Adam_RAdam_SGD.ipynb

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  {
   "cell_type": "markdown",
   "metadata": {
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   "source": [
    "## MNIST "
   ]
  },
  {
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   "execution_count": 145,
   "metadata": {
    "colab": {},
    "colab_type": "code",
    "id": "DPRhJ_m34-PB"
   },
   "outputs": [],
   "source": [
    "import os\n",
    "import torch\n",
    "import torch.nn as nn\n",
    "import torchvision.datasets as dset\n",
    "import torchvision.transforms as transforms\n",
    "import torch.nn.functional as F\n",
    "import torch.optim as optim\n",
    "from matplotlib.pyplot import figure\n",
    "from radam import *\n",
    "import time\n",
    "\n",
    "import matplotlib.pyplot as plt"
   ]
  },
  {
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   "execution_count": 146,
   "metadata": {
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   "source": [
    "root = './data'\n",
    "if not os.path.exists(root):\n",
    "    os.mkdir(root)"
   ]
  },
  {
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   "execution_count": 147,
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   "source": [
    "train_set = dset.MNIST(root=root, train=True, transform=transforms.ToTensor(), download=True)\n",
    "test_set = dset.MNIST(root=root, train=False, transform=transforms.ToTensor(), download=True)"
   ]
  },
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   "source": [
    "batch_size = 50\n",
    "total_epoch = 80\n",
    "learning_rate = 0.01\n",
    "use_cuda = torch.cuda.is_available() "
   ]
  },
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   },
   "outputs": [],
   "source": [
    "train_loader = torch.utils.data.DataLoader( \n",
    "                 dataset=train_set,\n",
    "                 batch_size=batch_size,\n",
    "                 shuffle=True)\n",
    "test_loader = torch.utils.data.DataLoader(\n",
    "                dataset=test_set,\n",
    "                batch_size=batch_size,\n",
    "                shuffle=False)\n"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "## Model class\n",
    "Simple classifier composed with 2 convolution layer and 1 linear layer"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 150,
   "metadata": {},
   "outputs": [],
   "source": [
    "class p1CNN(nn.Module):\n",
    "    def __init__(self):\n",
    "        super(p1CNN, self).__init__()\n",
    "        self.c1 = nn.Conv2d(1, 6, kernel_size=3, padding=1)\n",
    "        self.c2 = nn.Conv2d(6, 1, kernel_size=3, padding=1)\n",
    "        self.mp = nn.MaxPool2d(kernel_size=2)\n",
    "        self.li = nn.Linear(7*7, 10)\n",
    "    \n",
    "    def forward(self, x):\n",
    "        x = self.mp(F.relu(self.c1(x)))\n",
    "        x = self.mp(F.relu(self.c2(x)))\n",
    "        x = x.view(-1, 7*7)\n",
    "        x = self.li(x)\n",
    "        return x\n",
    "\n",
    "def weights_init(m):\n",
    "    classname = m.__class__.__name__\n",
    "    for p in model.parameters():\n",
    "        p.data.fill_(1)\n",
    "\n",
    "        "
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "## Model Assign"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 151,
   "metadata": {
    "colab": {},
    "colab_type": "code",
    "id": "GlyL40rSPxDO"
   },
   "outputs": [],
   "source": [
    "model1 = p1CNN().cuda()\n",
    "model2 = p1CNN().cuda()\n",
    "model3 = p1CNN().cuda()\n",
    "model4 = p1CNN().cuda()\n",
    "model5 = p1CNN().cuda()\n",
    "model6 = p1CNN().cuda()\n",
    "model7 = p1CNN().cuda()\n",
    "model8 = p1CNN().cuda()\n",
    "model9 = p1CNN().cuda()\n",
    "tmp = p1CNN().cuda()\n",
    "tmp.load_state_dict(model1.state_dict())\n",
    "model2.load_state_dict(tmp.state_dict())\n",
    "model3.load_state_dict(tmp.state_dict())\n",
    "model4.load_state_dict(tmp.state_dict())\n",
    "model5.load_state_dict(tmp.state_dict())\n",
    "model6.load_state_dict(tmp.state_dict())\n",
    "model7.load_state_dict(tmp.state_dict())\n",
    "model8.load_state_dict(tmp.state_dict())\n",
    "model9.load_state_dict(tmp.state_dict())\n",
    "\n",
    "model_list = [model1, model2, model3, model4, model5, model6, model7, model8, model9]"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "## Optimizer Assign"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 152,
   "metadata": {
    "colab": {},
    "colab_type": "code",
    "id": "LHB6pCrAQJes"
   },
   "outputs": [],
   "source": [
    "optimizer1 = optim.Adam(model1.parameters(), lr=0.03)\n",
    "optimizer2 = optim.Adam(model2.parameters(), lr=0.01)\n",
    "optimizer3 = optim.Adam(model3.parameters(), lr=0.003)\n",
    "optimizer4 = RAdam(model4.parameters(), lr=0.03)\n",
    "optimizer5 = RAdam(model5.parameters(), lr=0.01)\n",
    "optimizer6 = RAdam(model6.parameters(), lr=0.003)\n",
    "optimizer7 = optim.SGD(model7.parameters(), lr=0.03)\n",
    "optimizer8 = optim.SGD(model8.parameters(), lr=0.01)\n",
    "optimizer9 = optim.SGD(model9.parameters(), lr=0.003)\n",
    "criterion = nn.CrossEntropyLoss() # [Question 6] What is 'nn.CrossEntropyLoss' used for?\n",
    "optim_list = [optimizer1, optimizer2, optimizer3, optimizer4, optimizer5, optimizer6, optimizer7, optimizer8, optimizer9] # , "
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "## Train 9 models "
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 153,
   "metadata": {
    "colab": {
     "base_uri": "https://localhost:8080/",
     "height": 1000
    },
    "colab_type": "code",
    "id": "iDz8qyb5SJjX",
    "outputId": "11a2f5d3-1943-4757-a4eb-b72d927dd40a",
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   },
   "outputs": [
    {
     "output_type": "stream",
     "name": "stdout",
     "text": "==>>> epoch: 183, batch index: 200, test loss: 0.215507, acc: 0.933\n==>>> epoch: 183, batch index: 1200, train loss: 0.245251, 1200\n==>>> epoch: 183, batch index: 200, test loss: 0.242526, acc: 0.925\n==>>> epoch: 183, batch index: 1200, train loss: 0.182791, 1200\n==>>> epoch: 183, batch index: 200, test loss: 0.178660, acc: 0.943\n==>>> epoch: 183, batch index: 1200, train loss: 0.213932, 1200\n==>>> epoch: 183, batch index: 200, test loss: 0.205223, acc: 0.937\n==>>> epoch: 183, batch index: 1200, train loss: 0.245663, 1200\n==>>> epoch: 183, batch index: 200, test loss: 0.240289, acc: 0.925\n==>>> epoch: 183, batch index: 1200, train loss: 0.171491, 1200\n==>>> epoch: 183, batch index: 200, test loss: 0.158848, acc: 0.949\n==>>> epoch: 183, batch index: 1200, train loss: 0.319831, 1200\n==>>> epoch: 183, batch index: 200, test loss: 0.316684, acc: 0.904\n==>>> epoch: 183, batch index: 1200, train loss: 0.459189, 1200\n==>>> epoch: 183, batch index: 200, test loss: 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acc: 0.951\n==>>> epoch: 189, batch index: 1200, train loss: 0.317944, 1200\n==>>> epoch: 189, batch index: 200, test