Milestone1-3ORG.ipynb

{
 "cells": [
  {
   "cell_type": "markdown",
   "metadata": {
    "id": "rhgpM92PMCd-"
   },
   "source": [
    "# Milestone 1: FL Intra-company\n",
    "\n",
    "Train a single model in a federated way for each company. This way, we keep the privacy of the data for each user and measure the performance of the model compared to the besalines of individual subjects and company."
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {
    "id": "rhgpM92PMCd-"
   },
   "source": [
    "# Scenario config with Flower\n",
    "\n",
    "Use of the 'simulation' module (version 0.18.0) which removes the scalability restrictions presented in previous versions\n",
    "\n",
    "It is necessary to install Flower with the 'simulation' extra"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 1,
   "metadata": {
    "colab": {
     "base_uri": "https://localhost:8080/"
    },
    "id": "BXG21C3dLj6i",
    "outputId": "f60586a0-3fc5-4801-919d-01977224a39b",
    "tags": []
   },
   "outputs": [],
   "source": [
    "# !pip install -U flwr[\"simulation\"]"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {
    "id": "tQk9ZzCBMf9r"
   },
   "source": [
    "Libraries"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 9,
   "metadata": {
    "id": "oKvjox6uMkhj"
   },
   "outputs": [],
   "source": [
    "import os\n",
    "import math\n",
    "\n",
    "# Make TensorFlow logs less verbose\n",
    "os.environ[\"TF_CPP_MIN_LOG_LEVEL\"] = \"3\"\n",
    "\n",
    "import flwr as fl\n",
    "import tensorflow as tf\n",
    "\n",
    "import numpy as np\n",
    "import pandas as pd\n",
    "from sklearn.preprocessing import StandardScaler\n",
    "from sklearn.model_selection import train_test_split\n",
    "from tensorflow.keras.utils import to_categorical\n",
    "\n",
    "from keras.models import Sequential\n",
    "from tensorflow.keras.layers import Dense, BatchNormalization\n",
    "from tensorflow.keras.optimizers import Adadelta\n",
    "\n",
    "from typing import Dict\n",
    "\n",
    "from flwr.common.logger import log\n",
    "from logging import INFO\n",
    "from csv import writer\n",
    "\n",
    "from numpy.random import seed\n",
    "from tensorflow.keras.utils import set_random_seed\n",
    "\n",
    "import matplotlib.pyplot as plt\n",
    "\n",
    "from tensorflow.keras.metrics import Precision, Recall, TrueNegatives, TruePositives, FalsePositives, FalseNegatives"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {
    "id": "30pJWfaTM_MC"
   },
   "source": [
    "Federated learning systems consist of a server and multiple clients.\n",
    "\n",
    "In Flower, we create clients by implementing subclasses of `flwr.client.Client` or `flwr.client.NumPyClient`.\n",
    "\n",
    "To implement the Flower client, we create a subclass of `flwr.client.NumPyClient` and implement the three methods `get_parameters`, `fit`, and `evaluate`:\n",
    "\n",
    "- `get_parameters`: Return the current local model parameters\n",
    "- `fit`: Receive model parameters from the server, train the model parameters on the local data, and return the (updated) model parameters to the server \n",
    "- `evaluate`: Received model parameters from the server, evaluate the model parameters on the local data, and return the evaluation result to the server\n",
    "\n",
    "We mentioned that our clients will use TensorFlow/Keras for the model training and evaluation. Keras models provide methods that make the implementation staightforward:\n",
    "- we can update the local model with server-provides parameters through `model.set_weights`\n",
    "- we can train/evaluate the model through `fit/evaluate`\n",
    "- we can get the updated model parameters through `model.get_weights`."
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 3,
   "metadata": {
    "id": "vE3mqBs0NHZi"
   },
   "outputs": [],
   "source": [
    "class FlowerClient(fl.client.NumPyClient):\n",
    "    def __init__(self, cid, model, x_train, y_train, x_val, y_val) -> None:\n",
    "        self.cid = cid\n",
    "        self.model = model\n",
    "        self.x_train, self.y_train = x_train, y_train\n",
    "        self.x_val, self.y_val = x_val, y_val\n",
    "\n",
    "    def get_parameters(self):\n",
    "        return self.model.get_weights()\n",
    "\n",
    "    def fit(self, parameters, config):\n",
    "        self.model.set_weights(parameters)\n",
    "        \n",
    "        seed(1)\n",
    "        set_random_seed(2)\n",
    "        \n",
    "        self.model.fit(self.x_train, self.y_train,\n",
    "                       epochs=int(config[\"epochs\"]),\n",
    "                       batch_size=32,\n",
    "                       verbose=0)\n",
    "        \n",
    "        return self.model.get_weights(), len(self.x_train), {}\n",
    "\n",
    "    def evaluate(self, parameters, config):\n",
    "        self.model.set_weights(parameters)\n",
    "        \n",
    "        loss, acc = self.model.evaluate(self.x_val, self.y_val, verbose=0)\n",
    "        \n",
    "        return loss, len(self.x_val), {\"accuracy\": acc, \"client\": self.cid}"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "Our class `FlowerClient` defines how local training/evaluation will be performed and allows Flower to call the local training/evaluation through `fit` and `evaluate`. Each instance of `FlowerClient` represents a *single client* in our federated learning system. \n",
    "\n",
    "Federated learning systems have multiple clients, so each client will be represented by its own instance of `FlowerClient`.\n",
    "- Flower calls `FlowerClient.fit` on the respective instance when the server selects a particular client for training \n",
    "- (and `FlowerClient.evaluate` for evaluation).\n",
    "\n",
    "In this notebook, we want to simulate a federated learning system with 21 clients on a single machine. This means that the server and all 21 clients will live on a single machine and share resources such as CPU, GPU, and memory. Having 21 clients would mean having 21 instances of `FlowerClient` im memory and 21 GRCP conections. **Doing this on a single machine can quickly exhaust the available memory resources, even if only a subset of these clients participates in a single round of federated learning.**\n",
    "\n",
    "In addition to the regular capabilities where server and clients run on multiple machines, **Flower therefore provides special simulation capabilities that create `FlowerClient` instances only when they are actually necessary for training or evaluation**.\n",
    "\n",
    "**To enable the Flower framework to create clients when necessary, we need to implement a function called `client_fn` that creates a `FlowerClient` instance on demand**. Flower calls `client_fn` whenever it needs an instance of one particular client to call `fit` **or** `evaluate` (those instances are usually discarded after use).\n",
    "- Clients are identified by a client ID, or short `cid`. The `cid` can be used, for example, to load different local data partitions for each client"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 4,
   "metadata": {},
   "outputs": [],
   "source": [
    "''' Load data from a particular client '''\n",
    "def prepare_model_data(client_file):\n",
    "    df = pd.read_csv(client_file)\n",
    "    \n",
    "    train, test = train_test_split(df, test_size=0.30, random_state=42)\n",
    "    \n",
    "    X_train = train[['psd_delta', 'psd_theta', 'psd_alpha', 'psd_beta', 'psd_gamma','eog_blinks', 'eog_var']]\n",
    "    X_test = test[['psd_delta', 'psd_theta', 'psd_alpha', 'psd_beta', 'psd_gamma','eog_blinks', 'eog_var']]\n",
    "    y_train = train['y_class']\n",
    "    y_test = test['y_class']\n",
    "    \n",
    "    scaler = StandardScaler()\n",
    "\n",
    "    X_train = scaler.fit_transform(X_train)\n",
    "    X_test = scaler.transform(X_test)\n",
    "    \n",
    "    return X_train, X_test, y_train, y_test"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 5,
   "metadata": {
    "id": "OtlBA2OFO0tf"
   },
   "outputs": [],
   "source": [
    "def client_fn(cid: str) -> fl.client.Client:\n",
    "    \n",
    "    # Model best hyperparameters (See notebook Milestone0-Optimization-Baseline)\n",
    "    neurons = 36\n",
    "    activation = \"relu\"\n",
    "    learning_rate = 0.180165\n",
    "    optimizer = Adadelta(learning_rate=learning_rate)\n",
    "\n",
    "    input_shape = (7,)\n",
    "\n",
    "    # Create model\n",
    "    model = Sequential()\n",
    "\n",
    "    model.add(Dense(neurons, input_shape=input_shape, activation=activation))\n",
    "\n",
    "    model.add(BatchNormalization())\n",
    "\n",
    "    model.add(Dense(neurons, activation=activation))\n",
    "    model.add(Dense(neurons, activation=activation))\n",
    "    model.add(Dense(neurons, activation=activation))\n",
    "\n",
    "    model.add(Dense(1, activation='sigmoid'))\n",
    "\n",
    "    model.compile(loss='binary_crossentropy', optimizer=optimizer, metrics=['accuracy'])\n",
    "\n",
    "    # Load data partition\n",
    "    base_path = \"./data/horizontal/\"\n",
    "    path = f\"{base_path}company_{(int(cid)%2)+1}/client_{cid}.csv\"\n",
    "    \n",
    "    x_train_cid, x_val_cid, y_train_cid, y_val_cid = prepare_model_data(path)\n",
    "\n",
    "    # Create and return client\n",
    "    return FlowerClient(cid, model, x_train_cid, y_train_cid, x_val_cid, y_val_cid)"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {
    "id": "6SVawWSgO48Q"
   },
   "source": [
    "We now have `FlowerClient` which defines client-side training and evaluation and `client_fn` which allows Flower to create `FlowerClient` instances whenever it needs to call `fit` or `evaluate` on one particular client.\n",
    "\n",
    "The next step is to define a custom strategy that will allow us to store aggregated weights, perform LOG tasks and to store the evaluation results for each round performed during the training process."
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 6,
   "metadata": {},
   "outputs": [],
   "source": [
    "class SaveModelStrategy(fl.server.strategy.FedAvg):\n",
    "    def aggregate_fit(self, rnd, results, failures):\n",
    "        aggregated_weights = super().aggregate_fit(rnd, results, failures)\n",
    "\n",
    "        return aggregated_weights\n",
    "\n",
    "    def aggregate_evaluate(self, rnd, results, failures):\n",
    "        super_result = super().aggregate_evaluate(rnd, results, failures)\n",
    "\n",
    "        log(\n",
    "            INFO,\n",
    "            f\"round-{rnd}-EVALUATION\"\n",
    "        )\n",
    "\n",
    "        accuracy = []\n",
    "        data = {}\n",
    "        for r in results:\n",
    "            acc = r[1].metrics[\"accuracy\"]\n",
    "            client = r[1].metrics[\"client\"]\n",
    "            data[client] = acc\n",
    "            accuracy.append(acc)\n",
    "\n",
    "        df = pd.DataFrame(data, index=[0], columns=sorted(data.keys()))\n",
    "        df.to_csv(f\"./results/milestone1-company_{company}.csv\", mode='a', index=False, header=False)\n",
    "        \n",
    "        log(\n",
    "            INFO,\n",
    "            sorted(data.items())\n",
    "        )\n",
    "        \n",
    "        np.array(accuracy)\n",
    "        log(\n",
    "            INFO,\n",
    "            f\"Aggregated accuracy: {np.mean(accuracy)} +- {np.std(accuracy)}\"\n",
    "        )\n",
    "        \n",
    "        return super_result"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "The last step is to start the actual simulation using `flwr.simulation.start_simulation`.\n",
    "\n",
    "The function `start_simulation` accepts a number of arguments, amongst them the `client_fn` used to create `FlowerClient` instances.\n",
    "- the clients IDs `clients_ids`\n",
    "- the number of rounds `num_rounds`\n",
    "- and the strategy. The strategy encapsulates the custom federated learning approach/algorithm that was implemented above."
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 7,
   "metadata": {},
   "outputs": [],
   "source": [
    "seed(1)\n",
    "set_random_seed(2)\n",
    "\n",
    "neurons = 36\n",
    "activation = \"relu\"\n",
    "learning_rate = 0.180165\n",
    "optimizer = Adadelta(learning_rate=learning_rate)\n",
    "\n",
    "input_shape = (7,)\n",
    "\n",
    "# Create model\n",
    "model = Sequential()\n",
    "\n",
    "model.add(Dense(neurons, input_shape=input_shape, activation=activation))\n",
    "\n",
    "model.add(BatchNormalization())\n",
    "\n",
    "model.add(Dense(neurons, activation=activation))\n",
    "model.add(Dense(neurons, activation=activation))\n",
    "model.add(Dense(neurons, activation=activation))\n",
    "\n",
    "model.add(Dense(1, activation='sigmoid'))\n",
    "\n",
    "model.compile(loss='binary_crossentropy', optimizer=optimizer, metrics=['accuracy'])\n",
    "\n",
    "# Get model weights as a list of NumPy ndarray's\n",
    "weights = model.get_weights()\n",
    "# Serialize ndarrays to `Parameters`\n",
    "parameters = fl.common.weights_to_parameters(weights)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 8,
   "metadata": {},
   "outputs": [],
   "source": [
    "# Parameter config for training from the server\n",
    "def fit_config(rnd: int) -> Dict[str, str]:\n",
    "    config = {\n",
    "        \"round\": str(rnd),\n",
    "        \"epochs\": str(1) \n",
    "    }\n",
    "    return config"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 15,
   "metadata": {
    "colab": {
     "base_uri": "https://localhost:8080/"
    },
    "collapsed": true,
    "id": "0Yxjysu5PM-A",
    "jupyter": {
     "outputs_hidden": true
    },
    "outputId": "cf5f1bab-0d94-4876-bd6a-cdb0652826ff",
    "tags": []
   },
   "outputs": [
    {
     "name": "stderr",
     "output_type": "stream",
     "text": [
      "INFO flower 2022-04-16 11:53:41,902 | app.py:144 | Ray initialized with resources: {'GPU': 1.0, 'object_store_memory': 5872093593.0, 'node:127.0.0.1': 1.0, 'CPU': 8.0, 'memory': 11744187188.0}\n",
      "INFO flower 2022-04-16 11:53:41,902 | app.py:153 | Starting Flower simulation running: {'num_rounds': 100}\n",
      "INFO flower 2022-04-16 11:53:41,903 | server.py:128 | Initializing global parameters\n",
      "INFO flower 2022-04-16 11:53:41,903 | server.py:323 | Using initial parameters provided by strategy\n",
      "INFO flower 2022-04-16 11:53:41,904 | server.py:130 | Evaluating initial parameters\n",
      "INFO flower 2022-04-16 11:53:41,904 | server.py:143 | FL starting\n",
      "DEBUG flower 2022-04-16 11:53:41,904 | server.py:265 | fit_round: strategy sampled 7 clients (out of 7)\n",
      "DEBUG flower 2022-04-16 11:53:50,210 | server.py:277 | fit_round received 7 results and 0 failures\n",
      "DEBUG flower 2022-04-16 11:53:50,226 | server.py:211 | evaluate_round: strategy sampled 7 clients (out of 7)\n"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "Saving round 1 aggregated_weights...\n"
     ]
    },
    {
     "name": "stderr",
     "output_type": "stream",
     "text": [
      "DEBUG flower 2022-04-16 11:53:51,948 | server.py:223 | evaluate_round received 7 results and 0 failures\n",
      "INFO flower 2022-04-16 11:53:51,949 | 2719366172.py:15 | round-1-EVALUATION\n",
      "INFO flower 2022-04-16 11:53:51,951 | 2719366172.py:31 | [(1, 0.9130434989929199), (2, 0.16470588743686676), (3, 0.6283524632453918), (4, 0.6147704720497131), (5, 0.6107784509658813), (8, 0.27969348430633545), (12, 0.6639344096183777)]\n",
      "INFO flower 2022-04-16 11:53:51,952 | 2719366172.py:37 | Aggregated accuracy: 0.5536112380879266 +- 0.23306524311036464\n",
      "DEBUG flower 2022-04-16 11:53:51,952 | server.py:265 | fit_round: strategy sampled 7 clients (out of 7)\n",
      "DEBUG flower 2022-04-16 11:53:56,613 | server.py:277 | fit_round received 7 results and 0 failures\n",
      "DEBUG flower 2022-04-16 11:53:56,629 | server.py:211 | evaluate_round: strategy sampled 7 clients (out of 7)\n"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "Saving round 2 aggregated_weights...\n"
     ]
    },
    {
     "name": "stderr",
     "output_type": "stream",
     "text": [
      "DEBUG flower 2022-04-16 11:53:58,517 | server.py:223 | evaluate_round received 7 results and 0 failures\n",
      "INFO flower 2022-04-16 11:53:58,517 | 2719366172.py:15 | round-2-EVALUATION\n",
      "INFO flower 2022-04-16 11:53:58,519 | 2719366172.py:31 | [(1, 0.8932806253433228), (2, 0.18431372940540314), (3, 0.6283524632453918), (4, 0.6127744317054749), (5, 0.6107784509658813), (8, 0.28352490067481995), (12, 0.6967213153839111)]\n",
      "INFO flower 2022-04-16 11:53:58,520 | 2719366172.py:37 | Aggregated accuracy: 0.5585351309606007 +- 0.2259481539255704\n",
      "DEBUG flower 2022-04-16 11:53:58,521 | server.py:265 | fit_round: strategy sampled 7 clients (out of 7)\n",
      "DEBUG flower 2022-04-16 11:54:03,223 | server.py:277 | fit_round received 7 results and 0 failures\n",
      "DEBUG flower 2022-04-16 11:54:03,238 | server.py:211 | evaluate_round: strategy sampled 7 clients (out of 7)\n"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "Saving round 3 aggregated_weights...\n"
     ]
    },
    {
     "name": "stderr",
     "output_type": "stream",
     "text": [
      "DEBUG flower 2022-04-16 11:54:04,996 | server.py:223 | evaluate_round received 7 results and 0 failures\n",
      "INFO flower 2022-04-16 11:54:04,997 | 2719366172.py:15 | round-3-EVALUATION\n",
      "INFO flower 2022-04-16 11:54:04,999 | 2719366172.py:31 | [(1, 0.8814229369163513), (2, 0.21960784494876862), (3, 0.6628352403640747), (4, 0.6207584738731384), (5, 0.6007984280586243), (8, 0.3409961760044098), (12, 0.7540983557701111)]\n",
      "INFO flower 2022-04-16 11:54:04,999 | 2719366172.py:37 | Aggregated accuracy: 0.5829310651336398 +- 0.21282679897605147\n",
      "DEBUG flower 2022-04-16 11:54:05,000 | server.py:265 | fit_round: strategy sampled 7 clients (out of 7)\n",
      "DEBUG flower 2022-04-16 11:54:09,653 | server.py:277 | fit_round received 7 results and 0 failures\n",
      "DEBUG flower 2022-04-16 11:54:09,669 | server.py:211 | evaluate_round: strategy sampled 7 clients (out of 7)\n"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "Saving round 4 aggregated_weights...\n"
     ]
    },
    {
     "name": "stderr",
     "output_type": "stream",
     "text": [
      "DEBUG flower 2022-04-16 11:54:11,386 | server.py:223 | evaluate_round received 7 results and 0 failures\n",
      "INFO flower 2022-04-16 11:54:11,386 | 2719366172.py:15 | round-4-EVALUATION\n",
      "INFO flower 2022-04-16 11:54:11,388 | 2719366172.py:31 | [(1, 0.8577075004577637), (2, 0.2862745225429535), (3, 0.6628352403640747), (4, 0.6367265582084656), (5, 0.6107784509658813), (8, 0.4099617004394531), (12, 0.7827869057655334)]\n",
      "INFO flower 2022-04-16 11:54:11,389 | 2719366172.py:37 | Aggregated accuracy: 0.6067244112491608 +- 0.18495528331587227\n",
      "DEBUG flower 2022-04-16 11:54:11,389 | server.py:265 | fit_round: strategy sampled 7 clients (out of 7)\n",
      "DEBUG flower 2022-04-16 11:54:15,982 | server.py:277 | fit_round received 7 results and 0 failures\n",
      "DEBUG flower 2022-04-16 11:54:15,997 | server.py:211 | evaluate_round: strategy sampled 7 clients (out of 7)\n"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "Saving round 5 aggregated_weights...\n"
     ]
    },
    {
     "name": "stderr",
     "output_type": "stream",
     "text": [
      "DEBUG flower 2022-04-16 11:54:17,814 | server.py:223 | evaluate_round received 7 results and 0 failures\n",
      "INFO flower 2022-04-16 11:54:17,814 | 2719366172.py:15 | round-5-EVALUATION\n",
      "INFO flower 2022-04-16 11:54:17,816 | 2719366172.py:31 | [(1, 0.7944663763046265), (2, 0.3333333432674408), (3, 0.6819923520088196), (4, 0.6407185792922974), (5, 0.6027944087982178), (8, 0.5210728049278259), (12, 0.7950819730758667)]\n",
      "INFO flower 2022-04-16 11:54:17,817 | 2719366172.py:37 | Aggregated accuracy: 0.6242085482392993 +- 0.15000044581847027\n",
      "DEBUG flower 2022-04-16 11:54:17,817 | server.py:265 | fit_round: strategy sampled 7 clients (out of 7)\n",
      "DEBUG flower 2022-04-16 11:54:22,496 | server.py:277 | fit_round received 7 results and 0 failures\n",
      "DEBUG flower 2022-04-16 11:54:22,511 | server.py:211 | evaluate_round: strategy sampled 7 clients (out of 7)\n"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "Saving round 6 aggregated_weights...\n"
     ]
    },
    {
     "name": "stderr",
     "output_type": "stream",
     "text": [
      "DEBUG flower 2022-04-16 11:54:24,214 | server.py:223 | evaluate_round received 7 results and 0 failures\n",
      "INFO flower 2022-04-16 11:54:24,215 | 2719366172.py:15 | round-6-EVALUATION\n",
      "INFO flower 2022-04-16 11:54:24,217 | 2719366172.py:31 | [(1, 0.695652186870575), (2, 0.4000000059604645), (3, 0.7088122367858887), (4, 0.682634711265564), (5, 0.628742516040802), (8, 0.5363984704017639), (12, 0.8442623019218445)]\n",
      "INFO flower 2022-04-16 11:54:24,218 | 2719366172.py:37 | Aggregated accuracy: 0.6423574898924146 +- 0.13081841129436766\n",
      "DEBUG flower 2022-04-16 11:54:24,218 | server.py:265 | fit_round: strategy sampled 7 clients (out of 7)\n",
      "DEBUG flower 2022-04-16 11:54:28,843 | server.py:277 | fit_round received 7 results and 0 failures\n",
      "DEBUG flower 2022-04-16 11:54:28,860 | server.py:211 | evaluate_round: strategy sampled 7 clients (out of 7)\n"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "Saving round 7 aggregated_weights...\n"
     ]
    },
    {
     "name": "stderr",
     "output_type": "stream",
     "text": [
      "DEBUG flower 2022-04-16 11:54:30,581 | server.py:223 | evaluate_round received 7 results and 0 failures\n",
      "INFO flower 2022-04-16 11:54:30,582 | 2719366172.py:15 | round-7-EVALUATION\n",
      "INFO flower 2022-04-16 11:54:30,584 | 2719366172.py:31 | [(1, 0.6324110627174377), (2, 0.4588235318660736), (3, 0.7088122367858887), (4, 0.7385229468345642), (5, 0.6686626672744751), (8, 0.5632184147834778), (12, 0.8565573692321777)]\n",
      "INFO flower 2022-04-16 11:54:30,585 | 2719366172.py:37 | Aggregated accuracy: 0.6610011756420135 +- 0.11823167837705646\n",
      "DEBUG flower 2022-04-16 11:54:30,585 | server.py:265 | fit_round: strategy sampled 7 clients (out of 7)\n",
      "DEBUG flower 2022-04-16 11:54:35,125 | server.py:277 | fit_round received 7 results and 0 failures\n",
      "DEBUG flower 2022-04-16 11:54:35,141 | server.py:211 | evaluate_round: strategy sampled 7 clients (out of 7)\n"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "Saving round 8 aggregated_weights...\n"
     ]
    },
    {
     "name": "stderr",
     "output_type": "stream",
     "text": [
      "DEBUG flower 2022-04-16 11:54:36,892 | server.py:223 | evaluate_round received 7 results and 0 failures\n",
      "INFO flower 2022-04-16 11:54:36,893 | 2719366172.py:15 | round-8-EVALUATION\n",
      "INFO flower 2022-04-16 11:54:36,895 | 2719366172.py:31 | [(1, 0.6007905006408691), (2, 0.5215686559677124), (3, 0.6896551847457886), (4, 0.7584830522537231), (5, 0.6926147937774658), (8, 0.5670498013496399), (12, 0.8852459192276001)]\n",
      "INFO flower 2022-04-16 11:54:36,895 | 2719366172.py:37 | Aggregated accuracy: 0.6736297011375427 +- 0.11488264225954635\n",
      "DEBUG flower 2022-04-16 11:54:36,896 | server.py:265 | fit_round: strategy sampled 7 clients (out of 7)\n",
      "DEBUG flower 2022-04-16 11:54:41,268 | server.py:277 | fit_round received 7 results and 0 failures\n",
      "DEBUG flower 2022-04-16 11:54:41,283 | server.py:211 | evaluate_round: strategy sampled 7 clients (out of 7)\n"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "Saving round 9 aggregated_weights...\n"
     ]
    },
    {
     "name": "stderr",
     "output_type": "stream",
     "text": [
      "DEBUG flower 2022-04-16 11:54:43,076 | server.py:223 | evaluate_round received 7 results and 0 failures\n",
      "INFO flower 2022-04-16 11:54:43,076 | 2719366172.py:15 | round-9-EVALUATION\n",
      "INFO flower 2022-04-16 11:54:43,079 | 2719366172.py:31 | [(1, 0.5810276865959167), (2, 0.5568627715110779), (3, 0.6819923520088196), (4, 0.7684630751609802), (5, 0.6986027956008911), (8, 0.5785440802574158), (12, 0.8975409865379333)]\n",
      "INFO flower 2022-04-16 11:54:43,079 | 2719366172.py:37 | Aggregated accuracy: 0.6804333925247192 +- 0.11386088922720537\n",
      "DEBUG flower 2022-04-16 11:54:43,079 | server.py:265 | fit_round: strategy sampled 7 clients (out of 7)\n",
      "DEBUG flower 2022-04-16 11:54:47,534 | server.py:277 | fit_round received 7 results and 0 failures\n",
      "DEBUG flower 2022-04-16 11:54:47,549 | server.py:211 | evaluate_round: strategy sampled 7 clients (out of 7)\n"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "Saving round 10 aggregated_weights...\n"
     ]
    },
    {
     "name": "stderr",
     "output_type": "stream",
     "text": [
      "DEBUG flower 2022-04-16 11:54:49,286 | server.py:223 | evaluate_round received 7 results and 0 failures\n",
      "INFO flower 2022-04-16 11:54:49,286 | 2719366172.py:15 | round-10-EVALUATION\n",
      "INFO flower 2022-04-16 11:54:49,289 | 2719366172.py:31 | [(1, 0.5652173757553101), (2, 0.5803921818733215), (3, 0.6743295192718506), (4, 0.7624750733375549), (5, 0.7025948166847229), (8, 0.5823754668235779), (12, 0.9057376980781555)]\n",
      "INFO flower 2022-04-16 11:54:49,289 | 2719366172.py:37 | Aggregated accuracy: 0.6818745902606419 +- 0.11395804069055826\n",
      "DEBUG flower 2022-04-16 11:54:49,290 | server.py:265 | fit_round: strategy sampled 7 clients (out of 7)\n",
      "DEBUG flower 2022-04-16 11:54:54,092 | server.py:277 | fit_round received 7 results and 0 failures\n",
      "DEBUG flower 2022-04-16 11:54:54,108 | server.py:211 | evaluate_round: strategy sampled 7 clients (out of 7)\n"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "Saving round 11 aggregated_weights...\n"
     ]
    },
    {
     "name": "stderr",
     "output_type": "stream",
     "text": [
      "DEBUG flower 2022-04-16 11:54:56,102 | server.py:223 | evaluate_round received 7 results and 0 failures\n",
      "INFO flower 2022-04-16 11:54:56,102 | 2719366172.py:15 | round-11-EVALUATION\n",
      "INFO flower 2022-04-16 11:54:56,104 | 2719366172.py:31 | [(1, 0.5612648129463196), (2, 0.6000000238418579), (3, 0.6781609058380127), (4, 0.7604790329933167), (5, 0.6926147937774658), (8, 0.5862069129943848), (12, 0.9139344096183777)]\n",
      "INFO flower 2022-04-16 11:54:56,105 | 2719366172.py:37 | Aggregated accuracy: 0.6846658417156765 +- 0.11370858209351996\n",
      "DEBUG flower 2022-04-16 11:54:56,105 | server.py:265 | fit_round: strategy sampled 7 clients (out of 7)\n",
      "DEBUG flower 2022-04-16 11:55:00,836 | server.py:277 | fit_round received 7 results and 0 failures\n",
      "DEBUG flower 2022-04-16 11:55:00,852 | server.py:211 | evaluate_round: strategy sampled 7 clients (out of 7)\n"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "Saving round 12 aggregated_weights...\n"
     ]
    },
    {
     "name": "stderr",
     "output_type": "stream",
     "text": [
      "DEBUG flower 2022-04-16 11:55:02,789 | server.py:223 | evaluate_round received 7 results and 0 failures\n",
      "INFO flower 2022-04-16 11:55:02,790 | 2719366172.py:15 | round-12-EVALUATION\n",
      "INFO flower 2022-04-16 11:55:02,792 | 2719366172.py:31 | [(1, 0.5573122501373291), (2, 0.5960784554481506), (3, 0.6819923520088196), (4, 0.7624750733375549), (5, 0.6966068148612976), (8, 0.5900382995605469), (12, 0.9098360538482666)]\n",
      "INFO flower 2022-04-16 11:55:02,792 | 2719366172.py:37 | Aggregated accuracy: 0.6849056141717094 +- 0.1133428849215779\n",
      "DEBUG flower 2022-04-16 11:55:02,793 | server.py:265 | fit_round: strategy sampled 7 clients (out of 7)\n",
      "DEBUG flower 2022-04-16 11:55:07,385 | server.py:277 | fit_round received 7 results and 0 failures\n",
      "DEBUG flower 2022-04-16 11:55:07,401 | server.py:211 | evaluate_round: strategy sampled 7 clients (out of 7)\n"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "Saving round 13 aggregated_weights...\n"
     ]
    },
    {
     "name": "stderr",
     "output_type": "stream",
     "text": [
      "DEBUG flower 2022-04-16 11:55:09,328 | server.py:223 | evaluate_round received 7 results and 0 failures\n",
      "INFO flower 2022-04-16 11:55:09,328 | 2719366172.py:15 | round-13-EVALUATION\n",
      "INFO flower 2022-04-16 11:55:09,330 | 2719366172.py:31 | [(1, 0.5612648129463196), (2, 0.6000000238418579), (3, 0.6819923520088196), (4, 0.7604790329933167), (5, 0.6966068148612976), (8, 0.5938697457313538), (12, 0.9098360538482666)]\n",
      "INFO flower 2022-04-16 11:55:09,331 | 2719366172.py:37 | Aggregated accuracy: 0.686292690890176 +- 0.11162470155860242\n",
      "DEBUG flower 2022-04-16 11:55:09,331 | server.py:265 | fit_round: strategy sampled 7 clients (out of 7)\n",
      "DEBUG flower 2022-04-16 11:55:13,724 | server.py:277 | fit_round received 7 results and 0 failures\n",
      "DEBUG flower 2022-04-16 11:55:13,740 | server.py:211 | evaluate_round: strategy sampled 7 clients (out of 7)\n"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "Saving round 14 aggregated_weights...\n"
     ]
    },
    {
     "name": "stderr",
     "output_type": "stream",
     "text": [
      "DEBUG flower 2022-04-16 11:55:15,454 | server.py:223 | evaluate_round received 7 results and 0 failures\n",
      "INFO flower 2022-04-16 11:55:15,455 | 2719366172.py:15 | round-14-EVALUATION\n",
      "INFO flower 2022-04-16 11:55:15,458 | 2719366172.py:31 | [(1, 0.5612648129463196), (2, 0.6117647290229797), (3, 0.6743295192718506), (4, 0.7604790329933167), (5, 0.7005987763404846), (8, 0.6091954112052917), (12, 0.9057376980781555)]\n",
      "INFO flower 2022-04-16 11:55:15,458 | 2719366172.py:37 | Aggregated accuracy: 0.6890528542654855 +- 0.10762670571104303\n",
      "DEBUG flower 2022-04-16 11:55:15,458 | server.py:265 | fit_round: strategy sampled 7 clients (out of 7)\n",
      "DEBUG flower 2022-04-16 11:55:20,099 | server.py:277 | fit_round received 7 results and 0 failures\n",
      "DEBUG flower 2022-04-16 11:55:20,114 | server.py:211 | evaluate_round: strategy sampled 7 clients (out of 7)\n"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "Saving round 15 aggregated_weights...\n"
     ]
    },
    {
     "name": "stderr",
     "output_type": "stream",
     "text": [
      "DEBUG flower 2022-04-16 11:55:21,902 | server.py:223 | evaluate_round received 7 results and 0 failures\n",
      "INFO flower 2022-04-16 11:55:21,902 | 2719366172.py:15 | round-15-EVALUATION\n",
      "INFO flower 2022-04-16 11:55:21,905 | 2719366172.py:31 | [(1, 0.5612648129463196), (2, 0.6313725709915161), (3, 0.6781609058380127), (4, 0.7604790329933167), (5, 0.7025948166847229), (8, 0.6513410210609436), (12, 0.9057376980781555)]\n",
      "INFO flower 2022-04-16 11:55:21,905 | 2719366172.py:37 | Aggregated accuracy: 0.6987072655132839 +- 0.10196817933838978\n",
      "DEBUG flower 2022-04-16 11:55:21,906 | server.py:265 | fit_round: strategy sampled 7 clients (out of 7)\n",
      "DEBUG flower 2022-04-16 11:55:26,473 | server.py:277 | fit_round received 7 results and 0 failures\n",
      "DEBUG flower 2022-04-16 11:55:26,489 | server.py:211 | evaluate_round: strategy sampled 7 clients (out of 7)\n"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "Saving round 16 aggregated_weights...\n"
     ]
    },
    {
     "name": "stderr",
     "output_type": "stream",
     "text": [
      "DEBUG flower 2022-04-16 11:55:28,308 | server.py:223 | evaluate_round received 7 results and 0 failures\n",
      "INFO flower 2022-04-16 11:55:28,309 | 2719366172.py:15 | round-16-EVALUATION\n",
      "INFO flower 2022-04-16 11:55:28,311 | 2719366172.py:31 | [(1, 0.5612648129463196), (2, 0.6274510025978088), (3, 0.6934865713119507), (4, 0.7604790329933167), (5, 0.7045907974243164), (8, 0.7203065156936646), (12, 0.9016393423080444)]\n",
      "INFO flower 2022-04-16 11:55:28,311 | 2719366172.py:37 | Aggregated accuracy: 0.7098882964679173 +- 0.0990081907533273\n",
      "DEBUG flower 2022-04-16 11:55:28,312 | server.py:265 | fit_round: strategy sampled 7 clients (out of 7)\n",
      "DEBUG flower 2022-04-16 11:55:32,852 | server.py:277 | fit_round received 7 results and 0 failures\n",
      "DEBUG flower 2022-04-16 11:55:32,867 | server.py:211 | evaluate_round: strategy sampled 7 clients (out of 7)\n"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "Saving round 17 aggregated_weights...\n"
     ]
    },
    {
     "name": "stderr",
     "output_type": "stream",
     "text": [
      "DEBUG flower 2022-04-16 11:55:34,564 | server.py:223 | evaluate_round received 7 results and 0 failures\n",
      "INFO flower 2022-04-16 11:55:34,564 | 2719366172.py:15 | round-17-EVALUATION\n",
      "INFO flower 2022-04-16 11:55:34,567 | 2719366172.py:31 | [(1, 0.573122501373291), (2, 0.6352941393852234), (3, 0.6934865713119507), (4, 0.7604790329933167), (5, 0.71856290102005), (8, 0.7356321811676025), (12, 0.8975409865379333)]\n",
      "INFO flower 2022-04-16 11:55:34,567 | 2719366172.py:37 | Aggregated accuracy: 0.716302616255624 +- 0.09468831135793786\n",
      "DEBUG flower 2022-04-16 11:55:34,568 | server.py:265 | fit_round: strategy sampled 7 clients (out of 7)\n",
      "DEBUG flower 2022-04-16 11:55:39,153 | server.py:277 | fit_round received 7 results and 0 failures\n",
      "DEBUG flower 2022-04-16 11:55:39,170 | server.py:211 | evaluate_round: strategy sampled 7 clients (out of 7)\n"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "Saving round 18 aggregated_weights...\n"
     ]
    },
    {
     "name": "stderr",
     "output_type": "stream",
     "text": [
      "DEBUG flower 2022-04-16 11:55:40,922 | server.py:223 | evaluate_round received 7 results and 0 failures\n",
      "INFO flower 2022-04-16 11:55:40,923 | 2719366172.py:15 | round-18-EVALUATION\n",
      "INFO flower 2022-04-16 11:55:40,925 | 2719366172.py:31 | [(1, 0.5770751237869263), (2, 0.6313725709915161), (3, 0.6858237385749817), (4, 0.7624750733375549), (5, 0.7225548624992371), (8, 0.7394636273384094), (12, 0.8975409865379333)]\n",
      "INFO flower 2022-04-16 11:55:40,926 | 2719366172.py:37 | Aggregated accuracy: 0.7166151404380798 +- 0.09492888406278657\n",
      "DEBUG flower 2022-04-16 11:55:40,926 | server.py:265 | fit_round: strategy sampled 7 clients (out of 7)\n",
      "DEBUG flower 2022-04-16 11:55:45,816 | server.py:277 | fit_round received 7 results and 0 failures\n",
      "DEBUG flower 2022-04-16 11:55:45,832 | server.py:211 | evaluate_round: strategy sampled 7 clients (out of 7)\n"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "Saving round 19 aggregated_weights...\n"
     ]
    },
    {
     "name": "stderr",
     "output_type": "stream",
     "text": [
      "DEBUG flower 2022-04-16 11:55:47,563 | server.py:223 | evaluate_round received 7 results and 0 failures\n",
      "INFO flower 2022-04-16 11:55:47,563 | 2719366172.py:15 | round-19-EVALUATION\n",
      "INFO flower 2022-04-16 11:55:47,566 | 2719366172.py:31 | [(1, 0.5849802494049072), (2, 0.6431372761726379), (3, 0.6781609058380127), (4, 0.7684630751609802), (5, 0.7265468835830688), (8, 0.7356321811676025), (12, 0.8934426307678223)]\n",
      "INFO flower 2022-04-16 11:55:47,566 | 2719366172.py:37 | Aggregated accuracy: 0.7186233145850045 +- 0.09149059039870396\n",
      "DEBUG flower 2022-04-16 11:55:47,567 | server.py:265 | fit_round: strategy sampled 7 clients (out of 7)\n",
      "DEBUG flower 2022-04-16 11:55:52,180 | server.py:277 | fit_round received 7 results and 0 failures\n",
      "DEBUG flower 2022-04-16 11:55:52,195 | server.py:211 | evaluate_round: strategy sampled 7 clients (out of 7)\n"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "Saving round 20 aggregated_weights...\n"
     ]
    },
    {
     "name": "stderr",
     "output_type": "stream",
     "text": [
      "DEBUG flower 2022-04-16 11:55:54,031 | server.py:223 | evaluate_round received 7 results and 0 failures\n",
      "INFO flower 2022-04-16 11:55:54,032 | 2719366172.py:15 | round-20-EVALUATION\n",
      "INFO flower 2022-04-16 11:55:54,034 | 2719366172.py:31 | [(1, 0.5889328122138977), (2, 0.6509804129600525), (3, 0.6743295192718506), (4, 0.7644710540771484), (5, 0.7325349450111389), (8, 0.7203065156936646), (12, 0.8893442749977112)]\n",
      "INFO flower 2022-04-16 11:55:54,035 | 2719366172.py:37 | Aggregated accuracy: 0.7172713620322091 +- 0.08846981937901074\n",
      "DEBUG flower 2022-04-16 11:55:54,035 | server.py:265 | fit_round: strategy sampled 7 clients (out of 7)\n",
      "DEBUG flower 2022-04-16 11:55:58,603 | server.py:277 | fit_round received 7 results and 0 failures\n",
      "DEBUG flower 2022-04-16 11:55:58,618 | server.py:211 | evaluate_round: strategy sampled 7 clients (out of 7)\n"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "Saving round 21 aggregated_weights...\n"
     ]
    },
    {
     "name": "stderr",
     "output_type": "stream",
     "text": [
      "DEBUG flower 2022-04-16 11:56:00,353 | server.py:223 | evaluate_round received 7 results and 0 failures\n",
      "INFO flower 2022-04-16 11:56:00,353 | 2719366172.py:15 | round-21-EVALUATION\n",
      "INFO flower 2022-04-16 11:56:00,356 | 2719366172.py:31 | [(1, 0.5928853750228882), (2, 0.658823549747467), (3, 0.6743295192718506), (4, 0.7624750733375549), (5, 0.7405189871788025), (8, 0.7126436829566956), (12, 0.8852459192276001)]\n",
      "INFO flower 2022-04-16 11:56:00,356 | 2719366172.py:37 | Aggregated accuracy: 0.7181317295346942 +- 0.08581336528310612\n",
      "DEBUG flower 2022-04-16 11:56:00,357 | server.py:265 | fit_round: strategy sampled 7 clients (out of 7)\n",
      "DEBUG flower 2022-04-16 11:56:05,068 | server.py:277 | fit_round received 7 results and 0 failures\n",
      "DEBUG flower 2022-04-16 11:56:05,083 | server.py:211 | evaluate_round: strategy sampled 7 clients (out of 7)\n"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "Saving round 22 aggregated_weights...\n"
     ]
    },
    {
     "name": "stderr",
     "output_type": "stream",
     "text": [
      "DEBUG flower 2022-04-16 11:56:06,819 | server.py:223 | evaluate_round received 7 results and 0 failures\n",
      "INFO flower 2022-04-16 11:56:06,819 | 2719366172.py:15 | round-22-EVALUATION\n",
      "INFO flower 2022-04-16 11:56:06,822 | 2719366172.py:31 | [(1, 0.6007905006408691), (2, 0.658823549747467), (3, 0.6743295192718506), (4, 0.7644710540771484), (5, 0.742514967918396), (8, 0.7126436829566956), (12, 0.8852459192276001)]\n",
