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#pragma once
#include <unordered_map>
#include <vector>
#include <torch/csrc/Export.h>
#include <torch/csrc/jit/tensorexpr/mem_dependency_checker.h>
namespace torch::jit::tensorexpr {
class Expr;
class Buf;
class Stmt;
enum C10_API_ENUM TensorAccessKind { kLoad, kStore, kMutate };
struct TORCH_API TensorAccessBoundsInfo {
TensorAccessKind kind;
std::vector<ExprPtr> start;
std::vector<ExprPtr> stop;
};
using BoundsInfo =
std::unordered_map<BufPtr, std::vector<TensorAccessBoundsInfo>>;
TORCH_API BoundsInfo
inferBounds(const StmtPtr& s, bool distinctAccessKinds = true);
// Bounds inference caching the analysis. The MemDependencyChecker must already
// have been run.
TORCH_API BoundsInfo getInferredBounds(
analysis::MemDependencyChecker& analyzer,
const StmtPtr& s,
bool distinctAccessKinds = true);
TORCH_API BoundsInfo getInferredBounds(
analysis::MemDependencyChecker& analyzer,
const ExprPtr& e,
bool distinctAccessKinds = true);
TORCH_API void printBoundsInfo(const BoundsInfo& v);
TORCH_API std::vector<ExprPtr> getBoundExtents(
const std::vector<TensorAccessBoundsInfo>& infos);
// The kind of dependency found, in increasing order of exclusivity.
enum class HazardKind {
ReadAfterWrite,
WriteAfterRead,
WriteAfterWrite,
NoDependency,
};
TORCH_API HazardKind getPotentialHazards(
analysis::MemDependencyChecker& analyzer,
const StmtPtr& A,
const StmtPtr& B);
// Returns true if there is a conflicting overlap between accesses in
// statements A and B. A conflicting overlap is an overlap in buffer accesses
// where at least one of the accesses is a Store.
TORCH_API bool hasConflictingOverlap(
analysis::MemDependencyChecker& analyzer,
const StmtPtr& A,
const StmtPtr& B);
// Same as above, between accesses in stores S1 and S2.
TORCH_API bool isOverlapping(
analysis::MemDependencyChecker& analyzer,
const StorePtr& S1,
const StorePtr& S2);
// Same as above, between accesses in store S and load L.
TORCH_API bool isOverlapping(
analysis::MemDependencyChecker& analyzer,
const StorePtr& S,
const LoadPtr& L);
} // namespace torch::jit::tensorexpr
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