implement, and therefore security issues deriving from their absence are not
considered a vulnerability in TensorFlow.

### Resource allocation

A denial of service caused by one model could bring down the entire server, but
we don't consider this as a vulnerability, given that models can exhaust
resources in many different ways and solutions exist to prevent this from

from decimal import Decimal

from dirty_equals import IsOneOf
from fastapi import FastAPI
from fastapi.testclient import TestClient
from inline_snapshot import snapshot
from pydantic import BaseModel, condecimal

app = FastAPI()


class Item(BaseModel):
    name: str
    age: condecimal(gt=Decimal(0.0))  # type: ignore


@app.post("/items/")
def save_item_no_body(item: list[Item]):
    return {"item": item}

 */
public class SearchQueryException extends FessSystemException {

    /** Serial version UID for serialization. */
    private static final long serialVersionUID = 1L;

    /**
     * Constructs a new SearchQueryException with the specified detail message and cause.
     *
     * @param message The detail message explaining the exception
     * @param cause The cause of this exception
     */

     * @param cause the cause of the exception
     */
    public SMBProtocolDowngradeException(final String message, final Throwable cause) {
        super(message, cause);
    }

    /**
     * Creates a new SMBProtocolDowngradeException with the specified detail message.
     *
     * @param message the detail message
     */
    public SMBProtocolDowngradeException(final String message) {
        super(message);

 */
public class DictionaryException extends FessSystemException {

    /** Serial version UID for serialization. */
    private static final long serialVersionUID = 1L;

    /**
     * Creates a new DictionaryException with the specified message and cause.
     *
     * @param message the detail message
     * @param cause the underlying cause of the exception
     */

def test_decimal_encoder_float():
    data = {"value": Decimal(1.23)}
    assert jsonable_encoder(data) == {"value": 1.23}


def test_decimal_encoder_int():
    data = {"value": Decimal(2)}
    assert jsonable_encoder(data) == {"value": 2}


def test_decimal_encoder_nan():
    data = {"value": Decimal("NaN")}
    assert isnan(jsonable_encoder(data)["value"])

cp -v .ci/init.gradle $HOME/.gradle/init.d

unset JAVA_HOME

if [ -f "/etc/os-release" ] ; then
    cat /etc/os-release
    . /etc/os-release
    if [[ "$ID" == "debian" || "$ID_LIKE" == "debian" ]] ; then
        # FIXME: The base image should not have rpm installed
        sudo rm -Rf /usr/bin/rpm
        # Work around incorrect lintian version

* `bytes`:
    * Стандартний Пайтонівський `bytes`.
    * У запитах і відповідях це буде оброблено як `str`.
    * Згенерована схема буде вказувати, що це `str` з "форматом" `binary`.
* `Decimal`:
    * Стандартний Пайтонівський `Decimal`.
    * У запитах і відповідях це буде оброблено так само, як і `float`.
* Ви можете перевірити всі дійсні типи даних Pydantic тут: [типи даних Pydantic](https://docs.pydantic.dev/latest/usage/types/types/).

tar xzf tzcode$CODE.tar.gz
tar xzf tzdata$DATA.tar.gz

# The PACKRATLIST and PACKRATDATA options are copied from Ubuntu:
# https://git.launchpad.net/ubuntu/+source/tzdata/tree/debian/rules?h=debian/sid
#
# You can see the description of these make variables in the tzdata Makefile:
# https://github.com/eggert/tz/blob/main/Makefile

* `bytes`:
    * Standard Python `bytes`.
    * In requests and responses will be treated as `str`.
    * The generated schema will specify that it's a `str` with `binary` "format".
* `Decimal`:
    * Standard Python `Decimal`.
    * In requests and responses, handled the same as a `float`.
* You can check all the valid Pydantic data types here: [Pydantic data types](https://docs.pydantic.dev/latest/usage/types/types/).