code: def _mock_init_weights(self, module):
      if hasattr(module, "weight") and module.weight is not None:
          module.weight.data.fill_(3)
      if (
          hasattr(module, "cluster_weight")
          and module.cluster_weight is not None
      ):
          module.cluster_weight.data.fill_(3)
      if hasattr(module, "bias") and module.bias is not None:
          module.bias.data.fill_(3)
      if (
          hasattr(module, "cluster_bias")
          and module.cluster_bias is not None
      ):
          module.cluster_bias.data.fill_(3)
  
      if hasattr(module, "emb_projs"):
          for i in range(len(module.emb_projs)):
              if module.emb_projs[i] is not None:
                  nn.init.constant_(module.emb_projs[i], 0.0003)
      if hasattr(module, "out_projs"):
          for i in range(len(module.out_projs)):
              if module.out_projs[i] is not None:
                  nn.init.constant_(module.out_projs[i], 0.0003)
  
      for param in ["r_emb", "r_w_bias", "r_r_bias", "r_bias"]:
          if (
              hasattr(module, param)
              and getattr(module, param) is not None
          ):
              weight = getattr(module, param)
              weight.data.fill_(3)
  
imports: import copy
  import random
  import unittest
  from transformers import TransfoXLConfig, is_torch_available
  from transformers.testing_utils import require_torch, require_torch_multi_gpu, slow, torch_device
  from ...generation.test_generation_utils import GenerationTesterMixin
  from ...test_configuration_common import ConfigTester
  from ...test_modeling_common import ModelTesterMixin, ids_tensor
label_desc: Use image node_id 14 for calling the TransfoXLModelTest obj's underlying member method code with example usage: obj._mock_init_weights(module) without return types