class_docstr: Base class for file writer.
  
  FileWriter consumes a DataSource and generates benchmark data as described
  in the DataSource. DataSource contains benchmark data metadata such as value
  generators, total number of records, and number of partitioned files.
  
  SubClass must implement `_write_to_path` function to write data under the
  given path and follow the spec described in DataSource.
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docstr: Return the hashed code of this file writer.
  
  The hashed code is used to create the folder that the writer can write
  data to. It is useful for benchmark data cache.
  
  Returns:
    The hashed code of the writer in hex str.
docstr_tok: ["Return","the","hashed","code","of","this","file","writer",".","The","hashed","code","is","used","to","create","the","folder","that","the","writer","can","write","data","to",".","It","is","useful","for","benchmark","data","cache",".","Returns",":","The","hashed","code","of","the","writer","in","hex","str","."]
code: def hash_code(self):
      """Return the hashed code of this file writer.
  
      The hashed code is used to create the folder that the writer can write
      data to. It is useful for benchmark data cache.
  
      Returns:
        The hashed code of the writer in hex str.
      """
      m = hashlib.sha256()
      # Hash the instance class name by default. Subclass can overload the
      # function to support customized hashing logic for its own state.
      m.update(self.__class__.__name__.encode())
      return m.hexdigest()
  
file_path: io/tests/test_atds_avro/utils/file_writer.py
imports: import abc
  import os
  import shutil
  import hashlib
  import tempfile
  import tensorflow
label_desc: Use image node_id 8 for calling the FileWriter obj's underlying member method code with example usage: obj.hash_code() and returns: m