---
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](https://arxiv.org/abs/2110.13100) 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)


<img src="https://production-media.paperswithcode.com/datasets/0dbd44d8-19d9-495d-918a-b0db80facaf3.png" alt="" width="600"/>

## 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}  
}
```