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python - Removing duplicates from a list of numPy arrays

I have an ordinary Python list that contains (multidimensional) numPy arrays, all of the same shape and with the same number of values. Some of the arrays in the list are duplicates of earlier ones.

I have the problem that I want to remove all the duplicates, but the fact that the data type is numPy arrays complicates this a bit...

? I can't use set() as numPy arrays are not hashable.
? I can't check for duplicates during insertion, as the arrays are generated in batches by a function and added to the list with .extend().
? numPy arrays aren't directly comparable without resorting to one of numPy's own functions, so I can't just go something that uses "if x in list"...
? The contents of the list need to remain numPy arrays at the end of the process; I could compare copies of the arrays converted to nested lists, but I can't convert the arrays to straight python lists permanently.

Any suggestions on how I can remove duplicates efficiently here?

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Using the solutions here: Most efficient property to hash for numpy array we see that hashing works best with a.tostring() if a is an numpy array. So:

import numpy as np
arraylist = [np.array([1,2,3,4]), np.array([1,2,3,4]), np.array([1,3,2,4])]
L = {array.tostring(): array for array in arraylist}
L.values() # [array([1, 3, 2, 4]), array([1, 2, 3, 4])]

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