`dtensor.shutdown_tpu_system`.

## Deprecations

*   The C++ `tensorflow::Code` and `tensorflow::Status` will become aliases of
    respectively `absl::StatusCode` and `absl::Status` in some future release.
    *   Use `tensorflow::OkStatus()` instead of `tensorflow::Status::OK()`.
    *   Stop constructing `Status` objects from `tensorflow::error::Code`.
    *   One MUST NOT access `tensorflow::errors::Code` fields. Accessing

  - `spec.usages` is now required, may not contain duplicate values, and must only contain known usages
  - `status.conditions` may not contain duplicate types
  - `status.conditions[*].status` is now required

INFO:     Uvicorn running on http://127.0.0.1:8000 (Press CTRL+C to quit)
INFO:     Started reloader process [2248755] using WatchFiles
INFO:     Started server process [2248757]
INFO:     Waiting for application startup.
INFO:     Application startup complete.
```

### Refactors

gradient-x($start-color: $gray-700, $end-color: $gray-800, $start-percent: 0%, $end-percent: 100%) {\n  background-image: linear-gradient(to right, $start-color $start-percent, $end-color $end-percent);\n}\n\n// Vertical gradient, from top to bottom\n//\n// Creates two color stops, start and end, by specifying a color and position for each color stop.\n@mixin gradient-y($start-color: $gray-700, $end-color: $gray-800, $start-percent: null, $end-percent: null) {\n  background-image: linear-gradient(to bottom,...

zetas[m] m-- t := f[start] f[start] = fieldAdd(t, f[start+2]) f[start+2] = fieldMontgomeryMulSu(zeta, f[start+2], t) t = f[start+1] f[start+1] = fieldAdd(t, f[start+3]) f[start+3] = fieldMontgomeryMulSu(zeta, f[start+3], t) } for start := 0; start < 256; start += 8 { zeta := zetas[m] m-- t := f[start] f[start] = fieldAdd(t, f[start+4]) f[start+4] = fieldMontgomeryMulSu(zeta, f[start+4], t) t = f[start+1] f[start+1] = fieldAdd(t, f[start+5]) f[start+5] = fieldMontgomeryMulSu(zeta, f[start+5], t) t = f[start+2]...

stop.\n@mixin gradient-y($start-color: $gray-700, $end-color: $gray-800, $start-percent: 0%, $end-percent: 100%) {\n  background-image: linear-gradient(to bottom, $start-color $start-percent, $end-color $end-percent);\n  background-repeat: repeat-x;\n}\n\n@mixin gradient-directional($start-color: $gray-700, $end-color: $gray-800, $deg: 45deg) {\n  background-image: linear-gradient($deg, $start-color, $end-color);\n  background-repeat: repeat-x;\n}\n@mixin gradient-x-three-colors($start-color: $blue, $mid-color:...

// overflowing m. After that, we need to reduce every time we shift. i := len(x.limbs) - 1 // For the first N - 1 limbs we can skip the actual shifting and position // them at the shifted position, which starts at min(N - 2, i). start := len(m.nat.limbs) - 2 if i < start { start = i } for j := start; j >= 0; j-- { out.limbs[j] = x.limbs[i] i-- } // We shift in the remaining limbs, reducing modulo m each time. for i >= 0 { out.shiftIn(x.limbs[i], m) i-- } return out } // ExpandFor ensures x has the...