_REGISTRY[calib_method] = cls
    return cls

  return decorator


class _CalibrationAlgorithmBase(abc.ABC):
  """Abstract base class for calibration algorithm."""

  def __init__(
      self,
      statistics: calib_stats_pb2.CalibrationStatistics,
      calib_opts: stablehlo_quant_config_pb2.CalibrationOptions,
  ):
    self._statistics = statistics
    self._calib_opts = calib_opts

## Klassen als Abhängigkeiten

Möglicherweise stellen Sie fest, dass Sie zum Erstellen einer Instanz einer Python-Klasse die gleiche Syntax verwenden.

Zum Beispiel:

```Python
class Cat:
    def __init__(self, name: str):
        self.name = name


fluffy = Cat(name="Mr Fluffy")
```

In diesem Fall ist `fluffy` eine Instanz der Klasse `Cat`.

Und um `fluffy` zu erzeugen, rufen Sie `Cat` auf.

```

then it is a "callable".

## Classes as dependencies

You might notice that to create an instance of a Python class, you use that same syntax.

For example:

```Python
class Cat:
    def __init__(self, name: str):
        self.name = name


fluffy = Cat(name="Mr Fluffy")
```

In this case, `fluffy` is an instance of the class `Cat`.

And to create `fluffy`, you are "calling" `Cat`.

в таком случае он является "вызываемым".

## Классы как зависимости

Вы можете заметить, что для создания экземпляра класса в Python используется тот же синтаксис.

Например:

```Python
class Cat:
    def __init__(self, name: str):
        self.name = name


fluffy = Cat(name="Mr Fluffy")
```

В данном случае `fluffy` является экземпляром класса `Cat`.

А чтобы создать `fluffy`, вы "вызываете" `Cat`.

  )
  tf.quantization.experimental.quantize_saved_model(
      '/tmp/input_model',
      '/tmp/output_model',
      quantization_options=quantization_options,
  )
  ```
  """

  def __init__(
      self,
      path_map: Mapping[str, os.PathLike[str]],
      expected_input_key_map: Optional[Mapping[str, Collection[str]]] = None,
  ):
    """Initializes TFRecord represenatative dataset saver.

🌅 📟 🤙 🎏.

, 👥 🔜 🎯 🕴 🔛 🔺.

## 📁 📊

➡️ 💬 👆 ✔️ 📁 📛 `my_super_project` 👈 🔌 🎧-📁 🤙 `sql_app` ⏮️ 📊 💖 👉:

```
.
└── sql_app
    ├── __init__.py
    ├── crud.py
    ├── database.py
    ├── main.py
    └── schemas.py
```

👉 🌖 🎏 📊 👥 ✔️ 🇸🇲 🔰.

🔜 ➡️ 👀 ⚫️❔ 🔠 📁/🕹 🔨.

## ✍ 🏒 🍕

➡️ 🔗 📁 `sql_app/database.py`.

## File structure

Let's say you have a directory named `my_super_project` that contains a sub-directory called `sql_app` with a structure like this:

```
.
└── sql_app
    ├── __init__.py
    ├── crud.py
    ├── database.py
    ├── main.py
    └── schemas.py
```

This is almost the same structure as we had for the SQLAlchemy tutorial.

Now let's see what each file/module does.

## 📁 📊

👫 🖼, ➡️ 💬 👆 ✔️ 📁 📛 `my_super_project` 👈 🔌 🎧-📁 🤙 `sql_app` ⏮️ 📊 💖 👉:

```
.
└── sql_app
    ├── __init__.py
    ├── crud.py
    ├── database.py
    ├── main.py
    ├── models.py
    └── schemas.py
```

📁 `__init__.py` 🛁 📁, ✋️ ⚫️ 💬 🐍 👈 `sql_app` ⏮️ 🌐 🚮 🕹 (🐍 📁) 📦.

🔜 ➡️ 👀 ⚫️❔ 🔠 📁/🕹 🔨.

## ❎ `SQLAlchemy`

🥇 👆 💪 ❎ `SQLAlchemy`:

```
.
└── sql_app
    ├── __init__.py
    ├── crud.py
    ├── database.py
    ├── main.py
    ├── models.py
    └── schemas.py
```

The file `__init__.py` is just an empty file, but it tells Python that `sql_app` with all its modules (Python files) is a package.

Now let's see what each file/module does.

                # TODO: probably make status_code a default class attribute for all
                # responses in Starlette
                response_signature = inspect.signature(current_response_class.__init__)
                status_code_param = response_signature.parameters.get("status_code")
                if status_code_param is not None:
                    if isinstance(status_code_param.default, int):