code: def test_batch_linear_lhs_fusion(self):
      z = 10
      for has_bias in [True, False]:
          counters.clear()
          module = MyModule4(z, "cuda", has_bias)
          input = [torch.randn(20, z, device="cuda")]
          traced = torch.compile(module)
          ref = module(*input)
          res = traced(*input)
          self.compare_pred(module, traced, input)
          self.assertEqual(counters["inductor"]["batch_fusion"], 2)
          self.assertEqual(
              counters["inductor"]["scmerge_split_removed"],
              1,
          )
          self.assertEqual(
              counters["inductor"]["scmerge_cat_removed"],
              1,
          )
          ref.sum().backward()
          res.sum().backward()
          self.compare_parameters(module, traced, rtol=1e-8, atol=1e-8)
          self.compare_gradients(module, traced, rtol=1e-8, atol=1e-8)
          counters.clear()
  
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 8 for calling the TestGroupBatchFusion obj's underlying member method code with example usage: obj.test_batch_linear_lhs_fusion() without return types