FEDERATED_LSTM_BATCH_A_wordlist_included.ipynb

{
  "nbformat": 4,
  "nbformat_minor": 0,
  "metadata": {
    "colab": {
      "name": "FEDERATED_LSTM_BATCH_A_MIXED.ipynb",
      "provenance": [],
      "collapsed_sections": []
    },
    "kernelspec": {
      "name": "python3",
      "display_name": "Python 3"
    }
  },
  "cells": [
    {
      "cell_type": "code",
      "metadata": {
        "id": "yI_onVYcTGWV"
      },
      "source": [
        "!pip install syft==0.2.4"
      ],
      "execution_count": null,
      "outputs": []
    },
    {
      "cell_type": "code",
      "metadata": {
        "id": "ttnV32xq5esC",
        "outputId": "6c0d59d3-66df-4d68-e885-b2a9f9006245",
        "colab": {
          "base_uri": "https://localhost:8080/",
          "height": 1000
        }
      },
      "source": [
        "%%time\n",
        "\n",
        "import torch\n",
        "import torch.nn as nn\n",
        "import torch.nn.functional as F\n",
        "import torch.optim as optim\n",
        "import logging\n",
        "import argparse\n",
        "import sys\n",
        "import pandas as pd\n",
        "\n",
        "import syft as sy\n",
        "from syft.workers.websocket_client import WebsocketClientWorker\n",
        "from syft.frameworks.torch.fl import utils\n",
        "from syft.frameworks.torch.nn import LSTM\n",
        "from syft.federated.floptimizer import Optims\n",
        "\n",
        "import pickle\n",
        "import numpy as np\n",
        "import tensorflow as tf\n",
        "from tensorflow.keras import layers, callbacks\n",
        "from sklearn.model_selection import train_test_split\n",
        "\n",
        "import warnings\n",
        "warnings.filterwarnings(\"ignore\")\n",
        "\n",
        "logger = logging.getLogger(__name__)\n",
        "\n",
        "\n",
        "class Arguments():\n",
        "    def __init__(self):\n",
        "        self.batch_size = 64\n",
        "        self.test_batch_size = 1000\n",
        "        self.epochs = 50\n",
        "        self.federate_after_n_batches = 100\n",
        "        self.lr = 0.001\n",
        "        self.cuda = False\n",
        "        self.seed = 1\n",
        "\n",
        "\n",
        "args = Arguments()\n",
        "\n",
        "class Net(nn.Module):\n",
        "    def __init__(self):\n",
        "        super(Net, self).__init__()\n",
        "        self.word_embeddings = nn.Embedding(39, 128)\n",
        "        self.lstm = LSTM(128, 128, batch_first=True)\n",
        "        self.dropout = nn.Dropout(0.5)\n",
        "        self.linear1 = nn.Linear(47*128, 100)\n",
        "        self.linear2 = nn.Linear(100, 1)\n",
        "\n",
        "\n",
        "    def init_hidden(self):\n",
        "        return (torch.zeros(self.num_layers, self.batch_size, self.hidden_dim),\n",
        "                torch.zeros(self.num_layers, self.batch_size, self.hidden_dim))\n",
        "\n",
        "\n",
        "    def forward(self, x):\n",
        "        embedded = self.word_embeddings(x)\n",
        "        x, (ht, ct) = self.lstm(embedded)\n",
        "        x = x.contiguous().view(-1, 47*128)\n",
        "        x = F.relu(x)\n",
        "        x = self.dropout(x)\n",
        "        x = F.relu(self.linear1(x))\n",
        "        x = F.sigmoid(self.linear2(x))\n",
        "        return x\n",
        "\n",
        "\n",
        "def test_worker(model, device, test_loader, worker):\n",
        "    model.eval()\n",
        "    test_loss = 0\n",
        "    correct = 0\n",
        "    with torch.no_grad():\n",
        "        for data, target in test_loader:\n",
        "            data, target = data.to(device), target.to(device)\n",
        "            output = model(data)\n",
        "            test_loss += F.binary_cross_entropy(output.squeeze(), target.float(), reduction=\"sum\").item()  # sum up batch loss\n",
        "            pred = torch.round(output.squeeze())\n",
        "            correct += pred.eq(target.float().view_as(pred)).sum().item()\n",
        "\n",
        "    test_loss /= len(test_loader.dataset)\n",
        "\n",
        "    logger.debug(\"\\n\")\n",
        "    accuracy = 100.0 * correct / len(test_loader.dataset)\n",
        "    logger.info(\n",
        "        \"Test on {}'s dataset: Average loss: {:.4f}, Accuracy: {}/{} ({:.2f}%)\\n\".format(\n",
        "            worker.id, test_loss, correct, len(test_loader.dataset), accuracy\n",
        "        )\n",
        "    )\n",
        "\n",
        "def train_on_batches(worker, batches, model_in, device, lr):\n",
        "    model = model_in.copy()\n",
        "    optimizer = optim.Adam(model.parameters(), lr = 0.001)\n",
        "    model.train()\n",
        "    model.send(worker)\n",
        "    loss_local = False\n",
        "\n",
        "    for batch_idx, (data, target) in enumerate(batches):\n",
        "        loss_local = False\n",
        "        data, target = data.to(device), target.to(device)\n",
        "        optimizer.zero_grad()\n",
        "        output = model(data)\n",
        "        loss = F.binary_cross_entropy(output.squeeze(), target.float())\n",
        "        loss.backward()\n",
        "        optimizer.step()\n",
        "        if batch_idx % int(len(batches)/2) == 0:\n",
        "            loss = loss.get()\n",
        "            loss_local = True\n",
        "            logger.debug(\n",
        "                \"Train Worker {}: ({:.0f}%)]\\tLoss: {:.6f}\".format(\n",
        "                    worker.id,\n",
        "                    100.0 * batch_idx / len(batches),\n",
        "                    loss.item(),\n",
        "                )\n",
        "            )\n",
        "\n",
        "    if not loss_local:\n",
        "        loss = loss.get()\n",
        "    model.get()\n",
        "    return model, loss\n",
        "\n",
        "\n",
        "def get_next_batches(fdataloader: sy.FederatedDataLoader, nr_batches: int):\n",
        "    batches = {}\n",
        "    for worker_id in fdataloader.workers:\n",
        "        worker = fdataloader.federated_dataset.datasets[worker_id].location\n",
        "        batches[worker] = []\n",
        "    try:\n",
        "        for i in range(nr_batches):\n",
        "            next_batches = next(fdataloader)\n",
        "            for worker in next_batches:\n",
        "                batches[worker].append(next_batches[worker])\n",
        "    except StopIteration:\n",
        "        pass\n",
        "    return batches\n",
        "\n",
        "\n",
        "def train(\n",
        "    model, device, federated_train_loader, lr, federate_after_n_batches, epoch, test_loader, abort_after_one=False\n",
        "):\n",
        "    model.train()\n",
        "\n",
        "    nr_batches = federate_after_n_batches\n",
        "\n",
        "    models = {}\n",
        "    loss_values = {}\n",
        "\n",
        "    iter(federated_train_loader)  # initialize iterators\n",
        "    batches = get_next_batches(federated_train_loader, nr_batches)\n",
        "    counter = 0\n",
        "\n",
        "    while True:\n",
        "        if counter==0:\n",
        "            logger.debug(f\"Starting training epoch {epoch}\")\n",
        "        data_for_all_workers = True\n",
        "        load = []\n",
        "        for worker in batches:\n",
        "            if worker not in load:\n",
        "               load.append(worker)\n",
        "            curr_batches = batches[worker]\n",
        "            if curr_batches:\n",
        "                models[worker], loss_values[worker] = train_on_batches(\n",
        "                    worker, curr_batches, model, device, lr\n",
        "                )\n",
        "            else:\n",
        "                data_for_all_workers = False\n",
        "\n",
        "        counter += nr_batches\n",
        "        if not data_for_all_workers:\n",
        "            for worker in load:\n",
        "                test_worker(models[worker], device, test_loader, worker)\n",
        "            break\n",
        "\n",
        "        if counter % 200==0:\n",
        "            model = utils.federated_avg(models)\n",
        "            logger.debug(f\"Federated-averaging after trained on given batches\")\n",
        "\n",
        "        batches = get_next_batches(federated_train_loader, nr_batches)\n",
        "        if abort_after_one:\n",
        "            break\n",
        "    return model\n",
        "\n",
        "\n",
        "def test(args, model, device, test_loader, max_accuracy, epochs_no_improve):\n",
        "    model.eval()\n",
        "    test_loss = 0\n",
        "    correct = 0\n",
        "    pred_list = []\n",
        "    test_list = []\n",
        "    with torch.no_grad():\n",
        "        for data, target in test_loader:\n",
        "            data, target = data.to(device), target.to(device)\n",
        "            output = model(data)\n",
        "            test_loss += F.binary_cross_entropy(output.squeeze(), target.float(), reduction='sum').item() # sum up batch loss\n",
        "            pred = torch.round(output.squeeze())\n",
        "            correct += pred.eq(target.float().view_as(pred)).sum().item()\n",
        "            pred_list.append(pred.numpy())\n",
        "            test_list.append(target.float().view_as(pred).numpy())\n",
        "\n",
        "    test_loss /= len(test_loader.dataset)\n",
        "\n",
        "    print('\\nTest set: Average loss: {:.4f}, Accuracy: {}/{} ({:.2f}%)\\n'.format(\n",
        "        test_loss, correct, len(test_loader.dataset),\n",
        "        100. * correct / len(test_loader.dataset)))\n",
        "    \n",
        "    accuracy = 100. * correct / len(test_loader.dataset)\n",
        "\n",
        "    if accuracy > max_accuracy:\n",
        "        epochs_no_improve = 0\n",
        "        max_accuracy = accuracy\n",
        "    else:\n",
        "        epochs_no_improve += 1\n",
        "\n",
        "    return pred_list, test_list, max_accuracy, epochs_no_improve, accuracy\n",
        "\n",
        "\n",
        "DATA_FILE = '/content/drive/My Drive/Colab Notebooks/MIXED_CORRECT/traindata_augmented_sampled.pkl'\n",
        "\n",
        "\n",
        "KEEP_LABELS_DICT = {\n",
        "    \"alice\": ['ramnit', 'kraken', 'simda', 'nymaim2', 'pizd'],\n",
        "    \"bob\": ['banjori', 'pykspa', 'ramdo', 'qakbot', 'cryptolocker', 'gozi'],\n",
        "    \"charlie\": ['locky', 'corebot', 'dircrypt', 'matsnu', 'suppobox'],\n",
        "    \"testing\": ['pykspa', 'simda', 'kraken', 'qakbot', 'cryptolocker', 'locky', 'ramdo', 'ramnit', 'banjori', 'corebot', 'dircrypt', 'gozi', 'nymaim2', 'pizd', 'matsnu', 'suppobox']\n",
        "}\n",
        "\n",
        "original = ['benign']\n",
        "\n",
        "dga = ['pykspa', 'simda', 'kraken', 'qakbot', 'cryptolocker', 'locky', 'ramdo', 'ramnit', 'banjori', 'corebot', 'dircrypt', 'gozi', 'nymaim2', 'pizd', 'matsnu', 'suppobox']\n",
        "\n",
        "\n",
        "\n",
        "def init_data(id):\n",
        "    data = pickle.load(open(DATA_FILE, 'rb'))\n",
        "    test_dataset=data[:64000]\n",
        "    data = data[64000:]\n",
        "    X = data[\"text\"]\n",
        "    labels = data[\"label\"]\n",
        "    data_client = data.loc[data['label'].isin(KEEP_LABELS_DICT[id])]\n",
        "    data_benign = data.loc[data['label'].isin(original)]\n",
        "    if id=='alice':\n",
        "        data_client = pd.concat([data_client, data_benign[:45000]], ignore_index=True, sort=False)\n",
        "    elif id=='bob':\n",
        "        data_client = pd.concat([data_client, data_benign[45000:83000]], ignore_index=True, sort=False)\n",
        "    elif id=='charlie':\n",
        "        data_client = pd.concat([data_client, data_benign[83000:]], ignore_index=True, sort=False)\n",
        "    else:\n",
        "        data_client=test_dataset\n",
        "\n",
        "    data_client = data_client.sample(frac=1)\n",
        "\n",
        "    y = [0 if x == 'benign' else 1 for x in data_client['label']]\n",
        "    valid_chars = {'7': 1, 'i': 2, 'x': 3, '5': 4, 'w': 5, 't': 6, 'v': 7, 'g': 8, 'k': 9, 'd': 10, 'z': 11, '6': 12, '-': 13, '_': 14, 'a': 15, 'p': 16, 'e': 17, '9': 18, 'b': 19, 'f': 20, 'y': 21, \n",
        "                   '2': 22, 'c': 23, 'l': 24, 's': 25, 'n': 26, 'h': 27, '3': 28, 'u': 29, 'm': 30, '0': 31, 'r': 32, 'j': 33, '8': 34, 'o': 35, '4': 36, '1': 37, 'q': 38}\n",
        "    max_features = len(valid_chars) + 1\n",
        "    max_len = 47\n",
        "    X = data_client[\"text\"]\n",
        "    X = [[valid_chars[y] for y in x] for x in X]\n",
        "    X = tf.keras.preprocessing.sequence.pad_sequences(X, maxlen=max_len, padding='pre')\n",
        "\n",
        "    return np.array(X), np.array(y).reshape(len(y),1), max_features, max_len\n",
        "\n",
        "\n",
        "def main():\n",
        "    hook = sy.TorchHook(torch)\n",
        "    bob = sy.VirtualWorker(hook, id=\"bob\")  # define remote worker bob\n",
        "    alice = sy.VirtualWorker(hook, id=\"alice\")  # and alice\n",
        "    charlie = sy.VirtualWorker(hook, id=\"charlie\") #and bob\n",
        "\n",
        "    workers = [alice, bob, charlie]\n",
        "\n",
        "    use_cuda = args.cuda and torch.cuda.is_available()\n",
        "\n",
        "    torch.manual_seed(args.seed)\n",
        "\n",
        "    device = torch.device(\"cuda\" if use_cuda else \"cpu\")\n",
        "\n",
        "    kwargs = {\"num_workers\": 1, \"pin_memory\": True} if use_cuda else {}\n",
        "\n",
        "    for i in ['alice', 'bob', 'charlie', 'testing']:\n",
        "        X, Y, max_features, max_len = init_data(i)\n",
        "        if i=='testing':\n",
        "            test_data = torch.utils.data.TensorDataset(torch.LongTensor(X), torch.LongTensor(Y))\n",
        "        else:\n",
        "            selected_data = torch.LongTensor(X)\n",
        "            selected_targets = torch.LongTensor(Y).squeeze(1)\n",
        "            if i=='bob':\n",
        "                bob_train_dataset = sy.BaseDataset(data=selected_data, targets=selected_targets).send(bob)\n",
