expectedTranspose.addEdge(N4, N3, E34);

    Network<Integer, String> transpose = transpose(directedGraph);
    assertThat(transpose).isEqualTo(expectedTranspose);
    assertThat(transpose(transpose)).isSameInstanceAs(directedGraph);
    AbstractNetworkTest.validateNetwork(transpose);

    assertThat(transpose.edgesConnecting(N1, N2)).isEmpty();
    assertThat(transpose.edgeConnectingOrNull(N1, N2)).isNull();

    Table<String, Integer, Character> transpose = Tables.transpose(original);
    original.put(1, "foo", 'a');
    assertSame(original.columnKeySet(), transpose.rowKeySet());
    assertSame(original.rowKeySet(), transpose.columnKeySet());
    assertSame(original.columnMap(), transpose.rowMap());
    assertSame(original.rowMap(), transpose.columnMap());
    assertSame(original.values(), transpose.values());

    Table<String, Integer, Character> transpose = Tables.transpose(original);
    original.put(1, "foo", 'a');
    assertSame(original.columnKeySet(), transpose.rowKeySet());
    assertSame(original.rowKeySet(), transpose.columnKeySet());
    assertSame(original.columnMap(), transpose.rowMap());
    assertSame(original.rowMap(), transpose.columnMap());
    assertSame(original.values(), transpose.values());

    expectedTranspose.addEdge(N4, N3, E34);

    Network<Integer, String> transpose = transpose(directedGraph);
    assertThat(transpose).isEqualTo(expectedTranspose);
    assertThat(transpose(transpose)).isSameInstanceAs(directedGraph);
    AbstractNetworkTest.validateNetwork(transpose);

    assertThat(transpose.edgesConnecting(N1, N2)).isEmpty();
    assertThat(transpose.edgeConnecting(N1, N2).isPresent()).isFalse();

    public int inDegree(N node) {
      return delegate().outDegree(node); // transpose
    }

    @Override
    public int outDegree(N node) {
      return delegate().inDegree(node); // transpose
    }

    @Override
    public boolean hasEdgeConnecting(N nodeU, N nodeV) {
      return delegate().hasEdgeConnecting(nodeV, nodeU); // transpose
    }

    @Override

                         {6, 15, 24, 6, 15, 24, 6, 15, 24}};

  for (int i{}; i < 4; ++i) {
    bool transpose_a = transpose_a_vals[i];
    bool transpose_b = transpose_b_vals[i];
    Model MatMulModel =
        [transpose_a, transpose_b](
            AbstractContext* ctx,
            absl::Span<AbstractTensorHandle* const> inputs,

     *    dA = U * B.T
     *    dB = A.T * U
     *
     *    where A.T means `transpose(A)`
     */
    AbstractTensorHandle* upstream_grad = grad_outputs[0];

    // Get transpose attrs
    bool t_a;
    TF_RETURN_IF_ERROR(forward_attrs_.Get("transpose_a", &t_a));

    bool t_b;
    TF_RETURN_IF_ERROR(forward_attrs_.Get("transpose_b", &t_b));

    // Conj each input
    AbstractTensorHandle* conj_output;

    super(false, true, true, true, false);
  }

  @Override
  Table<Character, String, Integer> makeTable() {
    Table<String, Character, Integer> original = TreeBasedTable.create();
    return Tables.transpose(original);
  }

    super(false, true, true, true, false);
  }

  @Override
  Table<Character, String, Integer> makeTable() {
    Table<String, Character, Integer> original = TreeBasedTable.create();
    return Tables.transpose(original);
  }

    super(false, true, true, true, true);
  }

  @Override
  Table<String, Character, Integer> makeTable() {
    Table<Character, String, Integer> original = TreeBasedTable.create();
    return Tables.transpose(original);
  }