petastorm VS nni

Compare petastorm vs nni and see what are their differences.


Petastorm library enables single machine or distributed training and evaluation of deep learning models from datasets in Apache Parquet format. It supports ML frameworks such as Tensorflow, Pytorch, and PySpark and can be used from pure Python code. (by uber)
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petastorm nni
1 3
1,338 10,838
3.3% 2.2%
7.4 9.7
8 days ago 6 days ago
Python Python
Apache License 2.0 MIT License
The number of mentions indicates the total number of mentions that we've tracked plus the number of user suggested alternatives.
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.


Posts with mentions or reviews of petastorm. We have used some of these posts to build our list of alternatives and similar projects.


Posts with mentions or reviews of nni. We have used some of these posts to build our list of alternatives and similar projects. The last one was on 2021-10-04.

What are some alternatives?

When comparing petastorm and nni you can also consider the following projects:

horovod - Distributed training framework for TensorFlow, Keras, PyTorch, and Apache MXNet.

optuna - A hyperparameter optimization framework

autogluon - AutoGluon: AutoML for Text, Image, and Tabular Data

FLAML - A fast library for AutoML and tuning.

hyperopt - Distributed Asynchronous Hyperparameter Optimization in Python

AutoML - This is a collection of our NAS and Vision Transformer work. [Moved to:]

LightAutoML - LAMA - automatic model creation framework

torchextractor - Feature extraction made simple with torchextractor

automlbenchmark - OpenML AutoML Benchmarking Framework

lightwood - Lightwood is Legos for Machine Learning.

waypoint-examples - Example Apps that can be deployed with Waypoint

d2l-en - Interactive deep learning book with multi-framework code, math, and discussions. Adopted at 300 universities from 55 countries including Stanford, MIT, Harvard, and Cambridge.