        "            if i=='alice':\n",
        "                alice_train_dataset = sy.BaseDataset(data=selected_data, targets=selected_targets).send(alice)\n",
        "            if i=='charlie':\n",
        "                charlie_train_dataset = sy.BaseDataset(data=selected_data, targets=selected_targets).send(charlie)\n",
        "\n",
        "    federated_train_dataset = sy.FederatedDataset([bob_train_dataset, alice_train_dataset, charlie_train_dataset])\n",
        "\n",
        "    federated_train_loader = sy.FederatedDataLoader(federated_train_dataset,\n",
        "        batch_size=args.batch_size,\n",
        "        shuffle=True,\n",
        "        iter_per_worker=True,\n",
        "        **kwargs,\n",
        "    )\n",
        "\n",
        "\n",
        "\n",
        "    test_loader = torch.utils.data.DataLoader(test_data,\n",
        "        batch_size=args.test_batch_size, shuffle=True, **kwargs)\n",
        "\n",
        "    model = Net().to(device)\n",
        "\n",
        "\n",
        "    max_accuracy = 0.0\n",
        "    epochs_no_improve = 0  \n",
        "    accuracy_list = [0.0]\n",
        "    state_dict = torch.load(\"/content/drive/My Drive/Colab Notebooks/MIXED_CORRECT/MODELS_MIXED/Federated_Mixed/BATCH/LSTM/A/12.pt\")\n",
        "    model.load_state_dict(state_dict)\n",
        "    for epoch in range(13, args.epochs + 1):\n",
        "        model = train(model, device, federated_train_loader, args.lr, args.federate_after_n_batches, epoch, test_loader)\n",
        "        pred_list, test_list, max_accuracy, epochs_no_improve, accuracy = test(args, model, device, test_loader, max_accuracy, epochs_no_improve)\n",
        "        torch.save(model.state_dict(), \"/content/drive/My Drive/Colab Notebooks/MIXED_CORRECT/MODELS_MIXED/Federated_Mixed/BATCH/LSTM/A/\"+str(epoch)+\".pt\")\n",
        "        accuracy_list.append(accuracy)\n",
        "        print(accuracy_list)\n",
        "        if epochs_no_improve > 2:\n",
        "           print('Early stopping!')\n",
        "           break\n",
        "\n",
        "\n",
        "    pred_list = [a.squeeze().tolist() for a in pred_list]\n",
        "    total = []\n",
        "    for i in pred_list:\n",
        "        total += i\n",
        "    pred_list = total\n",
        "\n",
        "    test_list = [a.squeeze().tolist() for a in test_list]\n",
        "    total = []\n",
        "    for i in test_list:\n",
        "        total += i\n",
        "    test_list = total\n",
        "\n",
        "    pred_list = ['benign' if x==0 else 'dga' for x in pred_list]\n",
        "    test_list = ['benign' if x==0 else 'dga' for x in test_list]\n",
        "\n",
        "\n",
        "    from sklearn.metrics import classification_report\n",
        "    print(classification_report(test_list, pred_list))\n",
        "\n",
        "    from sklearn.metrics import confusion_matrix\n",
        "    import seaborn as sns\n",
        "    confusion_matrix_df = pd.DataFrame(confusion_matrix(test_list, pred_list))\n",
        "    print(confusion_matrix_df)\n",
        "    sns.heatmap(confusion_matrix_df, annot=True)\n",
        "\n",
        "if __name__ == \"__main__\":\n",
        "    FORMAT = \"%(asctime)s %(levelname)s %(filename)s(l:%(lineno)d) - %(message)s\"\n",
        "    LOG_LEVEL = logging.DEBUG\n",
        "    logging.basicConfig(format=FORMAT, level=LOG_LEVEL)\n",
        "\n",
        "    websockets_logger = logging.getLogger(\"websockets\")\n",
        "    websockets_logger.setLevel(logging.DEBUG)\n",
        "    websockets_logger.addHandler(logging.StreamHandler())\n",
        "\n",
        "    main()"
      ],
      "execution_count": null,
      "outputs": [
        {
          "output_type": "stream",
          "text": [
            "2020-09-20 21:18:22,171 DEBUG <timed exec>(l:153) - Starting training epoch 13\n",
            "2020-09-20 21:18:23,442 DEBUG <timed exec>(l:112) - Train Worker bob: (0%)]\tLoss: 0.166174\n",
            "2020-09-20 21:18:53,826 DEBUG <timed exec>(l:112) - Train Worker bob: (50%)]\tLoss: 0.069294\n",
            "2020-09-20 21:19:23,887 DEBUG <timed exec>(l:112) - Train Worker alice: (0%)]\tLoss: 0.074732\n",
            "2020-09-20 21:19:54,114 DEBUG <timed exec>(l:112) - Train Worker alice: (50%)]\tLoss: 0.098570\n",
            "2020-09-20 21:20:25,043 DEBUG <timed exec>(l:112) - Train Worker charlie: (0%)]\tLoss: 0.037184\n",
            "2020-09-20 21:20:56,254 DEBUG <timed exec>(l:112) - Train Worker charlie: (50%)]\tLoss: 0.091601\n",
            "2020-09-20 21:21:33,643 DEBUG <timed exec>(l:112) - Train Worker bob: (0%)]\tLoss: 0.108872\n",
            "2020-09-20 21:22:05,458 DEBUG <timed exec>(l:112) - Train Worker bob: (50%)]\tLoss: 0.046760\n",
            "2020-09-20 21:22:37,325 DEBUG <timed exec>(l:112) - Train Worker alice: (0%)]\tLoss: 0.182109\n",
            "2020-09-20 21:23:08,347 DEBUG <timed exec>(l:112) - Train Worker alice: (50%)]\tLoss: 0.057152\n",
            "2020-09-20 21:23:39,386 DEBUG <timed exec>(l:112) - Train Worker charlie: (0%)]\tLoss: 0.081369\n",
            "2020-09-20 21:24:10,584 DEBUG <timed exec>(l:112) - Train Worker charlie: (50%)]\tLoss: 0.058460\n",
            "2020-09-20 21:24:41,272 DEBUG <timed exec>(l:175) - Federated-averaging after trained on given batches\n",
            "2020-09-20 21:24:47,680 DEBUG <timed exec>(l:112) - Train Worker bob: (0%)]\tLoss: 0.430676\n",
            "2020-09-20 21:25:20,381 DEBUG <timed exec>(l:112) - Train Worker bob: (50%)]\tLoss: 0.059529\n",
            "2020-09-20 21:25:54,282 DEBUG <timed exec>(l:112) - Train Worker alice: (0%)]\tLoss: 0.215775\n",
            "2020-09-20 21:26:25,440 DEBUG <timed exec>(l:112) - Train Worker alice: (50%)]\tLoss: 0.071901\n",
            "2020-09-20 21:26:56,404 DEBUG <timed exec>(l:112) - Train Worker charlie: (0%)]\tLoss: 0.130723\n",
            "2020-09-20 21:27:26,862 DEBUG <timed exec>(l:112) - Train Worker charlie: (50%)]\tLoss: 0.112366\n",
            "2020-09-20 21:28:03,402 DEBUG <timed exec>(l:112) - Train Worker bob: (0%)]\tLoss: 0.183104\n",
            "2020-09-20 21:28:34,307 DEBUG <timed exec>(l:112) - Train Worker bob: (50%)]\tLoss: 0.137358\n",
            "2020-09-20 21:29:05,106 DEBUG <timed exec>(l:112) - Train Worker alice: (0%)]\tLoss: 0.173422\n",
            "2020-09-20 21:29:36,081 DEBUG <timed exec>(l:112) - Train Worker alice: (50%)]\tLoss: 0.172351\n",
            "2020-09-20 21:30:07,437 DEBUG <timed exec>(l:112) - Train Worker charlie: (0%)]\tLoss: 0.086691\n",
            "2020-09-20 21:30:38,936 DEBUG <timed exec>(l:112) - Train Worker charlie: (50%)]\tLoss: 0.013269\n",
            "2020-09-20 21:31:10,210 DEBUG <timed exec>(l:175) - Federated-averaging after trained on given batches\n",
            "2020-09-20 21:31:17,119 DEBUG <timed exec>(l:112) - Train Worker bob: (0%)]\tLoss: 0.247245\n",
            "2020-09-20 21:31:48,041 DEBUG <timed exec>(l:112) - Train Worker bob: (50%)]\tLoss: 0.049385\n",
            "2020-09-20 21:32:19,135 DEBUG <timed exec>(l:112) - Train Worker alice: (0%)]\tLoss: 0.576940\n",
            "2020-09-20 21:32:49,891 DEBUG <timed exec>(l:112) - Train Worker alice: (50%)]\tLoss: 0.114497\n",
            "2020-09-20 21:33:20,781 DEBUG <timed exec>(l:112) - Train Worker charlie: (0%)]\tLoss: 0.140201\n",
            "2020-09-20 21:33:51,790 DEBUG <timed exec>(l:112) - Train Worker charlie: (50%)]\tLoss: 0.171628\n",
            "2020-09-20 21:34:28,722 DEBUG <timed exec>(l:112) - Train Worker bob: (0%)]\tLoss: 0.023684\n",
            "2020-09-20 21:35:00,969 DEBUG <timed exec>(l:112) - Train Worker bob: (50%)]\tLoss: 0.110883\n",
            "2020-09-20 21:35:33,264 DEBUG <timed exec>(l:112) - Train Worker alice: (0%)]\tLoss: 0.376150\n",
            "2020-09-20 21:36:04,885 DEBUG <timed exec>(l:112) - Train Worker alice: (50%)]\tLoss: 0.167497\n",
            "2020-09-20 21:36:36,346 DEBUG <timed exec>(l:112) - Train Worker charlie: (0%)]\tLoss: 0.099608\n",
            "2020-09-20 21:37:06,816 DEBUG <timed exec>(l:112) - Train Worker charlie: (50%)]\tLoss: 0.044069\n",
            "2020-09-20 21:37:36,702 DEBUG <timed exec>(l:175) - Federated-averaging after trained on given batches\n",
            "2020-09-20 21:37:42,933 DEBUG <timed exec>(l:112) - Train Worker bob: (0%)]\tLoss: 0.089862\n",
            "2020-09-20 21:38:13,527 DEBUG <timed exec>(l:112) - Train Worker bob: (50%)]\tLoss: 0.048005\n",
            "2020-09-20 21:38:43,895 DEBUG <timed exec>(l:112) - Train Worker alice: (0%)]\tLoss: 0.207820\n",
            "2020-09-20 21:39:14,352 DEBUG <timed exec>(l:112) - Train Worker alice: (50%)]\tLoss: 0.071638\n",
            "2020-09-20 21:39:44,875 DEBUG <timed exec>(l:112) - Train Worker charlie: (0%)]\tLoss: 0.087993\n",
            "2020-09-20 21:40:16,690 DEBUG <timed exec>(l:112) - Train Worker charlie: (50%)]\tLoss: 0.093375\n",
            "2020-09-20 21:40:53,899 DEBUG <timed exec>(l:112) - Train Worker bob: (0%)]\tLoss: 0.070996\n",
            "2020-09-20 21:41:24,273 DEBUG <timed exec>(l:112) - Train Worker bob: (50%)]\tLoss: 0.126930\n",
            "2020-09-20 21:41:55,153 DEBUG <timed exec>(l:112) - Train Worker alice: (0%)]\tLoss: 0.247967\n",
            "2020-09-20 21:42:25,515 DEBUG <timed exec>(l:112) - Train Worker alice: (50%)]\tLoss: 0.144431\n",
            "2020-09-20 21:42:55,821 DEBUG <timed exec>(l:112) - Train Worker charlie: (0%)]\tLoss: 0.126755\n",
            "2020-09-20 21:43:26,027 DEBUG <timed exec>(l:112) - Train Worker charlie: (50%)]\tLoss: 0.240070\n",
            "2020-09-20 21:43:55,706 DEBUG <timed exec>(l:175) - Federated-averaging after trained on given batches\n",
            "2020-09-20 21:44:01,954 DEBUG <timed exec>(l:112) - Train Worker bob: (0%)]\tLoss: 0.204649\n",
            "2020-09-20 21:44:33,006 DEBUG <timed exec>(l:112) - Train Worker bob: (50%)]\tLoss: 0.147838\n",
            "2020-09-20 21:45:03,956 DEBUG <timed exec>(l:112) - Train Worker alice: (0%)]\tLoss: 0.325037\n",
            "2020-09-20 21:45:34,474 DEBUG <timed exec>(l:112) - Train Worker alice: (50%)]\tLoss: 0.195424\n",
            "2020-09-20 21:46:05,219 DEBUG <timed exec>(l:112) - Train Worker charlie: (0%)]\tLoss: 0.069423\n",
            "2020-09-20 21:46:35,553 DEBUG <timed exec>(l:112) - Train Worker charlie: (50%)]\tLoss: 0.066782\n",
            "2020-09-20 21:47:12,166 DEBUG <timed exec>(l:112) - Train Worker bob: (0%)]\tLoss: 0.219247\n",
            "2020-09-20 21:47:42,442 DEBUG <timed exec>(l:112) - Train Worker bob: (50%)]\tLoss: 0.062176\n",
            "2020-09-20 21:48:13,015 DEBUG <timed exec>(l:112) - Train Worker alice: (0%)]\tLoss: 0.339070\n",
            "2020-09-20 21:48:43,712 DEBUG <timed exec>(l:112) - Train Worker alice: (50%)]\tLoss: 0.086770\n",
            "2020-09-20 21:49:14,607 DEBUG <timed exec>(l:112) - Train Worker charlie: (0%)]\tLoss: 0.025383\n",
            "2020-09-20 21:49:45,543 DEBUG <timed exec>(l:112) - Train Worker charlie: (50%)]\tLoss: 0.175929\n",
            "2020-09-20 21:50:15,896 DEBUG <timed exec>(l:175) - Federated-averaging after trained on given batches\n",
            "2020-09-20 21:50:23,246 DEBUG <timed exec>(l:112) - Train Worker bob: (0%)]\tLoss: 0.094965\n",
            "2020-09-20 21:50:54,462 DEBUG <timed exec>(l:112) - Train Worker bob: (50%)]\tLoss: 0.107538\n",
            "2020-09-20 21:51:25,180 DEBUG <timed exec>(l:112) - Train Worker alice: (0%)]\tLoss: 0.137573\n",
            "2020-09-20 21:51:55,028 DEBUG <timed exec>(l:112) - Train Worker alice: (50%)]\tLoss: 0.048559\n",
            "2020-09-20 21:52:25,734 DEBUG <timed exec>(l:112) - Train Worker charlie: (0%)]\tLoss: 0.256895\n",
            "2020-09-20 21:52:55,915 DEBUG <timed exec>(l:112) - Train Worker charlie: (50%)]\tLoss: 0.016609\n",
            "2020-09-20 21:53:31,980 DEBUG <timed exec>(l:112) - Train Worker bob: (0%)]\tLoss: 0.094413\n",
            "2020-09-20 21:54:02,148 DEBUG <timed exec>(l:112) - Train Worker bob: (50%)]\tLoss: 0.067800\n",
            "2020-09-20 21:54:32,369 DEBUG <timed exec>(l:112) - Train Worker alice: (0%)]\tLoss: 0.285683\n",
            "2020-09-20 21:55:02,789 DEBUG <timed exec>(l:112) - Train Worker alice: (50%)]\tLoss: 0.128782\n",
            "2020-09-20 21:55:33,418 DEBUG <timed exec>(l:112) - Train Worker charlie: (0%)]\tLoss: 0.089560\n",
            "2020-09-20 21:56:04,195 DEBUG <timed exec>(l:112) - Train Worker charlie: (50%)]\tLoss: 0.103314\n",
            "2020-09-20 21:56:34,436 DEBUG <timed exec>(l:175) - Federated-averaging after trained on given batches\n",
            "2020-09-20 21:56:40,783 DEBUG <timed exec>(l:112) - Train Worker bob: (0%)]\tLoss: 0.113416\n",
            "2020-09-20 21:57:11,505 DEBUG <timed exec>(l:112) - Train Worker bob: (50%)]\tLoss: 0.040689\n",
            "2020-09-20 21:57:43,062 DEBUG <timed exec>(l:112) - Train Worker alice: (0%)]\tLoss: 0.101491\n",
            "2020-09-20 21:58:13,657 DEBUG <timed exec>(l:112) - Train Worker alice: (50%)]\tLoss: 0.079137\n",
            "2020-09-20 21:58:44,063 DEBUG <timed exec>(l:112) - Train Worker charlie: (0%)]\tLoss: 0.063588\n",
            "2020-09-20 21:59:14,390 DEBUG <timed exec>(l:112) - Train Worker charlie: (50%)]\tLoss: 0.128656\n",
            "2020-09-20 21:59:47,720 DEBUG <timed exec>(l:112) - Train Worker bob: (0%)]\tLoss: 0.058310\n",
            "2020-09-20 21:59:54,583 DEBUG <timed exec>(l:112) - Train Worker bob: (48%)]\tLoss: 0.040684\n",
            "2020-09-20 22:00:01,407 DEBUG <timed exec>(l:112) - Train Worker bob: (96%)]\tLoss: 0.389582\n",
            "2020-09-20 22:00:02,109 DEBUG <timed exec>(l:112) - Train Worker alice: (0%)]\tLoss: 0.207419\n",
            "2020-09-20 22:00:08,739 DEBUG <timed exec>(l:112) - Train Worker alice: (48%)]\tLoss: 0.098384\n",
            "2020-09-20 22:00:15,322 DEBUG <timed exec>(l:112) - Train Worker alice: (96%)]\tLoss: 0.193516\n",
            "2020-09-20 22:00:15,995 DEBUG <timed exec>(l:112) - Train Worker charlie: (0%)]\tLoss: 0.127162\n",
            "2020-09-20 22:00:22,562 DEBUG <timed exec>(l:112) - Train Worker charlie: (48%)]\tLoss: 0.120121\n",
            "2020-09-20 22:00:29,035 DEBUG <timed exec>(l:112) - Train Worker charlie: (96%)]\tLoss: 0.077179\n",
            "2020-09-20 22:00:29,084 DEBUG <timed exec>(l:175) - Federated-averaging after trained on given batches\n",
            "2020-09-20 22:01:05,259 DEBUG <timed exec>(l:82) - \n",
            "\n",
            "2020-09-20 22:01:05,260 INFO <timed exec>(l:86) - Test on bob's dataset: Average loss: 0.1515, Accuracy: 60432/64000 (94.42%)\n",
            "\n",
            "2020-09-20 22:01:42,182 DEBUG <timed exec>(l:82) - \n",
            "\n",
            "2020-09-20 22:01:42,183 INFO <timed exec>(l:86) - Test on alice's dataset: Average loss: 0.2157, Accuracy: 58986/64000 (92.17%)\n",
            "\n",
            "2020-09-20 22:02:18,484 DEBUG <timed exec>(l:82) - \n",
            "\n",
            "2020-09-20 22:02:18,485 INFO <timed exec>(l:86) - Test on charlie's dataset: Average loss: 0.2967, Accuracy: 58889/64000 (92.01%)\n",
            "\n"
          ],
          "name": "stderr"
        },
        {
          "output_type": "stream",
          "text": [
            "\n",
            "Test set: Average loss: 0.1515, Accuracy: 60432/64000 (94.42%)\n",
            "\n",
            "[0.0, 88.696875, 90.4203125, 91.215625, 91.8671875, 92.121875, 92.8203125, 93.2171875, 92.90625, 94.13125, 94.3296875, 94.3140625, 94.478125, 94.425]\n"
          ],
          "name": "stdout"
        },
        {
          "output_type": "stream",
          "text": [
            "2020-09-20 22:03:01,318 DEBUG <timed exec>(l:153) - Starting training epoch 14\n",
            "2020-09-20 22:03:01,980 DEBUG <timed exec>(l:112) - Train Worker bob: (0%)]\tLoss: 0.180791\n",
            "2020-09-20 22:03:32,615 DEBUG <timed exec>(l:112) - Train Worker bob: (50%)]\tLoss: 0.205418\n",
            "2020-09-20 22:04:03,426 DEBUG <timed exec>(l:112) - Train Worker alice: (0%)]\tLoss: 0.165329\n",
            "2020-09-20 22:04:33,910 DEBUG <timed exec>(l:112) - Train Worker alice: (50%)]\tLoss: 0.052740\n",
            "2020-09-20 22:05:04,284 DEBUG <timed exec>(l:112) - Train Worker charlie: (0%)]\tLoss: 0.013172\n",
            "2020-09-20 22:05:34,690 DEBUG <timed exec>(l:112) - Train Worker charlie: (50%)]\tLoss: 0.038260\n",
            "2020-09-20 22:06:11,016 DEBUG <timed exec>(l:112) - Train Worker bob: (0%)]\tLoss: 0.116111\n",
            "2020-09-20 22:06:41,461 DEBUG <timed exec>(l:112) - Train Worker bob: (50%)]\tLoss: 0.150461\n",
            "2020-09-20 22:07:11,821 DEBUG <timed exec>(l:112) - Train Worker alice: (0%)]\tLoss: 0.141449\n",
            "2020-09-20 22:07:42,109 DEBUG <timed exec>(l:112) - Train Worker alice: (50%)]\tLoss: 0.088576\n",
            "2020-09-20 22:08:13,634 DEBUG <timed exec>(l:112) - Train Worker charlie: (0%)]\tLoss: 0.100103\n",
            "2020-09-20 22:08:44,107 DEBUG <timed exec>(l:112) - Train Worker charlie: (50%)]\tLoss: 0.076758\n",
            "2020-09-20 22:09:13,957 DEBUG <timed exec>(l:175) - Federated-averaging after trained on given batches\n",
            "2020-09-20 22:09:21,991 DEBUG <timed exec>(l:112) - Train Worker bob: (0%)]\tLoss: 0.121415\n",
            "2020-09-20 22:09:52,545 DEBUG <timed exec>(l:112) - Train Worker bob: (50%)]\tLoss: 0.126786\n",
            "2020-09-20 22:10:23,116 DEBUG <timed exec>(l:112) - Train Worker alice: (0%)]\tLoss: 0.282224\n",
            "2020-09-20 22:10:53,614 DEBUG <timed exec>(l:112) - Train Worker alice: (50%)]\tLoss: 0.099149\n",
            "2020-09-20 22:11:23,554 DEBUG <timed exec>(l:112) - Train Worker charlie: (0%)]\tLoss: 0.124409\n",
            "2020-09-20 22:11:54,096 DEBUG <timed exec>(l:112) - Train Worker charlie: (50%)]\tLoss: 0.152883\n",
            "2020-09-20 22:12:30,008 DEBUG <timed exec>(l:112) - Train Worker bob: (0%)]\tLoss: 0.068269\n",
            "2020-09-20 22:12:59,927 DEBUG <timed exec>(l:112) - Train Worker bob: (50%)]\tLoss: 0.097812\n",
            "2020-09-20 22:13:30,801 DEBUG <timed exec>(l:112) - Train Worker alice: (0%)]\tLoss: 0.228543\n",
            "2020-09-20 22:14:01,831 DEBUG <timed exec>(l:112) - Train Worker alice: (50%)]\tLoss: 0.148432\n",
            "2020-09-20 22:14:32,857 DEBUG <timed exec>(l:112) - Train Worker charlie: (0%)]\tLoss: 0.096273\n",
            "2020-09-20 22:15:03,540 DEBUG <timed exec>(l:112) - Train Worker charlie: (50%)]\tLoss: 0.025244\n",
            "2020-09-20 22:15:33,724 DEBUG <timed exec>(l:175) - Federated-averaging after trained on given batches\n",
            "2020-09-20 22:15:40,132 DEBUG <timed exec>(l:112) - Train Worker bob: (0%)]\tLoss: 0.293977\n",
            "2020-09-20 22:16:11,769 DEBUG <timed exec>(l:112) - Train Worker bob: (50%)]\tLoss: 0.093321\n",
            "2020-09-20 22:16:43,365 DEBUG <timed exec>(l:112) - Train Worker alice: (0%)]\tLoss: 0.285464\n",
            "2020-09-20 22:17:15,909 DEBUG <timed exec>(l:112) - Train Worker alice: (50%)]\tLoss: 0.135658\n",
            "2020-09-20 22:17:48,376 DEBUG <timed exec>(l:112) - Train Worker charlie: (0%)]\tLoss: 0.092281\n",
            "2020-09-20 22:18:18,320 DEBUG <timed exec>(l:112) - Train Worker charlie: (50%)]\tLoss: 0.026189\n",
            "2020-09-20 22:18:56,354 DEBUG <timed exec>(l:112) - Train Worker bob: (0%)]\tLoss: 0.146694\n",
            "2020-09-20 22:19:26,676 DEBUG <timed exec>(l:112) - Train Worker bob: (50%)]\tLoss: 0.081890\n",
            "2020-09-20 22:19:57,211 DEBUG <timed exec>(l:112) - Train Worker alice: (0%)]\tLoss: 0.088365\n",
            "2020-09-20 22:20:27,598 DEBUG <timed exec>(l:112) - Train Worker alice: (50%)]\tLoss: 0.151006\n",
            "2020-09-20 22:20:58,168 DEBUG <timed exec>(l:112) - Train Worker charlie: (0%)]\tLoss: 0.195763\n",
            "2020-09-20 22:21:28,380 DEBUG <timed exec>(l:112) - Train Worker charlie: (50%)]\tLoss: 0.014559\n",
            "2020-09-20 22:21:58,428 DEBUG <timed exec>(l:175) - Federated-averaging after trained on given batches\n",
            "2020-09-20 22:22:04,856 DEBUG <timed exec>(l:112) - Train Worker bob: (0%)]\tLoss: 0.103176\n",
            "2020-09-20 22:22:34,947 DEBUG <timed exec>(l:112) - Train Worker bob: (50%)]\tLoss: 0.107864\n",
            "2020-09-20 22:23:05,247 DEBUG <timed exec>(l:112) - Train Worker alice: (0%)]\tLoss: 0.170938\n",
            "2020-09-20 22:23:35,304 DEBUG <timed exec>(l:112) - Train Worker alice: (50%)]\tLoss: 0.177925\n",
            "2020-09-20 22:24:05,596 DEBUG <timed exec>(l:112) - Train Worker charlie: (0%)]\tLoss: 0.129764\n",
            "2020-09-20 22:24:35,464 DEBUG <timed exec>(l:112) - Train Worker charlie: (50%)]\tLoss: 0.056377\n",
            "2020-09-20 22:25:14,870 DEBUG <timed exec>(l:112) - Train Worker bob: (0%)]\tLoss: 0.172566\n",
            "2020-09-20 22:25:44,555 DEBUG <timed exec>(l:112) - Train Worker bob: (50%)]\tLoss: 0.187642\n",
            "2020-09-20 22:26:14,236 DEBUG <timed exec>(l:112) - Train Worker alice: (0%)]\tLoss: 0.448716\n",
            "2020-09-20 22:26:44,473 DEBUG <timed exec>(l:112) - Train Worker alice: (50%)]\tLoss: 0.157310\n",
            "2020-09-20 22:27:15,084 DEBUG <timed exec>(l:112) - Train Worker charlie: (0%)]\tLoss: 0.054395\n",
            "2020-09-20 22:27:45,131 DEBUG <timed exec>(l:112) - Train Worker charlie: (50%)]\tLoss: 0.028404\n",
            "2020-09-20 22:28:14,795 DEBUG <timed exec>(l:175) - Federated-averaging after trained on given batches\n",
            "2020-09-20 22:28:21,183 DEBUG <timed exec>(l:112) - Train Worker bob: (0%)]\tLoss: 0.045567\n",
            "2020-09-20 22:28:51,421 DEBUG <timed exec>(l:112) - Train Worker bob: (50%)]\tLoss: 0.089016\n",
            "2020-09-20 22:29:22,172 DEBUG <timed exec>(l:112) - Train Worker alice: (0%)]\tLoss: 0.161224\n",
            "2020-09-20 22:29:53,053 DEBUG <timed exec>(l:112) - Train Worker alice: (50%)]\tLoss: 0.031869\n",
            "2020-09-20 22:30:23,498 DEBUG <timed exec>(l:112) - Train Worker charlie: (0%)]\tLoss: 0.063530\n",
            "2020-09-20 22:30:53,687 DEBUG <timed exec>(l:112) - Train Worker charlie: (50%)]\tLoss: 0.136382\n",
            "2020-09-20 22:31:29,569 DEBUG <timed exec>(l:112) - Train Worker bob: (0%)]\tLoss: 0.278171\n",
            "2020-09-20 22:31:59,671 DEBUG <timed exec>(l:112) - Train Worker bob: (50%)]\tLoss: 0.094023\n",
            "2020-09-20 22:32:30,017 DEBUG <timed exec>(l:112) - Train Worker alice: (0%)]\tLoss: 0.136843\n",
            "2020-09-20 22:32:59,684 DEBUG <timed exec>(l:112) - Train Worker alice: (50%)]\tLoss: 0.120396\n",
            "2020-09-20 22:33:29,362 DEBUG <timed exec>(l:112) - Train Worker charlie: (0%)]\tLoss: 0.019780\n",
            "2020-09-20 22:33:59,215 DEBUG <timed exec>(l:112) - Train Worker charlie: (50%)]\tLoss: 0.182681\n",
            "2020-09-20 22:34:28,592 DEBUG <timed exec>(l:175) - Federated-averaging after trained on given batches\n",
            "2020-09-20 22:34:37,828 DEBUG <timed exec>(l:112) - Train Worker bob: (0%)]\tLoss: 0.434558\n",
            "2020-09-20 22:35:08,542 DEBUG <timed exec>(l:112) - Train Worker bob: (50%)]\tLoss: 0.101506\n",
            "2020-09-20 22:35:38,651 DEBUG <timed exec>(l:112) - Train Worker alice: (0%)]\tLoss: 0.161186\n",
            "2020-09-20 22:36:08,720 DEBUG <timed exec>(l:112) - Train Worker alice: (50%)]\tLoss: 0.108422\n",
            "2020-09-20 22:36:38,831 DEBUG <timed exec>(l:112) - Train Worker charlie: (0%)]\tLoss: 0.024471\n",
            "2020-09-20 22:37:09,033 DEBUG <timed exec>(l:112) - Train Worker charlie: (50%)]\tLoss: 0.019502\n",
            "2020-09-20 22:37:45,228 DEBUG <timed exec>(l:112) - Train Worker bob: (0%)]\tLoss: 0.116538\n",
            "2020-09-20 22:38:15,481 DEBUG <timed exec>(l:112) - Train Worker bob: (50%)]\tLoss: 0.122625\n",
            "2020-09-20 22:38:45,527 DEBUG <timed exec>(l:112) - Train Worker alice: (0%)]\tLoss: 0.042454\n",
            "2020-09-20 22:39:15,482 DEBUG <timed exec>(l:112) - Train Worker alice: (50%)]\tLoss: 0.053055\n",
            "2020-09-20 22:39:45,651 DEBUG <timed exec>(l:112) - Train Worker charlie: (0%)]\tLoss: 0.105204\n",
            "2020-09-20 22:40:16,099 DEBUG <timed exec>(l:112) - Train Worker charlie: (50%)]\tLoss: 0.115830\n",
            "2020-09-20 22:40:45,660 DEBUG <timed exec>(l:175) - Federated-averaging after trained on given batches\n",
            "2020-09-20 22:40:51,989 DEBUG <timed exec>(l:112) - Train Worker bob: (0%)]\tLoss: 0.088343\n",
            "2020-09-20 22:41:22,348 DEBUG <timed exec>(l:112) - Train Worker bob: (50%)]\tLoss: 0.071150\n",
            "2020-09-20 22:41:53,107 DEBUG <timed exec>(l:112) - Train Worker alice: (0%)]\tLoss: 0.199060\n",
            "2020-09-20 22:42:23,773 DEBUG <timed exec>(l:112) - Train Worker alice: (50%)]\tLoss: 0.036909\n",
            "2020-09-20 22:42:54,477 DEBUG <timed exec>(l:112) - Train Worker charlie: (0%)]\tLoss: 0.068349\n",
            "2020-09-20 22:43:24,835 DEBUG <timed exec>(l:112) - Train Worker charlie: (50%)]\tLoss: 0.120882\n",
            "2020-09-20 22:43:56,782 DEBUG <timed exec>(l:112) - Train Worker bob: (0%)]\tLoss: 0.126977\n",
            "2020-09-20 22:44:03,481 DEBUG <timed exec>(l:112) - Train Worker bob: (48%)]\tLoss: 0.230890\n",
            "2020-09-20 22:44:10,191 DEBUG <timed exec>(l:112) - Train Worker bob: (96%)]\tLoss: 0.074862\n",
            "2020-09-20 22:44:10,885 DEBUG <timed exec>(l:112) - Train Worker alice: (0%)]\tLoss: 0.264067\n",
            "2020-09-20 22:44:17,557 DEBUG <timed exec>(l:112) - Train Worker alice: (48%)]\tLoss: 0.169680\n",
            "2020-09-20 22:44:24,274 DEBUG <timed exec>(l:112) - Train Worker alice: (96%)]\tLoss: 0.111741\n",
            "2020-09-20 22:44:24,962 DEBUG <timed exec>(l:112) - Train Worker charlie: (0%)]\tLoss: 0.027539\n",
            "2020-09-20 22:44:31,643 DEBUG <timed exec>(l:112) - Train Worker charlie: (48%)]\tLoss: 0.021984\n",
            "2020-09-20 22:44:38,166 DEBUG <timed exec>(l:112) - Train Worker charlie: (96%)]\tLoss: 0.005653\n",
            "2020-09-20 22:44:38,213 DEBUG <timed exec>(l:175) - Federated-averaging after trained on given batches\n",
            "2020-09-20 22:45:16,531 DEBUG <timed exec>(l:82) - \n",
            "\n",
            "2020-09-20 22:45:16,532 INFO <timed exec>(l:86) - Test on bob's dataset: Average loss: 0.1532, Accuracy: 60479/64000 (94.50%)\n",
            "\n",
            "2020-09-20 22:45:55,625 DEBUG <timed exec>(l:82) - \n",
            "\n",
            "2020-09-20 22:45:55,626 INFO <timed exec>(l:86) - Test on alice's dataset: Average loss: 0.1761, Accuracy: 59983/64000 (93.72%)\n",
            "\n",
            "2020-09-20 22:46:36,900 DEBUG <timed exec>(l:82) - \n",
            "\n",
            "2020-09-20 22:46:36,901 INFO <timed exec>(l:86) - Test on charlie's dataset: Average loss: 0.2500, Accuracy: 59536/64000 (93.03%)\n",
            "\n"
          ],
          "name": "stderr"
        },
        {
          "output_type": "stream",
          "text": [
            "\n",
            "Test set: Average loss: 0.1532, Accuracy: 60479/64000 (94.50%)\n",
            "\n",
            "[0.0, 88.696875, 90.4203125, 91.215625, 91.8671875, 92.121875, 92.8203125, 93.2171875, 92.90625, 94.13125, 94.3296875, 94.3140625, 94.478125, 94.425, 94.4984375]\n"
          ],
          "name": "stdout"
        },
        {
          "output_type": "stream",
          "text": [
            "2020-09-20 22:47:20,718 DEBUG <timed exec>(l:153) - Starting training epoch 15\n",
            "2020-09-20 22:47:21,366 DEBUG <timed exec>(l:112) - Train Worker bob: (0%)]\tLoss: 0.154346\n",
            "2020-09-20 22:47:52,070 DEBUG <timed exec>(l:112) - Train Worker bob: (50%)]\tLoss: 0.103425\n",
            "2020-09-20 22:48:22,407 DEBUG <timed exec>(l:112) - Train Worker alice: (0%)]\tLoss: 0.115297\n",
            "2020-09-20 22:48:52,507 DEBUG <timed exec>(l:112) - Train Worker alice: (50%)]\tLoss: 0.119584\n",
            "2020-09-20 22:49:22,786 DEBUG <timed exec>(l:112) - Train Worker charlie: (0%)]\tLoss: 0.088910\n",
            "2020-09-20 22:49:53,159 DEBUG <timed exec>(l:112) - Train Worker charlie: (50%)]\tLoss: 0.030309\n",
            "2020-09-20 22:50:29,307 DEBUG <timed exec>(l:112) - Train Worker bob: (0%)]\tLoss: 0.156566\n",
            "2020-09-20 22:51:00,369 DEBUG <timed exec>(l:112) - Train Worker bob: (50%)]\tLoss: 0.115547\n",
