ascendai/torch-npu

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镜像标签列表与下载命令

TorchNPU

The plugin is a deep learning adaptation framework based on Atlas, enabling Atlas NPUs to support the PyTorch framework and providing users of the PyTorch framework with the powerful computing power of Atlas AI processors.

Quick Reference

TorchNPU is maintained by the https://www.hiascend.com/developer/software/ai-frameworks/pytorch
Where to get help
- https://www.hiascend.com/developer/ascendhub
- https://www.hiascend.com/document/detail/zh/Pytorch/730/index/index.html
- https://www.hiascend.com/developer
- Issue Feedback

Supported Tags and Dockerfile Usage

Tag Specification

Tags follow the format:

text
<TorchNPU_version>-<CANN_version>-<chip>-<os>-<python_version>

Field	value	Description
TorchNPU Version	2.12.0	For details, see the version notes in the readme.
CANN_version	9.1.0	For details, see the version notes in the readme.
Chip	Specific example values can be found in the CANN mirror	chip model identifier
OS	ubuntu22.04 / openeuler24.03	OS distribution used for the base image
Python Version	py3.12	Major Python version pre-installed in the image

TorchNPU timely adaptation version (pt2.13)

2.13.0rc1-cann9.1.0-310p-ubuntu22.04-py3.12
2.13.0rc1-cann9.1.0-310p-openeuler24.03-py3.12
2.13.0rc1-cann9.1.0-910b-ubuntu22.04-py3.12
2.13.0rc1-cann9.1.0-910b-openeuler24.03-py3.12
2.13.0rc1-cann9.1.0-a3-ubuntu22.04-py3.12
2.13.0rc1-cann9.1.0-a3-openeuler24.03-py3.12
2.13.0rc1-cann9.1.0-950-ubuntu22.04-py3.12
2.13.0rc1-cann9.1.0-950-openeuler24.03-py3.12

Tag list for version 26.1.1

As shown below are all the image tags of the latest 26.1.1 version released by TorchNPU. For all the historical versions, please refer to Supported Tags

2.12.0.post2-cann9.1.0-310p-ubuntu22.04-py3.12
2.12.0.post2-cann9.1.0-310p-openeuler24.03-py3.12
2.12.0.post2-cann9.1.0-910b-ubuntu22.04-py3.12
2.12.0.post2-cann9.1.0-910b-openeuler24.03-py3.12
2.12.0.post2-cann9.1.0-a3-ubuntu22.04-py3.12
2.12.0.post2-cann9.1.0-a3-openeuler24.03-py3.12
2.12.0.post2-cann9.1.0-950-ubuntu22.04-py3.12
2.12.0.post2-cann9.1.0-950-openeuler24.03-py3.12
2.11.0.post2-cann9.1.0-310p-ubuntu22.04-py3.12
2.11.0.post2-cann9.1.0-310p-openeuler24.03-py3.12
2.11.0.post2-cann9.1.0-910b-ubuntu22.04-py3.12
2.11.0.post2-cann9.1.0-910b-openeuler24.03-py3.12
2.11.0.post2-cann9.1.0-a3-ubuntu22.04-py3.12
2.11.0.post2-cann9.1.0-a3-openeuler24.03-py3.12
2.11.0.post2-cann9.1.0-950-ubuntu22.04-py3.12
2.11.0.post2-cann9.1.0-950-openeuler24.03-py3.12
2.10.0.post6-cann9.1.0-310p-ubuntu22.04-py3.12
2.10.0.post6-cann9.1.0-310p-openeuler24.03-py3.12
2.10.0.post6-cann9.1.0-910b-ubuntu22.04-py3.12
2.10.0.post6-cann9.1.0-910b-openeuler24.03-py3.12
2.10.0.post6-cann9.1.0-a3-ubuntu22.04-py3.12
2.10.0.post6-cann9.1.0-a3-openeuler24.03-py3.12
2.10.0.post6-cann9.1.0-950-ubuntu22.04-py3.12
2.10.0.post6-cann9.1.0-950-openeuler24.03-py3.12
2.9.0.post8-cann9.1.0-310p-ubuntu22.04-py3.12
2.9.0.post8-cann9.1.0-310p-openeuler24.03-py3.12
2.9.0.post8-cann9.1.0-910b-ubuntu22.04-py3.12
2.9.0.post8-cann9.1.0-910b-openeuler24.03-py3.12
2.9.0.post8-cann9.1.0-a3-ubuntu22.04-py3.12
2.9.0.post8-cann9.1.0-a3-openeuler24.03-py3.12
2.9.0.post8-cann9.1.0-950-ubuntu22.04-py3.12
2.9.0.post8-cann9.1.0-950-openeuler24.03-py3.12
2.7.1.post10-cann9.1.0-310p-ubuntu22.04-py3.12
2.7.1.post10-cann9.1.0-310p-openeuler24.03-py3.12
2.7.1.post10-cann9.1.0-910b-ubuntu22.04-py3.12
2.7.1.post10-cann9.1.0-910b-openeuler24.03-py3.12
2.7.1.post10-cann9.1.0-a3-ubuntu22.04-py3.12
2.7.1.post10-cann9.1.0-a3-openeuler24.03-py3.12
2.7.1.post10-cann9.1.0-950-ubuntu22.04-py3.12
2.7.1.post10-cann9.1.0-950-openeuler24.03-py3.12

