AI-Toolbox
tensorflow
AI-Toolbox | tensorflow | |
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2 | 223 | |
641 | 182,575 | |
- | 0.5% | |
5.1 | 10.0 | |
4 months ago | 2 days ago | |
C++ | C++ | |
GNU General Public License v3.0 only | Apache License 2.0 |
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AI-Toolbox
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Impact of using sockets to communicate between Python and RL environment
Makes sense. I was just wondering if someone had any comparisons to share. I will create a toy environment in Unreal and compare integrating RL C++ libraries (looking at AI-Toolbox and mlpack) vs using Python with socket communication.
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Greedy AI agents learn to cooperate
I maintain a repository of many implementations of classical (tabular) RL algorithms [1] which you might enjoy playing with when starting out. I use it for both research and for student projects. The advantage of avoiding NNs when starting out is that it is much simpler to inspect the inner workings of an algorithm to see whether it's working or not.
I'm always happy to help if something is unclear or difficult so feel free to open issues there :)
[1]: https://github.com/Svalorzen/AI-Toolbox
tensorflow
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Side Quest Devblog #1: These Fakes are getting Deep
# L2-normalize the encoding tensors image_encoding = tf.math.l2_normalize(image_encoding, axis=1) audio_encoding = tf.math.l2_normalize(audio_encoding, axis=1) # Find euclidean distance between image_encoding and audio_encoding # Essentially trying to detect if the face is saying the audio # Will return nan without the 1e-12 offset due to https://github.com/tensorflow/tensorflow/issues/12071 d = tf.norm((image_encoding - audio_encoding) + 1e-12, ord='euclidean', axis=1, keepdims=True) discriminator = keras.Model(inputs=[image_input, audio_input], outputs=[d], name="discriminator")
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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? :)
What are some alternatives?
Recast/Detour - Industry-standard navigation-mesh toolset for games
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)
Veles - Distributed machine learning platform
Prophet - Tool for producing high quality forecasts for time series data that has multiple seasonality with linear or non-linear growth.
BayesOpt - BayesOpt: A toolbox for bayesian optimization, experimental design and stochastic bandits.
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
tiny-cnn - header only, dependency-free deep learning framework in C++14
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.
nano
scikit-learn - scikit-learn: machine learning in Python
Native System Automation - Native cross-platform system automation
LightFM - A Python implementation of LightFM, a hybrid recommendation algorithm.