From 16934a511ccd37a28000a9fabb3e6e5fc6f51ec9 Mon Sep 17 00:00:00 2001 From: Michalis Spyrou Date: Tue, 21 Aug 2018 18:03:58 +0100 Subject: COMPMID-1227 Implementing Space to Batch on OpenCL Change-Id: I6fd83d6584c56a4fd2470948f1987e23237c16d3 Reviewed-on: https://eu-gerrit-1.euhpc.arm.com/145577 Reviewed-by: Georgios Pinitas Tested-by: bsgcomp --- src/core/CL/CLKernelLibrary.cpp | 6 + src/core/CL/cl_kernels/space_to_batch.cl | 151 ++++++++++++++++++ src/core/CL/kernels/CLSpaceToBatchLayerKernel.cpp | 182 ++++++++++++++++++++++ src/runtime/CL/functions/CLSpaceToBatchLayer.cpp | 98 ++++++++++++ 4 files changed, 437 insertions(+) create mode 100644 src/core/CL/cl_kernels/space_to_batch.cl create mode 100644 src/core/CL/kernels/CLSpaceToBatchLayerKernel.cpp create mode 100644 src/runtime/CL/functions/CLSpaceToBatchLayer.cpp (limited to 'src') diff --git a/src/core/CL/CLKernelLibrary.cpp b/src/core/CL/CLKernelLibrary.cpp index 75ff2482c8..ef3a431f1a 100644 --- a/src/core/CL/CLKernelLibrary.cpp +++ b/src/core/CL/CLKernelLibrary.cpp @@ -364,6 +364,8 @@ const std::map CLKernelLibrary::_kernel_program_map = { "softmax_layer_max_shift_exp_sum_quantized_serial", "softmax_layer_quantized.cl" }, { "softmax_layer_max_shift_exp_sum_quantized_parallel", "softmax_layer_quantized.cl" }, { "softmax_layer_max_shift_exp_sum_serial", "softmax_layer.cl" }, + { "space_to_batch", "space_to_batch.cl" }, + { "space_to_batch_static", "space_to_batch.cl" }, { "softmax_layer_max_shift_exp_sum_parallel", "softmax_layer.cl" }, { "strided_slice", "slice_ops.cl" }, { "suppress_non_maximum", "canny.cl" }, @@ -758,6 +760,10 @@ const std::map CLKernelLibrary::_program_source_map = { "slice_ops.cl", #include "./cl_kernels/slice_ops.clembed" + }, + { + "space_to_batch.cl", +#include "./cl_kernels/space_to_batch.clembed" }, { "tablelookup.cl", diff --git a/src/core/CL/cl_kernels/space_to_batch.cl b/src/core/CL/cl_kernels/space_to_batch.cl new file mode 100644 index 0000000000..1343695ed1 --- /dev/null +++ b/src/core/CL/cl_kernels/space_to_batch.cl @@ -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 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 KOUTD, EXPRESS OR + * IMPLIED, OUTCLUDOUTG BUT NOT LIMITED TO THE WARRANTIES OF MERCHANTABILITY, + * FITNESS FOR A PARTICULAR PURPOSE AND NONOUTFROUTGEMENT. OUT NO EVENT SHALL THE + * AUTHORS OR COPYRIGHT HOLDERS BE LIABLE FOR ANY CLAIM, DAMAGES OR OTHER + * LIABILITY, WHETHER OUT AN ACTION OF CONTRACT, TORT OR OTHERWISE, ARISOUTG FROM, + * OUT OF OR OUT CONNECTION WITH THE SOFTWARE OR THE USE OR OTHER DEALOUTGS OUT THE + * SOFTWARE. + */ +#include "helpers.h" + +#if defined(BATCH_SIZE) && defined(DATA_TYPE) +/** Calculate the space to batch conversion. + * + * @note Datatype should be given as a preprocessor argument using -DDATA_TYPE=type. e.g. -DDATA_TYPE=float + * @note The block shape tensor rank must be passed at compile time using -DBLOCK_SHAPE_DIM. e.g. -DBLOCK_SHAPE_DIM=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 image 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 image + * @param[in] paddings_ptr Pointer to the second source image. Supported data types: S32 + * @param[in] paddings_stride_x Stride of the paddinds tensor in X dimension (in bytes) + * @param[in] paddings_step_x paddings_stride_x * number