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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 renormalize(self, modelparams):
 """ Renormalizes one or more states represented as model parameter vectors, such that each state has trace 1. :param np.ndarray modelparams: Array of shape ``(n_states, dim ** 2)`` representing one or more states as model parameter vectors. :return: The same state, normalized to trace one. """

        # The 0th basis element (identity) should have
        # a value 1 / sqrt{dim}, since the trace of that basis
        # element is fixed to be sqrt{dim} by convention.
        norm = modelparams[:, 0] * np.sqrt(self._dim)
        assert not np.sum(norm == 0)
        return modelparams / norm[:, None]