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Command Line Crash Course

Related tutorials

• http://cli.learncodethehardway.org/book/
• https://www.codecademy.com/courses/learn-the-command-line

Cheatsheets

• Linux auf einem Blatt
• Fasd

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# Terminal Cheat Sheet

pwd         # print working directory
ls          # list files in directory
cd          # change directory
~           # home directory
..          # up one directory
-           # previous working directory
help        # get help
-h          # get help

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--[[ 
Efficient LSTM in Torch using nngraph library. This code was optimized 
by Justin Johnson (@jcjohnson) based on the trick of batching up the 
LSTM GEMMs, as also seen in my efficient Python LSTM gist.
--]]

function LSTM.fast_lstm(input_size, rnn_size)
  local x = nn.Identity()()
  local prev_c = nn.Identity()()
  local prev_h = nn.Identity()()

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--[[ 
   This layer expects an [n x d] Tensor and normalizes each
   row to have unit L2 norm.
]]--
local L2Normalize, parent = torch.class('nn.L2Normalize', 'nn.Module')
function L2Normalize:__init()
   parent.__init(self)
end
function L2Normalize:updateOutput(input)

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"""
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)

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Git

Global Settings

• Related Setup: https://gist.github.com/hofmannsven/6814278
• Related Pro Tips: https://ochronus.com/git-tips-from-the-trenches/
• Interactive Beginners Tutorial: http://try.github.io/
• Git Cheatsheet by GitHub: https://services.github.com/on-demand/downloads/github-git-cheat-sheet/

Reminder

Press minus + shift + s and return to chop/fold long lines!

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title	subtitle	author	date	source
npm vs Yarn Command Translation Cheat Sheet	CLI commands comparison	yarn	July 2, 2017	https://yarnpkg.com/en/docs/migrating-from-npm

npm vs Yarn Command Translation Cheat Sheet

W3SS

import torch
import torch.nn as nn

torch.manual_seed(42)
x = torch.randn(2, 768)

# matrix multiply "ignores" the second row when calculating the first row
w = torch.randn(768, 768)
z1 = x[0] @ w
z2 = (x @ w)[0]

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"""
stable diffusion dreaming
creates hypnotic moving videos by smoothly walking randomly through the sample space

example way to run this script:

$ python stablediffusionwalk.py --prompt "blueberry spaghetti" --name blueberry

to stitch together the images, e.g.:
$ ffmpeg -r 10 -f image2 -s 512x512 -i blueberry/frame%06d.jpg -vcodec libx264 -crf 10 -pix_fmt yuv420p blueberry.mp4

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# -----------------------------------------------------------------------------
# AI-powered Git Commit Function
# Copy paste this gist into your ~/.bashrc or ~/.zshrc to gain the `gcm` command. It:
# 1) gets the current staged changed diff
# 2) sends them to an LLM to write the git commit message
# 3) allows you to easily accept, edit, regenerate, cancel
# But - just read and edit the code however you like
# the `llm` CLI util is awesome, can get it here: https://llm.datasette.io/en/stable/

gcm() {