sum(min_count=1) raises an exception

Start by reproducing the two DataArray.sum calls from the issue with the listed xarray, NumPy, and cupy-xarray versions, comparing the lazy computation graphs before compute(). No source file or test is named, so trace the sum(min_count=1) path into the cupy-backed reduction. Done means the min_count=1 case computes without the reported unsupported numpy.ndarray exception.

The first line works, the second raises an exception

import numpy as np
import xarray as xr
import cupy_xarray

xr.DataArray([1, 2, np.nan]).chunk(dim_0=1).as_cupy().sum().compute()
xr.DataArray([1, 2, np.nan]).chunk(dim_0=1).as_cupy().sum(min_count=1).compute()


xarray.DataArray'asarray-75d4a7ce4023e88c4c5563214cb235b4'
array(3.)
Coordinates: (0)
Indexes: (0)
Attributes: (0)
---------------------------------------------------------------------------
TypeError                                 Traceback (most recent call last)
Cell In[5], line 6
      3 import cupy_xarray
      5 xr.DataArray([1, 2, np.nan]).chunk(dim_0=1).as_cupy().sum().compute()
----> 6 xr.DataArray([1, 2, np.nan]).chunk(dim_0=1).as_cupy().sum(min_count=1).compute()

File [~/mambaforge/envs/cupy-seaice/lib/python3.12/site-packages/xarray/core/dataarray.py:1179](http://localhost:8888/lab/tree/icec/seaice/nb/~/mambaforge/envs/cupy-seaice/lib/python3.12/site-packages/xarray/core/dataarray.py#line=1178), in DataArray.compute(self, **kwargs)
   1154 """Manually trigger loading of this array's data from disk or a
   1155 remote source into memory and return a new array.
   1156 
   (...)
   1176 dask.compute
   1177 """
   1178 new = self.copy(deep=False)
-> 1179 return new.load(**kwargs)

File [~/mambaforge/envs/cupy-seaice/lib/python3.12/site-packages/xarray/core/dataarray.py:1147](http://localhost:8888/lab/tree/icec/seaice/nb/~/mambaforge/envs/cupy-seaice/lib/python3.12/site-packages/xarray/core/dataarray.py#line=1146), in DataArray.load(self, **kwargs)
   1127 def load(self, **kwargs) -> Self:
   1128     """Manually trigger loading of this array's data from disk or a
   1129     remote source into memory and return this array.
   1130 
   (...)
   1145     dask.compute
   1146     """
-> 1147     ds = self._to_temp_dataset().load(**kwargs)
   1148     new = self._from_temp_dataset(ds)
   1149     self._variable = new._variable

File [~/mambaforge/envs/cupy-seaice/lib/python3.12/site-packages/xarray/core/dataset.py:863](http://localhost:8888/lab/tree/icec/seaice/nb/~/mambaforge/envs/cupy-seaice/lib/python3.12/site-packages/xarray/core/dataset.py#line=862), in Dataset.load(self, **kwargs)
    860 chunkmanager = get_chunked_array_type(*lazy_data.values())
    862 # evaluate all the chunked arrays simultaneously
--> 863 evaluated_data: tuple[np.ndarray[Any, Any], ...] = chunkmanager.compute(
    864     *lazy_data.values(), **kwargs
    865 )
    867 for k, data in zip(lazy_data, evaluated_data):
    868     self.variables[k].data = data

File [~/mambaforge/envs/cupy-seaice/lib/python3.12/site-packages/xarray/namedarray/daskmanager.py:86](http://localhost:8888/lab/tree/icec/seaice/nb/~/mambaforge/envs/cupy-seaice/lib/python3.12/site-packages/xarray/namedarray/daskmanager.py#line=85), in DaskManager.compute(self, *data, **kwargs)
     81 def compute(
     82     self, *data: Any, **kwargs: Any
     83 ) -> tuple[np.ndarray[Any, _DType_co], ...]:
     84     from dask.array import compute
---> 86     return compute(*data, **kwargs)

File [~/mambaforge/envs/cupy-seaice/lib/python3.12/site-packages/dask/base.py:662](http://localhost:8888/lab/tree/icec/seaice/nb/~/mambaforge/envs/cupy-seaice/lib/python3.12/site-packages/dask/base.py#line=661), in compute(traverse, optimize_graph, scheduler, get, *args, **kwargs)
    659     postcomputes.append(x.__dask_postcompute__())
    661 with shorten_traceback():
--> 662     results = schedule(dsk, keys, **kwargs)
    664 return repack([f(r, *a) for r, (f, a) in zip(results, postcomputes)])

File cupy[/_core/core.pyx:1717](http://localhost:8888/_core/core.pyx#line=1716), in cupy._core.core._ndarray_base.__array_function__()

File [~/mambaforge/envs/cupy-seaice/lib/python3.12/site-packages/cupy/_sorting/search.py:211](http://localhost:8888/lab/tree/icec/seaice/nb/~/mambaforge/envs/cupy-seaice/lib/python3.12/site-packages/cupy/_sorting/search.py#line=210), in where(condition, x, y)
    209 if fusion._is_fusing():
    210     return fusion._call_ufunc(_where_ufunc, condition, x, y)
--> 211 return _where_ufunc(condition.astype('?'), x, y)

File cupy[/_core/_kernel.pyx:1286](http://localhost:8888/_core/_kernel.pyx#line=1285), in cupy._core._kernel.ufunc.__call__()

File cupy[/_core/_kernel.pyx:159](http://localhost:8888/_core/_kernel.pyx#line=158), in cupy._core._kernel._preprocess_args()

File cupy[/_core/_kernel.pyx:145](http://localhost:8888/_core/_kernel.pyx#line=144), in cupy._core._kernel._preprocess_arg()

TypeError: Unsupported type <class 'numpy.ndarray'>

Versions:

xr.__version__
np.__version__
cupy_xarray.__version__

'2024.6.0'
'1.26.4'
'0.1.3+9.g7fc3df5'

Same thing with numpy 2.0.0