loss: 0.312822, acc: 0.907\n==>>> epoch: 189, batch index: 1200, train loss: 0.456090, 1200\n==>>> epoch: 189, batch index: 200, test loss: 0.432683, acc: 0.869\n==>>> epoch: 190, batch index: 1200, train loss: 0.214940, 1200\n==>>> epoch: 190, batch index: 200, test loss: 0.206208, acc: 0.935\n==>>> epoch: 190, batch index: 1200, train loss: 0.218135, 1200\n==>>> epoch: 190, batch index: 200, test loss: 0.222114, acc: 0.932\n==>>> epoch: 190, batch index: 1200, train loss: 0.243982, 1200\n==>>> epoch: 190, batch index: 200, test loss: 0.240541, acc: 0.927\n==>>> epoch: 190, batch index: 1200, train loss: 0.185105, 1200\n==>>> epoch: 190, batch index: 200, test loss: 0.176877, acc: 0.945\n==>>> epoch: 190, batch index: 1200, train loss: 0.213313, 1200\n==>>> epoch: 190, batch index: 200, test loss: 0.203448, acc: 0.937\n==>>> epoch: 190, batch index: 1200, train loss: 0.244393, 1200\n==>>> epoch: 190, batch index: 200, test loss: 0.239480, acc: 0.926\n==>>> epoch: 190, batch index: 1200, train loss: 0.170320, 1200\n==>>> epoch: 190, batch index: 200, test loss: 0.154563, acc: 0.951\n==>>> epoch: 190, batch index: 1200, train loss: 0.317456, 1200\n==>>> epoch: 190, batch index: 200, test loss: 0.311317, acc: 0.906\n==>>> epoch: 190, batch index: 1200, train loss: 0.455570, 1200\n==>>> epoch: 190, batch index: 200, test loss: 0.432137, acc: 0.870\n==>>> epoch: 191, batch index: 1200, train loss: 0.214205, 1200\n==>>> epoch: 191, batch index: 200, test loss: 0.249002, acc: 0.924\n==>>> epoch: 191, batch index: 1200, train loss: 0.218511, 1200\n==>>> epoch: 191, batch index: 200, test loss: 0.219458, acc: 0.935\n==>>> epoch: 191, batch index: 1200, train loss: 0.243836, 1200\n==>>> epoch: 191, batch index: 200, test loss: 0.240046, acc: 0.926\n==>>> epoch: 191, batch index: 1200, train loss: 0.183850, 1200\n==>>> epoch: 191, batch index: 200, test loss: 0.194029, acc: 0.940\n==>>> epoch: 191, batch index: 1200, train loss: 0.213680, 1200\n==>>> epoch: 191, batch index: 200, test loss: 0.206061, acc: 0.936\n==>>> epoch: 191, batch index: 1200, train loss: 0.244611, 1200\n==>>> epoch: 191, batch index: 200, test loss: 0.239442, acc: 0.927\n==>>> epoch: 191, batch index: 1200, train loss: 0.169997, 1200\n==>>> epoch: 191, batch index: 200, test loss: 0.160171, acc: 0.948\n==>>> epoch: 191, batch index: 1200, train loss: 0.317449, 1200\n==>>> epoch: 191, batch index: 200, test loss: 0.313725, acc: 0.907\n==>>> epoch: 191, batch index: 1200, train loss: 0.455060, 1200\n==>>> epoch: 191, batch index: 200, test loss: 0.431879, acc: 0.870\n==>>> epoch: 192, batch index: 1200, train loss: 0.217106, 1200\n==>>> epoch: 192, batch index: 200, test loss: 0.208888, acc: 0.937\n==>>> epoch: 192, batch index: 1200, train loss: 0.218020, 1200\n==>>> epoch: 192, batch index: 200, test loss: 0.216552, acc: 0.934\n==>>> epoch: 192, batch index: 1200, train loss: 0.243331, 1200\n==>>> epoch: 192, batch index: 200, test loss: 0.239237, acc: 0.926\n==>>> epoch: 192, batch index: 1200, train loss: 0.182312, 1200\n==>>> epoch: 192, batch index: 200, test loss: 0.184111, acc: 0.942\n==>>> epoch: 192, batch index: 1200, train loss: 0.213328, 1200\n==>>> epoch: 192, batch index: 200, test loss: 0.206472, acc: 0.935\n==>>> epoch: 192, batch index: 1200, train loss: 0.244233, 1200\n==>>> epoch: 192, batch index: 200, test loss: 0.238844, acc: 0.926\n==>>> epoch: 192, batch index: 1200, train loss: 0.169778, 1200\n==>>> epoch: 192, batch index: 200, test loss: 