Summaries/AI/Pytorch/CodeLines.md

Pytorch

Run a docker container

This container runs in background

docker run -d -it --gpus all -name pytorch-container pytorch/pytorch:latest

Jupyter container with pytorch for GPU

docker run -e JUPYTER_ENABLE_LAB=yes -v /home/john/Work/pytorch/:/workspace/dev --gpus all --ipc=host --ulimit memlock=-1 --ulimit stack=67108864 --rm -p 8888:8888 jw/pytorch:0.1

Test GPU

import torch
print(torch.cuda.is_available())

Connect to running container

docker exec -it <container-name> bash
docker exec -it <container-name> bash -c "cat aap"

Stop and start an execistion container

docker stop <container-name>
docker start <container-name>

Example code

# Load libraries
import torch
import torch.nn as nn
from res.plot_lib import set_default, show_scatterplot, plot_bases
from matplotlib.pyplot import plot, title, axis

device = torch.device("cuda:0" if torch.cuda.is_available() else "cpu")