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Bagua Python Packages

Python packages with the GitHub topic bagua. Sorted by relevance, with stars and monthly downloads.
BaguaSys
bagua

Bagua is a deep learning training acceleration framework for PyTorch. It provides a one-stop training acceleration solution, including faster distributed training compared to PyTorch DDP, faster dataloader, kernel fusion, and more.

2K 882 81
PersiaML
persia

High performance distributed framework for training deep learning recommendation models based on PyTorch.

2K 411 54
BaguaSys
bagua-cuda111

Bagua Speeds up PyTorch

2K 882 81
BaguaSys
bagua-cuda113

Bagua is a deep learning training acceleration framework for PyTorch. It provides a one-stop training acceleration solution, including faster distributed training compared to PyTorch DDP, faster dataloader, kernel fusion, and more.

1K 882 81
BaguaSys
bagua-cuda115

Bagua is a deep learning training acceleration framework for PyTorch. It provides a one-stop training acceleration solution, including faster distributed training compared to PyTorch DDP, faster dataloader, kernel fusion, and more.

1K 882 81
BaguaSys
bagua-cuda102

Bagua Speeds up PyTorch

1K 882 81
BaguaSys
bagua-cuda116

Bagua is a deep learning training acceleration framework for PyTorch. It provides a one-stop training acceleration solution, including faster distributed training compared to PyTorch DDP, faster dataloader, kernel fusion, and more.

848 882 81
PersiaML
persia-cuda102

PersiaML Python Library

724 411 54
PersiaML
persia-cuda111

High performance distributed framework for training deep learning recommendation models based on PyTorch.

706 411 54
PersiaML
persia-cuda113

High performance distributed framework for training deep learning recommendation models based on PyTorch.

694 411 54
BaguaSys
bagua-cuda117

Bagua is a deep learning training acceleration framework for PyTorch. It provides a one-stop training acceleration solution, including faster distributed training compared to PyTorch DDP, faster dataloader, kernel fusion, and more.

342 882 81
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