forked from huawei/mindspore2022
709 lines
29 KiB
C++
709 lines
29 KiB
C++
/**
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* Copyright 2019-2021 Huawei Technologies Co., Ltd
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*
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* Licensed under the Apache License, Version 2.0 (the "License");
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* you may not use this file except in compliance with the License.
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* You may obtain a copy of the License at
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*
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* http://www.apache.org/licenses/LICENSE-2.0
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*
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* Unless required by applicable law or agreed to in writing, software
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* distributed under the License is distributed on an "AS IS" BASIS,
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* WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
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* See the License for the specific language governing permissions and
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* limitations under the License.
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*/
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#include "pipeline/jit/pass.h"
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#include <memory>
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#include <vector>
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#include <string>
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#include <unordered_map>
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#include <algorithm>
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#include "ir/func_graph_cloner.h"
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#include "pipeline/jit/parse/parse_base.h"
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#include "pipeline/jit/resource.h"
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#include "pipeline/jit/validator.h"
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#include "pipeline/jit/remove_value_node_dup.h"
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#include "frontend/optimizer/opt.h"
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#include "frontend/optimizer/optimizer.h"
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#include "frontend/optimizer/cse_pass.h"
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#include "frontend/optimizer/clean.h"
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#include "frontend/optimizer/irpass.h"
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#include "frontend/optimizer/graph_transform.h"
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#include "frontend/optimizer/auto_monad_eliminate.h"
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#include "frontend/parallel/context.h"
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#include "frontend/parallel/step_parallel.h"
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#include "frontend/parallel/step_auto_parallel.h"
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#include "frontend/parallel/cache_embedding/cache_embedding.h"
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#include "frontend/parallel/allreduce_fusion/step_allreduce_fusion.h"
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#include "frontend/optimizer/recompute.h"
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#include "utils/log_adapter.h"
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#include "pipeline/jit/pipeline_split.h"
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#include "pipeline/pynative/pynative_execute.h"
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#include "pipeline/jit/static_analysis/auto_monad.h"
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#include "frontend/optimizer/irpass/branch_culling.h"
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#include "frontend/optimizer/irpass/gradient_eliminate.h"
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#include "frontend/optimizer/irpass/parameter_eliminate.h"
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#include "frontend/optimizer/irpass/updatestate_eliminate.h"
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#if ((defined ENABLE_CPU) && (!defined _WIN32))
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#include "ps/util.h"
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#include "ps/ps_context.h"
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#endif
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namespace mindspore {
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namespace pipeline {
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using OptPassGroupMap = opt::OptPassGroupMap;
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using Optimizer = opt::Optimizer;
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using CompileGraphs = compile::CompileGraphs;
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using abstract::AnalysisResult;
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using mindspore::abstract::AnalysisContextPtr;
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using mindspore::validator::Validate;
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namespace {
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void DoRenormalize(const bool &changed, const FuncGraphPtr &func_graph, const ResourcePtr &res) {
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MS_EXCEPTION_IF_NULL(func_graph);
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MS_EXCEPTION_IF_NULL(res);
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abstract::AbstractBasePtrList args_spec;
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auto parameters = func_graph->parameters();
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(void)std::transform(parameters.begin(), parameters.end(), std::back_inserter(args_spec),
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[](const AnfNodePtr &p) -> AbstractBasePtr { return p->abstract(); });
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if (changed) {
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FuncGraphPtr new_fg = Renormalize(res, func_graph, args_spec);
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res->set_func_graph(new_fg);
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}
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res->set_args_spec(args_spec);
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}
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} // namespace
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bool SimplifyDataStructuresPass(const ResourcePtr &res) {
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MS_EXCEPTION_IF_NULL(res);
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FuncGraphPtr func_graph = res->func_graph();
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MS_EXCEPTION_IF_NULL(func_graph);
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bool changed = opt::SimplifyDataStructures(func_graph, res->manager());
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DoRenormalize(changed, func_graph, res);
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return true;
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}
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bool TransformTopGraphPass(const ResourcePtr &res) {
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MS_EXCEPTION_IF_NULL(res);
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if (res->func_graph() == nullptr) {
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MS_LOG(EXCEPTION) << "Transform top graph error.";
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}
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FuncGraphPtr func_graph = res->func_graph();
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if (opt::FuncGraphHasTupleInput(func_graph)) {
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opt::GraphTupleParamTransform graph_trans;
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func_graph = graph_trans(func_graph, res->manager());
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res->set_func_graph(func_graph);
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AbstractBasePtrList abs_spec_list;
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auto ¶ms = func_graph->parameters();
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std::transform(params.begin(), params.end(), std::back_inserter(abs_spec_list),
