{
  "id": 148715,
  "title": "Code Competition Doubts",
  "url": "/competitions/global-wheat-detection/discussion/148715",
  "author_name": "",
  "post_date": "2020-05-05T11:32:08.299288800Z",
  "votes": null,
  "comment_count": 5,
  "views": 0,
  "content": "<p>Due we have to include training code too in the notebook which we are submitting?</p>",
  "messages": [
    {
      "id": "834195",
      "postDate": "05/05/2020 11:32:08",
      "content": "<p>Due we have to include training code too in the notebook which we are submitting?</p>",
      "rawMarkdown": "Due we have to include training code too in the notebook which we are submitting?",
      "votes": null
    },
    {
      "id": "834223",
      "postDate": "05/05/2020 12:02:33",
      "content": "<p>No you don't. You can train your model wherever you want. On your notebook you just have to do the inference</p>",
      "rawMarkdown": "No you don't. You can train your model wherever you want. On your notebook you just have to do the inference",
      "votes": null
    },
    {
      "id": "834608",
      "postDate": "05/05/2020 16:43:39",
      "content": "<p>You will have to disclose the training code if you win :) But during the competition you can split your code as in <a href=\"https://www.kaggle.com/pestipeti/pytorch-starter-fasterrcnn-train\">https://www.kaggle.com/pestipeti/pytorch-starter-fasterrcnn-train</a> !</p>",
      "rawMarkdown": "You will have to disclose the training code if you win :) But during the competition you can split your code as in https://www.kaggle.com/pestipeti/pytorch-starter-fasterrcnn-train !",
      "votes": null
    },
    {
      "id": "835004",
      "postDate": "05/06/2020 01:20:05",
      "content": "<p>Thank you!</p>",
      "rawMarkdown": "Thank you!",
      "votes": null
    },
    {
      "id": "835005",
      "postDate": "05/06/2020 01:20:25",
      "content": "<p>Thank you!</p>",
      "rawMarkdown": "Thank you!",
      "votes": null
    },
    {
      "id": "870748",
      "postDate": "06/01/2020 21:58:28",
      "content": "<p>I'll ask here, to avoid creating new topic.</p>\n\n<p>So if I win, I should disclose the code and training code can be separate from submission/test-predicting code.\nBut should the training code be a Kaggle notebook, or can I run it locally, on my machine, and then load the model in submission notebook?</p>",
      "rawMarkdown": "I'll ask here, to avoid creating new topic.\n\nSo if I win, I should disclose the code and training code can be separate from submission/test-predicting code.\nBut should the training code be a Kaggle notebook, or can I run it locally, on my machine, and then load the model in submission notebook?",
      "votes": null
    }
  ],
  "comments": [
    {
      "id": 834223,
      "author_name": "pednt9",
      "author_url": "",
      "post_date": "05/05/2020 12:02:33",
      "content": "<p>No you don't. You can train your model wherever you want. On your notebook you just have to do the inference</p>",
      "votes": null,
      "replies": [
        {
          "id": 835004,
          "author_name": "jimitshah777",
          "author_url": "",
          "post_date": "05/06/2020 01:20:05",
          "content": "<p>Thank you!</p>",
          "votes": null,
          "replies": []
        }
      ]
    },
    {
      "id": 834608,
      "author_name": "bendvd",
      "author_url": "",
      "post_date": "05/05/2020 16:43:39",
      "content": "<p>You will have to disclose the training code if you win :) But during the competition you can split your code as in <a href=\"https://www.kaggle.com/pestipeti/pytorch-starter-fasterrcnn-train\">https://www.kaggle.com/pestipeti/pytorch-starter-fasterrcnn-train</a> !</p>",
      "votes": null,
      "replies": [
        {
          "id": 835005,
          "author_name": "jimitshah777",
          "author_url": "",
          "post_date": "05/06/2020 01:20:25",
          "content": "<p>Thank you!</p>",
          "votes": null,
          "replies": []
        }
      ]
    },
    {
      "id": 870748,
      "author_name": "bkarczewski",
      "author_url": "",
      "post_date": "06/01/2020 21:58:28",
      "content": "<p>I'll ask here, to avoid creating new topic.</p>\n\n<p>So if I win, I should disclose the code and training code can be separate from submission/test-predicting code.\nBut should the training code be a Kaggle notebook, or can I run it locally, on my machine, and then load the model in submission notebook?</p>",
      "votes": null,
      "replies": []
    }
  ],
  "raw_markdown_by_id": {
    "834195": "Due we have to include training code too in the notebook which we are submitting?",
    "834223": "No you don't. You can train your model wherever you want. On your notebook you just have to do the inference",
    "834608": "You will have to disclose the training code if you win :) But during the competition you can split your code as in https://www.kaggle.com/pestipeti/pytorch-starter-fasterrcnn-train !",
    "835004": "Thank you!",
    "835005": "Thank you!",
    "870748": "I'll ask here, to avoid creating new topic.\n\nSo if I win, I should disclose the code and training code can be separate from submission/test-predicting code.\nBut should the training code be a Kaggle notebook, or can I run it locally, on my machine, and then load the model in submission notebook?"
  },
  "source": "meta"
}