35 lines
1.0 KiB
Python
35 lines
1.0 KiB
Python
import random
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from tqdm import tqdm
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from extra.optimization.helpers import load_worlds, ast_str_to_lin
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from tinygrad.features.search import actions
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from tinygrad.codegen.linearizer import Linearizer
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tactions = set()
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def test_rebuild(lin):
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linr = Linearizer(lin.ast)
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for o in lin.applied_opts:
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assert o in actions, f"{o} is not in actions"
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tactions.add(o)
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linr.apply_opt(o)
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assert len(lin.sts) == len(linr.sts)
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for st1,st2 in zip(lin.sts, linr.sts):
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assert st1 == st2, f"{st1} != {st2}"
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if __name__ == "__main__":
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ast_strs = load_worlds(False, False, False)
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random.shuffle(ast_strs)
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ast_strs = ast_strs[:2000]
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for ast_str in tqdm(ast_strs):
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lin = ast_str_to_lin(ast_str)
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#if not lin.apply_tensor_cores():
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lin.hand_coded_optimizations()
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test_rebuild(lin)
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# confirm linearize can be called twice
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uops1 = lin.linearize().uops
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uops2 = lin.linearize().uops
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assert tuple(uops1) == tuple(uops2), f"uops mismatch {lin.colored_shape()}"
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print(len(tactions), len(actions))
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print(sorted(list(tactions)))
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