TF_Operation* r, const char* name,
                       bool transpose_a = false, bool transpose_b = false) {
    TF_OperationDescription* desc = TF_NewOperation(graph, "MatMul", name);
    if (transpose_a) {
      TF_SetAttrBool(desc, "transpose_a", 1);
    }
    if (transpose_b) {
      TF_SetAttrBool(desc, "transpose_b", 1);
    }
    TF_AddInput(desc, {l, 0});
    TF_AddInput(desc, {r, 0});

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

*   Fixes a `CHECK` failures in `UnbatchGradOp` ([CVE-2022-35952](https://cve.mitre.org/cgi-bin/cvename.cgi?name=CVE-2022-35952))
*   Fixes a segfault TFLite converter on per-channel quantized transposed convolutions ([CVE-2022-36027](https://cve.mitre.org/cgi-bin/cvename.cgi?name=CVE-2022-36027))
*   Fixes a `CHECK` failures in `AvgPool3DGrad` ([CVE-2022-35959](https://cve.mitre.org/cgi-bin/cvename.cgi?name=CVE-2022-35959))

for i := range e1 { e1[i] = samplePolyCBD(rnd, N) N++ } e2 := samplePolyCBD(rnd, N) u := make([]ringElement, k1024) // NTT⁻¹(AT ◦ r) + e1 for i := range u { var uHat nttElement for j := range r { // Note that i and j are inverted, as we need the transposed of A. uHat = polyAdd(uHat, nttMul(ex.a[j*k1024+i], r[j])) } u[i] = polyAdd(e1[i], inverseNTT(uHat)) } μ := ringDecodeAndDecompr(m) var vNTT nttElement // t⊺ ◦ r for i := range ex.t { vNTT = polyAdd(vNTT, nttMul(ex.t[i], r[i])) } v := polyAdd(po...