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 __eq__(self, other):
      if isinstance(other, self.__class__):
          return list(self.__args__) == list(other.__args__)
      else:
          return False
  
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 3 for calling the TensorType obj's underlying member method code with example usage: obj.__eq__(other) and returns: unknown, False