class_docstr: Store and retrieve report JSON files.
class_docstr_tok: ["Store","and","retrieve","report","JSON","files","."]
docstr: Creates a `_ReportAccessor` instance.
  
  Args:
    report_dir: Directory to store the report.
    filename: Name of the file.
  
  Returns:
    A `_ReportAccessor` instance.
docstr_tok: ["Creates","a","`","_ReportAccessor","`","instance",".","Args",":","report_dir",":","Directory","to","store","the","report",".","filename",":","Name","of","the","file",".","Returns",":","A","`","_ReportAccessor","`","instance","."]
code: def __init__(self, report_dir, filename="iteration_reports.json"):
      """Creates a `_ReportAccessor` instance.
  
      Args:
        report_dir: Directory to store the report.
        filename: Name of the file.
  
      Returns:
        A `_ReportAccessor` instance.
      """
  
      tf.io.gfile.makedirs(report_dir)
      self._full_filepath = os.path.join(report_dir, filename)
  
file_path: adanet/adanet/core/report_accessor.py
imports: from __future__ import absolute_import
  from __future__ import division
  from __future__ import print_function
  import json
  import os
  from absl import logging
  from adanet import subnetwork
  import numpy
  import six
  import tensorflow.compat.v2
label_desc: Use image node_id 1 to create a new _ReportAccessor object from inherited base classes: object with example: obj = _ReportAccessor(report_dir, filename)