ArrayRef<Attribute> dilations = op.getDilations().getValue();
    ArrayRef<Attribute> strides = op.getStrides().getValue();
    ArrayRef<Attribute> explicit_paddings;
    if (padding == tensorflow::Padding::EXPLICIT) {
      // EXPLICIT padding mode and the associated attribute is attached to
      // Conv2D.
      explicit_paddings =
          op->template getAttrOfType<ArrayAttr>("explicit_paddings").getValue();
    }

`日本語`                                 // UTF-8 input text as a raw literal
"\u65e5\u672c\u8a9e"                    // the explicit Unicode code points
"\U000065e5\U0000672c\U00008a9e"        // the explicit Unicode code points
"\xe6\x97\xa5\xe6\x9c\xac\xe8\xaa\x9e"  // the explicit UTF-8 bytes
</pre>

<p>
If the source code represents a character as two code points, such as

- [`KT-29878`](https://youtrack.jetbrains.com/issue/KT-29878) Smartcasts from type check or null check don't work if explicit true check as reference equality is used
- [`KT-29936`](https://youtrack.jetbrains.com/issue/KT-29936) Smartcasts don't work if comparing with return value of some function and explicit true/false check is used

  - `PriorityLevelConfiguration`: the `.spec.limited.nominalConcurrencyShares` field defaults to `30` only if the field is omitted (v1beta3 also defaulted an explicit `0` value to `30`). Specifying an explicit `0` value is not allowed in the `v1` version in v1.29 to ensure compatibility with `v1.28` API servers. In `v1.30`, explicit `0` values will be allowed in this field in the `v1` API.

// CHECK:  %4 = "tf.Conv2D"(%1, %3) <{data_format = "NHWC", dilations = [1, 1, 1, 1], explicit_paddings = [0, 0, 64, 64, 0, 0, 0, 0], padding = "EXPLICIT", strides = [1, 1, 1, 1], use_cudnn_on_gpu = true}> : (tensor<?x2x1x768xf32>, tensor<128x1x48x768xf32>) -> tensor<?x3x1x768xf32>
// CHECK:  %cst_3 = "tf.Const"() <{value = dense<[0, 3, 1, 2]> : tensor<4xi64>}> : () -> tensor<4xi64>

 - Kubeadm: during "init" an empty cgroupDriver value in the KubeletConfiguration is now always set to "systemd" unless the user is explicit about it. This requires existing machine setups to configure the container runtime to use the "systemd" driver. Documentation on this topic can be found here: https://kubernetes.io/docs/setup/production-environment/container-runtimes/. When upgrading...

- Kubeadm: during "kubeadm init/join/upgrade", always default the `cgroupDriver` value in the `KubeletConfiguration` to `systemd`, unless the user was explicit about the value. See [configure-cgroup-driver](https://kubernetes.io/docs/tasks/administer-cluster/kubeadm/configure-cgroup-driver/) for more details. ([#102133](https://github.com/kubernetes/kubernetes/pull/102133), [@pacoxu](https://github.com/pacoxu))...

## 0.110.3

### Docs

* 📝 Update references to Python version, FastAPI supports all the current versions, no need to make the version explicit. PR [#11496](https://github.com/tiangolo/fastapi/pull/11496) by [@tiangolo](https://github.com/tiangolo).

func.func @maxpool_explicit_padding(%arg0: tensor<2x12x20x7xi32>) -> tensor<2x3x5x7xi32> {
  // CHECK: tf.MaxPool
  // TODO(b/165938852): need to support explicit padding in max_pool.

  %0 = "tf.MaxPool"(%arg0) {data_format = "NHWC", ksize = [1, 2, 2, 1], padding = "EXPLICIT", strides = [1, 4, 4, 1]} : (tensor<2x12x20x7xi32>) -> tensor<2x3x5x7xi32>
  func.return %0 : tensor<2x3x5x7xi32>
}

                          type: string
                        type:
                          description: Type indicates whether this peer is configured
                            via the node-to-node mesh, or via en explicit global or
                            per-node BGPPeer object.
                          type: string
                      type: object
                    type: array
                  peersV6: