code: def get_workload(
      batch_size,
      num_classes=10,
      image_shape=(1, 28, 28),
      dtype="float32",
  ):
      """Get benchmark workload for a simple multilayer perceptron.
  
      Parameters
      ----------
      batch_size : int
          The batch size used in the model
  
      num_classes : int, optional
          Number of claseses
  
      image_shape : tuple, optional
          The input image shape
  
      dtype : str, optional
          The data type
  
      Returns
      -------
      mod : tvm.IRModule
          The relay module that contains a mlp network.
  
      params : dict of str to NDArray
          The parameters.
      """
      net = get_net(batch_size, num_classes, image_shape, dtype)
      return create_workload(net)
  
imports: from __future__ import absolute_import
  from tvm import relay
  from .init import create_workload
label_desc: Use image node_id 2 for calling a global function with example usage: get_workload(batch_size, num_classes, image_shape, dtype) and returns: create_workload