class_docstr: Class for generating a dictionary of all words in the PTB corpus
class_docstr_tok: ["Class","for","generating","a","dictionary","of","all","words","in","the","PTB","corpus"]
code: def _uncompress_data(self, work_directory):
      full_filepath = os.path.join(
          work_directory,
          FILENAME[self.dataset] + "." + EXTENSION[self.dataset],
      )
      if EXTENSION[self.dataset] == "tgz":
          import tarfile
  
          with tarfile.open(full_filepath, "r:gz") as tar:
              tar.extractall(path=work_directory)
      if EXTENSION[self.dataset] == "zip":
          import zipfile
  
          with zipfile.ZipFile(full_filepath, "r") as zip_handle:
              zip_handle.extractall(work_directory)
  
      print(
          "Successfully unzipped data to {}".format(
              os.path.join(work_directory, FILENAME[self.dataset])
          )
      )
  
file_path: nlp-architect/nlp_architect/data/ptb.py
imports: import os
  import sys
  import numpy
  import urllib.request
label_desc: Use image node_id 7 for calling the PTBDictionary obj's underlying member method code with example usage: obj._uncompress_data(work_directory) without return types