PyTorch-NLP
adaptdl
Our great sponsors
| PyTorch-NLP | adaptdl | |
|---|---|---|
| 1 | 4 | |
| 2,180 | 395 | |
| - | 0.0% | |
| 0.0 | 0.0 | |
| 10 months ago | about 1 year ago | |
| Python | Python | |
| BSD 3-clause "New" or "Revised" License | Apache License 2.0 |
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PyTorch-NLP
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Introduction to PyTorch
PyTorch-NLP
adaptdl
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Introduction to PyTorch
AdaptDL
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[Discussion] Open source scheduler and queuing system for model training/inferencing tasks?
check out https://github.com/petuum/adaptdl. It natively supports AWS/EKS (for the autoscaling feature), otherwise it can run anywhere on Kubernetes.
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Reduce cost by 3x in the cloud and improve GPU usage in shared clusters with AdaptDL for PyTorch
AdaptDL monitors training job performance in real-time, and elastically re-scales resources (GPUs, compute instances) while jobs are running. For each training job, AdaptDL automatically tunes the batch size, learning rate, and gradient accumulation. In the cloud (e.g. AWS), AdaptDL can auto-scale the number of provisioned Spot Instances. We’ve seen shared-cluster training jobs at Petuum and our partners complete 2–3x faster on average, with 3x cheaper cost in AWS using Spot Instances!
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How we were able to achieve hyper-parameter tuning (HPT) for deep learning workflows at 1.5x faster in our clusters and 3x cheaper on AWS
To tackle the problem of long and expensive HPT workflows, our team at Petuum collaborated with Microsoft to integrate AdaptDL with Neural Network Intelligence (NNI). AdaptDL is an open-source tool in the CASL (Composable, Automatic, and Scalable Learning) ecosystem. AdaptDL offers adaptive resource management for distributed clusters, and reduces the cost of deep learning workloads ranging from a few training/tuning trials to thousands. NNI from the Microsoft open-source community, is a toolkit for automatic machine learning (AutoML) and hyper-parameter tuning.
What are some alternatives?
PaddlePaddle - PArallel Distributed Deep LEarning: Machine Learning Framework from Industrial Practice （『飞桨』核心框架，深度学习&机器学习高性能单机、分布式训练和跨平台部署）
HandyRL - HandyRL is a handy and simple framework based on Python and PyTorch for distributed reinforcement learning that is applicable to your own environments.
spaCy - 💫 Industrial-strength Natural Language Processing (NLP) in Python
determined - Determined is an open-source machine learning platform that simplifies distributed training, hyperparameter tuning, experiment tracking, and resource management. Works with PyTorch and TensorFlow.
NLTK - NLTK Source
alpa - Training and serving large-scale neural networks with auto parallelization.
pytext - A natural language modeling framework based on PyTorch
FedML - FEDML - The unified and scalable ML library for large-scale distributed training, model serving, and federated learning. FEDML Launch, a cross-cloud scheduler, further enables running any AI jobs on any GPU cloud or on-premise cluster. Built on this library, FEDML Nexus AI (https://fedml.ai) is your generative AI platform at scale.
Jieba - 结巴中文分词
tutorials - PyTorch tutorials.
Stanza - Stanford NLP Python library for tokenization, sentence segmentation, NER, and parsing of many human languages
torchlambda - Lightweight tool to deploy PyTorch models to AWS Lambda