class_docstr: Factorizes the embedding matrix with projection to a small inner dimension.
  
  Like ALBERT (https://arxiv.org/abs/1909.11942).
  
  Interface matches mesh_tensorflow.transformer VocabEmbedding object.
code: def hidden_to_logits(self, hidden, context):
      del context
      hidden *= self._output_dim.size**-0.5
      tmp = mtf.einsum(
          [hidden, self._factor2], reduced_dims=[self._output_dim]
      )
      return mtf.einsum(
          [tmp, self._factor1], reduced_dims=[self._inner_dim]
      )
  
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 FactorizedVocabEmbedding obj's underlying member method code with example usage: obj.hidden_to_logits(hidden, context) and returns: mtf