html_url,issue_url,id,node_id,user,created_at,updated_at,author_association,body,reactions,performed_via_github_app,issue
https://github.com/pydata/xarray/pull/3117#issuecomment-511172148,https://api.github.com/repos/pydata/xarray/issues/3117,511172148,MDEyOklzc3VlQ29tbWVudDUxMTE3MjE0OA==,13301940,2019-07-14T04:25:07Z,2019-07-14T04:28:00Z,MEMBER,"@nvictus, thank you for your work! 

I just tried this on CuPy arrays, and it seems to be working during array creation: 

```python
In [1]: import cupy as cp                                                           

In [2]: import xarray as xr                                                         

In [3]: x = cp.arange(6).reshape(2, 3).astype('f')                                  

In [4]: y = cp.ones((2, 3), dtype='int')                           

In [5]: x                                                          
Out[5]: 
array([[0., 1., 2.],
       [3., 4., 5.]], dtype=float32)

In [6]: y                                                          
Out[6]: 
array([[1, 1, 1],
       [1, 1, 1]])

In [7]: y.device                                                   
Out[7]: <CUDA Device 0>

In [8]: x.device                                                   
Out[8]: <CUDA Device 0>

In [9]: ds = xr.Dataset()                                          

In [10]: ds['x'] = xr.DataArray(x, dims=['lat', 'lon'])            

In [11]: ds['y'] = xr.DataArray(y, dims=['lat', 'lon'])            

In [12]: ds                                                        
Out[12]: 
<xarray.Dataset>
Dimensions:  (lat: 2, lon: 3)
Dimensions without coordinates: lat, lon
Data variables:
    x        (lat, lon) float32 ...
    y        (lat, lon) int64 ...

In [13]: ds.x.data.device                                          
Out[13]: <CUDA Device 0>

In [14]: ds.y.data.device                                          
Out[14]: <CUDA Device 0>
```

 

Even though it failed when I tried applying an operation on the dataset, this is still awesome! I am very excited and looking forward to seeing this feature in xarray:

```python
In [15]: m = ds.mean(dim='lat')                                    
-------------------------------------------------------------------
TypeError                         Traceback (most recent call last)
<ipython-input-15-8e4d5e7d5ee3> in <module>
----> 1 m = ds.mean(dim='lat')

/glade/work/abanihi/devel/pangeo/xarray/xarray/core/common.py in wrapped_func(self, dim, skipna, **kwargs)
     65                 return self.reduce(func, dim, skipna=skipna,
     66                                    numeric_only=numeric_only, allow_lazy=True,
---> 67                                    **kwargs)
     68         else:
     69             def wrapped_func(self, dim=None, **kwargs):  # type: ignore

/glade/work/abanihi/devel/pangeo/xarray/xarray/core/dataset.py in reduce(self, func, dim, keep_attrs, keepdims, numeric_only, allow_lazy, **kwargs)
   3532                                                  keepdims=keepdims,
   3533                                                  allow_lazy=allow_lazy,
-> 3534                                                  **kwargs)
   3535 
   3536         coord_names = set(k for k in self.coords if k in variables)

/glade/work/abanihi/devel/pangeo/xarray/xarray/core/variable.py in reduce(self, func, dim, axis, keep_attrs, keepdims, allow_lazy, **kwargs)
   1392         input_data = self.data if allow_lazy else self.values
   1393         if axis is not None:
-> 1394             data = func(input_data, axis=axis, **kwargs)
   1395         else:
   1396             data = func(input_data, **kwargs)

/glade/work/abanihi/devel/pangeo/xarray/xarray/core/duck_array_ops.py in mean(array, axis, skipna, **kwargs)
    370         return _to_pytimedelta(mean_timedeltas, unit='us') + offset
    371     else:
--> 372         return _mean(array, axis=axis, skipna=skipna, **kwargs)
    373 
    374 

/glade/work/abanihi/devel/pangeo/xarray/xarray/core/duck_array_ops.py in f(values, axis, skipna, **kwargs)
    257 
    258         try:
--> 259             return func(values, axis=axis, **kwargs)
    260         except AttributeError:
    261             if isinstance(values, dask_array_type):

/glade/work/abanihi/devel/pangeo/xarray/xarray/core/nanops.py in nanmean(a, axis, dtype, out)
    158         return dask_array.nanmean(a, axis=axis, dtype=dtype)
    159 
--> 160     return np.nanmean(a, axis=axis, dtype=dtype)
    161 
    162 

/glade/work/abanihi/softwares/miniconda3/envs/xarray-tests/lib/python3.7/site-packages/numpy/core/overrides.py in public_api(*args, **kwargs)
    163             relevant_args = dispatcher(*args, **kwargs)
    164             return implement_array_function(
--> 165                 implementation, public_api, relevant_args, args, kwargs)
    166 
    167         if module is not None:

TypeError: no implementation found for 'numpy.nanmean' on types that implement __array_function__: [<class 'cupy.core.core.ndarray'>]
```



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