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#pragma once
#include <unordered_map>
#include <vector>
#include <torch/csrc/jit/tensorexpr/analysis.h>
#include <torch/csrc/jit/tensorexpr/ir.h>
#include <torch/csrc/jit/tensorexpr/ir_mutator.h>
#include <torch/csrc/jit/tensorexpr/ir_visitor.h>
#include <torch/csrc/jit/tensorexpr/reduction.h>
namespace torch {
namespace jit {
namespace tensorexpr {
using VarMapping = std::vector<std::pair<VarPtr, ExprPtr>>;
class VarSubMutator : public IRMutator {
public:
// NOLINTNEXTLINE(cppcoreguidelines-pro-type-member-init)
VarSubMutator(const VarMapping& var_mapping) {
for (auto& entry : var_mapping) {
VarPtr key_var = entry.first;
ExprPtr value = entry.second;
if (!key_var) {
throw malformed_input("missing key in VarSubMutator");
}
var_mapping_[key_var] = value;
}
}
ExprPtr mutate(VarPtr var) override {
auto iter = var_mapping_.find(var);
if (iter == var_mapping_.end()) {
return var;
}
return iter->second;
}
ExprPtr mutate(ReduceOpPtr var) override {
auto body = var->body()->accept_mutator(this);
// NOLINTNEXTLINE(cppcoreguidelines-init-variables)
std::vector<VarPtr> new_inner;
for (auto v : var->reduce_args()) {
ExprPtr e = v->accept_mutator(this);
if (VarPtr new_var = to<Var>(e)) {
new_inner.push_back(new_var);
} else {
VarFinder varFinder;
e->accept(&varFinder);
auto varlist = varFinder.vars();
new_inner.insert(new_inner.end(), varlist.begin(), varlist.end());
}
}
return alloc<ReduceOp>(body, new_inner, var->reducer());
}
private:
std::unordered_map<VarPtr, ExprPtr> var_mapping_;
};
} // namespace tensorexpr
} // namespace jit
} // namespace torch
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