jax.numpy reductions: avoid upcast of f16 when dtype is specified by user #26403
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jakevdp
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superbobry
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Feb 12, 2025
| @@ -231,7 +231,7 @@ def _reduce_sum(a: ArrayLike, axis: Axis = None, dtype: DTypeLike | None = None, | |||
| initial: ArrayLike | None = None, where: ArrayLike | None = None, | |||
| promote_integers: bool = True) -> Array: | |||
| return _reduction(a, "sum", lax.add, 0, preproc=_cast_to_numeric, | |||
| bool_op=lax.bitwise_or, upcast_f16_for_computation=True, | |||
| bool_op=lax.bitwise_or, upcast_f16_for_computation=(dtype is None), | |||
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Nit: you can drop parens around dtype is None here and elsewhere.
Agreed, we'll have to adjust tolerances for cases where the behavior has changed |
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Fixes #26365