0.155852, acc: 0.949\n==>>> epoch: 192, batch index: 1200, train loss: 0.316767, 1200\n==>>> epoch: 192, batch index: 200, test loss: 0.311759, acc: 0.907\n==>>> epoch: 192, batch index: 1200, train loss: 0.454577, 1200\n==>>> epoch: 192, batch index: 200, test loss: 0.430957, acc: 0.870\n==>>> epoch: 193, batch index: 1200, train loss: 0.212285, 1200\n==>>> epoch: 193, batch index: 200, test loss: 0.215469, acc: 0.931\n==>>> epoch: 193, batch index: 1200, train loss: 0.218323, 1200\n==>>> epoch: 193, batch index: 200, test loss: 0.215511, acc: 0.934\n==>>> epoch: 193, batch index: 1200, train loss: 0.243344, 1200\n==>>> epoch: 193, batch index: 200, test loss: 0.239674, acc: 0.926\n==>>> epoch: 193, batch index: 1200, train loss: 0.183622, 1200\n==>>> epoch: 193, batch index: 200, test loss: 0.176194, acc: 0.944\n==>>> epoch: 193, batch index: 1200, train loss: 0.214300, 1200\n==>>> epoch: 193, batch index: 200, test loss: 0.202575, acc: 0.936\n==>>> epoch: 193, batch index: 1200, train loss: 0.243965, 1200\n==>>> epoch: 193, batch index: 200, test loss: 0.237773, acc: 0.925\n==>>> epoch: 193, batch index: 1200, train loss: 0.170174, 1200\n==>>> epoch: 193, batch index: 200, test loss: 0.158260, acc: 0.949\n==>>> epoch: 193, batch index: 1200, train loss: 0.316791, 1200\n==>>> epoch: 193, batch index: 200, test loss: 0.311375, acc: 0.907\n==>>> epoch: 193, batch index: 1200, train loss: 0.454124, 1200\n==>>> epoch: 193, batch index: 200, test loss: 0.430626, acc: 0.870\n==>>> epoch: 194, batch index: 1200, train loss: 0.212594, 1200\n==>>> epoch: 194, batch index: 200, test loss: 0.210738, acc: 0.938\n==>>> epoch: 194, batch index: 1200, train loss: 0.217863, 1200\n==>>> epoch: 194, batch index: 200, test loss: 0.217624, acc: 0.934\n==>>> epoch: 194, batch index: 1200, train loss: 0.243209, 1200\n==>>> epoch: 194, batch index: 200, test loss: 0.238483, acc: 0.927\n==>>> epoch: 194, batch index: 1200, train loss: 0.180582, 1200\n==>>> epoch: 194, batch index: 200, test loss: 0.174702, acc: 0.946\n==>>> epoch: 194, batch index: 1200, train loss: 0.214223, 1200\n==>>> epoch: 194, batch index: 200, test loss: 0.207126, acc: 0.935\n==>>> epoch: 194, batch index: 1200, train loss: 0.243779, 1200\n==>>> epoch: 194, batch index: 200, test loss: 0.239685, acc: 0.926\n==>>> epoch: 194, batch index: 1200, train loss: 0.169733, 1200\n==>>> epoch: 194, batch index: 200, test loss: 0.151165, acc: 0.951\n==>>> epoch: 194, batch index: 1200, train loss: 0.316282, 1200\n==>>> epoch: 194, batch index: 200, test loss: 0.311092, acc: 0.907\n==>>> epoch: 194, batch index: 1200, train loss: 0.453586, 1200\n==>>> epoch: 194, batch index: 200, test loss: 0.430371, acc: 0.870\n==>>> epoch: 195, batch index: 1200, train loss: 0.212717, 1200\n==>>> epoch: 195, batch index: 200, test loss: 0.219272, acc: 0.934\n==>>> epoch: 195, batch index: 1200, train loss: 0.218026, 1200\n==>>> epoch: 195, batch index: 200, test loss: 0.220520, acc: 0.934\n==>>> epoch: 195, batch index: 1200, train loss: 0.243061, 1200\n==>>> epoch: 195, batch index: 200, test loss: 0.240997, acc: 0.926\n==>>> epoch: 195, batch index: 1200, train loss: 0.184583, 1200\n==>>> epoch: 195, batch index: 200, test loss: 0.172021, acc: 0.947\n==>>> epoch: 195, batch index: 1200, train loss: 0.214431, 1200\n==>>> epoch: 195, batch index: 200, test loss: 0.204803, acc: 0.937\n==>>> epoch: 195, batch index: 1200, train loss: 0.243645, 1200\n==>>> epoch: 195, batch index: 200, test loss: 