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[](const AnfNodePtr &node) { return node->abstract(); });
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res->set_args_spec(abs_spec_list);
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}
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return true;
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}
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bool CleanAfterOptAPass(const ResourcePtr &res) {
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MS_EXCEPTION_IF_NULL(res);
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FuncGraphPtr func_graph = res->func_graph();
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MS_EXCEPTION_IF_NULL(func_graph);
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bool changed = opt::CleanAfterOptA(func_graph, res->manager());
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DoRenormalize(changed, func_graph, res);
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return true;
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}
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FuncGraphPtr PrimBpOptPassStep1(const opt::irpass::OptimizeIRPassLib &irpass, const ResourcePtr &res) {
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MS_EXCEPTION_IF_NULL(res);
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MS_EXCEPTION_IF_NULL(res->func_graph());
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opt::OptPassConfig pynative_eliminate = opt::OptPassConfig({
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irpass.pynative_eliminate_,
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});
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opt::OptPassConfig switch_simplify = opt::OptPassConfig({
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irpass.switch_simplify_,
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});
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opt::OptPassConfig inline_opt = opt::OptPassConfig({
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irpass.inline_,
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});
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OptPassGroupMap map(
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{{"ad_eliminate", pynative_eliminate}, {"ad_inline", inline_opt}, {"ad_switch_simplify", switch_simplify}});
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auto prim_bprop_opt_step_1 = opt::Optimizer::MakeOptimizer("prim_bprop_opt_step_1", res, map);
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FuncGraphPtr func_graph = res->func_graph();
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WITH(MsProfile::GetProfile()->Step("prim_bprop_opt_step_1"))[&prim_bprop_opt_step_1, &func_graph]() {
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func_graph = prim_bprop_opt_step_1->step(func_graph, true);
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};
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return func_graph;
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}
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FuncGraphPtr PrimBpOptPassStep2(const opt::irpass::OptimizeIRPassLib &irpass, const ResourcePtr &res) {
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MS_EXCEPTION_IF_NULL(res);
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MS_EXCEPTION_IF_NULL(res->func_graph());
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opt::OptPassConfig special_op_simplify = opt::OptPassConfig({
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irpass.switch_simplify_,
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irpass.reduce_eliminate_,
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irpass.tile_eliminate_,
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irpass.arithmetic_simplify_,
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});
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opt::OptPassConfig inline_opt = opt::OptPassConfig({
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irpass.inline_,
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});
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auto re_auto_monadwrapper = [](const FuncGraphPtr &root, const opt::OptimizerPtr &) -> bool {
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return ReAutoMonad(root);
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};
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OptPassGroupMap map({{"ad_renormalize", opt::OptPassConfig::Renormalize()},
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{"ad_inline", inline_opt},
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{"ad_special_op_simplify", special_op_simplify},
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{"auto_monad_grad", opt::OptPassConfig(re_auto_monadwrapper)}});
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auto prim_bprop_opt_step_2 = opt::Optimizer::MakeOptimizer("prim_bprop_opt_step_2", res, map);
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FuncGraphPtr func_graph = res->func_graph();
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WITH(MsProfile::GetProfile()->Step("prim_bprop_opt_step_2"))[&prim_bprop_opt_step_2, &func_graph]() {
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func_graph = prim_bprop_opt_step_2->step(func_graph, true);
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};
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return func_graph;
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}
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FuncGraphPtr BpropGraphFinalOptPass(const ResourcePtr &res) {
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MS_EXCEPTION_IF_NULL(res);
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MS_EXCEPTION_IF_NULL(res->func_graph());
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if (!TransformTopGraphPass(res)) {
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MS_LOG(EXCEPTION) << "Run TransformTopGraphPass failed";
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}
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opt::irpass::OptimizeIRPassLib irpass;
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opt::OptPassConfig bg_final_opt = opt::OptPassConfig({
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irpass.inline_,
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irpass.tuple_list_get_set_item_eliminator_,
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irpass.tuple_list_get_item_eliminator_,
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irpass.tuple_list_set_item_eliminator_,
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irpass.depend_value_elim_,
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irpass.reshape_eliminate_,
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irpass.switch_simplify_,
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irpass.addn_zero_filter_,
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});
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opt::OptPassConfig fill_zeros_like = opt::OptPassConfig{irpass.zero_like_fill_zero_};
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OptPassGroupMap map({
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{"ad_final_opt", bg_final_opt},
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{"zeros_like", fill_zeros_like},
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});
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if (pynative::PynativeExecutor::GetInstance()->grad_executor()->need_renormalize()) {
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map.emplace_back(std::make_pair("renormalize", opt::OptPassConfig::Renormalize()));
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}
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auto bprop_graph_final_opt = opt::Optimizer::MakeOptimizer("bprop_graph_final_opt", res, map);
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FuncGraphPtr func_graph = res->func_graph();
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WITH(MsProfile::GetProfile()->Step("bprop_graph_final_opt"))[&bprop_graph_final_opt, &func_graph]() {
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func_graph = bprop_graph_final_opt->step(func_graph, true);
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};
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return func_graph;
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}
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namespace {
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bool ReAutoMonadWrapper(const FuncGraphPtr &root, const opt::OptimizerPtr &) { return ReAutoMonad(root); }
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bool parallel_mode() {
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#if ((defined ENABLE_CPU) && (!defined _WIN32))
