{
  "id": 323790,
  "title": "Supersonic speed prototyping with PyTorch Lightning",
  "url": "/competitions/unifesp-x-ray-body-part-classifier/discussion/323790",
  "author_name": "",
  "post_date": "2022-05-08T11:35:51.110328600Z",
  "votes": 4,
  "comment_count": 1,
  "views": 0,
  "content": "<ul>\n<li>Lightning Speed Prototyping. Simple notebook.</li>\n<li>Less imports. Easy to follow</li>\n<li>PyTorch Lightning project template.So less fuss.</li>\n<li>You can easily modify this code for different model, training methods (teacher student model, unsupervised training etc), add metrics and loggers(wandb)</li>\n<li><a href=\"https://www.kaggle.com/code/karkisa/lightning-dcm-classification-n1/notebook\" target=\"_blank\">NoteBook</a></li>\n</ul>",
  "messages": [
    {
      "id": "1781290",
      "postDate": "05/08/2022 11:35:51",
      "content": "<ul>\n<li>Lightning Speed Prototyping. Simple notebook.</li>\n<li>Less imports. Easy to follow</li>\n<li>PyTorch Lightning project template.So less fuss.</li>\n<li>You can easily modify this code for different model, training methods (teacher student model, unsupervised training etc), add metrics and loggers(wandb)</li>\n<li><a href=\"https://www.kaggle.com/code/karkisa/lightning-dcm-classification-n1/notebook\" target=\"_blank\">NoteBook</a></li>\n</ul>",
      "rawMarkdown": "Lightning Speed Prototyping. Simple notebook.\n- Less imports. Easy to follow\n- PyTorch Lightning project template.So less fuss.\n- You can easily modify this code for different model, training methods (teacher student model, unsupervised training etc), add metrics and loggers(wandb)\n- [NoteBook](https://www.kaggle.com/code/karkisa/lightning-dcm-classification-n1/notebook)",
      "votes": null
    },
    {
      "id": "1782608",
      "postDate": "05/09/2022 17:54:07",
      "content": "<p>This Kaggle post has a great explanation of how to use PyTorch Lightning for supersonic speed prototyping. The notebook is easy to follow, and the template makes it easy to modify the code for different models and training methods.</p>",
      "rawMarkdown": "This Kaggle post has a great explanation of how to use PyTorch Lightning for supersonic speed prototyping. The notebook is easy to follow, and the template makes it easy to modify the code for different models and training methods.",
      "votes": null
    }
  ],
  "comments": [
    {
      "id": 1782608,
      "author_name": "",
      "author_url": "",
      "post_date": "05/09/2022 17:54:07",
      "content": "<p>This Kaggle post has a great explanation of how to use PyTorch Lightning for supersonic speed prototyping. The notebook is easy to follow, and the template makes it easy to modify the code for different models and training methods.</p>",
      "votes": null,
      "replies": []
    }
  ],
  "raw_markdown_by_id": {
    "1781290": "Lightning Speed Prototyping. Simple notebook.\n- Less imports. Easy to follow\n- PyTorch Lightning project template.So less fuss.\n- You can easily modify this code for different model, training methods (teacher student model, unsupervised training etc), add metrics and loggers(wandb)\n- [NoteBook](https://www.kaggle.com/code/karkisa/lightning-dcm-classification-n1/notebook)",
    "1782608": "This Kaggle post has a great explanation of how to use PyTorch Lightning for supersonic speed prototyping. The notebook is easy to follow, and the template makes it easy to modify the code for different models and training methods."
  },
  "source": "meta"
}