def push(self, inputs=None):
        """
        Add another frame to the context. Optionally provide a tuple of
        (name list, Var list) to populate the new context frame.
        """
        self._current_graph.append({})

        if inputs is not None:
            if len(inputs[0]) != len(inputs[1]):
                raise ValueError("name list and Var list must be the same length")
            for name, var in zip(inputs[0], inputs[1]):
                self.add(var, torch_name=name)

        Add another frame to the context. Optionally provide a tuple of
        (name list, Var list) to populate the new context frame.
        
coremltools/converters/mil/frontend/torch/converter.py