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Add Docs glossary links (#16448)

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Signed-off-by: UltralyticsAssistant <web@ultralytics.com>
Co-authored-by: UltralyticsAssistant <web@ultralytics.com>
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Glenn Jocher 2024-09-23 23:48:46 +02:00 • committed by GitHub
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docs/en/yolov5/tutorials/multi_gpu_training.md
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@ -18,7 +18,7 @@ pip install -r requirements.txt # install
💡 ProTip! **Docker Image** is recommended for all Multi-GPU trainings. See [Docker Quickstart Guide](../environments/docker_image_quickstart_tutorial.md) <a href="https://hub.docker.com/r/ultralytics/yolov5"><img src="https://img.shields.io/docker/pulls/ultralytics/yolov5?logo=docker" alt="Docker Pulls"></a>
💡 ProTip! `torch.distributed.run` replaces `torch.distributed.launch` in **PyTorch>=1.9**. See [docs](https://pytorch.org/docs/stable/distributed.html) for details.
💡 ProTip! `torch.distributed.run` replaces `torch.distributed.launch` in **[PyTorch](https://www.ultralytics.com/glossary/pytorch)>=1.9**. See [docs](https://pytorch.org/docs/stable/distributed.html) for details.
## Training
@ -69,7 +69,7 @@ python -m torch.distributed.run --nproc_per_node 2 train.py --batch 64 --data co
<details>
<summary>Use SyncBatchNorm (click to expand)</summary>
[SyncBatchNorm](https://pytorch.org/docs/master/generated/torch.nn.SyncBatchNorm.html) could increase accuracy for multiple gpu training, however, it will slow down training by a significant factor. It is **only** available for Multiple GPU DistributedDataParallel training.
[SyncBatchNorm](https://pytorch.org/docs/master/generated/torch.nn.SyncBatchNorm.html) could increase [accuracy](https://www.ultralytics.com/glossary/accuracy) for multiple gpu training, however, it will slow down training by a significant factor. It is **only** available for Multiple GPU DistributedDataParallel training.
It is best used when the batch-size on **each** GPU is small (<= 8).
@ -121,7 +121,7 @@ python -m torch.distributed.run --master_port 1234 --nproc_per_node 2 ...
## Results
DDP profiling results on an [AWS EC2 P4d instance](../environments/aws_quickstart_tutorial.md) with 8x A100 SXM4-40GB for YOLOv5l for 1 COCO epoch.
DDP profiling results on an [AWS EC2 P4d instance](../environments/aws_quickstart_tutorial.md) with 8x A100 SXM4-40GB for YOLOv5l for 1 COCO [epoch](https://www.ultralytics.com/glossary/epoch).
<details>
<summary>Profiling code</summary>