code: def __init__(self, X, neighbour_matrix, batch_size=32):
      super().__init__(X, neighbour_matrix, batch_size)
      self.placeholder_labels = np.empty(batch_size, dtype=np.uint8)
  
imports: from abc import ABC, abstractmethod
  from functools import partial
  import itertools
  import random
  import math
  import numpy
  from tensorflow.keras.utils import Sequence
  from scipy.sparse import issparse
  from ..data import get_uint_ctype
label_desc: Use image node_id 1 to create a new UnsupervisedTripletGenerator object from inherited base classes: TripletGenerator with example: obj = UnsupervisedTripletGenerator(X, neighbour_matrix, batch_size)