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if (ps::PSContext::instance()->is_server() || ps::PSContext::instance()->is_scheduler()) {
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return false;
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}
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#endif
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std::string parallel_mode = parallel::ParallelContext::GetInstance()->parallel_mode();
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return (parallel_mode == parallel::AUTO_PARALLEL) || (parallel_mode == parallel::SEMI_AUTO_PARALLEL);
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}
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void AddParallelRenormalize(OptPassGroupMap *map_a) {
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if (parallel_mode()) {
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auto parallel_end_opt =
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find_if(map_a->begin(), map_a->end(), [](auto opt_pair) { return opt_pair.first == "grad"; });
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if (parallel_end_opt != map_a->end()) {
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map_a->insert(parallel_end_opt, {"parallel_renormalize", opt::OptPassConfig::Renormalize()});
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}
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}
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}
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opt::OptPassConfig GetOptPassA1(const opt::irpass::OptimizeIRPassLib &irpass) {
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return opt::OptPassConfig({
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irpass.switch_defer_inline_,
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irpass.switch_layer_defer_inline_,
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irpass.switch_simplify_,
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irpass.exchange_switch_depend_value_,
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irpass.float_depend_g_call_,
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// Safe inlining
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irpass.inline_,
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irpass.updatestate_eliminater_,
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irpass.load_eliminater_,
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irpass.stopgrad_eliminater_,
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irpass.partial_eliminate_,
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irpass.replace_applicator_,
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// Miscellaneous
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irpass.tuple_list_get_item_eliminator_,
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irpass.tuple_list_get_item_const_eliminator_,
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irpass.tuple_list_set_item_eliminator_,
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irpass.tuple_list_get_set_item_eliminator_,
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irpass.tuple_list_get_item_depend_reorder_,
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irpass.tuple_list_convert_item_index_to_positive_,
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irpass.env_get_item_eliminate_,
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irpass.env_get_item_add_eliminate_,
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irpass.env_get_set_item_eliminate_,
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irpass.env_get_item_depend_swap_,
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irpass.reshape_eliminate_,
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irpass.reduce_eliminate_,
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irpass.tile_eliminate_,
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irpass.transpose_eliminate_,
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irpass.minmaximum_grad_,
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irpass.get_make_ref_eliminate_,
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// Arithmetic simplifications
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irpass.arithmetic_simplify_,
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irpass.addn_zero_filter_,
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irpass.adjust_all_reduce_mul_add_,
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irpass.accumulaten_eliminater_,
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// Safe inlining
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irpass.inline_,
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irpass.updatestate_eliminater_,
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irpass.load_eliminater_,
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irpass.stopgrad_eliminater_,
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irpass.sparse_tensor_eliminate_,
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});
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}
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OptPassGroupMap GetOptPassesA(const opt::irpass::OptimizeIRPassLib &irpass) {
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opt::OptPassConfig a_1 = GetOptPassA1(irpass);
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opt::OptPassConfig a_2 = opt::OptPassConfig(
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{
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irpass.switch_simplify_,
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irpass.cast_eliminate_,
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irpass.specialize_transform_,
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irpass.merge_addn_,
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irpass.float_tuple_getitem_switch_,
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irpass.float_env_getitem_switch_,
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irpass.inline_,
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irpass.incorporate_getitem_set_,
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irpass.incorporate_call_,
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irpass.incorporate_call_switch_,
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irpass.incorporate_env_getitem_bypass_recursive_,
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irpass.incorporate_env_getitem_switch_,
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irpass.env_get_item_eliminate_,
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irpass.depend_value_elim_,
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irpass.all_reduce_const_elim_,
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},
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false, true);
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opt::OptPassConfig a_after_grad = opt::OptPassConfig({irpass.inline_without_move_});
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opt::OptPassConfig a_3 = opt::OptPassConfig(
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{
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irpass.arithmetic_simplify2_,
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irpass.same_eliminate_,
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irpass.check_bprop_eliminate_,
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irpass.switch_layer_defer_inline_,
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irpass.replace_applicator_,
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irpass.mirror_mini_step_elim_,
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irpass.virtual_add_elim_,
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irpass.row_tensor_add_zeros_like_,
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irpass.mini_step_allgather_replace_,
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irpass.micro_step_allgather_replace_,
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},
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false, true);
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opt::OptPassConfig accelerated_algorithm = opt::OptPassConfig({irpass.less_batch_normalization_});
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opt::OptPassConfig virtual_dataset = opt::OptPassConfig({irpass.virtual_dataset_eliminate_});
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opt::OptPassConfig after_resolve_pass =
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opt::OptPassConfig({irpass.get_make_ref_eliminate_, irpass.replace_old_param_});
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// Before adjusting map_a, check GetA1A2() and GetOptPynativeGradEpiloguePhases().
