions/CLWidthConcatenateLayer.h @@ -29,6 +29,8 @@ #include "arm_compute/core/Window.h" #include "arm_compute/runtime/IFunction.h" +#include "arm_compute/core/CL/kernels/CLWidthConcatenate2TensorsKernel.h" +#include "arm_compute/core/CL/kernels/CLWidthConcatenate4TensorsKernel.h" #include "arm_compute/core/CL/kernels/CLWidthConcatenateLayerKernel.h" #include @@ -40,7 +42,9 @@ class ICLTensor; /** Basic function to execute concatenate tensors along x axis. This function calls the following kernel: * - * -# @ref CLDepthConcatenateLayerKernel + * -# @ref CLWidthConcatenateLayerKernel + * -# @ref CLWidthConcatenate2TensorsKernel (if there are exactly 2 input tensors) + * -# @ref CLWidthConcatenate4TensorsKernel (if there are exactly 4 input tensors) * */ class CLWidthConcatenateLayer : public IFunction @@ -74,6 +78,8 @@ public: private: std::unique_ptr _concat_kernels_vector; + CLWidthConcatenate2TensorsKernel _concat_x2_kernel; + CLWidthConcatenate4TensorsKernel _concat_x4_kernel; unsigned int _num_inputs; }; } // namespace arm_compute diff --git a/src/core/CL/CLKernelLibrary.cpp b/src/core/CL/CLKernelLibrary.cpp index b9b3ce970b..847236925a 100644 --- a/src/core/CL/CLKernelLibrary.cpp +++ b/src/core/CL/CLKernelLibrary.cpp @@ -182,6 +182,8 @@ const std::map CLKernelLibrary::_kernel_program_map = { "combine_gradients_L2", "canny.cl" }, { "concatenate_depth", "concatenate.cl" }, { "concatenate_width", "concatenate.cl" }, + { "concatenate_width_x2", "concatenate.cl" }, + { "concatenate_width_x4", "concatenate.cl" }, { "convolution_rectangle", "convolution_rectangle.cl" }, { "col2im", "col2im.cl" }, { "convert_depth_down", "depth_convert.cl" }, diff --git a/src/core/CL/cl_kernels/concatenate.cl b/src/core/CL/cl_kernels/concatenate.cl index a232a94dfc..0e8805f9b6 100644 --- a/src/core/CL/cl_kernels/concatenate.cl +++ b/src/core/CL/cl_kernels/concatenate.cl @@ -25,13 +25,218 @@ #if defined(DATA_TYPE) && defined(VEC_SIZE) +#if defined(DEPTH) && defined(ELEMENT_SIZE) + +#if defined(INPUT1_WIDTH) + +#if ELEMENT_SIZE == 1 +#define COND_DATA_TYPE char +#elif ELEMENT_SIZE == 2 +#define COND_DATA_TYPE short +#elif ELEMENT_SIZE == 4 +#define COND_DATA_TYPE int +#else // ELEMENT_SIZE +#error "Element size not supported" +#endif // ELEMENT_SIZE + +#if VEC_SIZE == 2 +#define SEQ ((int2)(0, 1)) +#elif VEC_SIZE == 4 +#define SEQ ((int4)(0, 1, 2, 3)) +#elif VEC_SIZE == 8 +#define SEQ ((int8)(0, 1, 2, 3, 4, 5, 6, 7)) +#elif VEC_SIZE == 16 +#define SEQ ((int16)(0, 1, 2, 3, 4, 5, 6, 7, 8, 9, 10, 11, 12, 13, 14, 15)) +#else // VEC_SIZE +#error "Vector size not supported" +#endif // VEC_SIZE +/** This kernel concatenates two input tensors into the output tensor along the first dimension + * + * @note The data type has to be passed at compile time using -DDATA_TYPE. i.e. -DDATA_TYPE=float + * @note Vector size has to be passed at compile time using -DVEC_SIZE. i.e. -DVEC_SIZE=16 + * @note The offset for the first spatial dimension has to be passed at compile time using -DWIDTH_OFFSET. i.e. -DWIDTH_OFFSET=128 + * @note Tensor depth should be given as a preprocessor argument using -DDEPTH=size. e.g. -DDEPTH=16 + * @note First input tensor width should be given as a preprocessor argument using -DINPUT1_WIDTH=width. e.g. -DINPUT1_WIDTH=8 + * + * @param[in] src1_ptr Pointer to the source tensor. Supported data types: U8/S8/QASYMM8/U16/S16/F16/U32/F32 + * @param[in] src1_stride_x Stride of the source tensor in X dimension (in bytes) + * @param[in] src1_step_x src_stride_x * number of elements along X processed per workitem(in bytes) + * @param[in] src1_stride_y Stride of the source tensor in Y dimension (in bytes) + * @param[in] src1_step_y src_stride_y * number of elements along Y processed per workitem(in bytes) + * @param[in] src1_stride_z Stride of the source tensor in Z dimension (in bytes) + * @param[in] src1_step_z src_stride_z * number of elements along Z processed per workitem(in bytes) + * @param[in] src1_stride_w Stride of the first source tensor in Z dimension (in bytes) + * @param[in] src1_step_w src_stride_z * number of elements along Z processed per workitem(in bytes) + * @param[in] src1_offset_first_element_in_bytes The offset of the first element in the source tensor + * @param[in] src2_ptr Pointer to the source tensor. Supported data types: same as @p src1_ptr + * @param[in] src2_stride_x Stride of the source tensor in X dimension (in bytes) + * @param[in] src2_step_x src_stride_x * number of elements along X processed per workitem(in bytes) + * @param[in] src2_stride_y Stride of the source tensor in Y dimension (in bytes) + * @param[in] src2_step_y src_stride_y * number of elements along Y processed per workitem(in bytes) + * @param[in] src2_stride_z Stride of the source tensor in Z dimension (in bytes) + * @param[in] src2_step_z src_stride_z * number of elements along Z processed per