t0.Multiply(&t1, &t0) // x^1023 -> 1023 = 2^10 - 1 t1.Square(&t0) // 2^11 - 2 for i := 1; i < 10; i++ { // 2^20 - 2^10 t1.Square(&t1) } t1.Multiply(&t1, &t0) // 2^20 - 1 t2.Square(&t1) // 2^21 - 2 for i := 1; i < 20; i++ { // 2^40 - 2^20 t2.Square(&t2) } t1.Multiply(&t2, &t1) // 2^40 - 1 t1.Square(&t1) // 2^41 - 2 for i := 1; i < 10; i++ { // 2^50 - 2^10 t1.Square(&t1) } t0.Multiply(&t1, &t0) // 2^50 - 1 t1.Square(&t0) // 2^51 - 2 for i := 1; i < 50; i++ { // 2^100 - 2^50 t1.Square(&t1) } t1.Multiply(&t1,...

* 🌐 Add Chinese translation for Tutorial - Extra Data Types. PR [#2410](https://github.com/tiangolo/fastapi/pull/2410) by [@maoyibo](https://github.com/maoyibo).
* 🌐 Add Japanese translation for Deployment - Docker. PR [#2312](https://github.com/tiangolo/fastapi/pull/2312) by [@tokusumi](https://github.com/tokusumi).

2C10          ; mapped                 ; 2C40          # 4.1  GLAGOLITIC CAPITAL LETTER NASHI
2C11          ; mapped                 ; 2C41          # 4.1  GLAGOLITIC CAPITAL LETTER ONU
2C12          ; mapped                 ; 2C42          # 4.1  GLAGOLITIC CAPITAL LETTER POKOJI
2C13          ; mapped                 ; 2C43          # 4.1  GLAGOLITIC CAPITAL LETTER RITSI

t0.Multiply(&t1, &t0) // x^1023 -> 1023 = 2^10 - 1 t1.Square(&t0) // 2^11 - 2 for i := 1; i < 10; i++ { // 2^20 - 2^10 t1.Square(&t1) } t1.Multiply(&t1, &t0) // 2^20 - 1 t2.Square(&t1) // 2^21 - 2 for i := 1; i < 20; i++ { // 2^40 - 2^20 t2.Square(&t2) } t1.Multiply(&t2, &t1) // 2^40 - 1 t1.Square(&t1) // 2^41 - 2 for i := 1; i < 10; i++ { // 2^50 - 2^10 t1.Square(&t1) } t0.Multiply(&t1, &t0) // 2^50 - 1 t1.Square(&t0) // 2^51 - 2 for i := 1; i < 50; i++ { // 2^100 - 2^50 t1.Square(&t1) } t1.Multiply(&t1,...

pkg syscall (freebsd-arm64), const DLT_LAPB_WITH_DIR ideal-int
pkg syscall (freebsd-arm64), const DLT_LAPD = 203
pkg syscall (freebsd-arm64), const DLT_LAPD ideal-int
pkg syscall (freebsd-arm64), const DLT_LIN = 212
pkg syscall (freebsd-arm64), const DLT_LIN ideal-int
pkg syscall (freebsd-arm64), const DLT_LINUX_EVDEV = 216
pkg syscall (freebsd-arm64), const DLT_LINUX_EVDEV ideal-int

 * If you use masked losses with Keras the loss values may be different in TensorFlow `2.12` compared to previous versions.
 * In cases where the mask was previously ignored, you will now get an error if you pass a mask with an incompatible shape.

### Major Features and Improvements

`tf.keras`: