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Don't use numba objectmode with vector boolean inc_subtensor #1243

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Merged
merged 1 commit into from
Feb 24, 2025
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Don't use numba objectmode with vector boolean inc_subtensor #1243

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10 changes: 8 additions & 2 deletions pytensor/link/numba/dispatch/subtensor.py
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Original file line number Diff line number Diff line change
Expand Up @@ -130,7 +130,6 @@ def numba_funcify_AdvancedSubtensor(op, node, **kwargs):
if isinstance(idx.type, TensorType)
]

# Special case for consecutive consecutive vector indices
def broadcasted_to(x_bcast: tuple[bool, ...], to_bcast: tuple[bool, ...]):
# Check that x is not broadcasted to y based on broadcastable info
if len(x_bcast) < len(to_bcast):
Expand Down Expand Up @@ -176,7 +175,14 @@ def broadcasted_to(x_bcast: tuple[bool, ...], to_bcast: tuple[bool, ...]):
or (
isinstance(op, AdvancedIncSubtensor)
and not op.set_instead_of_inc
and not op.ignore_duplicates
and not (
op.ignore_duplicates
# Only vector integer indices can have "duplicates", not scalars or boolean vectors
or all(
adv_idx["ndim"] == 0 or adv_idx["dtype"] == "bool"
for adv_idx in adv_idxs
)
)
)
):
return generate_fallback_impl(op, node, **kwargs)
Expand Down
8 changes: 8 additions & 0 deletions tests/link/numba/test_subtensor.py
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Expand Up @@ -314,8 +314,16 @@ def test_AdvancedIncSubtensor1(x, y, indices):
np.arange(3 * 4 * 5).reshape((3, 4, 5)),
-np.arange(1 * 4 * 5).reshape(1, 4, 5),
(np.array([True, False, False])), # Broadcasted boolean index
False, # It shouldn't matter what we set this to, boolean indices cannot be duplicate
False,
False,
),
(
np.arange(3 * 4 * 5).reshape((3, 4, 5)),
-np.arange(1 * 4 * 5).reshape(1, 4, 5),
(np.array([True, False, False])), # Broadcasted boolean index
True, # It shouldn't matter what we set this to, boolean indices cannot be duplicate
False,
False,
),
(
Expand Down