code: def squared_distance(self, other):
          
          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)
docs: Squared distance of two Vectors.
  
          >>> dense1 = DenseVector(array.array('d', [1., 2.]))
          >>> dense1.squared_distance(dense1)
          0.0
          >>> dense2 = np.array([2., 1.])
          >>> dense1.squared_distance(dense2)
          2.0
          >>> dense3 = [2., 1.]
          >>> dense1.squared_distance(dense3)
          2.0
          >>> sparse1 = SparseVector(2, [0, 1], [2., 1.])
          >>> dense1.squared_distance(sparse1)
          2.0
          >>> dense1.squared_distance([1.,])
          Traceback (most recent call last):
              ...
          AssertionError: dimension mismatch
          >>> dense1.squared_distance(SparseVector(1, [0,], [1.,]))
          Traceback (most recent call last):
              ...
          AssertionError: dimension mismatch