This class implements the sharpness-aware minimization technique, which
        boosts model performance on various tasks, e.g., ResNet on image
        classification.

*   `tf.data`:

    *   Added support for cross-trainer data caching in tf.data service. This
        saves computation resources when concurrent training jobs train from the

scales as it avoids margin collapsing.\n// stylelint-disable-next-line selector-list-comma-newline-after\nh1, h2, h3, h4, h5, h6 {\n  margin-top: 0;\n  margin-bottom: $headings-margin-bottom;\n}\n\n// Reset margins on paragraphs\n//\n// Similarly, the top margin on `<p>`s get reset. However, we also reset the\n// bottom margin to use `rem` units instead of `em`.\np {\n  margin-top: 0;\n  margin-bottom: $paragraph-margin-bottom;\n}\n\n// Abbreviations\n//\n// 1. Duplicate behavior to the data-* attribute...

%heading;\n  @include font-size($h4-font-size);\n}\n\nh5 {\n  @extend %heading;\n  @include font-size($h5-font-size);\n}\n\nh6 {\n  @extend %heading;\n  @include font-size($h6-font-size);\n}\n\n\n// Reset margins on paragraphs\n//\n// Similarly, the top margin on `<p>`s get reset. However, we also reset the\n// bottom margin to use `rem` units instead of `em`.\n\np {\n  margin-top: 0;\n  margin-bottom: $paragraph-margin-bottom;\n}\n\n\n// Abbreviations\n//\n// 1. Add the correct text decoration in...

{ return nil, nil, errors.New("extendedGCD: both a and m are even") } size := max(len(a.limbs), len(m.limbs)) u = NewNat().set(a).expand(size) v := NewNat().set(m).expand(size) A = NewNat().reset(len(m.limbs)) A.limbs[0] = 1 B := NewNat().reset(len(a.limbs)) C := NewNat().reset(len(m.limbs)) D := NewNat().reset(len(a.limbs)) D.limbs[0] = 1 // Before and after each loop iteration, the following hold: // // u = A*a - B*m // v = D*m - C*a // 0 < u <= a // 0 <= v <= m // 0 <= A < m // 0 <= B <= a // 0...

{ return nil, nil, errors.New("extendedGCD: both a and m are even") } size := max(len(a.limbs), len(m.limbs)) u = NewNat().set(a).expand(size) v := NewNat().set(m).expand(size) A = NewNat().reset(len(m.limbs)) A.limbs[0] = 1 B := NewNat().reset(len(a.limbs)) C := NewNat().reset(len(m.limbs)) D := NewNat().reset(len(a.limbs)) D.limbs[0] = 1 // Before and after each loop iteration, the following hold: // // u = A*a - B*m // v = D*m - C*a // 0 < u <= a // 0 <= v <= m // 0 <= A < m // 0 <= B <= a // 0...

- Server-side apply behavior has been regularized in the case where a field is removed from the applied configuration. Removed fields which have no other owners are deleted from the live object, or reset to their default value if they have one. Safe ownership transfers, such as the transfer of a `replicas` field from a user to an HPA without resetting to the default value are documented in [Transferring Ownership](https://kubernetes.io/docs/refere...

This means that now, if you set a value in a context variable before `yield`, the value would still be available after `yield` (as you would intuitively expect). And it also means that you can reset the context variable with a token afterwards.

For example, this works correctly now:

```Python
from contextvars import ContextVar
from typing import Any, Dict, Optional

pkg go/doc, type Package struct, Examples []*Example
pkg go/doc, type Type struct, Examples []*Example
pkg hash/maphash, func MakeSeed() Seed
pkg hash/maphash, method (*Hash) BlockSize() int
pkg hash/maphash, method (*Hash) Reset()
pkg hash/maphash, method (*Hash) Seed() Seed
pkg hash/maphash, method (*Hash) SetSeed(Seed)
pkg hash/maphash, method (*Hash) Size() int
pkg hash/maphash, method (*Hash) Sum([]uint8) []uint8