return i
		}
		i++
		fails++
		if fails >= 4+i>>4 && i < t {
			// Give up on IndexByte, it isn't skipping ahead
			// far enough to be better than Rabin-Karp.
			// Experiments (using IndexPeriodic) suggest
			// the cutover is about 16 byte skips.
			// TODO: if large prefixes of sep are matching
			// we should cutover at even larger average skips,

## Quick Start

[ {
  "scenario" : "org.gradle.performance.experiment.declarativedsl.DeclarativeDslFirstUsePerformanceTest.clean checkout",
  "durations" : [ {
    "testProject" : "largeEmptyMultiProjectDeclarativeDsl",
    "linux" : 468
  } ]
}, {
  "scenario" : "org.gradle.performance.experiment.declarativedsl.DeclarativeDslFirstUsePerformanceTest.cold daemon",
  "durations" : [ {
    "testProject" : "largeEmptyMultiProjectDeclarativeDsl",
    "linux" : 467
  } ]

## Testing locally with Traefik { #testing-locally-with-traefik }

You can easily run the experiment locally with a stripped path prefix using <a href="https://docs.traefik.io/" class="external-link" target="_blank">Traefik</a>.

* Fornecer diretamente 2 interfaces _web_ de documentação interativa.

---

Nós apenas arranhamos a superfície, mas você já tem idéia de como tudo funciona.

Experimente mudar a seguinte linha:

```Python
    return {"item_name": item.name, "item_id": item_id}
```

...de:

```Python
        ... "item_name": item.name ...
```

...para:

*   Add `execute_fn_for_device function` to dynamically choose the
    implementation based on underlying device placement.
*   Eager:
    *   Add `reduce_logsumexp` benchmark with experiment compile.
    *   Give `EagerTensor`s a meaningful `__array__` implementation.
    *   Add another version of defun matmul for performance analysis.
*   `tf.function`/AutoGraph: