patternSet.exclude("snippets/**/*.adoc");
            });

            // TODO: This breaks the provider
            task.setSourceDir(extension.getUserManual().getStagedDocumentation().get().getAsFile());
            // TODO: This breaks the provider
            task.setOutputDir(extension.getUserManual().getStagingRoot().dir("render-multi").get().getAsFile());

  // line breaks. The message must not contain line breaks.
  // If unset, the message is "failed rule: {Rule}".
  // e.g. "must be a URL with the host matching spec.host"
  // If the Expression contains line breaks. Message is required.
  // The message must not contain line breaks.
  // If unset, the message is "failed Expression: {Expression}".
  // +optional

    for (int i = 0; i < 11; i++) {
      limiter.acquire(); // #7, showing off the warmup starting from totally cold
    }

    // make sure the areas (times) remain the same, while permits are different
    assertEvents(
        "R0.00, R1.38, R1.13, R0.88, R0.63, R0.50, R0.50, R0.50", // #1
        "U4.50", // #2

   * returned either this request, or the request upon which this request was derived with
   * [newBuilder].
   *
   * @suppress this method breaks Dokka! https://github.com/Kotlin/dokka/issues/2473
   */
  fun tag(): Any? = tag<Any>()

  /**
   * Returns the tag attached with [type] as a key, or null if no tag is attached with that
   * key.
   */

the Machine Intelligence team at Google Brain to conduct research in machine
learning and neural networks. However, the framework is versatile enough to be
used in other areas as well.

TensorFlow provides stable [Python](https://www.tensorflow.org/api_docs/python)
and [C++](https://www.tensorflow.org/api_docs/cc) APIs, as well as a
non-guaranteed backward compatible API for

    link: https://www.azepug.az/posts/fastapi/#building-simple-e-commerce-with-nuxtjs-and-fastapi-series
    title: Building simple E-Commerce with NuxtJS and FastAPI
  - author: Rodrigo Arenas
    author_link: https://rodrigo-arenas.medium.com/
    link: https://medium.com/analytics-vidhya/serve-a-machine-learning-model-using-sklearn-fastapi-and-docker-85aabf96729b
    title: "Serve a machine learning model using Sklearn, FastAPI and Docker"

    for (int i = 0; i < 11; i++) {
      limiter.acquire(); // #7, showing off the warmup starting from totally cold
    }

    // make sure the areas (times) remain the same, while permits are different
    assertEvents(
        "R0.00, R1.38, R1.13, R0.88, R0.63, R0.50, R0.50, R0.50", // #1
        "U4.50", // #2

          assertEquals(true, ioe.cause?.cause?.message?.startsWith("Invalid input to toASCII"))
        }
        else -> throw ioe
      }
    }
  }

  @Test
  @Disabled("breaks conscrypt test")
  fun testBouncyCastleRequest() {
    assumeNetwork()

    try {
      Security.insertProviderAt(BouncyCastleProvider(), 1)
      Security.insertProviderAt(BouncyCastleJsseProvider(), 2)

<div class="termy">

```console
$ uvicorn main:app --reload

<span style="color: green;">INFO</span>:     Uvicorn running on http://127.0.0.1:8000 (Press CTRL+C to quit)
```

</div>

Si creas un app como:

```Python hl_lines="3"
{!../../../docs_src/first_steps/tutorial002.py!}
```

y lo guardas en un archivo `main.py`, entonces ejecutarías `uvicorn` así:

<div class="termy">

// the [Scanner.Scan] method will step through the 'tokens' of a file, skipping
// the bytes between the tokens. The specification of a token is
// defined by a split function of type [SplitFunc]; the default split
// function breaks the input into lines with line termination stripped. [Scanner.Split]
// functions are defined in this package for scanning a file into
// lines, bytes, UTF-8-encoded runes, and space-delimited words. The