|6 days ago||about 1 hour ago|
|-||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.
Non-determinism in GPT-4 is caused by Sparse MoE
3 projects | news.ycombinator.com | 4 Aug 2023
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.
Can someone explain how keras code gets into the Tensorflow package?
2 projects | /r/tensorflow | 24 Jul 2023
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:
How to do deep learning with Caffe?
4 projects | /r/SubSimulatorGPT2 | 6 Jun 2023
You can use Tensorflow's deep learning API for this.
Ask HN: What is a AI chip and how does it work?
4 projects | news.ycombinator.com | 27 May 2023
This is indeed the bread-and-butter, but there is use of all sorts of standard linear algebra algorithms. You can check various xla-related (accelerated linear algebra) folders in tensorflow or torch folders in pytorch to see the list of what is used ,
Mastering Data Science: Top 10 GitHub Repos You Need to Know
10 projects | dev.to | 24 Apr 2023
2. TensorFlow Developed by the Google Brain team, TensorFlow is a powerful open-source machine learning framework that’s perfect for deep learning and neural network projects. With TensorFlow, you can build and train complex models using an intuitive and flexible API, making it an essential tool for any data scientist looking to delve into deep learning.
Tensorflow V2 - LSTM Penn Tree Bank Dataset
2 projects | /r/LanguageTechnology | 15 Apr 2023
I found the official Tensorflow V1 code from a Github branch here (https://github.com/tensorflow/tensorflow/blob/r0.7/tensorflow/models/rnn/ptb/ptb_word_lm.py). All code necessary to run that file is in the /ptb folder (except data).
.gitignore that is not checked into repository
4 projects | news.ycombinator.com | 2 Apr 2023
The problem with open source: not enough contributors
2 projects | dev.to | 18 Mar 2023
In their report they show the 10 projects with the biggest number of contributors. The first one is microsoft/vscode with 19.8K contributors in 2022 and the 10th place is tensorflow/tensorflow with 4.4K contributors. That's really nice, but my guess is that most repositories have very few contributors.
I plan to build my own AI powered search engine for my portfolio. Do you know ones that are open-source?
6 projects | /r/opensource | 17 Mar 2023
TensorFlow - This one needs no introduction. It’s widely-used and it has several tools and community resources for training and deploying ML/DL models. This one is JS based and I’m not too familiar with JS except that I know a lot of people use it for web development. What I like about it is that it’s used for speech and image recognition. And one of my favorites are text summarization.
OpenXLA Is Available Now
5 projects | news.ycombinator.com | 9 Mar 2023
If you mean StableHLO, then it has an MLIR dialect: https://github.com/openxla/stablehlo/blob/main/stablehlo/dia....
In the StableHLO spec, we are talking about this in more abstract terms - "StableHLO opset" - to be able to unambiguously reason about the semantics of StableHLO programs. However, in practice the StableHLO dialect is the primary implementation of the opset at the moment.
I wrote "primary implementation" because e.g. there is also ongoing work on adding StableHLO support to the TFLite flatbuffer schema: https://github.com/tensorflow/tensorflow/blob/master/tensorf.... Having an abstract notion of the StableHLO opset enables us to have a source of truth that all the implementations correspond to.
What are some alternatives?
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）
Prophet - Tool for producing high quality forecasts for time series data that has multiple seasonality with linear or non-linear growth.
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
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.
scikit-learn - scikit-learn: machine learning in Python
LightFM - A Python implementation of LightFM, a hybrid recommendation algorithm.
xgboost - Scalable, Portable and Distributed Gradient Boosting (GBDT, GBRT or GBM) Library, for Python, R, Java, Scala, C++ and more. Runs on single machine, Hadoop, Spark, Dask, Flink and DataFlow
MLflow - Open source platform for the machine learning lifecycle
Pytorch - Tensors and Dynamic neural networks in Python with strong GPU acceleration
Deeplearning4j - Suite of tools for deploying and training deep learning models using the JVM. Highlights include model import for keras, tensorflow, and onnx/pytorch, a modular and tiny c++ library for running math code and a java based math library on top of the core c++ library. Also includes samediff: a pytorch/tensorflow like library for running deep learning using automatic differentiation.
Keras - Deep Learning for humans