issues: 287223508

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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
287223508 MDU6SXNzdWUyODcyMjM1MDg= 1815 apply_ufunc(dask='parallelized') with multiple outputs 2443309 closed 0     17 2018-01-09T20:40:52Z 2020-08-19T06:57:55Z 2020-08-19T06:57:55Z MEMBER      

I have an application where I'd like to use apply_ufunc with dask on a function that requires multiple inputs and outputs. This was left as a TODO item in the #1517. However, its not clear to me looking at the code how this can be done given the current form of dask's atop. I'm hoping @shoyer has already thought of a clever solution here...

Code Sample, a copy-pastable example if possible

```python def func(foo, bar):

assert foo.shape == bar.shape
spam = np.zeros_like(bar)
spam2 = np.full_like(bar, 2)


return spam, spam2

foo = xr.DataArray(np.zeros((10, 10))).chunk() bar = xr.DataArray(np.zeros((10, 10))).chunk() + 5

xrfunc = xr.apply_ufunc(func, foo, bar, output_core_dims=[[], []], dask='parallelized') ```

Problem description

This currently raises a NotImplementedError.

Expected Output

Multiple dask arrays. In my example above, two dask arrays.

Output of xr.show_versions()

INSTALLED VERSIONS ------------------ commit: None python: 3.6.4.final.0 python-bits: 64 OS: Linux OS-release: 4.4.86+ machine: x86_64 processor: x86_64 byteorder: little LC_ALL: en_US.UTF-8 LANG: en_US.UTF-8 LOCALE: en_US.UTF-8 xarray: 0.10.0+dev.c92020a pandas: 0.22.0 numpy: 1.13.3 scipy: 1.0.0 netCDF4: 1.3.1 h5netcdf: 0.5.0 Nio: None zarr: 2.2.0a2.dev176 bottleneck: 1.2.1 cyordereddict: None dask: 0.16.0 distributed: 1.20.2+36.g7387410 matplotlib: 2.1.1 cartopy: None seaborn: None setuptools: 38.4.0 pip: 9.0.1 conda: 4.3.29 pytest: 3.3.2 IPython: 6.2.1 sphinx: None

cc @mrocklin, @arbennett

 
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   completed 13221727 issue

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