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 batch_size(self, features, _labels):
      return tf.shape(features["image"])[0]
  
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 4 for calling the Image2Seq obj's underlying member method code with example usage: obj.batch_size(features, _labels) and returns: tf