I have gone all similar question and solutions provided, but not getting desired output.
I have a list of dask delayed objects.
for i in my_list:
projection = Projection(self.expression, i)
fi = projection.decode()
var.append(fi)
where Projection is a class having decode function which has @dask.delayed decorator. Inside this function, we are fitting random-forest.
Var is:
[Delayed('decode-82afe417-9d1e-48ff-95a3-02ddc90c6970'),
Delayed('decode-0a872626-996a-4a19-8b45-b39acb44257f'),
Delayed('decode-cfa53fd4-cf5b-47f1-a672-440dc5f5ca35'),
Delayed('decode-29cf7f51-2e7a-4c9d-8ac0-bc2259d50b6f'),
Delayed('decode-2edc8324-f9df-4402-a1ed-44a6a9067f1d'),
Delayed('decode-05de7417-49a5-40b7-8098-f2aad50bd934'),
Delayed('decode-80916f08-2d28-4811-9ab4-e526af978aac'),
Delayed('decode-da4a8874-77b5-4d75-aede-c96b5e73e888'),
Delayed('decode-1c1fe7f0-a32b-4a0a-9d13-bb45710a3738')
Now I want to compute this var and want to get a list or array or dataframe. For that purpose, I tried various options:
option1
dask.compute(*var)
option2
v = dask.array.from_array(np.array(var), chunks=(100,))
dask.array.compute(*v)
option3
v = dask.array.from_delayed(np.array(var))
dask.array.compute(*v)
option4
v = dask.array.from_delayed(np.array(var))
v.compute()
but in all cases, either I get again the list of delayed objects or time out.
Thanks in advance.
Option 1 appears to be the most appropriate one, Options 3 and 4 will result in a list of delayed objects because in those options v
contains nested delayed objects.
It would help to know more details about the setup (local/distributed), data magnitude, computation intensity, and the activity on the dask dashboard.
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