Related to #4212

When trying to get the Calculating Seasonal Averages from Timeseries of Monthly Means example from the documentation to work with cupy I'm experiencing an unexpected Unsupported type <class 'numpy.ndarray'> error when calling ds_unweighted = ds.groupby('time.season').mean('time')

I dug through this with @quasiben and it seems to be related to the as_shared_dtype function.

What happened:

Running the MCVE below results in Unsupported type <class 'numpy.ndarray'>. It seems at somewhere in the stack there is a call to _replace_nan(a, 0) where the cupy array is having nan values replaced with 0. This ends up as a call to xarray.core.duck_array_ops.where with the "is nan", 0 and the cupy array being passed.

However _where calls as_shared_dtype on the 0 and cupy array, which converts the 0 to a scalar numpy array.

Cupy is then passed this numpy array to it's where function which does raises the exception.

What you expected to happen:

The cupy.where function can either take a Python int/float or a cupy array, not a numpy scalar.

Therefore a few things could be done here: 1. Xarray could not convert the int/float to a numpy array 1. It could convert it to a cupy array 1. Cupy could be modified to accept a numpy scalar.

We thew together a quick fix for option 2, which I'll put in a draft PR. But happy to discuss the alternatives.

Minimal Complete Verifiable Example:

```python import numpy as np import pandas as pd import xarray as xr import matplotlib.pyplot as plt

import cupy as cp

Load data

ds = xr.tutorial.open_dataset("rasm").load()

Move data to GPU

ds.Tair.data = cp.asarray(ds.Tair.data)

ds_unweighted = ds.groupby("time.season").mean("time")

Calculate the weights by grouping by 'time.season'.

month_length = ds.time.dt.days_in_month weights = ( month_length.groupby("time.season") / month_length.groupby("time.season").sum() )

Test that the sum of the weights for each season is 1.0

np.testing.assert_allclose(weights.groupby("time.season").sum().values, np.ones(4))

Move weights to GPU

weights.data = cp.asarray(weights.data)

Calculate the weighted average

ds_weighted = ds * weights ds_weighted = ds_weighted.groupby("time.season") ds_weighted = ds_weighted.sum(dim="time") ```

Traceback

