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Solve the following problem using Python, implementing the functions described below, one line at a time
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Description:

def _varslist2axis(cls, fluent: 'TensorFluent', vars_list: List[str]) -> List[int]:
        '''Maps the `vars_list` into a list of axis indices
        corresponding to the `fluent` scope.

        Args:
            x: The fluent.
            vars_list: The list of variables to be aggregated over.

        Returns:
            List[int]: a list of axis.
        '''
        axis = []
        for var in vars_list:
            if var in fluent.scope.as_list():
                ax = fluent.scope.index(var)
                if fluent.batch:
                    ax += 1
                axis.append(ax)
        return axis