code: def test_conv_layout_convert_with_view(self):
      class Model(torch.nn.Module):
          def __init__(self):
              super().__init__()
              self.conv = nn.Conv2d(
                  3, 128, kernel_size=3, padding=1, stride=1, bias=False
              )
              self.bn = nn.BatchNorm2d(3)
  
          def forward(self, x):
              x = self.bn(x)
              x = self.conv(x)
              return torch.flatten(x, 1)
  
      mod = Model().to(self.device).eval()
  
      @torch.compile()
      def foo(mod, inp):
          return mod(inp)
  
      with torch.no_grad():
          x = torch.rand(2, 3, 5, 5).to(self.device)
          mod_eager = mod(x)
          self.assertEqual(foo(mod, x), mod_eager)
  
imports: import contextlib
  import functools
  import importlib
  import itertools
  import os
  import sys
  import unittest
  import weakref
  import torch
  from torch import nn
  from torch._inductor import config
  from torch._inductor.utils import override_lowering, run_and_get_code
  from torch.testing import FileCheck
  from torch.testing._internal.common_cuda import SM80OrLater
  from torch.testing._internal.common_utils import IS_CI, IS_WINDOWS, TEST_WITH_ASAN, TEST_WITH_ROCM, TestCase
  from inductor.test_torchinductor import check_model, check_model_cuda, copy_tests
  from torch.testing._internal.inductor_utils import HAS_CPU, HAS_CUDA
label_desc: Use image node_id 15 for calling the OptimizeForInferenceTemplate obj's underlying member method code with example usage: obj.test_conv_layout_convert_with_view() and returns: mod, torch