Drop support for Python 3.8 (#34314)

* drop python 3.8

* update docker files

---------

Co-authored-by: ydshieh <ydshieh@users.noreply.github.com>

CONTRIBUTING.md

@@ -132,7 +132,7 @@ You will need basic `git` proficiency to contribute to
 manual. Type `git --help` in a shell and enjoy! If you prefer books, [Pro
 Git](https://git-scm.com/book/en/v2) is a very good reference.
 
-You'll need **[Python 3.8](https://github.com/huggingface/transformers/blob/main/setup.py#L449)** or above to contribute to 🤗 Transformers. Follow the steps below to start contributing:
+You'll need **[Python 3.9](https://github.com/huggingface/transformers/blob/main/setup.py#L449)** or above to contribute to 🤗 Transformers. Follow the steps below to start contributing:
 
 1. Fork the [repository](https://github.com/huggingface/transformers) by
    clicking on the **[Fork](https://github.com/huggingface/transformers/fork)** button on the repository's page. This creates a copy of the code

README.md

@@ -249,7 +249,7 @@ The model itself is a regular [Pytorch `nn.Module`](https://pytorch.org/docs/sta
 
 ### With pip
 
-This repository is tested on Python 3.8+, Flax 0.4.1+, PyTorch 1.11+, and TensorFlow 2.6+.
+This repository is tested on Python 3.9+, Flax 0.4.1+, PyTorch 1.11+, and TensorFlow 2.6+.
 
 You should install 🤗 Transformers in a [virtual environment](https://docs.python.org/3/library/venv.html). If you're unfamiliar with Python virtual environments, check out the [user guide](https://packaging.python.org/guides/installing-using-pip-and-virtual-environments/).
 

docker/transformers-all-latest-gpu/Dockerfile

@@ -1,4 +1,4 @@
-FROM nvidia/cuda:12.1.0-cudnn8-devel-ubuntu20.04
+FROM nvidia/cuda:12.1.0-cudnn8-devel-ubuntu22.04
 LABEL maintainer="Hugging Face"
 
 ARG DEBIAN_FRONTEND=noninteractive

docker/transformers-pytorch-gpu/Dockerfile

@@ -1,4 +1,4 @@
-FROM nvidia/cuda:12.1.0-cudnn8-devel-ubuntu20.04
+FROM nvidia/cuda:12.1.0-cudnn8-devel-ubuntu22.04
 LABEL maintainer="Hugging Face"
 
 ARG DEBIAN_FRONTEND=noninteractive

docker/transformers-quantization-latest-gpu/Dockerfile

@@ -1,4 +1,4 @@
-FROM nvidia/cuda:11.8.0-cudnn8-devel-ubuntu20.04
+FROM nvidia/cuda:11.8.0-cudnn8-devel-ubuntu22.04
 LABEL maintainer="Hugging Face"
 
 ARG DEBIAN_FRONTEND=noninteractive
@@ -9,12 +9,12 @@ SHELL ["sh", "-lc"]
 # The following `ARG` are mainly used to specify the versions explicitly & directly in this docker file, and not meant
 # to be used as arguments for docker build (so far).
 
-ARG PYTORCH='2.2.1'
+ARG PYTORCH='2.4.1'
 # Example: `cu102`, `cu113`, etc.
 ARG CUDA='cu118'
 
 RUN apt update
-RUN apt install -y git libsndfile1-dev tesseract-ocr espeak-ng python python3-pip ffmpeg
+RUN apt install -y git libsndfile1-dev tesseract-ocr espeak-ng python3 python3-pip ffmpeg
 RUN python3 -m pip install --no-cache-dir --upgrade pip
 
 ARG REF=main
@@ -53,7 +53,7 @@ RUN python3 -m pip install --no-cache-dir gguf
 
 # Add autoawq for quantization testing
 # >=v0.2.3 needed for compatibility with torch 2.2.1
-RUN python3 -m pip install --no-cache-dir https://github.com/casper-hansen/AutoAWQ/releases/download/v0.2.3/autoawq-0.2.3+cu118-cp38-cp38-linux_x86_64.whl
+RUN python3 -m pip install --no-cache-dir https://github.com/casper-hansen/AutoAWQ/releases/download/v0.2.3/autoawq-0.2.3+cu118-cp310-cp310-linux_x86_64.whl
 
 # Add quanto for quantization testing
 RUN python3 -m pip install --no-cache-dir optimum-quanto

docker/transformers-tensorflow-gpu/Dockerfile

@@ -1,4 +1,4 @@
-FROM nvidia/cuda:12.1.0-cudnn8-devel-ubuntu20.04
+FROM nvidia/cuda:12.1.0-cudnn8-devel-ubuntu22.04
 LABEL maintainer="Hugging Face"
 
 ARG DEBIAN_FRONTEND=noninteractive

docs/source/de/contributing.md

@@ -112,7 +112,7 @@ Bevor Sie irgendwelchen Code schreiben, empfehlen wir Ihnen dringend, die besteh
 
 Sie benötigen grundlegende `git`-Kenntnisse, um zu 🤗 Transformers beizutragen. Obwohl `git` nicht das einfachste Werkzeug ist, hat es ein sehr gutes Handbuch. Geben Sie `git --help` in eine Shell ein und genießen Sie es! Wenn Sie Bücher bevorzugen, ist [Pro Git](https://git-scm.com/book/en/v2) eine gute Anlaufstelle.
 
