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PaddleSeg/benchmark is used for monitoring the speed of model training.
The content is as follow:
├── README.md
├── configs
│ ├── cityscapes_30imgs.yml
│ ├── fastscnn.yml
│ ├── ocrnet_hrnetw48.yml
│ └── segformer_b0.yml
├── deeplabv3p.yml
├── hrnet.yml
├── hrnet48.yml
├── run_all.sh
├── run_benchmark.sh
├── run_fp16.sh
└── run_fp32.sh
Use Docker to configure the environment.
- docker image: paddlepaddle/paddle:latest-gpu-cuda10.1-cudnn7
- CUDA 10.1 + cudnn7
- paddle=2.1.2
- py=37
git clone https://github.com/PaddlePaddle/PaddleSeg.git
cd PaddleSeg
bash benchmark/run_all.sh
Add the following parameter when training.
--profiler_options="batch_range=[50, 60]; profile_path=model.profile