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OptPassGroupMap map_a({{"a_1", a_1},
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{"parameter_eliminate", opt::OptPassConfig(opt::irpass::ParameterEliminator())},
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{"a_2", a_2},
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{"accelerated_algorithm", accelerated_algorithm},
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{"auto_parallel", opt::OptPassConfig(parallel::StepAutoParallel)},
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{"parallel", opt::OptPassConfig(parallel::StepParallel)},
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{"allreduce_fusion", opt::OptPassConfig(parallel::StepAllreduceFusion)},
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{"virtual_dataset", virtual_dataset},
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{"virtual_output", opt::OptPassConfig({irpass.virtual_output_eliminate_})},
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{"grad", opt::OptPassConfig(opt::irpass::ExpandJPrim())},
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{"after_resolve", after_resolve_pass},
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{"a_after_grad", a_after_grad},
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{"renormalize", opt::OptPassConfig::Renormalize()},
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{"auto_monad_grad", opt::OptPassConfig(ReAutoMonadWrapper)},
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{"auto_monad_eliminator", opt::OptPassConfig(opt::AutoMonadEliminator())},
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{"cse", opt::OptPassConfig(opt::CSEPass(false))},
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{"a_3", a_3}});
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AddParallelRenormalize(&map_a);
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return map_a;
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}
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OptPassGroupMap GetA1A2(const opt::irpass::OptimizeIRPassLib &irpass) {
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auto opt_a = GetOptPassesA(irpass);
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constexpr auto opt_a1_index = 0;
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constexpr auto parameter_eliminate = 1;
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constexpr auto opt_a2_index = 2;
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OptPassGroupMap a1_a2({opt_a[opt_a1_index], opt_a[parameter_eliminate], opt_a[opt_a2_index]});
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return a1_a2;
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}
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OptPassGroupMap GetOptPassesAfterCconv(const opt::irpass::OptimizeIRPassLib &irpass) {
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opt::OptPassConfig c_1 = opt::OptPassConfig({
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// Safe inlining,
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irpass.inline_,
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irpass.updatestate_eliminater_,
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irpass.load_eliminater_,
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irpass.switch_call_monad_eliminater_,
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irpass.stopgrad_eliminater_,
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irpass.partial_eliminate_,
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});
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OptPassGroupMap map_a({{"c_1", c_1},
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{"cse", opt::OptPassConfig(opt::CSEPass(false))},
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{"renormalize", opt::OptPassConfig::Renormalize()}});
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return map_a;
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}
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OptPassGroupMap GetOptPassesTransformGraph(const opt::irpass::OptimizeIRPassLib &irpass) {
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opt::OptPassConfig d_1 =
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opt::OptPassConfig({irpass.call_graph_tuple_transform_, irpass.tuple_list_get_item_eliminator_,
