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 ids_to_embedding(self, ids, context):
      del context
      tmp = mtf.gather(self._factor1, ids, self._vocab_dim)
      return mtf.einsum(
          [tmp, self._factor2], 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 2 for calling the FactorizedVocabEmbedding obj's underlying member method code with example usage: obj.ids_to_embedding(ids, context) and returns: mtf