Haaroon

git branch -m main master
git push -u origin master
git remote set-head origin master
# Now go to github in a browser, 
# open the repo, click settings, branch and change the default branch to master 
git push origin --delete main

nileshtrivedi

Raspberry Pi on Internet via reverse SSH tunnel

HackerNews discussed this with many alternative solutions: https://news.ycombinator.com/item?id=24893615

I already have my own domain name: mydomain.com. I wanted to be able to run some webapps on my Raspberry Pi 4B running perpetually at home in headless mode (just needs 5W power and wireless internet). I wanted to be able to access these apps from public Internet. Dynamic DNS wasn't an option because my ISP blocks all incoming traffic. ngrok would work but the free plan is too restrictive.

I bought a cheap 2GB RAM, 20GB disk VM + a 25GB volume on Hetzner for about 4 EUR/month. Hetzner gave me a static IP for it. I haven't purchased a floating IP yet.

FilippoVajana

import os
import tarfile
import imageio
import tqdm
import numpy as np

def get_nomnist():
    classes = ["A", "B", "C", "D", "E", "F", "G", "H", "I", "J"]
    tar_path = "./data/no-mnist/archive/notMNIST_large.tar"
    tmp_path = "./data/no-mnist/archive/tmp"

saniaky

Complete solution for websites hosting

This gist contains example of how you can configure nginx reverse-proxy with autmatic container discovery, SSL certificates generation (using Let's Encrypt) and auto updates.

Features:

• Automatically detect new containers and reconfigure nginx reverse-proxy
• Automatically generate/update SSL certificates for all specified containers.
• Watch for new docker images and update them.
• Ban bots and hackers who are trying to bruteforce your website or do anything suspicious.

arokem

bogdan-kulynych

# WARNING: These steps seem to not work anymore!

#!/bin/bash

# Purge existign CUDA first
sudo apt --purge remove "cublas*" "cuda*"
sudo apt --purge remove "nvidia*"

# Install CUDA Toolkit 10
wget https://developer.download.nvidia.com/compute/cuda/repos/ubuntu1804/x86_64/cuda-repo-ubuntu1804_10.0.130-1_amd64.deb

dnlcrl

import torch
import torch.nn as nn

class Model(nn.Module):
    def __init__(self):
        super(Model, self).__init__()
        self.linear = nn.Linear(1,1)

    def forward(self, x):
        y = self.linear(x)

bstriner

"""
A series of speed tests on pytorch LSTMs.
- LSTM is fastest (no surprise)
- When you have to go timestep-by-timestep, LSTMCell is faster than LSTM
- Iterating using chunks is slightly faster than __iter__ or indexing depending on setup

**Results**

My Ubuntu server:
    OS: posix, pytorch version: 0.4.0a0+67bbf58

ottonemo

import torch
import pickle

ts = [torch.ones(10, 20) + n for n in range(4)]
diff = 0

with open('tensor.pickle', 'wb') as f:
    for t in ts:
        start = f.tell()
        torch.save(t, f)

blackgate

Known Issues: On High Sierra there are problems related to the screen brightness and sleep issues.

1. Reset SMC and NVRAM

SMC: https://support.apple.com/en-us/HT201295

NVRAM: https://support.apple.com/en-us/HT204063

2. Change the gpu-power-prefs and disable SIP