code: def __init__(self, values=None, tracker=None):
      self.tracker = tracker
      if tracker and values:
          values = {k: tracker.track(v) for k, v in values.items()}
      super().__init__(values or [])
  
imports: from functools import wraps
  from keras.backend.common.global_state import get_global_attribute
  from keras.backend.common.global_state import set_global_attribute
  from keras.utils import python_utils
label_desc: Use image node_id 1 to create a new TrackedDict object from inherited base classes: dict with example: obj = TrackedDict(values, tracker)