code: def forward(self, x: torch.Tensor) -> torch.Tensor:
      t = torch.split(x, [6, 8, 10], dim=1)
      a0 = self.bn0(self.linear0(t[0] + 0.1))
      a1 = self.bn1(self.linear1(t[1] + 0.2))
      a2 = self.bn2(self.linear2(t[2] + 0.3))
      a3 = self.linear3(torch.sin(t[0]))
      a4 = self.linear4(torch.cos(t[1]))
      a5 = self.linear5(torch.sin(t[2] * 0.5))
  
      b = torch.cat([a0, a1, a2, a3, a4, a5])
      return torch.sigmoid(b)
  
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 2 for calling the MyModule2 obj's underlying member method code with example usage: obj.forward(x) and returns: torch