class_docstr: Get streaming accuracy statistics every time a new command is founded.
  
  Attributes:
    _how_many_gt: How many ground truths.
    _how_many_gt_matched: How many ground truths have been matched.
    _how_many_fp: How many commands have been fired as false positive.
    _how_many_c: How many commands have been fired correctly.
    _how_many_w: How many commands have been fired wrongly.
    _gt_occurrence: A list to record which commands and when it occurs in the
      input audio stream.
    _previous_c: A variable to record the last status of _how_many_c.
    _previous_w: A variable to record the last status of _how_many_w.
    _previous_fp: A variable to record the last status of _how_many_fp.
docstr: Load ground truth and timestamp pairs and store it in time order.
code: def read_ground_truth_file(self, file_name):
      """Load ground truth and timestamp pairs and store it in time order."""
      with open(file_name, "r") as f:
          for line in f:
              line_split = line.strip().split(",")
              if len(line_split) != 2:
                  continue
              timestamp = round(float(line_split[1]))
              label = line_split[0]
              self._gt_occurrence.append([label, timestamp])
      self._gt_occurrence = sorted(
          self._gt_occurrence, key=lambda item: item[1]
      )
  
file_path: tensorflow-upstream/tensorflow/examples/speech_commands/accuracy_utils.py
imports: import numpy
  import tensorflow
label_desc: Use image node_id 2 for calling the StreamingAccuracyStats obj's underlying member method code with example usage: obj.read_ground_truth_file(file_name) without return types