Writing an apt proxy conf file /etc/apt/apt.conf.d/proxy.conf as below.
Acquire::http::Proxy "socks5h://127.0.0.1:1080";
Acquire::https::Proxy "socks5h://127.0.0.1:1080";
Acquire::socks::Proxy "socks5h://127.0.0.1:1080";
And the proxy settings will be applied the next time we run apt.
Create the config file:
mkdir -p /etc/systemd/system/docker.service.d && \
vi /etc/systemd/system/docker.service.d/http-proxy.confPut up the configs:
| import torch | |
| import time | |
| # --- Test 1 | |
| N = 10 | |
| n = 1000 | |
| A = torch.randn(n, n) | |
| B = torch.randn(n, n) |
| import numpy as np | |
| import numpy.random as npr | |
| import time | |
| # --- Test 1 | |
| N = 100 | |
| n = 2000 | |
| A = npr.randn(n, n) | |
| B = npr.randn(n, n) |
| # Online backup a sqlite3 DB. | |
| # python3 sqlite_online_backup.py db_to_backup.sqlite backup_db.sqlite | |
| import sqlite3 | |
| import sqlitebck | |
| import sys | |
| fname_to_backup = sys.argv[1] | |
| fname_backup = sys.argv[2] |
| '''This scripts implements Kim's paper "Convolutional Neural Networks for Sentence Classification" | |
| with a very small embedding size (20) than the commonly used values (100 - 300) as it gives better | |
| result with much less parameters. | |
| Run on GPU: THEANO_FLAGS=mode=FAST_RUN,device=gpu,floatX=float32 python imdb_cnn.py | |
| Get to 0.853 test accuracy after 5 epochs. 13s/epoch on Nvidia GTX980 GPU. | |
| ''' | |
| from __future__ import print_function |