      "INFO flower 2022-04-16 11:56:06,822 | 2719366172.py:37 | Aggregated accuracy: 0.7198313134057182 +- 0.08441731718047386\n",
      "DEBUG flower 2022-04-16 11:56:06,822 | server.py:265 | fit_round: strategy sampled 7 clients (out of 7)\n",
      "DEBUG flower 2022-04-16 11:56:11,451 | server.py:277 | fit_round received 7 results and 0 failures\n",
      "DEBUG flower 2022-04-16 11:56:11,466 | server.py:211 | evaluate_round: strategy sampled 7 clients (out of 7)\n"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "Saving round 23 aggregated_weights...\n"
     ]
    },
    {
     "name": "stderr",
     "output_type": "stream",
     "text": [
      "DEBUG flower 2022-04-16 11:56:13,341 | server.py:223 | evaluate_round received 7 results and 0 failures\n",
      "INFO flower 2022-04-16 11:56:13,342 | 2719366172.py:15 | round-23-EVALUATION\n",
      "INFO flower 2022-04-16 11:56:13,344 | 2719366172.py:31 | [(1, 0.6007905006408691), (2, 0.6509804129600525), (3, 0.6743295192718506), (4, 0.7644710540771484), (5, 0.742514967918396), (8, 0.7088122367858887), (12, 0.8852459192276001)]\n",
      "INFO flower 2022-04-16 11:56:13,345 | 2719366172.py:37 | Aggregated accuracy: 0.718163515840258 +- 0.08531686361716163\n",
      "DEBUG flower 2022-04-16 11:56:13,345 | server.py:265 | fit_round: strategy sampled 7 clients (out of 7)\n",
      "DEBUG flower 2022-04-16 11:56:17,957 | server.py:277 | fit_round received 7 results and 0 failures\n",
      "DEBUG flower 2022-04-16 11:56:17,972 | server.py:211 | evaluate_round: strategy sampled 7 clients (out of 7)\n"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "Saving round 24 aggregated_weights...\n"
     ]
    },
    {
     "name": "stderr",
     "output_type": "stream",
     "text": [
      "DEBUG flower 2022-04-16 11:56:19,875 | server.py:223 | evaluate_round received 7 results and 0 failures\n",
      "INFO flower 2022-04-16 11:56:19,876 | 2719366172.py:15 | round-24-EVALUATION\n",
      "INFO flower 2022-04-16 11:56:19,878 | 2719366172.py:31 | [(1, 0.6047430634498596), (2, 0.6470588445663452), (3, 0.6743295192718506), (4, 0.7644710540771484), (5, 0.7445109486579895), (8, 0.7126436829566956), (12, 0.8770492076873779)]\n",
      "INFO flower 2022-04-16 11:56:19,878 | 2719366172.py:37 | Aggregated accuracy: 0.7178294743810382 +- 0.08276853992493938\n",
      "DEBUG flower 2022-04-16 11:56:19,879 | server.py:265 | fit_round: strategy sampled 7 clients (out of 7)\n",
      "DEBUG flower 2022-04-16 11:56:24,709 | server.py:277 | fit_round received 7 results and 0 failures\n",
      "DEBUG flower 2022-04-16 11:56:24,725 | server.py:211 | evaluate_round: strategy sampled 7 clients (out of 7)\n"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "Saving round 25 aggregated_weights...\n"
     ]
    },
    {
     "name": "stderr",
     "output_type": "stream",
     "text": [
      "DEBUG flower 2022-04-16 11:56:26,379 | server.py:223 | evaluate_round received 7 results and 0 failures\n",
      "INFO flower 2022-04-16 11:56:26,380 | 2719366172.py:15 | round-25-EVALUATION\n",
      "INFO flower 2022-04-16 11:56:26,383 | 2719366172.py:31 | [(1, 0.6166008114814758), (2, 0.6392157077789307), (3, 0.6819923520088196), (4, 0.7644710540771484), (5, 0.742514967918396), (8, 0.7088122367858887), (12, 0.881147563457489)]\n",
      "INFO flower 2022-04-16 11:56:26,383 | 2719366172.py:37 | Aggregated accuracy: 0.719250670501164 +- 0.08214659942879529\n",
      "DEBUG flower 2022-04-16 11:56:26,384 | server.py:265 | fit_round: strategy sampled 7 clients (out of 7)\n",
      "DEBUG flower 2022-04-16 11:56:31,057 | server.py:277 | fit_round received 7 results and 0 failures\n",
      "DEBUG flower 2022-04-16 11:56:31,073 | server.py:211 | evaluate_round: strategy sampled 7 clients (out of 7)\n"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "Saving round 26 aggregated_weights...\n"
     ]
    },
    {
     "name": "stderr",
     "output_type": "stream",
     "text": [
      "DEBUG flower 2022-04-16 11:56:32,796 | server.py:223 | evaluate_round received 7 results and 0 failures\n",
      "INFO flower 2022-04-16 11:56:32,797 | 2719366172.py:15 | round-26-EVALUATION\n",
      "INFO flower 2022-04-16 11:56:32,799 | 2719366172.py:31 | [(1, 0.6166008114814758), (2, 0.6392157077789307), (3, 0.6819923520088196), (4, 0.7624750733375549), (5, 0.7465069890022278), (8, 0.7126436829566956), (12, 0.8852459192276001)]\n",
      "INFO flower 2022-04-16 11:56:32,800 | 2719366172.py:37 | Aggregated accuracy: 0.720668647970472 +- 0.08326037239014732\n",
      "DEBUG flower 2022-04-16 11:56:32,800 | server.py:265 | fit_round: strategy sampled 7 clients (out of 7)\n",
      "DEBUG flower 2022-04-16 11:56:37,444 | server.py:277 | fit_round received 7 results and 0 failures\n",
      "DEBUG flower 2022-04-16 11:56:37,460 | server.py:211 | evaluate_round: strategy sampled 7 clients (out of 7)\n"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "Saving round 27 aggregated_weights...\n"
     ]
    },
    {
     "name": "stderr",
     "output_type": "stream",
     "text": [
      "DEBUG flower 2022-04-16 11:56:39,298 | server.py:223 | evaluate_round received 7 results and 0 failures\n",
      "INFO flower 2022-04-16 11:56:39,298 | 2719366172.py:15 | round-27-EVALUATION\n",
      "INFO flower 2022-04-16 11:56:39,300 | 2719366172.py:31 | [(1, 0.6245059370994568), (2, 0.6352941393852234), (3, 0.6819923520088196), (4, 0.7604790329933167), (5, 0.7504990100860596), (8, 0.7088122367858887), (12, 0.881147563457489)]\n",
      "INFO flower 2022-04-16 11:56:39,301 | 2719366172.py:37 | Aggregated accuracy: 0.7203900388308934 +- 0.08141617972567261\n",
      "DEBUG flower 2022-04-16 11:56:39,301 | server.py:265 | fit_round: strategy sampled 7 clients (out of 7)\n",
      "DEBUG flower 2022-04-16 11:56:43,965 | server.py:277 | fit_round received 7 results and 0 failures\n",
      "DEBUG flower 2022-04-16 11:56:43,981 | server.py:211 | evaluate_round: strategy sampled 7 clients (out of 7)\n"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "Saving round 28 aggregated_weights...\n"
     ]
    },
    {
     "name": "stderr",
     "output_type": "stream",
     "text": [
      "DEBUG flower 2022-04-16 11:56:45,683 | server.py:223 | evaluate_round received 7 results and 0 failures\n",
      "INFO flower 2022-04-16 11:56:45,684 | 2719366172.py:15 | round-28-EVALUATION\n",
      "INFO flower 2022-04-16 11:56:45,686 | 2719366172.py:31 | [(1, 0.6245059370994568), (2, 0.6313725709915161), (3, 0.6781609058380127), (4, 0.7584830522537231), (5, 0.7524949908256531), (8, 0.7126436829566956), (12, 0.881147563457489)]\n",
      "INFO flower 2022-04-16 11:56:45,687 | 2719366172.py:37 | Aggregated accuracy: 0.7198298147746495 +- 0.08218773512025035\n",
      "DEBUG flower 2022-04-16 11:56:45,687 | server.py:265 | fit_round: strategy sampled 7 clients (out of 7)\n",
      "DEBUG flower 2022-04-16 11:56:50,347 | server.py:277 | fit_round received 7 results and 0 failures\n",
      "DEBUG flower 2022-04-16 11:56:50,363 | server.py:211 | evaluate_round: strategy sampled 7 clients (out of 7)\n"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "Saving round 29 aggregated_weights...\n"
     ]
    },
    {
     "name": "stderr",
     "output_type": "stream",
     "text": [
      "DEBUG flower 2022-04-16 11:56:52,130 | server.py:223 | evaluate_round received 7 results and 0 failures\n",
      "INFO flower 2022-04-16 11:56:52,131 | 2719366172.py:15 | round-29-EVALUATION\n",
      "INFO flower 2022-04-16 11:56:52,133 | 2719366172.py:31 | [(1, 0.6245059370994568), (2, 0.6352941393852234), (3, 0.6743295192718506), (4, 0.7584830522537231), (5, 0.7524949908256531), (8, 0.7088122367858887), (12, 0.8770492076873779)]\n",
      "INFO flower 2022-04-16 11:56:52,134 | 2719366172.py:37 | Aggregated accuracy: 0.7187098690441677 +- 0.08079500518242007\n",
      "DEBUG flower 2022-04-16 11:56:52,134 | server.py:265 | fit_round: strategy sampled 7 clients (out of 7)\n",
      "DEBUG flower 2022-04-16 11:56:56,833 | server.py:277 | fit_round received 7 results and 0 failures\n",
      "DEBUG flower 2022-04-16 11:56:56,849 | server.py:211 | evaluate_round: strategy sampled 7 clients (out of 7)\n"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "Saving round 30 aggregated_weights...\n"
     ]
    },
    {
     "name": "stderr",
     "output_type": "stream",
     "text": [
      "DEBUG flower 2022-04-16 11:56:58,621 | server.py:223 | evaluate_round received 7 results and 0 failures\n",
      "INFO flower 2022-04-16 11:56:58,622 | 2719366172.py:15 | round-30-EVALUATION\n",
      "INFO flower 2022-04-16 11:56:58,624 | 2719366172.py:31 | [(1, 0.6245059370994568), (2, 0.6392157077789307), (3, 0.6781609058380127), (4, 0.7584830522537231), (5, 0.7544910311698914), (8, 0.7126436829566956), (12, 0.868852436542511)]\n",
      "INFO flower 2022-04-16 11:56:58,624 | 2719366172.py:37 | Aggregated accuracy: 0.719478964805603 +- 0.07771336268851814\n",
      "DEBUG flower 2022-04-16 11:56:58,625 | server.py:265 | fit_round: strategy sampled 7 clients (out of 7)\n",
      "DEBUG flower 2022-04-16 11:57:03,287 | server.py:277 | fit_round received 7 results and 0 failures\n",
      "DEBUG flower 2022-04-16 11:57:03,303 | server.py:211 | evaluate_round: strategy sampled 7 clients (out of 7)\n"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "Saving round 31 aggregated_weights...\n"
     ]
    },
    {
     "name": "stderr",
     "output_type": "stream",
     "text": [
      "DEBUG flower 2022-04-16 11:57:05,211 | server.py:223 | evaluate_round received 7 results and 0 failures\n",
      "INFO flower 2022-04-16 11:57:05,211 | 2719366172.py:15 | round-31-EVALUATION\n",
      "INFO flower 2022-04-16 11:57:05,213 | 2719366172.py:31 | [(1, 0.6324110627174377), (2, 0.6392157077789307), (3, 0.6743295192718506), (4, 0.7604790329933167), (5, 0.7544910311698914), (8, 0.7164750695228577), (12, 0.8729507923126221)]\n",
      "INFO flower 2022-04-16 11:57:05,214 | 2719366172.py:37 | Aggregated accuracy: 0.721478887966701 +- 0.07792208580528703\n",
      "DEBUG flower 2022-04-16 11:57:05,214 | server.py:265 | fit_round: strategy sampled 7 clients (out of 7)\n",
      "DEBUG flower 2022-04-16 11:57:10,000 | server.py:277 | fit_round received 7 results and 0 failures\n",
      "DEBUG flower 2022-04-16 11:57:10,015 | server.py:211 | evaluate_round: strategy sampled 7 clients (out of 7)\n"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "Saving round 32 aggregated_weights...\n"
     ]
    },
    {
     "name": "stderr",
     "output_type": "stream",
     "text": [
      "DEBUG flower 2022-04-16 11:57:11,713 | server.py:223 | evaluate_round received 7 results and 0 failures\n",
      "INFO flower 2022-04-16 11:57:11,714 | 2719366172.py:15 | round-32-EVALUATION\n",
      "INFO flower 2022-04-16 11:57:11,716 | 2719366172.py:31 | [(1, 0.6284584999084473), (2, 0.6431372761726379), (3, 0.6743295192718506), (4, 0.7644710540771484), (5, 0.7584830522537231), (8, 0.7203065156936646), (12, 0.8729507923126221)]\n",
      "INFO flower 2022-04-16 11:57:11,717 | 2719366172.py:37 | Aggregated accuracy: 0.7231623870985848 +- 0.0785185795123031\n",
      "DEBUG flower 2022-04-16 11:57:11,717 | server.py:265 | fit_round: strategy sampled 7 clients (out of 7)\n",
      "DEBUG flower 2022-04-16 11:57:16,316 | server.py:277 | fit_round received 7 results and 0 failures\n",
      "DEBUG flower 2022-04-16 11:57:16,331 | server.py:211 | evaluate_round: strategy sampled 7 clients (out of 7)\n"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "Saving round 33 aggregated_weights...\n"
     ]
    },
    {
     "name": "stderr",
     "output_type": "stream",
     "text": [
      "DEBUG flower 2022-04-16 11:57:18,052 | server.py:223 | evaluate_round received 7 results and 0 failures\n",
      "INFO flower 2022-04-16 11:57:18,052 | 2719366172.py:15 | round-33-EVALUATION\n",
      "INFO flower 2022-04-16 11:57:18,055 | 2719366172.py:31 | [(1, 0.6284584999084473), (2, 0.6392157077789307), (3, 0.6743295192718506), (4, 0.7664670944213867), (5, 0.7604790329933167), (8, 0.7203065156936646), (12, 0.8729507923126221)]\n",
      "INFO flower 2022-04-16 11:57:18,055 | 2719366172.py:37 | Aggregated accuracy: 0.7231724517686027 +- 0.07938430176229679\n",
      "DEBUG flower 2022-04-16 11:57:18,056 | server.py:265 | fit_round: strategy sampled 7 clients (out of 7)\n",
      "DEBUG flower 2022-04-16 11:57:22,689 | server.py:277 | fit_round received 7 results and 0 failures\n",
      "DEBUG flower 2022-04-16 11:57:22,705 | server.py:211 | evaluate_round: strategy sampled 7 clients (out of 7)\n"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "Saving round 34 aggregated_weights...\n"
     ]
    },
    {
     "name": "stderr",
     "output_type": "stream",
     "text": [
      "DEBUG flower 2022-04-16 11:57:24,558 | server.py:223 | evaluate_round received 7 results and 0 failures\n",
      "INFO flower 2022-04-16 11:57:24,558 | 2719366172.py:15 | round-34-EVALUATION\n",
      "INFO flower 2022-04-16 11:57:24,561 | 2719366172.py:31 | [(1, 0.6284584999084473), (2, 0.6470588445663452), (3, 0.6781609058380127), (4, 0.7704590559005737), (5, 0.7604790329933167), (8, 0.7203065156936646), (12, 0.8729507923126221)]\n",
      "INFO flower 2022-04-16 11:57:24,561 | 2719366172.py:37 | Aggregated accuracy: 0.725410521030426 +- 0.07821632939294505\n",
      "DEBUG flower 2022-04-16 11:57:24,561 | server.py:265 | fit_round: strategy sampled 7 clients (out of 7)\n",
      "DEBUG flower 2022-04-16 11:57:29,078 | server.py:277 | fit_round received 7 results and 0 failures\n",
      "DEBUG flower 2022-04-16 11:57:29,094 | server.py:211 | evaluate_round: strategy sampled 7 clients (out of 7)\n"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "Saving round 35 aggregated_weights...\n"
     ]
    },
    {
     "name": "stderr",
     "output_type": "stream",
     "text": [
      "DEBUG flower 2022-04-16 11:57:30,981 | server.py:223 | evaluate_round received 7 results and 0 failures\n",
      "INFO flower 2022-04-16 11:57:30,982 | 2719366172.py:15 | round-35-EVALUATION\n",
      "INFO flower 2022-04-16 11:57:30,984 | 2719366172.py:31 | [(1, 0.6284584999084473), (2, 0.6470588445663452), (3, 0.6819923520088196), (4, 0.772455096244812), (5, 0.7704590559005737), (8, 0.7241379022598267), (12, 0.8729507923126221)]\n",
      "INFO flower 2022-04-16 11:57:30,985 | 2719366172.py:37 | Aggregated accuracy: 0.7282160776002067 +- 0.07872287082045828\n",
      "DEBUG flower 2022-04-16 11:57:30,985 | server.py:265 | fit_round: strategy sampled 7 clients (out of 7)\n",
      "DEBUG flower 2022-04-16 11:57:35,600 | server.py:277 | fit_round received 7 results and 0 failures\n",
      "DEBUG flower 2022-04-16 11:57:35,616 | server.py:211 | evaluate_round: strategy sampled 7 clients (out of 7)\n"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "Saving round 36 aggregated_weights...\n"
     ]
    },
    {
     "name": "stderr",
     "output_type": "stream",
     "text": [
      "DEBUG flower 2022-04-16 11:57:37,379 | server.py:223 | evaluate_round received 7 results and 0 failures\n",
      "INFO flower 2022-04-16 11:57:37,379 | 2719366172.py:15 | round-36-EVALUATION\n",
      "INFO flower 2022-04-16 11:57:37,382 | 2719366172.py:31 | [(1, 0.6284584999084473), (2, 0.6470588445663452), (3, 0.6819923520088196), (4, 0.7684630751609802), (5, 0.7704590559005737), (8, 0.7203065156936646), (12, 0.8729507923126221)]\n",
      "INFO flower 2022-04-16 11:57:37,383 | 2719366172.py:37 | Aggregated accuracy: 0.7270984479359218 +- 0.0784501195086973\n",
      "DEBUG flower 2022-04-16 11:57:37,383 | server.py:265 | fit_round: strategy sampled 7 clients (out of 7)\n",
      "DEBUG flower 2022-04-16 11:57:42,112 | server.py:277 | fit_round received 7 results and 0 failures\n",
      "DEBUG flower 2022-04-16 11:57:42,127 | server.py:211 | evaluate_round: strategy sampled 7 clients (out of 7)\n"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "Saving round 37 aggregated_weights...\n"
     ]
    },
    {
     "name": "stderr",
     "output_type": "stream",
     "text": [
      "DEBUG flower 2022-04-16 11:57:43,891 | server.py:223 | evaluate_round received 7 results and 0 failures\n",
      "INFO flower 2022-04-16 11:57:43,891 | 2719366172.py:15 | round-37-EVALUATION\n",
      "INFO flower 2022-04-16 11:57:43,894 | 2719366172.py:31 | [(1, 0.6324110627174377), (2, 0.6431372761726379), (3, 0.6858237385749817), (4, 0.7664670944213867), (5, 0.7684630751609802), (8, 0.7164750695228577), (12, 0.8729507923126221)]\n",
      "INFO flower 2022-04-16 11:57:43,894 | 2719366172.py:37 | Aggregated accuracy: 0.726532586983272 +- 0.07779388955671396\n",
      "DEBUG flower 2022-04-16 11:57:43,895 | server.py:265 | fit_round: strategy sampled 7 clients (out of 7)\n",
      "DEBUG flower 2022-04-16 11:57:48,697 | server.py:277 | fit_round received 7 results and 0 failures\n",
      "DEBUG flower 2022-04-16 11:57:48,712 | server.py:211 | evaluate_round: strategy sampled 7 clients (out of 7)\n"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "Saving round 38 aggregated_weights...\n"
     ]
    },
    {
     "name": "stderr",
     "output_type": "stream",
     "text": [
      "DEBUG flower 2022-04-16 11:57:50,636 | server.py:223 | evaluate_round received 7 results and 0 failures\n",
      "INFO flower 2022-04-16 11:57:50,636 | 2719366172.py:15 | round-38-EVALUATION\n",
      "INFO flower 2022-04-16 11:57:50,638 | 2719366172.py:31 | [(1, 0.6363636255264282), (2, 0.6470588445663452), (3, 0.6819923520088196), (4, 0.7684630751609802), (5, 0.772455096244812), (8, 0.7164750695228577), (12, 0.8729507923126221)]\n",
      "INFO flower 2022-04-16 11:57:50,639 | 2719366172.py:37 | Aggregated accuracy: 0.7279655507632664 +- 0.0772957801326504\n",
      "DEBUG flower 2022-04-16 11:57:50,639 | server.py:265 | fit_round: strategy sampled 7 clients (out of 7)\n",
      "DEBUG flower 2022-04-16 11:57:55,254 | server.py:277 | fit_round received 7 results and 0 failures\n",
      "DEBUG flower 2022-04-16 11:57:55,270 | server.py:211 | evaluate_round: strategy sampled 7 clients (out of 7)\n"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "Saving round 39 aggregated_weights...\n"
     ]
    },
    {
     "name": "stderr",
     "output_type": "stream",
     "text": [
      "DEBUG flower 2022-04-16 11:57:56,999 | server.py:223 | evaluate_round received 7 results and 0 failures\n",
      "INFO flower 2022-04-16 11:57:56,999 | 2719366172.py:15 | round-39-EVALUATION\n",
      "INFO flower 2022-04-16 11:57:57,001 | 2719366172.py:31 | [(1, 0.6363636255264282), (2, 0.6470588445663452), (3, 0.6819923520088196), (4, 0.7704590559005737), (5, 0.7764471173286438), (8, 0.7164750695228577), (12, 0.8729507923126221)]\n",
      "INFO flower 2022-04-16 11:57:57,002 | 2719366172.py:37 | Aggregated accuracy: 0.7288209795951843 +- 0.07778554053181774\n",
      "DEBUG flower 2022-04-16 11:57:57,002 | server.py:265 | fit_round: strategy sampled 7 clients (out of 7)\n",
      "DEBUG flower 2022-04-16 11:58:01,701 | server.py:277 | fit_round received 7 results and 0 failures\n",
      "DEBUG flower 2022-04-16 11:58:01,717 | server.py:211 | evaluate_round: strategy sampled 7 clients (out of 7)\n"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "Saving round 40 aggregated_weights...\n"
     ]
    },
    {
     "name": "stderr",
     "output_type": "stream",
     "text": [
      "DEBUG flower 2022-04-16 11:58:03,536 | server.py:223 | evaluate_round received 7 results and 0 failures\n",
      "INFO flower 2022-04-16 11:58:03,537 | 2719366172.py:15 | round-40-EVALUATION\n",
      "INFO flower 2022-04-16 11:58:03,539 | 2719366172.py:31 | [(1, 0.6403161883354187), (2, 0.6470588445663452), (3, 0.6819923520088196), (4, 0.772455096244812), (5, 0.7824351191520691), (8, 0.7164750695228577), (12, 0.8729507923126221)]\n",
      "INFO flower 2022-04-16 11:58:03,540 | 2719366172.py:37 | Aggregated accuracy: 0.7305262088775635 +- 0.07782301075369578\n",
      "DEBUG flower 2022-04-16 11:58:03,540 | server.py:265 | fit_round: strategy sampled 7 clients (out of 7)\n",
      "DEBUG flower 2022-04-16 11:58:08,274 | server.py:277 | fit_round received 7 results and 0 failures\n",
      "DEBUG flower 2022-04-16 11:58:08,290 | server.py:211 | evaluate_round: strategy sampled 7 clients (out of 7)\n"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "Saving round 41 aggregated_weights...\n"
     ]
    },
    {
     "name": "stderr",
     "output_type": "stream",
     "text": [
      "DEBUG flower 2022-04-16 11:58:09,984 | server.py:223 | evaluate_round received 7 results and 0 failures\n",
      "INFO flower 2022-04-16 11:58:09,985 | 2719366172.py:15 | round-41-EVALUATION\n",
      "INFO flower 2022-04-16 11:58:09,987 | 2719366172.py:31 | [(1, 0.6442687511444092), (2, 0.6431372761726379), (3, 0.6781609058380127), (4, 0.7704590559005737), (5, 0.7804391384124756), (8, 0.7203065156936646), (12, 0.8729507923126221)]\n",
      "INFO flower 2022-04-16 11:58:09,987 | 2719366172.py:37 | Aggregated accuracy: 0.7299603479249137 +- 0.07772864433172624\n",
      "DEBUG flower 2022-04-16 11:58:09,988 | server.py:265 | fit_round: strategy sampled 7 clients (out of 7)\n",
      "DEBUG flower 2022-04-16 11:58:14,729 | server.py:277 | fit_round received 7 results and 0 failures\n",
      "DEBUG flower 2022-04-16 11:58:14,745 | server.py:211 | evaluate_round: strategy sampled 7 clients (out of 7)\n"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "Saving round 42 aggregated_weights...\n"
     ]
    },
    {
     "name": "stderr",
     "output_type": "stream",
     "text": [
      "DEBUG flower 2022-04-16 11:58:16,601 | server.py:223 | evaluate_round received 7 results and 0 failures\n",
      "INFO flower 2022-04-16 11:58:16,602 | 2719366172.py:15 | round-42-EVALUATION\n",
      "INFO flower 2022-04-16 11:58:16,604 | 2719366172.py:31 | [(1, 0.6442687511444092), (2, 0.6431372761726379), (3, 0.6781609058380127), (4, 0.7704590559005737), (5, 0.7784430980682373), (8, 0.7241379022598267), (12, 0.8729507923126221)]\n",
      "INFO flower 2022-04-16 11:58:16,605 | 2719366172.py:37 | Aggregated accuracy: 0.7302225402423314 +- 0.07749183090863132\n",
      "DEBUG flower 2022-04-16 11:58:16,605 | server.py:265 | fit_round: strategy sampled 7 clients (out of 7)\n",
      "DEBUG flower 2022-04-16 11:58:21,250 | server.py:277 | fit_round received 7 results and 0 failures\n",
      "DEBUG flower 2022-04-16 11:58:21,266 | server.py:211 | evaluate_round: strategy sampled 7 clients (out of 7)\n"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "Saving round 43 aggregated_weights...\n"
     ]
    },
    {
     "name": "stderr",
     "output_type": "stream",
     "text": [
      "DEBUG flower 2022-04-16 11:58:23,025 | server.py:223 | evaluate_round received 7 results and 0 failures\n",
      "INFO flower 2022-04-16 11:58:23,025 | 2719366172.py:15 | round-43-EVALUATION\n",
      "INFO flower 2022-04-16 11:58:23,028 | 2719366172.py:31 | [(1, 0.6442687511444092), (2, 0.6392157077789307), (3, 0.6743295192718506), (4, 0.7684630751609802), (5, 0.7804391384124756), (8, 0.7203065156936646), (12, 0.8729507923126221)]\n",
      "INFO flower 2022-04-16 11:58:23,028 | 2719366172.py:37 | Aggregated accuracy: 0.7285676428249904 +- 0.07858469783326691\n",
      "DEBUG flower 2022-04-16 11:58:23,029 | server.py:265 | fit_round: strategy sampled 7 clients (out of 7)\n",
      "DEBUG flower 2022-04-16 11:58:27,775 | server.py:277 | fit_round received 7 results and 0 failures\n",
      "DEBUG flower 2022-04-16 11:58:27,791 | server.py:211 | evaluate_round: strategy sampled 7 clients (out of 7)\n"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "Saving round 44 aggregated_weights...\n"
     ]
    },
    {
     "name": "stderr",
     "output_type": "stream",
     "text": [
      "DEBUG flower 2022-04-16 11:58:29,474 | server.py:223 | evaluate_round received 7 results and 0 failures\n",
      "INFO flower 2022-04-16 11:58:29,475 | 2719366172.py:15 | round-44-EVALUATION\n",
      "INFO flower 2022-04-16 11:58:29,477 | 2719366172.py:31 | [(1, 0.6403161883354187), (2, 0.6392157077789307), (3, 0.6743295192718506), (4, 0.7684630751609802), (5, 0.7804391384124756), (8, 0.7164750695228577), (12, 0.8729507923126221)]\n",
      "INFO flower 2022-04-16 11:58:29,478 | 2719366172.py:37 | Aggregated accuracy: 0.7274556415421622 +- 0.07926468092535477\n",
      "DEBUG flower 2022-04-16 11:58:29,478 | server.py:265 | fit_round: strategy sampled 7 clients (out of 7)\n",
      "DEBUG flower 2022-04-16 11:58:34,181 | server.py:277 | fit_round received 7 results and 0 failures\n",
      "DEBUG flower 2022-04-16 11:58:34,197 | server.py:211 | evaluate_round: strategy sampled 7 clients (out of 7)\n"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "Saving round 45 aggregated_weights...\n"
     ]
    },
    {
     "name": "stderr",
     "output_type": "stream",
     "text": [
      "DEBUG flower 2022-04-16 11:58:35,911 | server.py:223 | evaluate_round received 7 results and 0 failures\n",
      "INFO flower 2022-04-16 11:58:35,911 | 2719366172.py:15 | round-45-EVALUATION\n",
      "INFO flower 2022-04-16 11:58:35,913 | 2719366172.py:31 | [(1, 0.6403161883354187), (2, 0.6392157077789307), (3, 0.6781609058380127), (4, 0.7664670944213867), (5, 0.7824351191520691), (8, 0.7126436829566956), (12, 0.8647540807723999)]\n",
      "INFO flower 2022-04-16 11:58:35,914 | 2719366172.py:37 | Aggregated accuracy: 0.7262846827507019 +- 0.07691817091523363\n",
      "DEBUG flower 2022-04-16 11:58:35,914 | server.py:265 | fit_round: strategy sampled 7 clients (out of 7)\n",
      "DEBUG flower 2022-04-16 11:58:40,783 | server.py:277 | fit_round received 7 results and 0 failures\n",
      "DEBUG flower 2022-04-16 11:58:40,799 | server.py:211 | evaluate_round: strategy sampled 7 clients (out of 7)\n"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "Saving round 46 aggregated_weights...\n"
     ]
    },
    {
     "name": "stderr",
     "output_type": "stream",
     "text": [
      "DEBUG flower 2022-04-16 11:58:42,581 | server.py:223 | evaluate_round received 7 results and 0 failures\n",
      "INFO flower 2022-04-16 11:58:42,581 | 2719366172.py:15 | round-46-EVALUATION\n",
      "INFO flower 2022-04-16 11:58:42,584 | 2719366172.py:31 | [(1, 0.6403161883354187), (2, 0.6352941393852234), (3, 0.6781609058380127), (4, 0.7644710540771484), (5, 0.7824351191520691), (8, 0.7164750695228577), (12, 0.8565573692321777)]\n",
      "INFO flower 2022-04-16 11:58:42,584 | 2719366172.py:37 | Aggregated accuracy: 0.7248156922204154 +- 0.07526042899159976\n",
      "DEBUG flower 2022-04-16 11:58:42,585 | server.py:265 | fit_round: strategy sampled 7 clients (out of 7)\n",
      "DEBUG flower 2022-04-16 11:58:47,148 | server.py:277 | fit_round received 7 results and 0 failures\n",
      "DEBUG flower 2022-04-16 11:58:47,164 | server.py:211 | evaluate_round: strategy sampled 7 clients (out of 7)\n"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "Saving round 47 aggregated_weights...\n"
     ]
    },
    {
     "name": "stderr",
     "output_type": "stream",
     "text": [
      "DEBUG flower 2022-04-16 11:58:48,906 | server.py:223 | evaluate_round received 7 results and 0 failures\n",
      "INFO flower 2022-04-16 11:58:48,906 | 2719366172.py:15 | round-47-EVALUATION\n",
      "INFO flower 2022-04-16 11:58:48,909 | 2719366172.py:31 | [(1, 0.6403161883354187), (2, 0.6352941393852234), (3, 0.6781609058380127), (4, 0.7624750733375549), (5, 0.7804391384124756), (8, 0.7164750695228577), (12, 0.8524590134620667)]\n",
      "INFO flower 2022-04-16 11:58:48,909 | 2719366172.py:37 | Aggregated accuracy: 0.7236599326133728 +- 0.07386877690136626\n",
      "DEBUG flower 2022-04-16 11:58:48,910 | server.py:265 | fit_round: strategy sampled 7 clients (out of 7)\n",
      "DEBUG flower 2022-04-16 11:58:53,578 | server.py:277 | fit_round received 7 results and 0 failures\n",
      "DEBUG flower 2022-04-16 11:58:53,594 | server.py:211 | evaluate_round: strategy sampled 7 clients (out of 7)\n"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "Saving round 48 aggregated_weights...\n"
     ]
    },
    {
     "name": "stderr",
     "output_type": "stream",
     "text": [
      "DEBUG flower 2022-04-16 11:58:55,307 | server.py:223 | evaluate_round received 7 results and 0 failures\n",
      "INFO flower 2022-04-16 11:58:55,308 | 2719366172.py:15 | round-48-EVALUATION\n",
      "INFO flower 2022-04-16 11:58:55,310 | 2719366172.py:31 | [(1, 0.6363636255264282), (2, 0.6352941393852234), (3, 0.6781609058380127), (4, 0.7624750733375549), (5, 0.7784430980682373), (8, 0.7203065156936646), (12, 0.8483606576919556)]\n",
      "INFO flower 2022-04-16 11:58:55,310 | 2719366172.py:37 | Aggregated accuracy: 0.7227720022201538 +- 0.07325408593727091\n",
      "DEBUG flower 2022-04-16 11:58:55,311 | server.py:265 | fit_round: strategy sampled 7 clients (out of 7)\n",
      "DEBUG flower 2022-04-16 11:58:59,982 | server.py:277 | fit_round received 7 results and 0 failures\n",
      "DEBUG flower 2022-04-16 11:58:59,998 | server.py:211 | evaluate_round: strategy sampled 7 clients (out of 7)\n"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "Saving round 49 aggregated_weights...\n"
     ]
    },
    {
     "name": "stderr",
     "output_type": "stream",
     "text": [
      "DEBUG flower 2022-04-16 11:59:01,755 | server.py:223 | evaluate_round received 7 results and 0 failures\n",
      "INFO flower 2022-04-16 11:59:01,755 | 2719366172.py:15 | round-49-EVALUATION\n",
      "INFO flower 2022-04-16 11:59:01,758 | 2719366172.py:31 | [(1, 0.6403161883354187), (2, 0.6352941393852234), (3, 0.6781609058380127), (4, 0.7644710540771484), (5, 0.7804391384124756), (8, 0.7241379022598267), (12, 0.8442623019218445)]\n",
      "INFO flower 2022-04-16 11:59:01,758 | 2719366172.py:37 | Aggregated accuracy: 0.7238688043185643 +- 0.07197135834383526\n",
      "DEBUG flower 2022-04-16 11:59:01,758 | server.py:265 | fit_round: strategy sampled 7 clients (out of 7)\n",
      "DEBUG flower 2022-04-16 11:59:06,412 | server.py:277 | fit_round received 7 results and 0 failures\n",
      "DEBUG flower 2022-04-16 11:59:06,428 | server.py:211 | evaluate_round: strategy sampled 7 clients (out of 7)\n"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "Saving round 50 aggregated_weights...\n"
     ]
    },
    {
     "name": "stderr",
     "output_type": "stream",
     "text": [
      "DEBUG flower 2022-04-16 11:59:08,275 | server.py:223 | evaluate_round received 7 results and 0 failures\n",
      "INFO flower 2022-04-16 11:59:08,276 | 2719366172.py:15 | round-50-EVALUATION\n",
      "INFO flower 2022-04-16 11:59:08,278 | 2719366172.py:31 | [(1, 0.6403161883354187), (2, 0.6352941393852234), (3, 0.6704980731010437), (4, 0.7664670944213867), (5, 0.7804391384124756), (8, 0.7241379022598267), (12, 0.8442623019218445)]\n",
      "INFO flower 2022-04-16 11:59:08,278 | 2719366172.py:37 | Aggregated accuracy: 0.7230592625481742 +- 0.07287939356935771\n",
      "DEBUG flower 2022-04-16 11:59:08,279 | server.py:265 | fit_round: strategy sampled 7 clients (out of 7)\n",
      "DEBUG flower 2022-04-16 11:59:12,895 | server.py:277 | fit_round received 7 results and 0 failures\n",
      "DEBUG flower 2022-04-16 11:59:12,919 | server.py:211 | evaluate_round: strategy sampled 7 clients (out of 7)\n"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "Saving round 51 aggregated_weights...\n"
     ]
    },
    {
     "name": "stderr",
     "output_type": "stream",
     "text": [
      "DEBUG flower 2022-04-16 11:59:14,648 | server.py:223 | evaluate_round received 7 results and 0 failures\n",
      "INFO flower 2022-04-16 11:59:14,648 | 2719366172.py:15 | round-51-EVALUATION\n",
      "INFO flower 2022-04-16 11:59:14,651 | 2719366172.py:31 | [(1, 0.6363636255264282), (2, 0.6392157077789307), (3, 0.6704980731010437), (4, 0.7684630751609802), (5, 0.7784430980682373), (8, 0.7241379022598267), (12, 0.8442623019218445)]\n",
      "INFO flower 2022-04-16 11:59:14,651 | 2719366172.py:37 | Aggregated accuracy: 0.723054826259613 +- 0.07282932033873764\n",
      "DEBUG flower 2022-04-16 11:59:14,652 | server.py:265 | fit_round: strategy sampled 7 clients (out of 7)\n",
      "DEBUG flower 2022-04-16 11:59:19,296 | server.py:277 | fit_round received 7 results and 0 failures\n",
      "DEBUG flower 2022-04-16 11:59:19,312 | server.py:211 | evaluate_round: strategy sampled 7 clients (out of 7)\n"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "Saving round 52 aggregated_weights...\n"
     ]
    },
    {
     "name": "stderr",
     "output_type": "stream",
     "text": [
      "DEBUG flower 2022-04-16 11:59:21,075 | server.py:223 | evaluate_round received 7 results and 0 failures\n",
      "INFO flower 2022-04-16 11:59:21,076 | 2719366172.py:15 | round-52-EVALUATION\n",
      "INFO flower 2022-04-16 11:59:21,078 | 2719366172.py:31 | [(1, 0.6324110627174377), (2, 0.6392157077789307), (3, 0.6704980731010437), (4, 0.7684630751609802), (5, 0.7764471173286438), (8, 0.7279693484306335), (12, 0.8483606576919556)]\n",
      "INFO flower 2022-04-16 11:59:21,079 | 2719366172.py:37 | Aggregated accuracy: 0.7233378631728036 +- 0.07430178898348812\n",
      "DEBUG flower 2022-04-16 11:59:21,079 | server.py:265 | fit_round: strategy sampled 7 clients (out of 7)\n",
      "DEBUG flower 2022-04-16 11:59:25,726 | server.py:277 | fit_round received 7 results and 0 failures\n",
      "DEBUG flower 2022-04-16 11:59:25,748 | server.py:211 | evaluate_round: strategy sampled 7 clients (out of 7)\n"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "Saving round 53 aggregated_weights...\n"
     ]
    },
    {
     "name": "stderr",
     "output_type": "stream",
     "text": [
      "DEBUG flower 2022-04-16 11:59:27,591 | server.py:223 | evaluate_round received 7 results and 0 failures\n",
      "INFO flower 2022-04-16 11:59:27,592 | 2719366172.py:15 | round-53-EVALUATION\n",
      "INFO flower 2022-04-16 11:59:27,594 | 2719366172.py:31 | [(1, 0.6284584999084473), (2, 0.6392157077789307), (3, 0.6743295192718506), (4, 0.7684630751609802), (5, 0.7764471173286438), (8, 0.7318007946014404), (12, 0.8483606576919556)]\n",
      "INFO flower 2022-04-16 11:59:27,595 | 2719366172.py:37 | Aggregated accuracy: 0.7238679102488926 +- 0.0746780515813104\n",
      "DEBUG flower 2022-04-16 11:59:27,595 | server.py:265 | fit_round: strategy sampled 7 clients (out of 7)\n",
      "DEBUG flower 2022-04-16 11:59:32,196 | server.py:277 | fit_round received 7 results and 0 failures\n",
      "DEBUG flower 2022-04-16 11:59:32,219 | server.py:211 | evaluate_round: strategy sampled 7 clients (out of 7)\n"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "Saving round 54 aggregated_weights...\n"
     ]
    },
    {
     "name": "stderr",
     "output_type": "stream",
     "text": [
      "DEBUG flower 2022-04-16 11:59:34,096 | server.py:223 | evaluate_round received 7 results and 0 failures\n",
      "INFO flower 2022-04-16 11:59:34,097 | 2719366172.py:15 | round-54-EVALUATION\n",
      "INFO flower 2022-04-16 11:59:34,099 | 2719366172.py:31 | [(1, 0.6245059370994568), (2, 0.6392157077789307), (3, 0.6743295192718506), (4, 0.7644710540771484), (5, 0.7784430980682373), (8, 0.7318007946014404), (12, 0.8524590134620667)]\n",
      "INFO flower 2022-04-16 11:59:34,100 | 2719366172.py:37 | Aggregated accuracy: 0.7236035891941616 +- 0.07626835058472901\n",
      "DEBUG flower 2022-04-16 11:59:34,100 | server.py:265 | fit_round: strategy sampled 7 clients (out of 7)\n",
      "DEBUG flower 2022-04-16 11:59:38,775 | server.py:277 | fit_round received 7 results and 0 failures\n",
      "DEBUG flower 2022-04-16 11:59:38,791 | server.py:211 | evaluate_round: strategy sampled 7 clients (out of 7)\n"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "Saving round 55 aggregated_weights...\n"
     ]
    },
    {
     "name": "stderr",
     "output_type": "stream",
     "text": [
      "DEBUG flower 2022-04-16 11:59:40,577 | server.py:223 | evaluate_round received 7 results and 0 failures\n",
      "INFO flower 2022-04-16 11:59:40,577 | 2719366172.py:15 | round-55-EVALUATION\n",
      "INFO flower 2022-04-16 11:59:40,579 | 2719366172.py:31 | [(1, 0.6245059370994568), (2, 0.6431372761726379), (3, 0.6704980731010437), (4, 0.7684630751609802), (5, 0.7764471173286438), (8, 0.7318007946014404), (12, 0.8524590134620667)]\n",
      "INFO flower 2022-04-16 11:59:40,580 | 2719366172.py:37 | Aggregated accuracy: 0.7239016124180385 +- 0.07614879492831457\n",
      "DEBUG flower 2022-04-16 11:59:40,581 | server.py:265 | fit_round: strategy sampled 7 clients (out of 7)\n",
      "DEBUG flower 2022-04-16 11:59:45,433 | server.py:277 | fit_round received 7 results and 0 failures\n",
      "DEBUG flower 2022-04-16 11:59:45,450 | server.py:211 | evaluate_round: strategy sampled 7 clients (out of 7)\n"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "Saving round 56 aggregated_weights...\n"
     ]
    },
    {
     "name": "stderr",
     "output_type": "stream",
     "text": [
      "DEBUG flower 2022-04-16 11:59:47,182 | server.py:223 | evaluate_round received 7 results and 0 failures\n",
      "INFO flower 2022-04-16 11:59:47,183 | 2719366172.py:15 | round-56-EVALUATION\n",
      "INFO flower 2022-04-16 11:59:47,185 | 2719366172.py:31 | [(1, 0.6245059370994568), (2, 0.6431372761726379), (3, 0.6666666865348816), (4, 0.7684630751609802), (5, 0.7784430980682373), (8, 0.7356321811676025), (12, 0.8524590134620667)]\n",
      "INFO flower 2022-04-16 11:59:47,185 | 2719366172.py:37 | Aggregated accuracy: 0.7241867525236947 +- 0.07681401947281805\n",
      "DEBUG flower 2022-04-16 11:59:47,186 | server.py:265 | fit_round: strategy sampled 7 clients (out of 7)\n",
      "DEBUG flower 2022-04-16 11:59:51,917 | server.py:277 | fit_round received 7 results and 0 failures\n",
      "DEBUG flower 2022-04-16 11:59:51,940 | server.py:211 | evaluate_round: strategy sampled 7 clients (out of 7)\n"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "Saving round 57 aggregated_weights...\n"
     ]
    },
    {
     "name": "stderr",
     "output_type": "stream",
     "text": [
      "DEBUG flower 2022-04-16 11:59:53,800 | server.py:223 | evaluate_round received 7 results and 0 failures\n",
      "INFO flower 2022-04-16 11:59:53,800 | 2719366172.py:15 | round-57-EVALUATION\n",
      "INFO flower 2022-04-16 11:59:53,803 | 2719366172.py:31 | [(1, 0.6245059370994568), (2, 0.6392157077789307), (3, 0.6666666865348816), (4, 0.7684630751609802), (5, 0.7804391384124756), (8, 0.7432950139045715), (12, 0.8483606576919556)]\n",