0.238546, acc: 0.926\n==>>> epoch: 195, batch index: 1200, train loss: 0.169240, 1200\n==>>> epoch: 195, batch index: 200, test loss: 0.155072, acc: 0.950\n==>>> epoch: 195, batch index: 1200, train loss: 0.315978, 1200\n==>>> epoch: 195, batch index: 200, test loss: 0.309344, acc: 0.907\n==>>> epoch: 195, batch index: 1200, train loss: 0.453138, 1200\n==>>> epoch: 195, batch index: 200, test loss: 0.429824, acc: 0.871\n==>>> epoch: 196, batch index: 1200, train loss: 0.210450, 1200\n==>>> epoch: 196, batch index: 200, test loss: 0.200142, acc: 0.937\n==>>> epoch: 196, batch index: 1200, train loss: 0.217528, 1200\n==>>> epoch: 196, batch index: 200, test loss: 0.219674, acc: 0.933\n==>>> epoch: 196, batch index: 1200, train loss: 0.243071, 1200\n==>>> epoch: 196, batch index: 200, test loss: 0.240219, acc: 0.927\n==>>> epoch: 196, batch index: 1200, train loss: 0.181529, 1200\n==>>> epoch: 196, batch index: 200, test loss: 0.179674, acc: 0.944\n==>>> epoch: 196, batch index: 1200, train loss: 0.213851, 1200\n==>>> epoch: 196, batch index: 200, test loss: 0.204398, acc: 0.937\n==>>> epoch: 196, batch index: 1200, train loss: 0.243293, 1200\n==>>> epoch: 196, batch index: 200, test loss: 0.237830, acc: 0.926\n==>>> epoch: 196, batch index: 1200, train loss: 0.169067, 1200\n==>>> epoch: 196, batch index: 200, test loss: 0.154085, acc: 0.949\n==>>> epoch: 196, batch index: 1200, train loss: 0.315549, 1200\n==>>> epoch: 196, batch index: 200, test loss: 0.311347, acc: 0.906\n==>>> epoch: 196, batch index: 1200, train loss: 0.452696, 1200\n==>>> epoch: 196, batch index: 200, test loss: 0.429420, acc: 0.871\n==>>> epoch: 197, batch index: 1200, train loss: 0.213332, 1200\n==>>> epoch: 197, batch index: 200, test loss: 0.201055, acc: 0.936\n==>>> epoch: 197, batch index: 1200, train loss: 0.218664, 1200\n==>>> epoch: 197, batch index: 200, test loss: 0.221503, acc: 0.932\n==>>> epoch: 197, batch index: 1200, train loss: 0.242835, 1200\n==>>> epoch: 197, batch index: 200, test loss: 0.238272, acc: 0.927\n==>>> epoch: 197, batch index: 1200, train loss: 0.184128, 1200\n==>>> epoch: 197, batch index: 200, test loss: 0.173197, acc: 0.946\n==>>> epoch: 197, batch index: 1200, train loss: 0.213927, 1200\n==>>> epoch: 197, batch index: 200, test loss: 0.210183, acc: 0.932\n==>>> epoch: 197, batch index: 1200, train loss: 0.243285, 1200\n==>>> epoch: 197, batch index: 200, test loss: 0.238397, acc: 0.926\n==>>> epoch: 197, batch index: 1200, train loss: 0.169054, 1200\n==>>> epoch: 197, batch index: 200, test loss: 0.153706, acc: 0.951\n==>>> epoch: 197, batch index: 1200, train loss: 0.315247, 1200\n==>>> epoch: 197, batch index: 200, test loss: 0.313285, acc: 0.906\n==>>> epoch: 197, batch index: 1200, train loss: 0.452235, 1200\n==>>> epoch: 197, batch index: 200, test loss: 0.428863, acc: 0.870\n==>>> epoch: 198, batch index: 1200, train loss: 0.210980, 1200\n==>>> epoch: 198, batch index: 200, test loss: 0.252621, acc: 0.919\n==>>> epoch: 198, batch index: 1200, train loss: 0.218490, 1200\n==>>> epoch: 198, batch index: 200, test loss: 0.215908, acc: 0.934\n==>>> epoch: 198, batch index: 1200, train loss: 0.242519, 1200\n==>>> epoch: 198, batch index: 200, test loss: 0.239581, acc: 0.926\n==>>> epoch: 198, batch index: 1200, train loss: 0.180993, 1200\n==>>> epoch: 198, batch index: 200, test loss: 0.178471, acc: 0.942\n==>>> epoch: 198, batch index: 1200, train loss: 0.213120, 1200\n==>>> epoch: 198, batch index: 200, test loss: 0.214438, acc: 