{
  "id": 323811,
  "title": "TFrecords public dataset & example code for TPU training and inference",
  "url": "/competitions/herbarium-2022-fgvc9/discussion/323811",
  "author_name": "John Park",
  "post_date": "2022-05-08T14:11:16.538000",
  "votes": 2,
  "comment_count": 3,
  "views": 0,
  "content": "<p>Hi everyone,</p>\n<p>Happy Kaggling! </p>\n<p>TFrecords data is now available for the competition. Please see below:</p>\n<p><a href=\"https://www.kaggle.com/datasets/parkjohnychae/herbarium-2022-tfrec-256\" target=\"_blank\">TF records training set 256 x 256</a><br>\n<a href=\"https://www.kaggle.com/datasets/parkjohnychae/herbarium-2022-train-tfrec-480\" target=\"_blank\">TF records training set 480 x 480</a><br>\n<a href=\"https://www.kaggle.com/datasets/parkjohnychae/herbarium-2022-test-tfrec-480\" target=\"_blank\">TF records test set 480 x 480</a></p>\n<p>Please refer to an example notebook below about how to do the training/testing with .tfrec fiiles:<br>\n<a href=\"https://www.kaggle.com/code/parkjohnychae/8x-faster-training-with-tpu-lb-0-72-in-9-hr\" target=\"_blank\">Faster training with TPU - Training and Testing in resolution 380 x380 with TFrecords 480 x 480</a></p>",
  "messages": [
    {
      "id": 1782620,
      "postDate": "2022-05-09T18:07:10.707Z",
      "content": "<p>This is great! The TFRecords data will be very helpful for training models on the Herbarium dataset. Thanks for sharing!</p>",
      "rawMarkdown": "This is great! The TFRecords data will be very helpful for training models on the Herbarium dataset. Thanks for sharing!",
      "votes": 2,
      "replies": [
        {
          "id": 1782951,
          "postDate": "2022-05-10T02:44:08.097Z",
          "content": "<p>My pleasure, <a href=\"https://www.kaggle.com/satoshidatamoto\" target=\"_blank\">@satoshidatamoto</a>! Feel free to try them out and leave me feedback!</p>",
          "rawMarkdown": "My pleasure, @satoshidatamoto! Feel free to try them out and leave me feedback!",
          "votes": 1
        }
      ]
    },
    {
      "id": 1781444,
      "postDate": "2022-05-08T14:11:16.540Z",
      "content": "<p>Hi everyone,</p>\n<p>Happy Kaggling! </p>\n<p>TFrecords data is now available for the competition. Please see below:</p>\n<p><a href=\"https://www.kaggle.com/datasets/parkjohnychae/herbarium-2022-tfrec-256\" target=\"_blank\">TF records training set 256 x 256</a><br>\n<a href=\"https://www.kaggle.com/datasets/parkjohnychae/herbarium-2022-train-tfrec-480\" target=\"_blank\">TF records training set 480 x 480</a><br>\n<a href=\"https://www.kaggle.com/datasets/parkjohnychae/herbarium-2022-test-tfrec-480\" target=\"_blank\">TF records test set 480 x 480</a></p>\n<p>Please refer to an example notebook below about how to do the training/testing with .tfrec fiiles:<br>\n<a href=\"https://www.kaggle.com/code/parkjohnychae/8x-faster-training-with-tpu-lb-0-72-in-9-hr\" target=\"_blank\">Faster training with TPU - Training and Testing in resolution 380 x380 with TFrecords 480 x 480</a></p>",
      "rawMarkdown": "Hi everyone,\n\nHappy Kaggling! \n\nTFrecords data is now available for the competition. Please see below:\n\n[TF records training set 256 x 256](https://www.kaggle.com/datasets/parkjohnychae/herbarium-2022-tfrec-256)\n[TF records training set 480 x 480](https://www.kaggle.com/datasets/parkjohnychae/herbarium-2022-train-tfrec-480)\n[TF records test set 480 x 480](https://www.kaggle.com/datasets/parkjohnychae/herbarium-2022-test-tfrec-480)\n\nPlease refer to an example notebook below about how to do the training/testing with .tfrec fiiles:\n[Faster training with TPU - Training and Testing in resolution 380 x380 with TFrecords 480 x 480](https://www.kaggle.com/code/parkjohnychae/8x-faster-training-with-tpu-lb-0-72-in-9-hr)\n\n\n\n",
      "votes": 2
    },
    {
      "id": 2182156,
      "postDate": "2023-03-15T01:15:29.750Z",
      "content": "<p>Thank you. Too late but glad it is still here!</p>",
      "rawMarkdown": "Thank you. Too late but glad it is still here!"
    }
  ],
  "comments": [
    {
      "id": 1782620,
      "author_name": "",
      "author_url": "",
      "post_date": "2022-05-09T18:07:10.707000",
      "content": "<p>This is great! The TFRecords data will be very helpful for training models on the Herbarium dataset. Thanks for sharing!</p>",
      "votes": 2,
      "replies": [
        {
          "id": 1782951,
          "author_name": "John Park",
          "author_url": "",
          "post_date": "2022-05-10T02:44:08.097000",
          "content": "<p>My pleasure, <a href=\"https://www.kaggle.com/satoshidatamoto\" target=\"_blank\">@satoshidatamoto</a>! Feel free to try them out and leave me feedback!</p>",
          "votes": 1,
          "replies": []
        }
      ]
    },
    {
      "id": 2182156,
      "author_name": "Benjamin Brooks",
      "author_url": "",
      "post_date": "2023-03-15T01:15:29.750000",
      "content": "<p>Thank you. Too late but glad it is still here!</p>",
      "votes": 0,
      "replies": []
    }
  ],
  "raw_markdown_by_id": {
    "1782620": "This is great! The TFRecords data will be very helpful for training models on the Herbarium dataset. Thanks for sharing!",
    "1781444": "Hi everyone,\n\nHappy Kaggling! \n\nTFrecords data is now available for the competition. Please see below:\n\n[TF records training set 256 x 256](https://www.kaggle.com/datasets/parkjohnychae/herbarium-2022-tfrec-256)\n[TF records training set 480 x 480](https://www.kaggle.com/datasets/parkjohnychae/herbarium-2022-train-tfrec-480)\n[TF records test set 480 x 480](https://www.kaggle.com/datasets/parkjohnychae/herbarium-2022-test-tfrec-480)\n\nPlease refer to an example notebook below about how to do the training/testing with .tfrec fiiles:\n[Faster training with TPU - Training and Testing in resolution 380 x380 with TFrecords 480 x 480](https://www.kaggle.com/code/parkjohnychae/8x-faster-training-with-tpu-lb-0-72-in-9-hr)\n\n\n\n",
    "2182156": "Thank you. Too late but glad it is still here!"
  }
}