      "INFO flower 2022-04-16 11:59:53,803 | 2719366172.py:37 | Aggregated accuracy: 0.7244208880833217 +- 0.07687980015767712\n",
      "DEBUG flower 2022-04-16 11:59:53,804 | server.py:265 | fit_round: strategy sampled 7 clients (out of 7)\n",
      "DEBUG flower 2022-04-16 11:59:58,319 | server.py:277 | fit_round received 7 results and 0 failures\n",
      "DEBUG flower 2022-04-16 11:59:58,335 | server.py:211 | evaluate_round: strategy sampled 7 clients (out of 7)\n"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "Saving round 58 aggregated_weights...\n"
     ]
    },
    {
     "name": "stderr",
     "output_type": "stream",
     "text": [
      "DEBUG flower 2022-04-16 12:00:00,180 | server.py:223 | evaluate_round received 7 results and 0 failures\n",
      "INFO flower 2022-04-16 12:00:00,180 | 2719366172.py:15 | round-58-EVALUATION\n",
      "INFO flower 2022-04-16 12:00:00,183 | 2719366172.py:31 | [(1, 0.6284584999084473), (2, 0.6392157077789307), (3, 0.6666666865348816), (4, 0.7684630751609802), (5, 0.7804391384124756), (8, 0.7509578466415405), (12, 0.8401639461517334)]\n",
      "INFO flower 2022-04-16 12:00:00,183 | 2719366172.py:37 | Aggregated accuracy: 0.7249092715127128 +- 0.07462382340386609\n",
      "DEBUG flower 2022-04-16 12:00:00,183 | server.py:265 | fit_round: strategy sampled 7 clients (out of 7)\n",
      "DEBUG flower 2022-04-16 12:00:04,832 | server.py:277 | fit_round received 7 results and 0 failures\n",
      "DEBUG flower 2022-04-16 12:00:04,848 | server.py:211 | evaluate_round: strategy sampled 7 clients (out of 7)\n"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "Saving round 59 aggregated_weights...\n"
     ]
    },
    {
     "name": "stderr",
     "output_type": "stream",
     "text": [
      "DEBUG flower 2022-04-16 12:00:06,556 | server.py:223 | evaluate_round received 7 results and 0 failures\n",
      "INFO flower 2022-04-16 12:00:06,556 | 2719366172.py:15 | round-59-EVALUATION\n",
      "INFO flower 2022-04-16 12:00:06,559 | 2719366172.py:31 | [(1, 0.6284584999084473), (2, 0.6470588445663452), (3, 0.6666666865348816), (4, 0.7704590559005737), (5, 0.7764471173286438), (8, 0.7662835121154785), (12, 0.8401639461517334)]\n",
      "INFO flower 2022-04-16 12:00:06,559 | 2719366172.py:37 | Aggregated accuracy: 0.7279339517865863 +- 0.0740829635409856\n",
      "DEBUG flower 2022-04-16 12:00:06,560 | server.py:265 | fit_round: strategy sampled 7 clients (out of 7)\n",
      "DEBUG flower 2022-04-16 12:00:11,278 | server.py:277 | fit_round received 7 results and 0 failures\n",
      "DEBUG flower 2022-04-16 12:00:11,295 | server.py:211 | evaluate_round: strategy sampled 7 clients (out of 7)\n"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "Saving round 60 aggregated_weights...\n"
     ]
    },
    {
     "name": "stderr",
     "output_type": "stream",
     "text": [
      "DEBUG flower 2022-04-16 12:00:13,070 | server.py:223 | evaluate_round received 7 results and 0 failures\n",
      "INFO flower 2022-04-16 12:00:13,071 | 2719366172.py:15 | round-60-EVALUATION\n",
      "INFO flower 2022-04-16 12:00:13,073 | 2719366172.py:31 | [(1, 0.6284584999084473), (2, 0.6431372761726379), (3, 0.6666666865348816), (4, 0.772455096244812), (5, 0.7764471173286438), (8, 0.7662835121154785), (12, 0.8401639461517334)]\n",
      "INFO flower 2022-04-16 12:00:13,073 | 2719366172.py:37 | Aggregated accuracy: 0.7276588763509478 +- 0.07487218613352684\n",
      "DEBUG flower 2022-04-16 12:00:13,074 | server.py:265 | fit_round: strategy sampled 7 clients (out of 7)\n",
      "DEBUG flower 2022-04-16 12:00:17,742 | server.py:277 | fit_round received 7 results and 0 failures\n",
      "DEBUG flower 2022-04-16 12:00:17,766 | server.py:211 | evaluate_round: strategy sampled 7 clients (out of 7)\n"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "Saving round 61 aggregated_weights...\n"
     ]
    },
    {
     "name": "stderr",
     "output_type": "stream",
     "text": [
      "DEBUG flower 2022-04-16 12:00:19,556 | server.py:223 | evaluate_round received 7 results and 0 failures\n",
      "INFO flower 2022-04-16 12:00:19,557 | 2719366172.py:15 | round-61-EVALUATION\n",
      "INFO flower 2022-04-16 12:00:19,559 | 2719366172.py:31 | [(1, 0.6284584999084473), (2, 0.6431372761726379), (3, 0.6704980731010437), (4, 0.772455096244812), (5, 0.7744510769844055), (8, 0.7701149582862854), (12, 0.8401639461517334)]\n",
      "INFO flower 2022-04-16 12:00:19,559 | 2719366172.py:37 | Aggregated accuracy: 0.7284684181213379 +- 0.0745496061953238\n",
      "DEBUG flower 2022-04-16 12:00:19,560 | server.py:265 | fit_round: strategy sampled 7 clients (out of 7)\n",
      "DEBUG flower 2022-04-16 12:00:24,273 | server.py:277 | fit_round received 7 results and 0 failures\n",
      "DEBUG flower 2022-04-16 12:00:24,296 | server.py:211 | evaluate_round: strategy sampled 7 clients (out of 7)\n"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "Saving round 62 aggregated_weights...\n"
     ]
    },
    {
     "name": "stderr",
     "output_type": "stream",
     "text": [
      "DEBUG flower 2022-04-16 12:00:26,134 | server.py:223 | evaluate_round received 7 results and 0 failures\n",
      "INFO flower 2022-04-16 12:00:26,135 | 2719366172.py:15 | round-62-EVALUATION\n",
      "INFO flower 2022-04-16 12:00:26,137 | 2719366172.py:31 | [(1, 0.6245059370994568), (2, 0.6431372761726379), (3, 0.6743295192718506), (4, 0.7684630751609802), (5, 0.7744510769844055), (8, 0.7701149582862854), (12, 0.8401639461517334)]\n",
      "INFO flower 2022-04-16 12:00:26,137 | 2719366172.py:37 | Aggregated accuracy: 0.7278808270181928 +- 0.07458696512847368\n",
      "DEBUG flower 2022-04-16 12:00:26,138 | server.py:265 | fit_round: strategy sampled 7 clients (out of 7)\n",
      "DEBUG flower 2022-04-16 12:00:30,826 | server.py:277 | fit_round received 7 results and 0 failures\n",
      "DEBUG flower 2022-04-16 12:00:30,848 | server.py:211 | evaluate_round: strategy sampled 7 clients (out of 7)\n"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "Saving round 63 aggregated_weights...\n"
     ]
    },
    {
     "name": "stderr",
     "output_type": "stream",
     "text": [
      "DEBUG flower 2022-04-16 12:00:32,585 | server.py:223 | evaluate_round received 7 results and 0 failures\n",
      "INFO flower 2022-04-16 12:00:32,586 | 2719366172.py:15 | round-63-EVALUATION\n",
      "INFO flower 2022-04-16 12:00:32,588 | 2719366172.py:31 | [(1, 0.6245059370994568), (2, 0.6431372761726379), (3, 0.6743295192718506), (4, 0.7704590559005737), (5, 0.7744510769844055), (8, 0.7739463448524475), (12, 0.8401639461517334)]\n",
      "INFO flower 2022-04-16 12:00:32,589 | 2719366172.py:37 | Aggregated accuracy: 0.7287133080618722 +- 0.07506373786563146\n",
      "DEBUG flower 2022-04-16 12:00:32,590 | server.py:265 | fit_round: strategy sampled 7 clients (out of 7)\n",
      "DEBUG flower 2022-04-16 12:00:37,220 | server.py:277 | fit_round received 7 results and 0 failures\n",
      "DEBUG flower 2022-04-16 12:00:37,237 | server.py:211 | evaluate_round: strategy sampled 7 clients (out of 7)\n"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "Saving round 64 aggregated_weights...\n"
     ]
    },
    {
     "name": "stderr",
     "output_type": "stream",
     "text": [
      "DEBUG flower 2022-04-16 12:00:38,984 | server.py:223 | evaluate_round received 7 results and 0 failures\n",
      "INFO flower 2022-04-16 12:00:38,985 | 2719366172.py:15 | round-64-EVALUATION\n",
      "INFO flower 2022-04-16 12:00:38,987 | 2719366172.py:31 | [(1, 0.6284584999084473), (2, 0.6431372761726379), (3, 0.6743295192718506), (4, 0.7704590559005737), (5, 0.7744510769844055), (8, 0.7816091775894165), (12, 0.8360655903816223)]\n",
      "INFO flower 2022-04-16 12:00:38,988 | 2719366172.py:37 | Aggregated accuracy: 0.7297871708869934 +- 0.07414362944055906\n",
      "DEBUG flower 2022-04-16 12:00:38,989 | server.py:265 | fit_round: strategy sampled 7 clients (out of 7)\n",
      "DEBUG flower 2022-04-16 12:00:43,803 | server.py:277 | fit_round received 7 results and 0 failures\n",
      "DEBUG flower 2022-04-16 12:00:43,819 | server.py:211 | evaluate_round: strategy sampled 7 clients (out of 7)\n"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "Saving round 65 aggregated_weights...\n"
     ]
    },
    {
     "name": "stderr",
     "output_type": "stream",
     "text": [
      "DEBUG flower 2022-04-16 12:00:45,554 | server.py:223 | evaluate_round received 7 results and 0 failures\n",
      "INFO flower 2022-04-16 12:00:45,554 | 2719366172.py:15 | round-65-EVALUATION\n",
      "INFO flower 2022-04-16 12:00:45,557 | 2719366172.py:31 | [(1, 0.6284584999084473), (2, 0.6392157077789307), (3, 0.6743295192718506), (4, 0.772455096244812), (5, 0.7744510769844055), (8, 0.7816091775894165), (12, 0.8401639461517334)]\n",
      "INFO flower 2022-04-16 12:00:45,557 | 2719366172.py:37 | Aggregated accuracy: 0.7300975748470852 +- 0.07580947492504654\n",
      "DEBUG flower 2022-04-16 12:00:45,558 | server.py:265 | fit_round: strategy sampled 7 clients (out of 7)\n",
      "DEBUG flower 2022-04-16 12:00:50,289 | server.py:277 | fit_round received 7 results and 0 failures\n",
      "DEBUG flower 2022-04-16 12:00:50,305 | server.py:211 | evaluate_round: strategy sampled 7 clients (out of 7)\n"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "Saving round 66 aggregated_weights...\n"
     ]
    },
    {
     "name": "stderr",
     "output_type": "stream",
     "text": [
      "DEBUG flower 2022-04-16 12:00:52,385 | server.py:223 | evaluate_round received 7 results and 0 failures\n",
      "INFO flower 2022-04-16 12:00:52,385 | 2719366172.py:15 | round-66-EVALUATION\n",
      "INFO flower 2022-04-16 12:00:52,387 | 2719366172.py:31 | [(1, 0.6284584999084473), (2, 0.6352941393852234), (3, 0.6743295192718506), (4, 0.772455096244812), (5, 0.7744510769844055), (8, 0.7931034564971924), (12, 0.8401639461517334)]\n",
      "INFO flower 2022-04-16 12:00:52,388 | 2719366172.py:37 | Aggregated accuracy: 0.7311793906348092 +- 0.0777044001880479\n",
      "DEBUG flower 2022-04-16 12:00:52,388 | server.py:265 | fit_round: strategy sampled 7 clients (out of 7)\n",
      "DEBUG flower 2022-04-16 12:00:56,600 | server.py:277 | fit_round received 7 results and 0 failures\n",
      "DEBUG flower 2022-04-16 12:00:56,622 | server.py:211 | evaluate_round: strategy sampled 7 clients (out of 7)\n"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "Saving round 67 aggregated_weights...\n"
     ]
    },
    {
     "name": "stderr",
     "output_type": "stream",
     "text": [
      "DEBUG flower 2022-04-16 12:00:58,384 | server.py:223 | evaluate_round received 7 results and 0 failures\n",
      "INFO flower 2022-04-16 12:00:58,385 | 2719366172.py:15 | round-67-EVALUATION\n",
      "INFO flower 2022-04-16 12:00:58,387 | 2719366172.py:31 | [(1, 0.6284584999084473), (2, 0.6313725709915161), (3, 0.6743295192718506), (4, 0.7744510769844055), (5, 0.7744510769844055), (8, 0.7931034564971924), (12, 0.8442623019218445)]\n",
      "INFO flower 2022-04-16 12:00:58,388 | 2719366172.py:37 | Aggregated accuracy: 0.7314897860799517 +- 0.07938282337845093\n",
      "DEBUG flower 2022-04-16 12:00:58,388 | server.py:265 | fit_round: strategy sampled 7 clients (out of 7)\n",
      "DEBUG flower 2022-04-16 12:01:02,794 | server.py:277 | fit_round received 7 results and 0 failures\n",
      "DEBUG flower 2022-04-16 12:01:02,810 | server.py:211 | evaluate_round: strategy sampled 7 clients (out of 7)\n"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "Saving round 68 aggregated_weights...\n"
     ]
    },
    {
     "name": "stderr",
     "output_type": "stream",
     "text": [
      "DEBUG flower 2022-04-16 12:01:04,609 | server.py:223 | evaluate_round received 7 results and 0 failures\n",
      "INFO flower 2022-04-16 12:01:04,610 | 2719366172.py:15 | round-68-EVALUATION\n",
      "INFO flower 2022-04-16 12:01:04,612 | 2719366172.py:31 | [(1, 0.6284584999084473), (2, 0.6274510025978088), (3, 0.6743295192718506), (4, 0.7744510769844055), (5, 0.7744510769844055), (8, 0.8007662892341614), (12, 0.8401639461517334)]\n",
      "INFO flower 2022-04-16 12:01:04,613 | 2719366172.py:37 | Aggregated accuracy: 0.7314387730189732 +- 0.08018500418477072\n",
      "DEBUG flower 2022-04-16 12:01:04,613 | server.py:265 | fit_round: strategy sampled 7 clients (out of 7)\n",
      "DEBUG flower 2022-04-16 12:01:09,483 | server.py:277 | fit_round received 7 results and 0 failures\n",
      "DEBUG flower 2022-04-16 12:01:09,500 | server.py:211 | evaluate_round: strategy sampled 7 clients (out of 7)\n"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "Saving round 69 aggregated_weights...\n"
     ]
    },
    {
     "name": "stderr",
     "output_type": "stream",
     "text": [
      "DEBUG flower 2022-04-16 12:01:11,165 | server.py:223 | evaluate_round received 7 results and 0 failures\n",
      "INFO flower 2022-04-16 12:01:11,166 | 2719366172.py:15 | round-69-EVALUATION\n",
      "INFO flower 2022-04-16 12:01:11,168 | 2719366172.py:31 | [(1, 0.6284584999084473), (2, 0.6274510025978088), (3, 0.6781609058380127), (4, 0.7744510769844055), (5, 0.7744510769844055), (8, 0.8045976758003235), (12, 0.8483606576919556)]\n",
      "INFO flower 2022-04-16 12:01:11,168 | 2719366172.py:37 | Aggregated accuracy: 0.7337044136864799 +- 0.08189196807072656\n",
      "DEBUG flower 2022-04-16 12:01:11,169 | server.py:265 | fit_round: strategy sampled 7 clients (out of 7)\n",
      "DEBUG flower 2022-04-16 12:01:15,831 | server.py:277 | fit_round received 7 results and 0 failures\n",
      "DEBUG flower 2022-04-16 12:01:15,847 | server.py:211 | evaluate_round: strategy sampled 7 clients (out of 7)\n"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "Saving round 70 aggregated_weights...\n"
     ]
    },
    {
     "name": "stderr",
     "output_type": "stream",
     "text": [
      "DEBUG flower 2022-04-16 12:01:17,693 | server.py:223 | evaluate_round received 7 results and 0 failures\n",
      "INFO flower 2022-04-16 12:01:17,694 | 2719366172.py:15 | round-70-EVALUATION\n",
      "INFO flower 2022-04-16 12:01:17,696 | 2719366172.py:31 | [(1, 0.6284584999084473), (2, 0.6274510025978088), (3, 0.6781609058380127), (4, 0.7744510769844055), (5, 0.7704590559005737), (8, 0.8045976758003235), (12, 0.8442623019218445)]\n",
      "INFO flower 2022-04-16 12:01:17,697 | 2719366172.py:37 | Aggregated accuracy: 0.732548645564488 +- 0.08080162300156328\n",
      "DEBUG flower 2022-04-16 12:01:17,697 | server.py:265 | fit_round: strategy sampled 7 clients (out of 7)\n",
      "DEBUG flower 2022-04-16 12:01:22,210 | server.py:277 | fit_round received 7 results and 0 failures\n",
      "DEBUG flower 2022-04-16 12:01:22,227 | server.py:211 | evaluate_round: strategy sampled 7 clients (out of 7)\n"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "Saving round 71 aggregated_weights...\n"
     ]
    },
    {
     "name": "stderr",
     "output_type": "stream",
     "text": [
      "DEBUG flower 2022-04-16 12:01:24,089 | server.py:223 | evaluate_round received 7 results and 0 failures\n",
      "INFO flower 2022-04-16 12:01:24,090 | 2719366172.py:15 | round-71-EVALUATION\n",
      "INFO flower 2022-04-16 12:01:24,092 | 2719366172.py:31 | [(1, 0.6284584999084473), (2, 0.6313725709915161), (3, 0.6781609058380127), (4, 0.7744510769844055), (5, 0.7704590559005737), (8, 0.8007662892341614), (12, 0.8442623019218445)]\n",
      "INFO flower 2022-04-16 12:01:24,093 | 2719366172.py:37 | Aggregated accuracy: 0.7325615286827087 +- 0.07960256856475564\n",
      "DEBUG flower 2022-04-16 12:01:24,093 | server.py:265 | fit_round: strategy sampled 7 clients (out of 7)\n",
      "DEBUG flower 2022-04-16 12:01:28,719 | server.py:277 | fit_round received 7 results and 0 failures\n",
      "DEBUG flower 2022-04-16 12:01:28,741 | server.py:211 | evaluate_round: strategy sampled 7 clients (out of 7)\n"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "Saving round 72 aggregated_weights...\n"
     ]
    },
    {
     "name": "stderr",
     "output_type": "stream",
     "text": [
      "DEBUG flower 2022-04-16 12:01:30,691 | server.py:223 | evaluate_round received 7 results and 0 failures\n",
      "INFO flower 2022-04-16 12:01:30,692 | 2719366172.py:15 | round-72-EVALUATION\n",
      "INFO flower 2022-04-16 12:01:30,694 | 2719366172.py:31 | [(1, 0.6284584999084473), (2, 0.6313725709915161), (3, 0.6819923520088196), (4, 0.7744510769844055), (5, 0.7704590559005737), (8, 0.8007662892341614), (12, 0.8401639461517334)]\n",
      "INFO flower 2022-04-16 12:01:30,695 | 2719366172.py:37 | Aggregated accuracy: 0.732523398739951 +- 0.07842649301282992\n",
      "DEBUG flower 2022-04-16 12:01:30,695 | server.py:265 | fit_round: strategy sampled 7 clients (out of 7)\n",
      "DEBUG flower 2022-04-16 12:01:35,239 | server.py:277 | fit_round received 7 results and 0 failures\n",
      "DEBUG flower 2022-04-16 12:01:35,262 | server.py:211 | evaluate_round: strategy sampled 7 clients (out of 7)\n"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "Saving round 73 aggregated_weights...\n"
     ]
    },
    {
     "name": "stderr",
     "output_type": "stream",
     "text": [
      "DEBUG flower 2022-04-16 12:01:36,983 | server.py:223 | evaluate_round received 7 results and 0 failures\n",
      "INFO flower 2022-04-16 12:01:36,983 | 2719366172.py:15 | round-73-EVALUATION\n",
      "INFO flower 2022-04-16 12:01:36,985 | 2719366172.py:31 | [(1, 0.6284584999084473), (2, 0.6352941393852234), (3, 0.6819923520088196), (4, 0.7744510769844055), (5, 0.772455096244812), (8, 0.8007662892341614), (12, 0.8360655903816223)]\n",
      "INFO flower 2022-04-16 12:01:36,986 | 2719366172.py:37 | Aggregated accuracy: 0.7327832920210702 +- 0.07705887743162589\n",
      "DEBUG flower 2022-04-16 12:01:36,986 | server.py:265 | fit_round: strategy sampled 7 clients (out of 7)\n",
      "DEBUG flower 2022-04-16 12:01:41,816 | server.py:277 | fit_round received 7 results and 0 failures\n",
      "DEBUG flower 2022-04-16 12:01:41,839 | server.py:211 | evaluate_round: strategy sampled 7 clients (out of 7)\n"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "Saving round 74 aggregated_weights...\n"
     ]
    },
    {
     "name": "stderr",
     "output_type": "stream",
     "text": [
      "DEBUG flower 2022-04-16 12:01:43,597 | server.py:223 | evaluate_round received 7 results and 0 failures\n",
      "INFO flower 2022-04-16 12:01:43,597 | 2719366172.py:15 | round-74-EVALUATION\n",
      "INFO flower 2022-04-16 12:01:43,600 | 2719366172.py:31 | [(1, 0.6324110627174377), (2, 0.6274510025978088), (3, 0.6819923520088196), (4, 0.7744510769844055), (5, 0.7744510769844055), (8, 0.8007662892341614), (12, 0.8319672346115112)]\n",
      "INFO flower 2022-04-16 12:01:43,600 | 2719366172.py:37 | Aggregated accuracy: 0.7319271564483643 +- 0.0771599594593533\n",
      "DEBUG flower 2022-04-16 12:01:43,601 | server.py:265 | fit_round: strategy sampled 7 clients (out of 7)\n",
      "DEBUG flower 2022-04-16 12:01:48,386 | server.py:277 | fit_round received 7 results and 0 failures\n",
      "DEBUG flower 2022-04-16 12:01:48,402 | server.py:211 | evaluate_round: strategy sampled 7 clients (out of 7)\n"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "Saving round 75 aggregated_weights...\n"
     ]
    },
    {
     "name": "stderr",
     "output_type": "stream",
     "text": [
