| def get_gpu_memory_map(): | |
| """Get the current gpu usage. | |
| Returns | |
| ------- | |
| usage: dict | |
| Keys are device ids as integers. | |
| Values are memory usage as integers in MB. | |
| """ | |
| result = subprocess.check_output( |
| import requests | |
| def download_file_from_google_drive(id, destination): | |
| def get_confirm_token(response): | |
| for key, value in response.cookies.items(): | |
| if key.startswith('download_warning'): | |
| return value | |
| return None |
| perl tools/tokenizer.perl -a -no-escape -l en -q < sample_sentences.txt > sample_sentences.atok | |
| python translate.py -gpu 0 -model available_models/averaged-10-epoch.pt -src sample_sentences.atok -verbose -output sample_sentences.de.atok |
docker pull nvcr.io/nvidia/pytorch:18.01-py3
nvidia-docker run -it --name sai nvcr.io/nvidia/pytorch:18.01-py3 /bin/bash
(Just try to import torch in python shell here). Exit with Ctrl+D.
docker commit -m test -a sai pytorch_sai nvcr.io/mila1234/pytorch_sai:1
docker push nvcr.io/mila1234/pytorch_sai:1
Source: #clusters by Olexa Bilanuik
Important Environment Variables
PATH: Ordered, colon (:)-separated list of directories. List of directories searched by the shell for executables to execute.LD_LIBRARY_PATH: Ordered, colon (:)-separated list of directories. Contributes to, but is not the only, list of directories searched by the dynamic linker for libraries to load.Execution of a Program in a Shell
cmd arg arg arg... in a shell, your shell will:
| http://www.sixarm.com/about/java-install-openjdk-ant-ivy-on-ubuntu-linux.html | |
| https://freethreads.wordpress.com/2012/07/22/pylucene-installation-on-ubuntu-12-04/ | |
| http://apache.forsale.plus/lucene/pylucene/ | |
| https://lucene.apache.org/pylucene/install.html |
| import datetime | |
| import linecache | |
| import os | |
| import pynvml3 | |
| import torch | |
| print_tensor_sizes = True | |
| last_tensor_sizes = set() | |
| gpu_profile_fn = f'{datetime.datetime.now():%d-%b-%y-%H:%M:%S}-gpu_mem_prof.txt' |