OOM is a nightmare for PyTorch users. However, most of them do not know the exact memory footprint during training. This project helps you depict the GPU memory usage changing curve during training. We record the peak GPU memory of an operator at the moment of the operator finished. The operator can be computing of a FWD submodule or a BWD submodule.
python train.py
python visualize.py memstats.pkl
involution Official implementation of a neural operator as described in Involution: Inverting the Inherence of Convolution for Visual Recognition (CVP
A simple GUI-based COCO-style JSON Polygon masks' annotation tool to facilitate quick and efficient crowd-sourced generation of annotation masks and bounding boxes. Optionally, one could choose to us
DanceTrack DanceTrack is a benchmark for tracking multiple objects in uniform appearance and diverse motion. DanceTrack provides box and identity anno
S2S2Net Sentinel-2 Super-Resolution Segmentation Network Getting started Install
Train in Germany, Test in The USA: Making 3D Object Detectors Generalize This paper has been accpeted by Conference on Computer Vision and Pattern Rec
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cumm CUda Matrix Multiply library. cumm is developed during learning of CUTLASS, which use too much c++ template and make code unmaintainable. So I de
ViDT: An Efficient and Effective Fully Transformer-based Object Detector by Hwanjun Song1, Deqing Sun2, Sanghyuk Chun1, Varun Jampani2, Dongyoon Han1,
Accelerating Antimicrobial Discovery with Controllable Deep Generative Models and Molecular Dynamics This work will be published in Nature Biomedical
CATE: Computation-aware Neural Architecture Encoding with Transformers Code for paper: CATE: Computation-aware Neural Architecture Encoding with Trans
Task: Create a CLI Calculator Step 0: Creating Virtual Environment $ python -m
An Empirical Study on GANs with Margin Cosine Loss and Relativistic Discriminator This is a Pytorch implementation for the paper "An Empirical Study o
Learning to Segment the Tail [arXiv] In this repository, we release code for Learning to Segment The Tail (LST). The code is directly modified from th
RITA: a Study on Scaling Up Generative Protein Sequence Models RITA is a family of autoregressive protein models, developed by a collaboration of Ligh
DeepBay This project was created with the objective of compile Machine Learning Architectures created using Tensorflow or Keras. The architectures mus
TorchSeg This project aims at providing a fast, modular reference implementation for semantic segmentation models using PyTorch. Highlights Modular De
A Python library for high performance ensemble learning ML-Ensemble combines a Scikit-learn high-level API with a low-level computational graph framew
GAN-image-detection This repository contains a GAN-generated image detector developed to distinguish real images from synthetic ones. The detector is
Example of wrapping SPL token by ERC2-20 interface in Neon Requirements Install
READ THIS FIRST This repo is an anonymized version of an existing repository of GitHub, for the AIStats 2021 submission: SparseFed: Mitigating Model P
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