/**
     * Return the <code>InputStream</code> used to read information
     * from this pipe instance. Presumably data would first be written
     * to the <code>OutputStream</code> associated with this Named
     * Pipe instance although this is not a requirement (e.g. a
     * read-only named pipe would write data to this stream on
     * connection). Reading from this stream may block. Therefore it

{!../../docs_src/metadata/tutorial001.py!}
```

/// tip

You can write Markdown in the `description` field and it will be rendered in the output.

///

With this configuration, the automatic API docs would look like:

<img src="/img/tutorial/metadata/image01.png">

## License identifier

Since OpenAPI 3.1.0 and FastAPI 0.99.0, you can also set the `license_info` with an `identifier` instead of a `url`.

For example:

   * free slot.
   *
   * The table size is capped because, when there are more threads
   * than CPUs, supposing that each thread were bound to a CPU,
   * there would exist a perfect hash function mapping threads to
   * slots that eliminates collisions. When we reach capacity, we
   * search for this mapping by randomly varying the hash codes of

  // security reasons anyway. Therefore, the FRQ.close() method provides a way to stop the thread
  // explicitly. This test checks that calling that method does allow an app's ClassLoader to be
  // gc'd even if there is a still a FinalizableReferenceQueue in a static field. (Setting the field

            false
        fi
    done
}

@test "No duplicate files on Windows" {
    cat <<EOF
Please rename files so there are no repeats. For example, README.md and
Readme.md would be the same file on Windows. In this test, you would get a
warning for "readme.md" because it makes everything lowercase. There are
repeats of these filename(s) with different casing:
EOF

# Header Parameter Models

If you have a group of related **header parameters**, you can create a **Pydantic model** to declare them.

This would allow you to **re-use the model** in **multiple places** and also to declare validations and metadata for all the parameters at once. 😎

/// note

This is supported since FastAPI version `0.115.0`. 🤓

///

## Header Parameters with a Pydantic Model

    /*
     * For example, if concentration=2.0, the following takes the square root of
     * the uniformly-distributed random integer, then truncates any fractional
     * part, so higher integers would appear (in this case linearly) more often
     * than lower ones.
     */
    return (int) Math.pow(a, 1.0 / concentration);
  }

  @AfterExperiment
  void tearDown() {
    double req = requests.get();

```Python hl_lines="1  9  12"
{!../../docs_src/response_change_status_code/tutorial001.py!}
```

And then you can return any object you need, as you normally would (a `dict`, a database model, etc).

And if you declared a `response_model`, it will still be used to filter and convert the object you returned.

# Query Parameter Models

If you have a group of **query parameters** that are related, you can create a **Pydantic model** to declare them.

This would allow you to **re-use the model** in **multiple places** and also to declare validations and metadata for all the parameters at once. 😎

/// note

This is supported since FastAPI version `0.115.0`. 🤓

///

## Query Parameters with a Pydantic Model

issue in TensorFlow Lite that is not about Converters, Play Services or Ops
body: - type: dropdown id: issue-type attributes: label: Issue Type description:
What type of issue would you like to report? multiple: false options: - Bug -
Build/Install - Performance - Support - Feature Request - Documentation Feature
Request - Documentation Bug - Others validations: required: true - type: