README.md · 123/pytorch

# PyTorch Ascend Adapter

## Overview

This repository develops the **PyTorch Ascend Adapter** named **torch_npu** to adapt **Ascend NPU** to **PyTorch** so that developers who use the **PyTorch** can obtain powerful compute capabilities of **Ascend AI Processors**.

Ascend is a full-stack AI computing infrastructure for industry applications and services based on Huawei Ascend processors and software. For more information about Ascend, see [Ascend Community](https://www.hiascend.com/en/).

## Installation

### From Binary

Provide users with wheel package to quickly install **torch_npu**. Before installing **torch_npu**, complete the installation of **CANN** according to [Ascend Auxiliary Software](#ascend-auxiliary-software). To obtain the **CANN** installation package, refer to the [CANN Installation](https://www.hiascend.com/en/software/cann/community).

1. **Install PyTorch**

Install **PyTorch** through pip.

**For Aarch64:**

```Python
pip3 install torch==2.1.0
```

**For x86:**

```Python
pip3 install torch==2.1.0+cpu  --index-url https://download.pytorch.org/whl/cpu
```

2. **Install torch-npu dependencies**

Run the following command to install dependencies.

```Python
pip3 install pyyaml
pip3 install setuptools
```

If the installation fails, use the download link or visit the [PyTorch official website](https://pytorch.org/) to download the installation package of the corresponding version.

| OS arch | Python version | link                                                         |
| ------- | -------------- | ------------------------------------------------------------ |
| x86     | Python3.8      | [link](https://download.pytorch.org/whl/cpu/torch-2.1.0%2Bcpu-cp38-cp38-linux_x86_64.whl#sha256=9e5cfd931a65b38d222755a45dabb53b836be31bc620532bc66fee77e3ff67dc) |
| x86     | Python3.9      | [link](https://download.pytorch.org/whl/cpu/torch-2.1.0%2Bcpu-cp39-cp39-linux_x86_64.whl#sha256=86cc28df491fa84738affe752f9870791026565342f69e4ab63e5b935f00a495) |
| x86     | Python3.10     | [link](https://download.pytorch.org/whl/cpu/torch-2.1.0%2Bcpu-cp310-cp310-linux_x86_64.whl#sha256=5077921fc2b54e69a534f3a9c0b98493c79a5547c49d46f5e77e42da3610e011) |
| aarch64 | Python3.8      | [link](https://download.pytorch.org/whl/cpu/torch-2.1.0-cp38-cp38-manylinux_2_17_aarch64.manylinux2014_aarch64.whl#sha256=761822761fffaa1c18a62c5deb13abaa780862577d3eadc428f1daa632536905) |
| aarch64 | Python3.9      | [link](https://download.pytorch.org/whl/cpu/torch-2.1.0-cp39-cp39-manylinux_2_17_aarch64.manylinux2014_aarch64.whl#sha256=de7d63c6ecece118684415a3dbd4805af4a4c1ee1490cccf7405d8c240a481b4) |
| aarch64 | Python3.10     | [link](https://download.pytorch.org/whl/cpu/torch-2.1.0-cp310-cp310-manylinux_2_17_aarch64.manylinux2014_aarch64.whl#sha256=a04a0296d47f28960f51c18c5489a8c3472f624ec3b5bcc8e2096314df8c3342) |

3. **Install torch-npu**

```
pip3 install torch-npu==2.1.0rc1
```

### From Source

In some special scenarios, users may need to compile **torch-npu** by themselves.Select a branch in table [Ascend Auxiliary Software](#ascend-auxiliary-software) and a Python version in table [PyTorch and Python Version Matching Table](#pytorch-and-python-version-matching-table) first. The docker image is recommended for compiling torch-npu through the following steps(It is recommended to mount the working path only and avoid the system path to reduce security risks.):

1. **Clone torch-npu**

```
   git clone https://github.com/ascend/pytorch.git -b v2.1.0-5.0.rc3 --depth 1
   ```

2. **Build Docker Image**

```
   cd pytorch/ci/docker/{arch} # {arch} for X86 or ARM
   docker build -t manylinux-builder:v1 .
   ```

3. **Enter Docker Container**

```
   docker run -it -v /{code_path}/pytorch:/home/pytorch manylinux-builder:v1 bash
   # {code_path} is the torch_npu source code path
   ```