            "2020-09-20 22:51:30,518 DEBUG <timed exec>(l:112) - Train Worker alice: (0%)]\tLoss: 0.158855\n",
            "2020-09-20 22:52:00,605 DEBUG <timed exec>(l:112) - Train Worker alice: (50%)]\tLoss: 0.155663\n",
            "2020-09-20 22:52:30,613 DEBUG <timed exec>(l:112) - Train Worker charlie: (0%)]\tLoss: 0.095391\n",
            "2020-09-20 22:53:00,871 DEBUG <timed exec>(l:112) - Train Worker charlie: (50%)]\tLoss: 0.100942\n",
            "2020-09-20 22:53:30,242 DEBUG <timed exec>(l:175) - Federated-averaging after trained on given batches\n",
            "2020-09-20 22:53:39,702 DEBUG <timed exec>(l:112) - Train Worker bob: (0%)]\tLoss: 0.108783\n",
            "2020-09-20 22:54:10,178 DEBUG <timed exec>(l:112) - Train Worker bob: (50%)]\tLoss: 0.115272\n",
            "2020-09-20 22:54:40,257 DEBUG <timed exec>(l:112) - Train Worker alice: (0%)]\tLoss: 0.241145\n",
            "2020-09-20 22:55:10,501 DEBUG <timed exec>(l:112) - Train Worker alice: (50%)]\tLoss: 0.064462\n",
            "2020-09-20 22:55:40,873 DEBUG <timed exec>(l:112) - Train Worker charlie: (0%)]\tLoss: 0.110746\n",
            "2020-09-20 22:56:11,368 DEBUG <timed exec>(l:112) - Train Worker charlie: (50%)]\tLoss: 0.040037\n",
            "2020-09-20 22:56:47,510 DEBUG <timed exec>(l:112) - Train Worker bob: (0%)]\tLoss: 0.064508\n",
            "2020-09-20 22:57:17,846 DEBUG <timed exec>(l:112) - Train Worker bob: (50%)]\tLoss: 0.188581\n",
            "2020-09-20 22:57:48,024 DEBUG <timed exec>(l:112) - Train Worker alice: (0%)]\tLoss: 0.246092\n",
            "2020-09-20 22:58:18,103 DEBUG <timed exec>(l:112) - Train Worker alice: (50%)]\tLoss: 0.095217\n",
            "2020-09-20 22:58:48,026 DEBUG <timed exec>(l:112) - Train Worker charlie: (0%)]\tLoss: 0.124950\n",
            "2020-09-20 22:59:17,735 DEBUG <timed exec>(l:112) - Train Worker charlie: (50%)]\tLoss: 0.106204\n",
            "2020-09-20 22:59:46,913 DEBUG <timed exec>(l:175) - Federated-averaging after trained on given batches\n",
            "2020-09-20 22:59:53,170 DEBUG <timed exec>(l:112) - Train Worker bob: (0%)]\tLoss: 0.172243\n",
            "2020-09-20 23:00:22,940 DEBUG <timed exec>(l:112) - Train Worker bob: (50%)]\tLoss: 0.124176\n",
            "2020-09-20 23:00:53,110 DEBUG <timed exec>(l:112) - Train Worker alice: (0%)]\tLoss: 0.226557\n",
            "2020-09-20 23:01:23,452 DEBUG <timed exec>(l:112) - Train Worker alice: (50%)]\tLoss: 0.184865\n",
            "2020-09-20 23:01:54,320 DEBUG <timed exec>(l:112) - Train Worker charlie: (0%)]\tLoss: 0.044885\n",
            "2020-09-20 23:02:24,335 DEBUG <timed exec>(l:112) - Train Worker charlie: (50%)]\tLoss: 0.043891\n",
            "2020-09-20 23:03:03,700 DEBUG <timed exec>(l:112) - Train Worker bob: (0%)]\tLoss: 0.085931\n",
            "2020-09-20 23:03:33,627 DEBUG <timed exec>(l:112) - Train Worker bob: (50%)]\tLoss: 0.067646\n",
            "2020-09-20 23:04:03,726 DEBUG <timed exec>(l:112) - Train Worker alice: (0%)]\tLoss: 0.102067\n",
            "2020-09-20 23:04:33,569 DEBUG <timed exec>(l:112) - Train Worker alice: (50%)]\tLoss: 0.093803\n",
            "2020-09-20 23:05:03,463 DEBUG <timed exec>(l:112) - Train Worker charlie: (0%)]\tLoss: 0.106668\n",
            "2020-09-20 23:05:33,599 DEBUG <timed exec>(l:112) - Train Worker charlie: (50%)]\tLoss: 0.011613\n",
            "2020-09-20 23:06:03,329 DEBUG <timed exec>(l:175) - Federated-averaging after trained on given batches\n",
            "2020-09-20 23:06:09,646 DEBUG <timed exec>(l:112) - Train Worker bob: (0%)]\tLoss: 0.106184\n",
            "2020-09-20 23:06:39,514 DEBUG <timed exec>(l:112) - Train Worker bob: (50%)]\tLoss: 0.119256\n",
            "2020-09-20 23:07:09,871 DEBUG <timed exec>(l:112) - Train Worker alice: (0%)]\tLoss: 0.182762\n",
            "2020-09-20 23:07:40,036 DEBUG <timed exec>(l:112) - Train Worker alice: (50%)]\tLoss: 0.062086\n",
            "2020-09-20 23:08:10,721 DEBUG <timed exec>(l:112) - Train Worker charlie: (0%)]\tLoss: 0.128623\n",
            "2020-09-20 23:08:40,968 DEBUG <timed exec>(l:112) - Train Worker charlie: (50%)]\tLoss: 0.189890\n",
            "2020-09-20 23:09:17,085 DEBUG <timed exec>(l:112) - Train Worker bob: (0%)]\tLoss: 0.177849\n",
            "2020-09-20 23:09:47,896 DEBUG <timed exec>(l:112) - Train Worker bob: (50%)]\tLoss: 0.337437\n",
            "2020-09-20 23:10:18,846 DEBUG <timed exec>(l:112) - Train Worker alice: (0%)]\tLoss: 0.143293\n",
            "2020-09-20 23:10:49,345 DEBUG <timed exec>(l:112) - Train Worker alice: (50%)]\tLoss: 0.127848\n",
            "2020-09-20 23:11:19,957 DEBUG <timed exec>(l:112) - Train Worker charlie: (0%)]\tLoss: 0.078736\n",
            "2020-09-20 23:11:50,180 DEBUG <timed exec>(l:112) - Train Worker charlie: (50%)]\tLoss: 0.114021\n",
            "2020-09-20 23:12:20,397 DEBUG <timed exec>(l:175) - Federated-averaging after trained on given batches\n",
            "2020-09-20 23:12:30,507 DEBUG <timed exec>(l:112) - Train Worker bob: (0%)]\tLoss: 0.144346\n",
            "2020-09-20 23:13:00,523 DEBUG <timed exec>(l:112) - Train Worker bob: (50%)]\tLoss: 0.202640\n",
            "2020-09-20 23:13:31,034 DEBUG <timed exec>(l:112) - Train Worker alice: (0%)]\tLoss: 0.329119\n",
            "2020-09-20 23:14:01,119 DEBUG <timed exec>(l:112) - Train Worker alice: (50%)]\tLoss: 0.105754\n",
            "2020-09-20 23:14:31,130 DEBUG <timed exec>(l:112) - Train Worker charlie: (0%)]\tLoss: 0.049091\n",
            "2020-09-20 23:15:01,304 DEBUG <timed exec>(l:112) - Train Worker charlie: (50%)]\tLoss: 0.011112\n",
            "2020-09-20 23:15:37,393 DEBUG <timed exec>(l:112) - Train Worker bob: (0%)]\tLoss: 0.256724\n",
            "2020-09-20 23:16:08,000 DEBUG <timed exec>(l:112) - Train Worker bob: (50%)]\tLoss: 0.035821\n",
            "2020-09-20 23:16:38,498 DEBUG <timed exec>(l:112) - Train Worker alice: (0%)]\tLoss: 0.130767\n",
            "2020-09-20 23:17:08,936 DEBUG <timed exec>(l:112) - Train Worker alice: (50%)]\tLoss: 0.114637\n",
            "2020-09-20 23:17:40,289 DEBUG <timed exec>(l:112) - Train Worker charlie: (0%)]\tLoss: 0.108981\n",
            "2020-09-20 23:18:10,925 DEBUG <timed exec>(l:112) - Train Worker charlie: (50%)]\tLoss: 0.041600\n",
            "2020-09-20 23:18:40,868 DEBUG <timed exec>(l:175) - Federated-averaging after trained on given batches\n",
            "2020-09-20 23:18:47,310 DEBUG <timed exec>(l:112) - Train Worker bob: (0%)]\tLoss: 0.048653\n",
            "2020-09-20 23:19:17,658 DEBUG <timed exec>(l:112) - Train Worker bob: (50%)]\tLoss: 0.243800\n",
            "2020-09-20 23:19:48,246 DEBUG <timed exec>(l:112) - Train Worker alice: (0%)]\tLoss: 0.363350\n",
            "2020-09-20 23:20:18,668 DEBUG <timed exec>(l:112) - Train Worker alice: (50%)]\tLoss: 0.226188\n",
            "2020-09-20 23:20:49,014 DEBUG <timed exec>(l:112) - Train Worker charlie: (0%)]\tLoss: 0.072021\n",
            "2020-09-20 23:21:19,486 DEBUG <timed exec>(l:112) - Train Worker charlie: (50%)]\tLoss: 0.099687\n",
            "2020-09-20 23:22:00,405 DEBUG <timed exec>(l:112) - Train Worker bob: (0%)]\tLoss: 0.258652\n",
            "2020-09-20 23:22:31,084 DEBUG <timed exec>(l:112) - Train Worker bob: (50%)]\tLoss: 0.207617\n",
            "2020-09-20 23:23:02,507 DEBUG <timed exec>(l:112) - Train Worker alice: (0%)]\tLoss: 0.214695\n",
            "2020-09-20 23:23:33,514 DEBUG <timed exec>(l:112) - Train Worker alice: (50%)]\tLoss: 0.086643\n",
            "2020-09-20 23:24:04,422 DEBUG <timed exec>(l:112) - Train Worker charlie: (0%)]\tLoss: 0.069754\n",
            "2020-09-20 23:24:34,988 DEBUG <timed exec>(l:112) - Train Worker charlie: (50%)]\tLoss: 0.091231\n",
            "2020-09-20 23:25:04,721 DEBUG <timed exec>(l:175) - Federated-averaging after trained on given batches\n",
            "2020-09-20 23:25:11,167 DEBUG <timed exec>(l:112) - Train Worker bob: (0%)]\tLoss: 0.081417\n",
            "2020-09-20 23:25:41,618 DEBUG <timed exec>(l:112) - Train Worker bob: (50%)]\tLoss: 0.132074\n",
            "2020-09-20 23:26:12,330 DEBUG <timed exec>(l:112) - Train Worker alice: (0%)]\tLoss: 0.321819\n",
            "2020-09-20 23:26:42,810 DEBUG <timed exec>(l:112) - Train Worker alice: (50%)]\tLoss: 0.126129\n",
            "2020-09-20 23:27:13,463 DEBUG <timed exec>(l:112) - Train Worker charlie: (0%)]\tLoss: 0.088658\n",
            "2020-09-20 23:27:43,956 DEBUG <timed exec>(l:112) - Train Worker charlie: (50%)]\tLoss: 0.019136\n",
            "2020-09-20 23:28:16,114 DEBUG <timed exec>(l:112) - Train Worker bob: (0%)]\tLoss: 0.158255\n",
            "2020-09-20 23:28:22,954 DEBUG <timed exec>(l:112) - Train Worker bob: (48%)]\tLoss: 0.073222\n",
            "2020-09-20 23:28:29,778 DEBUG <timed exec>(l:112) - Train Worker bob: (96%)]\tLoss: 0.129245\n",
            "2020-09-20 23:28:30,508 DEBUG <timed exec>(l:112) - Train Worker alice: (0%)]\tLoss: 0.395739\n",
            "2020-09-20 23:28:37,374 DEBUG <timed exec>(l:112) - Train Worker alice: (48%)]\tLoss: 0.115043\n",
            "2020-09-20 23:28:44,144 DEBUG <timed exec>(l:112) - Train Worker alice: (96%)]\tLoss: 0.178609\n",
            "2020-09-20 23:28:44,841 DEBUG <timed exec>(l:112) - Train Worker charlie: (0%)]\tLoss: 0.045819\n",
            "2020-09-20 23:28:51,588 DEBUG <timed exec>(l:112) - Train Worker charlie: (48%)]\tLoss: 0.068710\n",
            "2020-09-20 23:28:58,211 DEBUG <timed exec>(l:112) - Train Worker charlie: (96%)]\tLoss: 0.159351\n",
            "2020-09-20 23:28:58,261 DEBUG <timed exec>(l:175) - Federated-averaging after trained on given batches\n",
            "2020-09-20 23:29:39,706 DEBUG <timed exec>(l:82) - \n",
            "\n",
            "2020-09-20 23:29:39,707 INFO <timed exec>(l:86) - Test on bob's dataset: Average loss: 0.1383, Accuracy: 60725/64000 (94.88%)\n",
            "\n",
            "2020-09-20 23:30:21,220 DEBUG <timed exec>(l:82) - \n",
            "\n",
            "2020-09-20 23:30:21,221 INFO <timed exec>(l:86) - Test on alice's dataset: Average loss: 0.1791, Accuracy: 59819/64000 (93.47%)\n",
            "\n",
            "2020-09-20 23:31:01,790 DEBUG <timed exec>(l:82) - \n",
            "\n",
            "2020-09-20 23:31:01,791 INFO <timed exec>(l:86) - Test on charlie's dataset: Average loss: 0.2589, Accuracy: 59476/64000 (92.93%)\n",
            "\n"
          ],
          "name": "stderr"
        },
        {
          "output_type": "stream",
          "text": [
            "\n",
            "Test set: Average loss: 0.1383, Accuracy: 60725/64000 (94.88%)\n",
            "\n",
            "[0.0, 88.696875, 90.4203125, 91.215625, 91.8671875, 92.121875, 92.8203125, 93.2171875, 92.90625, 94.13125, 94.3296875, 94.3140625, 94.478125, 94.425, 94.4984375, 94.8828125]\n"
          ],
          "name": "stdout"
        },
        {
          "output_type": "stream",
          "text": [
            "2020-09-20 23:31:52,488 DEBUG <timed exec>(l:153) - Starting training epoch 16\n",
            "2020-09-20 23:31:53,153 DEBUG <timed exec>(l:112) - Train Worker bob: (0%)]\tLoss: 0.197851\n",
            "2020-09-20 23:32:23,486 DEBUG <timed exec>(l:112) - Train Worker bob: (50%)]\tLoss: 0.069183\n",
            "2020-09-20 23:32:53,736 DEBUG <timed exec>(l:112) - Train Worker alice: (0%)]\tLoss: 0.156110\n",
            "2020-09-20 23:33:24,244 DEBUG <timed exec>(l:112) - Train Worker alice: (50%)]\tLoss: 0.235762\n",
            "2020-09-20 23:33:55,936 DEBUG <timed exec>(l:112) - Train Worker charlie: (0%)]\tLoss: 0.095369\n",
            "2020-09-20 23:34:28,825 DEBUG <timed exec>(l:112) - Train Worker charlie: (50%)]\tLoss: 0.043432\n",
            "2020-09-20 23:35:05,022 DEBUG <timed exec>(l:112) - Train Worker bob: (0%)]\tLoss: 0.213960\n",
            "2020-09-20 23:35:35,485 DEBUG <timed exec>(l:112) - Train Worker bob: (50%)]\tLoss: 0.237320\n",
            "2020-09-20 23:36:06,007 DEBUG <timed exec>(l:112) - Train Worker alice: (0%)]\tLoss: 0.132164\n",
            "2020-09-20 23:36:36,509 DEBUG <timed exec>(l:112) - Train Worker alice: (50%)]\tLoss: 0.087984\n",
            "2020-09-20 23:37:07,001 DEBUG <timed exec>(l:112) - Train Worker charlie: (0%)]\tLoss: 0.096249\n",
            "2020-09-20 23:37:37,547 DEBUG <timed exec>(l:112) - Train Worker charlie: (50%)]\tLoss: 0.064002\n",
            "2020-09-20 23:38:07,618 DEBUG <timed exec>(l:175) - Federated-averaging after trained on given batches\n",
            "2020-09-20 23:38:13,991 DEBUG <timed exec>(l:112) - Train Worker bob: (0%)]\tLoss: 0.073800\n",
            "2020-09-20 23:38:44,613 DEBUG <timed exec>(l:112) - Train Worker bob: (50%)]\tLoss: 0.099265\n",
            "2020-09-20 23:39:16,437 DEBUG <timed exec>(l:112) - Train Worker alice: (0%)]\tLoss: 0.066705\n",
            "2020-09-20 23:39:46,904 DEBUG <timed exec>(l:112) - Train Worker alice: (50%)]\tLoss: 0.064432\n",
            "2020-09-20 23:40:17,351 DEBUG <timed exec>(l:112) - Train Worker charlie: (0%)]\tLoss: 0.096753\n",
            "2020-09-20 23:40:47,979 DEBUG <timed exec>(l:112) - Train Worker charlie: (50%)]\tLoss: 0.173413\n",
            "2020-09-20 23:41:30,680 DEBUG <timed exec>(l:112) - Train Worker bob: (0%)]\tLoss: 0.047800\n",
            "2020-09-20 23:42:01,394 DEBUG <timed exec>(l:112) - Train Worker bob: (50%)]\tLoss: 0.116657\n",
            "2020-09-20 23:42:32,208 DEBUG <timed exec>(l:112) - Train Worker alice: (0%)]\tLoss: 0.306320\n",
            "2020-09-20 23:43:02,848 DEBUG <timed exec>(l:112) - Train Worker alice: (50%)]\tLoss: 0.160894\n",
            "2020-09-20 23:43:33,440 DEBUG <timed exec>(l:112) - Train Worker charlie: (0%)]\tLoss: 0.046746\n",
            "2020-09-20 23:44:04,052 DEBUG <timed exec>(l:112) - Train Worker charlie: (50%)]\tLoss: 0.020043\n",
            "2020-09-20 23:44:34,431 DEBUG <timed exec>(l:175) - Federated-averaging after trained on given batches\n",
            "2020-09-20 23:44:40,790 DEBUG <timed exec>(l:112) - Train Worker bob: (0%)]\tLoss: 0.181198\n",
            "2020-09-20 23:45:11,180 DEBUG <timed exec>(l:112) - Train Worker bob: (50%)]\tLoss: 0.201522\n",
            "2020-09-20 23:45:41,488 DEBUG <timed exec>(l:112) - Train Worker alice: (0%)]\tLoss: 0.320458\n",
            "2020-09-20 23:46:12,054 DEBUG <timed exec>(l:112) - Train Worker alice: (50%)]\tLoss: 0.120566\n",
