Someone implemented instance weighted CE loss for PyTorch
Wrote about this a year ago.
Forgot about it, a friend reminded me.
You can pass lists to the python command line arguments.
parser.add_argument('--classifier_conf', default=[512, 2048, 5005], nargs='+', type=int)
and then just add params to your call as follows
--classifier_conf 512 2048 5005
Linux subsystem in Windows 10
It works and installs in literally 2 clicks (run one command in Powershell and then just one-click install your Linux distro of choice in Windows Store (yes, this very funny indeed))!
Why would you need this?
To make and backup files on one command for example =)
Something like this becomes reality on Windows:
cd /mnt/d/ && \
TIME=`date +%b-%d-%y` && \
FILENAME=working_files_tar-$TIME.tar.gz && \
INCREMENTAL_FILE=backup_data.snar && \
echo 'Using folderlist' $FOLDERS && \
tar -czg $(<folders_backup.txt) --listed-incremental=$INCREMENTAL_FILE --verbose -f $FILENAME
Also, you may add rsync or scp and you are good to go!
Also other potential use cases:
- You are somehow vendor locked (I depend on proprietary drivers for my thunderbolt port to attach an external GPU) or just are used to Windows' windows (or are just lazy to install Linux);
- You need one particular Linux program or you need to quickly test something / do not want to bother replicating your environment under Windows (yes, you can also run Docker, but there will be some learning curve);
- You run all of your programs remotely, and use your Windows machine as a thin client, but sometimes you need git / bash / rsync - i.e. to download movies from your personal NAS;
Happy holidays to everyone)
Spark in me 2018 annual retrospective
- My personal progress and some views;
- ML is still amazing, but there are no illusions anymore;
- Telegram is still amazing, but commercialization looms;
- FAIR is an inspiration;
- Imcinnes with UMAP and HDBSCAN as well;
Еще написал немного по-русски, немного со спецификой, если вам так удобнее
Environment setup for DS / ML / DL
Some time ago made a small guide for setting up an environment on a black Ubuntu machine.
If works both for CV and NLP.
If you like this, please tell me, I will add newer things:
- CUDA10 with PyTorch 1.0;
- Scripts for managing GPU fan speed;
Sentiment datasets in Russian
Just randomly found several links.
- study.mokoron.com/ - annotated tweets
(My GPUs are ~70C under full load xD)
Now Google Photos explicitly shows that it knows faces of your family members.
Spell-checking on various scales in Russian
Bayes + n-gram rules = spell-checker for words / sentences
Welcome to NeurIPS 2018 Turorial Sessions. This tutorial on Visualization for Machine Learning will provide an introduction to the landscape of ML visualizaions, organized by types of users and their...
- PyText github.com/facebookresearch/pyte
- TLDR - FastText meets PyTorch;
- Very similar to AllenNLP in nature;
- Will be useful if you can afford to write modules for their framework to solve 100 identical tasks (i.e. like Facebook with 200 languages);
- In itself - seems to be too high maintenance to use;
I will not use use it.
NLP library build on top of PyTorch 1.0 by Facebook?
- No repo link though (github.com/facebookresearch/pyte
- The paper also mentions the same limited API as AllenNLP has ... =(
Painting with GANs
This looks just awesome.
I guess it will not work in real resolutions yet.
This kind of mirrors my own old post
Channel Edit Photo