Nvbenjo is a utility for benchmarking inference of deep learning models on NVIDIA GPUs.
Project description
Nvbenjo
Nvbenjo is a utility for benchmarking inference of deep learning models on NVIDIA GPUs. It supports models in Onnx format as well as PyTorch models.
Usage
# Specify models to run in the command line
nvbenjo \
"+nvbenjo.models={\
efficientnet: {type_or_path: 'torchvision:efficientnet_b0', shape:['B',3,224,224], batch_sizes: [16,32]},\
resnet: {type_or_path: 'torchvision:wide_resnet101_2', shape: ['B',3,224,224], batch_sizes: [16,32]}\
}"
# or better, specify your own config (or one of the pre-defined config files)
nvbenjo -cn small
nvbenjo -cn="/my/config/path/myconfig.yaml"
# override single arguments of your config
nvbenjo -cn="/my/config/path/myconfig.yaml" nvbenjo.models.mymodel.num_batches=10
# show current config and help
nvbenjo -cn="/my/config/path/myconfig.yaml" --help
Development
Example using uv:
uv sync --extra dev --extra onnx-cpu # or gpu
uv run nvbenjo
# for a quick run
uv run nvbenjo -cn small
# tests
uv run pytest
uv run nox
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