docstr: Returns the model's metrics values as a dict.
  
  If any of the metric result is a dict (containing multiple metrics),
  each of them gets added to the top level returned dict of this method.
  
  Returns:
      A `dict` containing values of the metrics listed in `self.metrics`.
      Example: `{'loss': 0.2, 'accuracy': 0.7}`.
code: def get_metrics_result(self):
      """Returns the model's metrics values as a dict.
  
      If any of the metric result is a dict (containing multiple metrics),
      each of them gets added to the top level returned dict of this method.
  
      Returns:
          A `dict` containing values of the metrics listed in `self.metrics`.
          Example: `{'loss': 0.2, 'accuracy': 0.7}`.
      """
      return_metrics = {}
      for metric in self.metrics:
          result = metric.result()
          if isinstance(result, dict):
              return_metrics.update(result)
          else:
              return_metrics[metric.name] = result
      return self._pythonify_logs(return_metrics)
  
imports: import platform
  import warnings
  import tree
  from keras import backend
  from keras import metrics
  from keras import ops
  from keras import optimizers
  from keras.optimizers.loss_scale_optimizer import LossScaleOptimizer
  from keras.saving import serialization_lib
  from keras.trainers.compile_utils import CompileLoss
  from keras.trainers.compile_utils import CompileMetrics
  from keras.trainers.data_adapters import data_adapter_utils
  from keras.utils import traceback_utils
  from keras.utils import tracking
label_desc: Use image node_id 14 for calling the Trainer obj's underlying member method code with example usage: obj.get_metrics_result() and returns: self