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#pragma once
#include <torch/csrc/jit/tensorexpr/codegen.h>
#include <torch/csrc/jit/tensorexpr/ir.h>
#include <torch/csrc/jit/tensorexpr/ir_simplifier.h>
#include <torch/csrc/jit/tensorexpr/llvm_codegen.h>
#include <torch/csrc/jit/tensorexpr/loopnest.h>
namespace torch {
namespace jit {
class TEWrapper {
public:
TEWrapper() = default;
void call(const std::vector<void*>& args);
template <typename ExpectedType>
bool checkInput(const at::Tensor& t) {
#ifdef TORCH_ENABLE_LLVM
return t.is_contiguous() && t.dtype().Match<ExpectedType>();
#else
return false;
#endif
}
#ifdef TORCH_ENABLE_LLVM
void update(std::unique_ptr<tensorexpr::LLVMCodeGen>&& cg_);
#endif
private:
#ifdef TORCH_ENABLE_LLVM
std::unique_ptr<tensorexpr::LLVMCodeGen> cg;
#endif
};
std::shared_ptr<TEWrapper> createDiv();
std::shared_ptr<TEWrapper> createLogit();
std::shared_ptr<TEWrapper> createRelu();
std::shared_ptr<TEWrapper> createTanh();
std::shared_ptr<TEWrapper> createSigmoid();
std::shared_ptr<TEWrapper> createSignedLog1p();
std::shared_ptr<TEWrapper> createClamp();
std::shared_ptr<TEWrapper> createClampNanToNum();
} // namespace jit
} // namespace torch
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