"].");
    return;
  }
  if (!ic_dst->MergeInput(dst.index, shape)) {
    status->status = tensorflow::errors::InvalidArgument(
        "Cannot update edge, incompatible shapes: ", ic_dst->DebugString(shape),
        " and ", ic_dst->DebugString(ic_dst->input(dst.index)), ".");
    return;
  }
  status->status = graph->graph.UpdateEdge(&new_src.oper->node, new_src.index,

  // be inferred.
  TF_Status* status = TF_NewStatus();
  TF_Graph* graph = TF_NewGraph();

  // Create this failure by trying to add two nodes with incompatible shapes
  // (A tensor with shape [2] and a tensor with shape [3] cannot be added).
  const char data[] = {1, 2, 3};
  const int64_t vec2_dims[] = {2};
  unique_tensor_ptr vec2_tensor(

  * The Docker-CRI implementation is enabled by default.
  * It is not compatible with containers created by older Kubelets. It is
    recommended to drain your node before upgrade. If you choose to perform
    an in-place upgrade, the Kubelet will automatically restart all
    Kubernetes-managed containers on the node.
  * It is not compatible with CNI plugins that do not conform to the

* fix nsenter GetFileType issue in containerized kubelet ([#62467](https://github.com/kubernetes/kubernetes/pull/62467), [@andyzhangx](https://github.com/andyzhangx))
* fix incompatible file type checking on Windows ([#62154](https://github.com/kubernetes/kubernetes/pull/62154), [@dixudx](https://github.com/dixudx))

* Resolves forbidden error when the `daemon-set-controller` cluster role access `controllerrevisions` resources. ([#62146](https://github.com/kubernetes/kubernetes/pull/62146), [@frodenas](https://github.com/frodenas))
* fix incompatible file type checking on Windows ([#62154](https://github.com/kubernetes/kubernetes/pull/62154), [@dixudx](https://github.com/dixudx))

   * least one cipher suite enabled.
   *
   * For protocols, at least one of the [required protocols][tlsVersions] must match the socket's
   * enabled protocols.
   */
  fun isCompatible(socket: SSLSocket): Boolean {
    if (!isTls) {
      return false
    }

    if (tlsVersionsAsString != null &&
      !tlsVersionsAsString.hasIntersection(socket.enabledProtocols, naturalOrder())
    ) {

        CipherSuite.TLS_ECDHE_ECDSA_WITH_AES_256_CBC_SHA.javaName,
      )
    assertThat(tlsSpec.isCompatible(socket)).isTrue()
    socket.enabledCipherSuites =
      arrayOf(
        CipherSuite.TLS_ECDHE_ECDSA_WITH_AES_256_CBC_SHA.javaName,
      )
    assertThat(tlsSpec.isCompatible(socket)).isFalse()
  }

  @Test
  fun allEnabledCipherSuites() {
    platform.assumeNotConscrypt()

# JSON Compatible Encoder

There are some cases where you might need to convert a data type (like a Pydantic model) to something compatible with JSON (like a `dict`, `list`, etc).

For example, if you need to store it in a database.

For that, **FastAPI** provides a `jsonable_encoder()` function.

## Using the `jsonable_encoder`

Let's imagine that you have a database `fake_db` that only receives JSON compatible data.

            assertHasAccepted(
                "Method com.example.Task.getSourceCompatibility(): Is not binary compatible. Reason for accepting this: Upgraded property" to listOf("Method return type has changed", "Method is now abstract"),
                "Method com.example.Task.setSourceCompatibility(java.lang.String): Is not binary compatible. Reason for accepting this: Upgraded property" to listOf("Method has been removed"),

            if (c2MoreSpecific) {
                // Incomparable due to cross-assignable arguments (i.e.
                // foo(String, Object) vs. foo(Object, String))
                return INCOMPARABLE;
            }

            return MORE_SPECIFIC;
        }

        if (c2MoreSpecific) {
            return LESS_SPECIFIC;
        }

        // Incomparable due to non-related arguments (i.e.