Question

我正在尝试使用大量数据启动dask.cluster.Kmeans。因为我用numpy包装dask.array数组，所以可以使用CPU。由于cupy中未实现功能，因此似乎无法使用GPU。

我尝试重现Mattew Rocklin的示例（https://blog.dask.org/2019/01/03/dask-array-gpus-first-steps），该示例是从CuPy随机生成器生成随机dask数组的，虽然可以，但是我不想使用这种情况。

用cupy包装dask.array-不起作用。

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

我希望此数组的总和，但会出现以下错误：

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

那么我如何通过dask数组管理CuPy的工作？

Answer 1

从CuPy数组创建Dask数组时，需要提供da.from_array关键字参数asarray=False。因此，您的代码将如下所示。

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

如何从CuPy数组创建dask数组？

1 个答案: