colab_regular.ipynb

{
 "nbformat": 4,
 "nbformat_minor": 0,
 "metadata": {
  "kernelspec": {
   "display_name": "Python 3",
   "language": "python",
   "name": "python3"
  },
  "language_info": {
   "codemirror_mode": {
    "name": "ipython",
    "version": 2
   },
   "file_extension": ".py",
   "mimetype": "text/x-python",
   "name": "python",
   "nbconvert_exporter": "python",
   "pygments_lexer": "ipython2",
   "version": "2.7.6"
  },
  "colab": {
   "name": "colab.ipynb",
   "provenance": [],
   "machine_shape": "hm"
  },
  "accelerator": "GPU"
 },
 "cells": [
  {
   "cell_type": "code",
   "execution_count": null,
   "outputs": [],
   "source": [
    "# Is it Nvidia P100 or V100?  :D\n",
    "!nvidia-smi"
   ],
   "metadata": {
    "collapsed": false,
    "pycharm": {
     "name": "#%%\n"
    }
   }
  },
  {
   "cell_type": "code",
   "metadata": {
    "id": "8CFm7TmDTJLI",
    "pycharm": {
     "name": "#%%\n"
    },
    "colab": {
     "base_uri": "https://localhost:8080/",
     "height": 1000
    },
    "outputId": "eba7d51a-76df-4945-ab63-99109e936663"
   },
   "source": [
    "# This cell does the follows.\n",
    "# 1. Mount the google drive to colab, you will see a folder named \"gdrive\" then.\n",
    "# 2. Locate the main ipynb file, to which the working directory is set.\n",
    "# Then everything goes just as the same as in a local machine or server.\n",
    "# This cell does the follows.\n",
    "# 1. Mount the google drive to colab, you will see a folder named \"gdrive\" then.\n",
    "# 2. Locate the main ipynb file, to which the working directory is set.\n",
    "# Then everything goes just as the same as in a local machine or server.\n",
    "import sys, os\n",
    "if 'google.colab' in sys.modules:\n",
    "    from google.colab import drive\n",
    "    drive.mount('/content/gdrive')\n",
    "\n",
    "    !cp -rn '/content/gdrive/MyDrive/affwild2' '/home'   # This line copy the data from google drive to colab folder. Loading data directly\n",
    "    # from colab may be faster. But since colab ends a session for every 12 or 24 hours, the copy process has to be carried out for each time\n",
    "    # when a new session established.\n",
    "    os.chdir('/home/affwild2')\n",
    "    !unzip npy_data.zip\n",
    "\n",
    "    # If not copied, use the following two lines. In this case the data will be loaded from google drive. It may or may not be slower. Need to confirm.\n",
    "    file_name = 'colab_regular.ipynb'\n",
    "    os.chdir('/content/gdrive/MyDrive/ABAW2-attention')\n",
    "\n",
    "    # Find the main py file and change the working directory to it. If the main py is not the working directory, then \n",
    "    # maybe we can still locate the main py file first, then goes to the desired directory by a relative directory.\n",
    "    import subprocess\n",
    "    path_to_file = subprocess.check_output('find . -type f -name ' + str(file_name), shell=True).decode(\"utf-8\")\n",
    "    print(path_to_file)\n",
    "    path_to_file = path_to_file.replace(file_name,\"\").replace('\\n',\"\") # Remove the file name from the absolute directory.\n",
    "    os.chdir(path_to_file)\n",
    "    !pwd"
   ],
   "execution_count": 2,
   "outputs": [
    {
     "output_type": "stream",
     "text": [
      "Mounted at /content/gdrive\n",
      "Archive:  compacted_48.zip\n",
      "   creating: compacted_48/\n",
      "   creating: compacted_48/P01-T01/\n",
      "  inflating: compacted_48/P01-T01/continuous_label.npy  \n",
      "  inflating: compacted_48/P01-T01/frame.npy  \n",
      "  inflating: compacted_48/P01-T01/success.npy  \n",
      "   creating: compacted_48/P02-T01/\n",
      "  inflating: compacted_48/P02-T01/continuous_label.npy  \n",
      "  inflating: compacted_48/P02-T01/frame.npy  \n",
      "  inflating: compacted_48/P02-T01/success.npy  \n",
      "   creating: compacted_48/P03-T01/\n",
      "  inflating: compacted_48/P03-T01/continuous_label.npy  \n",
      "  inflating: compacted_48/P03-T01/frame.npy  \n",
      "  inflating: compacted_48/P03-T01/success.npy  \n",
      "   creating: compacted_48/P04-T01/\n",
      "  inflating: compacted_48/P04-T01/continuous_label.npy  \n",
      "  inflating: compacted_48/P04-T01/frame.npy  \n",
      "  inflating: compacted_48/P04-T01/success.npy  \n",
      "   creating: compacted_48/P05-T01/\n",
      "  inflating: compacted_48/P05-T01/continuous_label.npy  \n",
      "  inflating: compacted_48/P05-T01/frame.npy  \n",
      "  inflating: compacted_48/P05-T01/success.npy  \n",
      "   creating: compacted_48/P06-T01/\n",
      "  inflating: compacted_48/P06-T01/continuous_label.npy  \n",
      "  inflating: compacted_48/P06-T01/frame.npy  \n",
      "  inflating: compacted_48/P06-T01/success.npy  \n",
      "   creating: compacted_48/P07-T01/\n",
      "  inflating: compacted_48/P07-T01/continuous_label.npy  \n",
      "  inflating: compacted_48/P07-T01/frame.npy  \n",
      "  inflating: compacted_48/P07-T01/success.npy  \n",
      "   creating: compacted_48/P08-T01/\n",
      "  inflating: compacted_48/P08-T01/continuous_label.npy  \n",
      "  inflating: compacted_48/P08-T01/frame.npy  \n",
      "  inflating: compacted_48/P08-T01/success.npy  \n",
      "   creating: compacted_48/P09-T01/\n",
      "  inflating: compacted_48/P09-T01/continuous_label.npy  \n",
      "  inflating: compacted_48/P09-T01/frame.npy  \n",
      "  inflating: compacted_48/P09-T01/success.npy  \n",
      "   creating: compacted_48/P10-T01/\n",
      "  inflating: compacted_48/P10-T01/continuous_label.npy  \n",
      "  inflating: compacted_48/P10-T01/frame.npy  \n",
      "  inflating: compacted_48/P10-T01/success.npy  \n",
      "   creating: compacted_48/P11-T01/\n",
      "  inflating: compacted_48/P11-T01/continuous_label.npy  \n",
      "  inflating: compacted_48/P11-T01/frame.npy  \n",
      "  inflating: compacted_48/P11-T01/success.npy  \n",
      "   creating: compacted_48/P12-T01/\n",
      "  inflating: compacted_48/P12-T01/continuous_label.npy  \n",
      "  inflating: compacted_48/P12-T01/frame.npy  \n",
      "  inflating: compacted_48/P12-T01/success.npy  \n",
      "   creating: compacted_48/P13-T01/\n",
      "  inflating: compacted_48/P13-T01/continuous_label.npy  \n",
      "  inflating: compacted_48/P13-T01/frame.npy  \n",
      "  inflating: compacted_48/P13-T01/success.npy  \n",
      "   creating: compacted_48/P14-T01/\n",
      "  inflating: compacted_48/P14-T01/continuous_label.npy  \n",
      "  inflating: compacted_48/P14-T01/frame.npy  \n",
      "  inflating: compacted_48/P14-T01/success.npy  \n",
      "   creating: compacted_48/P15-T01/\n",
      "  inflating: compacted_48/P15-T01/continuous_label.npy  \n",
      "  inflating: compacted_48/P15-T01/frame.npy  \n",
      "  inflating: compacted_48/P15-T01/success.npy  \n",
      "   creating: compacted_48/P16-T01/\n",
      "  inflating: compacted_48/P16-T01/continuous_label.npy  \n",
      "  inflating: compacted_48/P16-T01/frame.npy  \n",
      "  inflating: compacted_48/P16-T01/success.npy  \n",
      "   creating: compacted_48/P17-T01/\n",
      "  inflating: compacted_48/P17-T01/continuous_label.npy  \n",
      "  inflating: compacted_48/P17-T01/frame.npy  \n",
      "  inflating: compacted_48/P17-T01/success.npy  \n",
      "   creating: compacted_48/P18-T01/\n",
      "  inflating: compacted_48/P18-T01/continuous_label.npy  \n",
      "  inflating: compacted_48/P18-T01/frame.npy  \n",
      "  inflating: compacted_48/P18-T01/success.npy  \n",
      "   creating: compacted_48/P19-T01/\n",
      "  inflating: compacted_48/P19-T01/continuous_label.npy  \n",
      "  inflating: compacted_48/P19-T01/frame.npy  \n",
      "  inflating: compacted_48/P19-T01/success.npy  \n",
      "   creating: compacted_48/P20-T01/\n",
      "  inflating: compacted_48/P20-T01/continuous_label.npy  \n",
      "  inflating: compacted_48/P20-T01/frame.npy  \n",
      "  inflating: compacted_48/P20-T01/success.npy  \n",
      "   creating: compacted_48/P21-T01/\n",
      "  inflating: compacted_48/P21-T01/continuous_label.npy  \n",
      "  inflating: compacted_48/P21-T01/frame.npy  \n",
      "  inflating: compacted_48/P21-T01/success.npy  \n",
      "   creating: compacted_48/P22-T01/\n",
      "  inflating: compacted_48/P22-T01/continuous_label.npy  \n",
      "  inflating: compacted_48/P22-T01/frame.npy  \n",
      "  inflating: compacted_48/P22-T01/success.npy  \n",
      "   creating: compacted_48/P23-T01/\n",
      "  inflating: compacted_48/P23-T01/continuous_label.npy  \n",
      "  inflating: compacted_48/P23-T01/frame.npy  \n",
      "  inflating: compacted_48/P23-T01/success.npy  \n",
      "   creating: compacted_48/P24-T01/\n",
      "  inflating: compacted_48/P24-T01/continuous_label.npy  \n",
      "  inflating: compacted_48/P24-T01/frame.npy  \n",
      "  inflating: compacted_48/P24-T01/success.npy  \n",
      "   creating: compacted_48/P25-T01/\n",
      "  inflating: compacted_48/P25-T01/continuous_label.npy  \n",
      "  inflating: compacted_48/P25-T01/frame.npy  \n",
      "  inflating: compacted_48/P25-T01/success.npy  \n",
      "   creating: compacted_48/P26-T01/\n",
      "  inflating: compacted_48/P26-T01/continuous_label.npy  \n",
      "  inflating: compacted_48/P26-T01/frame.npy  \n",
      "  inflating: compacted_48/P26-T01/success.npy  \n",
      "   creating: compacted_48/P27-T01/\n",
      "  inflating: compacted_48/P27-T01/continuous_label.npy  \n",
      "  inflating: compacted_48/P27-T01/frame.npy  \n",
      "  inflating: compacted_48/P27-T01/success.npy  \n",
      "   creating: compacted_48/P28-T01/\n",
      "  inflating: compacted_48/P28-T01/continuous_label.npy  \n",
      "  inflating: compacted_48/P28-T01/frame.npy  \n",
      "  inflating: compacted_48/P28-T01/success.npy  \n",
      "   creating: compacted_48/P29-T01/\n",
      "  inflating: compacted_48/P29-T01/continuous_label.npy  \n",
      "  inflating: compacted_48/P29-T01/frame.npy  \n",
      "  inflating: compacted_48/P29-T01/success.npy  \n",
      "   creating: compacted_48/P30-T01/\n",
      "  inflating: compacted_48/P30-T01/continuous_label.npy  \n",
      "  inflating: compacted_48/P30-T01/frame.npy  \n",
      "  inflating: compacted_48/P30-T01/success.npy  \n",
      "   creating: compacted_48/P31-T01/\n",
      "  inflating: compacted_48/P31-T01/continuous_label.npy  \n",
      "  inflating: compacted_48/P31-T01/frame.npy  \n",
      "  inflating: compacted_48/P31-T01/success.npy  \n",
      "   creating: compacted_48/P32-T01/\n",
      "  inflating: compacted_48/P32-T01/continuous_label.npy  \n",
      "  inflating: compacted_48/P32-T01/frame.npy  \n",
      "  inflating: compacted_48/P32-T01/success.npy  \n",
      "   creating: compacted_48/P33-T01/\n",
      "  inflating: compacted_48/P33-T01/continuous_label.npy  \n",
      "  inflating: compacted_48/P33-T01/frame.npy  \n",
      "  inflating: compacted_48/P33-T01/success.npy  \n",
      "   creating: compacted_48/P34-T01/\n",
      "  inflating: compacted_48/P34-T01/continuous_label.npy  \n",
      "  inflating: compacted_48/P34-T01/frame.npy  \n",
      "  inflating: compacted_48/P34-T01/success.npy  \n",
      "   creating: compacted_48/P35-T01/\n",
      "  inflating: compacted_48/P35-T01/continuous_label.npy  \n",
      "  inflating: compacted_48/P35-T01/frame.npy  \n",
      "  inflating: compacted_48/P35-T01/success.npy  \n",
      "   creating: compacted_48/P36-T01/\n",
      "  inflating: compacted_48/P36-T01/continuous_label.npy  \n",
      "  inflating: compacted_48/P36-T01/frame.npy  \n",
      "  inflating: compacted_48/P36-T01/success.npy  \n",
      "   creating: compacted_48/P37-T01/\n",
      "  inflating: compacted_48/P37-T01/continuous_label.npy  \n",
      "  inflating: compacted_48/P37-T01/frame.npy  \n",
      "  inflating: compacted_48/P37-T01/success.npy  \n",
      "   creating: compacted_48/P38-T01/\n",
      "  inflating: compacted_48/P38-T01/continuous_label.npy  \n",
      "  inflating: compacted_48/P38-T01/frame.npy  \n",
      "  inflating: compacted_48/P38-T01/success.npy  \n",
      "   creating: compacted_48/P39-T01/\n",
      "  inflating: compacted_48/P39-T01/continuous_label.npy  \n",
      "  inflating: compacted_48/P39-T01/frame.npy  \n",
      "  inflating: compacted_48/P39-T01/success.npy  \n",
      "   creating: compacted_48/P40-T01/\n",
      "  inflating: compacted_48/P40-T01/continuous_label.npy  \n",
      "  inflating: compacted_48/P40-T01/frame.npy  \n",
      "  inflating: compacted_48/P40-T01/success.npy  \n",
      "   creating: compacted_48/P41-T01/\n",
      "  inflating: compacted_48/P41-T01/continuous_label.npy  \n",
      "  inflating: compacted_48/P41-T01/frame.npy  \n",
      "  inflating: compacted_48/P41-T01/success.npy  \n",
      "   creating: compacted_48/P42-T01/\n",
      "  inflating: compacted_48/P42-T01/continuous_label.npy  \n",
      "  inflating: compacted_48/P42-T01/frame.npy  \n",
      "  inflating: compacted_48/P42-T01/success.npy  \n",
      "   creating: compacted_48/P43-T01/\n",
      "  inflating: compacted_48/P43-T01/continuous_label.npy  \n",
      "  inflating: compacted_48/P43-T01/frame.npy  \n",
      "  inflating: compacted_48/P43-T01/success.npy  \n",
      "   creating: compacted_48/P44-T01/\n",
      "  inflating: compacted_48/P44-T01/continuous_label.npy  \n",
      "  inflating: compacted_48/P44-T01/frame.npy  \n",
      "  inflating: compacted_48/P44-T01/success.npy  \n",
      "   creating: compacted_48/P45-T01/\n",
      "  inflating: compacted_48/P45-T01/continuous_label.npy  \n",
      "  inflating: compacted_48/P45-T01/frame.npy  \n",
      "  inflating: compacted_48/P45-T01/success.npy  \n",
      "   creating: compacted_48/P46-T01/\n",
      "  inflating: compacted_48/P46-T01/continuous_label.npy  \n",
      "  inflating: compacted_48/P46-T01/frame.npy  \n",
      "  inflating: compacted_48/P46-T01/success.npy  \n",
      "   creating: compacted_48/P47-T01/\n",
      "  inflating: compacted_48/P47-T01/continuous_label.npy  \n",
      "  inflating: compacted_48/P47-T01/frame.npy  \n",
      "  inflating: compacted_48/P47-T01/success.npy  \n",
      "   creating: compacted_48/P48-T01/\n",
      "  inflating: compacted_48/P48-T01/continuous_label.npy  \n",
      "  inflating: compacted_48/P48-T01/frame.npy  \n",
      "  inflating: compacted_48/P48-T01/success.npy  \n",
      "   creating: compacted_48/P49-T01/\n",
      "  inflating: compacted_48/P49-T01/continuous_label.npy  \n",
      "  inflating: compacted_48/P49-T01/frame.npy  \n",
      "  inflating: compacted_48/P49-T01/success.npy  \n",
      "   creating: compacted_48/P50-T01/\n",
      "  inflating: compacted_48/P50-T01/continuous_label.npy  \n",
      "  inflating: compacted_48/P50-T01/frame.npy  \n",
      "  inflating: compacted_48/P50-T01/success.npy  \n",
      "   creating: compacted_48/P51-T01/\n",
      "  inflating: compacted_48/P51-T01/continuous_label.npy  \n",
      "  inflating: compacted_48/P51-T01/frame.npy  \n",
      "  inflating: compacted_48/P51-T01/success.npy  \n",
      "   creating: compacted_48/P52-T01/\n",
      "  inflating: compacted_48/P52-T01/continuous_label.npy  \n",
      "  inflating: compacted_48/P52-T01/frame.npy  \n",
      "  inflating: compacted_48/P52-T01/success.npy  \n",
      "   creating: compacted_48/P53-T01/\n",
      "  inflating: compacted_48/P53-T01/continuous_label.npy  \n",
      "  inflating: compacted_48/P53-T01/frame.npy  \n",
      "  inflating: compacted_48/P53-T01/success.npy  \n",
      "   creating: compacted_48/P54-T01/\n",
      "  inflating: compacted_48/P54-T01/continuous_label.npy  \n",
      "  inflating: compacted_48/P54-T01/frame.npy  \n",
      "  inflating: compacted_48/P54-T01/success.npy  \n",
      "   creating: compacted_48/P55-T01/\n",
      "  inflating: compacted_48/P55-T01/continuous_label.npy  \n",
      "  inflating: compacted_48/P55-T01/frame.npy  \n",
      "  inflating: compacted_48/P55-T01/success.npy  \n",
      "   creating: compacted_48/P56-T01/\n",
      "  inflating: compacted_48/P56-T01/continuous_label.npy  \n",
      "  inflating: compacted_48/P56-T01/frame.npy  \n",
      "  inflating: compacted_48/P56-T01/success.npy  \n",
      "   creating: compacted_48/P57-T01/\n",
      "  inflating: compacted_48/P57-T01/continuous_label.npy  \n",
      "  inflating: compacted_48/P57-T01/frame.npy  \n",
      "  inflating: compacted_48/P57-T01/success.npy  \n",
      "   creating: compacted_48/P58-T01/\n",
      "  inflating: compacted_48/P58-T01/continuous_label.npy  \n",
      "  inflating: compacted_48/P58-T01/frame.npy  \n",
      "  inflating: compacted_48/P58-T01/success.npy  \n",
      "   creating: compacted_48/P59-T01/\n",
      "  inflating: compacted_48/P59-T01/continuous_label.npy  \n",
      "  inflating: compacted_48/P59-T01/frame.npy  \n",
      "  inflating: compacted_48/P59-T01/success.npy  \n",
      "   creating: compacted_48/P60-T01/\n",
      "  inflating: compacted_48/P60-T01/continuous_label.npy  \n",
      "  inflating: compacted_48/P60-T01/frame.npy  \n",
      "  inflating: compacted_48/P60-T01/success.npy  \n",
      "   creating: compacted_48/P61-T01/\n",
      "  inflating: compacted_48/P61-T01/continuous_label.npy  \n",
      "  inflating: compacted_48/P61-T01/frame.npy  \n",
      "  inflating: compacted_48/P61-T01/success.npy  \n",
      "   creating: compacted_48/P62-T01/\n",
      "  inflating: compacted_48/P62-T01/continuous_label.npy  \n",
      "  inflating: compacted_48/P62-T01/frame.npy  \n",
      "  inflating: compacted_48/P62-T01/success.npy  \n",
      "   creating: compacted_48/P63-T01/\n",
      "  inflating: compacted_48/P63-T01/continuous_label.npy  \n",
      "  inflating: compacted_48/P63-T01/frame.npy  \n",
      "  inflating: compacted_48/P63-T01/success.npy  \n",
      "   creating: compacted_48/P64-T01/\n",
      "  inflating: compacted_48/P64-T01/continuous_label.npy  \n",
      "  inflating: compacted_48/P64-T01/frame.npy  \n",
      "  inflating: compacted_48/P64-T01/success.npy  \n",
      "   creating: compacted_48/P65-T01/\n",
      "  inflating: compacted_48/P65-T01/continuous_label.npy  \n",
      "  inflating: compacted_48/P65-T01/frame.npy  \n",
      "  inflating: compacted_48/P65-T01/success.npy  \n",
      "   creating: compacted_48/P66-T01/\n",
      "  inflating: compacted_48/P66-T01/continuous_label.npy  \n",
      "  inflating: compacted_48/P66-T01/frame.npy  \n",
      "  inflating: compacted_48/P66-T01/success.npy  \n",
      "   creating: compacted_48/P67-T01/\n",
      "  inflating: compacted_48/P67-T01/continuous_label.npy  \n",
      "  inflating: compacted_48/P67-T01/frame.npy  \n",
      "  inflating: compacted_48/P67-T01/success.npy  \n",
      "   creating: compacted_48/P68-T01/\n",
      "  inflating: compacted_48/P68-T01/continuous_label.npy  \n",
      "  inflating: compacted_48/P68-T01/frame.npy  \n",
      "  inflating: compacted_48/P68-T01/success.npy  \n",
      "   creating: compacted_48/P69-T01/\n",
      "  inflating: compacted_48/P69-T01/continuous_label.npy  \n",
      "  inflating: compacted_48/P69-T01/frame.npy  \n",
      "  inflating: compacted_48/P69-T01/success.npy  \n",
      "   creating: compacted_48/P70-T01/\n",
      "  inflating: compacted_48/P70-T01/continuous_label.npy  \n",
      "  inflating: compacted_48/P70-T01/frame.npy  \n",
      "  inflating: compacted_48/P70-T01/success.npy  \n",
      "   creating: compacted_48/P71-T01/\n",
      "  inflating: compacted_48/P71-T01/continuous_label.npy  \n",
      "  inflating: compacted_48/P71-T01/frame.npy  \n",
      "  inflating: compacted_48/P71-T01/success.npy  \n",
      "   creating: compacted_48/P72-T01/\n",
      "  inflating: compacted_48/P72-T01/continuous_label.npy  \n",
      "  inflating: compacted_48/P72-T01/frame.npy  \n",
      "  inflating: compacted_48/P72-T01/success.npy  \n",
      "   creating: compacted_48/P73-T01/\n",
      "  inflating: compacted_48/P73-T01/continuous_label.npy  \n",
      "  inflating: compacted_48/P73-T01/frame.npy  \n",
      "  inflating: compacted_48/P73-T01/success.npy  \n",
      "   creating: compacted_48/P74-T01/\n",
      "  inflating: compacted_48/P74-T01/continuous_label.npy  \n",
      "  inflating: compacted_48/P74-T01/frame.npy  \n",
      "  inflating: compacted_48/P74-T01/success.npy  \n",
      "   creating: compacted_48/P75-T01/\n",
      "  inflating: compacted_48/P75-T01/continuous_label.npy  \n",
      "  inflating: compacted_48/P75-T01/frame.npy  \n",
      "  inflating: compacted_48/P75-T01/success.npy  \n",
      "   creating: compacted_48/P76-T01/\n",
      "  inflating: compacted_48/P76-T01/continuous_label.npy  \n",
      "  inflating: compacted_48/P76-T01/frame.npy  \n",
      "  inflating: compacted_48/P76-T01/success.npy  \n",
      "   creating: compacted_48/P77-T01/\n",
      "  inflating: compacted_48/P77-T01/continuous_label.npy  \n",
      "  inflating: compacted_48/P77-T01/frame.npy  \n",
      "  inflating: compacted_48/P77-T01/success.npy  \n",
      "   creating: compacted_48/P78-T01/\n",
      "  inflating: compacted_48/P78-T01/continuous_label.npy  \n",
      "  inflating: compacted_48/P78-T01/frame.npy  \n",
      "  inflating: compacted_48/P78-T01/success.npy  \n",
      "   creating: compacted_48/P79-T01/\n",
      "  inflating: compacted_48/P79-T01/continuous_label.npy  \n",
      "  inflating: compacted_48/P79-T01/frame.npy  \n",
      "  inflating: compacted_48/P79-T01/success.npy  \n",
      "   creating: compacted_48/P80-T01/\n",
      "  inflating: compacted_48/P80-T01/continuous_label.npy  \n",
      "  inflating: compacted_48/P80-T01/frame.npy  \n",
