/* * Copyright (c) 2022 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 "GpuKernelComponentGroup.h" #include "arm_compute/core/ITensorInfo.h" #include "arm_compute/core/Validate.h" #include "src/dynamic_fusion/sketch/gpu/components/IGpuKernelComponent.h" #include namespace arm_compute { namespace experimental { namespace dynamic_fusion { bool GpuKernelComponentGroup::add_component(ComponentPtr component) { ARM_COMPUTE_ERROR_ON_MSG(_finalized, "The component group has been finalized and cannot be altered."); // note: Constraint 1 is guaranteed as a precondition // Constraint 2 if (component->type() != GpuComponentType::Output && _components.size() >= max_fused_components) { return false; } // Constraint 3.1: Pattern: (Unfusable + Output) if (!_components.empty() && get_root_component()->type() == GpuComponentType::Unfusable && component->type() != GpuComponentType::Output) { return false; } // Constraint 3.2 if (!_components.empty() && (component->type() != GpuComponentType::Simple && component->type() != GpuComponentType::Output)) { return false; } // Constraint 4 if (component->type() != GpuComponentType::Unfusable && component->tensors().get_const_dst_tensors().size() != 1U) { return false; } // Constraint 5 if (!_components.empty() && !(get_root_component()->properties() == component->properties())) { return false; } // Constraint 7 if (!_components.empty()) { const auto root_dst_tensors = get_root_component()->tensors().get_const_dst_tensors(); ARM_COMPUTE_ERROR_ON(root_dst_tensors.empty()); const auto first_dst_tensor = root_dst_tensors[0]; const auto dst_tensors = component->tensors().get_const_dst_tensors(); for (const auto &t : root_dst_tensors) { if (detail::have_different_dimensions(t->tensor_shape(), first_dst_tensor->tensor_shape(), 0)) { return false; } } for (const auto &t : dst_tensors) { if (detail::have_different_dimensions(t->tensor_shape(), first_dst_tensor->tensor_shape(), 0)) { return false; } } } // Constraint 8 if (!_components.empty()) { const auto root_dst_tensors = get_root_component()->tensors().get_const_dst_tensors(); ARM_COMPUTE_ERROR_ON(root_dst_tensors.empty()); const auto first_dst_tensor_layout = root_dst_tensors[0]->data_layout(); const auto dst_tensors = component->tensors().get_const_dst_tensors(); for (const auto &t : root_dst_tensors) { if (t->data_layout() != first_dst_tensor_layout) { return false; } } for (const auto &t : dst_tensors) { if (t->data_layout() != first_dst_tensor_layout) { return false; } } } // Constraint 9 if (component->tensors().get_const_dst_tensors().size() >= max_dst_tensors) { return false; } // Constraint 9 corollary if (component->type() == GpuComponentType::Output && _components.size() >= max_fused_components + max_dst_tensors) { return false; } _components.push_back(component); return true; } void GpuKernelComponentGroup::finalize() { if (_finalized) { return; } _finalized = true; std::set output_tensors; std::map> possible_tile_map; std::map tile_usages; for (auto component : _components) { const auto tensors = component->tensors(); const auto src_tensors = tensors.get_const_src_tensors(); const auto dst_tensors = tensors.get_const_dst_tensors(); // Detect input, output and intermediate tensors. for (auto tensor : src_tensors) { const auto output_tensors_it = output_tensors.find(tensor); if (output_tensors_it != output_tensors.end()) { // This tensor is the output of another operator. // It must be marked as intermediate tensor. output_tensors.erase(output_tensors_it); _interm_tensors.insert(tensor); } else if (_interm_tensors.find(tensor) == _interm_tensors.end()) { _input_tensors.insert(tensor); tile_usages[tensor] = 0; possible_tile_map.emplace(tensor, std::vector()); } } for (auto tensor : dst_tensors) { ARM_COMPUTE_ERROR_ON(_input_tensors.find(tensor) != _input_tensors.end()); ARM_COMPUTE_ERROR_ON(output_tensors.find(tensor) != output_tensors.end()); ARM_COMPUTE_ERROR_ON(_interm_tensors.find(tensor) != _interm_tensors.end()); output_tensors.insert(tensor); tile_usages[tensor] = 0; possible_tile_map.emplace(tensor, std::vector()); } // Check if the output can overwrite the input tile. const auto component_type = component->type(); if (component_type == GpuComponentType::Simple || component_type == GpuComponentType::Output) { ARM_COMPUTE_ERROR_ON(dst_tensors.size() != 1); const auto dst_tensor = dst_tensors[0]; const auto &dst_shape = dst_tensor->tensor_shape(); const auto &dst_type = dst_tensor->data_type(); tile_usages[dst_tensor] = 0; for (auto src_tensor : src_tensors) { const