OVERLAY_REMOVED: `overlay.removed${EVENT_KEY}`,\n  }\n\n  const ClassName = {\n    CARD: 'card',\n  }\n\n  const Selector = {\n    CARD: `.${ClassName.CARD}`,\n    DATA_REFRESH: '[data-card-widget=\"card-refresh\"]',\n  }\n\n  const Default = {\n    source: '',\n    sourceSelector: '',\n    params: {},\n    trigger: Selector.DATA_REFRESH,\n    content: '.card-body',\n    loadInContent: true,\n    loadOnInit: true,\n    responseType: '',\n    overlayTemplate: '<div class=\"overlay\"><i class=\"fas fa-2x...

* With this PR, kubectl and other RestClient's using the AuthProvider framework can make OIDC authenticated requests, and, if there is a refresh token present, the tokens will be refreshed as needed. ([#25270](https://github.com/kubernetes/kubernetes/pull/25270), [@bobbyrullo](https://github.com/bobbyrullo))

    // Stalling the socket will cause TWO requests to time out!
    server.enqueue(MockResponse(socketPolicy = StallSocketAtStart))

    // The 3rd request should be sent to a fresh connection.
    server.enqueue(
      MockResponse(body = "fresh connection"),
    )

    // The first call times out.
    val call1 = client.newCall(Request(server.url("/")))
    assertFailsWith<IOException> {
      call1.execute()

  // - `resourceVersionMatch` = NotOlderThan
  //   is interpreted as "data at least as new as the provided `resourceVersion`"
  //   and the bookmark event is send when the state is synced
  //   to a `resourceVersion` at least as fresh as the one provided by the ListOptions.
  //   If `resourceVersion` is unset, this is interpreted as "consistent read" and the
  //   bookmark event is send when the state is synced at least to the moment

build:mkl_aarch64_threadpool --define=build_with_mkl_aarch64=true
build:mkl_aarch64_threadpool -c opt

# CUDA: This config refers to building CUDA op kernels with nvcc.
build:cuda --repo_env TF_NEED_CUDA=1
build:cuda --crosstool_top=@local_config_cuda//crosstool:toolchain
build:cuda --@local_config_cuda//:enable_cuda

# CUDA: This config refers to building CUDA op kernels with clang.
build:cuda_clang --config=cuda