[dynamo] add benchmark for guard eval (#142430)

Benchmarks:
- 713.2us (3.10)
- 598.8us (3.12)

Pull Request resolved: https://github.com/pytorch/pytorch/pull/142430
Approved by: https://github.com/jansel
ghstack dependencies: #142117

benchmarks/dynamo/microbenchmarks/dynamo_guard_eval.py

@@ -0,0 +1,46 @@
+import time
+import timeit
+
+import numpy as np
+
+import torch
+import torch._dynamo.config
+
+
+# to satisfy linter complaining about undefined variable
+foo = None
+
+args = [f"x{i}" for i in range(100)]
+fn_str = f"""\
+def foo({", ".join(args)}):
+    n = {" + ".join(arg + ".shape[0]" for arg in args)}
+    return x0 + n
+"""
+
+exec(fn_str, globals())
+torch._dynamo.config.cache_size_limit = 16
+
+
+def bench(name, fn):
+    torch._dynamo.reset()
+    inps = [[torch.randn(i) for _ in range(100)] for i in range(10, 101, 10)]
+
+    def run_fn():
+        for inp in inps:
+            fn(*inp)
+
+    start = time.perf_counter()
+    for _ in range(3):
+        run_fn()
+    end = time.perf_counter()
+
+    results = timeit.repeat(lambda: run_fn(), number=1000, repeat=10)
+    print(f"{name} {np.median(results) * 1000:.1f}us (warmup={end - start:.1f}s)")
+
+
+def main():
+    bench("compiled", torch.compile(foo, dynamic=False))  # type: ignore[F821]
+
+
+if __name__ == "__main__":
+    main()