paths:
      - CITATION.cff

permissions:
  contents: read

jobs:
  validate:
    if: github.repository == 'tensorflow/tensorflow' # Don't do this in forks
    name: "validate"
    runs-on: ubuntu-latest
    steps:
      - name: Check out a copy of the repository
        uses: actions/checkout@1af3b93b6815bc44a9784bd300feb67ff0d1eeb3 # v6.0.0

      - name: Check whether the citation metadata from CITATION.cff is valid

      contents: read  # for actions/checkout to fetch code
      security-events: write  # for github/codeql-action/analyze to upload SARIF results
    runs-on: ubuntu-latest

    strategy:
      fail-fast: false
      matrix:
        # Override automatic language detection by changing the below list
        # Supported options are ['csharp', 'cpp', 'go', 'java', 'javascript', 'python']

### Est-ce que la concurrence est mieux que le parallélisme ?

Nope ! C'est ça la morale de l'histoire.

from typing import Annotated

import pytest
from fastapi import FastAPI
from fastapi.testclient import TestClient
from inline_snapshot import snapshot


@pytest.fixture(name="client")
def get_client():
    from pydantic import (
        BaseModel,
        ConfigDict,
        PlainSerializer,
        TypeAdapter,
        WithJsonSchema,
    )

    class FakeNumpyArray:
        def __init__(self):

# despite lacking Nvidia CUDA support.
TFCI_BUILD_PIP_PACKAGE_WHEEL_NAME_ARG="--repo_env=WHEEL_NAME=tensorflow"
TFCI_DOCKER_ENABLE=1
TFCI_DOCKER_IMAGE=us-docker.pkg.dev/ml-oss-artifacts-published/ml-public-container/ml-build-arm64:latest
TFCI_DOCKER_PULL_ENABLE=1
TFCI_DOCKER_REBUILD_ARGS="--target=tf ci/official/containers/ml_build_arm64"
TFCI_INDEX_HTML_ENABLE=1
TFCI_LIB_SUFFIX="-cpu-linux-arm64"
TFCI_OUTPUT_DIR=build_output
TFCI_WHL_AUDIT_ENABLE=1

typing_extensions ~= 4.14.1
gast == 0.4.0
termcolor == 2.3.0
wrapt == 1.16.0
tblib == 2.0.0
ml_dtypes >= 0.5.1, < 0.6.0
auditwheel >= 6.1.0
# Install tensorboard, and keras
# Note that here we want the latest version that matches TF major.minor version
# Note that we must use nightly here as these are used in nightly jobs
# For release jobs, we will pin these on the release branch
keras-nightly ~= 3.10.0.dev
tb-nightly ~= 2.20.0.a

* `datetime.timedelta`:
    * 파이썬의 `datetime.timedelta`.
    * 요청과 응답에서 전체 초(seconds)의 `float`로 표현됩니다.
    * Pydantic은 "ISO 8601 시차 인코딩"으로 표현하는 것 또한 허용합니다. <a href="https://docs.pydantic.dev/latest/concepts/serialization/#json_encoders" class="external-link" target="_blank">더 많은 정보는 이 문서에서 확인하십시오.</a>.
* `frozenset`:
    * 요청과 응답에서 `set`와 동일하게 취급됩니다:
        * 요청 시, 리스트를 읽어 중복을 제거하고 `set`로 변환합니다.

### GNU/Linux and macOS

```sh
docker-compose pull
docker-compose up
```

or

```sh
docker stack deploy --compose-file docker-compose.yaml minio
```

name: 'Dependency Review'
on: [pull_request]

permissions:
  contents: read

jobs:
  dependency-review:
    runs-on: ubuntu-latest
    steps:
      - name: 'Checkout Repository'
        uses: actions/checkout@v4
      - name: 'Dependency Review'

from typing import Annotated

import pytest
from fastapi import FastAPI, Form
from fastapi.exceptions import FastAPIDeprecationWarning
from fastapi.testclient import TestClient
from inline_snapshot import snapshot

from .utils import needs_py310


def get_client():
    app = FastAPI()
    with pytest.warns(FastAPIDeprecationWarning):

        @app.post("/items/")
        async def read_items(