-Sie benötigen **[Python 3.8](https://github.com/huggingface/transformers/blob/main/setup.py#L426)** oder höher, um zu 🤗 Transformers beizutragen. Folgen Sie den nachstehenden Schritten, um mit dem Beitrag zu beginnen:
+Sie benötigen **[Python 3.9](https://github.com/huggingface/transformers/blob/main/setup.py#L426)** oder höher, um zu 🤗 Transformers beizutragen. Folgen Sie den nachstehenden Schritten, um mit dem Beitrag zu beginnen:
 
 1. Forken Sie das [Repository](https://github.com/huggingface/transformers), indem Sie auf den **[Fork](https://github.com/huggingface/transformers/fork)**-Button auf der Seite des Repositorys klicken. Dadurch wird eine Kopie des Codes auf Ihrem GitHub-Account erstellt.
 

docs/source/ko/contributing.md

@@ -113,7 +113,7 @@ python src/transformers/commands/transformers_cli.py env
 
 🤗 Transformers에 기여하기 위해서는 기본적인 `git` 사용 능력이 필요합니다. `git`은 사용하기 쉬운 도구는 아니지만, 매우 훌륭한 매뉴얼을 제공합니다. 쉘(shell)에서 `git --help`을 입력하여 확인해보세요! 만약 책을 선호한다면, [Pro Git](https://git-scm.com/book/en/v2)은 매우 좋은 참고 자료가 될 것입니다.
 
-🤗 Transformers에 기여하려면 **[Python 3.8](https://github.com/huggingface/transformers/blob/main/setup.py#L426)** 이상의 버전이 필요합니다. 기여를 시작하려면 다음 단계를 따르세요:
+🤗 Transformers에 기여하려면 **[Python 3.9](https://github.com/huggingface/transformers/blob/main/setup.py#L426)** 이상의 버전이 필요합니다. 기여를 시작하려면 다음 단계를 따르세요:
 
 1. 저장소 페이지에서 **[Fork](https://github.com/huggingface/transformers/fork)** 버튼을 클릭하여 저장소를 포크하세요. 이렇게 하면 코드의 복사본이 여러분의 GitHub 사용자 계정 아래에 생성됩니다.
 

docs/source/zh/contributing.md

@@ -112,7 +112,7 @@ python src/transformers/commands/transformers_cli.py env
 
 要为 🤗 Transformers 做贡献，你需要基本的 `git` 使用技能。虽然 `git` 不是一个很容易使用的工具，但它提供了非常全面的手册，在命令行中输入 `git --help` 并享受吧！如果你更喜欢书籍，[Pro Git](https://git-scm.com/book/en/v2)是一本很好的参考书。
 
-要为 🤗 Transformers 做贡献，你需要 **[Python 3.8](https://github.com/huggingface/transformers/blob/main/setup.py#L426)** 或更高版本。请按照以下步骤开始贡献：
+要为 🤗 Transformers 做贡献，你需要 **[Python 3.9](https://github.com/huggingface/transformers/blob/main/setup.py#L426)** 或更高版本。请按照以下步骤开始贡献：
 
 1. 点击[仓库](https://github.com/huggingface/transformers)页面上的 **[Fork](https://github.com/huggingface/transformers/fork)** 按钮，这会在你的 GitHub 账号下拷贝一份代码。
 

setup.py

@@ -150,7 +150,7 @@ _deps = [
     "pytest>=7.2.0,<8.0.0",
     "pytest-timeout",
     "pytest-xdist",
-    "python>=3.8.0",
+    "python>=3.9.0",
     "ray[tune]>=2.7.0",
     "regex!=2019.12.17",
     "requests",
@@ -451,7 +451,7 @@ setup(
     zip_safe=False,
     extras_require=extras,
     entry_points={"console_scripts": ["transformers-cli=transformers.commands.transformers_cli:main"]},
-    python_requires=">=3.8.0",
+    python_requires=">=3.9.0",
     install_requires=list(install_requires),
     classifiers=[
         "Development Status :: 5 - Production/Stable",
@@ -461,7 +461,6 @@ setup(
         "License :: OSI Approved :: Apache Software License",
         "Operating System :: OS Independent",
         "Programming Language :: Python :: 3",
-        "Programming Language :: Python :: 3.8",
         "Programming Language :: Python :: 3.9",
         "Programming Language :: Python :: 3.10",
         "Topic :: Scientific/Engineering :: Artificial Intelligence",

src/transformers/dependency_versions_table.py

@@ -56,7 +56,7 @@ deps = {
     "pytest": "pytest>=7.2.0,<8.0.0",
     "pytest-timeout": "pytest-timeout",
     "pytest-xdist": "pytest-xdist",
-    "python": "python>=3.8.0",
+    "python": "python>=3.9.0",
     "ray[tune]": "ray[tune]>=2.7.0",
     "regex": "regex!=2019.12.17",
     "requests": "requests",