under `tf.keras.dtensor` in this release (refer to the `tf.keras` entry).
    The tutoral and guide for DTensor will be published on
    https://www.tensorflow.org/. Please stay tuned.

*   [oneDNN CPU performance optimizations](https://github.com/tensorflow/community/blob/master/rfcs/20210930-enable-onednn-ops.md)
    are available in Linux x86, Windows x86, and Linux aarch64 packages.

to `.form-control` as it's not specific enough. For details, see\n//    https://github.com/twbs/bootstrap/issues/11586.\n\n[type=\"search\"] {\n  outline-offset: -2px; // 1\n  -webkit-appearance: textfield; // 2\n}\n\n// 1. A few input types should stay LTR\n// See https://rtlstyling.com/posts/rtl-styling#form-inputs\n// 2. RTL only output\n// See https://rtlcss.com/learn/usage-guide/control-directives/#raw\n\n/* rtl:raw:\n[type=\"tel\"],\n[type=\"url\"],\n[type=\"email\"],\n[type=\"number\"] {\n...

now involves a // subtraction. // 2. If step 2 (both [x] and [y] are even) runs, abort immediately. This // case needs to be handled by the caller. // 3. Subtract copies of [x] and [y] as needed in step 6 (both [u] and [v] // are odd) so coefficients stay in bounds. // 4. Replace the [u >= v] check with [u > v]. This changes the end // condition to [v = 0] rather than [u = 0]. This saves an extra // subtraction due to which coefficients were negated. // 5. Rename x and y to a and n, to capture that...