How to use the tensornetwork.block_tensor.index.fuse_degeneracies function in tensornetwork

for n in range(1, len(charges)):
    #list of unique charges and list of their degeneracies
    #on the next unfused leg of the tensor
    leg_charges, leg_degeneracies = np.unique(charges[n], return_counts=True)

    #fuse the unique charges
    #Note: entries in `fused_charges` are not unique anymore.
    #flow1 = 1 because the flow of leg 0 has already been
    #mulitplied above
    fused_charges = fuse_charge_pair(
        q1=accumulated_charges, flow1=1, q2=leg_charges, flow2=flows[n])
    #compute the degeneracies of `fused_charges` charges
    #`fused_degeneracies` is a list of degeneracies such that
    # `fused_degeneracies[n]` is the degeneracy of of
    # charge `c = fused_charges[n]`.
    fused_degeneracies = fuse_degeneracies(accumulated_degeneracies,
                                           leg_degeneracies)
    #compute the new degeneracies resulting from fusing
    #`accumulated_charges` and `leg_charges_2`
    accumulated_charges = np.unique(fused_charges)
    accumulated_degeneracies = np.empty(
        len(accumulated_charges), dtype=np.int64)
    for n in range(len(accumulated_charges)):
      accumulated_degeneracies[n] = np.sum(
          fused_degeneracies[fused_charges == accumulated_charges[n]])
  return accumulated_charges, accumulated_degeneracies