in datasets/MixedPrioritizedSampler.py [0:0]
def __init__(self, capacity, fixed_weights=None, fixed_scale=1.0,
init_weight=1.0):
"""
fixed_weights: weights that wont be updated by self.update()
"""
assert fixed_weights is None or len(fixed_weights) == capacity
self._capacity = capacity
self._tree_size = 2 * capacity - 1
self.fixed_scale = fixed_scale
self.fixed_weights = np.zeros(self._capacity) if fixed_weights is None \
else fixed_weights
self.tree = np.zeros(self._tree_size)
self._initialized = False
self.initialize(init_weight)