/** * \file dnn/src/cuda/local_share/backward_data/algo.h * MegEngine is Licensed under the Apache License, Version 2.0 (the "License") * * Copyright (c) 2014-2021 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/oprs.h" #include "src/common/algo_base.h" #include "src/common/metahelper.h" #include "src/common/utils.h" #include "src/cuda/handle.h" #include "src/cuda/local_share/opr_impl.h" #include namespace megdnn { namespace cuda { class LocalShareBackwardDataImpl::AlgoBase : public Algorithm { protected: ~AlgoBase() = default; public: enum class AlgoType : uint32_t { CUDA_IMPLICIT_GEMM, CUDA_BATCHED_MATMUL, }; using Mapper = std::unordered_map; AlgoBase() : Algorithm() { m_handle_type = Handle::HandleType::CUDA; } struct SizeArgs { LocalShareBackwardDataImpl* opr; TensorLayout filter_layout, diff_layout, grad_layout; std::string to_string() const; SizeArgs(LocalShareBackwardDataImpl* opr, const TensorLayout& filter, const TensorLayout& diff, const TensorLayout& grad); }; struct ExecArgs : public SizeArgs { const TensorND *filter_tensor, *diff_tensor, *grad_tensor; Workspace workspace; ExecArgs(LocalShareBackwardDataImpl* opr, _megdnn_tensor_in filter, _megdnn_tensor_in diff, _megdnn_tensor_out grad, _megdnn_workspace workspace); }; virtual bool is_available(const SizeArgs& args) const = 0; virtual size_t get_workspace_in_bytes(const SizeArgs& args) const = 0; virtual void exec(const ExecArgs& args) const = 0; bool is_available_wk(const SizeArgs& args, size_t limit) { return is_available(args) && get_workspace_in_bytes(args) <= limit; } bool is_available_attribute( const SizeArgs& args, const AlgoAttribute& positive_attr = AlgoAttribute::REPRODUCIBLE, const AlgoAttribute& negative_attr = AlgoAttribute::DEFAULT, size_t limit = std::numeric_limits::max()) { return contain_attribute_all(positive_attr) && !contain_attribute_any(negative_attr) && is_available_wk(args, limit); } AlgoBase& check_workspace(const SizeArgs& args, const Workspace& workspace) { auto req = get_workspace_in_bytes(args); megdnn_assert(req <= workspace.size, "local share conv fwd algo %s: required workspace %zu " "bytes, got %zu", name(), req, workspace.size); return *this; } }; class LocalShareBackwardDataImpl::AlgoImplicitGemm final : public AlgoBase { public: bool is_available(const SizeArgs& args) const override; size_t get_workspace_in_bytes(const SizeArgs& args) const override; void exec(const ExecArgs& args) const override; AlgoAttribute attribute() const override { return AlgoAttribute::REPRODUCIBLE; } const char* name() const override { return "LOCAL_SHARE_IMPLICIT_GEMM"; } MEGDNN_DECL_ALGO_TYPE(CUDA_IMPLICIT_GEMM) }; class LocalShareBackwardDataImpl::AlgoBatchedMatMul final : public AlgoBase { public: bool is_available(const SizeArgs& args) const override; size_t get_workspace_in_bytes(const SizeArgs& args) const override; WorkspaceBundle get_workspace_bundle(dt_byte* raw_ptr, const SizeArgs& args) const; void exec(const ExecArgs& args) const override; AlgoAttribute attribute() const override { return AlgoAttribute::REPRODUCIBLE; } const char* name() const override { return "LOCAL_SHARE_BATCHED_MATMUL"; } MEGDNN_DECL_ALGO_TYPE(CUDA_BATCHED_MATMUL) }; class LocalShareBackwardDataImpl::AlgoPack : NonCopyableObj { AlgoBase::Mapper m_all_algos_map; public: AlgoPack(); AlgoImplicitGemm implicit_gemm; AlgoBatchedMatMul batched_matmul; std::vector all_algos; const AlgoBase::Mapper& all_algos_map() const { return m_all_algos_map; } }; } // namespace cuda } // namespace megdnn // vim: syntax=cpp.doxygen