/** * \file dnn/src/fallback/conv_bias/im2col/algos.h * MegEngine is Licensed under the Apache License, Version 2.0 (the "License") * * Copyright (c) 2014-2020 Megvii Inc. All rights reserved. * * Unless required by applicable law or agreed to in writing, * software distributed under the License is distributed on an * "AS IS" BASIS, WITHOUT ARRANTIES OR CONDITIONS OF ANY KIND, either express or implied. */ #pragma once #include "megdnn/thin/small_vector.h" #include "src/common/utils.h" #include "src/fallback/conv_bias/opr_impl.h" #include "src/fallback/matrix_mul/opr_impl.h" #include "src/common/opr_delegate.h" namespace megdnn { namespace fallback { class ConvBiasImpl::AlgoIm2col final : public AlgoBase { //! calculate m_oc_tile_size in choice_ohw_oc_block() fucntion, //! when m_oc_tile_size < this value m_oc_tile_size = ohw static constexpr size_t DEFAULT_OHW_MIN_TILE_SIZE = 32; //! when nr_threads > 1 and round(ohw,nr_threads)>nr_threads, //! m_oc_tile_size = DEFAULT_OC_TILE_SIZE static constexpr size_t DEFAULT_OC_TILE_SIZE = 512; //! when m_oc_tile_size > this value m_oc_tile_size = //! DEFAULT_OC_MAX_TILE_SIZE static constexpr size_t DEFAULT_OC_MAX_TILE_SIZE = 1024; //! when m_oc_tile_size < this value m_oc_tile_size = //! DEFAULT_OC_MIN_TILE_SIZE the purpose is aligning the calculation static constexpr size_t DEFAULT_OC_MIN_TILE_SIZE = 128; fallback::MatrixMulImpl::KernSizeParam get_matmul_kern_param( const NCBKernSizeParam& param, size_t ohw_tile_size, size_t oc_tile_size) const; WorkspaceBundle get_bundle(const NCBKernSizeParam& param) const; void choice_ohw_oc_block( const NCBKernSizeParam& param, size_t& oc_tile_size, size_t& ohw_tile_size, size_t block_m, size_t block_n, fallback::MatrixMulImpl::AlgoBase::PackMode pack_mode) const; public: AlgoIm2col(MatrixMulImpl::AlgoBase* matmul_algo, size_t ohw_tile_size) : m_matmul_algo(matmul_algo), m_ohw_tile_size(ohw_tile_size) {} bool is_reproducible() const override { return true; } const char* name() const override { if (m_name.empty()) { m_name = ssprintf("IM2COLMATMUL:%s:%zu", m_matmul_algo->name(), m_ohw_tile_size); } return m_name.c_str(); } bool usable(const NCBKernSizeParam& param, AlgoSelectionStrategy algo_selection_strategy) const override; size_t get_workspace(const NCBKernSizeParam& param) const override; SmallVector dispatch_kerns( const NCBKernSizeParam& param) const override; bool is_preferred( const NCBKernSizeParam& param) const override { if (param.src_type.category() == DTypeCategory::QUANTIZED) { static CpuOprDelegationStorage<1> storage; auto conv_bias_opr = storage.get(); return static_cast(conv_bias_opr) ->is_matmul_quantized_prefer(param); } auto&& fm = param.filter_meta; auto OC = fm.ocpg, IC = fm.icpg; return OC >= 32 || IC >= 32; } private: MatrixMulImpl::AlgoBase* m_matmul_algo; mutable std::string m_name; const size_t m_ohw_tile_size; }; } // namespace fallback } // namespace megdnn // vim: syntax=cpp.doxygen