different.
        *   `tf.quantize_and_dequantize_v4` (accidentally introduced in
            TensorFlow 2.4): Use `tf.quantization.quantize_and_dequantize_v2`
            instead.
        *   `tf.batch_mat_mul_v3` (accidentally introduced in TensorFlow 2.6):
            Use `tf.linalg.matmul` instead.
        *   `tf.sparse_segment_sum_grad` (accidentally introduced in TensorFlow

## Changes by Kind

### Bug or Regression

- Fix detach from non-existant nodes and support dangling volumes (#104912, @gnufied) [SIG Cloud Provider and Storage]
- Revert PR #102925 which introduced unexpected scheduling behavior based on balanced resource allocation (#105526, @harisund) [SIG Scheduling]

## Dependencies

### Added
_Nothing has changed._

### Changed
_Nothing has changed._

* 🔧 Update sponsors, remove Deta. PR [#11041](https://github.com/tiangolo/fastapi/pull/11041) by [@tiangolo](https://github.com/tiangolo).
* 💄 Fix CSS breaking RTL languages (erroneously introduced by a previous RTL PR). PR [#11039](https://github.com/tiangolo/fastapi/pull/11039) by [@tiangolo](https://github.com/tiangolo).

impl.Register("aes", "AES-NI", &supportsAES) } if cpu.ARM64 { impl.Register("aes", "Armv8.0", &supportsAES) } if cpu.PPC64 || cpu.PPC64le { // The POWER architecture doesn't have a way to turn off AES support // at runtime with GODEBUG=cpu.something=off, so introduce a new GODEBUG // knob for that. It's intentionally only checked at init() time, to // avoid the performance overhead of checking it every time. if godebug.Value("#ppc64aes") == "off" { supportsAES = false } impl.Register("aes", "POWER8", &supportsAES)...