code: def forward(self, x):
      l1_out = torch.split(x.to(self.device), 100, dim=1)
      l1_linear = [
          torch.nn.functional.linear(
              l1_out[i], self.weights[i], self.biases[i]
          )
          for i in range(len(l1_out))
      ]
      l1_out = torch.cat(l1_linear, dim=1)
      return torch.sin(l1_out)
  
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 MyModule5 obj's underlying member method code with example usage: obj.forward(x) and returns: torch