      "DEBUG flower 2022-04-16 12:01:50,128 | server.py:223 | evaluate_round received 7 results and 0 failures\n",
      "INFO flower 2022-04-16 12:01:50,129 | 2719366172.py:15 | round-75-EVALUATION\n",
      "INFO flower 2022-04-16 12:01:50,131 | 2719366172.py:31 | [(1, 0.6324110627174377), (2, 0.6274510025978088), (3, 0.6819923520088196), (4, 0.7704590559005737), (5, 0.7764471173286438), (8, 0.8007662892341614), (12, 0.8278688788414001)]\n",
      "INFO flower 2022-04-16 12:01:50,132 | 2719366172.py:37 | Aggregated accuracy: 0.7310565369469779 +- 0.07626764242894836\n",
      "DEBUG flower 2022-04-16 12:01:50,132 | server.py:265 | fit_round: strategy sampled 7 clients (out of 7)\n",
      "DEBUG flower 2022-04-16 12:01:54,882 | server.py:277 | fit_round received 7 results and 0 failures\n",
      "DEBUG flower 2022-04-16 12:01:54,899 | server.py:211 | evaluate_round: strategy sampled 7 clients (out of 7)\n"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "Saving round 76 aggregated_weights...\n"
     ]
    },
    {
     "name": "stderr",
     "output_type": "stream",
     "text": [
      "DEBUG flower 2022-04-16 12:01:56,664 | server.py:223 | evaluate_round received 7 results and 0 failures\n",
      "INFO flower 2022-04-16 12:01:56,665 | 2719366172.py:15 | round-76-EVALUATION\n",
      "INFO flower 2022-04-16 12:01:56,667 | 2719366172.py:31 | [(1, 0.6324110627174377), (2, 0.6313725709915161), (3, 0.6819923520088196), (4, 0.7684630751609802), (5, 0.7764471173286438), (8, 0.8045976758003235), (12, 0.8278688788414001)]\n",
      "INFO flower 2022-04-16 12:01:56,668 | 2719366172.py:37 | Aggregated accuracy: 0.7318789618355888 +- 0.07588606568384902\n",
      "DEBUG flower 2022-04-16 12:01:56,668 | server.py:265 | fit_round: strategy sampled 7 clients (out of 7)\n",
      "DEBUG flower 2022-04-16 12:02:01,221 | server.py:277 | fit_round received 7 results and 0 failures\n",
      "DEBUG flower 2022-04-16 12:02:01,243 | server.py:211 | evaluate_round: strategy sampled 7 clients (out of 7)\n"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "Saving round 77 aggregated_weights...\n"
     ]
    },
    {
     "name": "stderr",
     "output_type": "stream",
     "text": [
      "DEBUG flower 2022-04-16 12:02:02,942 | server.py:223 | evaluate_round received 7 results and 0 failures\n",
      "INFO flower 2022-04-16 12:02:02,942 | 2719366172.py:15 | round-77-EVALUATION\n",
      "INFO flower 2022-04-16 12:02:02,945 | 2719366172.py:31 | [(1, 0.6324110627174377), (2, 0.6313725709915161), (3, 0.6819923520088196), (4, 0.7684630751609802), (5, 0.7784430980682373), (8, 0.8045976758003235), (12, 0.8278688788414001)]\n",
      "INFO flower 2022-04-16 12:02:02,945 | 2719366172.py:37 | Aggregated accuracy: 0.7321641019412449 +- 0.07605655219233222\n",
      "DEBUG flower 2022-04-16 12:02:02,946 | server.py:265 | fit_round: strategy sampled 7 clients (out of 7)\n",
      "DEBUG flower 2022-04-16 12:02:07,565 | server.py:277 | fit_round received 7 results and 0 failures\n",
      "DEBUG flower 2022-04-16 12:02:07,581 | server.py:211 | evaluate_round: strategy sampled 7 clients (out of 7)\n"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "Saving round 78 aggregated_weights...\n"
     ]
    },
    {
     "name": "stderr",
     "output_type": "stream",
     "text": [
      "DEBUG flower 2022-04-16 12:02:09,265 | server.py:223 | evaluate_round received 7 results and 0 failures\n",
      "INFO flower 2022-04-16 12:02:09,265 | 2719366172.py:15 | round-78-EVALUATION\n",
      "INFO flower 2022-04-16 12:02:09,267 | 2719366172.py:31 | [(1, 0.6324110627174377), (2, 0.6313725709915161), (3, 0.6819923520088196), (4, 0.7704590559005737), (5, 0.7764471173286438), (8, 0.8045976758003235), (12, 0.8278688788414001)]\n",
      "INFO flower 2022-04-16 12:02:09,268 | 2719366172.py:37 | Aggregated accuracy: 0.7321641019412449 +- 0.07602661369632646\n",
      "DEBUG flower 2022-04-16 12:02:09,269 | server.py:265 | fit_round: strategy sampled 7 clients (out of 7)\n",
      "DEBUG flower 2022-04-16 12:02:13,860 | server.py:277 | fit_round received 7 results and 0 failures\n",
      "DEBUG flower 2022-04-16 12:02:13,876 | server.py:211 | evaluate_round: strategy sampled 7 clients (out of 7)\n"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "Saving round 79 aggregated_weights...\n"
     ]
    },
    {
     "name": "stderr",
     "output_type": "stream",
     "text": [
      "DEBUG flower 2022-04-16 12:02:15,551 | server.py:223 | evaluate_round received 7 results and 0 failures\n",
      "INFO flower 2022-04-16 12:02:15,552 | 2719366172.py:15 | round-79-EVALUATION\n",
      "INFO flower 2022-04-16 12:02:15,554 | 2719366172.py:31 | [(1, 0.6324110627174377), (2, 0.6352941393852234), (3, 0.6819923520088196), (4, 0.7684630751609802), (5, 0.7744510769844055), (8, 0.8007662892341614), (12, 0.8237704634666443)]\n",
      "INFO flower 2022-04-16 12:02:15,554 | 2719366172.py:37 | Aggregated accuracy: 0.7310212084225246 +- 0.07372372056779654\n",
      "DEBUG flower 2022-04-16 12:02:15,555 | server.py:265 | fit_round: strategy sampled 7 clients (out of 7)\n",
      "DEBUG flower 2022-04-16 12:02:20,160 | server.py:277 | fit_round received 7 results and 0 failures\n",
      "DEBUG flower 2022-04-16 12:02:20,177 | server.py:211 | evaluate_round: strategy sampled 7 clients (out of 7)\n"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "Saving round 80 aggregated_weights...\n"
     ]
    },
    {
     "name": "stderr",
     "output_type": "stream",
     "text": [
      "DEBUG flower 2022-04-16 12:02:22,129 | server.py:223 | evaluate_round received 7 results and 0 failures\n",
      "INFO flower 2022-04-16 12:02:22,130 | 2719366172.py:15 | round-80-EVALUATION\n",
      "INFO flower 2022-04-16 12:02:22,132 | 2719366172.py:31 | [(1, 0.6324110627174377), (2, 0.6352941393852234), (3, 0.6819923520088196), (4, 0.772455096244812), (5, 0.7744510769844055), (8, 0.8007662892341614), (12, 0.8237704634666443)]\n",
      "INFO flower 2022-04-16 12:02:22,133 | 2719366172.py:37 | Aggregated accuracy: 0.7315914971487862 +- 0.07402596638159221\n",
      "DEBUG flower 2022-04-16 12:02:22,134 | server.py:265 | fit_round: strategy sampled 7 clients (out of 7)\n",
      "DEBUG flower 2022-04-16 12:02:26,465 | server.py:277 | fit_round received 7 results and 0 failures\n",
      "DEBUG flower 2022-04-16 12:02:26,481 | server.py:211 | evaluate_round: strategy sampled 7 clients (out of 7)\n"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "Saving round 81 aggregated_weights...\n"
     ]
    },
    {
     "name": "stderr",
     "output_type": "stream",
     "text": [
      "DEBUG flower 2022-04-16 12:02:28,155 | server.py:223 | evaluate_round received 7 results and 0 failures\n",
      "INFO flower 2022-04-16 12:02:28,156 | 2719366172.py:15 | round-81-EVALUATION\n",
      "INFO flower 2022-04-16 12:02:28,158 | 2719366172.py:31 | [(1, 0.6324110627174377), (2, 0.6352941393852234), (3, 0.6819923520088196), (4, 0.7704590559005737), (5, 0.7784430980682373), (8, 0.7969348430633545), (12, 0.8278688788414001)]\n",
      "INFO flower 2022-04-16 12:02:28,159 | 2719366172.py:37 | Aggregated accuracy: 0.7319147757121495 +- 0.07446392226592377\n",
      "DEBUG flower 2022-04-16 12:02:28,159 | server.py:265 | fit_round: strategy sampled 7 clients (out of 7)\n",
      "DEBUG flower 2022-04-16 12:02:32,795 | server.py:277 | fit_round received 7 results and 0 failures\n",
      "DEBUG flower 2022-04-16 12:02:32,811 | server.py:211 | evaluate_round: strategy sampled 7 clients (out of 7)\n"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "Saving round 82 aggregated_weights...\n"
     ]
    },
    {
     "name": "stderr",
     "output_type": "stream",
     "text": [
      "DEBUG flower 2022-04-16 12:02:34,542 | server.py:223 | evaluate_round received 7 results and 0 failures\n",
      "INFO flower 2022-04-16 12:02:34,543 | 2719366172.py:15 | round-82-EVALUATION\n",
      "INFO flower 2022-04-16 12:02:34,545 | 2719366172.py:31 | [(1, 0.6324110627174377), (2, 0.6352941393852234), (3, 0.6781609058380127), (4, 0.772455096244812), (5, 0.7784430980682373), (8, 0.7931034564971924), (12, 0.8278688788414001)]\n",
      "INFO flower 2022-04-16 12:02:34,546 | 2719366172.py:37 | Aggregated accuracy: 0.7311052339417594 +- 0.07452810995952128\n",
      "DEBUG flower 2022-04-16 12:02:34,546 | server.py:265 | fit_round: strategy sampled 7 clients (out of 7)\n",
      "DEBUG flower 2022-04-16 12:02:39,219 | server.py:277 | fit_round received 7 results and 0 failures\n",
      "DEBUG flower 2022-04-16 12:02:39,236 | server.py:211 | evaluate_round: strategy sampled 7 clients (out of 7)\n"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "Saving round 83 aggregated_weights...\n"
     ]
    },
    {
     "name": "stderr",
     "output_type": "stream",
     "text": [
      "DEBUG flower 2022-04-16 12:02:40,976 | server.py:223 | evaluate_round received 7 results and 0 failures\n",
      "INFO flower 2022-04-16 12:02:40,977 | 2719366172.py:15 | round-83-EVALUATION\n",
      "INFO flower 2022-04-16 12:02:40,979 | 2719366172.py:31 | [(1, 0.6324110627174377), (2, 0.6352941393852234), (3, 0.6781609058380127), (4, 0.772455096244812), (5, 0.7784430980682373), (8, 0.7931034564971924), (12, 0.8278688788414001)]\n",
      "INFO flower 2022-04-16 12:02:40,980 | 2719366172.py:37 | Aggregated accuracy: 0.7311052339417594 +- 0.07452810995952125\n",
      "DEBUG flower 2022-04-16 12:02:40,980 | server.py:265 | fit_round: strategy sampled 7 clients (out of 7)\n",
      "DEBUG flower 2022-04-16 12:02:45,708 | server.py:277 | fit_round received 7 results and 0 failures\n",
      "DEBUG flower 2022-04-16 12:02:45,724 | server.py:211 | evaluate_round: strategy sampled 7 clients (out of 7)\n"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "Saving round 84 aggregated_weights...\n"
     ]
    },
    {
     "name": "stderr",
     "output_type": "stream",
     "text": [
      "DEBUG flower 2022-04-16 12:02:47,556 | server.py:223 | evaluate_round received 7 results and 0 failures\n",
      "INFO flower 2022-04-16 12:02:47,557 | 2719366172.py:15 | round-84-EVALUATION\n",
      "INFO flower 2022-04-16 12:02:47,559 | 2719366172.py:31 | [(1, 0.6324110627174377), (2, 0.6352941393852234), (3, 0.6781609058380127), (4, 0.7704590559005737), (5, 0.7784430980682373), (8, 0.7931034564971924), (12, 0.8278688788414001)]\n",
      "INFO flower 2022-04-16 12:02:47,559 | 2719366172.py:37 | Aggregated accuracy: 0.730820085321154 +- 0.074373014730866\n",
      "DEBUG flower 2022-04-16 12:02:47,560 | server.py:265 | fit_round: strategy sampled 7 clients (out of 7)\n",
      "DEBUG flower 2022-04-16 12:02:52,239 | server.py:277 | fit_round received 7 results and 0 failures\n",
      "DEBUG flower 2022-04-16 12:02:52,255 | server.py:211 | evaluate_round: strategy sampled 7 clients (out of 7)\n"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "Saving round 85 aggregated_weights...\n"
     ]
    },
    {
     "name": "stderr",
     "output_type": "stream",
     "text": [
      "DEBUG flower 2022-04-16 12:02:54,191 | server.py:223 | evaluate_round received 7 results and 0 failures\n",
      "INFO flower 2022-04-16 12:02:54,191 | 2719366172.py:15 | round-85-EVALUATION\n",
      "INFO flower 2022-04-16 12:02:54,193 | 2719366172.py:31 | [(1, 0.6324110627174377), (2, 0.6352941393852234), (3, 0.6781609058380127), (4, 0.7764471173286438), (5, 0.7824351191520691), (8, 0.7892720103263855), (12, 0.8278688788414001)]\n",
      "INFO flower 2022-04-16 12:02:54,194 | 2719366172.py:37 | Aggregated accuracy: 0.7316984619413104 +- 0.07479320449453995\n",
      "DEBUG flower 2022-04-16 12:02:54,194 | server.py:265 | fit_round: strategy sampled 7 clients (out of 7)\n",
      "DEBUG flower 2022-04-16 12:02:59,034 | server.py:277 | fit_round received 7 results and 0 failures\n",
      "DEBUG flower 2022-04-16 12:02:59,050 | server.py:211 | evaluate_round: strategy sampled 7 clients (out of 7)\n"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "Saving round 86 aggregated_weights...\n"
     ]
    },
    {
     "name": "stderr",
     "output_type": "stream",
     "text": [
      "DEBUG flower 2022-04-16 12:03:00,797 | server.py:223 | evaluate_round received 7 results and 0 failures\n",
      "INFO flower 2022-04-16 12:03:00,798 | 2719366172.py:15 | round-86-EVALUATION\n",
      "INFO flower 2022-04-16 12:03:00,800 | 2719366172.py:31 | [(1, 0.6324110627174377), (2, 0.6352941393852234), (3, 0.6781609058380127), (4, 0.7784430980682373), (5, 0.7824351191520691), (8, 0.7931034564971924), (12, 0.8278688788414001)]\n",
      "INFO flower 2022-04-16 12:03:00,801 | 2719366172.py:37 | Aggregated accuracy: 0.732530951499939 +- 0.07539589940374902\n",
      "DEBUG flower 2022-04-16 12:03:00,801 | server.py:265 | fit_round: strategy sampled 7 clients (out of 7)\n",
      "DEBUG flower 2022-04-16 12:03:05,501 | server.py:277 | fit_round received 7 results and 0 failures\n",
      "DEBUG flower 2022-04-16 12:03:05,517 | server.py:211 | evaluate_round: strategy sampled 7 clients (out of 7)\n"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "Saving round 87 aggregated_weights...\n"
     ]
    },
    {
     "name": "stderr",
     "output_type": "stream",
     "text": [
      "DEBUG flower 2022-04-16 12:03:07,237 | server.py:223 | evaluate_round received 7 results and 0 failures\n",
      "INFO flower 2022-04-16 12:03:07,238 | 2719366172.py:15 | round-87-EVALUATION\n",
      "INFO flower 2022-04-16 12:03:07,240 | 2719366172.py:31 | [(1, 0.6324110627174377), (2, 0.6352941393852234), (3, 0.6858237385749817), (4, 0.7804391384124756), (5, 0.7804391384124756), (8, 0.7854406237602234), (12, 0.8278688788414001)]\n",
      "INFO flower 2022-04-16 12:03:07,241 | 2719366172.py:37 | Aggregated accuracy: 0.7325309600148883 +- 0.07381414503837055\n",
      "DEBUG flower 2022-04-16 12:03:07,241 | server.py:265 | fit_round: strategy sampled 7 clients (out of 7)\n",
      "DEBUG flower 2022-04-16 12:03:12,190 | server.py:277 | fit_round received 7 results and 0 failures\n",
      "DEBUG flower 2022-04-16 12:03:12,212 | server.py:211 | evaluate_round: strategy sampled 7 clients (out of 7)\n"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "Saving round 88 aggregated_weights...\n"
     ]
    },
    {
     "name": "stderr",
     "output_type": "stream",
     "text": [
      "DEBUG flower 2022-04-16 12:03:13,986 | server.py:223 | evaluate_round received 7 results and 0 failures\n",
      "INFO flower 2022-04-16 12:03:13,987 | 2719366172.py:15 | round-88-EVALUATION\n",
      "INFO flower 2022-04-16 12:03:13,990 | 2719366172.py:31 | [(1, 0.6324110627174377), (2, 0.6352941393852234), (3, 0.6858237385749817), (4, 0.7804391384124756), (5, 0.7804391384124756), (8, 0.7854406237602234), (12, 0.8278688788414001)]\n",
      "INFO flower 2022-04-16 12:03:13,990 | 2719366172.py:37 | Aggregated accuracy: 0.7325309600148883 +- 0.07381414503837055\n",
      "DEBUG flower 2022-04-16 12:03:13,991 | server.py:265 | fit_round: strategy sampled 7 clients (out of 7)\n",
      "DEBUG flower 2022-04-16 12:03:18,756 | server.py:277 | fit_round received 7 results and 0 failures\n",
      "DEBUG flower 2022-04-16 12:03:18,778 | server.py:211 | evaluate_round: strategy sampled 7 clients (out of 7)\n"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "Saving round 89 aggregated_weights...\n"
     ]
    },
    {
     "name": "stderr",
     "output_type": "stream",
     "text": [
      "DEBUG flower 2022-04-16 12:03:20,802 | server.py:223 | evaluate_round received 7 results and 0 failures\n",
      "INFO flower 2022-04-16 12:03:20,802 | 2719366172.py:15 | round-89-EVALUATION\n",
      "INFO flower 2022-04-16 12:03:20,805 | 2719366172.py:31 | [(1, 0.6324110627174377), (2, 0.6352941393852234), (3, 0.6858237385749817), (4, 0.7804391384124756), (5, 0.7844311594963074), (8, 0.7854406237602234), (12, 0.8319672346115112)]\n",
      "INFO flower 2022-04-16 12:03:20,805 | 2719366172.py:37 | Aggregated accuracy: 0.7336867281368801 +- 0.07495430659777903\n",
      "DEBUG flower 2022-04-16 12:03:20,806 | server.py:265 | fit_round: strategy sampled 7 clients (out of 7)\n",
      "DEBUG flower 2022-04-16 12:03:25,123 | server.py:277 | fit_round received 7 results and 0 failures\n",
      "DEBUG flower 2022-04-16 12:03:25,146 | server.py:211 | evaluate_round: strategy sampled 7 clients (out of 7)\n"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "Saving round 90 aggregated_weights...\n"
     ]
    },
    {
     "name": "stderr",
     "output_type": "stream",
     "text": [
      "DEBUG flower 2022-04-16 12:03:27,016 | server.py:223 | evaluate_round received 7 results and 0 failures\n",
      "INFO flower 2022-04-16 12:03:27,017 | 2719366172.py:15 | round-90-EVALUATION\n",
      "INFO flower 2022-04-16 12:03:27,019 | 2719366172.py:31 | [(1, 0.6324110627174377), (2, 0.6235294342041016), (3, 0.6934865713119507), (4, 0.7784430980682373), (5, 0.7844311594963074), (8, 0.7854406237602234), (12, 0.8319672346115112)]\n",
      "INFO flower 2022-04-16 12:03:27,020 | 2719366172.py:37 | Aggregated accuracy: 0.7328155977385384 +- 0.07645520067597192\n",
      "DEBUG flower 2022-04-16 12:03:27,020 | server.py:265 | fit_round: strategy sampled 7 clients (out of 7)\n",
      "DEBUG flower 2022-04-16 12:03:31,489 | server.py:277 | fit_round received 7 results and 0 failures\n",
      "DEBUG flower 2022-04-16 12:03:31,505 | server.py:211 | evaluate_round: strategy sampled 7 clients (out of 7)\n"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "Saving round 91 aggregated_weights...\n"
     ]
    },
    {
     "name": "stderr",
     "output_type": "stream",
     "text": [
      "DEBUG flower 2022-04-16 12:03:33,132 | server.py:223 | evaluate_round received 7 results and 0 failures\n",
      "INFO flower 2022-04-16 12:03:33,133 | 2719366172.py:15 | round-91-EVALUATION\n",
      "INFO flower 2022-04-16 12:03:33,135 | 2719366172.py:31 | [(1, 0.6324110627174377), (2, 0.6235294342041016), (3, 0.6934865713119507), (4, 0.7784430980682373), (5, 0.7824351191520691), (8, 0.7816091775894165), (12, 0.8237704634666443)]\n",
      "INFO flower 2022-04-16 12:03:33,136 | 2719366172.py:37 | Aggregated accuracy: 0.730812132358551 +- 0.07439352710299367\n",
      "DEBUG flower 2022-04-16 12:03:33,136 | server.py:265 | fit_round: strategy sampled 7 clients (out of 7)\n",
      "DEBUG flower 2022-04-16 12:03:37,751 | server.py:277 | fit_round received 7 results and 0 failures\n",
      "DEBUG flower 2022-04-16 12:03:37,774 | server.py:211 | evaluate_round: strategy sampled 7 clients (out of 7)\n"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "Saving round 92 aggregated_weights...\n"
     ]
    },
    {
     "name": "stderr",
     "output_type": "stream",
     "text": [
      "DEBUG flower 2022-04-16 12:03:39,499 | server.py:223 | evaluate_round received 7 results and 0 failures\n",
      "INFO flower 2022-04-16 12:03:39,499 | 2719366172.py:15 | round-92-EVALUATION\n",
      "INFO flower 2022-04-16 12:03:39,502 | 2719366172.py:31 | [(1, 0.6324110627174377), (2, 0.6196078658103943), (3, 0.6934865713119507), (4, 0.7784430980682373), (5, 0.7844311594963074), (8, 0.7816091775894165), (12, 0.8237704634666443)]\n",
      "INFO flower 2022-04-16 12:03:39,502 | 2719366172.py:37 | Aggregated accuracy: 0.7305370569229126 +- 0.07541042684558229\n",