of elements along X processed per workitem(in bytes) + * @param[in] paddings_stride_y Stride of the paddinds tensor in Y dimension (in bytes) + * @param[in] paddings_step_y paddings_stride_y * number of elements along Y processed per workitem(in bytes) + * @param[in] paddingse_offset_first_element_in_bytes The offset of the first element in the second source image + * @param[in] block_shape_ptr Pointer to the block shape tensor. Supported data types: S32 + * @param[in] block_shape_stride_x Stride of the block shape 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 block shape 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] block_shape_offset_first_element_in_bytes The offset of the first element in the block shapetensor + * @param[in] batch_id The output 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 destination 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 image + */ +__kernel void space_to_batch( + TENSOR4D_DECLARATION(input), + IMAGE_DECLARATION(paddings), + VECTOR_DECLARATION(block_shape), + const int batch_id, + TENSOR3D_DECLARATION(output)) +{ + Tensor4D in = CONVERT_TO_TENSOR4D_STRUCT_NO_STEP(input, 0); + Image pad = CONVERT_TO_IMAGE_STRUCT_NO_STEP(paddings); + Vector block = CONVERT_TO_VECTOR_STRUCT_NO_STEP(block_shape); + Tensor3D out = CONVERT_TO_TENSOR3D_STRUCT(output); + + const int PAD_LEFT_X = *((__global int *)offset(&pad, 0, 0)); + const int PAD_RIGHT_X = *((__global int *)offset(&pad, 1, 0)); + const int PAD_LEFT_Y = *((__global int *)offset(&pad, 0, 1)); + const int PAD_RIGHT_Y = *((__global int *)offset(&pad, 1, 1)); + + int block_x = *((__global int *)vector_offset(&block, 0)); + int block_y = *((__global int *)vector_offset(&block, 1)); + + const int out_x = get_global_id(0); + const int out_y = get_global_id(1); + const int z = get_global_id(2); + + if((out_x >= PAD_LEFT_X && out_x < WIDTH_OUT - PAD_RIGHT_X) && (out_y >= PAD_LEFT_Y && out_y < HEIGHT_OUT - PAD_RIGHT_Y)) + { + const int r = (BATCH_SIZE / (block_x * block_y)); + const int w = batch_id % r; + const int in_x = (out_x - PAD_LEFT_X) * block_x + (batch_id / r) % block_x; + const int in_y = (out_y - PAD_LEFT_Y) * block_y + (batch_id / r) / block_x; + *((__global DATA_TYPE *)out.ptr) = *((__global DATA_TYPE *)tensor4D_offset(&in, in_x, in_y, z, w)); + } +} +#endif // defined(BATCH_SIZE) && defined(DATA_TYPE) + +#if defined(BATCH_SIZE) && defined(DATA_TYPE) && defined(BLOCK_SHAPE_X) && defined(BLOCK_SHAPE_Y) && defined(PAD_LEFT_X) && defined(PAD_RIGHT_X) && defined(PAD_LEFT_Y) && defined(PAD_RIGHT_Y) +/** Calculate the space to batch conversion. + * + * @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 + * @note The starting pad value of x must be passed at compile time using -DPAD_LEFT_X. e.g. -DPAD_LEFT_X=2 + * @note The ending pad value of x must be passed at compile time using -DPAD_RIGHT_X. e.g. -DPAD_RIGHT_X=2 + * @note The starting pad value of y must be passed at compile time using -DPAD_LEFT_Y. e.g. -DPAD_LEFT_Y=2 + * @note The ending pad value of y must be passed at compile time using -DPAD_RIGHT_Y. e.g. -DPAD_RIGHT_X=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 image 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 image + * @param[in] batch_id The output 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 