From 6a8d3b6db13042a859972c33cf40cfeb6d7cfcda Mon Sep 17 00:00:00 2001 From: Michalis Spyrou Date: Fri, 31 Aug 2018 10:07:09 +0100 Subject: COMPMID-1218 Implementing Batch to Space on OpenCL Change-Id: I12ba4c0c35f086ea3f395970b85af5bf8f94850b Reviewed-on: https://eu-gerrit-1.euhpc.arm.com/145052 Reviewed-by: Pablo Tello Tested-by: Jenkins --- src/core/CL/CLKernelLibrary.cpp | 6 + src/core/CL/cl_kernels/batch_to_space.cl | 131 ++++++++++++++++ src/core/CL/kernels/CLBatchToSpaceLayerKernel.cpp | 172 ++++++++++++++++++++++ 3 files changed, 309 insertions(+) create mode 100644 src/core/CL/cl_kernels/batch_to_space.cl create mode 100644 src/core/CL/kernels/CLBatchToSpaceLayerKernel.cpp (limited to 'src/core/CL') diff --git a/src/core/CL/CLKernelLibrary.cpp b/src/core/CL/CLKernelLibrary.cpp index 6f45756c12..29fd672a96 100644 --- a/src/core/CL/CLKernelLibrary.cpp +++ b/src/core/CL/CLKernelLibrary.cpp @@ -153,6 +153,8 @@ const std::map CLKernelLibrary::_kernel_program_map = { "arithmetic_add", "arithmetic_op.cl" }, { "arithmetic_sub", "arithmetic_op.cl" }, { "arithmetic_div", "arithmetic_op.cl" }, + { "batch_to_space", "batch_to_space.cl" }, + { "batch_to_space_static", "batch_to_space.cl" }, { "batchnormalization_layer_nchw", "batchnormalization_layer.cl" }, { "batchnormalization_layer_nhwc", "batchnormalization_layer.cl" }, { "bitwise_or", "bitwise_op.cl" }, @@ -454,6 +456,10 @@ const std::map CLKernelLibrary::_program_source_map = { "arithmetic_op_quantized.cl", #include "./cl_kernels/arithmetic_op_quantized.clembed" + }, + { + "batch_to_space.cl", +#include "./cl_kernels/batch_to_space.clembed" }, { "bitwise_op.cl", diff --git a/src/core/CL/cl_kernels/batch_to_space.cl b/src/core/CL/cl_kernels/batch_to_space.cl new file mode 100644 index 0000000000..3043c2cf17 --- /dev/null +++ b/src/core/CL/cl_kernels/batch_to_space.cl @@ -0,0 +1,131 @@ +/* + * 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 withoutput restriction, including withoutput limitation the + * rights to use, copy, modify, merge, publish, distribute, sublicense, and/or + * sell copies of the Software, and to permit persons to whom the Software is + * furnished to do so, subject to the following conditions: + * + * The above copyright notice and this permission notice shall be included in all + * copies or substantial portions of the Software. + * + * THE SOFTWARE IS PROVIDED "AS IS", WITHOUT WARRANTY OF ANY KIND, EXPRESS OR + * IMPLIED, INCLUDING BUT NOT LIMITED TO THE WARRANTIES OF MERCHANTABILITY, + * FITNESS FOR A PARTICULAR PURPOSE AND NONINFRINGEMENT. IN NO EVENT SHALL THE + * AUTHORS OR COPYRIGHT HOLDERS BE LIABLE FOR ANY CLAIM, DAMAGES OR OTHER + * LIABILITY, WHETHER IN AN ACTION OF CONTRACT, TORT OR OTHERWISE, ARISING FROM, + * OUT OF OR IN CONNECTION WITH THE SOFTWARE OR THE USE OR OTHER DEALINGS IN THE + * SOFTWARE. + */ +#include "helpers.h" + +#if defined(DATA_TYPE) && defined(BATCH_SIZE) +/** Batch to space transformation. + * + * @note Datatype should be given as a preprocessor argument using -DDATA_TYPE=type. e.g. -DDATA_TYPE=float + * @note Datatype should be given as a preprocessor argument using -DDATA_TYPE=type. e.g. -DDATA_TYPE=float + * @note The input tensor batch size must be passed at compile time using -DBATCH_SIZE. e.g. -DBATCH_SIZE=2 + * + * @param[in] input_ptr Pointer to the source tensor. Supported data types: U8/S8/QASYMM8/U16/S16/F16/U32/S32/F32 + * @param[in] input_stride_x Stride of the source tensor in X dimension (in bytes) + * @param[in] input_step_x input_stride_x * number of elements along X processed per workitem(in bytes) + * @param[in] input_stride_y Stride of the source tensor in Y dimension (in bytes) + * @param[in] input_step_y input_stride_y * number of elements along Y processed per workitem(in bytes) + * @param[in] input_stride_z Stride of the source tensor in Z dimension (in bytes) + * @param[in] input_step_z input_stride_z * number of elements