Lyken17/Efficient-PyTorch
A collection of best practices for efficiently training large neural network models using PyTorch.
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This repository shares optimization techniques for PyTorch training pipelines, focusing on maximizing training throughput. It demonstrates achieving approximately 730 images per second when training ResNet-50 on ImageNet through various tuning tips and best practices. The benchmarks compare favorably against TensorFlow and MXNet implementations.
Frequently asked
- What is Lyken17/Efficient-PyTorch?
- A collection of best practices for efficiently training large neural network models using PyTorch.
- Is Efficient-PyTorch open source?
- Yes — Lyken17/Efficient-PyTorch is an open-source project tracked on heatdrop.
- What language is Efficient-PyTorch written in?
- Lyken17/Efficient-PyTorch is primarily written in Python.
- How popular is Efficient-PyTorch?
- Lyken17/Efficient-PyTorch has 1.1k stars on GitHub.
- Where can I find Efficient-PyTorch?
- Lyken17/Efficient-PyTorch is on GitHub at https://github.com/Lyken17/Efficient-PyTorch.