{
 "cells": [
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "### Downloads and resizes imagenet"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "1. Create spot instance\n",
    "2. Mount EFS\n",
    "3. Download imagenet from kaggle and untar\n",
    "4. Resize images to 80, 160, 320, 375"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 1,
   "metadata": {
    "collapsed": true
   },
   "outputs": [],
   "source": [
    "%reload_ext autoreload\n",
    "%autoreload 2\n",
    "%matplotlib inline"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 2,
   "metadata": {
    "collapsed": true
   },
   "outputs": [],
   "source": [
    "from aws_setup import *"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "#### Define parameters"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 3,
   "metadata": {
    "collapsed": true
   },
   "outputs": [],
   "source": [
    "vpc_name='fast-ai'"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "#### Get Existing VPC by tag name"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 4,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "ec2.Vpc(id='vpc-6e6b2a17')"
      ]
     },
     "execution_count": 4,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "vpc = get_vpc(vpc_name); vpc"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "#### Create EFS (if you haven't already)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 6,
   "metadata": {},
   "outputs": [],
   "source": [
    "efs_tag = f'{vpc_name}-efs'"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "metadata": {
    "collapsed": true
   },
   "outputs": [],
   "source": [
    "efs = create_efs(efs_tag, vpc, performance_mode='maxIO')"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "#### Request Spot instance"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 7,
   "metadata": {
    "collapsed": true
   },
   "outputs": [],
   "source": [
    "instance_name = f'{vpc_name}-instance'\n",
    "# Recommend a high compute instance as we need to do multi-threaded resizing later on\n",
    "instance_type = 'c5.4xlarge'"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 8,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "'0.301400'"
      ]
     },
     "execution_count": 8,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "spot_price = get_spot_prices()[instance_type]\n",
    "bid_price = \"%.4f\" % (float(spot_price)*3)\n",
    "print(f'Spot price: {spot_price}, Bid price: {bid_price}')"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 9,
   "metadata": {
    "collapsed": true
   },
   "outputs": [],
   "source": [
    "launch_specs = LaunchSpecs(vpc, instance_type=instance_type).build()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 10,
   "metadata": {
    "collapsed": true
   },
   "outputs": [],
   "source": [
    "launch_specs['BlockDeviceMappings'][0]['Ebs']['VolumeSize'] = 1000"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 11,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "{'BlockDeviceMappings': [{'DeviceName': '/dev/sda1',\n",
       "   'Ebs': {'DeleteOnTermination': True,\n",
       "    'VolumeSize': 1000,\n",
       "    'VolumeType': 'gp2'}}],\n",
       " 'ImageId': 'ami-8c4288f4',\n",
       " 'InstanceType': 'c5.4xlarge',\n",
       " 'KeyName': 'aws-key-fast-ai',\n",
       " 'NetworkInterfaces': [{'AssociatePublicIpAddress': True,\n",
       "   'DeviceIndex': 0,\n",
       "   'Groups': ['sg-f60fca88'],\n",
       "   'SubnetId': 'subnet-f056ff89'}]}"
      ]
     },
     "execution_count": 11,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "launch_specs"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 12,
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "Waiting on spot fullfillment...\n",
      "Fullfillment completed. InstanceId: i-0cabe3a45ec1ef32c\n",
      "Rebooting...\n",
      "Completed. SSH:  ssh -i ~/.ssh/aws-key-fast-ai.pem ubuntu@54.202.209.226\n"
     ]
    },
    {
     "data": {
      "text/plain": [
       "ec2.Instance(id='i-0cabe3a45ec1ef32c')"
      ]
     },
     "execution_count": 12,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "instance = create_spot_instance(instance_name, launch_specs, spot_price=bid_price); instance"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "metadata": {
    "collapsed": true
   },
   "outputs": [],
   "source": [
    "# instance = get_instance(instance_name); instance\n",
    "get_ssh_command(instance)"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "### SSH"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 35,
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "Connecting to SSH...\n",
      "Connected!\n"
     ]
    }
   ],
   "source": [
    "client = connect_to_instance(instance)"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "#### Mount EFS"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 16,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "'fs-0ea233a7.efs.us-west-2.amazonaws.com'"
      ]
     },
     "execution_count": 16,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "efs_addr = get_efs_address('fast-ai-efs'); efs_addr"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 17,
   "metadata": {},
   "outputs": [],
   "source": [
    "_ = run_command(client, 'mkdir ~/efs_mount')"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 18,
   "metadata": {
    "collapsed": true
   },
   "outputs": [],
   "source": [
    "efs_mount_cmd = f'sudo mount -t nfs -o nfsvers=4.1,rsize=1048576,wsize=1048576,hard,timeo=600,retrans=2 {efs_addr}:/ ~/efs_mount'\n",
    "_ = run_command(client, efs_mount_cmd)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 34,
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "run_command returned: \n",
      "efs_saved.txt\r\n",
      "\n"
     ]
    }
   ],
   "source": [
    "_ = run_command(client, 'ls efs_mount') # no reformatting"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {
    "collapsed": true
   },
   "source": [
    "## Tmux"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 37,
   "metadata": {},
   "outputs": [],
   "source": [
    "tsess = TmuxSession(client, 'sess')"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "### Download dataset from kaggle"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 19,
   "metadata": {},
   "outputs": [],
   "source": [
    "_ = run_command(client, 'mkdir ~/.kaggle')"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 21,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "('', '')"
      ]
     },
     "execution_count": 21,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "kaggle_file = Path.home()/'.kaggle/kaggle.json'\n",
    "upload_file(client, str(kaggle_file), '.kaggle/kaggle.json')"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 32,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "('', '')"
      ]
     },
     "execution_count": 32,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "download_kaggle_file = Path.cwd()/'upload_scripts/download_kaggle_imagenet.sh'\n",
    "upload_file(client, str(download_kaggle_file), 'download_kaggle_imagenet.sh')"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 33,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "('', '')"
      ]
     },
     "execution_count": 33,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "tsess.run_cmd('bash download_kaggle_imagenet.sh')"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "### Upload image resize"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 40,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "('', '')"
      ]
     },
     "execution_count": 40,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "# imagenet_formatting.sh uses this for multithreaded resizing\n",
    "# resize_imags.py methods are taken from fast.ai dataset.py\n",
    "upload_path = Path.cwd()/'upload_scripts/resize_images.py'\n",
    "upload_file(client, str(upload_path), 'resize_images.py')"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 47,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "('', '')"
      ]
     },
     "execution_count": 47,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "# creates sizes 80, 160, 320, 375 and stores files in EFS\n",
    "upload_path = Path.cwd()/'upload_scripts/imagenet_formatting.sh'\n",
    "upload_file(client, str(upload_path), 'imagenet_formatting.sh')"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "metadata": {
    "collapsed": true
   },
   "outputs": [],
   "source": [
    "tsess.run_cmd('bash imagenet_formatting.sh')"
   ]
  }
 ],
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