class_docstr: TensorType defines a type for tensors, which consists of a list of dimensions.
  Example:
      class M(torch.nn.Module):
          def forward(self, x:TensorType((1,2,3, Dyn)), y:TensorType((1,2,3, Dyn))):
              return torch.add(x, y)
code: def __repr__(self):
      return f"TensorType[{self.__args__}]"
  
file_path: pytorch/torch/fx/tensor_type.py
imports: from torch.fx.experimental.unification import Var
  from ._compatibility import compatibility
label_desc: Use image node_id 2 for calling the TensorType obj's underlying member method code with example usage: obj.__repr__() and returns: str, self, str