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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 apply_grad_cartesian_tensor(grad_X, zmat_dist):
 """Apply the gradient for transformation to cartesian space onto zmat_dist. Args: grad_X (:class:`numpy.ndarray`):
 A ``(3, n, n, 3)`` array. The mathematical details of the index layout is explained in :meth:`~chemcoord.Cartesian.get_grad_zmat()`. zmat_dist (:class:`~chemcoord.Zmat`):
 Distortions in Zmatrix space. Returns: :class:`~chemcoord.Cartesian`: Distortions in cartesian space. """

    columns = ['bond', 'angle', 'dihedral']
    C_dist = zmat_dist.loc[:, columns].values.T
    try:
        C_dist = C_dist.astype('f8')
        C_dist[[1, 2], :] = np.radians(C_dist[[1, 2], :])
    except (TypeError, AttributeError):
        C_dist[[1, 2], :] = sympy.rad(C_dist[[1, 2], :])
    cart_dist = np.tensordot(grad_X, C_dist, axes=([3, 2], [0, 1])).T
    from chemcoord.cartesian_coordinates.cartesian_class_main import Cartesian
    return Cartesian(atoms=zmat_dist['atom'],
                     coords=cart_dist, index=zmat_dist.index)