workitem(in bytes) + * @param[in] src2_stride_w Stride of the first source tensor in Z dimension (in bytes) + * @param[in] src2_step_w src_stride_z * number of elements along Z processed per workitem(in bytes) + * @param[in] src2_offset_first_element_in_bytes The offset of the first element in the source tensor + * @param[out] dst_ptr Pointer to the destination tensor. Supported data types: same as @p src1_ptr + * @param[in] dst_stride_x Stride of the destination tensor in X dimension (in bytes) + * @param[in] dst_step_x dst_stride_x * number of elements along X processed per workitem(in bytes) + * @param[in] dst_stride_y Stride of the destination tensor in Y dimension (in bytes) + * @param[in] dst_step_y dst_stride_y * number of elements along Y processed per workitem(in bytes) + * @param[in] dst_stride_z Stride of the source tensor in Z dimension (in bytes) + * @param[in] dst_step_z dst_stride_z * number of elements along Z processed per workitem(in bytes) + * @param[in] dst_stride_w Stride of the destination tensor in Z dimension (in bytes) + * @param[in] dst_step_w output_stride_z * number of elements along Z processed per workitem(in bytes) + * @param[in] dst_offset_first_element_in_bytes The offset of the first element in the destination tensor + */ +__kernel void concatenate_width_x2( + TENSOR4D_DECLARATION(src1), + TENSOR4D_DECLARATION(src2), + TENSOR4D_DECLARATION(dst)) +{ + Tensor4D dst = CONVERT_TO_TENSOR4D_STRUCT(dst, DEPTH); + + // Calculate input indices + const int x = get_global_id(0) * (int)VEC_SIZE; + const int y = get_global_id(1); + const int z = get_global_id(2) % (int)DEPTH; + const int w = get_global_id(2) / (int)DEPTH; + const int x1 = min(x, (int)INPUT1_WIDTH); + const int x2 = max(x - (int)INPUT1_WIDTH, -(int)VEC_SIZE); + + // Calculate inputs and output addresses + const __global uchar *in1_ptr = src1_ptr + (int)src1_offset_first_element_in_bytes + x1 * (int)src1_stride_x + y * (int)src1_stride_y + z * (int)src1_stride_z + w * (int)src1_stride_w; + const __global uchar *in2_ptr = src2_ptr + (int)src2_offset_first_element_in_bytes + x2 * (int)src2_stride_x + y * (int)src2_stride_y + z * (int)src2_stride_z + w * (int)src2_stride_w; + + const VEC_DATA_TYPE(DATA_TYPE, VEC_SIZE) src1_values = VLOAD(VEC_SIZE)(0, (__global DATA_TYPE *)in1_ptr); + const VEC_DATA_TYPE(DATA_TYPE, VEC_SIZE) src2_values = VLOAD(VEC_SIZE)(0, (__global DATA_TYPE *)in2_ptr); + + const VEC_DATA_TYPE(int, VEC_SIZE) x_coords = SEQ + (VEC_DATA_TYPE(int, VEC_SIZE))(x); + const VEC_DATA_TYPE(COND_DATA_TYPE, VEC_SIZE) cond = CONVERT(x_coords < (VEC_DATA_TYPE(int, VEC_SIZE))(INPUT1_WIDTH), VEC_DATA_TYPE(COND_DATA_TYPE, VEC_SIZE)); + const VEC_DATA_TYPE(DATA_TYPE, VEC_SIZE) values = select(src2_values, src1_values, cond); + + VSTORE(VEC_SIZE) + (values, 0, (__global DATA_TYPE *)dst.ptr); +} + +#if defined(INPUT2_WIDTH) && defined(INPUT3_WIDTH) +/** This kernel concatenates four input tensors into the output tensor along the first dimension + * + * @note The data type has to be passed at compile time using -DDATA_TYPE. i.e. -DDATA_TYPE=float + * @note Vector size has to be passed at compile time using -DVEC_SIZE. i.e. -DVEC_SIZE=16 + * @note The offset for the first spatial dimension has to be passed at compile time using -DWIDTH_OFFSET. i.e. -DWIDTH_OFFSET=128 + * @note Tensor depth should be given as a preprocessor argument using -DDEPTH=size. e.g. -DDEPTH=16 + * @note First input tensor width should be given as a preprocessor argument using -DINPUT1_WIDTH=width. e.g. -DINPUT1_WIDTH=8 + * @note Second input tensor width should be given as a preprocessor argument using -DINPUT2_WIDTH=width. e.g. -DINPUT2_WIDTH=8 + * @note Third input tensor width should be given as a preprocessor argument using -DINPUT3_WIDTH=width. e.g. -DINPUT3_WIDTH=8 + * + * @param[in] src1_ptr Pointer to the source tensor. Supported data types: U8/S8/QASYMM8/U16/S16/F16/U32/F32 + * @param[in] src1_stride_x Stride of the source tensor in X dimension (in bytes) + * @param[in] src1_step_x src_stride_x * number of elements along X processed per workitem(in bytes) + * @param[in] src1_stride_y Stride of the source tensor in Y dimension (in bytes) + * @param[in] src1_step_y src_stride_y * number of elements along Y processed per workitem(in bytes) + * @param[in] src1_stride_z Stride of the source tensor in Z dimension (in bytes) + * @param[in] src1_step_z src_stride_z * number of elements along Z processed per workitem(in bytes) + * @param[in] src1_stride_w Stride of the first source tensor in Z dimension (in bytes) + * @param[in] src1_step_w src_stride_z * number of elements along Z processed per workitem(in bytes) + * @param[in] src1_offset_first_element_in_bytes The offset of the first element in the source tensor + * @param[in] src2_ptr Pointer to the source tensor. Supported data types: same as @p src1_ptr + * @param[in] src2_stride_x Stride of the source tensor in X dimension (in bytes) + * @param[in] src2_step_x src_stride_x * number of elements along X processed per workitem(in bytes) + * @param[in] src2_stride_y Stride of the source tensor in Y dimension (in bytes) + * @param[in] src2_step_y src_stride_y * number of elements along Y processed per workitem(in bytes) + * @param[in] src2_stride_z Stride of the source tensor in Z dimension (in bytes) + * @param[in] src2_step_z src_stride_z * number of elements along Z processed per workitem(in bytes) + * @param[in] src2_stride_w Stride of the first source tensor in Z dimension (in bytes) + * @param[in] src2_step_w src_stride_z * number of elements along Z processed per workitem(in bytes) + * @param[in] src2_offset_first_element_in_bytes The offset of the first element in the source tensor + * @param[in] src3_ptr Pointer to the source tensor. Supported data types: same as @p src1_ptr + * @param[in] src3_stride_x Stride of the source tensor in X dimension (in bytes) + * @param[in] src3_step_x src_stride_x * number of elements along X processed per workitem(in bytes) + * @param[in] src3_stride_y Stride of the source tensor in Y dimension (in bytes) + * @param[in] src3_step_y src_stride_y * number of elements along Y processed per workitem(in bytes) + * @param[in] src3_stride_z Stride of the source tensor in Z dimension (in bytes) + * @param[in] src3_step_z src_stride_z * number of elements along Z processed per workitem(in bytes) + * @param[in] src3_stride_w Stride of the first source tensor in Z dimension (in bytes) + * @param[in] src3_step_w src_stride_z * number of elements along Z processed per workitem(in bytes) + * @param[in] src3_offset_first_element_in_bytes The offset of the first element in the source tensor + * @param[in] src4_ptr Pointer to the source tensor. Supported data types: same as @p src1_ptr + * @param[in] src4_stride_x Stride of the source tensor in X dimension (in bytes) + * @param[in] src4_step_x src_stride_x * number of elements along X processed per workitem(in bytes) + * @param[in] src4_stride_y Stride of the source tensor in Y dimension (in bytes) + * @param[in] src4_step_y src_stride_y * number of elements along Y processed per workitem(in bytes) + * @param[in] src4_stride_z Stride of the source tensor in Z dimension (in bytes) + * @param[in] src4_step_z src_stride_z * number of elements along Z processed per workitem(in bytes) + * @param[in] src4_stride_w Stride of the first source tensor in Z dimension (in bytes) + * @param[in] src4_step_w src_stride_z * number of elements along Z processed per workitem(in bytes) + * @param[in] src4_offset_first_element_in_bytes The offset of the first element in the source tensor + * @param[out] dst_ptr Pointer to the destination tensor. Supported data types: same as @p src1_ptr + * @param[in] dst_stride_x Stride of the destination tensor in X dimension (in bytes) + * @param[in] dst_step_x dst_stride_x * number of elements along X processed per workitem(in bytes) + * @param[in] dst_stride_y Stride of the destination tensor in Y dimension (in bytes) + * @param[in] dst_step_y dst_stride_y * number of elements along Y processed per workitem(in bytes) + * @param[in] dst_stride_z Stride of the source tensor in Z dimension (in bytes) + * @param[in] dst_step_z dst_stride_z * number of elements along Z processed per workitem(in bytes) + * @param[in] dst_stride_w Stride of the destination tensor in Z dimension (in bytes) + * @param[in] dst_step_w output_stride_z * number of elements along Z processed per workitem(in bytes) + * @param[in] dst_offset_first_element_in_bytes The offset of the first element in the destination tensor + */ +__kernel void concatenate_width_x4( + TENSOR4D_DECLARATION(src1), + TENSOR4D_DECLARATION(src2), + TENSOR4D_DECLARATION(src3), + TENSOR4D_DECLARATION(src4), + TENSOR4D_DECLARATION(dst)) +{ + Tensor4D dst = CONVERT_TO_TENSOR4D_STRUCT(dst, DEPTH); + + // Calculate input indices + const int x = get_global_id(0) * (int)VEC_SIZE; + const int y = get_global_id(1); + const int z = get_global_id(2) % (int)DEPTH; + const int w = get_global_id(2) / (int)DEPTH; + + const int x1 = min(x, (int)INPUT1_WIDTH); + const int x2 = min(max(x - (int)INPUT1_WIDTH, -(int)VEC_SIZE), (int)INPUT2_WIDTH); + const int x3 = min(max(x - (int)INPUT1_WIDTH - (int)INPUT2_WIDTH, -(int)VEC_SIZE), (int)INPUT3_WIDTH); + const int x4 = max(x - (int)INPUT1_WIDTH - (int)INPUT2_WIDTH - (int)INPUT3_WIDTH, -(int)VEC_SIZE); + + // Calculate inputs and output addresses + const __global uchar *in1_ptr = src1_ptr + (int)src1_offset_first_element_in_bytes + x1 * (int)src1_stride_x + y * (int)src1_stride_y + z * (int)src1_stride_z + w * (int)src1_stride_w; + const __global uchar *in2_ptr = src2_ptr + (int)src2_offset_first_element_in_bytes + x2 * (int)src2_stride_x + y * (int)src2_stride_y + z * (int)src2_stride_z + w * (int)src2_stride_w; + const __global uchar *in3_ptr = src3_ptr + (int)src3_offset_first_element_in_bytes + x3 * (int)src3_stride_x + y * (int)src3_stride_y + z * (int)src3_stride_z + w * (int)src3_stride_w; + const __global uchar *in4_ptr = src4_ptr + (int)src4_offset_first_element_in_bytes + x4 * (int)src4_stride_x + y * (int)src4_stride_y + z * (int)src4_stride_z + w * (int)src4_stride_w; + + const VEC_DATA_TYPE(DATA_TYPE, VEC_SIZE) src1_values = VLOAD(VEC_SIZE)(0, (__global DATA_TYPE *)in1_ptr); + const VEC_DATA_TYPE(DATA_TYPE, VEC_SIZE) src2_values = VLOAD(VEC_SIZE)(0, (__global DATA_TYPE *)in2_ptr); + const VEC_DATA_TYPE(DATA_TYPE, VEC_SIZE) src3_values = VLOAD(VEC_SIZE)(0, (__global DATA_TYPE *)in3_ptr); + const VEC_DATA_TYPE(DATA_TYPE, VEC_SIZE) src4_values = VLOAD(VEC_SIZE)(0, (__global DATA_TYPE *)in4_ptr); + + const VEC_DATA_TYPE(int, VEC_SIZE) x_coords = SEQ + (VEC_DATA_TYPE(int, VEC_SIZE))(x); + + const VEC_DATA_TYPE(COND_DATA_TYPE, VEC_SIZE) cond_in2 = CONVERT(x_coords < (VEC_DATA_TYPE(int, VEC_SIZE))(INPUT1_WIDTH), VEC_DATA_TYPE(COND_DATA_TYPE, VEC_SIZE)); + const VEC_DATA_TYPE(COND_DATA_TYPE, VEC_SIZE) cond_in3 = CONVERT(x_coords < (VEC_DATA_TYPE(int, VEC_SIZE))(INPUT1_WIDTH + INPUT2_WIDTH), VEC_DATA_TYPE(COND_DATA_TYPE, VEC_SIZE)); + const VEC_DATA_TYPE(COND_DATA_TYPE, VEC_SIZE) cond_in4 = CONVERT(x_coords < (VEC_DATA_TYPE(int, VEC_SIZE))(INPUT1_WIDTH + INPUT2_WIDTH + INPUT3_WIDTH), VEC_DATA_TYPE(COND_DATA_TYPE, VEC_SIZE)); + + VEC_DATA_TYPE(DATA_TYPE, VEC_SIZE) + values = select(src2_values, src1_values, cond_in2); + values = select(src3_values, values, cond_in3); + values = select(src4_values, values, cond_in4); + + VSTORE(VEC_SIZE) + (values, 0, (__global DATA_TYPE *)dst.ptr); +} +#endif /* defined(INPUT2_WIDTH) && defined(INPUT3_WIDTH) */ +#endif /* defined(INPUT1_WIDTH) */ +#endif /* defined(DEPTH) && defined(ELEMENT_SIZE) */ + #if defined(WIDTH_OFFSET) && defined(DEPTH) /** This kernel concatenates the input tensor into the output tensor along the first dimension * * @note The data type has to be passed at compile time using -DDATA_TYPE. i.e. -DDATA_TYPE=float * @note Vector size has to be passed at compile time using -DVEC_SIZE. i.e. -DVEC_SIZE=16 * @note The offset for the first spatial dimension has to be passed at compile time using -DWIDTH_OFFSET. i.e. -DWIDTH_OFFSET=128 - * @note Tensor depth should be given as a preprocessor argument using -DDEPTH=size. e.g. -DDEPTH16 + * @note Tensor depth should be given as a preprocessor argument using -DDEPTH=size. e.g. -DDEPTH=16 * * @param[in] src_ptr Pointer to the source tensor. Supported data types: U8/S8/QASYMM8/U16/S16/F16/U32/F32 * @param[in] src_stride_x Stride of the source tensor in X dimension (in bytes) @@ -53,7 +258,6 @@ * @param[in] dst_stride_w Stride of the destination tensor in Z dimension (in bytes) * @param[in] dst_step_w output_stride_z * number of elements along Z processed per workitem(in bytes) * @param[in] dst_offset_first_element_in_bytes The offset of the first element in the destination tensor - * @param[in] offset The offset to the first valid element of the output tensor in bytes */ __kernel void concatenate_width( TENSOR4D_DECLARATION(src), diff --git a/src/core/CL/kernels/CLWidthConcatenate2TensorsKernel.cpp b/src/core/CL/kernels/CLWidthConcatenate2TensorsKernel.cpp new file mode 100644 index 0000000000..b0d27cbc87 --- /dev/null +++ b/src/core/CL/kernels/CLWidthConcatenate2TensorsKernel.cpp @@ -0,0 +1,151 @@ +/* + * Copyright (c) 2018 ARM Limited. + * + * SPDX-License-Identifier: MIT + * + * Permission is hereby granted, free of charge, to any person obtaining a copy + * of this software and associated documentation files (the "Software"), to + * deal in the Software without restriction, including without limitation the + * rights to use, copy, modify, merge, publish, distribute, sublicense, and/or + * sell copies of the Software, and to permit persons to whom the Software is + * furnished to do so, subject to the following conditions: + * + * The above copyright notice and this permission notice shall be included in all + * copies or substantial portions of the Software. + * + * THE SOFTWARE IS PROVIDED "AS IS", WITHOUT WARRANTY OF ANY KIND, EXPRESS OR + * IMPLIED, INCLUDING BUT NOT LIMITED TO THE WARRANTIES OF MERCHANTABILITY, + * FITNESS FOR A PARTICULAR PURPOSE AND NONINFRINGEMENT. IN NO EVENT SHALL THE + * AUTHORS OR COPYRIGHT HOLDERS BE LIABLE FOR ANY CLAIM, DAMAGES OR OTHER + * LIABILITY, WHETHER IN AN ACTION OF CONTRACT, TORT OR OTHERWISE, ARISING FROM, + * OUT OF OR IN CONNECTION WITH THE SOFTWARE OR THE USE OR OTHER DEALINGS IN THE + * SOFTWARE. + */ +#include "arm_compute/core/CL/kernels/CLWidthConcatenate2TensorsKernel.h" + +#include "arm_compute/core/AccessWindowStatic.h" +#include "arm_compute/core/CL/CLHelpers.h" +#include "arm_compute/core/CL/CLKernelLibrary.h" +#include "arm_compute/core/CL/CLValidate.h" +#include "arm_compute/core/CL/ICLTensor.h" +#include "arm_compute/core/CL/OpenCL.h" +#include "arm_compute/core/Error.h" +#include "arm_compute/core/Helpers.h" +#include "arm_compute/core/IAccessWindow.h" +#include "arm_compute/core/TensorInfo.h" +#include "arm_compute/core/Utils.h" +#include "arm_compute/core/Window.h" +#include "arm_compute/core/utils/misc/ShapeCalculator.h" + +#include "support/ToolchainSupport.h" + +namespace arm_compute +{ +namespace +{ +constexpr unsigned int num_elems_processed_per_iteration = 8; + +std::pair validate_and_configure_window(ITensorInfo *input1, ITensorInfo *input2, ITensorInfo *output) +{ + // The window needs to be based on the output + Window win = calculate_max_window(*output, Steps(num_elems_processed_per_iteration)); + AccessWindowStatic input1_access(input1, 0, 0, ceil_to_multiple(input1->dimension(0), num_elems_processed_per_iteration) + num_elems_processed_per_iteration, input1->dimension(1)); + AccessWindowStatic input2_access(input2, -num_elems_processed_per_iteration, 0, ceil_to_multiple(input2->dimension(0), num_elems_processed_per_iteration) + num_elems_processed_per_iteration, + input2->dimension(1)); + AccessWindowHorizontal output_access(output, 0, num_elems_processed_per_iteration); + bool window_changed = update_window_and_padding(win, input1_access, input2_access, output_access); + + Window win_collapsed = win.collapse(win, Window::DimZ); + + Status err = (window_changed) ? ARM_COMPUTE_CREATE_ERROR(ErrorCode::RUNTIME_ERROR, "Insufficient Padding!") : Status{}; + return std::make_pair(err, win_collapsed); +} +Status validate_arguments(const ITensorInfo *input1, const ITensorInfo *input2, const ITensorInfo *output) +{ + ARM_COMPUTE_RETURN_ERROR_ON_NULLPTR(input1, input2, output); + ARM_COMPUTE_RETURN_ERROR_ON_F16_UNSUPPORTED(input1); + ARM_COMPUTE_RETURN_ERROR_ON_DATA_TYPE_CHANNEL_NOT_IN(input1, 1, DataType::U8, DataType::S8, DataType::QASYMM8, DataType::U16, DataType::S16, DataType::F16, DataType::U32, + DataType::F32); + ARM_COMPUTE_RETURN_ERROR_ON_MISMATCHING_DATA_TYPES(input1, input2, output); + ARM_COMPUTE_RETURN_ERROR_ON(input1->dimension(0) + input2->dimension(0) > output->dimension(0)); + + for(size_t i = 1; i < Coordinates::num_max_dimensions; ++i) + { + ARM_COMPUTE_RETURN_ERROR_ON(input1->dimension(i) != output->dimension(i)); + ARM_COMPUTE_RETURN_ERROR_ON(input2->dimension(i) != output->dimension(i)); + } + ARM_COMPUTE_RETURN_ERROR_ON(input1->num_dimensions() > 4); + + return Status{}; +} +} // namespace + +CLWidthConcatenate2TensorsKernel::CLWidthConcatenate2TensorsKernel() + : _input1(nullptr), _input2(nullptr), _output(nullptr) +{ +} + +Status CLWidthConcatenate2TensorsKernel::validate(const ITensorInfo *input1, const ITensorInfo *input2, const ITensorInfo *output) +{ + ARM_COMPUTE_RETURN_ON_ERROR(validate_arguments(input1, input2, output)); + ARM_COMPUTE_RETURN_ON_ERROR(validate_and_configure_window(input1->clone().get(), input2->clone().get(), output->clone().get()).first); + return Status{}; +} + +void CLWidthConcatenate2TensorsKernel::configure(const ICLTensor *input1, const ICLTensor *input2, ICLTensor *output) +{ + ARM_COMPUTE_ERROR_ON_NULLPTR(input1, input2, output); + ARM_COMPUTE_ERROR_THROW_ON(validate_arguments(input1->info(), input2->info(), output->info())); + + _input1 = input1; + _input2 = input2; + _output = output; + + // Add build options + CLBuildOptions build_opts; + build_opts.add_option("-DDATA_TYPE=" + get_underlying_cl_type_from_data_type(input1->info()->data_type())); + build_opts.add_option("-DVEC_SIZE=" + support::cpp11::to_string(num_elems_processed_per_iteration)); + build_opts.add_option("-DDEPTH=" + support::cpp11::to_string(input1->info()->dimension(2))); + build_opts.add_option("-DINPUT1_WIDTH=" + support::cpp11::to_string(input1->info()->dimension(0))); + build_opts.add_option("-DELEMENT_SIZE=" + support::cpp11::to_string(input1->info()->element_size())); + + // Create kernel + _kernel = static_cast(CLKernelLibrary::get().create_kernel("concatenate_width_x2", build_opts.options())); + + // Configure kernel window + auto win_config = validate_and_configure_window(input1->info(), input2->info(), output->info()); + ARM_COMPUTE_ERROR_THROW_ON(std::get<0>(win_config)); + + ICLKernel::configure_internal(std::get<1>(win_config)); + + // Set config_id for enabling LWS tuning + _config_id = "concatenate_width_x2_"; + _config_id += lower_string(string_from_data_type(input1->info()->data_type())); + _config_id += "_"; + _config_id += support::cpp11::to_string(input1->info()->dimension(0)); + _config_id += "_"; + _config_id += support::cpp11::to_string(input1->info()->dimension(1)); + _config_id += "_"; + _config_id += support::cpp11::to_string(input2->info()->dimension(0)); + _config_id += "_"; + _config_id += support::cpp11::to_string(input2->info()->dimension(1)); +} + +void CLWidthConcatenate2TensorsKernel::run(const Window &window, cl::CommandQueue &queue) +{ + ARM_COMPUTE_ERROR_ON_UNCONFIGURED_KERNEL(this); + ARM_COMPUTE_ERROR_ON_INVALID_SUBWINDOW(ICLKernel::window(), window); + + Window slice = window.first_slice_window_4D(); + + do + { + unsigned int idx = 0; + add_4D_tensor_argument(idx, _input1, slice); + add_4D_tensor_argument(idx, _input2, slice); + add_4D_tensor_argument(idx, _output, slice); + enqueue(queue, *this, window, lws_hint()); + } + while(window.slide_window_slice_4D(slice)); +} +} // namespace arm_compute diff --git a/src/core/CL/kernels/CLWidthConcatenate4TensorsKernel.cpp b/src/core/CL/kernels/CLWidthConcatenate4TensorsKernel.cpp new file mode 100644 index 0000000000..75aef9cce0 --- /dev/null +++ b/src/core/CL/kernels/CLWidthConcatenate4TensorsKernel.cpp @@ -0,0 +1,171 @@ +/* + * Copyright (c) 2018 ARM Limited. + * + * SPDX-License-Identifier: MIT + * + * Permission is hereby granted, free of charge, to any person obtaining a copy + * of this software and associated documentation files (the "Software"), to + * deal in the Software without restriction, including without limitation the + * rights to use, copy, modify, merge, publish, distribute, sublicense, and/or + * sell copies of the Software, and to permit persons to whom the Software is + * furnished to do so, subject to the following conditions: + * + * The above copyright notice and this permission notice shall be included in all + * copies or substantial portions of the Software. + * + * THE SOFTWARE IS PROVIDED "AS IS", WITHOUT WARRANTY OF ANY KIND, EXPRESS OR + * IMPLIED, INCLUDING BUT NOT LIMITED TO THE WARRANTIES OF MERCHANTABILITY, + * FITNESS FOR A PARTICULAR PURPOSE AND NONINFRINGEMENT. IN NO EVENT SHALL THE + * AUTHORS OR COPYRIGHT HOLDERS BE LIABLE FOR ANY CLAIM, DAMAGES OR OTHER + * LIABILITY, WHETHER IN AN ACTION OF CONTRACT, TORT OR OTHERWISE, ARISING FROM, + * OUT OF OR IN CONNECTION WITH THE SOFTWARE OR THE USE OR OTHER DEALINGS IN THE + * SOFTWARE. + */ +#include "arm_compute/core/CL/kernels/CLWidthConcatenate4TensorsKernel.h" + +#include "arm_compute/core/AccessWindowStatic.h" +#include "arm_compute/core/CL/CLHelpers.h" +#include "arm_compute/core/CL/CLKernelLibrary.h" +#include "arm_compute/core/CL/CLValidate.h" +#include "arm_compute/core/CL/ICLTensor.h" +#include "arm_compute/core/CL/OpenCL.h" +#include "arm_compute/core/Error.h" +#include "arm_compute/core/Helpers.h" +#include "arm_compute/core/IAccessWindow.h" +#include "arm_compute/core/TensorInfo.h" +#include "arm_compute/core/Utils.h" +#include "arm_compute/core/Window.h" +#include "arm_compute/core/utils/misc/ShapeCalculator.h" + +#include "support/ToolchainSupport.h" + +namespace arm_compute +{ +namespace +{ +constexpr unsigned int num_elems_processed_per_iteration = 8; + +std::pair validate_and_configure_window(ITensorInfo *input1, ITensorInfo *input2, ITensorInfo *input3, ITensorInfo *input4, ITensorInfo *output) +{ + // The window needs to be based on the output + Window win = calculate_max_window(*output, Steps(num_elems_processed_per_iteration)); + AccessWindowStatic input1_access(input1, 0, 0, ceil_to_multiple(input1->dimension(0), num_elems_processed_per_iteration) + num_elems_processed_per_iteration, input1->dimension(1)); + AccessWindowStatic input2_access(input2, -num_elems_processed_per_iteration, 0, ceil_to_multiple(input2->dimension(0), num_elems_processed_per_iteration) + num_elems_processed_per_iteration, + input2->dimension(1)); + AccessWindowStatic input3_access(input3, -num_elems_processed_per_iteration, 0, ceil_to_multiple(input3->dimension(0), num_elems_processed_per_iteration) + num_elems_processed_per_iteration, + input3->dimension(1)); + AccessWindowStatic input4_access(input4, -num_elems_processed_per_iteration, 0, ceil_to_multiple(input4->dimension(0), num_elems_processed_per_iteration) + num_elems_processed_per_iteration, + input4->dimension(1)); + AccessWindowHorizontal output_access(output, 0, num_elems_processed_per_iteration); + bool window_changed = update_window_and_padding(win, input1_access, input2_access, input3_access, input4_access, output_access); + + Window win_collapsed = win.collapse(win, Window::DimZ); + + Status err = (window_changed) ? ARM_COMPUTE_CREATE_ERROR(ErrorCode::RUNTIME_ERROR, "Insufficient Padding!") : Status{}; + return std::make_pair(err, win_collapsed); +} +Status validate_arguments(const ITensorInfo *input1, const ITensorInfo *input2, const ITensorInfo *input3, const ITensorInfo *input4, const ITensorInfo *output) +{ + ARM_COMPUTE_RETURN_ERROR_ON_NULLPTR(input1, input2, input3, input4, output); + ARM_COMPUTE_RETURN_ERROR_ON_F16_UNSUPPORTED(input1); + ARM_COMPUTE_RETURN_ERROR_ON_DATA_TYPE_CHANNEL_NOT_IN(input1, 