Files
pytorch/benchmarks
Yiming Zhou 47524dcc48 [benchmark] Add more timm models (#165381)
Added following models to timm_models

- [convnextv2_nano.fcmae_ft_in22k_in1k](https://huggingface.co/timm/convnextv2_nano.fcmae_ft_in22k_in1k)
- [vit_base_patch14_dinov2.lvd142m](https://huggingface.co/timm/vit_base_patch14_dinov2.lvd142m)
- [ViT-B-16-SigLIP-i18n-256](https://huggingface.co/timm/ViT-B-16-SigLIP-i18n-256)
- [deit_tiny_patch16_224.fb_in1k](https://huggingface.co/timm/deit_tiny_patch16_224.fb_in1k)

Pull Request resolved: https://github.com/pytorch/pytorch/pull/165381
Approved by: https://github.com/BoyuanFeng
2025-10-15 01:19:10 +00:00
..
2025-04-27 09:56:42 +00:00

PyTorch Benchmarks

This folder contains scripts that produce reproducible timings of various PyTorch features.

It also provides mechanisms to compare PyTorch with other frameworks.

Setup environment

Make sure you're on a machine with CUDA, torchvision, and pytorch installed. Install in the following order:

# Install torchvision. It comes with the pytorch stable release binary
python -m pip install torch torchvision

# Install the latest pytorch master from source.
# It should supersede the installation from the release binary.
cd $PYTORCH_HOME
python -m pip install --no-build-isolation -v -e .

# Check the pytorch installation version
python -c "import torch; print(torch.__version__)"

Benchmark List

Please refer to each subfolder to discover each benchmark suite. Links are provided where descriptions exist: