From ceaa0bfe219631b5a4e638613f90f9fa47a3defe Mon Sep 17 00:00:00 2001 From: Manuel Bottini Date: Tue, 16 Feb 2021 15:15:19 +0000 Subject: Remove OpenGL ES support Remove the following: - Relevant backend kernels - Relevant backend functions - Relevant backend validation tests - Relevant backend specific examples - Remove backend support from Graph API - Remove backend support from build system Update documentation Resolves: COMPMID-4149 Change-Id: Id0621d6ee35169754de458103907aaba4ef770c0 Signed-off-by: Manuel Bottini Reviewed-on: https://review.mlplatform.org/c/ml/ComputeLibrary/+/5097 Tested-by: Arm Jenkins Reviewed-by: Michele Di Giorgio Reviewed-by: Georgios Pinitas --- .../GLES_COMPUTE/kernels/GCPoolingLayerKernel.cpp | 374 --------------------- 1 file changed, 374 deletions(-) delete mode 100644 src/core/GLES_COMPUTE/kernels/GCPoolingLayerKernel.cpp (limited to 'src/core/GLES_COMPUTE/kernels/GCPoolingLayerKernel.cpp') diff --git a/src/core/GLES_COMPUTE/kernels/GCPoolingLayerKernel.cpp b/src/core/GLES_COMPUTE/kernels/GCPoolingLayerKernel.cpp deleted file mode 100644 index 13efd10532..0000000000 --- a/src/core/GLES_COMPUTE/kernels/GCPoolingLayerKernel.cpp +++ /dev/null @@ -1,374 +0,0 @@ -/* - * Copyright (c) 2017-2020 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/GLES_COMPUTE/kernels/GCPoolingLayerKernel.h" - -#include "arm_compute/core/GLES_COMPUTE/GCHelpers.h" -#include "arm_compute/core/GLES_COMPUTE/GCKernelLibrary.h" -#include "arm_compute/core/GLES_COMPUTE/IGCTensor.h" -#include "arm_compute/core/GLES_COMPUTE/OpenGLES.h" -#include "arm_compute/core/Helpers.h" -#include "arm_compute/core/TensorInfo.h" -#include "arm_compute/core/Utils.h" -#include "arm_compute/core/Validate.h" -#include "arm_compute/core/Window.h" -#include "src/core/AccessWindowStatic.h" -#include "src/core/helpers/AutoConfiguration.h" -#include "src/core/helpers/WindowHelpers.h" -#include "support/StringSupport.h" - -#include -#include -#include - -using namespace arm_compute; - -namespace -{ -// Internal window config info -using GCPoolingConfig = std::pair; //num_elems_processed_per_iteration, border_size - -void auto_init(const ITensorInfo *input, ITensorInfo *output, unsigned int pooled_w, unsigned int pooled_h) -{ - TensorShape output_shape{ input->tensor_shape() }; - output_shape.set(0, pooled_w); - output_shape.set(1, pooled_h); - - auto_init_if_empty(*output, input->clone()->set_tensor_shape(output_shape)); -} - -Status validate_arguments(const ITensorInfo *input, const ITensorInfo *output, const PoolingLayerInfo &pool_info, const ITensorInfo *indices) -{ - ARM_COMPUTE_RETURN_ERROR_ON_NULLPTR(input, output); - ARM_COMPUTE_RETURN_ERROR_ON_MSG(indices, "Indices not supported in GLES backend"); - ARM_COMPUTE_RETURN_ERROR_ON_DATA_TYPE_CHANNEL_NOT_IN(input, 1, DataType::F16, DataType::F32); - ARM_COMPUTE_RETURN_ERROR_ON_MSG((is_data_type_quantized_asymmetric(input->data_type()) && pool_info.pool_type == PoolingType::L2), - "Unsupported combination of parameters!"); - ARM_COMPUTE_RETURN_ERROR_ON(!pool_info.pad_stride_info.padding_is_symmetric()); - - const bool is_global_pooling = pool_info.is_global_pooling; - const unsigned int pool_size = is_global_pooling ? input->tensor_shape().x() : pool_info.pool_size.width; - - ARM_COMPUTE_RETURN_ERROR_ON_MSG(is_global_pooling && (input->tensor_shape().x() != input->tensor_shape().y()), - "Global pooling is supported only with rectangular inputs!"); - ARM_COMPUTE_RETURN_ERROR_ON_MSG(!is_global_pooling && ((pool_info.pad_stride_info.pad().first >= pool_size) || (pool_info.pad_stride_info.pad().second >= pool_size)), - "Invalid pool size and pool pad combination!"); - ARM_COMPUTE_RETURN_ERROR_ON_MSG(pool_info.pool_size.width != pool_info.pool_size.height, "Invalid Pool size, width not equal to height!"); - - // Checks performed when output is configured - if(output->total_size() != 0) - { - ARM_COMPUTE_RETURN_ERROR_ON_MISMATCHING_DATA_TYPES(input, output); - - unsigned