How to use the tensornetwork.TensorNetwork function in tensornetwork

def get_env_isometry_5(hamiltonian, reduced_density, isometry, unitary):

    net = tn.TensorNetwork("tensorflow")

    iso_l = net.add_node(isometry)
    iso_c = net.add_node(isometry)

    iso_l_con = net.add_node(tf.conj(isometry))
    iso_c_con = net.add_node(tf.conj(isometry))
    iso_r_con = net.add_node(tf.conj(isometry))

    op = net.add_node(hamiltonian)
    rho = net.add_node(reduced_density)

    un_l = net.add_node(unitary)
    un_l_con = net.add_node(tf.conj(unitary))

    un_r = net.add_node(unitary)
    un_r_con = net.add_node(tf.conj(unitary))

def scalar_product(bottom, top):
    """
    calculate the Hilbert-schmidt inner product between `bottom` and `top'
    Args:
        bottom (tf.Tensor)
        top (tf.Tensor)
    Returns:
        tf.Tensor:  the inner product
    """

    net = tn.TensorNetwork("tensorflow")
    b = net.add_node(tf.conj(bottom))
    t = net.add_node(top)
    edges = [net.connect(b[n], t[n]) for n in range(len(bottom.shape))]
    out = net.contract_between(b, t)
    return out.get_tensor()

def two_site_descending_super_operator(rho, isometry, unitary):
    """
    binary mera two-site descending super operator
    Args:
        rho (tf.Tensor):      hamiltonian
        isometry (tf.Tensor): isometry of the binary mera 
        unitary  (tf.Tensor): disentanlger of the mera
    Returns:
        tf.Tensor
    """

    net = tn.TensorNetwork("tensorflow")

    iso_l = net.add_node(isometry)
    iso_r = net.add_node(isometry)
    iso_l_con = net.add_node(tf.conj(isometry))
    iso_r_con = net.add_node(tf.conj(isometry))
    rho = net.add_node(reduced_density)
    un = net.add_node(unitary)
    un_con = net.add_node(tf.conj(unitary))

    out_order = [un_con[0], un_con[1], un[0], un[1]]

    edges[0] = net.connect(iso_l[0], iso_l_con[0])
    edges[1] = net.connect(iso_r[1], iso_r_con[1])
    edges[2] = net.connect(iso_l[2], rho[0])
    edges[3] = net.connect(iso_l_con[2], rho[2])
    edges[4] = net.connect(iso_r[2], rho[1])

def right_ascending_super_operator(hamiltonian, isometry, unitary):
    """
    binary mera right ascending super operator
    Args:
        hamiltonian (tf.Tensor): hamiltonian
        isometry (tf.Tensor): isometry of the binary mera 
        unitary  (tf.Tensor): disentanlger of the mera
    Returns:
        tf.Tensor
    """

    net = tn.TensorNetwork("tensorflow")

    iso_l = net.add_node(isometry)
    iso_c = net.add_node(isometry)
    iso_r = net.add_node(isometry)

    iso_l_con = net.add_node(tf.conj(isometry))
    iso_c_con = net.add_node(tf.conj(isometry))
    iso_r_con = net.add_node(tf.conj(isometry))

    op = net.add_node(hamiltonian)

    un_l = net.add_node(unitary)
    un_l_con = net.add_node(tf.conj(unitary))

    un_r = net.add_node(unitary)
    un_r_con = net.add_node(tf.conj(unitary))

def right_descending_super_operator(reduced_density, isometry, unitary):
    """
    binary mera right descending super operator
    Args:
        reduced_density (tf.Tensor): reduced density matrix
        isometry (tf.Tensor): isometry of the binary mera 
        unitary  (tf.Tensor): disentanlger of the mera
    Returns:
        tf.Tensor
    """

    net = tn.TensorNetwork("tensorflow")

    iso_l = net.add_node(isometry)
    iso_c = net.add_node(isometry)
    iso_r = net.add_node(isometry)

    iso_l_con = net.add_node(tf.conj(isometry))
    iso_c_con = net.add_node(tf.conj(isometry))
    iso_r_con = net.add_node(tf.conj(isometry))

    rho = net.add_node(reduced_density)

    un_l = net.add_node(unitary)
    un_l_con = net.add_node(tf.conj(unitary))

    un_r = net.add_node(unitary)
    un_r_con = net.add_node(tf.conj(unitary))

"""Applies a two-site local operator to an MPS.
    Takes two MPS site tensors and returns new ones, with a center matrix.
    """
  if tf.executing_eagerly():
    # FIXME: Not ideal, but these ops are very costly at compile time
    op_shp = tf.shape(op)
    tf.assert_equal(
        tf.shape(A1)[1],
        op_shp[2],
        message="Operator dimensions do not match MPS physical dimensions.")
    tf.assert_equal(
        tf.shape(A2)[1],
        op_shp[3],
        message="Operator dimensions do not match MPS physical dimensions.")

  net = tn.TensorNetwork("tensorflow")
  nA1 = net.add_node(A1, axis_names=["L", "p", "R"])
  nA2 = net.add_node(A2, axis_names=["L", "p", "R"])
  nop = net.add_node(op, axis_names=["p_out_1", "p_out_2", "p_in_1", "p_in_2"])

  net.connect(nA1["R"], nA2["L"])
  net.connect(nA1["p"], nop["p_in_1"])
  net.connect(nA2["p"], nop["p_in_2"])

  output_order = [nA1["L"], nop["p_out_1"], nop["p_out_2"], nA2["R"]]

  nA12 = net.contract_between(nA1, nA2)
  n_block = net.contract_between(nop, nA12)

  nA1_new, nC, nA2_new, s_rest = net.split_node_full_svd(
      n_block,
      output_order[:2],

def left_descending_super_operator(reduced_density, isometry, unitary):
    """
    binary mera left descending super operator
    Args:
        reduced_density (tf.Tensor): reduced density matrix
        isometry (tf.Tensor): isometry of the binary mera 
        unitary  (tf.Tensor): disentanlger of the mera
    Returns:
        tf.Tensor
    """

    net = tn.TensorNetwork("tensorflow")

    iso_l = net.add_node(isometry)
    iso_c = net.add_node(isometry)
    iso_r = net.add_node(isometry)

    iso_l_con = net.add_node(tf.conj(isometry))
    iso_c_con = net.add_node(tf.conj(isometry))
    iso_r_con = net.add_node(tf.conj(isometry))

    rho = net.add_node(reduced_density)

    un_l = net.add_node(unitary)
    un_l_con = net.add_node(tf.conj(unitary))

    un_r = net.add_node(unitary)
    un_r_con = net.add_node(tf.conj(unitary))

def left_ascending_super_operator(hamiltonian, isometry, unitary):
    """
    binary mera left ascending super operator
    Args:
        hamiltonian (tf.Tensor): hamiltonian
        isometry (tf.Tensor): isometry of the binary mera 
        unitary  (tf.Tensor): disentanlger of the mera
    Returns:
        tf.Tensor
    """

    net = tn.TensorNetwork("tensorflow")

    iso_l = net.add_node(isometry)
    iso_c = net.add_node(isometry)
    iso_r = net.add_node(isometry)

    iso_l_con = net.add_node(tf.conj(isometry))
    iso_c_con = net.add_node(tf.conj(isometry))
    iso_r_con = net.add_node(tf.conj(isometry))

    op = net.add_node(hamiltonian)

    un_l = net.add_node(unitary)
    un_l_con = net.add_node(tf.conj(unitary))

    un_r = net.add_node(unitary)
    un_r_con = net.add_node(tf.conj(unitary))