The following code is intentionally skeletal. Please feel free to flesh out the details according to your own needs.
import os
import builtins
import argparse
import torch
import torch.distributed as dist
from torchvision.datasets import ImageFolder
from torch.utils.data import DataLoader
| for a in `ls -1 *.tar`; do mkdir ${a%.*}; tar -xf $a -C ${a%.*}; rm -f $a; done & |
| srun --qos=interactive --gres=gpu:2 --ntasks=8 --constraint="gpu_24gb" --pty bash | |
| # interactive on greene | |
| srun --gres=gpu:a100:1 --cpus-per-task=4 --mem=240GB --pty bash |
| wget -i filename.txt |
| from pycocotools.coco import COCO | |
| import numpy as np | |
| dataDir = '/home/emin/coco' | |
| dataType = 'val2017' | |
| annFile = '{}/annotations/instances_{}.json'.format(dataDir, dataType) | |
| coco = COCO(annFile) # build COCO object | |
| catIds = coco.getCatIds() # category ids (80) |
| For transfering the file file.fl, from the first cluster, issue: | |
| scp file.fl [email protected]:/scratch/eo41/ | |
| For transfering the entire directory origin, issue: | |
| scp -r -q origin [email protected]:/scratch/eo41/ |
| nohup python -u /misc/vlgscratch5/LakeGroup/emin/sayavakepicut/read_video.py --save-dir '/misc/vlgscratch5/LakeGroup/emin/sayavakepicut/5fps_300s/ava_trainval' --fps 5 --seg-len 300 '/misc/vlgscratch5/LakeGroup/shared_data/ava_v2/trainval' & |
| checkpoint = torch.load(CHECKPOINT_PATH) | |
| model.module.load_state_dict(checkpoint['model_state_dict']) | |
| del checkpoint | |
| torch.cuda.empty_cache() |
| ls -1 | wc -l |
| git init | |
| git add . && git commit -m "first commit" | |
| git remote add origin REMOTE_GITHUB_REPO_URL | |
| git remote -v | |
| git push origin master |