Dockerfile build parameters

See dockerfile:dockerfile

parameters	Description	Required	Reference Source	Value
TORCH_VERSION	Full TorchNPU version number	Yes	TorchNPU repo releases	2.12.0.post2
CHIP_ARCH	chip architecture identifier	Yes	CANN image tag rules	Specific example values can be found in the CANN mirror
OS	Base image operating system	Yes	CANN image tag rules	ubuntu / openeuler
OS_VERSION	Operating system version	Yes	CANN image tag rules	22.04 / 24.03
PY_VERSION	Python version pre-installed in base image	Yes	CANN image tag rules	3.11
CANN_VERSION	CANN toolkit version	Yes	CANN base image repo	9.1.0
ARCH	Host hardware architecture	Yes	Environment hardware	arm / x86
PY_TAG	Python package ABI tag (cp + version number)	Yes	Strictly match PY_VERSION	cp311
TORCH_NPU_RELEASE_VERSION	Official TorchNPU release tag (including PyTorch version)	Yes	TorchNPU repo releases	v26.1.1-pytorch2.12.0.post2
TORCH_NPU_PATCH_TAG	TorchNPU version number in the release package name	Yes	TorchNPU repo releases	2.12.0.post2
MANYLINUX_VER	PyPI package compatible system version	No	torch official wheel spec	manylinux_2_28
PIP_MIRROR_URL	pip installation source URL (Tsinghua mirror by default)	No	PyPI mirror sources	https://pypi.tuna.tsinghua.edu.cn/simple

Parameter Sources

Image tags, operating systems, and version information:https://quay.io/repository/ascend/cann?tab=tags tag
TORCH_NPU_RELEASE_VERSION and TORCH_NPU_PATCH_TAG parameter values are from TorchNPU Official Release Versions. Example with a wheel download URL:

[***]

TORCH_NPU_RELEASE_VERSION is the part between download/ and /torch_npu-, e.g. v26.1.1-pytorch2.12.0.
TORCH_NPU_PATCH_TAG is the part between torch_npu- and -cp310, e.g. 2.12.0.post2.

Quick Start

Build TorchNPU Image

Taking the construction of the 2.12.0.post2-a3-ubuntu22.04-py3.12 image as an example:

bash
docker build \
  --build-arg CHIP_ARCH=a3 \
  --build-arg OS=ubuntu \
  --build-arg OS_VERSION=22.04 \
  --build-arg PY_VERSION=3.11 \
  --build-arg CANN_VERSION=9.1.0 \
  --build-arg ARCH=arm \
  --build-arg PY_TAG=cp311 \
  --build-arg TORCH_NPU_RELEASE_TAG=v26.1.1-pytorch2.12.0 \
  --build-arg TORCH_NPU_PATCH_TAG=2.12.0.post2 \
  -t image_name:tag \
  -f Dockerfile .

Note: If your build environment requires a proxy, pass proxy variables via --build-arg, for example:

bash
docker build \
  --build-arg HTTP_PROXY=http://proxy.example.com:8080 \
  --build-arg HTTPS_PROXY=http://proxy.example.com:8080 \
  --build-arg NO_PROXY=localhost,127.0.0.1 \
  ... \
  -f Dockerfile .

Replace the proxy address and port with your actual environment values.

Run TorchNPU Container

bash
docker run \
    --name pta_container \
    --device /dev/davinci1 \
    --device /dev/davinci_manager \
    --device /dev/devmm_svm \
    --device /dev/hisi_hdc \
    -v /usr/local/dcmi:/usr/local/dcmi \
    -v /usr/local/bin/npu-smi:/usr/local/bin/npu-smi \
    -v /usr/local/Ascend/driver/lib64/:/usr/local/Ascend/driver/lib64/ \
    -v /usr/local/Ascend/driver/version.info:/usr/local/Ascend/driver/version.info \
    -v /etc/ascend_install.info:/etc/ascend_install.info \
    -it ascend/pta:tag bash

Running CANN containers on 950 series aarch64 architecture products

bash
docker run \
    --name pta_container \
    --device /dev/davinci1 \
    --device /dev/davinci_manager \
    --device /dev/hisi_hdc \
    --device /dev/ummu \
    --device /dev/uburma \
    -v /usr/local/dcmi:/usr/local/dcmi \
    -v /usr/local/bin/npu-smi:/usr/local/bin/npu-smi \
    -v /usr/local/Ascend/driver/lib64/:/usr/local/Ascend/driver/lib64/ \
    -v /usr/local/Ascend/driver/version.info:/usr/local/Ascend/driver/version.info \
    -v /etc/ascend_install.info:/etc/ascend_install.info \
    -it ascend/pta:tag bash

Secondary Development

bash
# Use TorchNPU image as base image and add user software
FROM quay.io/ascend/torch-npu:2.12.0.post2-cann9.0.0-910b-ubuntu22.04-py3.12 

RUN apt update -y && \
    apt install gcc ...

...

License/Disclaimer

See the license information for TorchNPU included in these images.

Like all container images, pre-installed software packages (Python, system libraries, etc.) may be subject to their own licenses.

The released Atlas software images are community versions; they are not intended for commercial use and serve solely as references for production practices.

Liability disclaimers are displayed in the image startup information and on the Atlas image platform.

镜像拉取方式

您可以使用以下命令拉取该镜像。请将 <标签> 替换为具体的标签版本。如需查看所有可用标签版本，请访问标签列表页面。

轩辕镜像加速拉取命令点我查看更多 torch-npu 镜像标签

docker pull docker.xuanyuan.run/ascendai/torch-npu:<标签>

使用方法：

DockerHub 原生拉取命令

docker pull ascendai/torch-npu:<标签>

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