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irpass.tuple_list_get_item_const_eliminator_, irpass.tuple_list_set_item_eliminator_,
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irpass.tuple_list_get_set_item_eliminator_, irpass.tuple_list_get_item_depend_reorder_,
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irpass.tuple_list_convert_item_index_to_positive_});
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OptPassGroupMap map_a({{"d_1", d_1}, {"renormalize", opt::OptPassConfig::Renormalize()}});
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return map_a;
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}
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OptPassGroupMap GetOptPassesB(const opt::irpass::OptimizeIRPassLib &irpass) {
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opt::OptPassConfig b_1 = opt::OptPassConfig({irpass.zero_like_fill_zero_,
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irpass.tuple_list_get_item_eliminator_,
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irpass.tuple_list_get_item_const_eliminator_,
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irpass.tuple_list_set_item_eliminator_,
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irpass.tuple_list_get_set_item_eliminator_,
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irpass.tuple_list_get_item_depend_reorder_,
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irpass.tuple_list_convert_item_index_to_positive_,
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irpass.float_tuple_getitem_switch_,
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irpass.reset_defer_inline_,
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irpass.inline_,
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irpass.updatestate_eliminater_,
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irpass.load_eliminater_,
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irpass.stopgrad_eliminater_,
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irpass.special_op_eliminate_,
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irpass.get_make_ref_eliminate_,
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irpass.incorporate_env_getitem_,
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irpass.incorporate_env_getitem_switch_,
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irpass.env_get_item_eliminate_,
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irpass.env_get_item_add_eliminate_,
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irpass.env_get_set_item_eliminate_,
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irpass.env_get_item_depend_swap_,
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irpass.incorporate_env_getitem_switch_layer_,
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irpass.value_based_eliminate_,
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irpass.virtual_accu_grad_,
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irpass.virtual_assign_add_,
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irpass.mirror_micro_step_},
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false, true);
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opt::OptPassConfig b_2 = opt::OptPassConfig({
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irpass.replace_refkey_by_param_,
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irpass.make_ref_eliminate_,
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irpass.get_ref_param_eliminate_,
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irpass.row_tensor_eliminate_,
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});
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OptPassGroupMap map({
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{"b_1", b_1},
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{"b_2", b_2},
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{"renormalize", opt::OptPassConfig::Renormalize()},
|
|
{"cse", opt::OptPassConfig(opt::CSEPass(false))},
|
|
});
|
|
return map;
|
|
}
|
|
|
|
OptPassGroupMap GetOptPassesPynativeElim(const opt::irpass::OptimizeIRPassLib &irpass) {
|
|
opt::OptPassConfig pynative_eliminate = opt::OptPassConfig({
|
|
irpass.pynative_eliminate_,
|
|
});
|
|
|
|
OptPassGroupMap map({
|
|
{"pynative_eliminate", pynative_eliminate},
|
|
});
|
|
return map;
|
|
}
|