            "2020-09-20 23:46:42,465 DEBUG <timed exec>(l:112) - Train Worker charlie: (0%)]\tLoss: 0.026873\n",
            "2020-09-20 23:47:12,913 DEBUG <timed exec>(l:112) - Train Worker charlie: (50%)]\tLoss: 0.033085\n",
            "2020-09-20 23:47:56,272 DEBUG <timed exec>(l:112) - Train Worker bob: (0%)]\tLoss: 0.087968\n",
            "2020-09-20 23:48:26,730 DEBUG <timed exec>(l:112) - Train Worker bob: (50%)]\tLoss: 0.105011\n",
            "2020-09-20 23:48:57,218 DEBUG <timed exec>(l:112) - Train Worker alice: (0%)]\tLoss: 0.277901\n",
            "2020-09-20 23:49:28,035 DEBUG <timed exec>(l:112) - Train Worker alice: (50%)]\tLoss: 0.094166\n",
            "2020-09-20 23:49:59,099 DEBUG <timed exec>(l:112) - Train Worker charlie: (0%)]\tLoss: 0.019916\n",
            "2020-09-20 23:50:29,615 DEBUG <timed exec>(l:112) - Train Worker charlie: (50%)]\tLoss: 0.046255\n",
            "2020-09-20 23:50:59,337 DEBUG <timed exec>(l:175) - Federated-averaging after trained on given batches\n",
            "2020-09-20 23:51:05,800 DEBUG <timed exec>(l:112) - Train Worker bob: (0%)]\tLoss: 0.044050\n",
            "2020-09-20 23:51:36,114 DEBUG <timed exec>(l:112) - Train Worker bob: (50%)]\tLoss: 0.111080\n",
            "2020-09-20 23:52:06,571 DEBUG <timed exec>(l:112) - Train Worker alice: (0%)]\tLoss: 0.161875\n",
            "2020-09-20 23:52:36,775 DEBUG <timed exec>(l:112) - Train Worker alice: (50%)]\tLoss: 0.167219\n",
            "2020-09-20 23:53:07,116 DEBUG <timed exec>(l:112) - Train Worker charlie: (0%)]\tLoss: 0.033559\n",
            "2020-09-20 23:53:37,428 DEBUG <timed exec>(l:112) - Train Worker charlie: (50%)]\tLoss: 0.087672\n",
            "2020-09-20 23:54:14,155 DEBUG <timed exec>(l:112) - Train Worker bob: (0%)]\tLoss: 0.129169\n",
            "2020-09-20 23:54:44,921 DEBUG <timed exec>(l:112) - Train Worker bob: (50%)]\tLoss: 0.041057\n",
            "2020-09-20 23:55:16,012 DEBUG <timed exec>(l:112) - Train Worker alice: (0%)]\tLoss: 0.167819\n",
            "2020-09-20 23:55:46,619 DEBUG <timed exec>(l:112) - Train Worker alice: (50%)]\tLoss: 0.106268\n",
            "2020-09-20 23:56:17,213 DEBUG <timed exec>(l:112) - Train Worker charlie: (0%)]\tLoss: 0.074984\n",
            "2020-09-20 23:56:47,593 DEBUG <timed exec>(l:112) - Train Worker charlie: (50%)]\tLoss: 0.067450\n",
            "2020-09-20 23:57:17,608 DEBUG <timed exec>(l:175) - Federated-averaging after trained on given batches\n",
            "2020-09-20 23:57:31,250 DEBUG <timed exec>(l:112) - Train Worker bob: (0%)]\tLoss: 0.138440\n",
            "2020-09-20 23:58:01,579 DEBUG <timed exec>(l:112) - Train Worker bob: (50%)]\tLoss: 0.114876\n",
            "2020-09-20 23:58:31,375 DEBUG <timed exec>(l:112) - Train Worker alice: (0%)]\tLoss: 0.112484\n",
            "2020-09-20 23:59:01,066 DEBUG <timed exec>(l:112) - Train Worker alice: (50%)]\tLoss: 0.037944\n",
            "2020-09-20 23:59:31,181 DEBUG <timed exec>(l:112) - Train Worker charlie: (0%)]\tLoss: 0.017741\n",
            "2020-09-21 00:00:00,972 DEBUG <timed exec>(l:112) - Train Worker charlie: (50%)]\tLoss: 0.073808\n",
            "2020-09-21 00:00:37,358 DEBUG <timed exec>(l:112) - Train Worker bob: (0%)]\tLoss: 0.090679\n",
            "2020-09-21 00:01:07,037 DEBUG <timed exec>(l:112) - Train Worker bob: (50%)]\tLoss: 0.060159\n",
            "2020-09-21 00:01:37,014 DEBUG <timed exec>(l:112) - Train Worker alice: (0%)]\tLoss: 0.078514\n",
            "2020-09-21 00:02:07,286 DEBUG <timed exec>(l:112) - Train Worker alice: (50%)]\tLoss: 0.041030\n",
            "2020-09-21 00:02:37,351 DEBUG <timed exec>(l:112) - Train Worker charlie: (0%)]\tLoss: 0.129437\n",
            "2020-09-21 00:03:07,377 DEBUG <timed exec>(l:112) - Train Worker charlie: (50%)]\tLoss: 0.050434\n",
            "2020-09-21 00:03:36,791 DEBUG <timed exec>(l:175) - Federated-averaging after trained on given batches\n",
            "2020-09-21 00:03:43,040 DEBUG <timed exec>(l:112) - Train Worker bob: (0%)]\tLoss: 0.188781\n",
            "2020-09-21 00:04:13,176 DEBUG <timed exec>(l:112) - Train Worker bob: (50%)]\tLoss: 0.149072\n",
            "2020-09-21 00:04:43,532 DEBUG <timed exec>(l:112) - Train Worker alice: (0%)]\tLoss: 0.197068\n",
            "2020-09-21 00:05:13,374 DEBUG <timed exec>(l:112) - Train Worker alice: (50%)]\tLoss: 0.065411\n",
            "2020-09-21 00:05:43,863 DEBUG <timed exec>(l:112) - Train Worker charlie: (0%)]\tLoss: 0.074438\n",
            "2020-09-21 00:06:14,096 DEBUG <timed exec>(l:112) - Train Worker charlie: (50%)]\tLoss: 0.034930\n",
            "2020-09-21 00:06:57,016 DEBUG <timed exec>(l:112) - Train Worker bob: (0%)]\tLoss: 0.196262\n",
            "2020-09-21 00:07:26,689 DEBUG <timed exec>(l:112) - Train Worker bob: (50%)]\tLoss: 0.057573\n",
            "2020-09-21 00:07:56,666 DEBUG <timed exec>(l:112) - Train Worker alice: (0%)]\tLoss: 0.225617\n",
            "2020-09-21 00:08:26,329 DEBUG <timed exec>(l:112) - Train Worker alice: (50%)]\tLoss: 0.083500\n",
            "2020-09-21 00:08:56,130 DEBUG <timed exec>(l:112) - Train Worker charlie: (0%)]\tLoss: 0.082169\n",
            "2020-09-21 00:09:26,630 DEBUG <timed exec>(l:112) - Train Worker charlie: (50%)]\tLoss: 0.021868\n",
            "2020-09-21 00:09:56,871 DEBUG <timed exec>(l:175) - Federated-averaging after trained on given batches\n",
            "2020-09-21 00:10:03,365 DEBUG <timed exec>(l:112) - Train Worker bob: (0%)]\tLoss: 0.138913\n",
            "2020-09-21 00:10:34,121 DEBUG <timed exec>(l:112) - Train Worker bob: (50%)]\tLoss: 0.057423\n",
            "2020-09-21 00:11:05,376 DEBUG <timed exec>(l:112) - Train Worker alice: (0%)]\tLoss: 0.253095\n",
            "2020-09-21 00:11:36,108 DEBUG <timed exec>(l:112) - Train Worker alice: (50%)]\tLoss: 0.076777\n",
            "2020-09-21 00:12:06,916 DEBUG <timed exec>(l:112) - Train Worker charlie: (0%)]\tLoss: 0.039827\n",
            "2020-09-21 00:12:37,159 DEBUG <timed exec>(l:112) - Train Worker charlie: (50%)]\tLoss: 0.050780\n",
            "2020-09-21 00:13:08,815 DEBUG <timed exec>(l:112) - Train Worker bob: (0%)]\tLoss: 0.248323\n",
            "2020-09-21 00:13:15,432 DEBUG <timed exec>(l:112) - Train Worker bob: (48%)]\tLoss: 0.168398\n",
            "2020-09-21 00:13:22,042 DEBUG <timed exec>(l:112) - Train Worker bob: (96%)]\tLoss: 0.129347\n",
            "2020-09-21 00:13:22,736 DEBUG <timed exec>(l:112) - Train Worker alice: (0%)]\tLoss: 0.237757\n",
            "2020-09-21 00:13:29,394 DEBUG <timed exec>(l:112) - Train Worker alice: (48%)]\tLoss: 0.082966\n",
            "2020-09-21 00:13:36,017 DEBUG <timed exec>(l:112) - Train Worker alice: (96%)]\tLoss: 0.112518\n",
            "2020-09-21 00:13:36,703 DEBUG <timed exec>(l:112) - Train Worker charlie: (0%)]\tLoss: 0.065044\n",
            "2020-09-21 00:13:43,348 DEBUG <timed exec>(l:112) - Train Worker charlie: (48%)]\tLoss: 0.024451\n",
            "2020-09-21 00:13:50,027 DEBUG <timed exec>(l:112) - Train Worker charlie: (96%)]\tLoss: 0.113231\n",
            "2020-09-21 00:13:50,075 DEBUG <timed exec>(l:175) - Federated-averaging after trained on given batches\n",
            "2020-09-21 00:14:36,838 DEBUG <timed exec>(l:82) - \n",
            "\n",
            "2020-09-21 00:14:36,840 INFO <timed exec>(l:86) - Test on bob's dataset: Average loss: 0.1466, Accuracy: 60662/64000 (94.78%)\n",
            "\n",
            "2020-09-21 00:15:23,644 DEBUG <timed exec>(l:82) - \n",
            "\n",
            "2020-09-21 00:15:23,645 INFO <timed exec>(l:86) - Test on alice's dataset: Average loss: 0.2080, Accuracy: 59093/64000 (92.33%)\n",
            "\n",
            "2020-09-21 00:16:11,031 DEBUG <timed exec>(l:82) - \n",
            "\n",
            "2020-09-21 00:16:11,032 INFO <timed exec>(l:86) - Test on charlie's dataset: Average loss: 0.2869, Accuracy: 59609/64000 (93.14%)\n",
            "\n"
          ],
          "name": "stderr"
        },
        {
          "output_type": "stream",
          "text": [
            "\n",
            "Test set: Average loss: 0.1466, Accuracy: 60662/64000 (94.78%)\n",
            "\n",
            "[0.0, 88.696875, 90.4203125, 91.215625, 91.8671875, 92.121875, 92.8203125, 93.2171875, 92.90625, 94.13125, 94.3296875, 94.3140625, 94.478125, 94.425, 94.4984375, 94.8828125, 94.784375]\n"
          ],
          "name": "stdout"
        },
        {
          "output_type": "stream",
          "text": [
            "2020-09-21 00:17:11,669 DEBUG <timed exec>(l:153) - Starting training epoch 17\n",
            "2020-09-21 00:17:12,325 DEBUG <timed exec>(l:112) - Train Worker bob: (0%)]\tLoss: 0.264938\n",
            "2020-09-21 00:17:42,904 DEBUG <timed exec>(l:112) - Train Worker bob: (50%)]\tLoss: 0.146468\n",
            "2020-09-21 00:18:13,763 DEBUG <timed exec>(l:112) - Train Worker alice: (0%)]\tLoss: 0.151123\n",
            "2020-09-21 00:18:44,380 DEBUG <timed exec>(l:112) - Train Worker alice: (50%)]\tLoss: 0.052102\n",
            "2020-09-21 00:19:14,970 DEBUG <timed exec>(l:112) - Train Worker charlie: (0%)]\tLoss: 0.026201\n",
            "2020-09-21 00:19:45,199 DEBUG <timed exec>(l:112) - Train Worker charlie: (50%)]\tLoss: 0.046465\n",
            "2020-09-21 00:20:21,520 DEBUG <timed exec>(l:112) - Train Worker bob: (0%)]\tLoss: 0.095224\n",
            "2020-09-21 00:20:51,752 DEBUG <timed exec>(l:112) - Train Worker bob: (50%)]\tLoss: 0.111180\n",
            "2020-09-21 00:21:22,153 DEBUG <timed exec>(l:112) - Train Worker alice: (0%)]\tLoss: 0.241469\n",
            "2020-09-21 00:21:53,407 DEBUG <timed exec>(l:112) - Train Worker alice: (50%)]\tLoss: 0.122401\n",
            "2020-09-21 00:22:23,748 DEBUG <timed exec>(l:112) - Train Worker charlie: (0%)]\tLoss: 0.031338\n",
            "2020-09-21 00:22:54,089 DEBUG <timed exec>(l:112) - Train Worker charlie: (50%)]\tLoss: 0.126525\n",
            "2020-09-21 00:23:24,059 DEBUG <timed exec>(l:175) - Federated-averaging after trained on given batches\n",
            "2020-09-21 00:23:30,447 DEBUG <timed exec>(l:112) - Train Worker bob: (0%)]\tLoss: 0.093389\n",
            "2020-09-21 00:24:00,833 DEBUG <timed exec>(l:112) - Train Worker bob: (50%)]\tLoss: 0.044319\n",
            "2020-09-21 00:24:31,330 DEBUG <timed exec>(l:112) - Train Worker alice: (0%)]\tLoss: 0.208058\n",
            "2020-09-21 00:25:01,988 DEBUG <timed exec>(l:112) - Train Worker alice: (50%)]\tLoss: 0.062034\n",
            "2020-09-21 00:25:32,644 DEBUG <timed exec>(l:112) - Train Worker charlie: (0%)]\tLoss: 0.063727\n",
            "2020-09-21 00:26:03,432 DEBUG <timed exec>(l:112) - Train Worker charlie: (50%)]\tLoss: 0.081724\n",
            "2020-09-21 00:26:47,501 DEBUG <timed exec>(l:112) - Train Worker bob: (0%)]\tLoss: 0.110058\n",
            "2020-09-21 00:27:19,274 DEBUG <timed exec>(l:112) - Train Worker bob: (50%)]\tLoss: 0.096740\n",
            "2020-09-21 00:27:50,432 DEBUG <timed exec>(l:112) - Train Worker alice: (0%)]\tLoss: 0.558492\n",
            "2020-09-21 00:28:23,967 DEBUG <timed exec>(l:112) - Train Worker alice: (50%)]\tLoss: 0.045702\n",
            "2020-09-21 00:28:57,193 DEBUG <timed exec>(l:112) - Train Worker charlie: (0%)]\tLoss: 0.060321\n",
            "2020-09-21 00:29:28,183 DEBUG <timed exec>(l:112) - Train Worker charlie: (50%)]\tLoss: 0.038407\n",
            "2020-09-21 00:29:58,643 DEBUG <timed exec>(l:175) - Federated-averaging after trained on given batches\n",
            "2020-09-21 00:30:05,147 DEBUG <timed exec>(l:112) - Train Worker bob: (0%)]\tLoss: 0.315679\n",
            "2020-09-21 00:30:35,691 DEBUG <timed exec>(l:112) - Train Worker bob: (50%)]\tLoss: 0.012717\n",
            "2020-09-21 00:31:05,970 DEBUG <timed exec>(l:112) - Train Worker alice: (0%)]\tLoss: 0.350469\n",
            "2020-09-21 00:31:36,117 DEBUG <timed exec>(l:112) - Train Worker alice: (50%)]\tLoss: 0.156277\n",
            "2020-09-21 00:32:06,260 DEBUG <timed exec>(l:112) - Train Worker charlie: (0%)]\tLoss: 0.062411\n",
            "2020-09-21 00:32:36,414 DEBUG <timed exec>(l:112) - Train Worker charlie: (50%)]\tLoss: 0.056126\n",
            "2020-09-21 00:33:11,970 DEBUG <timed exec>(l:112) - Train Worker bob: (0%)]\tLoss: 0.223830\n",
            "2020-09-21 00:33:41,695 DEBUG <timed exec>(l:112) - Train Worker bob: (50%)]\tLoss: 0.116349\n",
            "2020-09-21 00:34:11,452 DEBUG <timed exec>(l:112) - Train Worker alice: (0%)]\tLoss: 0.386363\n",
            "2020-09-21 00:34:40,937 DEBUG <timed exec>(l:112) - Train Worker alice: (50%)]\tLoss: 0.128141\n",
            "2020-09-21 00:35:10,496 DEBUG <timed exec>(l:112) - Train Worker charlie: (0%)]\tLoss: 0.057506\n",
            "2020-09-21 00:35:40,320 DEBUG <timed exec>(l:112) - Train Worker charlie: (50%)]\tLoss: 0.032689\n",
            "2020-09-21 00:36:09,337 DEBUG <timed exec>(l:175) - Federated-averaging after trained on given batches\n",
            "2020-09-21 00:36:23,813 DEBUG <timed exec>(l:112) - Train Worker bob: (0%)]\tLoss: 0.132067\n",
            "2020-09-21 00:36:53,514 DEBUG <timed exec>(l:112) - Train Worker bob: (50%)]\tLoss: 0.168642\n",
            "2020-09-21 00:37:23,876 DEBUG <timed exec>(l:112) - Train Worker alice: (0%)]\tLoss: 0.177286\n",
            "2020-09-21 00:37:54,814 DEBUG <timed exec>(l:112) - Train Worker alice: (50%)]\tLoss: 0.079844\n",
            "2020-09-21 00:38:24,979 DEBUG <timed exec>(l:112) - Train Worker charlie: (0%)]\tLoss: 0.102760\n",
            "2020-09-21 00:38:55,110 DEBUG <timed exec>(l:112) - Train Worker charlie: (50%)]\tLoss: 0.195127\n",
            "2020-09-21 00:39:30,837 DEBUG <timed exec>(l:112) - Train Worker bob: (0%)]\tLoss: 0.134454\n",
            "2020-09-21 00:40:01,004 DEBUG <timed exec>(l:112) - Train Worker bob: (50%)]\tLoss: 0.187983\n",
            "2020-09-21 00:40:31,055 DEBUG <timed exec>(l:112) - Train Worker alice: (0%)]\tLoss: 0.249654\n",
            "2020-09-21 00:41:00,879 DEBUG <timed exec>(l:112) - Train Worker alice: (50%)]\tLoss: 0.099610\n",
            "2020-09-21 00:41:30,892 DEBUG <timed exec>(l:112) - Train Worker charlie: (0%)]\tLoss: 0.053209\n",
            "2020-09-21 00:42:01,118 DEBUG <timed exec>(l:112) - Train Worker charlie: (50%)]\tLoss: 0.066025\n",
