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- from tinygrad import Device
- from tinygrad.helpers import getenv, DEBUG, BEAM
- from tinygrad.engine.search import beam_search, time_linearizer, bufs_from_lin
- from extra.optimization.helpers import load_worlds, ast_str_to_lin
- if __name__ == "__main__":
- filter_reduce = bool(getenv("FILTER_REDUCE"))
- ast_strs = load_worlds(filter_reduce=filter_reduce, filter_novariable=True)
- dev = Device[Device.DEFAULT]
- test_n = getenv("TEST_N", 10)
- single = getenv("NUM", -1)
- if single != -1: ast_strs = ast_strs[single:single+1]
- beam_won, tested = 0, 0
- for num, ast in enumerate(ast_strs[:test_n]):
- def new_lin(): return ast_str_to_lin(ast, opts=dev.renderer)
- k = new_lin()
- # k.required_optimizations()
- if not (used_tensor_cores:=k.apply_tensor_cores(getenv("TC", 1))): k.hand_coded_optimizations()
- assert BEAM > 0
- lins = [(("tc" if used_tensor_cores else "hc"), k)]
- if used_tensor_cores:
- lins.append(("hc", new_lin()))
- lins[-1][1].hand_coded_optimizations()
- kb = new_lin()
- # kb.required_optimizations()
- test_rawbuffers = bufs_from_lin(kb) # allocate scratch buffers for optimization
- lins.append((f"beam{BEAM.value}", beam_search(kb, test_rawbuffers, BEAM.value, bool(getenv("BEAM_ESTIMATE", 1)))))
- timed = sorted([(nm, tk, time_linearizer(tk, test_rawbuffers, allow_test_size=False, clear_l2=True)) for nm, tk in lins], key=lambda x: x[2])
- if DEBUG >= 1: print(" < ".join(f"{nm:6s} : {lin.colored_shape(30, dense=True)} : {tm*1e6:8.2f} us" for nm, lin, tm in timed))
- tested += 1
- if timed[0][0].startswith("beam"):
- beam_won += 1
- print(f"{beam_won=} / {tested=} = {beam_won/tested:.3f}")
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