Fix environment variable name (#3893)

docs/pipeline_deploy/serving.en.md

@@ -338,7 +338,7 @@ docker run \
 - If CPU deployment is required, there is no need to specify `--gpus`.
 - If you need to enter the container for debugging, you can replace `/bin/bash server.sh` in the command with `/bin/bash`. Then execute `/bin/bash server.sh` inside the container.
 - If you want the server to run in the background, you can replace `-it` in the command with `-d`. After the container starts, you can view the container logs with `docker logs -f {container ID}`.
-- Add `-e PADDLEX_USE_HPIP=1` to use the PaddleX high-performance inference plugin to accelerate the pipeline inference process. Please refer to the [PaddleX High-Performance Inference Guide](./high_performance_inference.en.md) for more information.
+- Add `-e PADDLEX_HPS_USE_HPIP=1` to use the PaddleX high-performance inference plugin to accelerate the pipeline inference process. Please refer to the [PaddleX High-Performance Inference Guide](./high_performance_inference.en.md) for more information.
 
 You may observe output similar to the following:
 

docs/pipeline_deploy/serving.md

@@ -338,7 +338,7 @@ docker run \
 - 如果希望使用 CPU 部署，则不需要指定 `--gpus`。
 - 如果需要进入容器内部调试，可以将命令中的 `/bin/bash server.sh` 替换为 `/bin/bash`，然后在容器中执行 `/bin/bash server.sh`。
 - 如果希望服务器在后台运行，可以将命令中的 `-it` 替换为 `-d`。容器启动后，可通过 `docker logs -f {容器 ID}` 查看容器日志。
-- 在命令中添加 `-e PADDLEX_USE_HPIP=1` 可以使用 PaddleX 高性能推理插件加速产线推理过程。请参考 [PaddleX 高性能推理指南](./high_performance_inference.md) 获取更多信息。
+- 在命令中添加 `-e PADDLEX_HPS_USE_HPIP=1` 可以使用 PaddleX 高性能推理插件加速产线推理过程。请参考 [PaddleX 高性能推理指南](./high_performance_inference.md) 获取更多信息。
 
 可观察到类似下面的输出信息：