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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 get_inverse(self):
 """ Get the dense inverse covariance matrix. This is used for computing gradients, but it is not recommended in general. """

        return self.apply_inverse(np.eye(len(self._factor[0])), in_place=True)