class_docstr: Problem class for Program Search Algolisp task.
  
  Synthesizing programs from description and examples.
  
  Please see: https://arxiv.org/pdf/1802.04335.pdf for the full description.
class_docstr_tok: ["Problem","class","for","Program","Search","Algolisp","task",".","Synthesizing","programs","from","description","and","examples",".","Please","see",":","https",":","\/\/arxiv.org\/pdf\/1802.04335.pdf","for","the","full","description","."]
code: def _parse_json_to_dict(json_line):
      # First parse it through json.
      line_json_dict = json.loads(json_line)
  
      # The features of interest "text" and "short_tree" are stored as lists in
      # this dictionary -- "short_tree" is a nested list. We flatten and join the
      # lists on space, to return a string in both these cases.
  
      # Make another dictionary, to return only the features we want.
      return {
          "inputs": " ".join(line_json_dict["text"]),
          "targets": " ".join(
              [
                  i
                  for i in ProgramSearchAlgolisp._flatten_target_programs(
                      line_json_dict["short_tree"]
                  )
              ]
          ),
      }
  
file_path: tensor2tensor/tensor2tensor/data_generators/program_search.py
imports: from __future__ import absolute_import
  from __future__ import division
  from __future__ import print_function
  import gzip
  import json
  import os
  from tensor2tensor.data_generators import generator_utils
  from tensor2tensor.data_generators import problem
  from tensor2tensor.data_generators import text_problems
  from tensor2tensor.utils import registry
  import tensorflow.compat.v1
label_desc: Use image node_id 3 for calling the ProgramSearchAlgolisp obj's underlying member method code with example usage: obj._parse_json_to_dict(json_line) and returns: dict