"true" or "1", this environment variable makes `tf.nn.bias_add` operate
    deterministically (i.e. reproducibly), but currently only when XLA JIT
    compilation is *not* enabled. Setting `TF_DETERMINISTIC_OPS` to "true" or
    "1" also makes cuDNN convolution and max-pooling operate deterministically.
    This makes Keras Conv\*D and MaxPool\*D layers operate deterministically in

Setting options in `include_router` still makes sense in some cases, for example, to override or increase configurations from a third party router included in an app. But in a router that is part of a bigger application, it would probably make more sense to add those settings when creating the `APIRouter`.

**In `FastAPI`**

- Kubeadm: make the kubeconfig files for the kube-controller-manager and kube-scheduler use the LocalAPIEndpoint instead of the ControlPlaneEndpoint. This makes kubeadm clusters more reseliant to version skew problems during immutable upgrades: https://kubernetes.io/docs/setup/release/version-skew-policy/#kube-controller-manager-kube-...

breakpoint width. No query for the smallest breakpoint.\n// Makes the @content apply to the given breakpoint and wider.\n@mixin media-breakpoint-up($name, $breakpoints: $grid-breakpoints) {\n  $min: breakpoint-min($name, $breakpoints);\n  @if $min {\n    @media (min-width: $min) {\n      @content;\n    }\n  } @else {\n    @content;\n  }\n}\n\n// Media of at most the maximum breakpoint width. No query for the largest breakpoint.\n// Makes the @content apply to the given breakpoint and narrower.\n@mixin...

breakpoint width. No query for the smallest breakpoint.\n// Makes the @content apply to the given breakpoint and wider.\n@mixin media-breakpoint-up($name, $breakpoints: $grid-breakpoints) {\n  $min: breakpoint-min($name, $breakpoints);\n  @if $min {\n    @media (min-width: $min) {\n      @content;\n    }\n  } @else {\n    @content;\n  }\n}\n\n// Media of at most the maximum breakpoint width. No query for the largest breakpoint.\n// Makes the @content apply to the given breakpoint and narrower.\n@mixin...

Montgomery multiplication by a value out of the Montgomery domain // takes the result out of Montgomery representation. xR := NewNat().set(x).montgomeryRepresenta(m) // xR = x * R mod m return x.montgomeryMul(xR, y, m) // x = xR * y / R mod m } n := len(m.nat.limbs) xLimbs := x.limbs[:n] yLimbs := y.limbs[:n] switch n { default: // Attempt to use a stack-allocated backing array. T := make([]uint, 0, preallocLimbs*2) if cap(T) < n*2 { T = make([]uint, 0, n*2) } T = T[:n*2] // T = x * y for i := 0; i < n;...