```python-traceback Traceback (most recent call last): File "/home/jacob/miniconda3/envs/dask/lib/python3.7/runpy.py", line 193, in _run_module_as_main "__main__", mod_spec) File "/home/jacob/miniconda3/envs/dask/lib/python3.7/runpy.py", line 85, in _run_code exec(code, run_globals) File "/home/jacob/.vscode-server/extensions/ms-python.python-2020.6.91350/pythonFiles/lib/python/debugpy/__main__.py", line 45, in <module> cli.main() File "/home/jacob/.vscode-server/extensions/ms-python.python-2020.6.91350/pythonFiles/lib/python/debugpy/../debugpy/server/cli.py", line 430, in main run() File "/home/jacob/.vscode-server/extensions/ms-python.python-2020.6.91350/pythonFiles/lib/python/debugpy/../debugpy/server/cli.py", line 267, in run_file runpy.run_path(options.target, run_name=compat.force_str("__main__")) File "/home/jacob/miniconda3/envs/dask/lib/python3.7/runpy.py", line 263, in run_path pkg_name=pkg_name, script_name=fname) File "/home/jacob/miniconda3/envs/dask/lib/python3.7/runpy.py", line 96, in _run_module_code mod_name, mod_spec, pkg_name, script_name) File "/home/jacob/miniconda3/envs/dask/lib/python3.7/runpy.py", line 85, in _run_code exec(code, run_globals) File "/home/jacob/Projects/pydata/xarray/test_seasonal_averages.py", line 32, in <module> ds_weighted = ds_weighted.sum(dim="time") File "/home/jacob/Projects/pydata/xarray/xarray/core/common.py", line 84, in wrapped_func func, dim, skipna=skipna, numeric_only=numeric_only, **kwargs File "/home/jacob/Projects/pydata/xarray/xarray/core/groupby.py", line 994, in reduce return self.map(reduce_dataset) File "/home/jacob/Projects/pydata/xarray/xarray/core/groupby.py", line 923, in map return self._combine(applied) File "/home/jacob/Projects/pydata/xarray/xarray/core/groupby.py", line 943, in _combine applied_example, applied = peek_at(applied) File "/home/jacob/Projects/pydata/xarray/xarray/core/utils.py", line 183, in peek_at peek = next(gen) File "/home/jacob/Projects/pydata/xarray/xarray/core/groupby.py", line 922, in <genexpr> applied = (func(ds, *args, **kwargs) for ds in self._iter_grouped()) File "/home/jacob/Projects/pydata/xarray/xarray/core/groupby.py", line 990, in reduce_dataset return ds.reduce(func, dim, keep_attrs, **kwargs) File "/home/jacob/Projects/pydata/xarray/xarray/core/dataset.py", line 4313, in reduce **kwargs, File "/home/jacob/Projects/pydata/xarray/xarray/core/variable.py", line 1591, in reduce data = func(input_data, axis=axis, **kwargs) File "/home/jacob/Projects/pydata/xarray/xarray/core/duck_array_ops.py", line 324, in f return func(values, axis=axis, **kwargs) File "/home/jacob/Projects/pydata/xarray/xarray/core/nanops.py", line 111, in nansum a, mask = _replace_nan(a, 0) File "/home/jacob/Projects/pydata/xarray/xarray/core/nanops.py", line 21, in _replace_nan return where_method(val, mask, a), mask File "/home/jacob/Projects/pydata/xarray/xarray/core/duck_array_ops.py", line 274, in where_method return where(cond, data, other) File "/home/jacob/Projects/pydata/xarray/xarray/core/duck_array_ops.py", line 268, in where return _where(condition, *as_shared_dtype([x, y])) File "/home/jacob/Projects/pydata/xarray/xarray/core/duck_array_ops.py", line 56, in f return wrapped(*args, **kwargs) File "<__array_function__ internals>", line 6, in where File "cupy/core/core.pyx", line 1343, in cupy.core.core.ndarray.__array_function__ File "/home/jacob/miniconda3/envs/dask/lib/python3.7/site-packages/cupy/sorting/search.py", line 211, in where return _where_ufunc(condition.astype('?'), x, y) File "cupy/core/_kernel.pyx", line 906, in cupy.core._kernel.ufunc.__call__ File "cupy/core/_kernel.pyx", line 90, in cupy.core._kernel._preprocess_args TypeError: Unsupported type <class 'numpy.ndarray'> ```

Anything else we need to know?:

Environment:

Output of <tt>xr.show_versions()</tt>

INSTALLED VERSIONS ------------------ commit: 52043bc57f20438e8923790bca90b646c82442ad python: 3.7.6 | packaged by conda-forge | (default, Jun 1 2020, 18:57:50) [GCC 7.5.0] python-bits: 64 OS: Linux OS-release: 5.3.0-62-generic machine: x86_64 processor: x86_64 byteorder: little LC_ALL: None LANG: en_GB.UTF-8 LOCALE: en_GB.UTF-8 libhdf5: None libnetcdf: None xarray: 0.15.1 pandas: 0.25.3 numpy: 1.18.5 scipy: 1.5.0 netCDF4: None pydap: None h5netcdf: None h5py: None Nio: None zarr: None cftime: 1.2.0 nc_time_axis: None PseudoNetCDF: None rasterio: None cfgrib: 0.9.8.3 iris: None bottleneck: None dask: 2.20.0 distributed: 2.20.0 matplotlib: 3.2.2 cartopy: 0.17.0 seaborn: 0.10.1 numbagg: None pint: None setuptools: 49.1.0.post20200704 pip: 20.1.1 conda: None pytest: 5.4.3 IPython: 7.16.1 sphinx: None