code: def run_eval(interpreter, input_image):
      """Performs evaluation for input image over specified model.
  
      Args:
          interpreter: TFLite interpreter initialized with model to execute.
          input_image: Image input to the model.
  
      Returns:
          output: output tensor of model being executed.
      """
  
      # Get input and output tensors.
      input_details = interpreter.get_input_details()
      output_details = interpreter.get_output_details()
  
      # Test model on the input images.
      input_image = np.reshape(input_image, input_details[0]["shape"])
      interpreter.set_tensor(input_details[0]["index"], input_image)
  
      interpreter.invoke()
      output_data = interpreter.get_tensor(output_details[0]["index"])
      output = np.squeeze(output_data)
      return output
  
imports: import numpy
  import tensorflow
  from tensorflow.lite.tutorials import dataset
label_desc: Use image node_id 2 for calling a global function with example usage: run_eval(interpreter, input_image) and returns: output