[Python] np.where with a in-type condition

Given a numpy array

arr = np.array([1, 2, 3, 4, 5])


I need to construct a binary mask according to a (arbitrary, potentially long) list of values, i.e. given

values = np.array([2, 4, 5])


mask should be

mask = np.array([False, True, False, True, True])


So I want to avoid

condition = (arr==2) or (arr==4) or (arr==5)
mask = np.where(condition, arr)


to get something like

mask = np.in(values, arr)


Or, if it is not possible, how to construct a condition from an arbitrary list of values to feed into np.where?

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