4. **Compile torch-npu**

Take **Python 3.8** as an example.

```
   cd /home/pytorch
   bash ci/build.sh --python=3.8
   ```

## Getting Started

### Prerequisites

Initialize **CANN** environment variable by running the command as shown below.

```Shell
# Default path, change it if needed.
source /usr/local/Ascend/ascend-toolkit/set_env.sh
```

### Quick Verification

You can quickly experience **Ascend NPU** by the following simple examples.

```Python
import torch
import torch_npu

x = torch.randn(2, 2).npu()
y = torch.randn(2, 2).npu()
z = x.mm(y)

print(z)
```

## User Manual

Refer to [API of PyTorch Ascend Adapter](docs/api/torch_npu_apis.md) for more detailed informations.

## PyTorch and Python Version Matching Table

| PyTorch Version | Python Version                                            |
| ------------- | :----------------------------------------------------------- |
| PyTorch1.11.0 | Python3.7.x(>=3.7.5),Python3.8.x,Python3.9.x,Python3.10.x |
| PyTorch2.0.1  | Python3.8.x,Python3.9.x,Python3.10.x                       |
| PyTorch2.1.0  | Python3.8.x,Python3.9.x,Python3.10.x                       |

## Ascend Auxiliary Software

<table><thead align="left"><tr id="row721911327225"><th class="cellrowborder" valign="top" id="mcps1.2.6.1.1"><a name="p0878358152310"></a><a name="p0878358152310"></a>CANN Version
</th>
<th class="cellrowborder" valign="top" id="mcps1.2.6.1.2"><a name="p1833820270243"></a><a name="p1833820270243"></a>Supported PyTorch Version
</th>
<th class="cellrowborder" valign="top" id="mcps1.2.6.1.3"><a name="p7878175817236"></a><a name="p7878175817236"></a>Supported Adapter Version
</th>
<th class="cellrowborder" valign="top" id="mcps1.2.6.1.4"><a name="p58781058202311"></a><a name="p58781058202311"></a>Github Branch
</th>
<th class="cellrowborder" valign="top" id="mcps1.2.6.1.5"><a name="p1887865812234"></a><a name="p1887865812234"></a>AscendHub Image Version/Name(<a href="https://ascendhub.huawei.com/#/detail/pytorch-modelzoo" target="_blank" rel="noopener noreferrer">Link</a>)
</th>
</tr>
</thead>
<tbody><tr id="row1121913217224"><td class="cellrowborder" rowspan="3" valign="top" headers="mcps1.2.6.1.1 "><a name="p387812581238"></a><a name="p387812581238"></a>CANN 7.0.RC1
</td>
<td class="cellrowborder" valign="top" headers="mcps1.2.6.1.2 "><a name="p633892712241"></a><a name="p633892712241"></a>2.1.0
</td>
<td class="cellrowborder" valign="top" headers="mcps1.2.6.1.3 "><a name="p13878165862310"></a><a name="p13878165862310"></a>2.1.0.rc1
</td>
<td class="cellrowborder" valign="top" headers="mcps1.2.6.1.4 "><a name="p5878658162312"></a><a name="p5878658162312"></a>v2.1.0-5.0.rc3
</td>
<td class="cellrowborder" valign="top" headers="mcps1.2.6.1.5 "><a name="p1887895818234"></a><a name="p1887895818234"></a>-
</td>
</tr>
<tr id="row122191232122216"><td class="cellrowborder" valign="top" headers="mcps1.2.6.1.1 "><a name="p1333872762420"></a><a name="p1333872762420"></a>2.0.1
</td>
<td class="cellrowborder" valign="top" headers="mcps1.2.6.1.2 "><a name="p08788581239"></a><a name="p08788581239"></a>2.0.1
</td>
<td class="cellrowborder" valign="top" headers="mcps1.2.6.1.3 "><a name="p88793589233"></a><a name="p88793589233"></a>v2.0.1-5.0.rc3
</td>
<td class="cellrowborder" valign="top" headers="mcps1.2.6.1.4 "><a name="p18791958192318"></a><a name="p18791958192318"></a>-
</td>
</tr>
<tr id="row1220113211225"><td class="cellrowborder" valign="top" headers="mcps1.2.6.1.1 "><a name="p16339162718249"></a><a name="p16339162718249"></a>1.11.0
</td>
<td class="cellrowborder" valign="top" headers="mcps1.2.6.1.2 "><a name="p587919583231"></a><a name="p587919583231"></a>1.11.0.post4
</td>
<td class="cellrowborder" valign="top" headers="mcps1.2.6.1.3 "><a name="p1879185852316"></a><a name="p1879185852316"></a>v1.11.0-5.0.rc3
</td>
<td class="cellrowborder" valign="top" headers="mcps1.2.6.1.4 "><a name="p987915814231"></a><a name="p987915814231"></a>-
</td>
</tr>
<tr id="row92207321228"><td class="cellrowborder" valign="top" headers="mcps1.2.6.1.1 "><a name="p5879195862316"></a><a name="p5879195862316"></a>CANN 6.3.RC3.1
</td>
<td class="cellrowborder" valign="top" headers="mcps1.2.6.1.2 "><a name="p13391127102419"></a><a name="p13391127102419"></a>1.11.0
</td>
<td class="cellrowborder" valign="top" headers="mcps1.2.6.1.3 "><a name="p987935812311"></a><a name="p987935812311"></a>1.11.0.post3
</td>
<td class="cellrowborder" valign="top" headers="mcps1.2.6.1.4 "><a name="p178797587233"></a><a name="p178797587233"></a>v1.11.0-5.0.rc2.2
</td>
<td class="cellrowborder" valign="top" headers="mcps1.2.6.1.5 "><a name="p16879458102316"></a><a name="p16879458102316"></a>-
</td>
</tr>
<tr id="row17220143220221"><td class="cellrowborder" valign="top" headers="mcps1.2.6.1.1 "><a name="p287917582235"></a><a name="p287917582235"></a>CANN 6.3.RC3
</td>
<td class="cellrowborder" valign="top" headers="mcps1.2.6.1.2 "><a name="p933902762410"></a><a name="p933902762410"></a>1.11.0
</td>
<td class="cellrowborder" valign="top" headers="mcps1.2.6.1.3 "><a name="p10879135819230"></a><a name="p10879135819230"></a>1.11.0.post2
</td>
<td class="cellrowborder" valign="top" headers="mcps1.2.6.1.4 "><a name="p17879125816231"></a><a name="p17879125816231"></a>v1.11.0-5.0.rc2.1
</td>
<td class="cellrowborder" valign="top" headers="mcps1.2.6.1.5 "><a name="p10879155882310"></a><a name="p10879155882310"></a>-
</td>
</tr>
<tr id="row422116324224"><td class="cellrowborder" rowspan="3" valign="top" headers="mcps1.2.6.1.1 "><a name="p13879165832316"></a><a name="p13879165832316"></a>CANN 6.3.RC2
</td>
<td class="cellrowborder" valign="top" headers="mcps1.2.6.1.2 "><a name="p1191901662516"></a><a name="p1191901662516"></a>2.0.1
</td>
<td class="cellrowborder" valign="top" headers="mcps1.2.6.1.3 "><a name="p198791258142317"></a><a name="p198791258142317"></a>2.0.1.rc1
</td>
<td class="cellrowborder" valign="top" headers="mcps1.2.6.1.4 "><a name="p1587955816237"></a><a name="p1587955816237"></a>v2.0.1-5.0.rc2
</td>
<td class="cellrowborder" valign="top" headers="mcps1.2.6.1.5 "><a name="p0879558192313"></a><a name="p0879558192313"></a>-
</td>
</tr>
<tr id="row1522123282216"><td class="cellrowborder" valign="top" headers="mcps1.2.6.1.1 "><a name="p19191169254"></a><a name="p19191169254"></a>1.11.0
</td>
<td class="cellrowborder" valign="top" headers="mcps1.2.6.1.2 "><a name="p4879185815238"></a><a name="p4879185815238"></a>1.11.0.post1
</td>
<td class="cellrowborder" valign="top" headers="mcps1.2.6.1.3 "><a name="p887935810232"></a><a name="p887935810232"></a>v1.11.0-5.0.rc2
</td>
<td class="cellrowborder" valign="top" headers="mcps1.2.6.1.4 "><a name="p14879358172313"></a><a name="p14879358172313"></a>23.0.RC1-1.11.0
</td>
</tr>
<tr id="row19716641182317"><td class="cellrowborder" valign="top" headers="mcps1.2.6.1.1 "><a name="p691981615257"></a><a name="p691981615257"></a>1.8.1
</td>
<td class="cellrowborder" valign="top" headers="mcps1.2.6.1.2 "><a name="p208791758142314"></a><a name="p208791758142314"></a>1.8.1.post2
</td>
<td class="cellrowborder" valign="top" headers="mcps1.2.6.1.3 "><a name="p1987935852319"></a><a name="p1987935852319"></a>v1.8.1-5.0.rc2
</td>
<td class="cellrowborder" valign="top" headers="mcps1.2.6.1.4 "><a name="p1087918585237"></a><a name="p1087918585237"></a>23.0.RC1-1.8.1
</td>
</tr>
<tr id="row822143252217"><td class="cellrowborder" rowspan="2" valign="top" headers="mcps1.2.6.1.1 "><a name="p108803589235"></a><a name="p108803589235"></a>CANN 6.3.RC1
<a name="p129081558152312"></a><a name="p129081558152312"></a>
</td>
<td class="cellrowborder" valign="top" headers="mcps1.2.6.1.2 "><a name="p12346162018257"></a><a name="p12346162018257"></a>1.11.0
</td>
<td class="cellrowborder" valign="top" headers="mcps1.2.6.1.3 "><a name="p6880205814236"></a><a name="p6880205814236"></a>1.11.0
</td>
<td class="cellrowborder" valign="top" headers="mcps1.2.6.1.4 "><a name="p6880258162313"></a><a name="p6880258162313"></a>v1.11.0-5.0.rc1
</td>
<td class="cellrowborder" valign="top" headers="mcps1.2.6.1.5 "><a name="p08807589236"></a><a name="p08807589236"></a>-
</td>
</tr>
<tr id="row13745135213239"><td class="cellrowborder" valign="top" headers="mcps1.2.6.1.1 "><a name="p183463202251"></a><a name="p183463202251"></a>1.8.1
</td>
<td class="cellrowborder" valign="top" headers="mcps1.2.6.1.2 "><a name="p1888019580230"></a><a name="p1888019580230"></a>1.8.1.post1
</td>
<td class="cellrowborder" valign="top" headers="mcps1.2.6.1.3 "><a name="p15880105813236"></a><a name="p15880105813236"></a>v1.8.1-5.0.rc1
</td>
<td class="cellrowborder" valign="top" headers="mcps1.2.6.1.4 "><a name="p1588012586230"></a><a name="p1588012586230"></a>-
</td>
</tr>
<tr id="row1667135119236"><td class="cellrowborder" rowspan="3" valign="top" headers="mcps1.2.6.1.1 "><a name="p188801958102315"></a><a name="p188801958102315"></a>CANN 6.0.1
</td>
<td class="cellrowborder" valign="top" headers="mcps1.2.6.1.2 "><a name="p43395279244"></a><a name="p43395279244"></a>1.5.0
</td>
<td class="cellrowborder" valign="top" headers="mcps1.2.6.1.3 "><a name="p118801658182310"></a><a name="p118801658182310"></a>1.5.0.post8
</td>
<td class="cellrowborder" valign="top" headers="mcps1.2.6.1.4 "><a name="p4880125819233"></a><a name="p4880125819233"></a>v1.5.0-3.0.0
</td>
<td class="cellrowborder" valign="top" headers="mcps1.2.6.1.5 "><a name="p8880858122319"></a><a name="p8880858122319"></a>22.0.0
</td>
</tr>
<tr id="row123884481236"><td class="cellrowborder" valign="top" headers="mcps1.2.6.1.1 "><a name="p0339162717244"></a><a name="p0339162717244"></a>1.8.1
</td>
<td class="cellrowborder" valign="top" headers="mcps1.2.6.1.2 "><a name="p15880115811236"></a><a name="p15880115811236"></a>1.8.1
</td>
<td class="cellrowborder" valign="top" headers="mcps1.2.6.1.3 "><a name="p68808584233"></a><a name="p68808584233"></a>v1.8.1-3.0.0
</td>
<td class="cellrowborder" valign="top" headers="mcps1.2.6.1.4 "><a name="p1688035812238"></a><a name="p1688035812238"></a>22.0.0-1.8.1
</td>
</tr>
<tr id="row133914572237"><td class="cellrowborder" valign="top" headers="mcps1.2.6.1.1 "><a name="p10339102719241"></a><a name="p10339102719241"></a>1.11.0
</td>
<td class="cellrowborder" valign="top" headers="mcps1.2.6.1.2 "><a name="p9880205892318"></a><a name="p9880205892318"></a>1.11.0.rc2（beta)
</td>
<td class="cellrowborder" valign="top" headers="mcps1.2.6.1.3 "><a name="p888005822314"></a><a name="p888005822314"></a>v1.11.0-3.0.0
</td>
<td class="cellrowborder" valign="top" headers="mcps1.2.6.1.4 "><a name="p6880145812238"></a><a name="p6880145812238"></a>-
</td>
</tr>
<tr id="row127654514238"><td class="cellrowborder" rowspan="3" valign="top" headers="mcps1.2.6.1.1 "><a name="p1288085862314"></a><a name="p1288085862314"></a>CANN 6.0.RC1
</td>
<td class="cellrowborder" valign="top" headers="mcps1.2.6.1.2 "><a name="p20327103216255"></a><a name="p20327103216255"></a>1.5.0
</td>
<td class="cellrowborder" valign="top" headers="mcps1.2.6.1.3 "><a name="p7880145811235"></a><a name="p7880145811235"></a>1.5.0.post7
</td>
<td class="cellrowborder" valign="top" headers="mcps1.2.6.1.4 "><a name="p1788095815239"></a><a name="p1788095815239"></a>v1.5.0-3.0.rc3
</td>
<td class="cellrowborder" valign="top" headers="mcps1.2.6.1.5 "><a name="p6880115810237"></a><a name="p6880115810237"></a>22.0.RC3
</td>
</tr>
<tr id="row129461142152313"><td class="cellrowborder" valign="top" headers="mcps1.2.6.1.1 "><a name="p14327173292510"></a><a name="p14327173292510"></a>1.8.1
</td>
<td class="cellrowborder" valign="top" headers="mcps1.2.6.1.2 "><a name="p1588035812311"></a><a name="p1588035812311"></a>1.8.1.rc3
</td>
<td class="cellrowborder" valign="top" headers="mcps1.2.6.1.3 "><a name="p13880165816233"></a><a name="p13880165816233"></a>v1.8.1-3.0.rc3
</td>
<td class="cellrowborder" valign="top" headers="mcps1.2.6.1.4 "><a name="p108806581238"></a><a name="p108806581238"></a>22.0.RC3-1.8.1
</td>
</tr>
<tr id="row36411150122319"><td class="cellrowborder" valign="top" headers="mcps1.2.6.1.1 "><a name="p1132743211257"></a><a name="p1132743211257"></a>1.11.0
</td>
<td class="cellrowborder" valign="top" headers="mcps1.2.6.1.2 "><a name="p168800589238"></a><a name="p168800589238"></a>1.11.0.rc1（beta)
</td>
<td class="cellrowborder" valign="top" headers="mcps1.2.6.1.3 "><a name="p28816580233"></a><a name="p28816580233"></a>v1.11.0-3.0.rc3
</td>
<td class="cellrowborder" valign="top" headers="mcps1.2.6.1.4 "><a name="p198811588236"></a><a name="p198811588236"></a>-
</td>
</tr>
<tr id="row12371144713235"><td class="cellrowborder" rowspan="2" valign="top" headers="mcps1.2.6.1.1 "><a name="p11881558122317"></a><a name="p11881558122317"></a>CANN 5.1.RC2
</td>
<td class="cellrowborder" valign="top" headers="mcps1.2.6.1.2 "><a name="p629873412510"></a><a name="p629873412510"></a>1.5.0
</td>
<td class="cellrowborder" valign="top" headers="mcps1.2.6.1.3 "><a name="p3881105818236"></a><a name="p3881105818236"></a>1.5.0.post6
</td>
<td class="cellrowborder" valign="top" headers="mcps1.2.6.1.4 "><a name="p1088125852319"></a><a name="p1088125852319"></a>v1.5.0-3.0.rc2
</td>
<td class="cellrowborder" valign="top" headers="mcps1.2.6.1.5 "><a name="p20881258112316"></a><a name="p20881258112316"></a>22.0.RC2
</td>
</tr>
<tr id="row14956184342315"><td class="cellrowborder" valign="top" headers="mcps1.2.6.1.1 "><a name="p929893462515"></a><a name="p929893462515"></a>1.8.1
</td>
<td class="cellrowborder" valign="top" headers="mcps1.2.6.1.2 "><a name="p688120581238"></a><a name="p688120581238"></a>1.8.1.rc2
</td>
<td class="cellrowborder" valign="top" headers="mcps1.2.6.1.3 "><a name="p198819587236"></a><a name="p198819587236"></a>v1.8.1-3.0.rc2
</td>
<td class="cellrowborder" valign="top" headers="mcps1.2.6.1.4 "><a name="p1388175832319"></a><a name="p1388175832319"></a>22.0.RC2-1.8.1
</td>
</tr>
<tr id="row1522133210223"><td class="cellrowborder" rowspan="2" valign="top" headers="mcps1.2.6.1.1 "><a name="p7881205813233"></a><a name="p7881205813233"></a>CANN 5.1.RC1
</td>
<td class="cellrowborder" valign="top" headers="mcps1.2.6.1.2 "><a name="p1610094112517"></a><a name="p1610094112517"></a>1.5.0
</td>
<td class="cellrowborder" valign="top" headers="mcps1.2.6.1.3 "><a name="p12881165818235"></a><a name="p12881165818235"></a>1.5.0.post5
</td>
<td class="cellrowborder" valign="top" headers="mcps1.2.6.1.4 "><a name="p14881105892315"></a><a name="p14881105892315"></a>v1.5.0-3.0.rc1
</td>
<td class="cellrowborder" valign="top" headers="mcps1.2.6.1.5 "><a name="p5881115812234"></a><a name="p5881115812234"></a>22.0.RC1
</td>
</tr>
<tr id="row182218327224"><td class="cellrowborder" valign="top" headers="mcps1.2.6.1.1 "><a name="p19100441202520"></a><a name="p19100441202520"></a>1.8.1
</td>
<td class="cellrowborder" valign="top" headers="mcps1.2.6.1.2 "><a name="p688165810235"></a><a name="p688165810235"></a>1.8.1.rc1
</td>
<td class="cellrowborder" valign="top" headers="mcps1.2.6.1.3 "><a name="p6881195818236"></a><a name="p6881195818236"></a>v1.8.1-3.0.rc1
</td>
<td class="cellrowborder" valign="top" headers="mcps1.2.6.1.4 "><a name="p58817582239"></a><a name="p58817582239"></a>-
</td>
</tr>
<tr id="row137028392234"><td class="cellrowborder" valign="top" headers="mcps1.2.6.1.1 "><a name="p208815585236"></a><a name="p208815585236"></a>CANN 5.0.4
</td>
<td class="cellrowborder" valign="top" headers="mcps1.2.6.1.2 "><a name="p1289474162511"></a><a name="p1289474162511"></a>1.5.0
</td>
<td class="cellrowborder" valign="top" headers="mcps1.2.6.1.3 "><a name="p68812058102318"></a><a name="p68812058102318"></a>1.5.0.post4
</td>
<td class="cellrowborder" valign="top" headers="mcps1.2.6.1.4 "><a name="p17881658122311"></a><a name="p17881658122311"></a>2.0.4.tr5
</td>
<td class="cellrowborder" valign="top" headers="mcps1.2.6.1.5 "><a name="p1588119588233"></a><a name="p1588119588233"></a>21.0.4
</td>
</tr>
<tr id="row182227322224"><td class="cellrowborder" valign="top" headers="mcps1.2.6.1.1 "><a name="p1188113584232"></a><a name="p1188113584232"></a>CANN 5.0.3
</td>
<td class="cellrowborder" valign="top" headers="mcps1.2.6.1.2 "><a name="p1389417414253"></a><a name="p1389417414253"></a>1.8.1
</td>
<td class="cellrowborder" valign="top" headers="mcps1.2.6.1.3 "><a name="p14881358112314"></a><a name="p14881358112314"></a>1.5.0.post3
</td>
<td class="cellrowborder" valign="top" headers="mcps1.2.6.1.4 "><a name="p9881205862316"></a><a name="p9881205862316"></a>2.0.3.tr5
</td>
<td class="cellrowborder" valign="top" headers="mcps1.2.6.1.5 "><a name="p68811858122317"></a><a name="p68811858122317"></a>21.0.3
</td>
</tr>
<tr id="row17222203202219"><td class="cellrowborder" valign="top" headers="mcps1.2.6.1.1 "><a name="p68814580234"></a><a name="p68814580234"></a>CANN 5.0.2
</td>
<td class="cellrowborder" valign="top" headers="mcps1.2.6.1.2 "><a name="p610954522514"></a><a name="p610954522514"></a>1.5.0
</td>
<td class="cellrowborder" valign="top" headers="mcps1.2.6.1.3 "><a name="p1882758112318"></a><a name="p1882758112318"></a>1.5.0.post2
</td>
<td class="cellrowborder" valign="top" headers="mcps1.2.6.1.4 "><a name="p988215589234"></a><a name="p988215589234"></a>2.0.2.tr5
</td>
<td class="cellrowborder" valign="top" headers="mcps1.2.6.1.5 "><a name="p6882115811231"></a><a name="p6882115811231"></a>21.0.2
</td>
</tr>
</tbody>
</table>

## Suggestions and Communication

Everyone is welcome to contribute to the community. If you have any questions or suggestions, you can submit [Github Issues](https://github.com/Ascend/pytorch/issues). We will reply to you as soon as possible. Thank you very much.

## Branch Maintenance Policies

The version branches of AscendPyTorch have the following maintenance phases:

| **Status**        | **Duration** | **Description**                                                                                                                |
|-------------------|--------------|--------------------------------------------------------------------------------------------------------------------------------|
| Planning          | 1-3 months   | Plan features.                                                                                                                 |
| Development       | 3 months     | Develop features.                                                                                                              |
| Maintained        | 6-12 months  | Allow the incorporation of all resolved issues and release the version.                                                        |
| Unmaintained      | 0-3 months   | Allow the incorporation of all resolved issues. No dedicated maintenance personnel are available. No version will be released. |
| End Of Life (EOL) | N/A          | Do not accept any modification to a branch.                                                                                    |

## Maintenance Status of Existing Branches

| **Branch Name** | **Status** | **Launch Date** | **Subsequent Status** | **EOL Date** |
| --------------- | ---------- | --------------- | --------------------------------------- | ------------ |
| **v2.0.2** | EOL | 2021/7/29 | N/A | |
| **v2.0.3** | EOL | 2021/10/15 | N/A | |
| **v2.0.4** | EOL | 2022/1/15 | N/A | |
| **v3.0.rc1** | EOL | 2022/4/10 | N/A | |
| **v3.0.rc2** | EOL | 2022/7/15 | N/A | |
| **v3.0.rc3** | EOL | 2022/10/20 | N/A | |
| **v3.0.0** | Maintained | 2023/1/18 | Unmaintained 2024-1-18 estimated | |
| **v5.0.rc1** | Maintained | 2023/4/19 | Unmaintained 2024-4-19 estimated | |
| **v5.0.rc2** | Maintained | 2023/7/19 | Unmaintained 2024-7-19 estimated | |
| **v5.0.rc3** | Maintained | 2023/10/15 | Unmaintained 2024-10-15 estimated | |

## Reference Documents

For more detailed information on installation guides, model migration, training/inference tutorials, and API lists, please refer to the [PyTorch Ascend Adapter on the HiAI Community](https://www.hiascend.com/software/ai-frameworks/commercial).

| Document Name                    | Document Link                                                 |
| -------------------------------- | ------------------------------------------------------------ |
| AscendPyTorch Installation Guide  | [link](https://www.hiascend.com/document/detail/zh/canncommercial/70RC1/envdeployment/instg/instg_0083.html) |
| AscendPyTorch Network Model Migration and Training | [link](https://www.hiascend.com/document/detail/zh/canncommercial/70RC1/modeldevpt/ptmigr/AImpug_0002.html) |
| AscendPyTorch Online Inference    | [link](https://www.hiascend.com/document/detail/zh/canncommercial/70RC1/modeldevpt/ptonlineinfer/PyTorch_Infer_000001.html) |
| AscendPyTorch Operator Adaptation | [link](https://www.hiascend.com/document/detail/zh/canncommercial/70RC1/operatordev/tbeaicpudevg/atlasopdev_10_0086.html) |
| AscendPyTorch API List (PyTorch and Custom Interfaces) | [link](https://www.hiascend.com/document/detail/zh/canncommercial/70RC1/modeldevpt/ptmigr/ptaoplist_001.html) |

## License

PyTorch Ascend Adapter has a BSD-style license, as found in the [LICENSE](LICENSE) file.

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