class_docstr: A model that encodes an image and produces a sequence
  of tokens.
class_docstr_tok: ["A","model","that","encodes","an","image","and","produces","a","sequence","of","tokens","."]
code: def encode(self, features, _labels):
      encoder_fn = self.encoder_class(
          self.params["encoder.params"], self.mode
      )
      return encoder_fn(features["image"])
  
file_path: seq2seq/seq2seq/models/image2seq.py
imports: from __future__ import absolute_import
  from __future__ import division
  from __future__ import print_function
  from __future__ import unicode_literals
  import tensorflow
  from seq2seq import graph_utils
  from seq2seq.data import vocab
  from seq2seq.graph_utils import templatemethod
  from seq2seq.models.model_base import ModelBase
  from seq2seq.models.attention_seq2seq import AttentionSeq2Seq
label_desc: Use image node_id 3 for calling the Image2Seq obj's underlying member method code with example usage: obj.encode(features, _labels) and returns: encoder_fn