      "  inflating: compacted_48/P80-T01/success.npy  \n",
      "   creating: compacted_48/P81-T01/\n",
      "  inflating: compacted_48/P81-T01/continuous_label.npy  \n",
      "  inflating: compacted_48/P81-T01/frame.npy  \n",
      "  inflating: compacted_48/P81-T01/success.npy  \n",
      "   creating: compacted_48/P82-T01/\n",
      "  inflating: compacted_48/P82-T01/continuous_label.npy  \n",
      "  inflating: compacted_48/P82-T01/frame.npy  \n",
      "  inflating: compacted_48/P82-T01/success.npy  \n",
      "   creating: compacted_48/P83-T01/\n",
      "  inflating: compacted_48/P83-T01/continuous_label.npy  \n",
      "  inflating: compacted_48/P83-T01/frame.npy  \n",
      "  inflating: compacted_48/P83-T01/success.npy  \n",
      "   creating: compacted_48/P84-T01/\n",
      "  inflating: compacted_48/P84-T01/continuous_label.npy  \n",
      "  inflating: compacted_48/P84-T01/frame.npy  \n",
      "  inflating: compacted_48/P84-T01/success.npy  \n",
      "   creating: compacted_48/P85-T01/\n",
      "  inflating: compacted_48/P85-T01/continuous_label.npy  \n",
      "  inflating: compacted_48/P85-T01/frame.npy  \n",
      "  inflating: compacted_48/P85-T01/success.npy  \n",
      "   creating: compacted_48/P86-T01/\n",
      "  inflating: compacted_48/P86-T01/continuous_label.npy  \n",
      "  inflating: compacted_48/P86-T01/frame.npy  \n",
      "  inflating: compacted_48/P86-T01/success.npy  \n",
      "   creating: compacted_48/P87-T01/\n",
      "  inflating: compacted_48/P87-T01/continuous_label.npy  \n",
      "  inflating: compacted_48/P87-T01/frame.npy  \n",
      "  inflating: compacted_48/P87-T01/success.npy  \n",
      "   creating: compacted_48/P88-T01/\n",
      "  inflating: compacted_48/P88-T01/continuous_label.npy  \n",
      "  inflating: compacted_48/P88-T01/frame.npy  \n",
      "  inflating: compacted_48/P88-T01/success.npy  \n",
      "   creating: compacted_48/P89-T01/\n",
      "  inflating: compacted_48/P89-T01/continuous_label.npy  \n",
      "  inflating: compacted_48/P89-T01/frame.npy  \n",
      "  inflating: compacted_48/P89-T01/success.npy  \n",
      "   creating: compacted_48/P90-T01/\n",
      "  inflating: compacted_48/P90-T01/continuous_label.npy  \n",
      "  inflating: compacted_48/P90-T01/frame.npy  \n",
      "  inflating: compacted_48/P90-T01/success.npy  \n",
      "   creating: compacted_48/P91-T01/\n",
      "  inflating: compacted_48/P91-T01/continuous_label.npy  \n",
      "  inflating: compacted_48/P91-T01/frame.npy  \n",
      "  inflating: compacted_48/P91-T01/success.npy  \n",
      "   creating: compacted_48/P92-T01/\n",
      "  inflating: compacted_48/P92-T01/continuous_label.npy  \n",
      "  inflating: compacted_48/P92-T01/frame.npy  \n",
      "  inflating: compacted_48/P92-T01/success.npy  \n",
      "   creating: compacted_48/P93-T01/\n",
      "  inflating: compacted_48/P93-T01/continuous_label.npy  \n",
      "  inflating: compacted_48/P93-T01/frame.npy  \n",
      "  inflating: compacted_48/P93-T01/success.npy  \n",
      "   creating: compacted_48/P94-T01/\n",
      "  inflating: compacted_48/P94-T01/continuous_label.npy  \n",
      "  inflating: compacted_48/P94-T01/frame.npy  \n",
      "  inflating: compacted_48/P94-T01/success.npy  \n",
      "   creating: compacted_48/P95-T01/\n",
      "  inflating: compacted_48/P95-T01/continuous_label.npy  \n",
      "  inflating: compacted_48/P95-T01/frame.npy  \n",
      "  inflating: compacted_48/P95-T01/success.npy  \n",
      "   creating: compacted_48/P96-T01/\n",
      "  inflating: compacted_48/P96-T01/continuous_label.npy  \n",
      "  inflating: compacted_48/P96-T01/frame.npy  \n",
      "  inflating: compacted_48/P96-T01/success.npy  \n"
     ],
     "name": "stdout"
    },
    {
     "output_type": "error",
     "ename": "FileNotFoundError",
     "evalue": "ignored",
     "traceback": [
      "\u001B[0;31m---------------------------------------------------------------------------\u001B[0m",
      "\u001B[0;31mFileNotFoundError\u001B[0m                         Traceback (most recent call last)",
      "\u001B[0;32m<ipython-input-2-72c07c0f64b5>\u001B[0m in \u001B[0;36m<module>\u001B[0;34m()\u001B[0m\n\u001B[1;32m     20\u001B[0m     \u001B[0;31m# If not copied, use the following two lines. In this case the data will be loaded from google drive. It may or may not be slower. Need to confirm.\u001B[0m\u001B[0;34m\u001B[0m\u001B[0;34m\u001B[0m\u001B[0;34m\u001B[0m\u001B[0m\n\u001B[1;32m     21\u001B[0m     \u001B[0mfile_name\u001B[0m \u001B[0;34m=\u001B[0m \u001B[0;34m'colab.ipynb'\u001B[0m\u001B[0;34m\u001B[0m\u001B[0;34m\u001B[0m\u001B[0m\n\u001B[0;32m---> 22\u001B[0;31m     \u001B[0mos\u001B[0m\u001B[0;34m.\u001B[0m\u001B[0mchdir\u001B[0m\u001B[0;34m(\u001B[0m\u001B[0;34m'/content/gdrive/MyDrive/phd2'\u001B[0m\u001B[0;34m)\u001B[0m\u001B[0;34m\u001B[0m\u001B[0;34m\u001B[0m\u001B[0m\n\u001B[0m\u001B[1;32m     23\u001B[0m \u001B[0;34m\u001B[0m\u001B[0m\n\u001B[1;32m     24\u001B[0m     \u001B[0;31m# Find the main py file and change the working directory to it. If the main py is not the working directory, then\u001B[0m\u001B[0;34m\u001B[0m\u001B[0;34m\u001B[0m\u001B[0;34m\u001B[0m\u001B[0m\n",
      "\u001B[0;31mFileNotFoundError\u001B[0m: [Errno 2] No such file or directory: '/content/gdrive/MyDrive/phd2'"
     ]
    }
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "outputs": [],
   "source": [
