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Datasets:
SamsungSAILMontreal
/
deepnets1m

Tasks:
Graph Machine Learning
Image Classification
Size:
1M<n<10M
ArXiv:
License:
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metadata
license: mit
task_categories:
  - graph-ml
  - image-classification
pretty_name: DeepNets
size_categories:
  - 1M<n<10M

This is a copy of the DeepNets-1M dataset originally released at https://github.com/facebookresearch/ppuda under the MIT license.

The dataset presents diverse computational graphs (1M training and 1402 evaluation) of neural network architectures used in image classification. See detailed description at https://paperswithcode.com/dataset/deepnets-1m and in the Parameter Prediction for Unseen Deep Architectures paper.

There are four files in this dataset:

  • deepnets1m_eval.hdf5; # 16 MB (md5: 1f5641329271583ad068f43e1521517e)
  • deepnets1m_meta.tar.gz; # 35 MB (md5: a42b6f513da6bbe493fc16a30d6d4e3e), run tar -xf deepnets1m_meta.tar.gz to unpack it before running any code reading the dataset
  • deepnets1m_search.hdf5; # 1.3 GB (md5: 0a93f4b4e3b729ea71eb383f78ea9b53)
  • deepnets1m_train.hdf5; # 10.3 GB (md5: 90bbe84bb1da0d76cdc06d5ff84fa23d)

Citation

If you use this dataset, please cite it as:

@inproceedings{knyazev2021parameter,
  title={Parameter Prediction for Unseen Deep Architectures},
  author={Knyazev, Boris and Drozdzal, Michal and Taylor, Graham W and Romero-Soriano, Adriana},
  booktitle={Advances in Neural Information Processing Systems},
  year={2021}  
}