code: def __init__(self, z: int, has_bias: bool, device="cuda") -> None:
      super().__init__()
      self.z = z
      self.device = device
      self.seq_len = 10
      self.seq1 = [
          torch.nn.Linear(z, z, has_bias).to(self.device)
          for _ in range(self.seq_len)
      ]
      self.seq2 = [
          torch.nn.Linear(z, z, has_bias).to(self.device)
          for _ in range(self.seq_len)
      ]
      self.seq3 = [
          torch.nn.Linear(z, z, has_bias).to(self.device)
          for _ in range(self.seq_len)
      ]
  
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 MyModule object from inherited base classes: torch.nn with example: obj = MyModule(z, has_bias, device)