PaddleX/latest/pipeline_deploy/high_performance_inference

[giscus[bot]]

PaddleX/latest/pipeline_deploy/high_performance_inference

https://paddlepaddle.github.io/PaddleX/latest/pipeline_deploy/high_performance_inference.html

[jiauy]

有没有NPU的高性能支持，比如昇腾910b的，目前测试并发高的情况下，响应速度急剧下降，目前看是多进程对NPU资源的竞争性使用导致的。

[han508]

遇到了同样的问题，请问解决了吗

[jiauy]

不用了，换回GPU了，目前看910b适合部署大模型，小模型多并发性能不行

[a31413510]

您好，可否提供一下在npu上跑的模型和并发配置，我们想复现一下，看看能不能优化这块

[ItsDia]

请问为什么pipeline中指定yaml文件的时候会报如下错误？
pipeline = "paddlex/configs/image_classification/PP-HGNetV2-B6.yaml",

Traceback (most recent call last):
  File "D:\TestProject\pythonProject3\PaddleX\test.py", line 3, in <module>
    pipeline = create_pipeline(
               ^^^^^^^^^^^^^^^^
  File "D:\TestProject\pythonProject3\PaddleX\paddlex\inference\pipelines\__init__.py", line 119, in create_pipeline
    return create_pipeline_from_config(
           ^^^^^^^^^^^^^^^^^^^^^^^^^^^^
  File "D:\TestProject\pythonProject3\PaddleX\paddlex\inference\pipelines\__init__.py", line 70, in create_pipeline_from_config
    pipeline_name = config["Global"]["pipeline_name"]
                    ~~~~~~~~~~~~~~~~^^^^^^^^^^^^^^^^^
KeyError: 'pipeline_name'

[LounesAl]

It looks like you’re trying to use the config module inside the pipeline configuration. A good approach would be to copy one of the existing pipeline configs from .venv/lib/python3.xx/site-packages/paddlex/configs/pipelines and then modify the module_name accordingly.

You might also find this tutorial helpful:
🔗 OCR Pipeline Integration

[ItsDia]

Thanks a lot! i will try it.