pytorch/benchmarks/cpp/tensorexpr/bench_compile.cpp
Mikhail Zolotukhin 7ab654afd7 [TensorExpr] Rename Tensor::call to Tensor::load to be consistent with Buf and Placeholder. (#55826)
Summary:
Pull Request resolved: https://github.com/pytorch/pytorch/pull/55826

It's a mechanical change.

Differential Revision: D27717777

Test Plan: Imported from OSS

Reviewed By: navahgar

Pulled By: ZolotukhinM

fbshipit-source-id: fbc1bb99602250c706cf2c8c2684119c323e4d51
2021-04-13 12:08:53 -07:00

75 lines
2.7 KiB
C++

#include <benchmark/benchmark.h>
#include <torch/csrc/jit/tensorexpr/ir_simplifier.h>
#include <torch/csrc/jit/tensorexpr/loopnest.h>
#include <torch/csrc/jit/tensorexpr/tensor.h>
#include <torch/csrc/jit/tensorexpr/llvm_codegen.h>
#ifdef TORCH_ENABLE_LLVM
namespace te = torch::jit::tensorexpr;
static void BM_CompileSwish(benchmark::State& state) {
for (auto _ : state) {
constexpr int N = 512;
te::KernelScope ks;
te::VarHandle n("n", te::kInt);
te::Placeholder A(te::BufHandle("A", {N}, te::kFloat));
te::Tensor* relu = te::Compute("relu", {{n, "n"}}, [&](const te::VarHandle& i) {
return te::Max::make(A.load(i), 0.f, false);
});
te::Tensor* min6 = te::Compute("min6", {{n, "n"}}, [&](const te::VarHandle& i) {
return te::Min::make(relu->load(i), 6.f, false);
});
te::Tensor* plus3 = te::Compute("plus3", {{n, "n"}}, [&](const te::VarHandle& i) {
return min6->load(i) + 3.f;
});
te::Tensor* times = te::Compute("times", {{n, "n"}}, [&](const te::VarHandle& i) {
return A.load(i) * plus3->load(i);
});
te::Tensor* sixth = te::Compute("sixth", {{n, "n"}}, [&](const te::VarHandle& i) {
return times->load(i) * 1.f / 6.f;
});
te::LoopNest nest({sixth}, {relu, min6, plus3, times, sixth});
for (auto tensor : {relu, min6, plus3, times}) {
nest.computeInline(tensor->buf());
}
nest.prepareForCodegen();
te::Stmt* s = te::IRSimplifier::simplify(nest.root_stmt());
te::LLVMCodeGen cg(s, {A, sixth, n});
}
}
static void BM_CompileSwishLLVMOnly(benchmark::State& state) {
constexpr int N = 512;
te::KernelScope ks;
te::VarHandle n("n", te::kInt);
te::Placeholder A(te::BufHandle("A", {N}, te::kFloat));
te::Tensor* relu = te::Compute("relu", {{n, "n"}}, [&](const te::VarHandle& i) {
return te::Max::make(A.load(i), 0.f, false);
});
te::Tensor* min6 = te::Compute("min6", {{n, "n"}}, [&](const te::VarHandle& i) {
return te::Min::make(relu->load(i), 6.f, false);
});
te::Tensor* plus3 = te::Compute("plus3", {{n, "n"}}, [&](const te::VarHandle& i) {
return min6->load(i) + 3.f;
});
te::Tensor* times = te::Compute("times", {{n, "n"}}, [&](const te::VarHandle& i) {
return A.load(i) * plus3->load(i);
});
te::Tensor* sixth = te::Compute("sixth", {{n, "n"}}, [&](const te::VarHandle& i) {
return times->load(i) * 1.f / 6.f;
});
te::LoopNest nest({sixth}, {relu, min6, plus3, times, sixth});
for (auto tensor : {relu, min6, plus3, times}) {
nest.computeInline(tensor->buf());
}
nest.prepareForCodegen();
te::Stmt* s = te::IRSimplifier::simplify(nest.root_stmt());
for (auto _ : state) {
te::LLVMCodeGen cg(s, {A, sixth, n});
}
}
BENCHMARK(BM_CompileSwish);
BENCHMARK(BM_CompileSwishLLVMOnly);
#endif // TORCH_ENABLE_LLVM