code: def __init__(self, device, has_bias=True):
      super().__init__()
      self.device = device
  
      self.weights = torch.nn.ParameterList(
          [
              torch.nn.Parameter(torch.randn(50, 100)).to(self.device)
              for _ in range(5)
          ]
      )
  
      self.biases = (
          (
              [
                  torch.nn.Parameter(torch.randn(50)).to(self.device)
                  for _ in range(5)
              ]
          )
          if has_bias
          else [None for _ in range(5)]
      )
  
imports: import functools
  import unittest
  import torch
  import torch._inductor
  from torch._dynamo.test_case import run_tests, TestCase
  from torch._dynamo.utils import counters
  from torch.testing._internal.inductor_utils import HAS_CUDA
label_desc: Use image node_id 1 to create a new MyModule5 object from inherited base classes: torch.nn with example: obj = MyModule5(device, has_bias)