int pooled_w = 0; - unsigned int pooled_h = 0; - std::tie(pooled_w, pooled_h) = scaled_dimensions(input->dimension(0), - input->dimension(1), - pool_size, - pool_size, - pool_info.pad_stride_info); - ARM_COMPUTE_RETURN_ERROR_ON_MSG((output->dimension(0) != pooled_w) || (output->dimension(1) != pooled_h), - "Invalid output pooling dimensions!"); - } - - return Status{}; -} - -std::tuple validate_and_configure_window(ITensorInfo *input, ITensorInfo *output, const PoolingLayerInfo &pool_info) -{ - int pool_pad_x = 0; - int pool_pad_y = 0; - int pool_stride_x = 0; - int pool_stride_y = 0; - unsigned int pooled_w = 0; - unsigned int pooled_h = 0; - int pool_size = pool_info.pool_size.width; - const PadStrideInfo pad_stride_info = pool_info.pad_stride_info; - std::tie(pool_pad_x, pool_pad_y) = pad_stride_info.pad(); - std::tie(pool_stride_x, pool_stride_y) = pad_stride_info.stride(); - - ARM_COMPUTE_ERROR_ON_NULLPTR(input, output); - - // Update pool size in case of global pooling - pool_size = pool_info.is_global_pooling ? input->dimension(0) : pool_size; - - // Check output dimensions - std::tie(pooled_w, pooled_h) = scaled_dimensions(input->dimension(0), - input->dimension(1), - pool_size, - pool_size, - pad_stride_info); - - auto_init(input, output, pooled_w, pooled_h); - - BorderSize border_size = BorderSize(pool_pad_y, pool_pad_x); - - const int input_width = input->dimension(0); - const int input_height = input->dimension(1); - - unsigned int num_elems_processed_per_iteration = 1; - - // Create kernel - if(pool_size == 3) - { - // Check if we have pool3x3 with stride_x less equal than 3. In these cases, run an optimized OpenGLES kernel where - // each thread computes 4 output elements - const bool is_pool3x3_stride_le3 = (pool_size == 3) && (pool_stride_x <= 3); - - int num_elems_read_per_iteration = pool_size; - - if(input->data_type() == DataType::F32) - { - if(is_pool3x3_stride_le3) - { - // Change the number of elements processed and number of elements read per iteration for pooling 3x3 with stride less equal than 3 - num_elems_processed_per_iteration = 4; - num_elems_read_per_iteration = pool_size * (pool_stride_x + 1); - } - } - else - { - if(is_pool3x3_stride_le3) - { - num_elems_processed_per_iteration = 4; - } - else - { - num_elems_processed_per_iteration = 2; - } - } - - const int upper_bound_w = ((pooled_w - 1) * pool_stride_x - pool_pad_x + num_elems_read_per_iteration) - input_width; - const int upper_bound_h = ((pooled_h - 1) * pool_stride_y - pool_pad_y + pool_size) - input_height; - - border_size.right = std::max(upper_bound_w, pool_pad_x); - border_size.bottom = std::max(upper_bound_h, pool_pad_y); - } - else // Run general case - { - if(input->data_type() == DataType::F32) - { - num_elems_processed_per_iteration = 1; - } - else - { - num_elems_processed_per_iteration = 2; - } - - const int upper_bound_w = ((pooled_w - 1) * pool_stride_x - pool_pad_x + pool_size) - input_width; - const int upper_bound_h = ((pooled_h - 1) * pool_stride_y - pool_pad_y + pool_size) - input_height; - - border_size.right = std::max(upper_bound_w, pool_pad_x); - border_size.bottom = std::max(upper_bound_h, pool_pad_y); - } - // Configure kernel window - Window win = calculate_max_window(*output, Steps(num_elems_processed_per_iteration)); - - if(input->data_type() == DataType::F32) - { - AccessWindowStatic input_access(input, -pool_pad_x, -pool_pad_y, input_width + border_size.right, input_height + border_size.bottom); - AccessWindowHorizontal output_access(output, 0, num_elems_processed_per_iteration); - bool window_changed = update_window_and_padding(win, input_access, output_access); - output_access.set_valid_region(win, ValidRegion(Coordinates(), output->tensor_shape())); - Status err = (window_changed) ? ARM_COMPUTE_CREATE_ERROR(ErrorCode::RUNTIME_ERROR, "Insufficient Padding!") : Status{}; - return