* Introducing `tf.types.experimental.AtomicFunction` as the fastest way to perform TF computations in Python.

    * Can be accessed through `inference_fn` property of `ConcreteFunction`s
    * Does not support gradients.

Node object.

**Note**: This only impacts validating admission plugins that rely on old
values in certain fields, and does not impact calls from kubelets that go
through the built-in NodeRestriction admission plugin.

**Affected Versions**:
  - kube-apiserver v1.20.0 - v1.20.5
  - kube-apiserver v1.19.0 - v1.19.9
  - kube-apiserver <= v1.18.17

**Fixed Versions**:

A74F          ; valid                                  # 5.1  LATIN SMALL LETTER OO
A750          ; mapped                 ; A751          # 5.1  LATIN CAPITAL LETTER P WITH STROKE THROUGH DESCENDER
A751          ; valid                                  # 5.1  LATIN SMALL LETTER P WITH STROKE THROUGH DESCENDER
A752          ; mapped                 ; A753          # 5.1  LATIN CAPITAL LETTER P WITH FLOURISH

!important;\n}\n\n.text-center {\n  text-align: center !important;\n}\n\n.text-decoration-none {\n  text-decoration: none !important;\n}\n\n.text-decoration-underline {\n  text-decoration: underline !important;\n}\n\n.text-decoration-line-through {\n  text-decoration: line-through !important;\n}\n\n.text-lowercase {\n  text-transform: lowercase !important;\n}\n\n.text-uppercase {\n  text-transform: uppercase !important;\n}\n\n.text-capitalize {\n  text-transform: capitalize !important;\n}\n\n.text-wrap {\n...

      flex-grow: 1;\n        max-width: 100%;\n      }\n\n      @if $grid-row-columns > 0 {\n        @for $i from 1 through $grid-row-columns {\n          .row-cols#{$infix}-#{$i} {\n            @include row-cols($i);\n          }\n        }\n      }\n\n      .col#{$infix}-auto {\n        @include make-col-auto();\n      }\n\n      @if $columns > 0 {\n        @for $i from 1 through $columns {\n          .col#{$infix}-#{$i} {\n            @include make-col($i, $columns);\n          }\n        }\n...

        * Before this, the return content was first passed through `jsonable_encoder` to ensure it was a "jsonable" object, like a `dict`, instead of an arbitrary object with attributes (like an ORM model). That's why you should make sure to update your Pydantic models for objects with attributes to use `orm_mode = True`.
        * If you don't have a `response_model`, the return object will still be passed through `jsonable_encoder` first.

"slow path" // for nonces of other lengths. For a 96-bit nonce, the nonce, along // with a four-byte big-endian counter starting at one, is used // directly as the starting counter. For other nonce sizes, the counter // is computed by passing it through the GHASH function. if len(nonce) == gcmStandardNonceSize { copy(counter[:], nonce) counter[gcmBlockSize-1] = 1 } else { lenBlock := make([]byte, 16) byteorder.BEPutUint64(lenBlock[8:], uint64(len(nonce))*8) ghash(counter, H, nonce, lenBlock) } }...