A tool for monitoring and managing computing resources across multiple hosts

TensorHive TensorHive is an open source tool for monitoring and managing computing resources across multiple hosts. It solves the most common problems and nightmares about accessing and sharing your AI-oriented infrastructure across multiple, often competing users. It’s designed with simplicity, flexibility and configuration-friendliness in mind. Main features: GPU Reservation calendarEach column represents all reservation events for a GPU on a given day. In order to make a new reservation simply click and drag with your mouse, select GPU(s), add some […]

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Segmentation toolbox for EM connectomics

pytorch_connectomics The field of connectomics aims to reconstruct the wiring diagram of the brain by mapping the neural connections at the level of individual synapses. Recent advances in electronic microscopy (EM) have enabled the collection of a large number of image stacks at nanometer resolution, but the annotation requires expertise and is super time-consuming. Here we provide a deep learning framework powered by PyTorch for automatic and semi-automatic semantic and instance segmentation in connectomics, which is called PyTorch Connectomics (PyTC). […]

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A Python implementation of the Ensemble Slice Sampling method

zeus zeus is a Python implementation of the Ensemble Slice Sampling method. Fast & Robust Bayesian Inference, Efficient Markov Chain Monte Carlo (MCMC), Black-box inference, no hand-tuning, Excellent performance in terms of autocorrelation time and convergence rate, Scale to multiple CPUs without any extra effort. Example For instance, if you wanted to draw samples from a 10-dimensional Gaussian, you would do something like: import zeus import numpy as np def log_prob(x, ivar): return – 0.5 * np.sum(ivar * x**2.0) nsteps, […]

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Build a model which will take keywords as inputs and generate sentences as outputs

keytotext Idea is to build a model which will take keywords as inputs and generate sentences as outputs. Model: Keytotext is based on the Amazing T5 Model: k2t: Model k2t-tiny: Model k2t-base: Model mrm8488/t5-base-finetuned-common_gen (by Manuel Romero): Model Training Notebooks can be found in the Training Notebooks Folder Note: To add your own model to keytotext Please read Models Documentation Usage: Example usage: Example Notebooks can be found in the Notebooks Folder pip install keytotext UI: UI: pip install streamlit-tags […]

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PyTorch implementation of various fundamental RL algorithms

Reinforcement Learning (PyTorch) This repo will contain PyTorch implementation of various fundamental RL algorithms. It’s aimed at making it easy to start playing and learning about RL. The problem I came across investigating other DQN projects is that they either: Don’t have any evidence that they’ve actually achieved the published results Don’t have a “smart” replay buffer (i.e. they allocate (1M, 4, 84, 84) ~ 28 GBs! instead of (1M, 84, 84) ~ 7 GB) Lack of visualizations and debugging […]

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Machine Translation Weekly 79: More context in MT

The lack of broader context is one of the main problems in machine translation and in NLP in general. People tried various methods with actually quite mixed results. A recent preprint from Unbabel introduces an unusual quantification of context-awareness and based on that do some training improvements. The title of the paper is Measuring and Increasing Context Usage in Context-Aware Machine Translation and will be presented at ACL 2021. The paper measures how well informed the model is about the […]

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A Light-Weight Encoder-Decoder Based Network for Multimodal Biomedical Image Real-Time Segmentation

CFPNet-M This repository contains the implementation of a novel light-weight real-time network (CFPNet-Medicine: CFPNet-M) to segment different types of biomedical images. It is a medical version of CFPNet, and the dataset we used from top to bottom are DRIVE, ISBI-2012, Infrared Breast, CVC-ClinicDB and ISIC 2018. The details of CFPNet-M and CFPNet can be found here respectively. Architecture of CFPNet-M CFP module CFPNet-M Dataset In this project, we test five datasets: [x] Infrared Breast Dataset [x] Endoscopy (CVC-ClinicDB) [x] Electron […]

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An all MLP solution to image classification in Pytorch

ResMLP – Pytorch Implementation of ResMLP, an all MLP solution to image classification out of Facebook AI, in Pytorch Install $ pip install res-mlp-pytorch Usage import torch from res_mlp_pytorch import ResMLP model = ResMLP( image_size = 256, patch_size = 16, dim = 512, depth = 12, num_classes = 1000 ) img = torch.randn(1, 3, 256, 256) pred = model(img) # (1, 1000) Citations @misc{touvron2021resmlp, title = {ResMLP: Feedforward networks for image classification with data-efficient training}, author = {Hugo Touvron and […]

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TensorFlow implementation of Barlow Twins

Barlow-Twins-TF This repository iimplements Barlow Twins (Barlow Twins: Self-Supervised Learning via Redundancy Reduction) in TensorFlow and demonstrates it on the CIFAR10 dataset. Summary: With a ResNet20 as a trunk and a 3-layer MLP (each layer containing 2048 units) and 100 epochs of pre-training, this training notebook can give 62.61% accuracy on the CIFAR10 test set. The pre-training total takes ~23 minutes on a single Tesla V100. There are minor differences from the original implementation. However, the original loss function and […]

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Self-Supervised Contrastive Learning of Music Spectrograms

Self-Supervised Music Analysis Self-Supervised Contrastive Learning of Music Spectrograms. Dataset Songs on the Billboard Year End Hot 100 were collected from the years 1960-2020. This list tracks the top songs of the US market for a given calendar year based on aggregating metrics including streaming plays, physical and digital purchases, radio plays, etc. In total the dataset includes 5737 songs, excluding some songs which could not be found and some which are duplicates across multiple years. It’s worth noting that […]

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