    "# # roll back to torch 1.6.0 to maintain the consistency with other instances.\n",
    "# !rm -rf /usr/local/lib/python3.7/dist-packages/torch*\n",
    "#\n",
    "# import sys\n",
    "# sys.path.append('/usr/local/lib/python3.7/site-packages/')\n",
    "#\n",
    "# !pip install torch==1.6.0+cu101 torchvision==0.7.0+cu101 -f https://download.pytorch.org/whl/torch_stable.html\n",
    "# !pip install pandas ipykernel scipy\n",
    "#\n",
    "# import torch\n",
    "# print(torch.__version__)\n"
   ],
   "metadata": {
    "collapsed": false,
    "pycharm": {
     "name": "#%%\n"
    }
   }
  },
  {
   "cell_type": "code",
   "metadata": {
    "pycharm": {
     "name": "#%%\n"
    },
    "colab": {
     "base_uri": "https://localhost:8080/"
    },
    "id": "QN1uHaFpK37Z",
    "outputId": "0215e209-1efd-4264-ebca-31e4119c0619"
   },
   "source": [
    "!python main.py -model_load_path \"/content/gdrive/MyDrive/load_path\" -model_save_path \"/content/gdrive/MyDrive/save_path\" \\\n",
    "    -python_package_path \"/content/gdrive/MyDrive/ABAW2-attention\" -dataset_path \"/home/affwild2/\" -high_performance_cluster 1 -batch_size 8 -train_emotion \"arousal\" -head \"sh\"  -folds_to_run 4"
   ],
   "execution_count": null,
   "outputs": [
    {
     "output_type": "stream",
     "text": [
      "Running fold: 1\n",
      "How many folds? 9\n",
      "Downloading: \"https://download.pytorch.org/models/vgg11_bn-6002323d.pth\" to /root/.cache/torch/hub/checkpoints/vgg11_bn-6002323d.pth\n",
      "100% 507M/507M [00:19<00:00, 26.7MB/s]\n",
      "/usr/local/lib/python3.6/dist-packages/torch/nn/modules/rnn.py:61: UserWarning: dropout option adds dropout after all but last recurrent layer, so non-zero dropout expects num_layers greater than 1, but got dropout=0.5 and num_layers=1\n",
      "  \"num_layers={}\".format(dropout, num_layers))\n",
      "Layers with params to learn:\n",
      "\t spatial_embedding.spatial_model.11.weight\n",
      "\t spatial_embedding.spatial_model.11.bias\n",
      "\t spatial_embedding.spatial_model.12.weight\n",
      "\t spatial_embedding.spatial_model.12.bias\n",
      "\t spatial_embedding.spatial_model.15.weight\n",
      "\t spatial_embedding.spatial_model.15.bias\n",
      "\t spatial_embedding.spatial_model.16.weight\n",
      "\t spatial_embedding.spatial_model.16.bias\n",
      "\t spatial_embedding.spatial_model.18.weight\n",
      "\t spatial_embedding.spatial_model.18.bias\n",
      "\t spatial_embedding.spatial_model.19.weight\n",
      "\t spatial_embedding.spatial_model.19.bias\n",
      "\t spatial_embedding.spatial_model.22.weight\n",
      "\t spatial_embedding.spatial_model.22.bias\n",
      "\t spatial_embedding.spatial_model.23.weight\n",
      "\t spatial_embedding.spatial_model.23.bias\n",
      "\t spatial_embedding.spatial_model.25.weight\n",
      "\t spatial_embedding.spatial_model.25.bias\n",
      "\t spatial_embedding.spatial_model.26.weight\n",
      "\t spatial_embedding.spatial_model.26.bias\n",
      "\t spatial_embedding.shared_fc_layers.0.weight\n",
      "\t spatial_embedding.shared_fc_layers.0.bias\n",
      "\t spatial_embedding.shared_fc_layers.2.weight\n",
      "\t spatial_embedding.shared_fc_layers.2.bias\n",
      "\t temporal_block.rnn.weight_ih_l0\n",
      "\t temporal_block.rnn.weight_hh_l0\n",
      "\t temporal_block.rnn.bias_ih_l0\n",
      "\t temporal_block.rnn.bias_hh_l0\n",
      "\t temporal_block.rnn.weight_ih_l0_reverse\n",
      "\t temporal_block.rnn.weight_hh_l0_reverse\n",
      "\t temporal_block.rnn.bias_ih_l0_reverse\n",
      "\t temporal_block.rnn.bias_hh_l0_reverse\n",
      "\t temporal_block.fc_out.weight\n",
      "\t temporal_block.fc_out.bias\n",
      "\t 34 layers\n",
      "------\n",
      "Starting training, on device: cuda\n",
      "tcmalloc: large alloc 1541406720 bytes == 0xe97de000 @  0x7fbed59ed1e7 0x7fbed2e1b41e 0x7fbed2e6bbdb 0x7fbed2e6bc78 0x7fbed2f12e10 0x7fbed2f1353c 0x7fbed2f1365d 0x566f73 0x59fd0e 0x7fbed2e58ea7 0x50a12f 0x50beb4 0x507be4 0x509900 0x50a2fd 0x50beb4 0x507be4 0x588d41 0x59fd0e 0x7fbed2e58ea7 0x50a12f 0x50beb4 0x507be4 0x509900 0x50a2fd 0x50beb4 0x5095c8 0x50a2fd 0x50beb4 0x507be4 0x508ec2\n",
      "tcmalloc: large alloc 6165626880 bytes == 0x7fbc82800000 @  0x7fbed59cfb6b 0x7fbed59ef379 0x7fbe79e9674e 0x7fbe79e987b6 0x7fbeb4902d53 0x7fbeb42ed8cf 0x7fbeb4604cac 0x7fbeb45b031b 0x7fbeb45cf135 0x7fbeb45aab4b 0x7fbeb45b031b 0x7fbeb45cf135 0x7fbeb46992be 0x7fbeb5babd6e 0x7fbeb45b031b 0x7fbeb45cf135 0x7fbeb45aab4b 0x7fbeb45b031b 0x7fbeb45cf135 0x7fbeb46992be 0x7fbeb42d9800 0x7fbeb48067ea 0x7fbeb3e58081 0x7fbeb48f2c76 0x7fbeb48d6810 0x7fbec423f23d 0x7fbec4346d31 0x50a4a5 0x50cc96 0x5095c8 0x50a2fd\n",
      "tcmalloc: large alloc 6165626880 bytes == 0x7fbb13000000 @  0x7fbed59cfb6b 0x7fbed59ef379 0x7fbe79e9674e 0x7fbe79e987b6 0x7fbeb42ecfa2 0x7fbeb45d7bd3 0x7fbeb45af207 0x7fbeb45ca2dc 0x7fbeb45a678a 0x7fbeb45af207 0x7fbeb45ca2dc 0x7fbeb46960dd 0x7fbeb42fe09f 0x7fbeb43006b6 0x7fbeb4300bad 0x7fbeb4300f45 0x7fbeb4007e14 0x7fbeb45d7b09 0x7fbeb3e57ef0 0x7fbeb476791b 0x7fbeb4653b4c 0x7fbeb5ca86b4 0x7fbeb3e57ef0 0x7fbeb476791b 0x7fbeb48a839c 0x7fbec42f603b 0x7fbec42f6806 0x566f73 0x59fd0e 0x4b1eea 0x6196df\n",
      "Processed: 1/34 , 2.94%tcmalloc: large alloc 1538998272 bytes == 0xe9592000 @  0x7fbed59ed1e7 0x7fbed2e1b41e 0x7fbed2e6bbdb 0x7fbed2e6bc78 0x7fbed2f12e10 0x7fbed2f1353c 0x7fbed2f1365d 0x566f73 0x59fd0e 0x7fbed2e58ea7 0x50a12f 0x50beb4 0x507be4 0x509900 0x50a2fd 0x50beb4 0x507be4 0x588d41 0x59fd0e 0x7fbed2e58ea7 0x50a12f 0x50beb4 0x507be4 0x509900 0x50a2fd 0x50beb4 0x5095c8 0x50a2fd 0x50beb4 0x507be4 0x508ec2\n",