0.934\n==>>> epoch: 198, batch index: 1200, train loss: 0.243193, 1200\n==>>> epoch: 198, batch index: 200, test loss: 0.238284, acc: 0.927\n==>>> epoch: 198, batch index: 1200, train loss: 0.169010, 1200\n==>>> epoch: 198, batch index: 200, test loss: 0.156350, acc: 0.950\n==>>> epoch: 198, batch index: 1200, train loss: 0.314961, 1200\n==>>> epoch: 198, batch index: 200, test loss: 0.309087, acc: 0.907\n==>>> epoch: 198, batch index: 1200, train loss: 0.451790, 1200\n==>>> epoch: 198, batch index: 200, test loss: 0.428525, acc: 0.870\n==>>> epoch: 199, batch index: 1200, train loss: 0.210968, 1200\n==>>> epoch: 199, batch index: 200, test loss: 0.201902, acc: 0.934\n==>>> epoch: 199, batch index: 1200, train loss: 0.217694, 1200\n==>>> epoch: 199, batch index: 200, test loss: 0.218225, acc: 0.933\n==>>> epoch: 199, batch index: 1200, train loss: 0.242714, 1200\n==>>> epoch: 199, batch index: 200, test loss: 0.239306, acc: 0.926\n==>>> epoch: 199, batch index: 1200, train loss: 0.184556, 1200\n==>>> epoch: 199, batch index: 200, test loss: 0.168247, acc: 0.947\n==>>> epoch: 199, batch index: 1200, train loss: 0.212810, 1200\n==>>> epoch: 199, batch index: 200, test loss: 0.212372, acc: 0.934\n==>>> epoch: 199, batch index: 1200, train loss: 0.243008, 1200\n==>>> epoch: 199, batch index: 200, test loss: 0.238927, acc: 0.927\n==>>> epoch: 199, batch index: 1200, train loss: 0.168842, 1200\n==>>> epoch: 199, batch index: 200, test loss: 0.156296, acc: 0.951\n==>>> epoch: 199, batch index: 1200, train loss: 0.314889, 1200\n==>>> epoch: 199, batch index: 200, test loss: 0.309423, acc: 0.907\n==>>> epoch: 199, batch index: 1200, train loss: 0.451329, 1200\n==>>> epoch: 199, batch index: 200, test loss: 0.428077, acc: 0.870\n"
    }
   ],
   "source": [
    "train_loss_list, test_acc_list = [], []\n",
    "for i in range(9):\n",
    "    tmp1, tmp2 = [], []\n",
    "    for j in range(80):\n",
    "        tmp1.append(0)\n",
    "        tmp2.append(0)\n",
    "    train_loss_list.append(tmp1)\n",
    "    test_acc_list.append(tmp2)\n",
    "\n",
    "for epoch in range(total_epoch):\n",
    "    # trainning\n",
    "    for i, (model, optim) in enumerate(zip(model_list, optim_list)):\n",
    "        if epoch == 0 and i == 0:\n",
    "            start = time.time()\n",
    "\n",
    "        total_loss = 0\n",
    "        total_batch = 0\n",
    "        for batch_idx, (x, target) in enumerate(train_loader):\n",
    "            if use_cuda:\n",
    "                x, target = x.cuda(), target.cuda()\n",
    "            \n",
    "            \n",
    "                model.train()\n",
    "                optim.zero_grad()\n",
    "\n",
    "                out = model(x)\n",
    "                loss = criterion(out, target)\n",
    "                total_loss += loss.item()\n",
    "                loss.backward()\n",
    "                optim.step()\n",
    "            total_batch += 1\n",
    "        train_loss_list[i][epoch] = total_loss / total_batch\n",
    "        print ('==>>> epoch: {}, batch index: {}, train loss: {:.6f}, {}'\n",
    "                .format(epoch, batch_idx+1, total_loss / total_batch, total_batch))\n",
    "    \n",
    "    # testing\n",
    "        total_loss = 0\n",
    "        total_batch = 0\n",
    "        correct_cnt = 0\n",
    "        total_cnt = 0\n",
    "    \n",
    "        for batch_idx, (x, target) in enumerate(test_loader):\n",
    "            model.eval()\n",
    "            if use_cuda:\n",
    "                x, target = x.cuda(), target.cuda()\n",
    "                \n",
    "            out = model(x)\n",
    "            loss = criterion(out, target)\n",
    "            _, pred_label = torch.max(out.data, 1)\n",
    "            total_cnt += x.data.size()[0]\n",
    "            correct_cnt += (pred_label == target.data).sum().item()\n",
    "            \n",
    "            total_loss += loss.item()\n",
    "            total_batch += 1\n",
    "        test_acc_list[i][epoch] = correct_cnt / total_cnt\n",
    "        print ('==>>> epoch: {}, batch index: {}, test loss: {:.6f}, acc: {:.3f}'\n",
    "                .format(epoch, batch_idx+1, total_loss / total_batch, correct_cnt * 1.0 / total_cnt))\n",
    "        if epoch == 0 and i == 0:\n",
    "            end = time.time()\n",
    "            estimate = end - start\n",
    "            total = estimate * 9 * total_epoch\n",
    "            print(f'{total // 60} minute and {total % 60} sec left')\n"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "## Plot result, using subplot"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 164,
   "metadata": {},
   "outputs": [
    {
     "output_type": "execute_result",
     "data": {
      "text/plain": "Text(0.5, 0.98, 'Comparison of Adam, RAdam, SGD by train loss and test acc per epoch')"
     },
     "metadata": {},
     "execution_count": 164
    },
    {
     "output_type": "display_data",
     "data": {
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     },
     "metadata": {}
    }
   ],
   "source": [
    "figure(num=None, figsize=(16, 6), dpi=80, facecolor='w', edgecolor='k')\n",
    "plt.subplot(231)\n",
    "for i in range(3):\n",
    "    plt.plot(train_loss_list[i])\n",
    "\n",
    "plt.legend(labels=('Adam 0.03', 'Adam 0.01', 'Adam 0.003'))\n",
    "plt.xlabel('epoch')\n",
    "plt.ylabel('Loss')\n",
    "plt.grid()\n",
    "plt.ylim(0, 1)\n",
    "plt.subplot(234)\n",
    "for i in range(3):\n",
    "    plt.plot(test_acc_list[i])\n",
    "\n",
    "plt.legend(labels=('Adam 0.03', 'Adam 0.01', 'Adam 0.003'))\n",
    "plt.xlabel('epoch')\n",
    "plt.ylabel('Acc')\n",
    "plt.grid()\n",
    "plt.ylim(0.5, 1)\n",
    "plt.subplot(232)\n",
    "for i in range(3):\n",
    "    plt.plot(train_loss_list[i+3])\n",
    "\n",
    "plt.legend(labels=('RAdam 0.03', 'RAdam 0.01', 'RAdam 0.003'))\n",
    "plt.xlabel('epoch')\n",
    "plt.ylabel('Loss')\n",
    "plt.grid()\n",
    "plt.ylim(0, 1)\n",
    "plt.subplot(235)\n",
    "for i in range(3):\n",
    "    plt.plot(test_acc_list[i+3])\n",
    "\n",
    "plt.legend(labels=('RAdam 0.03', 'RAdam 0.01', 'RAdam 0.003'))\n",
    "plt.xlabel('epoch')\n",
    "plt.ylabel('Acc')\n",
    "plt.grid()\n",
    "plt.ylim(0.5, 1)\n",
    "plt.subplot(233)\n",
    "for i in range(3):\n",
    "    plt.plot(train_loss_list[i+6])\n",
    "\n",
    "plt.legend(labels=('SGD 0.03', 'SGD 0.01', 'SGD 0.003'))\n",
    "plt.xlabel('epoch')\n",
    "plt.ylabel('Loss')\n",
    "plt.grid()\n",
    "plt.ylim(0, 1)\n",
    "plt.subplot(236)\n",
    "for i in range(3):\n",
    "    plt.plot(test_acc_list[i+6])\n",
    "\n",
    "plt.legend(labels=('SGD 0.03', 'SGD 0.01', 'SGD 0.003'))\n",
    "plt.xlabel('epoch')\n",
    "plt.ylabel('Acc')\n",
    "plt.grid()\n",
    "plt.ylim(0.5, 1)\n",
    "\n",
    "plt.suptitle('Comparison of Adam, RAdam, SGD by train loss and test acc per epoch')"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "## Plot only Adam"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 160,
