def normalize_binop_value(self, other):
if other is None:
return other
if isinstance(other, cudf.Scalar):
# expensive device-host transfer just to
# adjust the dtype
other = other.value
elif isinstance(other, np.ndarray) and other.ndim == 0:
other = other.item()
other_dtype = np.min_scalar_type(other)
if other_dtype.kind in {"b", "i", "u", "f"}:
if isinstance(other, cudf.Scalar):
return other
other_dtype = np.promote_types(self.dtype, other_dtype)
if other_dtype == np.dtype("float16"):
other = np.dtype("float32").type(other)
other_dtype = other.dtype
if self.dtype.kind == "b":
other_dtype = min_signed_type(other)
if np.isscalar(other):
other = np.dtype(other_dtype).type(other)
return other
else:
ary = utils.scalar_broadcast_to(other,
size=len(self),
dtype=other_dtype)
return column.build_column(
data=Buffer.from_array_lik(ary),
dtype=ary.dtype,
mask=self.mask,
)
else:
raise TypeError(f"cannot broadcast {type(other)}")
def normalize_binop_value(self, other):
if other is None:
return other
other_dtype = np.min_scalar_type(other)
if other_dtype.kind in {"b", "i", "u", "f"}:
other_dtype = np.promote_types(self.dtype, other_dtype)
if other_dtype == np.dtype("float16"):
other = np.dtype("float32").type(other)
other_dtype = other.dtype
if self.dtype.kind == "b":
other_dtype = min_signed_type(other)
if np.isscalar(other):
other = np.dtype(other_dtype).type(other)
return other
else:
ary = utils.scalar_broadcast_to(other,
size=len(self),
dtype=other_dtype)
return column.build_column(
data=Buffer.from_array_lik(ary),
dtype=ary.dtype,
mask=self.mask,
)
else:
raise TypeError("cannot broadcast {}".format(type(other)))
