As configured in my dotfiles.
start new:
tmux
start new with session name:
""" | |
Minimal character-level Vanilla RNN model. Written by Andrej Karpathy (@karpathy) | |
BSD License | |
""" | |
import numpy as np | |
# data I/O | |
data = open('input.txt', 'r').read() # should be simple plain text file | |
chars = list(set(data)) | |
data_size, vocab_size = len(data), len(chars) |
As configured in my dotfiles.
start new:
tmux
start new with session name:
Enter this in the search box along with your search terms:
Get all gists from the user santisbon.
user:santisbon
Find all gists with a .yml extension.
extension:yml
Find all gists with HTML files.
language:html
# This isn't supposed to run as a bash script, i named it with ".sh" for syntax highlighting. | |
# https://developer.nvidia.com/nsight-systems | |
# https://docs.nvidia.com/nsight-systems/profiling/index.html | |
# My preferred nsys (command line executable used to create profiles) commands | |
# | |
# In your script, write | |
# torch.cuda.nvtx.range_push("region name") | |
# ... |
using namespace System.Management.Automation | |
Register-ArgumentCompleter -CommandName ssh,scp,sftp -Native -ScriptBlock { | |
param($wordToComplete, $commandAst, $cursorPosition) | |
$knownHosts = Get-Content ${Env:HOMEPATH}\.ssh\known_hosts ` | |
| ForEach-Object { ([string]$_).Split(' ')[0] } ` | |
| ForEach-Object { $_.Split(',') } ` | |
| Sort-Object -Unique | |
# For now just assume it's a hostname. |
This is unmaintained, please visit Ben-PH/spacemacs-cheatsheet
SPC q q
- quitSPC w /
- split window verticallySPC w
- - split window horizontallySPC 1
- switch to window 1SPC 2
- switch to window 2SPC w c
- delete current windowapt update | |
apt install -y emacs-nox aptitude screen xcscope-el gdb nano || echo 0 && echo "Success" | |
python3 -m pip install git-remote-codecommit opennmt-tf==1.25.1 | |
cat << EOF > ~/.gdbinit | |
set print thread-events off | |
define hook-run | |
catch throw | |
end | |
define hook-quit |
import numpy as np | |
from scipy import linalg | |
from sklearn.utils import array2d, as_float_array | |
from sklearn.base import TransformerMixin, BaseEstimator | |
class ZCA(BaseEstimator, TransformerMixin): | |
def __init__(self, regularization=10**-5, copy=False): | |
self.regularization = regularization |