Yukun Guo gyk
This is a set up for projects which want to check in only their source files, but have their gh-pages branch automatically updated with some compiled output every time they push.
A file below this one contains the steps for doing this with Travis CI. However, these days I recommend GitHub Actions, for the following reasons:
- It is much easier and requires less steps, because you are already authenticated with GitHub, so you don't need to share secret keys across services like you do when coordinate Travis CI and GitHub.
- It is free, with no quotas.
- Anecdotally, builds are much faster with GitHub Actions than with Travis CI, especially in terms of time spent waiting for a builder.
PdfLatex is a tool that converts Latex sources into PDF. This is specifically very important for researchers, as they use it to publish their findings. It could be installed very easily using Linux terminal, though this seems an annoying task on Windows. Installation commands are given below.
- Install the TexLive base
sudo apt-get install texlive-latex-base
- Also install the recommended and extra fonts to avoid running into the error [1], when trying to use pdflatex on latex files with more fonts.
| """ | |
| This is a batched LSTM forward and backward pass | |
| """ | |
| import numpy as np | |
| import code | |
| class LSTM: | |
| @staticmethod | |
| def init(input_size, hidden_size, fancy_forget_bias_init = 3): |
| // extract pixel from a CGImage | |
| /* use case: | |
| let extractor = PixelExtractor(img: UIImage(named: "gauge_vertical")!.CGImage!) | |
| let color = extractor.color_at(x: 10, y: 20) | |
| */ | |
| class PixelExtractor { | |
| // taken from http://stackoverflow.com/questions/24049313/ | |
| // and adapted to swift 1.2 |
| Download Google Drive files with WGET | |
| Example Google Drive download link: | |
| https://docs.google.com/open?id=[ID] | |
| To download the file with WGET you need to use this link: | |
| https://googledrive.com/host/[ID] | |
| Example WGET command: |
| """ | |
| 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) |
| ||| Demonstration of length preservation during vector concatenation. | |
| ||| Derived from Guillaume Allais's Agda original. | |
| ||| | |
| ||| Ignore the fact that functions here are named "reverse" -- they are really | |
| ||| concatenation. | |
| module ConcatVec | |
| import Data.Vect | |
| %default total |
The database can make use of a more expressive type system. Specifically to enforce invariants on data integrity at the schema level. But also understanding databases from a type theoretic point of view can lead to better, safer and more expressive type systems.
You do not want to keep writing database validation code in your application boundary. That is tiring. Instead let your database do that work. After all, it is where the data is stored. It is where the data is migrated. So shouldn't it also maintain the integrity and the constraints of the data?