class_docstr: Sequence2Sequence model with attention mechanism.
  
  Args:
    source_vocab_info: An instance of `VocabInfo`
      for the source vocabulary
    target_vocab_info: An instance of `VocabInfo`
      for the target vocabulary
    params: A dictionary of hyperparameters
class_docstr_tok: ["Sequence2Sequence","model","with","attention","mechanism",".","Args",":","source_vocab_info",":","An","instance","of","`","VocabInfo","`","for","the","source","vocabulary","target_vocab_info",":","An","instance","of","`","VocabInfo","`","for","the","target","vocabulary","params",":","A","dictionary","of","hyperparameters"]
code: def __init__(self, params, mode, name="att_seq2seq"):
      super(AttentionSeq2Seq, self).__init__(params, mode, name)
  
file_path: seq2seq/seq2seq/models/attention_seq2seq.py
imports: from __future__ import absolute_import
  from __future__ import division
  from __future__ import print_function
  from __future__ import unicode_literals
  from pydoc import locate
  import tensorflow
  from seq2seq import decoders
  from seq2seq.models.basic_seq2seq import BasicSeq2Seq
label_desc: Use image node_id 1 to create a new AttentionSeq2Seq object from inherited base classes: BasicSeq2Seq with example: obj = AttentionSeq2Seq(params, mode, name)