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Fix torch pad: (before, after) pairs were swapped for asymmetric pad_width #36

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Merged
jcmgray merged 1 commit into from
Aug 16, 2026
Merged

Fix torch pad: (before, after) pairs were swapped for asymmetric pad_width #36

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3 changes: 2 additions & 1 deletion autoray/autoray.py
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Original file line number Diff line number Diff line change
Expand Up @@ -4124,7 +4124,8 @@ def torch_pad(array, pad_width, mode="constant", constant_values=0):
try:
# numpy takes pads like ((0, 0), (1, 1), ... (n-1, n-1))
# torch takes pads like (n-1, n-1, n-2, n-2, n-3, n-3, ...)
pad = tuple(itertools.chain.from_iterable(pad_width))[::-1]
# i.e. axes reversed, but each (before, after) pair kept in order
pad = tuple(itertools.chain.from_iterable(reversed(pad_width)))

# a single tuple was specified ((a, b),) - use for all axes
if len(pad) == 2:
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6 changes: 6 additions & 0 deletions tests/test_autoray.py
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Expand Up @@ -418,12 +418,18 @@ def test_pad(backend):
(((1, 2),), (6, 7, 8)),
# different pad for every axis
(((4, 3), (2, 4), (3, 2)), (10, 10, 10)),
# asymmetric, including zero pads
(((0, 1), (2, 0), (3, 1)), (4, 6, 9)),
]:
B = ar.do("pad", A, pad_width)
assert shape(B) == new_shape
assert ar.to_numpy(ar.do("sum", A)) == pytest.approx(
ar.to_numpy(ar.do("sum", B))
)
# check the padding is placed the same way numpy places it
np.testing.assert_allclose(
ar.to_numpy(B), np.pad(ar.to_numpy(A), pad_width)
)


@pytest.mark.parametrize("backend", gen_params(backends=...))
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