chainer VS SmallPebble

Compare chainer vs SmallPebble and see what are their differences.

chainer

A flexible framework of neural networks for deep learning (by chainer)
Deep Learning Python neural-networks Machine Learning GPU Cuda cudnn Numpy cupy Chainer neural-network
Source Code
chainer.org
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SmallPebble

Minimal deep learning library written from scratch in Python, using NumPy/CuPy. (by sradc)
Autodiff Numpy cupy Deep Learning neural-network Python Machine Learning
Source Code
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chainer SmallPebble
2 6
5,861 112
0.3% -
0.0 0.0
8 months ago over 1 year ago
Python Python
MIT License Apache License 2.0
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.

chainer

Posts with mentions or reviews of chainer. We have used some of these posts to build our list of alternatives and similar projects. The last one was on 2023-07-19.

SmallPebble

Posts with mentions or reviews of SmallPebble. We have used some of these posts to build our list of alternatives and similar projects. The last one was on 2023-08-24.

What are some alternatives?

When comparing chainer and SmallPebble you can also consider the following projects:

chaiNNer - A node-based image processing GUI aimed at making chaining image processing tasks easy and customizable. Born as an AI upscaling application, chaiNNer has grown into an extremely flexible and powerful programmatic image processing application.

MyGrad - Drop-in autodiff for NumPy.

leptonai - A Pythonic framework to simplify AI service building

tmu - Implements the Tsetlin Machine, Coalesced Tsetlin Machine, Convolutional Tsetlin Machine, Regression Tsetlin Machine, and Weighted Tsetlin Machine, with support for continuous features, drop clause, Type III Feedback, focused negative sampling, multi-task classifier, autoencoder, literal budget, and one-vs-one multi-class classifier. TMU is written in Python with wrappers for C and CUDA-based clause evaluation and updating.

warp-drive - Extremely Fast End-to-End Deep Multi-Agent Reinforcement Learning Framework on a GPU (JMLR 2022)

XNOR-popcount-GEMM-PyTorch-CPU-CUDA - A PyTorch implemenation of real XNOR-popcount (1-bit op) GEMM Linear PyTorch extension support both CPU and CUDA

memoized_coduals - Shows that it is possible to implement reverse mode autodiff using a variation on the dual numbers called the codual numbers

GPU-Puzzles - Solve puzzles. Learn CUDA.

pytortto - deep learning from scratch. uses numpy/cupy, trains in GPU, follows pytorch API

caer - High-performance Vision library in Python. Scale your research, not boilerplate.

Pytorch - Tensors and Dynamic neural networks in Python with strong GPU acceleration

Tensor-Puzzles - Solve puzzles. Improve your pytorch.

chainer vs chaiNNer SmallPebble vs MyGrad chainer vs leptonai chainer vs tmu chainer vs warp-drive chainer vs XNOR-popcount-GEMM-PyTorch-CPU-CUDA SmallPebble vs memoized_coduals SmallPebble vs GPU-Puzzles chainer vs pytortto chainer vs caer chainer vs Pytorch SmallPebble vs Tensor-Puzzles