chainer
XNOR-popcount-GEMM-PyTorch-CPU-CUDA
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| chainer | XNOR-popcount-GEMM-PyTorch-CPU-CUDA | |
|---|---|---|
| 2 | 1 | |
| 5,864 | 14 | |
| 0.3% | - | |
| 0.0 | 2.5 | |
| 8 months ago | 11 months ago | |
| Python | Python | |
| 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.
chainer
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ChaiNNer – Node/Graph based image processing and AI upscaling GUI
There is already an AI framework named Chainer: https://github.com/chainer/chainer
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Protip: the upscaler matters a lot
Sorry maybe someone could chime in and help but I use chainer to upscale. https://github.com/chainer/chainer
XNOR-popcount-GEMM-PyTorch-CPU-CUDA
What are some alternatives?
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.
Binary-Convolutional-Neural-Network-Inference-on-GPU - GPU implementation of Xnor network on inference level.
leptonai - A Pythonic framework to simplify AI service building
3d-ken-burns - an implementation of 3D Ken Burns Effect from a Single Image using PyTorch
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.
caer - High-performance Vision library in Python. Scale your research, not boilerplate.
SmallPebble - Minimal deep learning library written from scratch in Python, using NumPy/CuPy.
QualityScaler - QualityScaler - image/video deeplearning upscaling for any GPU
warp-drive - Extremely Fast End-to-End Deep Multi-Agent Reinforcement Learning Framework on a GPU (JMLR 2022)
TensorRT - NVIDIA® TensorRT™ is an SDK for high-performance deep learning inference on NVIDIA GPUs. This repository contains the open source components of TensorRT.
pytortto - deep learning from scratch. uses numpy/cupy, trains in GPU, follows pytorch API
SBNN - Singular Binarized Neural Network based on GPU Bit Operations (see our SC-19 paper)