code: def __init__(self, num_instances, dim, zero_init=False, name=None):
      if zero_init:
          initializer = "zeros"
      else:
          initializer = "uniform"
      super(LatentFactor, self).__init__(
          input_dim=num_instances,
          output_dim=dim,
          embeddings_initializer=initializer,
          name=name,
      )
  
imports: from tensorflow.keras.layers import Embedding
  import tensorflow
label_desc: Use image node_id 1 to create a new LatentFactor object from inherited base classes: Embedding with example: obj = LatentFactor(num_instances, dim, zero_init, name)