1, DataType::U8, DataType::S8, DataType::QASYMM8, DataType::U16, DataType::S16, DataType::F16, DataType::U32, + DataType::F32); + ARM_COMPUTE_RETURN_ERROR_ON_MISMATCHING_DATA_TYPES(input1, input2, input3, input4, output); + ARM_COMPUTE_RETURN_ERROR_ON(input1->dimension(0) + input2->dimension(0) + input3->dimension(0) + input4->dimension(0) > output->dimension(0)); + + for(size_t i = 1; i < Coordinates::num_max_dimensions; ++i) + { + ARM_COMPUTE_RETURN_ERROR_ON(input1->dimension(i) != output->dimension(i)); + ARM_COMPUTE_RETURN_ERROR_ON(input2->dimension(i) != output->dimension(i)); + ARM_COMPUTE_RETURN_ERROR_ON(input3->dimension(i) != output->dimension(i)); + ARM_COMPUTE_RETURN_ERROR_ON(input4->dimension(i) != output->dimension(i)); + } + ARM_COMPUTE_RETURN_ERROR_ON(input1->num_dimensions() > 4); + + return Status{}; +} +} // namespace + +CLWidthConcatenate4TensorsKernel::CLWidthConcatenate4TensorsKernel() + : _input1(nullptr), _input2(nullptr), _input3(nullptr), _input4(nullptr), _output(nullptr) +{ +} + +Status CLWidthConcatenate4TensorsKernel::validate(const ITensorInfo *input1, const ITensorInfo *input2, const ITensorInfo *input3, const ITensorInfo *input4, const ITensorInfo *output) +{ + ARM_COMPUTE_RETURN_ON_ERROR(validate_arguments(input1, input2, input3, input4, output)); + ARM_COMPUTE_RETURN_ON_ERROR(validate_and_configure_window(input1->clone().get(), input2->clone().get(), input3->clone().get(), input4->clone().get(), output->clone().get()).first); + return Status{}; +} + +void CLWidthConcatenate4TensorsKernel::configure(const ICLTensor *input1, const ICLTensor *input2, const ICLTensor *input3, const ICLTensor *input4, ICLTensor *output) +{ + ARM_COMPUTE_ERROR_ON_NULLPTR(input1, input2, input3, input4, output); + ARM_COMPUTE_ERROR_THROW_ON(validate_arguments(input1->info(), input2->info(), input3->info(), input4->info(), output->info())); + + _input1 = input1; + _input2 = input2; + _input3 = input3; + _input4 = input4; + _output = output; + + // Add build options + CLBuildOptions build_opts; + build_opts.add_option("-DDATA_TYPE=" + get_underlying_cl_type_from_data_type(input1->info()->data_type())); + build_opts.add_option("-DVEC_SIZE=" + support::cpp11::to_string(num_elems_processed_per_iteration)); + build_opts.add_option("-DDEPTH=" + support::cpp11::to_string(input1->info()->dimension(2))); + build_opts.add_option("-DINPUT1_WIDTH=" + support::cpp11::to_string(input1->info()->dimension(0))); + build_opts.add_option("-DINPUT2_WIDTH=" + support::cpp11::to_string(input2->info()->dimension(0))); + build_opts.add_option("-DINPUT3_WIDTH=" + support::cpp11::to_string(input3->info()->dimension(0))); + build_opts.add_option("-DELEMENT_SIZE=" + support::cpp11::to_string(input1->info()->element_size())); + + // Create kernel + _kernel = static_cast(CLKernelLibrary::get().create_kernel("concatenate_width_x4", build_opts.options())); + + // Configure kernel window + auto win_config = validate_and_configure_window(input1->info(), input2->info(), input3->info(), input4->info(), output->info()); + ARM_COMPUTE_ERROR_THROW_ON(std::get<0>(win_config)); + + ICLKernel::configure_internal(std::get<1>(win_config)); + + // Set config_id for enabling LWS tuning + _config_id = "concatenate_width_x4_"; + _config_id += lower_string(string_from_data_type(input1->info()->data_type())); + _config_id += "_"; + _config_id += support::cpp11::to_string(input1->info()->dimension(0)); + _config_id += "_"; + _config_id += support::cpp11::to_string(input1->info()->dimension(1)); + _config_id += "_"; + _config_id += support::cpp11::to_string(input2->info()->dimension(0)); + _config_id += "_"; + _config_id += support::cpp11::to_string(input2->info()->dimension(1)); + _config_id += "_"; + _config_id += support::cpp11::to_string(input3->info()->dimension(0)); + _config_id += "_"; + _config_id += support::cpp11::to_string(input3->info()->dimension(1)); + _config_id += "_"; + _config_id += support::cpp11::to_string(input4->info()->dimension(0)); + _config_id += "_"; + _config_id += support::cpp11::to_string(input4->info()->dimension(1)); +} + +void CLWidthConcatenate4TensorsKernel::run(const Window &window, cl::CommandQueue &queue) +{ + ARM_COMPUTE_ERROR_ON_UNCONFIGURED_KERNEL(this); + ARM_COMPUTE_ERROR_ON_INVALID_SUBWINDOW(ICLKernel::window(), window); + + Window slice = window.first_slice_window_4D(); + + do + { + unsigned int idx = 0; + add_4D_tensor_argument(idx, _input1, slice); + add_4D_tensor_argument(idx, _input2, slice); + add_4D_tensor_argument(idx, _input3, slice); + add_4D_tensor_argument(idx, _input4, slice); + add_4D_tensor_argument(idx, _output, slice); + enqueue(queue, *this, window, lws_hint()); + } + while(window.slide_window_slice_4D(slice)); +} +} // namespace arm_compute diff --git a/src/runtime/CL/functions/CLWidthConcatenateLayer.cpp b/src/runtime/CL/functions/CLWidthConcatenateLayer.cpp index 5233ff4f52..46a2d80d10 