{
  "id": 75284,
  "title": "Notebook hangs",
  "url": "/competitions/quora-insincere-questions-classification/discussion/75284",
  "author_name": "",
  "post_date": "2018-12-20T07:54:29.078892200Z",
  "votes": -1,
  "comment_count": 3,
  "views": 0,
  "content": "<p>Hi guys,</p>\n\n<p>Everytime I train the model with Keras, the notebook hangs after few epochs. I am not able to scroll or do anything. Does anyone else experience the same thing and is there any available solution?</p>\n\n<p>Cheers</p>",
  "messages": [
    {
      "id": "442616",
      "postDate": "12/20/2018 07:54:29",
      "content": "<p>Hi guys,</p>\n\n<p>Everytime I train the model with Keras, the notebook hangs after few epochs. I am not able to scroll or do anything. Does anyone else experience the same thing and is there any available solution?</p>\n\n<p>Cheers</p>",
      "rawMarkdown": "Hi guys,\n\nEverytime I train the model with Keras, the notebook hangs after few epochs. I am not able to scroll or do anything. Does anyone else experience the same thing and is there any available solution?\n\nCheers",
      "votes": null
    },
    {
      "id": "442640",
      "postDate": "12/20/2018 09:00:06",
      "content": "<p>depends upon the kernel you are running.  maybe you are running out of memory? when running look at memory allocation at top right of the kernel page for memory usage.   maybe you need to reduce the size of the dataframe ? </p>\n\n<p>You could reduce its size through memory optimisation and that may help:</p>\n\n<p><a href=\"https://www.kaggle.com/richarde/how-to-easily-reduce-training-times\">https://www.kaggle.com/richarde/how-to-easily-reduce-training-times</a></p>",
      "rawMarkdown": "depends upon the kernel you are running.  maybe you are running out of memory? when running look at memory allocation at top right of the kernel page for memory usage.   maybe you need to reduce the size of the dataframe ? \n\nYou could reduce its size through memory optimisation and that may help:\n\nhttps://www.kaggle.com/richarde/how-to-easily-reduce-training-times",
      "votes": null
    },
    {
      "id": "442754",
      "postDate": "12/20/2018 12:49:27",
      "content": "<p>hmm 10/14 gb with GPU. I think it's should be ok, right?</p>",
      "rawMarkdown": "hmm 10/14 gb with GPU. I think it's should be ok, right?",
      "votes": null
    },
    {
      "id": "442755",
      "postDate": "12/20/2018 12:49:58",
      "content": "<p>The Google word2vec embedding takes up 9gb already</p>",
      "rawMarkdown": "The Google word2vec embedding takes up 9gb already",
      "votes": null
    }
  ],
  "comments": [
    {
      "id": 442640,
      "author_name": "richarde",
      "author_url": "",
      "post_date": "12/20/2018 09:00:06",
      "content": "<p>depends upon the kernel you are running.  maybe you are running out of memory? when running look at memory allocation at top right of the kernel page for memory usage.   maybe you need to reduce the size of the dataframe ? </p>\n\n<p>You could reduce its size through memory optimisation and that may help:</p>\n\n<p><a href=\"https://www.kaggle.com/richarde/how-to-easily-reduce-training-times\">https://www.kaggle.com/richarde/how-to-easily-reduce-training-times</a></p>",
      "votes": null,
      "replies": [
        {
          "id": 442754,
          "author_name": "",
          "author_url": "",
          "post_date": "12/20/2018 12:49:27",
          "content": "<p>hmm 10/14 gb with GPU. I think it's should be ok, right?</p>",
          "votes": null,
          "replies": []
        },
        {
          "id": 442755,
          "author_name": "",
          "author_url": "",
          "post_date": "12/20/2018 12:49:58",
          "content": "<p>The Google word2vec embedding takes up 9gb already</p>",
          "votes": null,
          "replies": []
        }
      ]
    }
  ],
  "raw_markdown_by_id": {
    "442616": "Hi guys,\n\nEverytime I train the model with Keras, the notebook hangs after few epochs. I am not able to scroll or do anything. Does anyone else experience the same thing and is there any available solution?\n\nCheers",
    "442640": "depends upon the kernel you are running.  maybe you are running out of memory? when running look at memory allocation at top right of the kernel page for memory usage.   maybe you need to reduce the size of the dataframe ? \n\nYou could reduce its size through memory optimisation and that may help:\n\nhttps://www.kaggle.com/richarde/how-to-easily-reduce-training-times",
    "442754": "hmm 10/14 gb with GPU. I think it's should be ok, right?",
    "442755": "The Google word2vec embedding takes up 9gb already"
  },
  "source": "meta"
}