class_docstr: Defines inference for tasks where both the input and output sequences
  are plain text.
  
  Params:
    file: File to write beam search information to.
class_docstr_tok: ["Defines","inference","for","tasks","where","both","the","input","and","output","sequences","are","plain","text",".","Params",":","file",":","File","to","write","beam","search","information","to","."]
code: def __init__(self, params):
      super(DumpBeams, self).__init__(params)
      self._beam_accum = {
          "predicted_ids": [],
          "beam_parent_ids": [],
          "scores": [],
          "log_probs": [],
      }
  
      if not self.params["file"]:
          raise ValueError("Must specify file for DumpBeams")
  
file_path: seq2seq/seq2seq/tasks/dump_beams.py
imports: from __future__ import absolute_import
  from __future__ import division
  from __future__ import print_function
  from __future__ import unicode_literals
  import numpy
  import tensorflow
  from seq2seq.tasks.inference_task import InferenceTask, unbatch_dict
label_desc: Use image node_id 1 to create a new DumpBeams object from inherited base classes: InferenceTask with example: obj = DumpBeams(params)