code: def test_custom_container_forward(self):
      class Inner(torch.nn.Module):
          def forward(self, x):
              return x + 10
  
      class CustomSequential(nn.Sequential):
          def __init__(self):
              super().__init__(nn.ReLU(), Inner())
  
          def forward(self, x):
              x = x + 3
              for mod in self:
                  x = mod(x)
              return x - 5
  
      self.checkModule(CustomSequential(), (torch.tensor(0.5),))
  
      class CustomModuleList(nn.ModuleList):
          def __init__(self):
              super().__init__([nn.ReLU(), Inner()])
  
          def forward(self, x):
              x = x + 3
              for mod in self:
                  x = mod(x)
              return x - 5
  
      self.checkModule(CustomModuleList(), (torch.tensor(0.5),))
  
      class CustomModuleDict(nn.ModuleDict):
          def __init__(self):
              super().__init__(
                  OrderedDict(
                      [
                          ("one", Inner()),
                          ("two", nn.ReLU()),
                          ("three", Inner()),
                      ]
                  )
              )
  
          def forward(self, x):
              x = x + 3
              names = torch.jit.annotate(List[str], [])
              for name, mod in self.items():
                  x = mod(x)
                  names.append(name)
              return names, x - 5
  
      self.checkModule(CustomModuleDict(), (torch.tensor(0.5),))
  
imports: import os
  import sys
  from typing import Any, List, Tuple
  from collections import OrderedDict
  import torch
  import torch.nn
  from torch.testing._internal.jit_utils import JitTestCase
label_desc: Use image node_id 3 for calling the TestModuleContainers obj's underlying member method code with example usage: obj.test_custom_container_forward() and returns: unknown, unknown, unknown, names,  unknown