class_docstr: Helper class for adaptive embeddings specifying a cluster of tokens.
  
  Essentially a wrapper around a vocab embedding for the cluster with additional
  metadata so that we can apply the embedding to the actual ids and hidden
  states.
docstr: Returns the logits for tokens within the cluster.
docstr_tok: ["Returns","the","logits","for","tokens","within","the","cluster","."]
code: def hidden_to_logits(self, hidden, context):
      """Returns the logits for tokens within the cluster."""
      return self._embedding.hidden_to_logits(hidden, context)
  
imports: import gin
  import mesh_tensorflow
  from mesh_tensorflow.transformer import transformer
  import tensorflow.compat.v1
label_desc: Use image node_id 3 for calling the _Cluster obj's underlying member method code with example usage: obj.hidden_to_logits(hidden, context) and returns: self