use a fast expand algorithm #135999
use a fast expand algorithm #135999
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🔗 Helpful Links🧪 See artifacts and rendered test results at hud.pytorch.org/pr/135999
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| try: | ||
| return sympy.expand(r) | ||
| return fast_expand(r) | ||
| except RecursionError: |
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btw it might be OK to remove the hasattr/RecursionError guarding with the change now, if it's now trivially obvious we won't blow out the stack expanding with the new code
| IndicatorTypes = (IsNonOverlappingAndDenseIndicator,) | ||
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| def _expandsums(args): |
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at least a teeny type signature would be nice lol
| for add in adds: | ||
| result = [a * b for a, b in itertools.product(result, add.args)] | ||
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| result = sympy.Add(*result) |
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Can't do make_args I guess, since we have to combine common terms
| # checks when re-creating objects. | ||
| new_args = [fast_expand(arg) for arg in expr.args] | ||
| if any(arg is not new_arg for arg, new_arg in zip(expr.args, new_args)): | ||
| return fast_expand(expr.func(*new_args)) |
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ok, RecursionError danger here, I guess
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Yes. However I'm not sure if replacing this line with expr = expr.func(*new_args) would work.
| if exp > 1: | ||
| return sympy.expand_multinomial(expr, deep=False) | ||
| elif exp < 0: | ||
| return 1 / sympy.expand_multinomial(1 / expr, deep=False) |
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I think this is impossible, because I added a FloatPow for this case
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@pytorchbot merge |
Merge startedYour change will be merged once all checks pass (ETA 0-4 Hours). Learn more about merging in the wiki. Questions? Feedback? Please reach out to the PyTorch DevX Team |
Pull Request resolved: pytorch#135999 Approved by: https://github.com/ezyang
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