            "2020-09-21 00:42:30,354 DEBUG <timed exec>(l:175) - Federated-averaging after trained on given batches\n",
            "2020-09-21 00:42:36,604 DEBUG <timed exec>(l:112) - Train Worker bob: (0%)]\tLoss: 0.079178\n",
            "2020-09-21 00:43:07,218 DEBUG <timed exec>(l:112) - Train Worker bob: (50%)]\tLoss: 0.046430\n",
            "2020-09-21 00:43:37,456 DEBUG <timed exec>(l:112) - Train Worker alice: (0%)]\tLoss: 0.367620\n",
            "2020-09-21 00:44:07,413 DEBUG <timed exec>(l:112) - Train Worker alice: (50%)]\tLoss: 0.060210\n",
            "2020-09-21 00:44:37,441 DEBUG <timed exec>(l:112) - Train Worker charlie: (0%)]\tLoss: 0.033849\n",
            "2020-09-21 00:45:07,471 DEBUG <timed exec>(l:112) - Train Worker charlie: (50%)]\tLoss: 0.005406\n",
            "2020-09-21 00:45:52,670 DEBUG <timed exec>(l:112) - Train Worker bob: (0%)]\tLoss: 0.190441\n",
            "2020-09-21 00:46:22,663 DEBUG <timed exec>(l:112) - Train Worker bob: (50%)]\tLoss: 0.210465\n",
            "2020-09-21 00:46:52,519 DEBUG <timed exec>(l:112) - Train Worker alice: (0%)]\tLoss: 0.540298\n",
            "2020-09-21 00:47:22,233 DEBUG <timed exec>(l:112) - Train Worker alice: (50%)]\tLoss: 0.067067\n",
            "2020-09-21 00:47:51,998 DEBUG <timed exec>(l:112) - Train Worker charlie: (0%)]\tLoss: 0.037426\n",
            "2020-09-21 00:48:22,003 DEBUG <timed exec>(l:112) - Train Worker charlie: (50%)]\tLoss: 0.063441\n",
            "2020-09-21 00:48:51,302 DEBUG <timed exec>(l:175) - Federated-averaging after trained on given batches\n",
            "2020-09-21 00:48:57,520 DEBUG <timed exec>(l:112) - Train Worker bob: (0%)]\tLoss: 0.261499\n",
            "2020-09-21 00:49:27,435 DEBUG <timed exec>(l:112) - Train Worker bob: (50%)]\tLoss: 0.059338\n",
            "2020-09-21 00:49:57,545 DEBUG <timed exec>(l:112) - Train Worker alice: (0%)]\tLoss: 0.189970\n",
            "2020-09-21 00:50:27,517 DEBUG <timed exec>(l:112) - Train Worker alice: (50%)]\tLoss: 0.054005\n",
            "2020-09-21 00:50:57,721 DEBUG <timed exec>(l:112) - Train Worker charlie: (0%)]\tLoss: 0.054381\n",
            "2020-09-21 00:51:27,646 DEBUG <timed exec>(l:112) - Train Worker charlie: (50%)]\tLoss: 0.039714\n",
            "2020-09-21 00:52:03,547 DEBUG <timed exec>(l:112) - Train Worker bob: (0%)]\tLoss: 0.135755\n",
            "2020-09-21 00:52:33,742 DEBUG <timed exec>(l:112) - Train Worker bob: (50%)]\tLoss: 0.024114\n",
            "2020-09-21 00:53:04,120 DEBUG <timed exec>(l:112) - Train Worker alice: (0%)]\tLoss: 0.105227\n",
            "2020-09-21 00:53:34,564 DEBUG <timed exec>(l:112) - Train Worker alice: (50%)]\tLoss: 0.056560\n",
            "2020-09-21 00:54:05,358 DEBUG <timed exec>(l:112) - Train Worker charlie: (0%)]\tLoss: 0.042689\n",
            "2020-09-21 00:54:35,426 DEBUG <timed exec>(l:112) - Train Worker charlie: (50%)]\tLoss: 0.049294\n",
            "2020-09-21 00:55:05,026 DEBUG <timed exec>(l:175) - Federated-averaging after trained on given batches\n",
            "2020-09-21 00:55:21,378 DEBUG <timed exec>(l:112) - Train Worker bob: (0%)]\tLoss: 0.131969\n",
            "2020-09-21 00:55:51,826 DEBUG <timed exec>(l:112) - Train Worker bob: (50%)]\tLoss: 0.109608\n",
            "2020-09-21 00:56:21,958 DEBUG <timed exec>(l:112) - Train Worker alice: (0%)]\tLoss: 0.359648\n",
            "2020-09-21 00:56:52,007 DEBUG <timed exec>(l:112) - Train Worker alice: (50%)]\tLoss: 0.075373\n",
            "2020-09-21 00:57:22,132 DEBUG <timed exec>(l:112) - Train Worker charlie: (0%)]\tLoss: 0.054340\n",
            "2020-09-21 00:57:52,512 DEBUG <timed exec>(l:112) - Train Worker charlie: (50%)]\tLoss: 0.065259\n",
            "2020-09-21 00:58:24,174 DEBUG <timed exec>(l:112) - Train Worker bob: (0%)]\tLoss: 0.210817\n",
            "2020-09-21 00:58:30,879 DEBUG <timed exec>(l:112) - Train Worker bob: (48%)]\tLoss: 0.153868\n",
            "2020-09-21 00:58:37,725 DEBUG <timed exec>(l:112) - Train Worker bob: (96%)]\tLoss: 0.128350\n",
            "2020-09-21 00:58:38,412 DEBUG <timed exec>(l:112) - Train Worker alice: (0%)]\tLoss: 0.528873\n",
            "2020-09-21 00:58:45,152 DEBUG <timed exec>(l:112) - Train Worker alice: (48%)]\tLoss: 0.162705\n",
            "2020-09-21 00:58:52,057 DEBUG <timed exec>(l:112) - Train Worker alice: (96%)]\tLoss: 0.090699\n",
            "2020-09-21 00:58:52,764 DEBUG <timed exec>(l:112) - Train Worker charlie: (0%)]\tLoss: 0.100982\n",
            "2020-09-21 00:58:59,655 DEBUG <timed exec>(l:112) - Train Worker charlie: (48%)]\tLoss: 0.011521\n",
            "2020-09-21 00:59:06,397 DEBUG <timed exec>(l:112) - Train Worker charlie: (96%)]\tLoss: 0.010515\n",
            "2020-09-21 00:59:06,443 DEBUG <timed exec>(l:175) - Federated-averaging after trained on given batches\n",
            "2020-09-21 00:59:59,757 DEBUG <timed exec>(l:82) - \n",
            "\n",
            "2020-09-21 00:59:59,758 INFO <timed exec>(l:86) - Test on bob's dataset: Average loss: 0.1342, Accuracy: 60836/64000 (95.06%)\n",
            "\n",
            "2020-09-21 01:00:52,136 DEBUG <timed exec>(l:82) - \n",
            "\n",
            "2020-09-21 01:00:52,137 INFO <timed exec>(l:86) - Test on alice's dataset: Average loss: 0.1813, Accuracy: 59546/64000 (93.04%)\n",
            "\n",
            "2020-09-21 01:01:44,851 DEBUG <timed exec>(l:82) - \n",
            "\n",
            "2020-09-21 01:01:44,852 INFO <timed exec>(l:86) - Test on charlie's dataset: Average loss: 0.2817, Accuracy: 59404/64000 (92.82%)\n",
            "\n"
          ],
          "name": "stderr"
        },
        {
          "output_type": "stream",
          "text": [
            "\n",
            "Test set: Average loss: 0.1342, Accuracy: 60836/64000 (95.06%)\n",
            "\n",
            "[0.0, 88.696875, 90.4203125, 91.215625, 91.8671875, 92.121875, 92.8203125, 93.2171875, 92.90625, 94.13125, 94.3296875, 94.3140625, 94.478125, 94.425, 94.4984375, 94.8828125, 94.784375, 95.05625]\n"
          ],
          "name": "stdout"
        },
        {
          "output_type": "stream",
          "text": [
            "2020-09-21 01:02:42,198 DEBUG <timed exec>(l:153) - Starting training epoch 18\n",
            "2020-09-21 01:02:42,857 DEBUG <timed exec>(l:112) - Train Worker bob: (0%)]\tLoss: 0.139891\n",
            "2020-09-21 01:03:13,477 DEBUG <timed exec>(l:112) - Train Worker bob: (50%)]\tLoss: 0.173520\n",
            "2020-09-21 01:03:44,151 DEBUG <timed exec>(l:112) - Train Worker alice: (0%)]\tLoss: 0.228202\n",
            "2020-09-21 01:04:15,047 DEBUG <timed exec>(l:112) - Train Worker alice: (50%)]\tLoss: 0.076675\n",
            "2020-09-21 01:04:46,104 DEBUG <timed exec>(l:112) - Train Worker charlie: (0%)]\tLoss: 0.034826\n",
            "2020-09-21 01:05:16,624 DEBUG <timed exec>(l:112) - Train Worker charlie: (50%)]\tLoss: 0.018044\n",
            "2020-09-21 01:06:04,322 DEBUG <timed exec>(l:112) - Train Worker bob: (0%)]\tLoss: 0.159269\n",
            "2020-09-21 01:06:34,911 DEBUG <timed exec>(l:112) - Train Worker bob: (50%)]\tLoss: 0.118764\n",
            "2020-09-21 01:07:05,349 DEBUG <timed exec>(l:112) - Train Worker alice: (0%)]\tLoss: 0.139653\n",
            "2020-09-21 01:07:35,635 DEBUG <timed exec>(l:112) - Train Worker alice: (50%)]\tLoss: 0.079835\n",
            "2020-09-21 01:08:06,156 DEBUG <timed exec>(l:112) - Train Worker charlie: (0%)]\tLoss: 0.166276\n",
            "2020-09-21 01:08:36,416 DEBUG <timed exec>(l:112) - Train Worker charlie: (50%)]\tLoss: 0.059567\n",
            "2020-09-21 01:09:05,946 DEBUG <timed exec>(l:175) - Federated-averaging after trained on given batches\n",
            "2020-09-21 01:09:12,294 DEBUG <timed exec>(l:112) - Train Worker bob: (0%)]\tLoss: 0.137214\n",
            "2020-09-21 01:09:42,949 DEBUG <timed exec>(l:112) - Train Worker bob: (50%)]\tLoss: 0.105394\n",
            "2020-09-21 01:10:14,179 DEBUG <timed exec>(l:112) - Train Worker alice: (0%)]\tLoss: 0.170051\n",
            "2020-09-21 01:10:44,702 DEBUG <timed exec>(l:112) - Train Worker alice: (50%)]\tLoss: 0.151373\n",
            "2020-09-21 01:11:15,538 DEBUG <timed exec>(l:112) - Train Worker charlie: (0%)]\tLoss: 0.109986\n",
            "2020-09-21 01:11:46,155 DEBUG <timed exec>(l:112) - Train Worker charlie: (50%)]\tLoss: 0.074773\n",
            "2020-09-21 01:12:33,457 DEBUG <timed exec>(l:112) - Train Worker bob: (0%)]\tLoss: 0.018891\n",
            "2020-09-21 01:13:03,984 DEBUG <timed exec>(l:112) - Train Worker bob: (50%)]\tLoss: 0.037349\n",
            "2020-09-21 01:13:34,504 DEBUG <timed exec>(l:112) - Train Worker alice: (0%)]\tLoss: 0.355893\n",
            "2020-09-21 01:14:04,815 DEBUG <timed exec>(l:112) - Train Worker alice: (50%)]\tLoss: 0.189483\n",
            "2020-09-21 01:14:34,831 DEBUG <timed exec>(l:112) - Train Worker charlie: (0%)]\tLoss: 0.119058\n",
            "2020-09-21 01:15:05,330 DEBUG <timed exec>(l:112) - Train Worker charlie: (50%)]\tLoss: 0.058990\n",
            "2020-09-21 01:15:34,938 DEBUG <timed exec>(l:175) - Federated-averaging after trained on given batches\n",
            "2020-09-21 01:15:41,293 DEBUG <timed exec>(l:112) - Train Worker bob: (0%)]\tLoss: 0.040842\n",
            "2020-09-21 01:16:11,281 DEBUG <timed exec>(l:112) - Train Worker bob: (50%)]\tLoss: 0.133892\n",
            "2020-09-21 01:16:41,322 DEBUG <timed exec>(l:112) - Train Worker alice: (0%)]\tLoss: 0.263987\n",
            "2020-09-21 01:17:11,148 DEBUG <timed exec>(l:112) - Train Worker alice: (50%)]\tLoss: 0.227403\n",
            "2020-09-21 01:17:41,084 DEBUG <timed exec>(l:112) - Train Worker charlie: (0%)]\tLoss: 0.086567\n",
            "2020-09-21 01:18:11,068 DEBUG <timed exec>(l:112) - Train Worker charlie: (50%)]\tLoss: 0.018577\n",
            "2020-09-21 01:18:46,750 DEBUG <timed exec>(l:112) - Train Worker bob: (0%)]\tLoss: 0.088356\n",
            "2020-09-21 01:19:16,919 DEBUG <timed exec>(l:112) - Train Worker bob: (50%)]\tLoss: 0.071781\n",
            "2020-09-21 01:19:47,298 DEBUG <timed exec>(l:112) - Train Worker alice: (0%)]\tLoss: 0.098840\n",
            "2020-09-21 01:20:18,168 DEBUG <timed exec>(l:112) - Train Worker alice: (50%)]\tLoss: 0.064249\n",
            "2020-09-21 01:20:48,665 DEBUG <timed exec>(l:112) - Train Worker charlie: (0%)]\tLoss: 0.058861\n",
            "2020-09-21 01:21:18,599 DEBUG <timed exec>(l:112) - Train Worker charlie: (50%)]\tLoss: 0.036100\n",
            "2020-09-21 01:21:48,257 DEBUG <timed exec>(l:175) - Federated-averaging after trained on given batches\n",
            "2020-09-21 01:22:06,044 DEBUG <timed exec>(l:112) - Train Worker bob: (0%)]\tLoss: 0.184601\n",
            "2020-09-21 01:22:35,772 DEBUG <timed exec>(l:112) - Train Worker bob: (50%)]\tLoss: 0.100328\n",
            "2020-09-21 01:23:05,697 DEBUG <timed exec>(l:112) - Train Worker alice: (0%)]\tLoss: 0.232940\n",
            "2020-09-21 01:23:35,698 DEBUG <timed exec>(l:112) - Train Worker alice: (50%)]\tLoss: 0.196782\n",
            "2020-09-21 01:24:05,662 DEBUG <timed exec>(l:112) - Train Worker charlie: (0%)]\tLoss: 0.043922\n",
            "2020-09-21 01:24:35,436 DEBUG <timed exec>(l:112) - Train Worker charlie: (50%)]\tLoss: 0.085856\n",
            "2020-09-21 01:25:10,863 DEBUG <timed exec>(l:112) - Train Worker bob: (0%)]\tLoss: 0.047918\n",
            "2020-09-21 01:25:40,905 DEBUG <timed exec>(l:112) - Train Worker bob: (50%)]\tLoss: 0.173193\n",
            "2020-09-21 01:26:11,693 DEBUG <timed exec>(l:112) - Train Worker alice: (0%)]\tLoss: 0.242798\n",
            "2020-09-21 01:26:42,683 DEBUG <timed exec>(l:112) - Train Worker alice: (50%)]\tLoss: 0.122307\n",
            "2020-09-21 01:27:13,594 DEBUG <timed exec>(l:112) - Train Worker charlie: (0%)]\tLoss: 0.205188\n",
            "2020-09-21 01:27:44,375 DEBUG <timed exec>(l:112) - Train Worker charlie: (50%)]\tLoss: 0.072081\n",
            "2020-09-21 01:28:14,460 DEBUG <timed exec>(l:175) - Federated-averaging after trained on given batches\n",
            "2020-09-21 01:28:20,836 DEBUG <timed exec>(l:112) - Train Worker bob: (0%)]\tLoss: 0.106283\n",
            "2020-09-21 01:28:51,484 DEBUG <timed exec>(l:112) - Train Worker bob: (50%)]\tLoss: 0.053218\n",
            "2020-09-21 01:29:22,245 DEBUG <timed exec>(l:112) - Train Worker alice: (0%)]\tLoss: 0.279110\n",
            "2020-09-21 01:29:53,820 DEBUG <timed exec>(l:112) - Train Worker alice: (50%)]\tLoss: 0.070491\n",
            "2020-09-21 01:30:25,595 DEBUG <timed exec>(l:112) - Train Worker charlie: (0%)]\tLoss: 0.104853\n",
            "2020-09-21 01:30:56,791 DEBUG <timed exec>(l:112) - Train Worker charlie: (50%)]\tLoss: 0.040193\n",
            "2020-09-21 01:31:47,450 DEBUG <timed exec>(l:112) - Train Worker bob: (0%)]\tLoss: 0.090289\n",
            "2020-09-21 01:32:18,501 DEBUG <timed exec>(l:112) - Train Worker bob: (50%)]\tLoss: 0.154187\n",
            "2020-09-21 01:32:49,653 DEBUG <timed exec>(l:112) - Train Worker alice: (0%)]\tLoss: 0.271670\n",
            "2020-09-21 01:33:20,851 DEBUG <timed exec>(l:112) - Train Worker alice: (50%)]\tLoss: 0.081876\n",
            "2020-09-21 01:33:52,251 DEBUG <timed exec>(l:112) - Train Worker charlie: (0%)]\tLoss: 0.032913\n",
            "2020-09-21 01:34:23,350 DEBUG <timed exec>(l:112) - Train Worker charlie: (50%)]\tLoss: 0.092680\n",
            "2020-09-21 01:34:53,886 DEBUG <timed exec>(l:175) - Federated-averaging after trained on given batches\n",
            "2020-09-21 01:35:00,421 DEBUG <timed exec>(l:112) - Train Worker bob: (0%)]\tLoss: 0.159794\n",
            "2020-09-21 01:35:31,484 DEBUG <timed exec>(l:112) - Train Worker bob: (50%)]\tLoss: 0.085162\n",
            "2020-09-21 01:36:02,660 DEBUG <timed exec>(l:112) - Train Worker alice: (0%)]\tLoss: 0.223138\n",
            "2020-09-21 01:36:33,867 DEBUG <timed exec>(l:112) - Train Worker alice: (50%)]\tLoss: 0.060927\n",
            "2020-09-21 01:37:05,291 DEBUG <timed exec>(l:112) - Train Worker charlie: (0%)]\tLoss: 0.046786\n",
            "2020-09-21 01:37:36,416 DEBUG <timed exec>(l:112) - Train Worker charlie: (50%)]\tLoss: 0.152765\n",
            "2020-09-21 01:38:13,769 DEBUG <timed exec>(l:112) - Train Worker bob: (0%)]\tLoss: 0.095162\n",
            "2020-09-21 01:38:44,870 DEBUG <timed exec>(l:112) - Train Worker bob: (50%)]\tLoss: 0.062593\n",