      "DEBUG flower 2022-04-16 12:03:39,502 | server.py:265 | fit_round: strategy sampled 7 clients (out of 7)\n",
      "DEBUG flower 2022-04-16 12:03:43,963 | server.py:277 | fit_round received 7 results and 0 failures\n",
      "DEBUG flower 2022-04-16 12:03:43,980 | server.py:211 | evaluate_round: strategy sampled 7 clients (out of 7)\n"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "Saving round 93 aggregated_weights...\n"
     ]
    },
    {
     "name": "stderr",
     "output_type": "stream",
     "text": [
      "DEBUG flower 2022-04-16 12:03:45,975 | server.py:223 | evaluate_round received 7 results and 0 failures\n",
      "INFO flower 2022-04-16 12:03:45,975 | 2719366172.py:15 | round-93-EVALUATION\n",
      "INFO flower 2022-04-16 12:03:45,977 | 2719366172.py:31 | [(1, 0.6284584999084473), (2, 0.6196078658103943), (3, 0.6973180174827576), (4, 0.7784430980682373), (5, 0.7824351191520691), (8, 0.7816091775894165), (12, 0.8237704634666443)]\n",
      "INFO flower 2022-04-16 12:03:45,978 | 2719366172.py:37 | Aggregated accuracy: 0.7302346059254238 +- 0.07570375413846499\n",
      "DEBUG flower 2022-04-16 12:03:45,978 | server.py:265 | fit_round: strategy sampled 7 clients (out of 7)\n",
      "DEBUG flower 2022-04-16 12:03:50,696 | server.py:277 | fit_round received 7 results and 0 failures\n",
      "DEBUG flower 2022-04-16 12:03:50,712 | server.py:211 | evaluate_round: strategy sampled 7 clients (out of 7)\n"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "Saving round 94 aggregated_weights...\n"
     ]
    },
    {
     "name": "stderr",
     "output_type": "stream",
     "text": [
      "DEBUG flower 2022-04-16 12:03:52,440 | server.py:223 | evaluate_round received 7 results and 0 failures\n",
      "INFO flower 2022-04-16 12:03:52,440 | 2719366172.py:15 | round-94-EVALUATION\n",
      "INFO flower 2022-04-16 12:03:52,442 | 2719366172.py:31 | [(1, 0.6284584999084473), (2, 0.6117647290229797), (3, 0.6973180174827576), (4, 0.7804391384124756), (5, 0.7824351191520691), (8, 0.7816091775894165), (12, 0.8237704634666443)]\n",
      "INFO flower 2022-04-16 12:03:52,443 | 2719366172.py:37 | Aggregated accuracy: 0.7293993064335415 +- 0.07755716521220592\n",
      "DEBUG flower 2022-04-16 12:03:52,443 | server.py:265 | fit_round: strategy sampled 7 clients (out of 7)\n",
      "DEBUG flower 2022-04-16 12:03:57,216 | server.py:277 | fit_round received 7 results and 0 failures\n",
      "DEBUG flower 2022-04-16 12:03:57,233 | server.py:211 | evaluate_round: strategy sampled 7 clients (out of 7)\n"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "Saving round 95 aggregated_weights...\n"
     ]
    },
    {
     "name": "stderr",
     "output_type": "stream",
     "text": [
      "DEBUG flower 2022-04-16 12:03:59,051 | server.py:223 | evaluate_round received 7 results and 0 failures\n",
      "INFO flower 2022-04-16 12:03:59,051 | 2719366172.py:15 | round-95-EVALUATION\n",
      "INFO flower 2022-04-16 12:03:59,054 | 2719366172.py:31 | [(1, 0.6245059370994568), (2, 0.6117647290229797), (3, 0.6973180174827576), (4, 0.7824351191520691), (5, 0.7824351191520691), (8, 0.7816091775894165), (12, 0.8237704634666443)]\n",
      "INFO flower 2022-04-16 12:03:59,054 | 2719366172.py:37 | Aggregated accuracy: 0.7291197947093419 +- 0.07849163352434736\n",
      "DEBUG flower 2022-04-16 12:03:59,055 | server.py:265 | fit_round: strategy sampled 7 clients (out of 7)\n",
      "DEBUG flower 2022-04-16 12:04:03,700 | server.py:277 | fit_round received 7 results and 0 failures\n",
      "DEBUG flower 2022-04-16 12:04:03,723 | server.py:211 | evaluate_round: strategy sampled 7 clients (out of 7)\n"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "Saving round 96 aggregated_weights...\n"
     ]
    },
    {
     "name": "stderr",
     "output_type": "stream",
     "text": [
      "DEBUG flower 2022-04-16 12:04:05,423 | server.py:223 | evaluate_round received 7 results and 0 failures\n",
      "INFO flower 2022-04-16 12:04:05,423 | 2719366172.py:15 | round-96-EVALUATION\n",
      "INFO flower 2022-04-16 12:04:05,425 | 2719366172.py:31 | [(1, 0.6245059370994568), (2, 0.6117647290229797), (3, 0.6973180174827576), (4, 0.7844311594963074), (5, 0.7864271402359009), (8, 0.7816091775894165), (12, 0.8237704634666443)]\n",
      "INFO flower 2022-04-16 12:04:05,426 | 2719366172.py:37 | Aggregated accuracy: 0.7299752320562091 +- 0.07908391980935996\n",
      "DEBUG flower 2022-04-16 12:04:05,426 | server.py:265 | fit_round: strategy sampled 7 clients (out of 7)\n",
      "DEBUG flower 2022-04-16 12:04:10,182 | server.py:277 | fit_round received 7 results and 0 failures\n",
      "DEBUG flower 2022-04-16 12:04:10,200 | server.py:211 | evaluate_round: strategy sampled 7 clients (out of 7)\n"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "Saving round 97 aggregated_weights...\n"
     ]
    },
    {
     "name": "stderr",
     "output_type": "stream",
     "text": [
      "DEBUG flower 2022-04-16 12:04:11,897 | server.py:223 | evaluate_round received 7 results and 0 failures\n",
      "INFO flower 2022-04-16 12:04:11,898 | 2719366172.py:15 | round-97-EVALUATION\n",
      "INFO flower 2022-04-16 12:04:11,900 | 2719366172.py:31 | [(1, 0.6245059370994568), (2, 0.6117647290229797), (3, 0.6973180174827576), (4, 0.7844311594963074), (5, 0.7864271402359009), (8, 0.7816091775894165), (12, 0.8237704634666443)]\n",
      "INFO flower 2022-04-16 12:04:11,901 | 2719366172.py:37 | Aggregated accuracy: 0.7299752320562091 +- 0.07908391980935994\n",
      "DEBUG flower 2022-04-16 12:04:11,901 | server.py:265 | fit_round: strategy sampled 7 clients (out of 7)\n",
      "DEBUG flower 2022-04-16 12:04:16,506 | server.py:277 | fit_round received 7 results and 0 failures\n",
      "DEBUG flower 2022-04-16 12:04:16,521 | server.py:211 | evaluate_round: strategy sampled 7 clients (out of 7)\n"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "Saving round 98 aggregated_weights...\n"
     ]
    },
    {
     "name": "stderr",
     "output_type": "stream",
     "text": [
      "DEBUG flower 2022-04-16 12:04:18,342 | server.py:223 | evaluate_round received 7 results and 0 failures\n",
      "INFO flower 2022-04-16 12:04:18,343 | 2719366172.py:15 | round-98-EVALUATION\n",
      "INFO flower 2022-04-16 12:04:18,345 | 2719366172.py:31 | [(1, 0.6245059370994568), (2, 0.6117647290229797), (3, 0.7049808502197266), (4, 0.7844311594963074), (5, 0.7884231805801392), (8, 0.7816091775894165), (12, 0.8237704634666443)]\n",
      "INFO flower 2022-04-16 12:04:18,345 | 2719366172.py:37 | Aggregated accuracy: 0.7313550710678101 +- 0.07887975217853205\n",
      "DEBUG flower 2022-04-16 12:04:18,346 | server.py:265 | fit_round: strategy sampled 7 clients (out of 7)\n",
      "DEBUG flower 2022-04-16 12:04:22,869 | server.py:277 | fit_round received 7 results and 0 failures\n",
      "DEBUG flower 2022-04-16 12:04:22,893 | server.py:211 | evaluate_round: strategy sampled 7 clients (out of 7)\n"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "Saving round 99 aggregated_weights...\n"
     ]
    },
    {
     "name": "stderr",
     "output_type": "stream",
     "text": [
      "DEBUG flower 2022-04-16 12:04:24,750 | server.py:223 | evaluate_round received 7 results and 0 failures\n",
      "INFO flower 2022-04-16 12:04:24,751 | 2719366172.py:15 | round-99-EVALUATION\n",
      "INFO flower 2022-04-16 12:04:24,753 | 2719366172.py:31 | [(1, 0.6245059370994568), (2, 0.6078431606292725), (3, 0.7049808502197266), (4, 0.7844311594963074), (5, 0.7884231805801392), (8, 0.7816091775894165), (12, 0.8196721076965332)]\n",
      "INFO flower 2022-04-16 12:04:24,754 | 2719366172.py:37 | Aggregated accuracy: 0.730209367615836 +- 0.07906376720077998\n",
      "DEBUG flower 2022-04-16 12:04:24,754 | server.py:265 | fit_round: strategy sampled 7 clients (out of 7)\n",
      "DEBUG flower 2022-04-16 12:04:29,418 | server.py:277 | fit_round received 7 results and 0 failures\n",
      "DEBUG flower 2022-04-16 12:04:29,441 | server.py:211 | evaluate_round: strategy sampled 7 clients (out of 7)\n"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "Saving round 100 aggregated_weights...\n"
     ]
    },
    {
     "name": "stderr",
     "output_type": "stream",
     "text": [
      "DEBUG flower 2022-04-16 12:04:31,140 | server.py:223 | evaluate_round received 7 results and 0 failures\n",
      "INFO flower 2022-04-16 12:04:31,140 | 2719366172.py:15 | round-100-EVALUATION\n",
      "INFO flower 2022-04-16 12:04:31,143 | 2719366172.py:31 | [(1, 0.6245059370994568), (2, 0.6078431606292725), (3, 0.7049808502197266), (4, 0.7844311594963074), (5, 0.7864271402359009), (8, 0.7777777910232544), (12, 0.8196721076965332)]\n",
      "INFO flower 2022-04-16 12:04:31,143 | 2719366172.py:37 | Aggregated accuracy: 0.7293768780572074 +- 0.07850851463782495\n",
      "INFO flower 2022-04-16 12:04:31,144 | server.py:182 | FL finished in 649.2394549999999\n",
      "INFO flower 2022-04-16 12:04:31,144 | app.py:149 | app_fit: losses_distributed [(1, 0.6687900330511254), (2, 0.6540609934156096), (3, 0.6393429726519358), (4, 0.6255454756254052), (5, 0.6131654352944849), (6, 0.6022306248309952), (7, 0.5929383274121947), (8, 0.5853164634930857), (9, 0.5790637192334358), (10, 0.5740556842361058), (11, 0.5701370249602203), (12, 0.5671203422420683), (13, 0.5647869603888431), (14, 0.5629403074591147), (15, 0.5614236930945008), (16, 0.5601020939713622), (17, 0.5589815930108194), (18, 0.5580613637090986), (19, 0.5573053471547648), (20, 0.556624142613478), (21, 0.5560123750740279), (22, 0.5554303411387811), (23, 0.5548982741622179), (24, 0.5544962335266631), (25, 0.5542022609962102), (26, 0.5538878839181471), (27, 0.5535464307885807), (28, 0.5532258367051349), (29, 0.5529922807887065), (30, 0.5527540365060519), (31, 0.5525005949376337), (32, 0.5522324640585374), (33, 0.5519150007509599), (34, 0.5515525699159383), (35, 0.5512332825910018), (36, 0.55091311539047), (37, 0.5506779129742948), (38, 0.5504822338716846), (39, 0.5502821910334178), (40, 0.5500965745749709), (41, 0.5498931131903442), (42, 0.5497242355676653), (43, 0.5495583154588466), (44, 0.5494171283314224), (45, 0.5492749435856598), (46, 0.5491664444075108), (47, 0.5490688324262681), (48, 0.548963294899736), (49, 0.548877472526055), (50, 0.5488321562223988), (51, 0.5487870000603957), (52, 0.5486914457880969), (53, 0.5485882698468248), (54, 0.5484732279982844), (55, 0.5483892343689561), (56, 0.5483239253423126), (57, 0.5482443844104065), (58, 0.5481714647793602), (59, 0.5481231117683262), (60, 0.5480430434034034), (61, 0.547980652490274), (62, 0.5479387141148738), (63, 0.5479183418312894), (64, 0.5479252178267771), (65, 0.5479169769739644), (66, 0.5478951400555081), (67, 0.5478645431660181), (68, 0.5478754413358357), (69, 0.547893959328349), (70, 0.5479148898031464), (71, 0.547894171597878), (72, 0.5479183742000684), (73, 0.5479554108005207), (74, 0.5479988045794054), (75, 0.5480159788223897), (76, 0.5480295781353866), (77, 0.5480844577764585), (78, 0.548147671749596), (79, 0.5482213306772687), (80, 0.5482837141529119), (81, 0.5483350255158329), (82, 0.5483889775923559), (83, 0.5483883841909298), (84, 0.548389948564066), (85, 0.5483902094129519), (86, 0.5483888703904168), (87, 0.5484024251701543), (88, 0.5484153364632796), (89, 0.5484058264060263), (90, 0.5484284569749933), (91, 0.5484199887419836), (92, 0.548436044664605), (93, 0.5484170757090061), (94, 0.5484547268448688), (95, 0.548465794793646), (96, 0.5485623661160259), (97, 0.5486617295598523), (98, 0.5487404883379258), (99, 0.5487886416105479), (100, 0.5488658444219399)]\n",
      "INFO flower 2022-04-16 12:04:31,145 | app.py:150 | app_fit: metrics_distributed {}\n",
      "INFO flower 2022-04-16 12:04:31,145 | app.py:151 | app_fit: losses_centralized []\n",
      "INFO flower 2022-04-16 12:04:31,145 | app.py:152 | app_fit: metrics_centralized {}\n",
      "INFO flower 2022-04-16 12:04:36,878 | app.py:144 | Ray initialized with resources: {'memory': 11438901659.0, 'CPU': 8.0, 'object_store_memory': 5719450828.0, 'GPU': 1.0, 'node:127.0.0.1': 1.0}\n",
      "INFO flower 2022-04-16 12:04:36,878 | app.py:153 | Starting Flower simulation running: {'num_rounds': 100}\n",
      "INFO flower 2022-04-16 12:04:36,879 | server.py:128 | Initializing global parameters\n",
      "INFO flower 2022-04-16 12:04:36,879 | server.py:323 | Using initial parameters provided by strategy\n",
      "INFO flower 2022-04-16 12:04:36,880 | server.py:130 | Evaluating initial parameters\n",
      "INFO flower 2022-04-16 12:04:36,880 | server.py:143 | FL starting\n",
      "DEBUG flower 2022-04-16 12:04:36,880 | server.py:265 | fit_round: strategy sampled 7 clients (out of 7)\n",
      "DEBUG flower 2022-04-16 12:04:44,759 | server.py:277 | fit_round received 7 results and 0 failures\n",
      "DEBUG flower 2022-04-16 12:04:44,775 | server.py:211 | evaluate_round: strategy sampled 7 clients (out of 7)\n"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "Saving round 1 aggregated_weights...\n"
     ]
    },
    {
     "name": "stderr",
     "output_type": "stream",
     "text": [
      "DEBUG flower 2022-04-16 12:04:46,390 | server.py:223 | evaluate_round received 7 results and 0 failures\n",
      "INFO flower 2022-04-16 12:04:46,390 | 2719366172.py:15 | round-1-EVALUATION\n",
      "INFO flower 2022-04-16 12:04:46,393 | 2719366172.py:31 | [(6, 0.8488371968269348), (7, 0.7233201861381531), (10, 0.8549618124961853), (11, 0.8503937125205994), (13, 0.6198347210884094), (14, 0.6666666865348816), (16, 0.7954545617103577)]\n",
      "INFO flower 2022-04-16 12:04:46,393 | 2719366172.py:37 | Aggregated accuracy: 0.7656384110450745 +- 0.08929735429439248\n",
      "DEBUG flower 2022-04-16 12:04:46,394 | server.py:265 | fit_round: strategy sampled 7 clients (out of 7)\n",
      "DEBUG flower 2022-04-16 12:04:50,684 | server.py:277 | fit_round received 7 results and 0 failures\n",
      "DEBUG flower 2022-04-16 12:04:50,700 | server.py:211 | evaluate_round: strategy sampled 7 clients (out of 7)\n"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "Saving round 2 aggregated_weights...\n"
     ]
    },
    {
     "name": "stderr",
     "output_type": "stream",
     "text": [
      "DEBUG flower 2022-04-16 12:04:52,482 | server.py:223 | evaluate_round received 7 results and 0 failures\n",
      "INFO flower 2022-04-16 12:04:52,482 | 2719366172.py:15 | round-2-EVALUATION\n",
      "INFO flower 2022-04-16 12:04:52,484 | 2719366172.py:31 | [(6, 0.8488371968269348), (7, 0.7233201861381531), (10, 0.8549618124961853), (11, 0.8503937125205994), (13, 0.6198347210884094), (14, 0.6666666865348816), (16, 0.7954545617103577)]\n",
      "INFO flower 2022-04-16 12:04:52,485 | 2719366172.py:37 | Aggregated accuracy: 0.7656384110450745 +- 0.08929735429439248\n",
      "DEBUG flower 2022-04-16 12:04:52,485 | server.py:265 | fit_round: strategy sampled 7 clients (out of 7)\n",
      "DEBUG flower 2022-04-16 12:04:56,992 | server.py:277 | fit_round received 7 results and 0 failures\n",
      "DEBUG flower 2022-04-16 12:04:57,008 | server.py:211 | evaluate_round: strategy sampled 7 clients (out of 7)\n"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "Saving round 3 aggregated_weights...\n"
     ]
    },
    {
     "name": "stderr",
     "output_type": "stream",
     "text": [
      "DEBUG flower 2022-04-16 12:04:58,712 | server.py:223 | evaluate_round received 7 results and 0 failures\n",
      "INFO flower 2022-04-16 12:04:58,712 | 2719366172.py:15 | round-3-EVALUATION\n",
      "INFO flower 2022-04-16 12:04:58,715 | 2719366172.py:31 | [(6, 0.8488371968269348), (7, 0.7233201861381531), (10, 0.8549618124961853), (11, 0.8503937125205994), (13, 0.6198347210884094), (14, 0.6666666865348816), (16, 0.7954545617103577)]\n",
      "INFO flower 2022-04-16 12:04:58,715 | 2719366172.py:37 | Aggregated accuracy: 0.7656384110450745 +- 0.08929735429439248\n",
      "DEBUG flower 2022-04-16 12:04:58,716 | server.py:265 | fit_round: strategy sampled 7 clients (out of 7)\n",
      "DEBUG flower 2022-04-16 12:05:03,189 | server.py:277 | fit_round received 7 results and 0 failures\n",
      "DEBUG flower 2022-04-16 12:05:03,205 | server.py:211 | evaluate_round: strategy sampled 7 clients (out of 7)\n"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "Saving round 4 aggregated_weights...\n"
     ]
    },
    {
     "name": "stderr",
     "output_type": "stream",
     "text": [
      "DEBUG flower 2022-04-16 12:05:04,927 | server.py:223 | evaluate_round received 7 results and 0 failures\n",
      "INFO flower 2022-04-16 12:05:04,927 | 2719366172.py:15 | round-4-EVALUATION\n",
      "INFO flower 2022-04-16 12:05:04,929 | 2719366172.py:31 | [(6, 0.8488371968269348), (7, 0.7233201861381531), (10, 0.8549618124961853), (11, 0.8503937125205994), (13, 0.6198347210884094), (14, 0.6666666865348816), (16, 0.7954545617103577)]\n",
      "INFO flower 2022-04-16 12:05:04,930 | 2719366172.py:37 | Aggregated accuracy: 0.7656384110450745 +- 0.08929735429439248\n",
      "DEBUG flower 2022-04-16 12:05:04,930 | server.py:265 | fit_round: strategy sampled 7 clients (out of 7)\n",
      "DEBUG flower 2022-04-16 12:05:09,466 | server.py:277 | fit_round received 7 results and 0 failures\n",
      "DEBUG flower 2022-04-16 12:05:09,482 | server.py:211 | evaluate_round: strategy sampled 7 clients (out of 7)\n"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "Saving round 5 aggregated_weights...\n"
     ]
    },
    {
     "name": "stderr",
     "output_type": "stream",
     "text": [
      "DEBUG flower 2022-04-16 12:05:11,254 | server.py:223 | evaluate_round received 7 results and 0 failures\n",
      "INFO flower 2022-04-16 12:05:11,254 | 2719366172.py:15 | round-5-EVALUATION\n",
      "INFO flower 2022-04-16 12:05:11,257 | 2719366172.py:31 | [(6, 0.8488371968269348), (7, 0.7233201861381531), (10, 0.8549618124961853), (11, 0.8503937125205994), (13, 0.6198347210884094), (14, 0.6666666865348816), (16, 0.7954545617103577)]\n",
      "INFO flower 2022-04-16 12:05:11,257 | 2719366172.py:37 | Aggregated accuracy: 0.7656384110450745 +- 0.08929735429439248\n",
      "DEBUG flower 2022-04-16 12:05:11,258 | server.py:265 | fit_round: strategy sampled 7 clients (out of 7)\n",
      "DEBUG flower 2022-04-16 12:05:15,775 | server.py:277 | fit_round received 7 results and 0 failures\n",
      "DEBUG flower 2022-04-16 12:05:15,790 | server.py:211 | evaluate_round: strategy sampled 7 clients (out of 7)\n"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "Saving round 6 aggregated_weights...\n"
     ]
    },
    {
     "name": "stderr",
     "output_type": "stream",
     "text": [
      "DEBUG flower 2022-04-16 12:05:17,480 | server.py:223 | evaluate_round received 7 results and 0 failures\n",
      "INFO flower 2022-04-16 12:05:17,481 | 2719366172.py:15 | round-6-EVALUATION\n",
      "INFO flower 2022-04-16 12:05:17,483 | 2719366172.py:31 | [(6, 0.8488371968269348), (7, 0.7233201861381531), (10, 0.8549618124961853), (11, 0.8503937125205994), (13, 0.6198347210884094), (14, 0.6666666865348816), (16, 0.7954545617103577)]\n",
      "INFO flower 2022-04-16 12:05:17,484 | 2719366172.py:37 | Aggregated accuracy: 0.7656384110450745 +- 0.08929735429439248\n",
      "DEBUG flower 2022-04-16 12:05:17,484 | server.py:265 | fit_round: strategy sampled 7 clients (out of 7)\n",
      "DEBUG flower 2022-04-16 12:05:21,701 | server.py:277 | fit_round received 7 results and 0 failures\n",
