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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
684930038 MDU6SXNzdWU2ODQ5MzAwMzg= 4372 Set `allow_rechunk=True` in `apply_ufunc` dcherian 2448579 closed 0     10 2020-08-24T20:02:50Z 2020-09-09T19:00:17Z 2020-09-09T19:00:17Z MEMBER      

What happened:

blockwise calls unify_chunks by default but apply_gufunc does not; so we have a regression in apply_ufunc now that we've switched from blockwise to apply_gufunc.

Minimal Complete Verifiable Example:

```python import operator

a = xr.DataArray(np.arange(10), dims=("a")).chunk({"a": 2}) b = xr.DataArray(np.arange(10), dims=("a")).chunk({"a": 4})

xr.apply_ufunc(operator.add, a, b, dask="parallelized", output_dtypes=[a.dtype]).compute() ```

raises ValueError: Dimension `'__loopdim0__'` with different chunksize present

on master but works with 0.16.0

I think we need to do dask_gufunc_kwargs.setdefault("allow_rechunk", True)

If we want to avoid that, we'll need to go through a deprecation cycle.

 
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   completed xarray 13221727 issue

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