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 __init__(self, params, mode, name="image_seq2seq"):
      super(Image2Seq, self).__init__(params, mode, name)
      self.params["source.reverse"] = False
      self.params["embedding.share"] = False
  
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 1 to create a new Image2Seq object from inherited base classes: AttentionSeq2Seq with example: obj = Image2Seq(params, mode, name)