在看一個機器學習項目的源碼時，看到有一個.compute()函數，結果到處都找不到它的用法，不過最后還是在Dask官網里找到了。

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下面是英文的文檔，各位可以就著百度翻譯查看。

compute(**kwargs)

Compute this dask collection
This turns a lazy Dask collection into its in-memory equivalent. For example a Dask.array turns into a numpy.array() and a Dask.dataframe turns into a Pandas dataframe. The entire dataset must fit into memory before calling this operation.

• Parameters:
  scheduler : string, optional
  Which scheduler to use like “threads”, “synchronous” or “processes”. If not provided, the default is to check the global settings first, and then fall back to the collection defaults.
  optimize_graph : bool, optional
  If True [default], the graph is optimized before computation. Otherwise the graph is run as is. This can be useful for debugging.
  kwargs
  Extra keywords to forward to the scheduler function.

總結

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