*   Add `RFFT2D` as builtin op. (`RFFT2D` also supports `RFFTD`.) Currently
        only supports float32 input.
    *   Add 5D support to `SLICE` op.
    *   TFLite Supports SingatureDef:
        *   TFLiteConverter exports models with SignatureDef
        *   Interpreter supports getting a list of signatures and getting
            callable function for a given signaturedef.

*   `tf.fill` only supports scalar contents, whereas `tf.constant` supports
    Tensor values.
*   `tf.fill` creates an Op in the computation graph that constructs the actual
    Tensor value at runtime. This is in contrast to `tf.constant` which embeds
    the entire Tensor into the graph with a `Const` node.
*   Because `tf.fill` evaluates at graph runtime, it supports dynamic shapes

            "allOf": [
              {
                "$ref": "#/components/schemas/io.k8s.api.core.v1.ObjectFieldSelector"
              }
            ],
            "description": "Selects a field of the pod: supports metadata.name, metadata.namespace, `metadata.labels['<KEY>']`, `metadata.annotations['<KEY>']`, spec.nodeName, spec.serviceAccountName, status.hostIP, status.podIP, status.podIPs."
          },
          "resourceFieldRef": {