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Fix handling of Python scalars in get_incompatible_dtype for NumPy 2.… #3143

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Fix handling of Python scalars in get_incompatible_dtype for NumPy 2.… #3143

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26 changes: 20 additions & 6 deletions deeplake/util/casting.py
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Original file line number Diff line number Diff line change
Expand Up @@ -20,6 +20,17 @@ def _get_bigger_dtype(d1, d2):
return np.object


# Map Python scalar types to their default NumPy equivalents.
# NumPy 2.x (NEP 50) no longer accepts raw Python scalars in np.can_cast,
# so we resolve them to a concrete dtype before calling can_cast.
_PYTHON_TYPE_TO_NUMPY_DTYPE = {
float: np.float64,
int: np.int64,
bool: np.bool_,
complex: np.complex128,
}


def get_dtype(val: Union[np.ndarray, Sequence, Sample]) -> np.dtype:
"""Get the dtype of a non-uniform mixed dtype sequence of samples."""

Expand Down Expand Up @@ -133,12 +144,15 @@ def get_incompatible_dtype(
elif samples.size == 1:
samples = samples.reshape(1).tolist()[0]

if isinstance(samples, (int, float, bool)) or hasattr(samples, "dtype"):
return (
None
if np.can_cast(samples, dtype)
else getattr(samples, "dtype", np.array(samples).dtype)
)
py_type = type(samples)
if py_type in _PYTHON_TYPE_TO_NUMPY_DTYPE:
# NumPy 2.x (NEP 50) removed support for passing raw Python scalars to
# np.can_cast. Convert to the equivalent NumPy dtype first.
from_dtype = _PYTHON_TYPE_TO_NUMPY_DTYPE[py_type]
return None if np.can_cast(from_dtype, dtype, casting="same_kind") else from_dtype
elif hasattr(samples, "dtype"):
from_dtype = samples.dtype
return None if np.can_cast(from_dtype, dtype, casting="same_kind") else from_dtype
elif isinstance(samples, str):
return None if dtype == np.dtype(str) else np.dtype(str)
elif isinstance(samples, Sequence):
Expand Down