class_docstr: MNISTDigitClassifier handler class. This handler extends class ImageClassifier from image_classifier.py, a
  default handler. This handler takes an image and returns the number in that image.
docstr: The post process of MNIST converts the predicted output response to a label.
  
  Args:
      data (list): The predicted output from the Inference with probabilities is passed
      to the post-process function
  Returns:
      list : A list of dictionary with predictons and explanations are returned.
code: def postprocess(self, data):
      """The post process of MNIST converts the predicted output response to a label.
  
      Args:
          data (list): The predicted output from the Inference with probabilities is passed
          to the post-process function
      Returns:
          list : A list of dictionary with predictons and explanations are returned.
      """
      # "add_counter" will register the metric if not already present in metric cache,
      # include the "ModelName" and "Level" dimensions by default and emit it
      self.context.metrics.add_counter(
          name="PostprocessCallCount", value=1, idx=None, dimensions=[]
      )
      # "add_percent" will register the metric if not already present in metric cache,
      # include the "ModelName" and "Level" dimensions by default and emit it
      # Note: "ExamplePercentMetric" is not defined in "metrics.yaml" and will be auto-detected
      self.context.metrics.add_percent(
          name="ExamplePercentMetric",
          value=50,
          idx=None,
          dimensions=[],
          metric_type=MetricTypes.HISTOGRAM,
      )
  
      return data.argmax(1).flatten().tolist()
  
file_path: serve/examples/custom_metrics/mnist_handler.py
imports: import time
  from torchvision import transforms
  from ts.metrics.dimension import Dimension
  from ts.metrics.metric_type_enum import MetricTypes
  from ts.torch_handler.image_classifier import ImageClassifier
label_desc: Use image node_id 3 for calling the MNISTDigitClassifier obj's underlying member method code with example usage: obj.postprocess(data) and returns: data