along Z processed per workitem(in bytes) + * @param[in] input_offset_first_element_in_bytes The offset of the first element in the first source tensor + * @param[in] batch_id The input tensor batch id + * @param[in] block_shape_ptr Pointer to the source tensor. Supported data types: S32 + * @param[in] block_shape_stride_x Stride of the source tensor in X dimension (in bytes) + * @param[in] block_shape_step_x block_shape_stride_x * number of elements along X processed per workitem(in bytes) + * @param[in] block_shape_stride_y Stride of the source tensor in Y dimension (in bytes) + * @param[in] block_shape_step_y block_shape_stride_y * number of elements along Y processed per workitem(in bytes) + * @param[in] input_offset_first_element_in_bytes The offset of the first element in the first source tensor + * @param[out] output_ptr Pointer to the destination tensor. Supported data types: same as @p input_ptr + * @param[in] output_stride_x Stride of the destination tensor in X dimension (in bytes) + * @param[in] output_step_x output_stride_x * number of elements along X processed per workitem(in bytes) + * @param[in] output_stride_y Stride of the destination tensor in Y dimension (in bytes) + * @param[in] output_step_y output_stride_y * number of elements along Y processed per workitem(in bytes) + * @param[in] output_stride_z Stride of the source tensor in Z dimension (in bytes) + * @param[in] output_step_z output_stride_z * number of elements along Z processed per workitem(in bytes) + * @param[in] output_offset_first_element_in_bytes The offset of the first element in the destination tensor + */ +__kernel void batch_to_space( + TENSOR3D_DECLARATION(input), + const int batch_id, + VECTOR_DECLARATION(block_shape), + TENSOR4D_DECLARATION(output)) +{ + Tensor3D in = CONVERT_TO_TENSOR3D_STRUCT(input); + Tensor4D out = CONVERT_TO_TENSOR4D_STRUCT_NO_STEP(output, 0); + Vector block = CONVERT_TO_VECTOR_STRUCT_NO_STEP(block_shape); + + const int block_x = *((__global int *)vector_offset(&block, 0)); + const int block_y = *((__global int *)vector_offset(&block, 1)); + + const int r = (BATCH_SIZE / (block_x * block_y)); + const int x = get_global_id(0); + const int y = get_global_id(1); + const int z = get_global_id(2); + const int w = batch_id % r; + + const int out_x = x * block_x + (batch_id / r) % block_x; + const int out_y = y * block_y + (batch_id / r) / block_x; + + *((__global DATA_TYPE *)tensor4D_offset(&out, out_x, out_y, z, w)) = *((__global DATA_TYPE *)in.ptr); +} +#endif // defined(DATA_TYPE) && defined(BATCH_SIZE) + +#if defined(DATA_TYPE) && defined(BATCH_SIZE) && defined(BLOCK_SHAPE_X) && defined(BLOCK_SHAPE_Y) +/** Batch to space transformation. + * + * @note Datatype should be given as a preprocessor argument using -DDATA_TYPE=type. e.g. -DDATA_TYPE=float + * @note The input tensor batch size must be passed at compile time using -DBATCH_SIZE. e.g. -DBATCH_SIZE=2 + * @note The block shape x must be passed at compile time using -DBLOCK_SHAPE_X. e.g. -DBLOCK_SHAPE_X=2 + * @note The block shape y must be passed at compile time using -DBLOCK_SHAPE_Y. e.g. -DBLOCK_SHAPE_Y=2 + * + * @param[in] input_ptr Pointer to the source tensor. Supported data types: U8/S8/QASYMM8/U16/S16/F16/U32/S32/F32 + * @param[in] input_stride_x Stride of the source tensor in X dimension (in bytes) + * @param[in] input_step_x input_stride_x * number of elements along X processed per workitem(in bytes) + * @param[in] input_stride_y Stride of the source tensor in Y dimension (in bytes) + * @param[in] input_step_y input_stride_y * number of elements along Y processed per workitem(in bytes) + * @param[in] input_stride_z Stride of the source tensor in Z dimension (in bytes) + * @param[in] input_step_z input_stride_z * number of elements along Z processed per workitem(in bytes) + * @param[in] input_offset_first_element_in_bytes The offset of the first element in the first source tensor + * @param[in] batch_id The input tensor batch id + * @param[out] output_ptr Pointer to the destination tensor. Supported data types: same as @p input_ptr + * @param[in] output_stride_x Stride of the destination tensor in X dimension (in bytes) + * @param[in] output_step_x output_stride_x * number of elements along X processed per workitem(in bytes) + * @param[in] output_stride_y Stride of the destination tensor in Y dimension (in bytes) + * @param[in] output_step_y output_stride_y * number of elements along Y processed per workitem(in bytes) + * @param[in] output_stride_z Stride of the source tensor in Z dimension (in bytes) + * @param[in] output_step_z output_stride_z * number of elements along Z processed per workitem(in bytes) + * @param[in] output_offset_first_element_in_bytes The offset of the first element in the destination tensor + */ +__kernel void batch_to_space_static( + TENSOR3D_DECLARATION(input), + const int batch_id, + TENSOR4D_DECLARATION(output)) +{ + Tensor3D in = CONVERT_TO_TENSOR3D_STRUCT(input); + Tensor4D out = CONVERT_TO_TENSOR4D_STRUCT_NO_STEP(output, 0); + + const int block_x = BLOCK_SHAPE_X; + const int block_y = BLOCK_SHAPE_Y; + + const int r = (BATCH_SIZE / (block_x * block_y)); + const int x = get_global_id(0); + const int y = get_global_id(1); + const int z = get_global_id(2); + const int w = batch_id % r; + + const int out_x = x * block_x + (batch_id / r) % block_x; + const int out_y = y * block_y + (batch_id / r) / block_x; + + *((__global DATA_TYPE *)tensor4D_offset(&out, out_x, out_y, z, w)) = *((__global DATA_TYPE *)in.ptr); +} +#endif // defined(DATA_TYPE) && defined(BATCH_SIZE) && defined(BLOCK_SHAPE_X) && defined(BLOCK_SHAPE_Y) \ No newline at end of file diff --git a/src/core/CL/kernels/CLBatchToSpaceLayerKernel.cpp b/src/core/CL/kernels/CLBatchToSpaceLayerKernel.cpp new file mode 100644 index 0000000000..e08d6f6ec5 --- /dev/null +++ b/src/core/CL/kernels/CLBatchToSpaceLayerKernel.cpp @@ -0,0 +1,172 @@ +/* + * 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/CLBatchToSpaceLayerKernel.h" + +#include "arm_compute/core/CL/CLHelpers.h" +#include "arm_compute/core/CL/CLValidate.h" +#include "arm_compute/core/CL/ICLTensor.h" +#include "arm_compute/core/utils/misc/ShapeCalculator.h" + +using namespace arm_compute::misc::shape_calculator; +namespace arm_compute +{ +namespace +{ +Status validate_arguments(const ITensorInfo *input, const ITensorInfo *block_info, const ITensorInfo *output) +{ + ARM_COMPUTE_RETURN_ERROR_ON_NULLPTR(input, block_info, output); + ARM_COMPUTE_RETURN_ERROR_ON_DATA_TYPE_CHANNEL_NOT_IN(block_info, 1, DataType::S32); + ARM_COMPUTE_RETURN_ERROR_ON(input->num_dimensions() > 4); + + // Validate output if initialized + if(output->total_size() != 0) + { + ARM_COMPUTE_RETURN_ERROR_ON(output->num_dimensions() > 4); + ARM_COMPUTE_RETURN_ERROR_ON_MISMATCHING_DATA_TYPES(input, output); + } + + return Status{}; +} +Status validate_arguments_static(const ITensorInfo *input, const int block_shape_x, const int block_shape_y, const ITensorInfo *output) +{ + ARM_COMPUTE_RETURN_ERROR_ON_NULLPTR(input, output); + ARM_COMPUTE_RETURN_ERROR_ON(input->num_dimensions() > 4); + ARM_COMPUTE_RETURN_ERROR_ON(block_shape_x <= 0); + ARM_COMPUTE_RETURN_ERROR_ON(block_shape_y <= 0); + + // Validate output if initialized + if(output->total_size() != 0) + { + ARM_COMPUTE_RETURN_ERROR_ON(input->tensor_shape()[0] != (block_shape_x * output->tensor_shape()[0])); + ARM_COMPUTE_RETURN_ERROR_ON(input->tensor_shape()[1] != (block_shape_x * output->tensor_shape()[1])); + ARM_COMPUTE_RETURN_ERROR_ON(input->tensor_shape()[2] != output->tensor_shape()[2]); + ARM_COMPUTE_RETURN_ERROR_ON(output->tensor_shape()[3] % (block_shape_x * block_shape_y) != 0); + ARM_COMPUTE_RETURN_ERROR_ON(output->num_dimensions() > 4); + ARM_COMPUTE_RETURN_ERROR_ON_MISMATCHING_DATA_TYPES(input, output); + } + + return Status{}; +} +} // namespace + +CLBatchToSpaceLayerKernel::CLBatchToSpaceLayerKernel() + : _input(nullptr), _block_shape(nullptr), _output(nullptr) +{ +} + +void CLBatchToSpaceLayerKernel::configure(const ICLTensor *input, const ICLTensor *block_shape, ICLTensor *output) +{ + ARM_COMPUTE_ERROR_ON_NULLPTR(input, output); + ARM_COMPUTE_ERROR_THROW_ON(validate_arguments(input->info(), block_shape->info(), output->info())); + + _input = input; + _block_shape = block_shape; + _output = output; + + // Create kernel + CLBuildOptions build_opts; + build_opts.add_option("-DDATA_TYPE=" + get_cl_type_from_data_type(input->info()->data_type())); + build_opts.add_option("-DBATCH_SIZE=" + support::cpp11::to_string(input->info()->dimension(3))); + build_opts.add_option("-DWIDTH_IN=" + support::cpp11::to_string(input->info()->dimension(0))); + _kernel = static_cast(CLKernelLibrary::get().create_kernel("batch_to_space", build_opts.options())); + + // Configure kernel window + Window win = calculate_max_window(*input->info(), Steps()); + ICLKernel::configure_internal(win); +} + +void CLBatchToSpaceLayerKernel::configure(const ICLTensor *input, const int32_t block_shape_x, const int32_t block_shape_y, ICLTensor *output) +{ + ARM_COMPUTE_ERROR_ON_NULLPTR(input, output); + + TensorShape output_shape = compute_batch_to_space_shape(input->info(), block_shape_x, block_shape_y); + auto_init_if_empty(*output->info(), output_shape, 1, input->info()->data_type()); + + ARM_COMPUTE_ERROR_THROW_ON(validate_arguments_static(input->info(), block_shape_x, block_shape_y, output->info())); + + _input = input; + _output = output; + + // Create kernel + CLBuildOptions build_opts; + build_opts.add_option("-DDATA_TYPE=" + get_cl_type_from_data_type(input->info()->data_type())); + build_opts.add_option("-DBATCH_SIZE=" + support::cpp11::to_string(input->info()->dimension(3))); + build_opts.add_option("-DBLOCK_SHAPE_X=" + support::cpp11::to_string(block_shape_x)); + build_opts.add_option("-DBLOCK_SHAPE_Y=" + support::cpp11::to_string(block_shape_y)); + build_opts.add_option("-DWIDTH_IN=" + support::cpp11::to_string(input->info()->dimension(0))); + _kernel = static_cast(CLKernelLibrary::get().create_kernel("batch_to_space_static", build_opts.options())); + + // Configure kernel window + Window win = calculate_max_window(*input->info(), Steps()); + ICLKernel::configure_internal(win); +} + +Status CLBatchToSpaceLayerKernel::validate(const ITensorInfo *input, const ITensorInfo *block_shape, const ITensorInfo *output) +{ + ARM_COMPUTE_RETURN_ERROR_ON_NULLPTR(input, block_shape, output); + ARM_COMPUTE_RETURN_ON_ERROR(validate_arguments(input, block_shape, output)); + return Status{}; +} + +Status CLBatchToSpaceLayerKernel::validate(const ITensorInfo *input, const int32_t block_shape_x, const int32_t block_shape_y, const ITensorInfo *output) +{ + ARM_COMPUTE_RETURN_ERROR_ON_NULLPTR(input, output); + ARM_COMPUTE_RETURN_ON_ERROR(validate_arguments_static(input, block_shape_x, block_shape_y, output)); + return Status{}; +} + +void CLBatchToSpaceLayerKernel::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_in = window.first_slice_window_3D(); + Window slice_out = window.first_slice_window_4D(); + + Window vector_slice = window.first_slice_window_1D(); + vector_slice.set(Window::DimX, Window::Dimension(0, 0, 0)); + + slice_out.set(Window::DimX, Window::Dimension(0, 0, 0)); + slice_out.set(Window::DimY, Window::Dimension(0, 0, 0)); + slice_out.set(Window::DimZ, Window::Dimension(0, 0, 0)); + slice_out.set(3, Window::Dimension(0, 0, 0)); + + int batch_id = 0; + do + { + unsigned int idx = 0; + add_3D_tensor_argument(idx, _input, slice_in); + add_argument(idx, batch_id); + if(_block_shape != nullptr) + { + add_1D_tensor_argument(idx, _block_shape, vector_slice); + } + add_4D_tensor_argument(idx, _output, slice_out); + enqueue(queue, *this, slice_in); + + ++batch_id; + } + while(window.slide_window_slice_3D(slice_in)); +} +} // namespace arm_compute -- cgit v1.2.1