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)))