   "metadata": {},
   "outputs": [
    {
     "output_type": "execute_result",
     "data": {
      "text/plain": "<matplotlib.legend.Legend at 0x155dbe577c8>"
     },
     "metadata": {},
     "execution_count": 160
    },
    {
     "output_type": "display_data",
     "data": {
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     },
     "metadata": {}
    }
   ],
   "source": [
    "figure(num=None, figsize=(14, 6), dpi=80, facecolor='w', edgecolor='k')\n",
    "plt.subplot(121)\n",
    "for i in range(3):\n",
    "    plt.plot(train_loss_list[i])\n",
    "\n",
    "plt.legend(labels=('Adam 0.1', 'Adam 0.01', 'Adam 0.001'))\n",
    "\n",
    "plt.subplot(122)\n",
    "for i in range(3):\n",
    "    plt.plot(test_acc_list[i])\n",
    "\n",
    "plt.legend(labels=('Adam 0.1', 'Adam 0.01', 'Adam 0.001'))\n",
    "\n"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "## Plot only RAdam"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 156,
   "metadata": {},
   "outputs": [
    {
     "output_type": "execute_result",
     "data": {
      "text/plain": "<matplotlib.legend.Legend at 0x155e3d1c908>"
     },
     "metadata": {},
     "execution_count": 156
    },
    {
     "output_type": "display_data",
     "data": {
      "text/plain": "<Figure size 1120x480 with 2 Axes>",
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\n"
     },
     "metadata": {}
    }
   ],
   "source": [
    "figure(num=None, figsize=(14, 6), dpi=80, facecolor='w', edgecolor='k')\n",
    "plt.subplot(121)\n",
    "for i in range(3):\n",
    "    plt.plot(train_loss_list[i+3])\n",
    "\n",
    "plt.legend(labels=('Radam 0.1', 'Radam 0.01', 'Radam 0.001'))\n",
    "\n",
    "plt.subplot(122)\n",
    "for i in range(3):\n",
    "    plt.plot(test_acc_list[i+3])\n",
    "\n",
    "plt.legend(labels=('Radam 0.1', 'Radam 0.01', 'Radam 0.001'))\n",
    "\n"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "## Plot only SGD"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 157,
   "metadata": {},
   "outputs": [
    {
     "output_type": "execute_result",
     "data": {
      "text/plain": "<matplotlib.legend.Legend at 0x155da26ab48>"
     },
     "metadata": {},
     "execution_count": 157
    },
    {
     "output_type": "display_data",
     "data": {
      "text/plain": "<Figure size 1120x480 with 2 Axes>",
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\n"
     },
     "metadata": {}
    }
   ],
   "source": [
    "figure(num=None, figsize=(14, 6), dpi=80, facecolor='w', edgecolor='k')\n",
    "plt.subplot(121)\n",
    "for i in range(3):\n",
    "    plt.plot(train_loss_list[i+6])\n",
    "\n",
    "plt.legend(labels=('SGD 0.1', 'SGD 0.01', 'SGD 0.001'))\n",
    "\n",
    "plt.subplot(122)\n",
    "for i in range(3):\n",
    "    plt.plot(test_acc_list[i+6])\n",
    "\n",
    "plt.legend(labels=('SGD 0.1', 'SGD 0.01', 'SGD 0.001'))"
   ]
  }
 ],
 "metadata": {
  "accelerator": "GPU",
  "colab": {
   "name": "2. 딥러닝개론.ipynb",
   "provenance": []
  },
  "kernelspec": {
   "display_name": "Python 3",
   "language": "python",
   "name": "python3"
  },
  "language_info": {
   "codemirror_mode": {
    "name": "ipython",
    "version": 3
   },
   "file_extension": ".py",
   "mimetype": "text/x-python",
   "name": "python",
   "nbconvert_exporter": "python",
   "pygments_lexer": "ipython3",
   "version": "3.7.4-final"
  }
 },
 "nbformat": 4,
 "nbformat_minor": 4
}