mindspore2022/mindspore/ccsrc/optimizer/irpass/specialize_transform.h

148 lines
4.4 KiB
C++

/**
* Copyright 2020 Huawei Technologies Co., Ltd
*
* Licensed under the Apache License, Version 2.0 (the "License");
* you may not use this file except in compliance with the License.
* You may obtain a copy of the License at
*
* http://www.apache.org/licenses/LICENSE-2.0
*
* Unless required by applicable law or agreed to in writing, software
* distributed under the License is distributed on an "AS IS" BASIS,
* WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
* See the License for the specific language governing permissions and
* limitations under the License.
*/
#ifndef MINDSPORE_CCSRC_OPTIMIZER_IRPASS_SPECIALIZE_TRANSFORM_H_
#define MINDSPORE_CCSRC_OPTIMIZER_IRPASS_SPECIALIZE_TRANSFORM_H_
#include <map>
#include <vector>
#include <memory>
#include <utility>
#include <unordered_map>
#include "optimizer/irpass.h"
#include "optimizer/optimizer.h"
#include "ir/visitor.h"
#include "ir/manager.h"
#include "ir/func_graph.h"
#include "ir/func_graph_cloner.h"
#include "operator/ops.h"
namespace mindspore {
namespace opt {
namespace irpass {
namespace internal {
class SpecializeTransform {
public:
SpecializeTransform() : cache_() {}
~SpecializeTransform() = default;
FuncGraphPtr operator()(const FuncGraphPtr &func_graph, std::vector<FuncGraphPtr> graph_args,
std::vector<PrimitivePtr> prim_args) {
if (cache_.count(func_graph) == 0) {
cache_[func_graph] = {};
}
auto &cache = cache_[func_graph];
auto key = std::make_pair(graph_args, prim_args);
if (cache.count(key) == 0) {
auto mng = func_graph->manager();
MS_EXCEPTION_IF_NULL(mng);
FuncGraphPtr new_fg = TransformableClone(func_graph, std::make_shared<TraceTransform>("sp"));
mng->AddFuncGraph(new_fg);
std::vector<AnfNodePtr> params = new_fg->parameters();
std::vector<AnfNodePtr> new_params;
size_t n = graph_args.size();
for (size_t i = 0; i < n; i++) {
if (graph_args[i] != nullptr) {
auto arg = NewValueNode(graph_args[i]);
(void)mng->Replace(params[i], arg);
continue;
}
if (prim_args[i] != nullptr) {
auto arg = NewValueNode(prim_args[i]);
(void)mng->Replace(params[i], arg);
continue;
}
new_params.push_back(params[i]);
}
mng->SetParameters(new_fg, new_params);
cache[key] = new_fg;
}
return cache[key];
}
private:
std::unordered_map<FuncGraphPtr,
std::map<std::pair<std::vector<FuncGraphPtr>, std::vector<PrimitivePtr>>, FuncGraphPtr>>
cache_;
};
} // namespace internal
// {G, Xs}
class SpecializeOnGraphArguments : public AnfVisitor {
public:
SpecializeOnGraphArguments() : specialize_transform_() {}
~SpecializeOnGraphArguments() override = default;
AnfNodePtr operator()(const OptimizerPtr &, const AnfNodePtr &node) override {
if (!node->isa<CNode>() || node->func_graph() == nullptr) {
return nullptr;
}
auto &inputs = node->cast<CNodePtr>()->inputs();
if (!IsValueNode<FuncGraph>(inputs[0])) {
return nullptr;
}
auto inp0_fg = GetValueNode<FuncGraphPtr>(inputs[0]);
if (inp0_fg->recursive()) {
return nullptr;
}
std::vector<FuncGraphPtr> graph_args;
std::vector<PrimitivePtr> prim_args;
std::vector<AnfNodePtr> new_xs;
bool hasVNode = false;
for (size_t i = 1; i < inputs.size(); i++) {
if (IsValueNode<FuncGraph>(inputs[i])) {
auto fg_vnode = GetValueNode<FuncGraphPtr>(inputs[i]);
graph_args.push_back(fg_vnode);
prim_args.emplace_back(nullptr);
hasVNode = true;
} else if (IsValueNode<Primitive>(inputs[i])) {
auto p_vnode = GetValueNode<PrimitivePtr>(inputs[i]);
graph_args.emplace_back(nullptr);
prim_args.push_back(p_vnode);
hasVNode = true;
} else {
graph_args.emplace_back(nullptr);
prim_args.emplace_back(nullptr);
new_xs.push_back(inputs[i]);
}
}
if (!hasVNode) {
return nullptr;
}
auto new_fg = specialize_transform_(inp0_fg, graph_args, prim_args);
(void)new_xs.insert(new_xs.begin(), NewValueNode(new_fg));
return node->func_graph()->NewCNode(new_xs);
}
private:
internal::SpecializeTransform specialize_transform_;
};
} // namespace irpass
} // namespace opt
} // namespace mindspore
#endif // MINDSPORE_CCSRC_OPTIMIZER_IRPASS_SPECIALIZE_TRANSFORM_H_