PER_DAY(
        displayName = "Slow Performance Regression Test",
        timeout = 420,
        channel = "commits",
    ),
    PER_WEEK(
        displayName = "Performance Experiment",
        timeout = 420,
        channel = "experiments",
    ),
    FLAKINESS_DETECTION(
        displayName = "Performance Test Flakiness Detection",
        timeout = 600,
        defaultBaselines = "flakiness-detection-commit",

     * determined experimentally to match our desired probability of false positives.
     */
    // NB: yes, this is surprisingly high, but that's what the experiments said was necessary
    // Raising this number slows the worst-case contains behavior, speeds up hashFloodingDetected,
    // and reduces the false-positive probability.
    static final int MAX_RUN_MULTIPLIER = 13;

			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,

```

</div>

Esse comando gerará o código em `./src/client` e usará o `axios` (a biblioteca HTTP frontend) internamente.

### Experimente o Código do Cliente

Agora você pode importar e usar o código do cliente, ele poderia ser assim, observe que você obtém preenchimento automático para os métodos:

<img src="/img/tutorial/generate-clients/image02.png">

    ] + select({
        "//tensorflow:android": [
            "//tensorflow/c/experimental/stream_executor:stream_executor_hdrs",
            "//tensorflow/core:portable_tensorflow_lib_lite",
        ],
        "//conditions:default": [
            ":tf_tensor",
            "//tensorflow/c/experimental/stream_executor",
            "//tensorflow/c/experimental/stream_executor:stream_executor_internal",
            "//tensorflow/core:framework",

//tensorflow/python/feature_column:vocabulary_testdata
//tensorflow/python/util:nest_test_main_lib
//tensorflow/lite/experimental/examples/lstm:rnn_cell
//tensorflow/lite/experimental/examples/lstm:rnn_cell.py
//tensorflow/lite/experimental/examples/lstm:unidirectional_sequence_lstm_test
//tensorflow/lite/experimental/examples/lstm:unidirectional_sequence_lstm_test.py
//tensorflow/lite/python:interpreter
//tensorflow/lite/python:interpreter_test

[ {
  "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
  } ]

{
  "performanceTests" : [ {
    "testId" : "org.gradle.performance.experiment.declarativedsl.DeclarativeDslFirstUsePerformanceTest.clean checkout",
    "groups" : [ {
      "testProject" : "largeEmptyMultiProjectDeclarativeDsl",
      "coverage" : {
        "per_day" : [ "linux", "macOs", "windows" ]
      }
    } ]
  }, {
    "testId" : "org.gradle.performance.experiment.declarativedsl.DeclarativeDslFirstUsePerformanceTest.cold daemon",

          <option value="io.reactivex.annotations.Experimental" />
          <option value="org.apache.http.annotation.Beta" />
          <option value="org.gradle.api.Incubating" />
          <option value="org.jetbrains.annotations.ApiStatus.Experimental" />
          <option value="rx.annotations.Beta" />
          <option value="rx.annotations.Experimental" />
        </set>
      </option>
    </inspection_tool>

import org.apache.maven.api.annotations.Experimental;
import org.apache.maven.api.annotations.Immutable;
import org.apache.maven.api.annotations.Nonnull;
import org.apache.maven.api.annotations.NotThreadSafe;
import org.apache.maven.api.annotations.Nullable;

import static java.util.Objects.requireNonNull;

/**
 *
 * @since 4.0.0
 */
@Experimental
@Immutable