code: def get_active_intent_accuracy(frame_ref, frame_hyp):
      """Get active intent accuracy of a frame.
  
      Args:
        frame_ref: single semantic frame from reference (ground truth) file.
        frame_hyp: single semantic frame from hypothesis (prediction) file.
  
      Returns:
        1.0 if the intent prediction is correct, otherwise 0.0.
      """
      return float(
          frame_ref["state"]["active_intent"]
          == frame_hyp["state"]["active_intent"]
      )
  
file_path: NeMo/nemo/collections/nlp/metrics/sgd_metrics.py
imports: import collections
  import numpy
  from rapidfuzz import fuzz
label_desc: Use image node_id 5 for calling a global function with example usage: get_active_intent_accuracy(frame_ref, frame_hyp) and returns: float