auto &src_shape = src_tensor->tensor_shape(); const auto &src_type = src_tensor->data_type(); if (src_shape == dst_shape && src_type == dst_type) { const auto tile_usages_it = tile_usages.find(src_tensor); ARM_COMPUTE_ERROR_ON(tile_usages_it == tile_usages.end()); if (component_type == GpuComponentType::Simple || tile_usages_it->second > 0) { // Increase the number of tile usages unless this component is an output // and the tile has not been shared with any component. // (Reason: output component doesn't change the content of the tile) ++tile_usages_it->second; } possible_tile_map[dst_tensor].push_back(src_tensor); } } } else { // Outputs of complex and unfusable components need dedicated tile. for (auto tensor : dst_tensors) { tile_usages[tensor] = 0; } } } // Find the smallest list of tiles that the intermediate tensors need to write to. for (auto tensor : _input_tensors) { _tile_map[tensor] = tensor; } for (auto component : _components) { const auto dst_tensors = component->tensors().get_const_dst_tensors(); for (auto tensor : dst_tensors) { const auto target_tiles = possible_tile_map.at(tensor); _tile_map[tensor] = tensor; for (auto target : target_tiles) { const auto num_usage = tile_usages[target]; if (num_usage <= 1) { // The target tile is consumed by only this operator, so we can reuse it // for the destination tensor data. _tile_map[tensor] = _tile_map.at(target); break; } } } } for (auto tensor : output_tensors) { _tile_map[tensor] = tensor; } // All intermediate tensors that cannot be shared with any previous tensor // will need to be declared as tile variable. for (auto tensor_tile : _tile_map) { if (tensor_tile.first == tensor_tile.second && _interm_tensors.find(tensor_tile.first) != _interm_tensors.end()) { _tiles.push_back(tensor_tile.first); } } std::set_union(_input_tensors.begin(), _input_tensors.end(), output_tensors.begin(), output_tensors.end(), std::back_inserter(_argument_tensors)); _any_output_tensor = *output_tensors.begin(); } std::vector GpuKernelComponentGroup::get_tiles() const { ARM_COMPUTE_ERROR_ON_MSG(!_finalized, "The component group must have been finalized."); return _tiles; } const ITensorInfo *GpuKernelComponentGroup::get_tile_for_tensor(const ITensorInfo *tensor) const { ARM_COMPUTE_ERROR_ON_MSG(!_finalized, "The component group must have been finalized."); if (_tile_map.find(tensor) != _tile_map.end()) { return _tile_map.at(tensor); } return tensor; } const ITensorInfo *GpuKernelComponentGroup::get_any_dst_tensor() const { ARM_COMPUTE_ERROR_ON_MSG(!_finalized, "The component group must have been finalized."); return _any_output_tensor; } std::vector GpuKernelComponentGroup::get_argument_tensors() const { ARM_COMPUTE_ERROR_ON_MSG(!_finalized, "The component group must have been finalized."); return _argument_tensors; } GpuKernelComponentGroup::ComponentPtr GpuKernelComponentGroup::get_root_component() const { if (empty()) { return nullptr; } return _components[0]; } bool GpuKernelComponentGroup::is_intermediate_tensor(const ITensorInfo *tensor) const { ARM_COMPUTE_ERROR_ON_MSG(!_finalized, "The component group must have been finalized."); return _interm_tensors.find(tensor) != _interm_tensors.end(); } bool GpuKernelComponentGroup::is_input_tensor(const ITensorInfo *tensor) const { ARM_COMPUTE_ERROR_ON_MSG(!_finalized, "The component group must have been finalized."); return _input_tensors.find(tensor) != _input_tensors.end(); } size_t GpuKernelComponentGroup::size() const { return _components.size(); } bool GpuKernelComponentGroup::empty() const { return _components.empty(); } GpuKernelComponentGroup::ComponentPtr &GpuKernelComponentGroup::operator[](size_t index) { return _components[index]; } const GpuKernelComponentGroup::ComponentPtr &GpuKernelComponentGroup::operator[](size_t index) const { return _components[index]; } typename std::vector::iterator GpuKernelComponentGroup::begin() { return _components.begin(); } typename std::vector::iterator GpuKernelComponentGroup::end() { return _components.end(); } typename std::vector::const_iterator GpuKernelComponentGroup::begin() const { return _components.cbegin(); } typename std::vector::const_iterator GpuKernelComponentGroup::end() const { return _components.cend(); } typename std::vector::const_iterator GpuKernelComponentGroup::cbegin() const { return _components.cbegin(); } typename std::vector::const_iterator GpuKernelComponentGroup::cend() const { return _components.cend(); } } // namespace dynamic_fusion } // namespace experimental } // namespace arm_compute