class_docstr: Test agents for distilling Transformer generator models.
docstr: Download models in advance so that their opt files can be used with --init-opt.
docstr_tok: ["Download","models","in","advance","so","that","their","opt","files","can","be","used","with","--","init-opt","."]
code: def setup(self):
      """
      Download models in advance so that their opt files can be used with --init-opt.
      """
  
      seed = 0
      random.seed(seed)
      np.random.seed(seed)
      torch.manual_seed(seed)
  
      datapath = "data"
      self._download_model(datapath)
  
      yield "Setup complete"
  
imports: import random
  from abc import ABC, abstractmethod
  from math import floor, log10
  from typing import Dict
  import numpy
  import pytest
  import torch
  from pytest_regressions.data_regression import DataRegressionFixture
  import parlai.utils.testing
  from parlai.core.opt import Opt
  from parlai.core.teachers import register_teacher, DialogTeacher
  from parlai.utils.data import DatatypeHelper
  from parlai.zoo.bart.build import download
  from parlai.zoo.blender.blender_90M import download
label_desc: Use image node_id 1 for calling the AbstractTestDistillation obj's underlying member method code with example usage: obj.setup() without return types