--bs-btn-border-radius: var(--bs-border-radius-sm);\n}\n\n.fade {\n  transition: opacity 0.15s linear;\n}\n@media (prefers-reduced-motion: reduce) {\n  .fade {\n    transition: none;\n  }\n}\n.fade:not(.show) {\n  opacity: 0;\n}\n\n.collapse:not(.show) {\n  display: none;\n}\n\n.collapsing {\n  height: 0;\n  overflow: hidden;\n  transition: height 0.35s ease;\n}\n@media (prefers-reduced-motion: reduce) {\n  .collapsing {\n    transition: none;\n  }\n}\n.collapsing.collapse-horizontal {\n  width: 0;\n  height:...

lock {\n  width: 100%;\n}\n\n.fade {\n  transition: opacity 0.15s linear;\n}\n\n@media (prefers-reduced-motion: reduce) {\n  .fade {\n    transition: none;\n  }\n}\n\n.fade:not(.show) {\n  opacity: 0;\n}\n\n.collapse:not(.show) {\n  display: none;\n}\n\n.collapsing {\n  position: relative;\n  height: 0;\n  overflow: hidden;\n  transition: height 0.35s ease;\n}\n\n@media (prefers-reduced-motion: reduce) {\n  .collapsing {\n    transition: none;\n  }\n}\n\n.collapsing.width {\n  width: 0;\n  height:...

&x); out != &v || !isReduced(out.Bytes()) { return false } // Test aliasing the first argument and the receiver. v1 = x if out := f(&v1, &v1, &x); out != &v1 || v1 != v || !isReduced(out.Bytes()) { return false } // Test aliasing the second argument and the receiver. v1 = x if out := f(&v1, &x, &v1); out != &v1 || v1 != v || !isReduced(out.Bytes()) { return false } // Test aliasing both arguments and the receiver. v1 = x if out := f(&v1, &v1, &v1); out != &v1 || v1 != v || !isReduced(out.Bytes()) { return...

        and `tf.data.Dataset.with_options()` respectively.
    *   New `tf.data.Dataset.reduce()` API allows users to reduce a finite
        dataset to a single element using a user-provided reduce function.
    *   New `tf.data.Dataset.window()` API allows users to create finite windows
        of input dataset; when combined with the `tf.data.Dataset.reduce()` API,
        this allows users to implement customized batching.

&x); out != &v || !isReduced(out.Bytes()) { return false } // Test aliasing the first argument and the receiver. v1 = x if out := f(&v1, &v1, &x); out != &v1 || v1 != v || !isReduced(out.Bytes()) { return false } // Test aliasing the second argument and the receiver. v1 = x if out := f(&v1, &x, &v1); out != &v1 || v1 != v || !isReduced(out.Bytes()) { return false } // Test aliasing both arguments and the receiver. v1 = x if out := f(&v1, &v1, &v1); out != &v1 || v1 != v || !isReduced(out.Bytes()) { return...

- Scores from PodTopologySpreading have reduced differentiation as maxSkew increases. ([#90820](https://github.com/kubernetes/kubernetes/pull/90820), [@alculquicondor](https://github.com/alculquicondor)) [SIG Scheduling]

### Internal

* ⬇️ Downgrade LLM translations model to GPT-5 to reduce mistakes. PR [#14823](https://github.com/fastapi/fastapi/pull/14823) by [@tiangolo](https://github.com/tiangolo).