and let DE be the Ray incident upon the first side of the Prism AC where
the Light goes into the Glass; and by putting the Proportion of the Sine
of Incidence to the Sine of Refraction as 17 to 11 find EF the first
refracted Ray. Then taking this Ray for the Incident Ray upon the second
side of the Glass BC where the Light goes out, find the next refracted
Ray FG by putting the Proportion of the Sine of Incidence to the Sine of

- Fix memory leak in kube-apiserver when underlying time goes forth and back. ([#96266](https://github.com/kubernetes/kubernetes/pull/96266), [@chenyw1990](https://github.com/chenyw1990)) [SIG API Machinery]

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pub    52931F4B72B4F54C
uid    Roman Leventov <******@****.***>

        layers during functional API construction should now work,
        e.g.`tf.image.ssim_multiscale`
    *   Error messages when Functional API construction goes wrong (and when ops
        cannot be converted to Keras layers automatically) should be clearer and
        easier to understand.
*   `Optimizer.minimize` can now accept a loss `Tensor` and a `GradientTape` as

pkg path/filepath (freebsd-arm64-cgo), const Separator = 47
pkg runtime (freebsd-arm64), const GOARCH = "arm64"
pkg runtime (freebsd-arm64), const GOOS = "freebsd"
pkg runtime (freebsd-arm64-cgo), const GOARCH = "arm64"
pkg runtime (freebsd-arm64-cgo), const GOOS = "freebsd"
pkg strconv (freebsd-arm64), const IntSize = 64
pkg strconv (freebsd-arm64-cgo), const IntSize = 64
pkg syscall (freebsd-arm64), const AF_APPLETALK = 16

pkg path/filepath (freebsd-riscv64-cgo), const Separator = 47 #53466
pkg runtime (freebsd-riscv64), const GOARCH = "riscv64" #53466
pkg runtime (freebsd-riscv64), const GOOS = "freebsd" #53466
pkg runtime (freebsd-riscv64-cgo), const GOARCH = "riscv64" #53466
pkg runtime (freebsd-riscv64-cgo), const GOOS = "freebsd" #53466
pkg runtime/cgo (freebsd-riscv64-cgo), func NewHandle(interface{}) Handle #53466

shape changes from [...] to [..., sizeof(`T`)/sizeof(`type`)].

If `T` is smaller than `type`, the operator requires that the rightmost
dimension be equal to sizeof(`type`)/sizeof(`T`). The shape then goes from
[..., sizeof(`type`)/sizeof(`T`)] to [...].

tf.bitcast() and tf.cast() work differently when real dtype is casted as a complex dtype