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1. More Device Support

The prosperity of the PaddlePaddle ecosystem is inseparable from the contributions of developers and users. We warmly welcome you to provide more device compatibility for PaddleX and greatly appreciate your feedback.

Currently, PaddleX supports Intel/Apple M series CPU, NVIDIA GPUs, XPU, Ascend NPU, Hygon DCU, and MLU. If the device you wish to support is not within the current scope, you can contribute by following the methods below.

1.1 Integration Device into PaddlePaddle Backend

The PaddlePaddle deep learning framework provides multiple integration solutions, including operator development and mapping, subgraph and whole graph integration, deep learning compiler backend integration, and open neural network format conversion. Device vendors can flexibly choose based on their chip architecture design and software stack maturity. For specific details, please refer to PaddlePaddle Custom Device Integration Solutions.

1.2 Support for PaddleCV devkits

Since PaddleX is based on the PaddlePaddle model library, after the device completes the integration into the PaddlePaddle backend, select the corresponding devkit to submit code based on the models already supported by the device to ensure that the relevant devkits are adapted to the corresponding device. Refer to the contribution guides for each devkit:

  1. PaddleClas

  2. PaddleDetection

  3. PaddleSeg

  4. PaddleOCR

  5. PaddleTS

2. Updating PaddleX

After completing the device integration into PaddlePaddle and the PaddleCV devkits, you need to update the device recognition-related code and documentation in PaddleX.

2.1 Inference Support

2.1.1 Version Support (Optional)

If the relevant device has specific requirements for the PaddlePaddle version, you can make judgments based on device information and version information during initialization. The relevant code is located in the _check_paddle_version function in PaddleX Initialization.

2.1.2 Setting Environment Variables (Optional)

If special environment variables need to be set when using the relevant device, you can modify the device environment setup code. The relevant code is located in the set_env_for_device function in PaddleX Environment Variable Settings.

2.1.3 Creating a Predictor

PaddleX's inference capability is provided based on the Paddle Inference Predictor. When creating a Predictor, you need to select different device based on device information and create passes. The relevant code is located in the _create function in PaddleX Predictor Creation.

2.1.4 Updating the Device Support List

When creating a Predictor, it will judge whether the device is already supported. The relevant code is located in the SUPPORT_DEVICE constant in PaddleX Predictor Option.

2.1.5 Updating the Multi-Devices User Guide

Please update the PaddleX multi-devices user guide and add the newly supported device information to the documentation. Both Chinese and English versions need to be updated. The Chinese version is PaddleX多硬件使用指南, and the English version is PaddleX Multi-Devices Usage Guide.

2.1.6 Updating the Installation Tutorial

Please provide device-related installation tutorials in both Chinese and English. The Chinese version can refer to 昇腾 NPU 飞桨安装教程, and the English version can refer to Ascend NPU PaddlePaddle Installation Tutorial.

2.1.7 Updating the Model List

Please provide a list of models supported by the device in both Chinese and English. The Chinese version can refer to PaddleX模型列表（昇腾 NPU）, and the English version can refer to PaddleX Model List (Huawei Ascend NPU).

2.2 Training Support

TODO

3. Submitting a PR

When you complete the device adaptation work, please submit a Pull Request to PaddleX with relevant information. We will validate the model and merge the relevant code after confirmation.

The relevant PR needs to provide information on reproducing model accuracy, including at least the following:

  • The software versions used to validate model accuracy, including but not limited to:

  • Paddle version

  • PaddleCustomDevice version (if any)

  • The branch of PaddleX or the corresponding devkit

  • The machine environment used to validate model accuracy, including but not limited to:

  • Chip model

  • Operating system version

  • Device driver version

  • Operator library version, etc.