|
|
|
OptPassGroupMap GetOptPassesC(const opt::irpass::OptimizeIRPassLib &) {
|
|
return OptPassGroupMap({{"renormalize", opt::OptPassConfig::Renormalize()}});
|
|
}
|
|
|
|
OptPassGroupMap GetControlPhases(const opt::irpass::OptimizeIRPassLib &irpass) {
|
|
opt::OptPassConfig control_group = opt::OptPassConfig(opt::irpass::ConvertSwitchReplacement());
|
|
OptPassGroupMap map({
|
|
{"control_group", control_group},
|
|
{"renormalize", opt::OptPassConfig::Renormalize()},
|
|
});
|
|
return map;
|
|
}
|
|
|
|
OptPassGroupMap GetOptPynativeGradEpiloguePhases(const opt::irpass::OptimizeIRPassLib &irpass) {
|
|
auto opt_a = GetOptPassesA(irpass);
|
|
auto a3 = opt_a[opt_a.size() - 1];
|
|
OptPassGroupMap map({
|
|
{"renormalize", opt::OptPassConfig::Renormalize()},
|
|
{"cse", opt::OptPassConfig(opt::CSEPass(false))},
|
|
{a3},
|
|
});
|
|
return map;
|
|
}
|
|
|
|
OptPassGroupMap GetInferenceOptPreparePhases() {
|
|
opt::irpass::InferenceOptPrepareLib irpass;
|
|
auto grad_var_prepare = opt::OptPassConfig({irpass.grad_var_prepare_});
|
|
opt::OptPassGroupMap prepare_map({{"inference_opt_prep", grad_var_prepare}});
|
|
return prepare_map;
|
|
}
|
|
|
|
OptPassGroupMap GetPreparePhases(const opt::irpass::OptimizeIRPassLib &irpass) {
|
|
opt::OptPassConfig prepare_group = opt::OptPassConfig({irpass.print_tuple_wrapper_});
|
|
OptPassGroupMap map({{"prepare_group", prepare_group}});
|
|
return map;
|
|
}
|
|
|
|
OptPassGroupMap GetBeforeRecomputePass(const opt::irpass::OptimizeIRPassLib &irpass) {
|
|
opt::OptPassConfig set_cell_output_no_recompute = opt::OptPassConfig({irpass.set_cell_output_no_recompute_});
|
|
OptPassGroupMap map({{"set_cell_output_no_recompute", set_cell_output_no_recompute}});
|
|
return map;
|
|
}
|
|
|
|
OptPassGroupMap GetAfterRecomputePass(const opt::irpass::OptimizeIRPassLib &) {
|
|
OptPassGroupMap map({{"cse", opt::OptPassConfig(opt::CSEPass(false))}});
|
|
return map;
|
|
}
|
|
|
|
static std::unordered_map<std::string, std::shared_ptr<Optimizer>> g_pass_opts = {};
|
|
|
|
void InitOpt(const ResourcePtr &res) {
|
|
if (g_pass_opts.size() == 0) {
|
|
opt::irpass::OptimizeIRPassLib irpass;
|
|
g_pass_opts["a1a2"] = Optimizer::MakeOptimizer("a1a2", res, GetA1A2(irpass));
|
|
g_pass_opts["opt_a"] = Optimizer::MakeOptimizer("opt_a", res, GetOptPassesA(irpass));
|
|
g_pass_opts["opt_b"] = Optimizer::MakeOptimizer("opt_b", res, GetOptPassesB(irpass), false, true);
|
|
g_pass_opts["opt_after_cconv"] =
|
|
Optimizer::MakeOptimizer("opt_after_cconv", res, GetOptPassesAfterCconv(irpass), false, true);
|
|
g_pass_opts["opt_trans_graph"] =
|
|
Optimizer::MakeOptimizer("opt_trans_graph", res, GetOptPassesTransformGraph(irpass), true, true);
|
|
g_pass_opts["renormal"] = Optimizer::MakeOptimizer("renormal", res, GetOptPassesC(irpass));
|
|
g_pass_opts["opt_control"] = Optimizer::MakeOptimizer("opt_control", res, GetControlPhases(irpass), true, true);
|
|
g_pass_opts["opt_grad_epilogue"] =
|
|
Optimizer::MakeOptimizer("opt_grad_epilogue", res, GetOptPynativeGradEpiloguePhases(irpass), true, false);
|
|
g_pass_opts["opt_prepare"] = Optimizer::MakeOptimizer("opt_prepare", res, GetPreparePhases(irpass));
|
|
g_pass_opts["opt_before_recompute"] =
|
|
Optimizer::MakeOptimizer("opt_before_recompute", res, GetBeforeRecomputePass(irpass));
|
|
g_pass_opts["opt_after_recompute"] =
|
|
Optimizer::MakeOptimizer("opt_after_recompute", res, GetAfterRecomputePass(irpass));
|
|
}
|
|
}
|
|
} // namespace
|
|
|
|
void ReclaimOptimizer() {
|
|
for (auto &opt : g_pass_opts) {
|
|
opt.second = nullptr;
|
|
}
|
|
g_pass_opts.clear();
|
|
}
|
|
|
|
bool OptPassGroup(const ResourcePtr &res, const std::string &name) {
|
|
MS_EXCEPTION_IF_NULL(res);
|
|
if (res->func_graph() == nullptr) {
|
|
MS_LOG(ERROR) << "Opt passes int64_t error";
|
|
return false;
|
|
}
|
|
|
|
FuncGraphPtr func_graph = res->func_graph();
|
|
MS_LOG(DEBUG) << "Start " << name << " func graph:" << func_graph->ToString() << ", "
|
|
<< func_graph->get_return()->DebugString(true);
|
|
InitOpt(res);
|
|
if (g_pass_opts.find(name) != g_pass_opts.end()) {
|
|
res->set_func_graph(g_pass_opts[name]->step(func_graph));
|
|
}
|
|
// Note: StepParallel may modify the AbstractValue of the parameters of func_graph, but they are not updated to
|
|
// res->args_spec_ yet. So if any later pass or action want to use that variable, it should be set here.