      "tcmalloc: large alloc 6155993088 bytes == 0x7fbc82800000 @  0x7fbed59cfb6b 0x7fbed59ef379 0x7fbe79e9674e 0x7fbe79e987b6 0x7fbeb4902d53 0x7fbeb42ed8cf 0x7fbeb4604cac 0x7fbeb45b031b 0x7fbeb45cf135 0x7fbeb45aab4b 0x7fbeb45b031b 0x7fbeb45cf135 0x7fbeb46992be 0x7fbeb5babd6e 0x7fbeb45b031b 0x7fbeb45cf135 0x7fbeb45aab4b 0x7fbeb45b031b 0x7fbeb45cf135 0x7fbeb46992be 0x7fbeb42d9800 0x7fbeb48067ea 0x7fbeb3e58081 0x7fbeb48f2c76 0x7fbeb48d6810 0x7fbec423f23d 0x7fbec4346d31 0x50a4a5 0x50cc96 0x5095c8 0x50a2fd\n",
      "tcmalloc: large alloc 6155993088 bytes == 0x7fb8db130000 @  0x7fbed59cfb6b 0x7fbed59ef379 0x7fbe79e9674e 0x7fbe79e987b6 0x7fbeb42ecfa2 0x7fbeb45d7bd3 0x7fbeb45af207 0x7fbeb45ca2dc 0x7fbeb45a678a 0x7fbeb45af207 0x7fbeb45ca2dc 0x7fbeb46960dd 0x7fbeb42fe09f 0x7fbeb43006b6 0x7fbeb4300bad 0x7fbeb4300f45 0x7fbeb4007e14 0x7fbeb45d7b09 0x7fbeb3e57ef0 0x7fbeb476791b 0x7fbeb4653b4c 0x7fbeb5ca86b4 0x7fbeb3e57ef0 0x7fbeb476791b 0x7fbeb48a839c 0x7fbec42f603b 0x7fbec42f6806 0x566f73 0x59fd0e 0x4b1eea 0x6196df\n",
      "Processed: 2/34 , 5.88%tcmalloc: large alloc 6165626880 bytes == 0x7fbb13000000 @  0x7fbed59cfb6b 0x7fbed59ef379 0x7fbe79e9674e 0x7fbe79e987b6 0x7fbeb4902d53 0x7fbeb42ed8cf 0x7fbeb4604cac 0x7fbeb45b031b 0x7fbeb45cf135 0x7fbeb45aab4b 0x7fbeb45b031b 0x7fbeb45cf135 0x7fbeb46992be 0x7fbeb5babd6e 0x7fbeb45b031b 0x7fbeb45cf135 0x7fbeb45aab4b 0x7fbeb45b031b 0x7fbeb45cf135 0x7fbeb46992be 0x7fbeb42d9800 0x7fbeb48067ea 0x7fbeb3e58081 0x7fbeb48f2c76 0x7fbeb48d6810 0x7fbec423f23d 0x7fbec4346d31 0x50a4a5 0x50cc96 0x5095c8 0x50a2fd\n",
      "tcmalloc: large alloc 6165626880 bytes == 0x7fbc82800000 @  0x7fbed59cfb6b 0x7fbed59ef379 0x7fbe79e9674e 0x7fbe79e987b6 0x7fbeb42ecfa2 0x7fbeb45d7bd3 0x7fbeb45af207 0x7fbeb45ca2dc 0x7fbeb45a678a 0x7fbeb45af207 0x7fbeb45ca2dc 0x7fbeb46960dd 0x7fbeb42fe09f 0x7fbeb43006b6 0x7fbeb4300bad 0x7fbeb4300f45 0x7fbeb4007e14 0x7fbeb45d7b09 0x7fbeb3e57ef0 0x7fbeb476791b 0x7fbeb4653b4c 0x7fbeb5ca86b4 0x7fbeb3e57ef0 0x7fbeb476791b 0x7fbeb48a839c 0x7fbec42f603b 0x7fbec42f6806 0x566f73 0x59fd0e 0x4b1eea 0x6196df\n",
      "Processed: 3/34 , 8.82%tcmalloc: large alloc 6165626880 bytes == 0x7fbb13000000 @  0x7fbed59cfb6b 0x7fbed59ef379 0x7fbe79e9674e 0x7fbe79e987b6 0x7fbeb4902d53 0x7fbeb42ed8cf 0x7fbeb4604cac 0x7fbeb45b031b 0x7fbeb45cf135 0x7fbeb45aab4b 0x7fbeb45b031b 0x7fbeb45cf135 0x7fbeb46992be 0x7fbeb5babd6e 0x7fbeb45b031b 0x7fbeb45cf135 0x7fbeb45aab4b 0x7fbeb45b031b 0x7fbeb45cf135 0x7fbeb46992be 0x7fbeb42d9800 0x7fbeb48067ea 0x7fbeb3e58081 0x7fbeb48f2c76 0x7fbeb48d6810 0x7fbec423f23d 0x7fbec4346d31 0x50a4a5 0x50cc96 0x5095c8 0x50a2fd\n",
      "tcmalloc: large alloc 6165626880 bytes == 0x7fb76b930000 @  0x7fbed59cfb6b 0x7fbed59ef379 0x7fbe79e9674e 0x7fbe79e987b6 0x7fbeb42ecfa2 0x7fbeb45d7bd3 0x7fbeb45af207 0x7fbeb45ca2dc 0x7fbeb45a678a 0x7fbeb45af207 0x7fbeb45ca2dc 0x7fbeb46960dd 0x7fbeb42fe09f 0x7fbeb43006b6 0x7fbeb4300bad 0x7fbeb4300f45 0x7fbeb4007e14 0x7fbeb45d7b09 0x7fbeb3e57ef0 0x7fbeb476791b 0x7fbeb4653b4c 0x7fbeb5ca86b4 0x7fbeb3e57ef0 0x7fbeb476791b 0x7fbeb48a839c 0x7fbec42f603b 0x7fbec42f6806 0x566f73 0x59fd0e 0x4b1eea 0x6196df\n",
      "Processed: 4/34 , 11.76%tcmalloc: large alloc 6136725504 bytes == 0x7fb8db130000 @  0x7fbed59cfb6b 0x7fbed59ef379 0x7fbe79e9674e 0x7fbe79e987b6 0x7fbeb4902d53 0x7fbeb42ed8cf 0x7fbeb4604cac 0x7fbeb45b031b 0x7fbeb45cf135 0x7fbeb45aab4b 0x7fbeb45b031b 0x7fbeb45cf135 0x7fbeb46992be 0x7fbeb5babd6e 0x7fbeb45b031b 0x7fbeb45cf135 0x7fbeb45aab4b 0x7fbeb45b031b 0x7fbeb45cf135 0x7fbeb46992be 0x7fbeb42d9800 0x7fbeb48067ea 0x7fbeb3e58081 0x7fbeb48f2c76 0x7fbeb48d6810 0x7fbec423f23d 0x7fbec4346d31 0x50a4a5 0x50cc96 0x5095c8 0x50a2fd\n",
      "tcmalloc: large alloc 6136725504 bytes == 0x7fbb13000000 @  0x7fbed59cfb6b 0x7fbed59ef379 0x7fbe79e9674e 0x7fbe79e987b6 0x7fbeb42ecfa2 0x7fbeb45d7bd3 0x7fbeb45af207 0x7fbeb45ca2dc 0x7fbeb45a678a 0x7fbeb45af207 0x7fbeb45ca2dc 0x7fbeb46960dd 0x7fbeb42fe09f 0x7fbeb43006b6 0x7fbeb4300bad 0x7fbeb4300f45 0x7fbeb4007e14 0x7fbeb45d7b09 0x7fbeb3e57ef0 0x7fbeb476791b 0x7fbeb4653b4c 0x7fbeb5ca86b4 0x7fbeb3e57ef0 0x7fbeb476791b 0x7fbeb48a839c 0x7fbec42f603b 0x7fbec42f6806 0x566f73 0x59fd0e 0x4b1eea 0x6196df\n",
      "Processed: 5/34 , 14.71%tcmalloc: large alloc 6175260672 bytes == 0x7fb76b930000 @  0x7fbed59cfb6b 0x7fbed59ef379 0x7fbe79e9674e 0x7fbe79e987b6 0x7fbeb4902d53 0x7fbeb42ed8cf 0x7fbeb4604cac 0x7fbeb45b031b 0x7fbeb45cf135 0x7fbeb45aab4b 0x7fbeb45b031b 0x7fbeb45cf135 0x7fbeb46992be 0x7fbeb5babd6e 0x7fbeb45b031b 0x7fbeb45cf135 0x7fbeb45aab4b 0x7fbeb45b031b 0x7fbeb45cf135 0x7fbeb46992be 0x7fbeb42d9800 0x7fbeb48067ea 0x7fbeb3e58081 0x7fbeb48f2c76 0x7fbeb48d6810 0x7fbec423f23d 0x7fbec4346d31 0x50a4a5 0x50cc96 0x5095c8 0x50a2fd\n",
      "tcmalloc: large alloc 6175260672 bytes == 0x7fb5fb800000 @  0x7fbed59cfb6b 0x7fbed59ef379 0x7fbe79e9674e 0x7fbe79e987b6 0x7fbeb42ecfa2 0x7fbeb45d7bd3 0x7fbeb45af207 0x7fbeb45ca2dc 0x7fbeb45a678a 0x7fbeb45af207 0x7fbeb45ca2dc 0x7fbeb46960dd 0x7fbeb42fe09f 0x7fbeb43006b6 0x7fbeb4300bad 0x7fbeb4300f45 0x7fbeb4007e14 0x7fbeb45d7b09 0x7fbeb3e57ef0 0x7fbeb476791b 0x7fbeb4653b4c 0x7fbeb5ca86b4 0x7fbeb3e57ef0 0x7fbeb476791b 0x7fbeb48a839c 0x7fbec42f603b 0x7fbec42f6806 0x566f73 0x59fd0e 0x4b1eea 0x6196df\n",
