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: Compute delta of StreamingAccuracyStats against last status.
code: def delta(self):
      """Compute delta of StreamingAccuracyStats against last status."""
      fp_delta = self._how_many_fp - self._previous_fp
      w_delta = self._how_many_w - self._previous_w
      c_delta = self._how_many_c - self._previous_c
      if fp_delta == 1:
          recognition_state = "(False Positive)"
      elif c_delta == 1:
          recognition_state = "(Correct)"
      elif w_delta == 1:
          recognition_state = "(Wrong)"
      else:
          raise ValueError("Unexpected state in statistics")
      # Update the previous status
      self._previous_c = self._how_many_c
      self._previous_w = self._how_many_w
      self._previous_fp = self._how_many_fp
      return recognition_state
  
file_path: tensorflow/tensorflow/examples/speech_commands/accuracy_utils.py
imports: import numpy
  import tensorflow
label_desc: Use image node_id 3 for calling the StreamingAccuracyStats obj's underlying member method code with example usage: obj.delta() and returns: recognition_state