            "2020-09-21 01:39:16,171 DEBUG <timed exec>(l:112) - Train Worker alice: (0%)]\tLoss: 0.119357\n",
            "2020-09-21 01:39:47,528 DEBUG <timed exec>(l:112) - Train Worker alice: (50%)]\tLoss: 0.079398\n",
            "2020-09-21 01:40:19,038 DEBUG <timed exec>(l:112) - Train Worker charlie: (0%)]\tLoss: 0.064398\n",
            "2020-09-21 01:40:50,204 DEBUG <timed exec>(l:112) - Train Worker charlie: (50%)]\tLoss: 0.013400\n",
            "2020-09-21 01:41:21,073 DEBUG <timed exec>(l:175) - Federated-averaging after trained on given batches\n",
            "2020-09-21 01:41:41,653 DEBUG <timed exec>(l:112) - Train Worker bob: (0%)]\tLoss: 0.228582\n",
            "2020-09-21 01:42:13,857 DEBUG <timed exec>(l:112) - Train Worker bob: (50%)]\tLoss: 0.115802\n",
            "2020-09-21 01:42:45,275 DEBUG <timed exec>(l:112) - Train Worker alice: (0%)]\tLoss: 0.332572\n",
            "2020-09-21 01:43:16,576 DEBUG <timed exec>(l:112) - Train Worker alice: (50%)]\tLoss: 0.096219\n",
            "2020-09-21 01:43:47,844 DEBUG <timed exec>(l:112) - Train Worker charlie: (0%)]\tLoss: 0.088206\n",
            "2020-09-21 01:44:19,187 DEBUG <timed exec>(l:112) - Train Worker charlie: (50%)]\tLoss: 0.032753\n",
            "2020-09-21 01:44:51,611 DEBUG <timed exec>(l:112) - Train Worker bob: (0%)]\tLoss: 0.112951\n",
            "2020-09-21 01:44:58,413 DEBUG <timed exec>(l:112) - Train Worker bob: (48%)]\tLoss: 0.133540\n",
            "2020-09-21 01:45:05,212 DEBUG <timed exec>(l:112) - Train Worker bob: (96%)]\tLoss: 0.143082\n",
            "2020-09-21 01:45:05,904 DEBUG <timed exec>(l:112) - Train Worker alice: (0%)]\tLoss: 0.335545\n",
            "2020-09-21 01:45:12,682 DEBUG <timed exec>(l:112) - Train Worker alice: (48%)]\tLoss: 0.113239\n",
            "2020-09-21 01:45:19,478 DEBUG <timed exec>(l:112) - Train Worker alice: (96%)]\tLoss: 0.052102\n",
            "2020-09-21 01:45:20,168 DEBUG <timed exec>(l:112) - Train Worker charlie: (0%)]\tLoss: 0.049564\n",
            "2020-09-21 01:45:26,981 DEBUG <timed exec>(l:112) - Train Worker charlie: (48%)]\tLoss: 0.027623\n",
            "2020-09-21 01:45:33,848 DEBUG <timed exec>(l:112) - Train Worker charlie: (96%)]\tLoss: 0.003394\n",
            "2020-09-21 01:45:33,894 DEBUG <timed exec>(l:175) - Federated-averaging after trained on given batches\n",
            "2020-09-21 01:46:32,817 DEBUG <timed exec>(l:82) - \n",
            "\n",
            "2020-09-21 01:46:32,818 INFO <timed exec>(l:86) - Test on bob's dataset: Average loss: 0.1582, Accuracy: 60389/64000 (94.36%)\n",
            "\n",
            "2020-09-21 01:47:33,268 DEBUG <timed exec>(l:82) - \n",
            "\n",
            "2020-09-21 01:47:33,269 INFO <timed exec>(l:86) - Test on alice's dataset: Average loss: 0.1938, Accuracy: 59621/64000 (93.16%)\n",
            "\n",
            "2020-09-21 01:48:32,292 DEBUG <timed exec>(l:82) - \n",
            "\n",
            "2020-09-21 01:48:32,293 INFO <timed exec>(l:86) - Test on charlie's dataset: Average loss: 0.3206, Accuracy: 59389/64000 (92.80%)\n",
            "\n"
          ],
          "name": "stderr"
        },
        {
          "output_type": "stream",
          "text": [
            "\n",
            "Test set: Average loss: 0.1582, Accuracy: 60389/64000 (94.36%)\n",
            "\n",
            "[0.0, 88.696875, 90.4203125, 91.215625, 91.8671875, 92.121875, 92.8203125, 93.2171875, 92.90625, 94.13125, 94.3296875, 94.3140625, 94.478125, 94.425, 94.4984375, 94.8828125, 94.784375, 95.05625, 94.3578125]\n"
          ],
          "name": "stdout"
        },
        {
          "output_type": "stream",
          "text": [
            "2020-09-21 01:49:37,501 DEBUG <timed exec>(l:153) - Starting training epoch 19\n",
            "2020-09-21 01:49:38,201 DEBUG <timed exec>(l:112) - Train Worker bob: (0%)]\tLoss: 0.170109\n",
            "2020-09-21 01:50:09,460 DEBUG <timed exec>(l:112) - Train Worker bob: (50%)]\tLoss: 0.094131\n",
            "2020-09-21 01:50:40,437 DEBUG <timed exec>(l:112) - Train Worker alice: (0%)]\tLoss: 0.140312\n",
            "2020-09-21 01:51:11,386 DEBUG <timed exec>(l:112) - Train Worker alice: (50%)]\tLoss: 0.084191\n",
            "2020-09-21 01:51:42,527 DEBUG <timed exec>(l:112) - Train Worker charlie: (0%)]\tLoss: 0.027952\n",
            "2020-09-21 01:52:13,538 DEBUG <timed exec>(l:112) - Train Worker charlie: (50%)]\tLoss: 0.027802\n",
            "2020-09-21 01:53:03,975 DEBUG <timed exec>(l:112) - Train Worker bob: (0%)]\tLoss: 0.113121\n",
            "2020-09-21 01:53:34,581 DEBUG <timed exec>(l:112) - Train Worker bob: (50%)]\tLoss: 0.084995\n",
            "2020-09-21 01:54:05,556 DEBUG <timed exec>(l:112) - Train Worker alice: (0%)]\tLoss: 0.315854\n",
            "2020-09-21 01:54:36,582 DEBUG <timed exec>(l:112) - Train Worker alice: (50%)]\tLoss: 0.076678\n",
            "2020-09-21 01:55:12,513 DEBUG <timed exec>(l:112) - Train Worker charlie: (0%)]\tLoss: 0.061947\n",
            "2020-09-21 01:55:43,346 DEBUG <timed exec>(l:112) - Train Worker charlie: (50%)]\tLoss: 0.087355\n",
            "2020-09-21 01:56:13,018 DEBUG <timed exec>(l:175) - Federated-averaging after trained on given batches\n",
            "2020-09-21 01:56:19,401 DEBUG <timed exec>(l:112) - Train Worker bob: (0%)]\tLoss: 0.089562\n",
            "2020-09-21 01:56:50,076 DEBUG <timed exec>(l:112) - Train Worker bob: (50%)]\tLoss: 0.084581\n",
            "2020-09-21 01:57:21,120 DEBUG <timed exec>(l:112) - Train Worker alice: (0%)]\tLoss: 0.247724\n",
            "2020-09-21 01:57:52,001 DEBUG <timed exec>(l:112) - Train Worker alice: (50%)]\tLoss: 0.063941\n",
            "2020-09-21 01:58:22,606 DEBUG <timed exec>(l:112) - Train Worker charlie: (0%)]\tLoss: 0.059605\n",
            "2020-09-21 01:58:52,896 DEBUG <timed exec>(l:112) - Train Worker charlie: (50%)]\tLoss: 0.043894\n",
            "2020-09-21 01:59:28,836 DEBUG <timed exec>(l:112) - Train Worker bob: (0%)]\tLoss: 0.111704\n",
            "2020-09-21 01:59:59,141 DEBUG <timed exec>(l:112) - Train Worker bob: (50%)]\tLoss: 0.028827\n",
            "2020-09-21 02:00:29,539 DEBUG <timed exec>(l:112) - Train Worker alice: (0%)]\tLoss: 0.192493\n",
            "2020-09-21 02:01:00,533 DEBUG <timed exec>(l:112) - Train Worker alice: (50%)]\tLoss: 0.041888\n",
            "2020-09-21 02:01:31,309 DEBUG <timed exec>(l:112) - Train Worker charlie: (0%)]\tLoss: 0.076947\n",
            "2020-09-21 02:02:02,422 DEBUG <timed exec>(l:112) - Train Worker charlie: (50%)]\tLoss: 0.027466\n",
            "2020-09-21 02:02:33,240 DEBUG <timed exec>(l:175) - Federated-averaging after trained on given batches\n",
            "2020-09-21 02:02:56,643 DEBUG <timed exec>(l:112) - Train Worker bob: (0%)]\tLoss: 0.145319\n",
            "2020-09-21 02:03:28,104 DEBUG <timed exec>(l:112) - Train Worker bob: (50%)]\tLoss: 0.033230\n",
            "2020-09-21 02:03:58,818 DEBUG <timed exec>(l:112) - Train Worker alice: (0%)]\tLoss: 0.215516\n",
            "2020-09-21 02:04:29,275 DEBUG <timed exec>(l:112) - Train Worker alice: (50%)]\tLoss: 0.100401\n",
            "2020-09-21 02:04:59,841 DEBUG <timed exec>(l:112) - Train Worker charlie: (0%)]\tLoss: 0.110948\n",
            "2020-09-21 02:05:30,263 DEBUG <timed exec>(l:112) - Train Worker charlie: (50%)]\tLoss: 0.129859\n",
            "2020-09-21 02:06:06,937 DEBUG <timed exec>(l:112) - Train Worker bob: (0%)]\tLoss: 0.053652\n",
            "2020-09-21 02:06:37,499 DEBUG <timed exec>(l:112) - Train Worker bob: (50%)]\tLoss: 0.100901\n",
            "2020-09-21 02:07:08,239 DEBUG <timed exec>(l:112) - Train Worker alice: (0%)]\tLoss: 0.348269\n",
            "2020-09-21 02:07:39,443 DEBUG <timed exec>(l:112) - Train Worker alice: (50%)]\tLoss: 0.085228\n",
            "2020-09-21 02:08:10,705 DEBUG <timed exec>(l:112) - Train Worker charlie: (0%)]\tLoss: 0.077398\n",
            "2020-09-21 02:08:42,206 DEBUG <timed exec>(l:112) - Train Worker charlie: (50%)]\tLoss: 0.013951\n",
            "2020-09-21 02:09:12,388 DEBUG <timed exec>(l:175) - Federated-averaging after trained on given batches\n",
            "2020-09-21 02:09:18,849 DEBUG <timed exec>(l:112) - Train Worker bob: (0%)]\tLoss: 0.223810\n",
            "2020-09-21 02:09:49,545 DEBUG <timed exec>(l:112) - Train Worker bob: (50%)]\tLoss: 0.161734\n",
            "2020-09-21 02:10:20,370 DEBUG <timed exec>(l:112) - Train Worker alice: (0%)]\tLoss: 0.312687\n",
            "2020-09-21 02:10:51,028 DEBUG <timed exec>(l:112) - Train Worker alice: (50%)]\tLoss: 0.099608\n",
            "2020-09-21 02:11:21,653 DEBUG <timed exec>(l:112) - Train Worker charlie: (0%)]\tLoss: 0.134160\n",
            "2020-09-21 02:11:52,231 DEBUG <timed exec>(l:112) - Train Worker charlie: (50%)]\tLoss: 0.052580\n",
            "2020-09-21 02:12:45,332 DEBUG <timed exec>(l:112) - Train Worker bob: (0%)]\tLoss: 0.065426\n",
            "2020-09-21 02:13:16,129 DEBUG <timed exec>(l:112) - Train Worker bob: (50%)]\tLoss: 0.146758\n",
            "2020-09-21 02:13:47,776 DEBUG <timed exec>(l:112) - Train Worker alice: (0%)]\tLoss: 0.235764\n",
            "2020-09-21 02:14:18,644 DEBUG <timed exec>(l:112) - Train Worker alice: (50%)]\tLoss: 0.090071\n",
            "2020-09-21 02:14:49,084 DEBUG <timed exec>(l:112) - Train Worker charlie: (0%)]\tLoss: 0.114415\n",
            "2020-09-21 02:15:19,814 DEBUG <timed exec>(l:112) - Train Worker charlie: (50%)]\tLoss: 0.046313\n",
            "2020-09-21 02:15:50,095 DEBUG <timed exec>(l:175) - Federated-averaging after trained on given batches\n",
            "2020-09-21 02:15:56,665 DEBUG <timed exec>(l:112) - Train Worker bob: (0%)]\tLoss: 0.122799\n",
            "2020-09-21 02:16:27,267 DEBUG <timed exec>(l:112) - Train Worker bob: (50%)]\tLoss: 0.076397\n",
            "2020-09-21 02:16:57,867 DEBUG <timed exec>(l:112) - Train Worker alice: (0%)]\tLoss: 0.091085\n",
            "2020-09-21 02:17:28,388 DEBUG <timed exec>(l:112) - Train Worker alice: (50%)]\tLoss: 0.058391\n",
            "2020-09-21 02:17:59,526 DEBUG <timed exec>(l:112) - Train Worker charlie: (0%)]\tLoss: 0.081778\n",
            "2020-09-21 02:18:30,256 DEBUG <timed exec>(l:112) - Train Worker charlie: (50%)]\tLoss: 0.017979\n",
            "2020-09-21 02:19:24,147 DEBUG <timed exec>(l:112) - Train Worker bob: (0%)]\tLoss: 0.107045\n",
            "2020-09-21 02:19:54,297 DEBUG <timed exec>(l:112) - Train Worker bob: (50%)]\tLoss: 0.090390\n",
            "2020-09-21 02:20:24,308 DEBUG <timed exec>(l:112) - Train Worker alice: (0%)]\tLoss: 0.207882\n",
            "2020-09-21 02:20:54,260 DEBUG <timed exec>(l:112) - Train Worker alice: (50%)]\tLoss: 0.117319\n",
            "2020-09-21 02:21:24,363 DEBUG <timed exec>(l:112) - Train Worker charlie: (0%)]\tLoss: 0.055918\n",
            "2020-09-21 02:21:54,956 DEBUG <timed exec>(l:112) - Train Worker charlie: (50%)]\tLoss: 0.034369\n",
            "2020-09-21 02:22:25,112 DEBUG <timed exec>(l:175) - Federated-averaging after trained on given batches\n",
            "2020-09-21 02:22:31,554 DEBUG <timed exec>(l:112) - Train Worker bob: (0%)]\tLoss: 0.064259\n",
            "2020-09-21 02:23:02,599 DEBUG <timed exec>(l:112) - Train Worker bob: (50%)]\tLoss: 0.106231\n",
            "2020-09-21 02:23:33,526 DEBUG <timed exec>(l:112) - Train Worker alice: (0%)]\tLoss: 0.370605\n",
            "2020-09-21 02:24:04,569 DEBUG <timed exec>(l:112) - Train Worker alice: (50%)]\tLoss: 0.067111\n",
            "2020-09-21 02:24:36,241 DEBUG <timed exec>(l:112) - Train Worker charlie: (0%)]\tLoss: 0.049003\n",
            "2020-09-21 02:25:06,918 DEBUG <timed exec>(l:112) - Train Worker charlie: (50%)]\tLoss: 0.076714\n",
            "2020-09-21 02:25:43,252 DEBUG <timed exec>(l:112) - Train Worker bob: (0%)]\tLoss: 0.112640\n",
            "2020-09-21 02:26:13,938 DEBUG <timed exec>(l:112) - Train Worker bob: (50%)]\tLoss: 0.328903\n",
            "2020-09-21 02:26:44,512 DEBUG <timed exec>(l:112) - Train Worker alice: (0%)]\tLoss: 0.130788\n",
            "2020-09-21 02:27:15,076 DEBUG <timed exec>(l:112) - Train Worker alice: (50%)]\tLoss: 0.154761\n",
            "2020-09-21 02:27:45,784 DEBUG <timed exec>(l:112) - Train Worker charlie: (0%)]\tLoss: 0.055027\n",
            "2020-09-21 02:28:16,771 DEBUG <timed exec>(l:112) - Train Worker charlie: (50%)]\tLoss: 0.057252\n",
            "2020-09-21 02:28:46,796 DEBUG <timed exec>(l:175) - Federated-averaging after trained on given batches\n",
            "2020-09-21 02:29:10,802 DEBUG <timed exec>(l:112) - Train Worker bob: (0%)]\tLoss: 0.087195\n",
            "2020-09-21 02:29:42,017 DEBUG <timed exec>(l:112) - Train Worker bob: (50%)]\tLoss: 0.158864\n",
            "2020-09-21 02:30:13,393 DEBUG <timed exec>(l:112) - Train Worker alice: (0%)]\tLoss: 0.748173\n",
            "2020-09-21 02:30:44,060 DEBUG <timed exec>(l:112) - Train Worker alice: (50%)]\tLoss: 0.120298\n",
            "2020-09-21 02:31:15,288 DEBUG <timed exec>(l:112) - Train Worker charlie: (0%)]\tLoss: 0.064853\n",
            "2020-09-21 02:31:46,126 DEBUG <timed exec>(l:112) - Train Worker charlie: (50%)]\tLoss: 0.139858\n",
            "2020-09-21 02:32:18,273 DEBUG <timed exec>(l:112) - Train Worker bob: (0%)]\tLoss: 0.264220\n",
            "2020-09-21 02:32:24,948 DEBUG <timed exec>(l:112) - Train Worker bob: (48%)]\tLoss: 0.061091\n",
            "2020-09-21 02:32:31,579 DEBUG <timed exec>(l:112) - Train Worker bob: (96%)]\tLoss: 0.165315\n",
            "2020-09-21 02:32:32,281 DEBUG <timed exec>(l:112) - Train Worker alice: (0%)]\tLoss: 0.267284\n",
            "2020-09-21 02:32:38,905 DEBUG <timed exec>(l:112) - Train Worker alice: (48%)]\tLoss: 0.121640\n",
            "2020-09-21 02:32:45,603 DEBUG <timed exec>(l:112) - Train Worker alice: (96%)]\tLoss: 0.145361\n",
            "2020-09-21 02:32:46,282 DEBUG <timed exec>(l:112) - Train Worker charlie: (0%)]\tLoss: 0.087561\n",
            "2020-09-21 02:32:53,018 DEBUG <timed exec>(l:112) - Train Worker charlie: (48%)]\tLoss: 0.169552\n",
            "2020-09-21 02:32:59,562 DEBUG <timed exec>(l:112) - Train Worker charlie: (96%)]\tLoss: 0.061155\n",
            "2020-09-21 02:32:59,608 DEBUG <timed exec>(l:175) - Federated-averaging after trained on given batches\n",
