docstr: We should be able to differentiate between two ModuleDict instances
  that have different keys but the same value types.
docstr_tok: ["We","should","be","able","to","differentiate","between","two","ModuleDict","instances","that","have","different","keys","but","the","same","value","types","."]
code: def test_module_dict_same_type_different_name(self):
      """
      We should be able to differentiate between two ModuleDict instances
      that have different keys but the same value types.
      """
  
      class A(torch.nn.Module):
          def forward(self, x):
              return x
  
      class Foo(torch.nn.Module):
          def __init__(self, s):
              super().__init__()
              self.dict = torch.nn.ModuleDict(s)
  
          def forward(self, x):
              return x
  
      a = Foo({"foo": A()})
      b = Foo({"bar": A()})
      c = Foo({"bar": A()})
      self.assertDifferentType(a, b)
      self.assertSameType(b, c)
  
imports: import os
  import sys
  import io
  import torch
  from torch.testing._internal.jit_utils import JitTestCase
  from torch.testing._internal.common_utils import suppress_warnings
label_desc: Use image node_id 23 for calling the TestTypeSharing obj's underlying member method code with example usage: obj.test_module_dict_same_type_different_name() and returns: x, x