std::make_tuple(err, win, GCPoolingConfig(num_elems_processed_per_iteration, border_size)); - } - else - { - // Calculate output right and bottom border - const int output_width = output->dimension(0); - const int output_height = output->dimension(1); - const int output_padding_right = ceil_to_multiple(output_width, num_elems_processed_per_iteration) - output_width; - const int output_padding_bottom = ceil_to_multiple(output_height, 1) - output_height; - - const int input_total_width = std::max(int(input->padding().left), int(pool_pad_x)) + input_width + std::max(int(input->padding().right), int(pool_pad_x)); - const int input_padding_right = ceil_to_multiple(input_total_width, num_elems_processed_per_iteration) - input_width - pool_pad_x; - const int input_total_height = std::max(int(input->padding().top), int(pool_pad_y)) + input_height + std::max(int(input->padding().bottom), int(pool_pad_y)); - const int input_padding_bottom = input_total_height - input_height - pool_pad_y; - - // Configure kernel window - AccessWindowStatic input_access(input, -pool_pad_x, -pool_pad_y, input_width + input_padding_right, input_height + input_padding_bottom); - AccessWindowStatic output_access(output, 0, 0, output_width + output_padding_right, output_height + output_padding_bottom); - bool window_changed = update_window_and_padding(win, input_access, output_access); - output_access.set_valid_region(win, ValidRegion(Coordinates(), output->tensor_shape())); - Status err = (window_changed) ? ARM_COMPUTE_CREATE_ERROR(ErrorCode::RUNTIME_ERROR, "Insufficient Padding!") : Status{}; - return std::make_tuple(err, win, GCPoolingConfig(num_elems_processed_per_iteration, border_size)); - } -} -} // namespace - -GCPoolingLayerKernel::GCPoolingLayerKernel() - : _input(nullptr), _output(nullptr), _indices(nullptr), _pool_info(), _border_size(0), _num_elems_processed_per_iteration(1) -{ -} - -BorderSize GCPoolingLayerKernel::border_size() const -{ - return _border_size; -} - -void GCPoolingLayerKernel::configure(const IGCTensor *input, IGCTensor *output, const PoolingLayerInfo &pool_info, IGCTensor *indices) -{ - int pool_pad_x = 0; - int pool_pad_y = 0; - int pool_stride_x = 0; - int pool_stride_y = 0; - unsigned int pooled_w = 0; - unsigned int pooled_h = 0; - const PoolingType pool_type = pool_info.pool_type; - int pool_size = pool_info.pool_size.width; - const PadStrideInfo pad_stride_info = pool_info.pad_stride_info; - const bool exclude_padding = pool_info.exclude_padding; - std::tie(pool_pad_x, pool_pad_y) = pad_stride_info.pad(); - std::tie(pool_stride_x, pool_stride_y) = pad_stride_info.stride(); - - ARM_COMPUTE_ERROR_ON_NULLPTR(input, output); - - // Update pool size in case of global pooling - pool_size = pool_info.is_global_pooling ? input->info()->dimension(0) : pool_size; - - // Check output dimensions - std::tie(pooled_w, pooled_h) = scaled_dimensions(input->info()->dimension(0), - input->info()->dimension(1), - pool_size, - pool_size, - pad_stride_info); - - auto_init(input->info(), output->info(), pooled_w, pooled_h); - - ARM_COMPUTE_ERROR_THROW_ON(validate_arguments(input->info(), output->info(), pool_info, (indices) ? indices->info() : nullptr)); - - // Set instance variables - _input = input; - _output = output; - _pool_info = pool_info; - _indices = indices; - // Set build options - std::set build_opts; - build_opts.emplace("#define LOCAL_SIZE_X " + support::cpp11::to_string(1)); - build_opts.emplace("#define LOCAL_SIZE_Y " + support::cpp11::to_string(1)); - build_opts.emplace("#define LOCAL_SIZE_Z " + support::cpp11::to_string(1)); - if(input->info()->data_type() == DataType::F32) - { - build_opts.insert("#define DATA_TYPE_FP32"); - } - else - { - build_opts.insert("#define DATA_TYPE_FP16"); - } - if(exclude_padding) - { - build_opts.emplace("#define EXCLUDE_PADDING"); - } - build_opts.emplace(("#define POOL_" + string_from_pooling_type(pool_type))); - build_opts.emplace(("#define STRIDE_X " + support::cpp11::to_string(pool_stride_x))); - build_opts.emplace(("#define MAX_WIDTH " + support::cpp11::to_string(input->info()->dimension(0) + (exclude_padding ? 0 : pool_pad_x)))); - build_opts.emplace(("#define MAX_HEIGHT " + support::cpp11::to_string(input->info()->dimension(1) + (exclude_padding ? 0 : pool_pad_y)))); - build_opts.emplace(("#define STRIDE_Y " + support::cpp11::to_string(pool_stride_y))); - build_opts.emplace(("#define PAD_X " + support::cpp11::to_string(pool_pad_x))); - build_opts.emplace(("#define PAD_Y " + support::cpp11::to_string(pool_pad_y))); - - // Create kernel - if((pool_size == 2) || (pool_size == 3) || (pool_size == 7)) - { - // Check if we have pool3x3 with stride_x less equal than 3. In these cases, run an optimized OpenGLES kernel where - // each thread computes 4 output elements - const bool is_pool3x3_stride_le3 = (pool_size == 3) && (pool_stride_x <= 3); - - std::string kernel_name = "pooling_layer_" + support::cpp11::to_string(pool_size); - if(is_pool3x3_stride_le3) - { - build_opts.insert("#define POOLING_LAYER_3_OPTIMIZED"); - _kernel = static_cast(GCKernelLibrary::get().create_kernel(kernel_name + "_optimized", build_opts)); - } - else - { - build_opts.insert("#define POOLING_LAYER_" + support::cpp11::to_string(pool_size)); - _kernel = static_cast(GCKernelLibrary::get().create_kernel(kernel_name, build_opts)); - } - } - else // Run general case - { - build_opts.emplace(("#define POOL_SIZE " + support::cpp11::to_string(pool_size))); - - build_opts.insert("#define POOLING_LAYER_N"); - _kernel = static_cast(GCKernelLibrary::get().create_kernel("pooling_layer_n", build_opts)); - } - // Configure kernel window - auto win_config = validate_and_configure_window(input->info(), output->info(), pool_info); - ARM_COMPUTE_ERROR_THROW_ON(std::get<0>(win_config)); - - IGCKernel::configure(std::get<1>(win_config)); - GCPoolingConfig pooling_config = std::get<2>(win_config); - _num_elems_processed_per_iteration = pooling_config.first; - _border_size = pooling_config.second; -} - -Status GCPoolingLayerKernel::validate(const ITensorInfo *input, const ITensorInfo *output, const PoolingLayerInfo &pool_info, const ITensorInfo *indices) -{ - ARM_COMPUTE_RETURN_ON_ERROR(validate_arguments(input, output, pool_info, indices)); - ARM_COMPUTE_RETURN_ON_ERROR(std::get<0>(validate_and_configure_window(input->clone().get(), output->clone().get(), pool_info))); - - return Status{}; -} - -void GCPoolingLayerKernel::run(const Window &window) -{ - ARM_COMPUTE_ERROR_ON_UNCONFIGURED_KERNEL(this); - ARM_COMPUTE_ERROR_ON_INVALID_SUBWINDOW(IKernel::window(), window); - - unsigned int pool_pad_x; - unsigned int pool_pad_y; - unsigned int pool_stride_x; - unsigned int pool_stride_y; - std::tie(pool_pad_x, pool_pad_y) = _pool_info.pad_stride_info.pad(); - std::tie(pool_stride_x, pool_stride_y) = _pool_info.pad_stride_info.stride(); - - _kernel.use(); - - _output->set_needs_shifting(true); - - Window window_collapsed = window.collapse_if_possible(IGCKernel::window(), Window::DimZ); - - Window slice = window_collapsed.first_slice_window_3D(); - Window slice_in_orig = window_collapsed.first_slice_window_3D(); - - slice.shift(Window::DimX, -(_output->info()->padding()).left); - - do - { - // Upsample input by pool size - Window in_slice(slice_in_orig); // NOLINT - in_slice.set(Window::DimX, Window::Dimension(in_slice.x().start() - pool_pad_x, in_slice.x().end() * pool_stride_x, pool_stride_x * _num_elems_processed_per_iteration)); - in_slice.set(Window::DimY, Window::Dimension(in_slice.y().start() - pool_pad_y, in_slice.y().end() * pool_stride_y, pool_stride_y)); - - // Set inputs - unsigned int idx = 0; - add_3D_tensor_argument(idx, _input, 1, in_slice); - add_3D_tensor_argument(idx, _output, 2, slice); - - _kernel.update_shader_params(); - enqueue(*this, slice); - } - while(window_collapsed.slide_window_slice_3D(slice) && window_collapsed.slide_window_slice_3D(slice_in_orig)); -} -- cgit v1.2.1