Skip to content

Fix non-contiguous reshapes in numba backend #255

New issue

Have a question about this project? Sign up for a free GitHub account to open an issue and contact its maintainers and the community.

Sign up for GitHub

By clicking “Sign up for GitHub”, you agree to our terms of service and privacy statement. We’ll occasionally send you account related emails.

Already on GitHub? Sign in to your account

Merged
merged 1 commit into from
Mar 20, 2023
Merged

Fix non-contiguous reshapes in numba backend #255

Show file tree
Hide file tree
Changes from all commits
Commits
Show all changes
1 commit
Select commit
File filter

Filter by extension

Filter by extension
Conversations
Failed to load comments.
Loading
Jump to
Jump to file
Failed to load files.
Loading
Diff view
Diff view
2 changes: 1 addition & 1 deletion pytensor/link/numba/dispatch/elemwise.py
View file
Open in desktop
Original file line number Diff line number Diff line change
Expand Up @@ -841,7 +841,7 @@ def dimshuffle_inner(x, shuffle):

@numba_basic.numba_njit
def dimshuffle_inner(x, shuffle):
return np.reshape(x, ())
return np.reshape(np.ascontiguousarray(x), ())

# Without the following wrapper function we would see this error:
# E No implementation of function Function(<built-in function getitem>) found for signature:
Expand Down
11 changes: 11 additions & 0 deletions tests/link/numba/test_elemwise.py
View file
Open in desktop
Original file line number Diff line number Diff line change
Expand Up @@ -218,6 +218,17 @@ def test_Dimshuffle_returns_array():
assert out.ndim == 0


def test_Dimshuffle_non_contiguous():
"""The numba impl of reshape doesn't work with
non-contiguous arrays, make sure we work around that."""
x = at.dvector()
idx = at.vector(dtype="int64")
op = pytensor.tensor.elemwise.DimShuffle([True], [])
out = op(at.specify_shape(x[idx][::2], (1,)))
func = pytensor.function([x, idx], out, mode="NUMBA")
assert func(np.zeros(3), np.array([1])).ndim == 0


@pytest.mark.parametrize(
"careduce_fn, axis, v",
[
Expand Down