Stars
PyTorch compiler that accelerates training and inference. Get built-in optimizations for performance, memory, parallelism, and easily write your own.
A Fusion Code Generator for NVIDIA GPUs (commonly known as "nvFuser")
Supplementary material of "Deep Unsupervised Drum Transcription", ISMIR 2019
The largest collection of PyTorch image encoders / backbones. Including train, eval, inference, export scripts, and pretrained weights -- ResNet, ResNeXT, EfficientNet, NFNet, Vision Transformer (V…
Debugging, monitoring and visualization for Python Machine Learning and Data Science
PyTorch original implementation of Cross-lingual Language Model Pretraining.
Python package built to ease deep learning on graph, on top of existing DL frameworks.
Visualisation tool for CNNs in pytorch
A PyTorch Extension: Tools for easy mixed precision and distributed training in Pytorch
Code for visualizing the loss landscape of neural nets
pytorch-kaldi is a project for developing state-of-the-art DNN/RNN hybrid speech recognition systems. The DNN part is managed by pytorch, while feature extraction, label computation, and decoding a…
Playing around with JointVAE implementation - WIP
Projects and exercises for the latest Deep Learning ND program https://www.udacity.com/course/deep-learning-nanodegree--nd101
Transpile trained scikit-learn estimators to C, Java, JavaScript and others.
t-vi / AICamera
Forked from facebookarchive/AICameraDemonstration of using Caffe2 inside an Android application.
The fundamental package for scientific computing with Python.
Fast, modular reference implementation of Instance Segmentation and Object Detection algorithms in PyTorch.
Open standard for machine learning interoperability
A GPU-accelerated library containing highly optimized building blocks and an execution engine for data processing to accelerate deep learning training and inference applications.
A command-line and interactive shell framework.
An open-source C++ library developed and used at Facebook.
Deep Learning Projects that Build Themselves
PyTorch implementations of algorithms for density estimation
Pytorch implementation of our method for high-resolution (e.g. 2048x1024) photorealistic video-to-video translation.
[ECCV 2018]: T2Net: Synthetic-to-Realistic Translation for Depth Estimation Tasks
ICRA 2018 "Sparse-to-Dense: Depth Prediction from Sparse Depth Samples and a Single Image" (PyTorch Implementation)
MobileNetV1, MobileNetV2, VGG based SSD/SSD-lite implementation in Pytorch 1.0 / Pytorch 0.4. Out-of-box support for retraining on Open Images dataset. ONNX and Caffe2 support. Experiment Ideas lik…