How to create a dask-array from CuPy array?

I'm trying to launch dask.cluster.Kmeans with the huge amount of data. Working with CPU is OK since i wrap numpy arrays with dask.array. Working with GPU doesn't seem to be possible due to not implemented functionalities in cupy.

I've tried to reproduce Mattew Rocklin example (https://blog.dask.org/2019/01/03/dask-array-gpus-first-steps) on generating random dask array from CuPy random generator - and it works, but it's not the case I want to use.

Wrapping cupy with dask.array - doesn't work.

>>> import dask.array as da
>>> import cupy as cp
>>> da.from_array(cp.arange(100000)).sum().compute()

I expect the sum of this array but get the following error:

Traceback (most recent call last):
  File "<stdin>", line 1, in <module>
  File "/home/ubuntu/miniconda3/envs/cupy/lib/python3.6/site-packages/dask/base.py", line 175, in compute
    (result,) = compute(self, traverse=False, **kwargs)
  File "/home/ubuntu/miniconda3/envs/cupy/lib/python3.6/site-packages/dask/base.py", line 446, in compute
    results = schedule(dsk, keys, **kwargs)
  File "/home/ubuntu/miniconda3/envs/cupy/lib/python3.6/site-packages/dask/threaded.py", line 82, in get
    **kwargs
  File "/home/ubuntu/miniconda3/envs/cupy/lib/python3.6/site-packages/dask/local.py", line 491, in get_async
    raise_exception(exc, tb)
  File "/home/ubuntu/miniconda3/envs/cupy/lib/python3.6/site-packages/dask/compatibility.py", line 130, in reraise
    raise exc
  File "/home/ubuntu/miniconda3/envs/cupy/lib/python3.6/site-packages/dask/local.py", line 233, in execute_task
    result = _execute_task(task, data)
  File "/home/ubuntu/miniconda3/envs/cupy/lib/python3.6/site-packages/dask/core.py", line 119, in _execute_task
    return func(*args2)
  File "/home/ubuntu/miniconda3/envs/cupy/lib/python3.6/site-packages/dask/array/core.py", line 100, in getter
    c = np.asarray(c)
  File "/home/ubuntu/miniconda3/envs/cupy/lib/python3.6/site-packages/numpy/core/numeric.py", line 538, in asarray
    return array(a, dtype, copy=False, order=order)
ValueError: object __array__ method not producing an array

So how could I manage the work with CuPy through the dask array?

When creating the Dask Array from a CuPy array, you need to supply da.from_array the keyword argument asarray=False. So your code would look like the following.

>>> import dask.array as da
>>> import cupy as cp
>>> da.from_array(cp.arange(100000), asarray=False).sum().compute()