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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 squared_distance(self, other):
 """ Squared distance of two Vectors. 0.0 2.0 2.0 2.0 Traceback (most recent call last):
 AssertionError: dimension mismatch Traceback (most recent call last):
 AssertionError: dimension mismatch """

        assert len(self) == _vector_size(other), "dimension mismatch"
        if isinstance(other, SparseVector):
            return other.squared_distance(self)
        elif _have_scipy and scipy.sparse.issparse(other):
            return _convert_to_vector(other).squared_distance(self)

        if isinstance(other, Vector):
            other = other.toArray()
        elif not isinstance(other, np.ndarray):
            other = np.array(other)
        diff = self.toArray() - other
        return np.dot(diff, diff)