            "2020-09-21 02:33:49,173 DEBUG <timed exec>(l:82) - \n",
            "\n",
            "2020-09-21 02:33:49,174 INFO <timed exec>(l:86) - Test on bob's dataset: Average loss: 0.1373, Accuracy: 60812/64000 (95.02%)\n",
            "\n",
            "2020-09-21 02:35:11,943 DEBUG <timed exec>(l:82) - \n",
            "\n",
            "2020-09-21 02:35:11,944 INFO <timed exec>(l:86) - Test on alice's dataset: Average loss: 0.1998, Accuracy: 59581/64000 (93.10%)\n",
            "\n",
            "2020-09-21 02:36:18,078 DEBUG <timed exec>(l:82) - \n",
            "\n",
            "2020-09-21 02:36:18,079 INFO <timed exec>(l:86) - Test on charlie's dataset: Average loss: 0.2223, Accuracy: 60006/64000 (93.76%)\n",
            "\n"
          ],
          "name": "stderr"
        },
        {
          "output_type": "stream",
          "text": [
            "\n",
            "Test set: Average loss: 0.1373, Accuracy: 60812/64000 (95.02%)\n",
            "\n",
            "[0.0, 88.696875, 90.4203125, 91.215625, 91.8671875, 92.121875, 92.8203125, 93.2171875, 92.90625, 94.13125, 94.3296875, 94.3140625, 94.478125, 94.425, 94.4984375, 94.8828125, 94.784375, 95.05625, 94.3578125, 95.01875]\n"
          ],
          "name": "stdout"
        },
        {
          "output_type": "stream",
          "text": [
            "2020-09-21 02:37:30,601 DEBUG <timed exec>(l:153) - Starting training epoch 20\n",
            "2020-09-21 02:37:31,315 DEBUG <timed exec>(l:112) - Train Worker bob: (0%)]\tLoss: 0.025770\n",
            "2020-09-21 02:38:04,918 DEBUG <timed exec>(l:112) - Train Worker bob: (50%)]\tLoss: 0.154279\n",
            "2020-09-21 02:38:38,490 DEBUG <timed exec>(l:112) - Train Worker alice: (0%)]\tLoss: 0.180398\n",
            "2020-09-21 02:39:09,376 DEBUG <timed exec>(l:112) - Train Worker alice: (50%)]\tLoss: 0.127218\n",
            "2020-09-21 02:39:40,118 DEBUG <timed exec>(l:112) - Train Worker charlie: (0%)]\tLoss: 0.015373\n",
            "2020-09-21 02:40:10,653 DEBUG <timed exec>(l:112) - Train Worker charlie: (50%)]\tLoss: 0.031792\n",
            "2020-09-21 02:41:04,099 DEBUG <timed exec>(l:112) - Train Worker bob: (0%)]\tLoss: 0.107799\n",
            "2020-09-21 02:41:34,553 DEBUG <timed exec>(l:112) - Train Worker bob: (50%)]\tLoss: 0.172169\n",
            "2020-09-21 02:42:05,150 DEBUG <timed exec>(l:112) - Train Worker alice: (0%)]\tLoss: 0.069026\n",
            "2020-09-21 02:42:35,822 DEBUG <timed exec>(l:112) - Train Worker alice: (50%)]\tLoss: 0.154247\n",
            "2020-09-21 02:43:06,588 DEBUG <timed exec>(l:112) - Train Worker charlie: (0%)]\tLoss: 0.066625\n",
            "2020-09-21 02:43:37,689 DEBUG <timed exec>(l:112) - Train Worker charlie: (50%)]\tLoss: 0.040864\n",
            "2020-09-21 02:44:07,907 DEBUG <timed exec>(l:175) - Federated-averaging after trained on given batches\n",
            "2020-09-21 02:44:14,364 DEBUG <timed exec>(l:112) - Train Worker bob: (0%)]\tLoss: 0.142820\n",
            "2020-09-21 02:44:45,287 DEBUG <timed exec>(l:112) - Train Worker bob: (50%)]\tLoss: 0.151996\n",
            "2020-09-21 02:45:16,239 DEBUG <timed exec>(l:112) - Train Worker alice: (0%)]\tLoss: 0.181050\n",
            "2020-09-21 02:45:48,068 DEBUG <timed exec>(l:112) - Train Worker alice: (50%)]\tLoss: 0.030173\n",
            "2020-09-21 02:46:19,979 DEBUG <timed exec>(l:112) - Train Worker charlie: (0%)]\tLoss: 0.089994\n",
            "2020-09-21 02:46:51,639 DEBUG <timed exec>(l:112) - Train Worker charlie: (50%)]\tLoss: 0.027410\n",
            "2020-09-21 02:47:28,426 DEBUG <timed exec>(l:112) - Train Worker bob: (0%)]\tLoss: 0.128532\n",
            "2020-09-21 02:47:59,533 DEBUG <timed exec>(l:112) - Train Worker bob: (50%)]\tLoss: 0.115661\n",
            "2020-09-21 02:48:29,977 DEBUG <timed exec>(l:112) - Train Worker alice: (0%)]\tLoss: 0.139705\n",
            "2020-09-21 02:49:00,783 DEBUG <timed exec>(l:112) - Train Worker alice: (50%)]\tLoss: 0.158176\n",
            "2020-09-21 02:49:31,426 DEBUG <timed exec>(l:112) - Train Worker charlie: (0%)]\tLoss: 0.139378\n",
            "2020-09-21 02:50:01,884 DEBUG <timed exec>(l:112) - Train Worker charlie: (50%)]\tLoss: 0.223696\n",
            "2020-09-21 02:50:32,229 DEBUG <timed exec>(l:175) - Federated-averaging after trained on given batches\n",
            "2020-09-21 02:50:58,161 DEBUG <timed exec>(l:112) - Train Worker bob: (0%)]\tLoss: 0.052316\n",
            "2020-09-21 02:51:28,918 DEBUG <timed exec>(l:112) - Train Worker bob: (50%)]\tLoss: 0.134756\n",
            "2020-09-21 02:51:59,377 DEBUG <timed exec>(l:112) - Train Worker alice: (0%)]\tLoss: 0.256966\n",
            "2020-09-21 02:52:29,656 DEBUG <timed exec>(l:112) - Train Worker alice: (50%)]\tLoss: 0.036630\n",
            "2020-09-21 02:53:00,053 DEBUG <timed exec>(l:112) - Train Worker charlie: (0%)]\tLoss: 0.058017\n",
            "2020-09-21 02:53:30,122 DEBUG <timed exec>(l:112) - Train Worker charlie: (50%)]\tLoss: 0.002337\n",
            "2020-09-21 02:54:06,105 DEBUG <timed exec>(l:112) - Train Worker bob: (0%)]\tLoss: 0.201165\n",
            "2020-09-21 02:54:36,149 DEBUG <timed exec>(l:112) - Train Worker bob: (50%)]\tLoss: 0.115650\n",
            "2020-09-21 02:55:06,410 DEBUG <timed exec>(l:112) - Train Worker alice: (0%)]\tLoss: 0.229036\n",
            "2020-09-21 02:55:37,384 DEBUG <timed exec>(l:112) - Train Worker alice: (50%)]\tLoss: 0.237678\n",
            "2020-09-21 02:56:08,590 DEBUG <timed exec>(l:112) - Train Worker charlie: (0%)]\tLoss: 0.018540\n",
            "2020-09-21 02:56:40,268 DEBUG <timed exec>(l:112) - Train Worker charlie: (50%)]\tLoss: 0.010713\n",
            "2020-09-21 02:57:10,638 DEBUG <timed exec>(l:175) - Federated-averaging after trained on given batches\n",
            "2020-09-21 02:57:17,148 DEBUG <timed exec>(l:112) - Train Worker bob: (0%)]\tLoss: 0.221953\n",
            "2020-09-21 02:57:48,689 DEBUG <timed exec>(l:112) - Train Worker bob: (50%)]\tLoss: 0.146409\n",
            "2020-09-21 02:58:20,346 DEBUG <timed exec>(l:112) - Train Worker alice: (0%)]\tLoss: 0.122905\n",
            "2020-09-21 02:58:51,858 DEBUG <timed exec>(l:112) - Train Worker alice: (50%)]\tLoss: 0.064301\n",
            "2020-09-21 02:59:23,226 DEBUG <timed exec>(l:112) - Train Worker charlie: (0%)]\tLoss: 0.137252\n",
            "2020-09-21 02:59:54,445 DEBUG <timed exec>(l:112) - Train Worker charlie: (50%)]\tLoss: 0.010755\n",
            "2020-09-21 03:00:51,375 DEBUG <timed exec>(l:112) - Train Worker bob: (0%)]\tLoss: 0.184445\n",
            "2020-09-21 03:01:22,438 DEBUG <timed exec>(l:112) - Train Worker bob: (50%)]\tLoss: 0.260063\n",
            "2020-09-21 03:01:54,304 DEBUG <timed exec>(l:112) - Train Worker alice: (0%)]\tLoss: 0.345369\n",
            "2020-09-21 03:02:25,599 DEBUG <timed exec>(l:112) - Train Worker alice: (50%)]\tLoss: 0.082876\n",
            "2020-09-21 03:02:57,078 DEBUG <timed exec>(l:112) - Train Worker charlie: (0%)]\tLoss: 0.027620\n",
            "2020-09-21 03:03:28,346 DEBUG <timed exec>(l:112) - Train Worker charlie: (50%)]\tLoss: 0.038904\n",
            "2020-09-21 03:03:59,224 DEBUG <timed exec>(l:175) - Federated-averaging after trained on given batches\n",
            "2020-09-21 03:04:05,902 DEBUG <timed exec>(l:112) - Train Worker bob: (0%)]\tLoss: 0.082252\n",
            "2020-09-21 03:04:37,134 DEBUG <timed exec>(l:112) - Train Worker bob: (50%)]\tLoss: 0.105251\n",
            "2020-09-21 03:05:08,452 DEBUG <timed exec>(l:112) - Train Worker alice: (0%)]\tLoss: 0.163116\n",
            "2020-09-21 03:05:39,790 DEBUG <timed exec>(l:112) - Train Worker alice: (50%)]\tLoss: 0.191898\n",
            "2020-09-21 03:06:11,683 DEBUG <timed exec>(l:112) - Train Worker charlie: (0%)]\tLoss: 0.044840\n",
            "2020-09-21 03:06:43,010 DEBUG <timed exec>(l:112) - Train Worker charlie: (50%)]\tLoss: 0.009041\n",
            "2020-09-21 03:07:20,970 DEBUG <timed exec>(l:112) - Train Worker bob: (0%)]\tLoss: 0.139908\n",
            "2020-09-21 03:07:52,235 DEBUG <timed exec>(l:112) - Train Worker bob: (50%)]\tLoss: 0.109532\n",
            "2020-09-21 03:08:23,420 DEBUG <timed exec>(l:112) - Train Worker alice: (0%)]\tLoss: 0.382560\n",
            "2020-09-21 03:08:54,369 DEBUG <timed exec>(l:112) - Train Worker alice: (50%)]\tLoss: 0.025882\n",
            "2020-09-21 03:09:25,610 DEBUG <timed exec>(l:112) - Train Worker charlie: (0%)]\tLoss: 0.015906\n",
            "2020-09-21 03:09:56,725 DEBUG <timed exec>(l:112) - Train Worker charlie: (50%)]\tLoss: 0.024591\n",
            "2020-09-21 03:10:27,412 DEBUG <timed exec>(l:175) - Federated-averaging after trained on given batches\n",
            "2020-09-21 03:10:54,884 DEBUG <timed exec>(l:112) - Train Worker bob: (0%)]\tLoss: 0.082593\n",
            "2020-09-21 03:11:25,994 DEBUG <timed exec>(l:112) - Train Worker bob: (50%)]\tLoss: 0.159746\n",
            "2020-09-21 03:11:57,237 DEBUG <timed exec>(l:112) - Train Worker alice: (0%)]\tLoss: 0.081494\n",
            "2020-09-21 03:12:28,740 DEBUG <timed exec>(l:112) - Train Worker alice: (50%)]\tLoss: 0.066264\n",
            "2020-09-21 03:13:00,097 DEBUG <timed exec>(l:112) - Train Worker charlie: (0%)]\tLoss: 0.041387\n",
            "2020-09-21 03:13:30,950 DEBUG <timed exec>(l:112) - Train Worker charlie: (50%)]\tLoss: 0.027366\n",
            "2020-09-21 03:14:07,625 DEBUG <timed exec>(l:112) - Train Worker bob: (0%)]\tLoss: 0.086375\n",
            "2020-09-21 03:14:39,039 DEBUG <timed exec>(l:112) - Train Worker bob: (50%)]\tLoss: 0.093089\n",
            "2020-09-21 03:15:10,212 DEBUG <timed exec>(l:112) - Train Worker alice: (0%)]\tLoss: 0.300130\n",
            "2020-09-21 03:15:41,585 DEBUG <timed exec>(l:112) - Train Worker alice: (50%)]\tLoss: 0.090337\n",
            "2020-09-21 03:16:13,087 DEBUG <timed exec>(l:112) - Train Worker charlie: (0%)]\tLoss: 0.028512\n",
            "2020-09-21 03:16:43,691 DEBUG <timed exec>(l:112) - Train Worker charlie: (50%)]\tLoss: 0.167720\n",
            "2020-09-21 03:17:13,821 DEBUG <timed exec>(l:175) - Federated-averaging after trained on given batches\n",
            "2020-09-21 03:17:20,390 DEBUG <timed exec>(l:112) - Train Worker bob: (0%)]\tLoss: 0.042622\n",
            "2020-09-21 03:17:52,220 DEBUG <timed exec>(l:112) - Train Worker bob: (50%)]\tLoss: 0.064572\n",
            "2020-09-21 03:18:23,897 DEBUG <timed exec>(l:112) - Train Worker alice: (0%)]\tLoss: 0.183193\n",
            "2020-09-21 03:18:55,218 DEBUG <timed exec>(l:112) - Train Worker alice: (50%)]\tLoss: 0.225351\n",
            "2020-09-21 03:19:26,681 DEBUG <timed exec>(l:112) - Train Worker charlie: (0%)]\tLoss: 0.166137\n",
            "2020-09-21 03:19:57,469 DEBUG <timed exec>(l:112) - Train Worker charlie: (50%)]\tLoss: 0.135377\n",
            "2020-09-21 03:20:29,634 DEBUG <timed exec>(l:112) - Train Worker bob: (0%)]\tLoss: 0.151780\n",
            "2020-09-21 03:20:36,397 DEBUG <timed exec>(l:112) - Train Worker bob: (48%)]\tLoss: 0.143649\n",
            "2020-09-21 03:20:43,157 DEBUG <timed exec>(l:112) - Train Worker bob: (96%)]\tLoss: 0.040198\n",
            "2020-09-21 03:20:43,846 DEBUG <timed exec>(l:112) - Train Worker alice: (0%)]\tLoss: 0.087085\n",
            "2020-09-21 03:20:50,640 DEBUG <timed exec>(l:112) - Train Worker alice: (48%)]\tLoss: 0.227536\n",
            "2020-09-21 03:20:57,425 DEBUG <timed exec>(l:112) - Train Worker alice: (96%)]\tLoss: 0.144281\n",
            "2020-09-21 03:20:58,114 DEBUG <timed exec>(l:112) - Train Worker charlie: (0%)]\tLoss: 0.070017\n",
            "2020-09-21 03:21:04,909 DEBUG <timed exec>(l:112) - Train Worker charlie: (48%)]\tLoss: 0.049260\n",
            "2020-09-21 03:21:11,542 DEBUG <timed exec>(l:112) - Train Worker charlie: (96%)]\tLoss: 0.000764\n",
            "2020-09-21 03:21:11,590 DEBUG <timed exec>(l:175) - Federated-averaging after trained on given batches\n",
            "2020-09-21 03:22:22,583 DEBUG <timed exec>(l:82) - \n",
            "\n",
            "2020-09-21 03:22:22,584 INFO <timed exec>(l:86) - Test on bob's dataset: Average loss: 0.1626, Accuracy: 60305/64000 (94.23%)\n",
            "\n",
            "2020-09-21 03:23:52,508 DEBUG <timed exec>(l:82) - \n",
            "\n",
            "2020-09-21 03:23:52,508 INFO <timed exec>(l:86) - Test on alice's dataset: Average loss: 0.2029, Accuracy: 59662/64000 (93.22%)\n",
            "\n",
            "2020-09-21 03:25:03,362 DEBUG <timed exec>(l:82) - \n",
            "\n",
            "2020-09-21 03:25:03,363 INFO <timed exec>(l:86) - Test on charlie's dataset: Average loss: 0.3516, Accuracy: 58809/64000 (91.89%)\n",
            "\n"
          ],
          "name": "stderr"
        },
        {
          "output_type": "stream",
          "text": [
            "\n",
            "Test set: Average loss: 0.1626, Accuracy: 60305/64000 (94.23%)\n",
            "\n",
            "[0.0, 88.696875, 90.4203125, 91.215625, 91.8671875, 92.121875, 92.8203125, 93.2171875, 92.90625, 94.13125, 94.3296875, 94.3140625, 94.478125, 94.425, 94.4984375, 94.8828125, 94.784375, 95.05625, 94.3578125, 95.01875, 94.2265625]\n",
            "Early stopping!\n",
            "              precision    recall  f1-score   support\n",
            "\n",
            "      benign       0.91      0.98      0.94     32052\n",
            "         dga       0.98      0.90      0.94     31948\n",
            "\n",
            "    accuracy                           0.94     64000\n",
            "   macro avg       0.95      0.94      0.94     64000\n",
            "weighted avg       0.94      0.94      0.94     64000\n",
            "\n"
          ],
          "name": "stdout"
        },
        {
          "output_type": "stream",
          "text": [
            "2020-09-21 03:26:15,877 DEBUG pyplot.py(l:225) - Loaded backend module://ipykernel.pylab.backend_inline version unknown.\n"
          ],
          "name": "stderr"
        },
        {
          "output_type": "stream",
          "text": [
            "       0      1\n",
            "0  31460    592\n",
            "1   3103  28845\n",
            "CPU times: user 5h 41min 14s, sys: 26min 14s, total: 6h 7min 28s\n",
            "Wall time: 6h 8min 11s\n"
          ],
          "name": "stdout"
        }
      ]
    }
  ]
}