image + */ +__kernel void space_to_batch_static( + TENSOR4D_DECLARATION(input), + const int batch_id, + TENSOR3D_DECLARATION(output)) +{ + Tensor4D in = CONVERT_TO_TENSOR4D_STRUCT_NO_STEP(input, 0); + Tensor3D out = CONVERT_TO_TENSOR3D_STRUCT(output); + + int block_x = BLOCK_SHAPE_X; + int block_y = *((__global int *)vector_offset(&block, 1)); + + const int out_x = get_global_id(0); + const int out_y = get_global_id(1); + const int z = get_global_id(2); + + if((out_x >= PAD_LEFT_X && out_x < WIDTH_OUT - PAD_RIGHT_X) && (out_y >= PAD_LEFT_Y && out_y < HEIGHT_OUT - PAD_RIGHT_Y)) + { + const int r = (BATCH_SIZE / (block_x * block_y)); + const int w = batch_id % r; + const int in_x = (out_x - PAD_LEFT_X) * block_x + (batch_id / r) % block_x; + const int in_y = (out_y - PAD_LEFT_Y) * block_y + (batch_id / r) / block_x; + *((__global DATA_TYPE *)out.ptr) = *((__global DATA_TYPE *)tensor4D_offset(&in, in_x, in_y, z, w)); + } +} +#endif // defined(BATCH_SIZE) && defined(DATA_TYPE) && defined(BLOCK_SHAPE_X) && defined(BLOCK_SHAPE_Y) && defined(PAD_LEFT_X) && defined(PAD_RIGHT_X) && defined(PAD_LEFT_Y) && defined(PAD_RIGHT_Y) diff --git a/src/core/CL/kernels/CLSpaceToBatchLayerKernel.cpp b/src/core/CL/kernels/CLSpaceToBatchLayerKernel.cpp new file mode 100644 index 0000000000..cda6e96806 --- /dev/null +++ b/src/core/CL/kernels/CLSpaceToBatchLayerKernel.cpp @@ -0,0 +1,182 @@ +/* + * 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/CLSpaceToBatchLayerKernel.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 *padddings, const ITensorInfo *output) +{ + ARM_COMPUTE_RETURN_ERROR_ON_NULLPTR(input, block_info, padddings, 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_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 Size2D &padding_left, const Size2D &padding_right, + const ITensorInfo *output) +{ + ARM_COMPUTE_RETURN_ERROR_ON_NULLPTR(input, output); + ARM_COMPUTE_RETURN_ERROR_ON(block_shape_x < 1 || block_shape_y < 1); + ARM_COMPUTE_RETURN_ERROR_ON(input->num_dimensions() > 4); + + // Validate output if initialized + if(output->total_size() != 0) + { + ARM_COMPUTE_RETURN_ERROR_ON(output->tensor_shape()[0] < padding_left.x() + padding_right.y()); + ARM_COMPUTE_RETURN_ERROR_ON(input->tensor_shape()[0] / block_shape_x != (output->tensor_shape()[0] - padding_left.x() - padding_right.y())); + ARM_COMPUTE_RETURN_ERROR_ON(input->tensor_shape()[1] / block_shape_y != (output->tensor_shape()[1] - padding_left.x() - padding_right.y())); + 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_MISMATCHING_DATA_TYPES(input, output); + } + + return Status{}; +} +} // namespace + +CLSpaceToBatchLayerKernel::CLSpaceToBatchLayerKernel() + : _input(nullptr), _block_shape(nullptr), _paddings(nullptr), _output(nullptr) +{ +} + +void CLSpaceToBatchLayerKernel::configure(const ICLTensor *input, const ICLTensor *block_shape, const ICLTensor *paddings, ICLTensor *output) +{ + ARM_COMPUTE_ERROR_ON_NULLPTR(input, output); + ARM_COMPUTE_ERROR_THROW_ON(validate_arguments(input->info(), block_shape->info(), paddings->info(), output->info())); + + _input = input; + _block_shape = block_shape; + _paddings = paddings; + _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("-DWIDTH_OUT=" + support::cpp11::to_string(output->info()->dimension(0))); + build_opts.add_option("-DHEIGHT_OUT=" + support::cpp11::to_string(output->info()->dimension(1))); + build_opts.add_option("-DBATCH_SIZE=" + support::cpp11::to_string(output->info()->dimension(3))); + _kernel = static_cast(CLKernelLibrary::get().create_kernel("space_to_batch", build_opts.options())); + + // Configure kernel window + Window win = calculate_max_window(*output->info(), Steps()); + ICLKernel::configure_internal(win); +} + +void CLSpaceToBatchLayerKernel::configure(const ICLTensor *input, const int block_shape_x, const int block_shape_y, const Size2D &padding_left, const Size2D &padding_right, + ICLTensor *output) +{ + ARM_COMPUTE_ERROR_ON_NULLPTR(input, output); + + TensorShape output_shape = misc::shape_calculator::compute_space_to_batch_shape(input->info(), block_shape_x, block_shape_y, padding_left, padding_right); + 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, padding_left, padding_right, 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("-DWIDTH_OUT=" + support::cpp11::to_string(output->info()->dimension(0))); + build_opts.add_option("-DHEIGHT_OUT=" + support::cpp11::to_string(output->info()->dimension(1))); + build_opts.add_option("-DBATCH_SIZE=" + support::cpp11::to_string(output->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("-DPAD_START_X=" + support::cpp11::to_string(padding_left.x())); + build_opts.add_option("-DPAD_END_X=" + support::cpp11::to_string(padding_right.x())); + build_opts.add_option("-DPAD_START_Y=" + support::cpp11::to_string(padding_left.y())); + build_opts.add_option("-DPAD_END_Y=" + support::cpp11::to_string(padding_right.y())); + _kernel = static_cast(CLKernelLibrary::get().create_kernel("space_to_batch_static", build_opts.options())); + + // Configure kernel window + Window win = calculate_max_window(*output->info(), Steps()); + ICLKernel::configure_internal(win); +} + +Status CLSpaceToBatchLayerKernel::validate(const ITensorInfo *input, const ITensorInfo *block_shape, const ITensorInfo *paddings, const ITensorInfo *output) +{ + ARM_COMPUTE_RETURN_ON_ERROR(validate_arguments(input, block_shape, paddings, output)); + return Status{}; +} +Status CLSpaceToBatchLayerKernel::validate(const ITensorInfo *input, const int block_shape_x, const int block_shape_y, const Size2D &padding_left, const Size2D &padding_right, + const ITensorInfo *output) +{ + ARM_COMPUTE_RETURN_ON_ERROR(validate_arguments_static(input, block_shape_x, block_shape_y, padding_left, padding_right, output)); + return Status{}; +} + +void CLSpaceToBatchLayerKernel::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_out = window.first_slice_window_3D(); + + Window slice_in = window.first_slice_window_4D(); + slice_in.set(Window::DimX, Window::Dimension(0, 0, 0)); + slice_in.set(Window::DimY, Window::Dimension(0, 0, 0)); + slice_in.set(Window::DimZ, Window::Dimension(0, 0, 0)); + slice_in.set(3, Window::Dimension(0, 0, 0)); + + Window vector_slice = window.first_slice_window_1D(); + vector_slice.set(Window::DimX, Window::Dimension(0, 0, 0)); + + Window padding_slice = window.first_slice_window_2D(); + padding_slice.set(Window::DimX, Window::Dimension(0, 0, 0)); + padding_slice.set(Window::DimY, Window::Dimension(0, 0, 0)); + + int batch_id = 0; + do + { + unsigned int idx = 0; + add_4D_tensor_argument(idx, _input, slice_in); + if(_paddings != nullptr && _block_shape != nullptr) + { + add_2D_tensor_argument(idx, _paddings, padding_slice); + add_1D_tensor_argument(idx, _block_shape, vector_slice); + } + add_argument(idx, batch_id); + add_3D_tensor_argument(idx, _output, slice_out); + enqueue(queue, *this, slice_out); + ++batch_id; + } + while(window.slide_window_slice_3D(slice_out)); +} +} // namespace arm_compute \ No newline at end of file diff --git a/src/runtime/CL/functions/CLSpaceToBatchLayer.cpp b/src/runtime/CL/functions/CLSpaceToBatchLayer.cpp new file mode 100644 index 0000000000..76c1e188e6 --- /dev/null +++ b/src/runtime/CL/functions/CLSpaceToBatchLayer.cpp @@ -0,0 +1,98 @@ +/* + * 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/runtime/CL/functions/CLSpaceToBatchLayer.h" + +#include "arm_compute/core/Error.h" +#include "arm_compute/core/TensorInfo.h" +#include "arm_compute/core/Types.h" +#include "arm_compute/core/Validate.h" +#include "arm_compute/runtime/CL/CLScheduler.h" + +namespace arm_compute +{ +CLSpaceToBatchLayer::CLSpaceToBatchLayer() + : _space_to_batch_kernel(), _output(nullptr), _has_padding(false) +{ +} + +void CLSpaceToBatchLayer::configure(const ICLTensor *input, const ICLTensor *block_shape, const ICLTensor *paddings, ICLTensor *output) +{ + ARM_COMPUTE_ERROR_ON_NULLPTR(input, output); + + if(input->info()->tensor_shape().total_size() != output->info()->tensor_shape().total_size()) + { + _has_padding = true; + } + + _output = output; + _space_to_batch_kernel.configure(input, block_shape, paddings, output); +} + +void CLSpaceToBatchLayer::configure(const ICLTensor *input, const int block_shape_x, const int block_shape_y, const Size2D &padding_left, const Size2D &padding_right, ICLTensor *output) +{ + ARM_COMPUTE_ERROR_ON_NULLPTR(input, output); + + if(input->info()->tensor_shape().total_size() != output->info()->tensor_shape().total_size()) + { + _has_padding = true; + } + + _output = output; + _space_to_batch_kernel.configure(input, block_shape_x, block_shape_y, padding_left, padding_right, output); +} + +Status CLSpaceToBatchLayer::validate(const ITensorInfo *input, const ITensorInfo *block_shape, const ITensorInfo *paddings, const ITensorInfo *output) +{ + return CLSpaceToBatchLayerKernel::validate(input, block_shape, paddings, output); +} + +Status CLSpaceToBatchLayer::validate(const ITensorInfo *input, const int block_shape_x, const int block_shape_y, const Size2D &padding_left, const Size2D &padding_right, + const ITensorInfo *output) +{ + return CLSpaceToBatchLayerKernel::validate(input, block_shape_x, block_shape_y, padding_left, padding_right, output); +} + +void CLSpaceToBatchLayer::run() +{ + // Zero out output only if we have paddings + // TODO(micspy01): replace with memset once ready + if(_has_padding) + { + _output->map(CLScheduler::get().queue(), true); + if(is_data_type_quantized_asymmetric(_output->info()->data_type())) + { + const uint8_t quantized_zero = _output->info()->quantization_info().offset; + std::fill_n(_output->buffer(), _output->info()->total_size(), quantized_zero); + } + else + { + memset(_output->buffer(), 0, _output->info()->total_size()); + } + _output->unmap(CLScheduler::get().queue()); + } + + CLScheduler::get().enqueue(_space_to_batch_kernel, true); +} +} // namespace arm_compute -- cgit v1.2.1