code: def censor(self, censor_id):
      unique_censor_id, _ = tf.unique(censor_id)
      embedding_gather = tf.gather(
          self.variables[0], indices=unique_censor_id
      )
      norm = tf.norm(embedding_gather, axis=1, keepdims=True)
      return self.variables[0].scatter_nd_update(
          indices=tf.expand_dims(unique_censor_id, 1),
          updates=embedding_gather / tf.math.maximum(norm, 0.1),
      )
  
imports: from tensorflow.keras.layers import Embedding
  import tensorflow
label_desc: Use image node_id 2 for calling the LatentFactor obj's underlying member method code with example usage: obj.censor(censor_id) and returns: self