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https://github.com/lromul/nvidia-docker-makefile

An example of using nvidia-docker with Makefile

https://github.com/lromul/nvidia-docker-makefile

Science Score: 13.0%

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    Low similarity (4.6%) to scientific vocabulary
Last synced: 5 months ago · JSON representation

Repository

An example of using nvidia-docker with Makefile

Basic Info
  • Host: GitHub
  • Owner: lRomul
  • Language: Python
  • Default Branch: master
  • Homepage:
  • Size: 11.1 MB
Statistics
  • Stars: 5
  • Watchers: 1
  • Forks: 1
  • Open Issues: 0
  • Releases: 0
Created over 8 years ago · Last pushed over 4 years ago
Metadata Files
Readme

README.md

An example of using nvidia-docker with Makefile

Train EfficientNet B0 on CIFAR with argus and timm.

Requirements

The provided Dockerfile is supplied to build an image with CUDA support and cuDNN.

Build an image and enter bash session bash make build make run or just bash make then run training bash make COMMAND="python cifar_advanced.py --batch_size 256 --lr 0.001"

Run training using command argument bash make COMMAND="python cifar_advanced.py --batch_size 256 --lr 0.001"

Distributed data parallel training with Apex mixed precision and gradient accumulation bash make GPUS=2 COMMAND="./cifar_advanced.sh 2 --batch_size 128 --lr 0.0005 --amp --iter_size 2"

Other Makefile targets ```bash make # stop, build, run

do the same

make stop make build make run

make # by default all GPUs passed make GPUS=all # do the same make GPUS=none # without GPUs

make run GPUS=2 # pass the first two gpus make run GPUS='\"device=0,1\"' # pass GPUs numbered 0 and 1

make logs make exec # runs a new command in a running container make exec COMMAND="bash" # do the same make stop ```

Owner

  • Name: Ruslan Baikulov
  • Login: lRomul
  • Kind: user
  • Location: Moscow, Russia

Deep Learning Engineer

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Dependencies

Dockerfile docker
  • ghcr.io/osai-ai/dokai 21.11-pytorch build