      "Processed: 6/34 , 17.65%tcmalloc: large alloc 6165626880 bytes == 0x7fb7c7730000 @  0x7fbed59cfb6b 0x7fbed59ef379 0x7fbe79e9674e 0x7fbe79e987b6 0x7fbeb4902d53 0x7fbeb42ed8cf 0x7fbeb4604cac 0x7fbeb45b031b 0x7fbeb45cf135 0x7fbeb45aab4b 0x7fbeb45b031b 0x7fbeb45cf135 0x7fbeb46992be 0x7fbeb5babd6e 0x7fbeb45b031b 0x7fbeb45cf135 0x7fbeb45aab4b 0x7fbeb45b031b 0x7fbeb45cf135 0x7fbeb46992be 0x7fbeb42d9800 0x7fbeb48067ea 0x7fbeb3e58081 0x7fbeb48f2c76 0x7fbeb48d6810 0x7fbec423f23d 0x7fbec4346d31 0x50a4a5 0x50cc96 0x5095c8 0x50a2fd\n",
      "Processed: 11/11 , 100.0%\n",
      " Fold  2: Epoch  1 in 8095s || Train loss=0.114 | Val loss=0.090 | LR=1.0e-05 | best=1 | improvement=True-15\n",
      "{'Arousal': {'rmse': [0.36236537], 'pcc': [(0.061337714672821564, 1.8551616780429714e-11)], 'ccc': [0.05978981166608859]}, 'Valence': {'rmse': [0.29685184], 'pcc': [(0.1069988626047655, 7.953521147650714e-32)], 'ccc': [0.09708188100820135]}}\n",
      "{'Arousal': {'rmse': [0.2247105], 'pcc': [(0.20835051251328268, 6.46513831419029e-177)], 'ccc': [0.07846431637448001]}, 'Valence': {'rmse': [0.22200048], 'pcc': [(0.5083325488296828, 0.0)], 'ccc': [0.24174807349468425]}}\n",
      "------\n",
      "Saving checkpoint.\n",
      "Checkpoint saved.\n",
      "Processed: 11/11 , 100.0%\n",
      " Fold  2: Epoch  2 in 9026s || Train loss=0.055 | Val loss=0.061 | LR=1.0e-05 | best=2 | improvement=True-15\n",
      "{'Arousal': {'rmse': [0.2902887], 'pcc': [(0.2540578147402263, 1.0677028856017173e-175)], 'ccc': [0.20661761570590428]}, 'Valence': {'rmse': [0.19668283], 'pcc': [(0.3188483259999769, 4.8919711039305376e-281)], 'ccc': [0.31452206055684273]}}\n",
      "{'Arousal': {'rmse': [0.14199705], 'pcc': [(0.15938014032317438, 2.0766507656637868e-103)], 'ccc': [0.1357359720201668]}, 'Valence': {'rmse': [0.13680711], 'pcc': [(0.4727958595190045, 0.0)], 'ccc': [0.29714085525839423]}}\n",
      "------\n",
      "Saving checkpoint.\n",
      "Checkpoint saved.\n",
      "Processed: 11/11 , 100.0%\n",
      " Fold  2: Epoch  3 in 9481s || Train loss=0.049 | Val loss=0.062 | LR=1.0e-05 | best=2 | improvement=False-15\n",
      "{'Arousal': {'rmse': [0.2803512], 'pcc': [(0.33205509689504875, 4.7798277888606936e-306)], 'ccc': [0.2784403597293467]}, 'Valence': {'rmse': [0.19149897], 'pcc': [(0.34658041943982065, 0.0)], 'ccc': [0.342848984548831]}}\n",
      "{'Arousal': {'rmse': [0.17490256], 'pcc': [(0.011014815137651337, 0.13812312735875723)], 'ccc': [0.007397936364724549]}, 'Valence': {'rmse': [0.155191], 'pcc': [(0.38619122774999903, 0.0)], 'ccc': [0.29268589379511833]}}\n",
      "------\n",
      "Saving checkpoint.\n",
      "Checkpoint saved.\n",
      "Processed: 11/11 , 100.0%\n",
      " Fold  2: Epoch  4 in 9770s || Train loss=0.045 | Val loss=0.062 | LR=1.0e-05 | best=2 | improvement=False-15\n",
      "{'Arousal': {'rmse': [0.2711748], 'pcc': [(0.39293690698172146, 0.0)], 'ccc': [0.3340083350035636]}, 'Valence': {'rmse': [0.18094821], 'pcc': [(0.42296732864591263, 0.0)], 'ccc': [0.4189105807243896]}}\n",
      "{'Arousal': {'rmse': [0.15174954], 'pcc': [(0.14429616372867515, 6.491162853799236e-85)], 'ccc': [0.08397676304065997]}, 'Valence': {'rmse': [0.14338344], 'pcc': [(0.47616263070896375, 0.0)], 'ccc': [0.35068467146266985]}}\n",
      "------\n",
      "Saving checkpoint.\n",
      "Checkpoint saved.\n",
      "Processed: 11/11 , 100.0%\n",
      " Fold  2: Epoch  5 in 9959s || Train loss=0.041 | Val loss=0.063 | LR=1.0e-05 | best=2 | improvement=False-15\n",
      "{'Arousal': {'rmse': [0.26239008], 'pcc': [(0.4390008170826728, 0.0)], 'ccc': [0.3695874261708773]}, 'Valence': {'rmse': [0.17842501], 'pcc': [(0.4325526736066596, 0.0)], 'ccc': [0.4271968533376052]}}\n",
      "{'Arousal': {'rmse': [0.16078287], 'pcc': [(0.011998472640773665, 0.10625743679805234)], 'ccc': [0.008454804146893096]}, 'Valence': {'rmse': [0.14983287], 'pcc': [(0.38408538051969754, 0.0)], 'ccc': [0.3580658054001713]}}\n",
      "------\n",
      "Saving checkpoint.\n",
      "Checkpoint saved.\n",
      "Processed: 11/11 , 100.0%\n",
      " Fold  2: Epoch  6 in 10236s || Train loss=0.039 | Val loss=0.064 | LR=1.0e-05 | best=2 | improvement=False-15\n",
      "{'Arousal': {'rmse': [0.25346696], 'pcc': [(0.492843502061154, 0.0)], 'ccc': [0.41831000672622115]}, 'Valence': {'rmse': [0.17120105], 'pcc': [(0.47289947457161996, 0.0)], 'ccc': [0.46555969116988566]}}\n",
      "{'Arousal': {'rmse': [0.16827787], 'pcc': [(0.01333208368975527, 0.07268666292596317)], 'ccc': [0.007713355522255021]}, 'Valence': {'rmse': [0.14830722], 'pcc': [(0.4525054188434461, 0.0)], 'ccc': [0.35466166803192967]}}\n",
      "------\n",
      "Saving checkpoint.\n",
      "Checkpoint saved.\n",
      "Processed: 11/11 , 100.0%\n",
      " Fold  2: Epoch  7 in 10439s || Train loss=0.036 | Val loss=0.064 | LR=1.0e-05 | best=2 | improvement=False-15\n",
      "{'Arousal': {'rmse': [0.24540156], 'pcc': [(0.5344249880551708, 0.0)], 'ccc': [0.45519727339191557]}, 'Valence': {'rmse': [0.16571814], 'pcc': [(0.4901184520336199, 0.0)], 'ccc': [0.4774810390171074]}}\n",
      "{'Arousal': {'rmse': [0.14101201], 'pcc': [(0.05327102882467577, 7.165750807025568e-13)], 'ccc': [0.042151992365732645]}, 'Valence': {'rmse': [0.15003926], 'pcc': [(0.4224306989471789, 0.0)], 'ccc': [0.2914330043255095]}}\n",
      "------\n",
      "Saving checkpoint.\n",
      "Checkpoint saved.\n",
      "Processed: 18/34 , 52.94%"
     ],
     "name": "stdout"
    }
   ]
  }
 ]
}