lightweight-neural-architecture-search
This is a collection of our zero-cost NAS and efficient vision applications.
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Download Latest Version (.zip)- E3D_L.txt
- E3D_M.txt
- E3D_S.txt
- E3D_X3DL_FLOPs.py
- E3D_X3DM_FLOPs.py
- E3D_X3DS_FLOPs.py
- README.md
- deepmad-29M-224.txt
- deepmad-29M-288.txt
- deepmad-50M.txt
- deepmad-89M.txt
- deepmad-R18.txt
- deepmad-R34.txt
- deepmad-R50.txt
- R152-like.txt
- R18-like.txt
- R50-like.txt
- deepmad_29M_224.py
- deepmad_29M_288.py
- deepmad_50M.py
- deepmad_89M.py
- deepmad_R18_FLOPs.py
- deepmad_R34_FLOPs.py
- deepmad_R50_FLOPs.py
- MBV2_FLOPs.py
- R50_FLOPs.py
- README.md
- damoyolo_k1kx_small.py
- damoyolo_k1kx_tiny.py
- damoyolo_kxkx_medium.py
- gfocal_r50_fpn_ms6x.py
- maedet_l_6x_lr0.02.py
- maedet_m_6x_lr0.02.py
- maedet_s_6x_lr0.02.py
- madnas.py
- maedet_l.txt
- maedet_m.txt
- maedet_s.txt
- R50_FLOPs.py
- R50_FLOPs_predictor.py
- README.md
- mixed19d2G.txt
- mixed7d0G.txt
- Mixed_19d2G.py
- Mixed_7d0G.py
- README.md
- arch.png
- __init__.py
- base.py
- json.py
- yaml.py
- __init__.py
- file.py
- io.py
- __init__.py
- config.py
- config_ds.py
- constant.py
- data_utils.py
- error.py
- file_utils.py
- import_utils.py
- json_utils.py
- logger.py
- megatron_utils.py
- metric.py
- model_tag.py
- plugins.py
- registry.py
- tensor_utils.py
- timer.py
- torch_utils.py
- type_assert.py
- typing.py
- __init__.py
- version.py
- nas.txt
- tests.txt
- __init__.py
- base.py
- budgets.py
- builder.py
- README.md
- __init__.py
- blocks_basic_3D.py
- super_res3d_k1dwk1.py
- cnn3dnet.py
- demo.py
- __init__.py
- blocks_basic.py
- qconv.py
- super_quant_res_k1dwk1.py
- super_res_k1dwk1.py
- super_res_k1dwsek1.py
- super_res_k1kx.py
- super_res_k1kxk1.py
- super_res_kxkx.py
- cnnnet.py
- demo.py
- __init__.py
- population.py
- README.md
- __init__.py
- config.in
- read_log.py
- README.md
- sample.sh
- sampler.py
- conv_data.out
- conv_data.out.fp16
- conv_data.out.fp16.damoyolo
- conv_data.out.int8
- __init__.py
- op_profiler.jpg
- predictor.py
- R50.txt
- README.md
- test_predictor.py
- util.py
- __init__.py
- builder.py
- op_predictor.py
- robust_gpu_predictor.py
- __init__.py
- blocks_basic.py
- qconv.py
- super_quant_res_k1dwk1.py
- super_res_k1dwk1.py
- super_res_k1dwsek1.py
- super_res_k1kx.py
- super_res_k1kxk1.py
- super_res_kxkx.py
- __init__.py
- blocks_basic_3D.py
- super_res3d_k1dwk1.py
- __init__.py
- base.py
- builder.py
- cnn3dnet.py
- cnnnet.py
- README.md
- __init__.py
- builder.py
- compute_deepmad.py
- compute_ensemble.py
- compute_madnas.py
- compute_random.py
- compute_stentr.py
- README.md
- __init__.py
- base.py
- builder.py
- README.md
- searcher.py
- synchonizer.py
- __init__.py
- base.py
- basic_mutators.py
- builder.py
- conv3d_bn_relu_mutator.py
- conv_bn_relu_mutator.py
- super_quant_res_k1dwk1_mutator.py
- super_res3d_k1dwk1_mutator.py
- super_res_k1dwk1_mutator.py
- super_res_k1kx_mutator.py
- super_res_k1kxk1_mutator.py
- __init__.py
- base.py
- builder.py
- random_sample.py
- README.md
- space_3d_k1dwk1.py
- space_k1dwk1.py
- space_k1dwsek1.py
- space_k1kx.py
- space_k1kxk1.py
- space_kxkx.py
- space_quant_k1dwk1.py
- space_utils.py
- __init__.py
- README.md
- strategy.py
- __init__.py
- dict_action.py
- dist_utils.py
- file_utils.py
- import_utils.py
- logger.py
- misc.py
- __init__.py
- dist_search.sh
- export.py
- local_search.sh
- search.py
- .gitignore
- get_started.md
- installation.md
- LICENSE
- MANIFEST.in
- NOTICE
- README.md
- setup.cfg
- setup.py
# Installation Guide
1. Get the code
git clone https://github.com/alibaba/lightweight-neural-architecture-search
Downloads the entire project code from GitHub to your computer.
cd lightweight-neural-architecture-search
Moves into the project folder you just downloaded.
2. Python
Easy RecommendedPrerequisites
pip install .
Installs the package published on PyPI directly β no need to clone the source.
python <μ€νν νμΌλͺ
>.py # READMEμμ μ νν μ€ν νμΌλͺ
μ νμΈνμΈμ
Runs the Python script (or module).
If it runs without errors and prints output in the terminal, it worked.
// repository documentation
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