|
|
return true;
|
|
}
|
|
|
|
bool OptPassA1A2(const ResourcePtr &res) { return OptPassGroup(res, "a1a2"); }
|
|
bool OptPassAGroup(const ResourcePtr &res) { return OptPassGroup(res, "opt_a"); }
|
|
bool OptPassBGroup(const ResourcePtr &res) { return OptPassGroup(res, "opt_b"); }
|
|
bool OptPassAfterCconvGroup(const ResourcePtr &res) { return OptPassGroup(res, "opt_after_cconv"); }
|
|
bool OptPassTransformGraphGroup(const ResourcePtr &res) { return OptPassGroup(res, "opt_trans_graph"); }
|
|
bool ControlGroup(const ResourcePtr &res) { return OptPassGroup(res, "opt_control"); }
|
|
bool PrepareGroup(const ResourcePtr &res) { return OptPassGroup(res, "opt_prepare"); }
|
|
bool OptBeforeRecomputeGroup(const ResourcePtr &res) { return OptPassGroup(res, "opt_before_recompute"); }
|
|
bool OptAfterRecomputeGroup(const ResourcePtr &res) { return OptPassGroup(res, "opt_after_recompute"); }
|
|
|
|
bool OptPassRNGroup(const ResourcePtr &res) { return OptPassGroup(res, "renormal"); }
|
|
|
|
bool OptPassGradEpilogueGroup(const ResourcePtr &res) { return OptPassGroup(res, "opt_grad_epilogue"); }
|
|
|
|
bool AddRecomputationPass(const ResourcePtr &res) {
|
|
MS_EXCEPTION_IF_NULL(res);
|
|
opt::InsertRecomputedNodes(res->func_graph());
|
|
return true;
|
|
}
|
|
|
|
bool AddCacheEmbeddingPass(const ResourcePtr &res) {
|
|
MS_EXCEPTION_IF_NULL(res);
|
|
#if ((defined ENABLE_CPU) && (!defined _WIN32))
|
|
if (ps::PSContext::instance()->is_ps_mode()) {
|
|
return true;
|
|
}
|
|
#endif
|
|
FuncGraphPtr func_graph = res->func_graph();
|
|
MS_EXCEPTION_IF_NULL(func_graph);
|
|
|
|
parallel::AddCacheEmbedding(func_graph);
|
|
if (func_graph->has_flag(GRAPH_FLAG_CACHE_ENABLE)) {
|
|
auto params = func_graph->parameters();
|
|
AbstractBasePtrList args_spec_list;
|
|
std::for_each(params.begin(), params.end(),
|
|
[&args_spec_list](const AnfNodePtr &node) { args_spec_list.push_back(node->abstract()); });
|
|
func_graph = pipeline::Renormalize(res, func_graph, args_spec_list);
|
|
}
|
|
return true;
|
|
}
|
|
|
|
bool RemoveValueNodeDuplicationsPass(const ResourcePtr &res) {
|
|
MS_EXCEPTION_IF_NULL(res);
|
|
if (res->func_graph() == nullptr) {
|
|
MS_LOG(EXCEPTION) << "Remove value node duplications error.";
|
|
}
|
|
auto manager = res->manager();
|
|
HashCache hash_cache;
|
|
HashValue hashes;
|
|
// Remove duplicated value nodes across all graphs in manager
|
|
for (auto &fg : manager->func_graphs()) {
|
|
auto value_nodes = fg->value_nodes();
|
|
for (const auto &value_pair : value_nodes) {
|
|
TryToDoReplace(manager.get(), value_pair.first, &hash_cache, &hashes);
|
|
}
|
|
}
|
|
return true;
|
|
}
|
|
|
|
bool CconvPass(const ResourcePtr &res) {
|
|
MS_EXCEPTION_IF_NULL(res);
|
|
MS_EXCEPTION_IF_NULL(res->func_graph());
|
|
FuncGraphPtr func_graph = res->func_graph();
|
|
FuncGraphPtr new_fg = LiftingClone(func_graph);
|
|
res->set_func_graph(new_fg);
|
|
return true;
|
|
}
|
|
|
|
bool PipelineSplitPass(const ResourcePtr &res) { return PipelineSplit(res); }
|
|
|
|
void UpdateFuncGraphParameter(const FuncGraphPtr &func_graph) {
|
|
MS_EXCEPTION_IF_NULL(func_graph);
|
|
std::vector<AnfNodePtr> new_paras;
|
|
for (const auto ¶m : func_graph->parameters()) {
|
|
auto param_node = param->cast<ParameterPtr>();
|
|
MS_EXCEPTION_IF_NULL(param_node);
|
|
if (param_node->has_default()) {
|
|
new_paras.push_back(param_node);
|
|
continue;
|
|
}
|
|
AbstractBasePtr par_abs = param_node->abstract();
|
|
MS_EXCEPTION_IF_NULL(par_abs);
|
|
if (par_abs->isa<abstract::AbstractUndetermined>() ||
|
|
(MsContext::GetInstance()->get_param<bool>(MS_CTX_GRAD_FOR_SCALAR) && par_abs->BuildType() != nullptr &&
|
|
par_abs->BuildType()->isa<Number>())) {
|
|
new_paras.push_back(param_node);
|
|
}
|
|
}
|
|
func_graph->set_parameters(new_paras);
|
|
}
|
|
|
|
bool ValidatePass(const ResourcePtr &res) {
|
|
MS_EXCEPTION_IF_NULL(res);
|
|
MS_EXCEPTION_IF_NULL(res->func_graph());
|
|
FuncGraphPtr func_graph = res->func_graph();
|
|
Validate(func_graph);
|
|
UpdateFuncGraphParameter(func_graph);
|
|
return true;
|
|
}
|
|
|
|
bool InferenceOptPreparePass(const ResourcePtr &res) {
|
|
FuncGraphPtr func_graph = res->func_graph();
|
|
MS_EXCEPTION_IF_NULL(func_graph);
|
|
auto prepare_map = GetInferenceOptPreparePhases();
|
|
auto infer_opt_prepare = opt::Optimizer::MakeOptimizer("inference_prepare", res, prepare_map);
|
|
(void)infer_opt_prepare->step(func_graph, false);
|
|
return true;
|
|
}
|
|
|
|
bool PynativeOptPass(const ResourcePtr &res) {
|
|
FuncGraphPtr func_graph = res->func_graph();
|
|
MS_EXCEPTION_IF_NULL(func_graph);
|
|
opt::irpass::OptimizeIRPassLib irpass;
|
|
auto pynative_opt = GetOptPassesPynativeElim(irpass);
|
|
auto pynative_opt_opt = opt::Optimizer::MakeOptimizer("pynative_opt", res, pynative_opt);
|
|
(void)pynative_opt_opt->step(func_graph, false);
|
|
return true;
|
|
}
|
|
|
|
bool AutoMonadElimOptPass(const FuncGraphPtr &func_graph) {
|
|
MS_EXCEPTION_IF_NULL(func_graph);
|
|
MS_EXCEPTION_IF_NULL(func_graph->manager());
|
|
auto res = std::make_shared<pipeline::Resource>();
|
|
res->set_func_graph(func_graph);
|
|
res->set_manager(func_graph->manager());
|
|
|
|
// opt::irpass::OptimizeIRPassLib is not used here to avoid double free problems in external calls.
|
|
opt::SubstitutionPtr updatestate_eliminater = opt::MakeSubstitution(
|
|
std::make_shared<opt::irpass::UpdatestateEliminater>(), "updatestate_eliminater", prim::kPrimUpdateState);
|
|
opt::OptPassGroupMap elim_map({
|
|
{"updatestate_eliminate", opt::OptPassConfig({updatestate_eliminater})},
|
|
{"auto_monad_eliminator", opt::OptPassConfig(opt::AutoMonadEliminator())},
|
|
});
|
|
|
|
auto auto_monad_elim_opt = opt::Optimizer::MakeOptimizer("auto_monad_elim", res, elim_map);
|
|
(void)auto_monad_elim_opt->step(func_graph, false);
|
|
return true;
|
|
}
|
|
|
|
std::vector<PassItem> kVmPasses = {{"simplify_data_structures", SimplifyDataStructuresPass},
|
|
{"opt_before_recompute", OptBeforeRecomputeGroup},
|
|
{"opt_a", OptPassAGroup},
|
|
{"clean_after_opta", CleanAfterOptAPass},
|
|
{"opt_b", OptPassBGroup},
|
|
{"cconv", CconvPass},
|
|
{"opt_after_cconv", OptPassAfterCconvGroup},
|
|
{"remove_dup_value", RemoveValueNodeDuplicationsPass},
|
|
{"tuple_transform", OptPassTransformGraphGroup},
|
|
{"add_cache_embedding", AddCacheEmbeddingPass},
|
|
{"add_recomputation", AddRecomputationPass},
|
|
{"cse_after_recomputation", OptAfterRecomputeGroup}};
|
|
|
|
std::vector<PassItem> kGePasses = {{"simplify_data_structures", SimplifyDataStructuresPass},
|
|
{"opt_a", OptPassAGroup},
|
|
{"clean_after_opta", CleanAfterOptAPass},
|
|
{"opt_b", OptPassBGroup},
|
|
{"opt_control", ControlGroup},
|
|
{"opt_prepare", PrepareGroup},
|
|
{"cconv", CconvPass}};
|
|
|
|
std::vector<PassItem> kPynativePasses = {{"opt_a", OptPassAGroup},
|
|
{"opt_b", OptPassBGroup},
|
|
{"cconv", CconvPass},
|
|
{"transform_top", TransformTopGraphPass},
|
|
{"transform_graph", OptPassTransformGraphGroup}};
|
|
|
|
std::vector<PassItem> kInlinePasses = {{"simplify_data_structures", SimplifyDataStructuresPass}, {"a1a2", OptPassA1A2}};
|
|
} // namespace pipeline
|
|
} // namespace mindspore
|