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# pyre-strict
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import copy
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+ from functools import lru_cache
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from typing import List , OrderedDict , Tuple
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import torch
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from facto .inputgen .argtuple .gen import ArgumentTupleGenerator
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from facto .inputgen .specs .model import ConstraintProducer as cp
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- from facto .inputgen .utils .random_manager import random_manager
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from facto .inputgen .variable .type import ScalarDtype
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from facto .specdb .db import SpecDictDB
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# seed to generate identical cases every run to reproduce from bisect
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- random_manager .seed (1729 )
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MAX_CASES = 50
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@@ -104,6 +103,7 @@ def apply_scalar_contraints(op_name: str) -> list[ScalarDtype]:
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return [ScalarDtype .float , ScalarDtype .int ]
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+ @lru_cache (maxsize = None )
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def facto_testcase_gen (op_name : str ) -> List [Tuple [List [str ], OrderedDict [str , str ]]]:
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# minimal example to test add.Tensor using FACTO
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spec = SpecDictDB [op_name ]
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