code: def get_workload(
      batch_size,
      oshape=(3, 64, 64),
      ngf=128,
      random_len=100,
      layout="NCHW",
      dtype="float32",
  ):
      """Get benchmark workload for a DCGAN generator
  
      Parameters
      ----------
      batch_size : int
          The batch size used in the model
      oshape : tuple, optional
          The shape of output image, layout="CHW"
      ngf: int, optional
          The number of final feature maps in the generator
      random_len : int, optional
          The length of random input
      layout: str, optional
          The layout of conv2d transpose
      dtype : str, optional
          The data type
  
      Returns
      -------
      mod : tvm.IRModule
          The relay module that contains a DCGAN network.
      params : dict of str to NDArray
          The parameters.
      """
      net = get_net(
          batch_size,
          random_len,
          oshape=oshape,
          ngf=ngf,
          layout=layout,
          dtype=dtype,
      )
      return create_workload(net)
  
imports: from tvm import relay
  from .None import layers
  from .init import create_workload
label_desc: Use image node_id 4 for calling a global function with example usage: get_workload(batch_size, oshape, ngf, random_len, layout, dtype) and returns: create_workload