100644 --- a/src/runtime/CL/functions/CLWidthConcatenateLayer.cpp +++ b/src/runtime/CL/functions/CLWidthConcatenateLayer.cpp @@ -36,26 +36,46 @@ using namespace arm_compute; CLWidthConcatenateLayer::CLWidthConcatenateLayer() // NOLINT : _concat_kernels_vector(), + _concat_x2_kernel(), + _concat_x4_kernel(), _num_inputs(0) { } Status CLWidthConcatenateLayer::validate(const std::vector &inputs_vector, const ITensorInfo *output) // NOLINT { + const unsigned int num_inputs = inputs_vector.size(); + ARM_COMPUTE_RETURN_ERROR_ON_NULLPTR(output); - ARM_COMPUTE_RETURN_ERROR_ON(inputs_vector.size() < 2); + ARM_COMPUTE_RETURN_ERROR_ON(num_inputs < 2); // Output auto inizialitation if not yet initialized TensorInfo tmp_output_info = *output->clone(); TensorShape output_shape = arm_compute::misc::shape_calculator::calculate_width_concatenate_shape(inputs_vector); auto_init_if_empty(tmp_output_info, output_shape, 1, inputs_vector[0]->data_type()); - unsigned int width_offset = 0; - for(const auto &input : inputs_vector) + switch(num_inputs) { - ARM_COMPUTE_RETURN_ERROR_ON_NULLPTR(input); - ARM_COMPUTE_RETURN_ON_ERROR(CLWidthConcatenateLayerKernel::validate(input, width_offset, &tmp_output_info)); - width_offset += input->dimension(0); + case 2: + // Validate WidthConcatenate2Tensors kernels if there are 2 inputs + ARM_COMPUTE_RETURN_ERROR_ON_NULLPTR(inputs_vector[0], inputs_vector[1]); + ARM_COMPUTE_RETURN_ON_ERROR(CLWidthConcatenate2TensorsKernel::validate(inputs_vector[0], inputs_vector[1], &tmp_output_info)); + break; + case 4: + // Validate WidthConcatenate4Tensors kernels if there are 4 inputs + ARM_COMPUTE_RETURN_ERROR_ON_NULLPTR(inputs_vector[0], inputs_vector[1], inputs_vector[2], inputs_vector[3]); + ARM_COMPUTE_RETURN_ON_ERROR(CLWidthConcatenate4TensorsKernel::validate(inputs_vector[0], inputs_vector[1], inputs_vector[2], inputs_vector[3], &tmp_output_info)); + break; + default: + unsigned int width_offset = 0; + // Validate generic case of WidthConcatenate kernel + for(const auto &input : inputs_vector) + { + ARM_COMPUTE_RETURN_ERROR_ON_NULLPTR(input); + ARM_COMPUTE_RETURN_ON_ERROR(CLWidthConcatenateLayerKernel::validate(input, width_offset, &tmp_output_info)); + width_offset += input->dimension(0); + } + break; } return Status{}; @@ -74,16 +94,30 @@ void CLWidthConcatenateLayer::configure(std::vector inputs_vector, // Output auto inizialitation if not yet initialized auto_init_if_empty(*output->info(), output_shape, 1, inputs_vector[0]->info()->data_type()); - ARM_COMPUTE_ERROR_THROW_ON(CLWidthConcatenateLayer::validate(inputs_vector_info, output->info())); - - unsigned int width_offset = 0; - _concat_kernels_vector = arm_compute::support::cpp14::make_unique(_num_inputs); + ARM_COMPUTE_ERROR_THROW_ON(CLWidthConcatenateLayer::validate(inputs_vector_info, output->info())); - for(unsigned int i = 0; i < _num_inputs; i++) + switch(_num_inputs) { - _concat_kernels_vector[i].configure(inputs_vector.at(i), width_offset, output); - width_offset += inputs_vector.at(i)->info()->dimension(0); + case 2: + // Configure WidthConcatenate2Tensors kernel + _concat_x2_kernel.configure(inputs_vector.at(0), inputs_vector.at(1), output); + break; + case 4: + // Configure WidthConcatenate4Tensors kernel + _concat_x4_kernel.configure(inputs_vector.at(0), inputs_vector.at(1), inputs_vector.at(2), inputs_vector.at(3), output); + break; + default: + // Configure generic case WidthConcatenate kernels + _concat_kernels_vector = arm_compute::support::cpp14::make_unique(_num_inputs); + + unsigned int width_offset = 0; + for(unsigned int i = 0; i < _num_inputs; ++i) + { + _concat_kernels_vector[i].configure(inputs_vector.at(i), width_offset, output); + width_offset += inputs_vector.at(i)->info()->dimension(0); + } + break; } } @@ -91,8 +125,19 @@ void CLWidthConcatenateLayer::run() { cl::CommandQueue q = CLScheduler::get().queue(); - for(unsigned i = 0; i < _num_inputs; i++) + switch(_num_inputs) { - CLScheduler::get().enqueue(_concat_kernels_vector[i], true); + case 2: + CLScheduler::get().enqueue(_concat_x2_kernel, true); + break; + case 4: + CLScheduler::get().enqueue(_concat_x4_kernel, true); + break; + default: + for(unsigned int i = 0; i < _num_inputs; ++i) + { + CLScheduler::get().enqueue(_concat_kernels_vector[i], true); + } + break; } } diff --git a/tests/validation/fixtures/WidthConcatenateLayerFixture.h b/tests/validation/fixtures/WidthConcatenateLayerFixture.h index caad0feee0..1f79210350 100644 --- a/tests/validation/fixtures/WidthConcatenateLayerFixture.h +++ b/tests/validation/fixtures/WidthConcatenateLayerFixture.h @@ -52,7 +52,7 @@ public: { // Create input shapes std::mt19937 gen(library->seed()); - std::uniform_int_distribution<> num_dis(2, 4); + std::uniform_int_distribution<> num_dis(2, 8); const int num_tensors = num_dis(gen); std::vector shapes(num_tensors, shape); -- cgit v1.2.1