pyparsing
tensorflow
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pyparsing | tensorflow | |
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13 | 222 | |
2,091 | 182,456 | |
2.0% | 0.8% | |
8.3 | 10.0 | |
29 days ago | 3 days ago | |
Python | C++ | |
MIT License | Apache License 2.0 |
Stars - the number of stars that a project has on GitHub. Growth - month over month growth in stars.
Activity is a relative number indicating how actively a project is being developed. Recent commits have higher weight than older ones.
For example, an activity of 9.0 indicates that a project is amongst the top 10% of the most actively developed projects that we are tracking.
pyparsing
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Pyparsing 3.1.0 released
After over a year since the last release of pyparsing, I've bundled up all the bug-fixes and changes, and they are now released as pyparsing 3.1.0. Visit this link for the details.
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Need help developing an interpreter
Look into "parser combinators" for building an interpreter. There's a few ones out there, but PyParsing is one I've seen around that looks pretty nifty.
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About a month ago I posted about PRegEx, an open-source project which I had started that you can use to build RegEx patterns programmatically, which the subreddit seem to like. This prompted me to keep working on it, and one month later, PRegEx v2.0.0 is out!
I havent found a way to specify an exact character match in pyparsing - https://github.com/pyparsing/pyparsing/discussions/443
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Python toolkits
STDOUT: Lark or pyparsing
- TatSu takes grammars in variation of EBNF, outputs memoizing Python PEG parsers
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Parser Combinators in Haskell
Since it is not mentioned in the article: Python users may also want to check out pyparsing [0]. It is slightly different from Parsec/FParsec (for instance, it ignores all whitespace by default), but I think it is a really good project.
[0]: https://github.com/pyparsing/pyparsing/
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Pyparsing 3.0.x - off to a rocky start, but I think 3.0.6 looks fairly solid
Here is the page of all the new changes and features in pyparsing 3.0.
- luna is a Domain specific language that translates to regex. It's an attempt to make regex more readable.
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Recommended way to read and parse a couple thousand small files
Your pyparsing parser might benefit from a tune-up. This page has some performance tips: https://github.com/pyparsing/pyparsing/wiki/Performance-Tips.
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Script for extracting info from a SQL File
If your SQL has fairly complex structure, you will need a full blown SQL parser. If your statements are mostly simple select, you can get pretty close with Pyparsing, here is an example.
tensorflow
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Google lays off its Python team
[3]: https://github.com/tensorflow/tensorflow/graphs/contributors
- TensorFlow-metal on Apple Mac is junk for training
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🔥🚀 Top 10 Open-Source Must-Have Tools for Crafting Your Own Chatbot 🤖💬
To get up to speed with TensorFlow, check their quickstart Support TensorFlow on GitHub ⭐
- One .gitignore to rule them all
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10 Github repositories to achieve Python mastery
Explore here.
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GitHub and Developer Ecosystem Control
Part of the major userbase pull in GitHub revolves around hosting a considerable number of popular projects including Angular, React, Kubernetes, cpython, Ruby, tensorflow, and well even the software that powers this site Forem.
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Non-determinism in GPT-4 is caused by Sparse MoE
Right but that's not an inherent GPU determinism issue. It's a software issue.
https://github.com/tensorflow/tensorflow/issues/3103#issueco... is correct that it's not necessary, it's a choice.
Your line of reasoning appears to be "GPUs are inherently non-deterministic don't be quick to judge someone's code" which as far as I can tell is dead wrong.
Admittedly there are some cases and instructions that may result in non-determinism but they are inherently necessary. The author should thinking carefully before introducing non-determinism. There are many scenarios where it is irrelevant, but ultimately the issue we are discussing here isn't the GPU's fault.
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Can someone explain how keras code gets into the Tensorflow package?
and things like y = layers.ELU()(y) work as expected. I wanted to see a list of the available layers so I went to the Tensorflow GitHub repository and to the keras directory. There's a warning in that directory that says:
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Is it even possible to design a ML model without using Python or MATLAB? Like using C++, C or Java?
Exactly what language do you think TensorFlow is written in? :)
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How to do deep learning with Caffe?
You can use Tensorflow's deep learning API for this.
What are some alternatives?
parsita - The easiest way to parse text in Python
PaddlePaddle - PArallel Distributed Deep LEarning: Machine Learning Framework from Industrial Practice (『飞桨』核心框架,深度学习&机器学习高性能单机、分布式训练和跨平台部署)
parser - String parser combinators
Prophet - Tool for producing high quality forecasts for time series data that has multiple seasonality with linear or non-linear growth.
iregex - A way to write regex with objects instead of strings.
Pandas - Flexible and powerful data analysis / manipulation library for Python, providing labeled data structures similar to R data.frame objects, statistical functions, and much more
attoparsec - A fast Haskell library for parsing ByteStrings
LightGBM - A fast, distributed, high performance gradient boosting (GBT, GBDT, GBRT, GBM or MART) framework based on decision tree algorithms, used for ranking, classification and many other machine learning tasks.
sly - Sly Lex Yacc
scikit-learn - scikit-learn: machine learning in Python
Lark - Lark is a parsing toolkit for Python, built with a focus on ergonomics, performance and modularity.
LightFM - A Python implementation of LightFM, a hybrid recommendation algorithm.