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test(torch): cover low-precision outlier does not overflow in squashing scaler #1368

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test(torch): cover low-precision outlier does not overflow in squashing scaler #1368

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20 changes: 20 additions & 0 deletions tests/test_torch_preprocessing/test_torch_squashing_scaler.py
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Original file line number Diff line number Diff line change
Expand Up @@ -439,3 +439,23 @@ def test__blocked_transform_does_not_write_to_its_input(
_run_with_budgets(patch, _FORCE_BLOCKED, x, 64, 3.0)

_assert_bit_identical("input tensor", x, before)


@pytest.mark.parametrize("outlier", [1000.0, -1000.0])
@pytest.mark.parametrize("dtype", [torch.float16, torch.bfloat16])
def test__call__low_precision_outlier_does_not_overflow(
outlier: float, dtype: torch.dtype
) -> None:
# Both low-precision dtypes take the upcast path, so both need the cover.
scaler = TorchSquashingScaler()
x = torch.tensor(
[0, 1, 1, 1, 2, outlier],
dtype=dtype,
).unsqueeze(-1)

out = scaler(x, num_train_rows=5)

assert out.dtype == dtype
assert torch.isfinite(out).all()
assert 2.5 < abs(out[-1, 0].item()) <= 3.0
assert out[-1, 0].item() * outlier > 0
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