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I have the next code that I am trying to run in parallel:

inputs = range(10) 

def processInput(i,x):
   return model(x)

results = Parallel(n_jobs=num_cores)(delayed(processInput)(i,x) for i in inputs)

Where model is a convolutional neural net, and x a batch of images.

It raises a gigantic error which ends with "PicklingError: Could not pickle the task to send it to the workers."

I just want to run the model in parallel N times with dropout to do some variance calculation later. Am I doing it wrong?

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