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id node_id number title user state locked assignee milestone comments created_at updated_at ▲ closed_at author_association active_lock_reason draft pull_request body reactions performed_via_github_app state_reason repo type
1321228754 I_kwDOAMm_X85OwFnS 6845 Do we need to update AbstractArray for duck arrays? dcherian 2448579 open 0     6 2022-07-28T16:59:59Z 2022-07-29T17:20:39Z   MEMBER      

What happened?

I'm calling cupy.round on a DataArray wrapping a cupy array and it raises an error here: https://github.com/pydata/xarray/blob/3f7cc2da33d81e76afbfb82da57143b624b03a88/xarray/core/common.py#L155-L156

Traceback below:

``` --> 25 a = _core.array(a, copy=False) 26 return a.round(decimals, out=out) 27 cupy/_core/core.pyx in cupy._core.core.array() cupy/_core/core.pyx in cupy._core.core.array() cupy/_core/core.pyx in cupy._core.core._array_default() ~/miniconda3/envs/gpu/lib/python3.7/site-packages/xarray/core/common.py in __array__(self, dtype) 146 147 def __array__(self: Any, dtype: DTypeLike = None) -> np.ndarray: --> 148 return np.asarray(self.values, dtype=dtype) 149 150 def __repr__(self) -> str: ~/miniconda3/envs/gpu/lib/python3.7/site-packages/xarray/core/dataarray.py in values(self) 644 type does not support coercion like this (e.g. cupy). 645 """ --> 646 return self.variable.values 647 648 @values.setter ~/miniconda3/envs/gpu/lib/python3.7/site-packages/xarray/core/variable.py in values(self) 517 def values(self): 518 """The variable's data as a numpy.ndarray""" --> 519 return _as_array_or_item(self._data) 520 521 @values.setter ~/miniconda3/envs/gpu/lib/python3.7/site-packages/xarray/core/variable.py in _as_array_or_item(data) 257 TODO: remove this (replace with np.asarray) once these issues are fixed 258 """ --> 259 data = np.asarray(data) 260 if data.ndim == 0: 261 if data.dtype.kind == "M": cupy/_core/core.pyx in cupy._core.core.ndarray.__array__() TypeError: Implicit conversion to a NumPy array is not allowed. Please use `.get()` to construct a NumPy array explicitly. ```

What did you expect to happen?

Not an error? I'm not sure what's expected

np.round(dataarray) does actually work successfully.

My question is : Do we need to update AbstractArray.__array__ to return the underlying duck array instead of always a numpy array?

Minimal Complete Verifiable Example

No response

MVCE confirmation

  • [ ] Minimal example — the example is as focused as reasonably possible to demonstrate the underlying issue in xarray.
  • [ ] Complete example — the example is self-contained, including all data and the text of any traceback.
  • [ ] Verifiable example — the example copy & pastes into an IPython prompt or Binder notebook, returning the result.
  • [ ] New issue — a search of GitHub Issues suggests this is not a duplicate.

Relevant log output

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Anything else we need to know?

No response

Environment

xarray v2022.6.0 cupy 10.6.0 
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     xarray 13221727 issue

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