{\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: auto;\n...

: 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: auto;\n...

        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.

### 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).

!= nil { t.Errorf("failed bytes->FE->bytes round-trip: %v", err) } f2 := func(fe, r Element) bool { r.SetBytes(fe.Bytes()) // Intentionally not using Equal not to go through Bytes again. // Calling reduce because both Generate and SetBytes can produce // non-canonical representations. fe.reduce() r.reduce() return fe == r } if err := quick.Check(f2, nil); err != nil { t.Errorf("failed FE->bytes->FE round-trip: %v", err) } // Check some fixed vectors from dalek type feRTTest struct { fe Element b []byte...

!= nil { t.Errorf("failed bytes->FE->bytes round-trip: %v", err) } f2 := func(fe, r Element) bool { r.SetBytes(fe.Bytes()) // Intentionally not using Equal not to go through Bytes again. // Calling reduce because both Generate and SetBytes can produce // non-canonical representations. fe.reduce() r.reduce() return fe == r } if err := quick.Check(f2, nil); err != nil { t.Errorf("failed FE->bytes->FE round-trip: %v", err) } // Check some fixed vectors from dalek type feRTTest struct { fe Element b []byte...

- Improve speed of vSphere PV provisioning and reduce number of API calls ([#102351](https://github.com/kubernetes/kubernetes/pull/102351), [@gnufied](https://github.com/gnufied)) [SIG Cloud Provider and Storage]