      "DEBUG flower 2022-04-16 12:05:21,716 | server.py:211 | evaluate_round: strategy sampled 7 clients (out of 7)\n"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "Saving round 7 aggregated_weights...\n"
     ]
    },
    {
     "name": "stderr",
     "output_type": "stream",
     "text": [
      "DEBUG flower 2022-04-16 12:05:23,413 | server.py:223 | evaluate_round received 7 results and 0 failures\n",
      "INFO flower 2022-04-16 12:05:23,414 | 2719366172.py:15 | round-7-EVALUATION\n",
      "INFO flower 2022-04-16 12:05:23,416 | 2719366172.py:31 | [(6, 0.8488371968269348), (7, 0.7233201861381531), (10, 0.8549618124961853), (11, 0.8503937125205994), (13, 0.6198347210884094), (14, 0.6666666865348816), (16, 0.7954545617103577)]\n",
      "INFO flower 2022-04-16 12:05:23,417 | 2719366172.py:37 | Aggregated accuracy: 0.7656384110450745 +- 0.08929735429439248\n",
      "DEBUG flower 2022-04-16 12:05:23,417 | server.py:265 | fit_round: strategy sampled 7 clients (out of 7)\n",
      "DEBUG flower 2022-04-16 12:05:28,082 | server.py:277 | fit_round received 7 results and 0 failures\n",
      "DEBUG flower 2022-04-16 12:05:28,098 | server.py:211 | evaluate_round: strategy sampled 7 clients (out of 7)\n"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "Saving round 8 aggregated_weights...\n"
     ]
    },
    {
     "name": "stderr",
     "output_type": "stream",
     "text": [
      "DEBUG flower 2022-04-16 12:05:29,922 | server.py:223 | evaluate_round received 7 results and 0 failures\n",
      "INFO flower 2022-04-16 12:05:29,923 | 2719366172.py:15 | round-8-EVALUATION\n",
      "INFO flower 2022-04-16 12:05:29,925 | 2719366172.py:31 | [(6, 0.8488371968269348), (7, 0.7233201861381531), (10, 0.8549618124961853), (11, 0.8503937125205994), (13, 0.6198347210884094), (14, 0.6666666865348816), (16, 0.7954545617103577)]\n",
      "INFO flower 2022-04-16 12:05:29,926 | 2719366172.py:37 | Aggregated accuracy: 0.7656384110450745 +- 0.08929735429439248\n",
      "DEBUG flower 2022-04-16 12:05:29,926 | server.py:265 | fit_round: strategy sampled 7 clients (out of 7)\n",
      "DEBUG flower 2022-04-16 12:05:34,365 | server.py:277 | fit_round received 7 results and 0 failures\n",
      "DEBUG flower 2022-04-16 12:05:34,381 | server.py:211 | evaluate_round: strategy sampled 7 clients (out of 7)\n"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "Saving round 9 aggregated_weights...\n"
     ]
    },
    {
     "name": "stderr",
     "output_type": "stream",
     "text": [
      "DEBUG flower 2022-04-16 12:05:36,159 | server.py:223 | evaluate_round received 7 results and 0 failures\n",
      "INFO flower 2022-04-16 12:05:36,159 | 2719366172.py:15 | round-9-EVALUATION\n",
      "INFO flower 2022-04-16 12:05:36,162 | 2719366172.py:31 | [(6, 0.8488371968269348), (7, 0.7233201861381531), (10, 0.8549618124961853), (11, 0.8503937125205994), (13, 0.6198347210884094), (14, 0.6666666865348816), (16, 0.7954545617103577)]\n",
      "INFO flower 2022-04-16 12:05:36,162 | 2719366172.py:37 | Aggregated accuracy: 0.7656384110450745 +- 0.08929735429439248\n",
      "DEBUG flower 2022-04-16 12:05:36,163 | server.py:265 | fit_round: strategy sampled 7 clients (out of 7)\n",
      "DEBUG flower 2022-04-16 12:05:40,716 | server.py:277 | fit_round received 7 results and 0 failures\n",
      "DEBUG flower 2022-04-16 12:05:40,732 | server.py:211 | evaluate_round: strategy sampled 7 clients (out of 7)\n"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "Saving round 10 aggregated_weights...\n"
     ]
    },
    {
     "name": "stderr",
     "output_type": "stream",
     "text": [
      "DEBUG flower 2022-04-16 12:05:42,456 | server.py:223 | evaluate_round received 7 results and 0 failures\n",
      "INFO flower 2022-04-16 12:05:42,457 | 2719366172.py:15 | round-10-EVALUATION\n",
      "INFO flower 2022-04-16 12:05:42,459 | 2719366172.py:31 | [(6, 0.8488371968269348), (7, 0.7233201861381531), (10, 0.8549618124961853), (11, 0.8503937125205994), (13, 0.6198347210884094), (14, 0.6666666865348816), (16, 0.7954545617103577)]\n",
      "INFO flower 2022-04-16 12:05:42,460 | 2719366172.py:37 | Aggregated accuracy: 0.7656384110450745 +- 0.08929735429439248\n",
      "DEBUG flower 2022-04-16 12:05:42,460 | server.py:265 | fit_round: strategy sampled 7 clients (out of 7)\n",
      "DEBUG flower 2022-04-16 12:05:46,999 | server.py:277 | fit_round received 7 results and 0 failures\n",
      "DEBUG flower 2022-04-16 12:05:47,014 | server.py:211 | evaluate_round: strategy sampled 7 clients (out of 7)\n"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "Saving round 11 aggregated_weights...\n"
     ]
    },
    {
     "name": "stderr",
     "output_type": "stream",
     "text": [
      "DEBUG flower 2022-04-16 12:05:48,663 | server.py:223 | evaluate_round received 7 results and 0 failures\n",
      "INFO flower 2022-04-16 12:05:48,663 | 2719366172.py:15 | round-11-EVALUATION\n",
      "INFO flower 2022-04-16 12:05:48,665 | 2719366172.py:31 | [(6, 0.8488371968269348), (7, 0.7233201861381531), (10, 0.8549618124961853), (11, 0.8503937125205994), (13, 0.6198347210884094), (14, 0.6666666865348816), (16, 0.7954545617103577)]\n",
      "INFO flower 2022-04-16 12:05:48,666 | 2719366172.py:37 | Aggregated accuracy: 0.7656384110450745 +- 0.08929735429439248\n",
      "DEBUG flower 2022-04-16 12:05:48,667 | server.py:265 | fit_round: strategy sampled 7 clients (out of 7)\n",
      "DEBUG flower 2022-04-16 12:05:52,889 | server.py:277 | fit_round received 7 results and 0 failures\n",
      "DEBUG flower 2022-04-16 12:05:52,904 | server.py:211 | evaluate_round: strategy sampled 7 clients (out of 7)\n"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "Saving round 12 aggregated_weights...\n"
     ]
    },
    {
     "name": "stderr",
     "output_type": "stream",
     "text": [
      "DEBUG flower 2022-04-16 12:05:54,504 | server.py:223 | evaluate_round received 7 results and 0 failures\n",
      "INFO flower 2022-04-16 12:05:54,504 | 2719366172.py:15 | round-12-EVALUATION\n",
      "INFO flower 2022-04-16 12:05:54,506 | 2719366172.py:31 | [(6, 0.8488371968269348), (7, 0.7233201861381531), (10, 0.8549618124961853), (11, 0.8503937125205994), (13, 0.6198347210884094), (14, 0.6666666865348816), (16, 0.7954545617103577)]\n",
      "INFO flower 2022-04-16 12:05:54,507 | 2719366172.py:37 | Aggregated accuracy: 0.7656384110450745 +- 0.08929735429439248\n",
      "DEBUG flower 2022-04-16 12:05:54,507 | server.py:265 | fit_round: strategy sampled 7 clients (out of 7)\n",
      "DEBUG flower 2022-04-16 12:05:58,861 | server.py:277 | fit_round received 7 results and 0 failures\n",
      "DEBUG flower 2022-04-16 12:05:58,876 | server.py:211 | evaluate_round: strategy sampled 7 clients (out of 7)\n"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "Saving round 13 aggregated_weights...\n"
     ]
    },
    {
     "name": "stderr",
     "output_type": "stream",
     "text": [
      "DEBUG flower 2022-04-16 12:06:00,556 | server.py:223 | evaluate_round received 7 results and 0 failures\n",
      "INFO flower 2022-04-16 12:06:00,556 | 2719366172.py:15 | round-13-EVALUATION\n",
      "INFO flower 2022-04-16 12:06:00,559 | 2719366172.py:31 | [(6, 0.8488371968269348), (7, 0.7233201861381531), (10, 0.8549618124961853), (11, 0.8503937125205994), (13, 0.6198347210884094), (14, 0.6666666865348816), (16, 0.7954545617103577)]\n",
      "INFO flower 2022-04-16 12:06:00,559 | 2719366172.py:37 | Aggregated accuracy: 0.7656384110450745 +- 0.08929735429439248\n",
      "DEBUG flower 2022-04-16 12:06:00,559 | server.py:265 | fit_round: strategy sampled 7 clients (out of 7)\n",
      "DEBUG flower 2022-04-16 12:06:04,672 | server.py:277 | fit_round received 7 results and 0 failures\n",
      "DEBUG flower 2022-04-16 12:06:04,688 | server.py:211 | evaluate_round: strategy sampled 7 clients (out of 7)\n"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "Saving round 14 aggregated_weights...\n"
     ]
    },
    {
     "name": "stderr",
     "output_type": "stream",
     "text": [
      "DEBUG flower 2022-04-16 12:06:06,284 | server.py:223 | evaluate_round received 7 results and 0 failures\n",
      "INFO flower 2022-04-16 12:06:06,284 | 2719366172.py:15 | round-14-EVALUATION\n",
      "INFO flower 2022-04-16 12:06:06,287 | 2719366172.py:31 | [(6, 0.8488371968269348), (7, 0.7233201861381531), (10, 0.8549618124961853), (11, 0.8503937125205994), (13, 0.6198347210884094), (14, 0.6666666865348816), (16, 0.7954545617103577)]\n",
      "INFO flower 2022-04-16 12:06:06,287 | 2719366172.py:37 | Aggregated accuracy: 0.7656384110450745 +- 0.08929735429439248\n",
      "DEBUG flower 2022-04-16 12:06:06,288 | server.py:265 | fit_round: strategy sampled 7 clients (out of 7)\n",
      "DEBUG flower 2022-04-16 12:06:10,681 | server.py:277 | fit_round received 7 results and 0 failures\n",
      "DEBUG flower 2022-04-16 12:06:10,697 | server.py:211 | evaluate_round: strategy sampled 7 clients (out of 7)\n"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "Saving round 15 aggregated_weights...\n"
     ]
    },
    {
     "name": "stderr",
     "output_type": "stream",
     "text": [
      "DEBUG flower 2022-04-16 12:06:12,305 | server.py:223 | evaluate_round received 7 results and 0 failures\n",
      "INFO flower 2022-04-16 12:06:12,305 | 2719366172.py:15 | round-15-EVALUATION\n",
      "INFO flower 2022-04-16 12:06:12,308 | 2719366172.py:31 | [(6, 0.8488371968269348), (7, 0.7233201861381531), (10, 0.8549618124961853), (11, 0.8503937125205994), (13, 0.6198347210884094), (14, 0.6666666865348816), (16, 0.7954545617103577)]\n",
      "INFO flower 2022-04-16 12:06:12,308 | 2719366172.py:37 | Aggregated accuracy: 0.7656384110450745 +- 0.08929735429439248\n",
      "DEBUG flower 2022-04-16 12:06:12,309 | server.py:265 | fit_round: strategy sampled 7 clients (out of 7)\n",
      "DEBUG flower 2022-04-16 12:06:16,618 | server.py:277 | fit_round received 7 results and 0 failures\n",
      "DEBUG flower 2022-04-16 12:06:16,634 | server.py:211 | evaluate_round: strategy sampled 7 clients (out of 7)\n"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "Saving round 16 aggregated_weights...\n"
     ]
    },
    {
     "name": "stderr",
     "output_type": "stream",
     "text": [
      "DEBUG flower 2022-04-16 12:06:18,435 | server.py:223 | evaluate_round received 7 results and 0 failures\n",
      "INFO flower 2022-04-16 12:06:18,436 | 2719366172.py:15 | round-16-EVALUATION\n",
      "INFO flower 2022-04-16 12:06:18,438 | 2719366172.py:31 | [(6, 0.8488371968269348), (7, 0.7233201861381531), (10, 0.8549618124961853), (11, 0.8503937125205994), (13, 0.6198347210884094), (14, 0.6666666865348816), (16, 0.7954545617103577)]\n",
      "INFO flower 2022-04-16 12:06:18,439 | 2719366172.py:37 | Aggregated accuracy: 0.7656384110450745 +- 0.08929735429439248\n",
      "DEBUG flower 2022-04-16 12:06:18,439 | server.py:265 | fit_round: strategy sampled 7 clients (out of 7)\n",
      "DEBUG flower 2022-04-16 12:06:23,139 | server.py:277 | fit_round received 7 results and 0 failures\n",
      "DEBUG flower 2022-04-16 12:06:23,155 | server.py:211 | evaluate_round: strategy sampled 7 clients (out of 7)\n"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "Saving round 17 aggregated_weights...\n"
     ]
    },
    {
     "name": "stderr",
     "output_type": "stream",
     "text": [
      "DEBUG flower 2022-04-16 12:06:24,844 | server.py:223 | evaluate_round received 7 results and 0 failures\n",
      "INFO flower 2022-04-16 12:06:24,845 | 2719366172.py:15 | round-17-EVALUATION\n",
      "INFO flower 2022-04-16 12:06:24,847 | 2719366172.py:31 | [(6, 0.8488371968269348), (7, 0.7233201861381531), (10, 0.8549618124961853), (11, 0.8503937125205994), (13, 0.6198347210884094), (14, 0.6666666865348816), (16, 0.7954545617103577)]\n",
      "INFO flower 2022-04-16 12:06:24,848 | 2719366172.py:37 | Aggregated accuracy: 0.7656384110450745 +- 0.08929735429439248\n",
      "DEBUG flower 2022-04-16 12:06:24,848 | server.py:265 | fit_round: strategy sampled 7 clients (out of 7)\n",
      "DEBUG flower 2022-04-16 12:06:29,298 | server.py:277 | fit_round received 7 results and 0 failures\n",
      "DEBUG flower 2022-04-16 12:06:29,313 | server.py:211 | evaluate_round: strategy sampled 7 clients (out of 7)\n"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "Saving round 18 aggregated_weights...\n"
     ]
    },
    {
     "name": "stderr",
     "output_type": "stream",
     "text": [
      "DEBUG flower 2022-04-16 12:06:30,907 | server.py:223 | evaluate_round received 7 results and 0 failures\n",
      "INFO flower 2022-04-16 12:06:30,908 | 2719366172.py:15 | round-18-EVALUATION\n",
      "INFO flower 2022-04-16 12:06:30,910 | 2719366172.py:31 | [(6, 0.8488371968269348), (7, 0.7233201861381531), (10, 0.8549618124961853), (11, 0.8503937125205994), (13, 0.6198347210884094), (14, 0.6666666865348816), (16, 0.7954545617103577)]\n",
      "INFO flower 2022-04-16 12:06:30,910 | 2719366172.py:37 | Aggregated accuracy: 0.7656384110450745 +- 0.08929735429439248\n",
      "DEBUG flower 2022-04-16 12:06:30,911 | server.py:265 | fit_round: strategy sampled 7 clients (out of 7)\n",
      "DEBUG flower 2022-04-16 12:06:35,356 | server.py:277 | fit_round received 7 results and 0 failures\n",
      "DEBUG flower 2022-04-16 12:06:35,371 | server.py:211 | evaluate_round: strategy sampled 7 clients (out of 7)\n"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "Saving round 19 aggregated_weights...\n"
     ]
    },
    {
     "name": "stderr",
     "output_type": "stream",
     "text": [
      "DEBUG flower 2022-04-16 12:06:36,995 | server.py:223 | evaluate_round received 7 results and 0 failures\n",
      "INFO flower 2022-04-16 12:06:36,996 | 2719366172.py:15 | round-19-EVALUATION\n",
      "INFO flower 2022-04-16 12:06:36,998 | 2719366172.py:31 | [(6, 0.8488371968269348), (7, 0.7233201861381531), (10, 0.8549618124961853), (11, 0.8503937125205994), (13, 0.6198347210884094), (14, 0.6666666865348816), (16, 0.7954545617103577)]\n",
      "INFO flower 2022-04-16 12:06:36,998 | 2719366172.py:37 | Aggregated accuracy: 0.7656384110450745 +- 0.08929735429439248\n",
      "DEBUG flower 2022-04-16 12:06:36,999 | server.py:265 | fit_round: strategy sampled 7 clients (out of 7)\n",
      "DEBUG flower 2022-04-16 12:06:41,179 | server.py:277 | fit_round received 7 results and 0 failures\n",
      "DEBUG flower 2022-04-16 12:06:41,194 | server.py:211 | evaluate_round: strategy sampled 7 clients (out of 7)\n"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "Saving round 20 aggregated_weights...\n"
     ]
    },
    {
     "name": "stderr",
     "output_type": "stream",
     "text": [
      "DEBUG flower 2022-04-16 12:06:42,902 | server.py:223 | evaluate_round received 7 results and 0 failures\n",
      "INFO flower 2022-04-16 12:06:42,902 | 2719366172.py:15 | round-20-EVALUATION\n",
      "INFO flower 2022-04-16 12:06:42,905 | 2719366172.py:31 | [(6, 0.8488371968269348), (7, 0.7233201861381531), (10, 0.8549618124961853), (11, 0.8503937125205994), (13, 0.6198347210884094), (14, 0.6666666865348816), (16, 0.7954545617103577)]\n",
      "INFO flower 2022-04-16 12:06:42,905 | 2719366172.py:37 | Aggregated accuracy: 0.7656384110450745 +- 0.08929735429439248\n",
      "DEBUG flower 2022-04-16 12:06:42,906 | server.py:265 | fit_round: strategy sampled 7 clients (out of 7)\n",
      "DEBUG flower 2022-04-16 12:06:47,333 | server.py:277 | fit_round received 7 results and 0 failures\n",
      "DEBUG flower 2022-04-16 12:06:47,349 | server.py:211 | evaluate_round: strategy sampled 7 clients (out of 7)\n"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "Saving round 21 aggregated_weights...\n"
     ]
    },
    {
     "name": "stderr",
     "output_type": "stream",
     "text": [
      "DEBUG flower 2022-04-16 12:06:49,192 | server.py:223 | evaluate_round received 7 results and 0 failures\n",
      "INFO flower 2022-04-16 12:06:49,192 | 2719366172.py:15 | round-21-EVALUATION\n",
      "INFO flower 2022-04-16 12:06:49,195 | 2719366172.py:31 | [(6, 0.8488371968269348), (7, 0.7233201861381531), (10, 0.8549618124961853), (11, 0.8503937125205994), (13, 0.6239669322967529), (14, 0.6666666865348816), (16, 0.7954545617103577)]\n",
      "INFO flower 2022-04-16 12:06:49,195 | 2719366172.py:37 | Aggregated accuracy: 0.7662287269319806 +- 0.08834006934542402\n",
      "DEBUG flower 2022-04-16 12:06:49,196 | server.py:265 | fit_round: strategy sampled 7 clients (out of 7)\n",
      "DEBUG flower 2022-04-16 12:06:53,455 | server.py:277 | fit_round received 7 results and 0 failures\n",
      "DEBUG flower 2022-04-16 12:06:53,470 | server.py:211 | evaluate_round: strategy sampled 7 clients (out of 7)\n"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "Saving round 22 aggregated_weights...\n"
     ]
    },
    {
     "name": "stderr",
     "output_type": "stream",
     "text": [
      "DEBUG flower 2022-04-16 12:06:55,128 | server.py:223 | evaluate_round received 7 results and 0 failures\n",
      "INFO flower 2022-04-16 12:06:55,129 | 2719366172.py:15 | round-22-EVALUATION\n",
      "INFO flower 2022-04-16 12:06:55,131 | 2719366172.py:31 | [(6, 0.8488371968269348), (7, 0.7233201861381531), (10, 0.8549618124961853), (11, 0.8503937125205994), (13, 0.6239669322967529), (14, 0.6666666865348816), (16, 0.7954545617103577)]\n",
      "INFO flower 2022-04-16 12:06:55,131 | 2719366172.py:37 | Aggregated accuracy: 0.7662287269319806 +- 0.088340069345424\n",
      "DEBUG flower 2022-04-16 12:06:55,132 | server.py:265 | fit_round: strategy sampled 7 clients (out of 7)\n",
      "DEBUG flower 2022-04-16 12:06:59,409 | server.py:277 | fit_round received 7 results and 0 failures\n",
      "DEBUG flower 2022-04-16 12:06:59,425 | server.py:211 | evaluate_round: strategy sampled 7 clients (out of 7)\n"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "Saving round 23 aggregated_weights...\n"
     ]
    },
    {
     "name": "stderr",
     "output_type": "stream",
     "text": [
      "DEBUG flower 2022-04-16 12:07:01,138 | server.py:223 | evaluate_round received 7 results and 0 failures\n",
      "INFO flower 2022-04-16 12:07:01,138 | 2719366172.py:15 | round-23-EVALUATION\n",
      "INFO flower 2022-04-16 12:07:01,140 | 2719366172.py:31 | [(6, 0.8488371968269348), (7, 0.7193675637245178), (10, 0.8549618124961853), (11, 0.8385826945304871), (13, 0.6239669322967529), (14, 0.6666666865348816), (16, 0.7954545617103577)]\n",
      "INFO flower 2022-04-16 12:07:01,141 | 2719366172.py:37 | Aggregated accuracy: 0.7639767783028739 +- 0.08709473793150073\n",
      "DEBUG flower 2022-04-16 12:07:01,141 | server.py:265 | fit_round: strategy sampled 7 clients (out of 7)\n",
      "DEBUG flower 2022-04-16 12:07:05,603 | server.py:277 | fit_round received 7 results and 0 failures\n",
      "DEBUG flower 2022-04-16 12:07:05,618 | server.py:211 | evaluate_round: strategy sampled 7 clients (out of 7)\n"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "Saving round 24 aggregated_weights...\n"
     ]
    },
    {
     "name": "stderr",
     "output_type": "stream",
     "text": [
      "DEBUG flower 2022-04-16 12:07:07,282 | server.py:223 | evaluate_round received 7 results and 0 failures\n",
      "INFO flower 2022-04-16 12:07:07,283 | 2719366172.py:15 | round-24-EVALUATION\n",
      "INFO flower 2022-04-16 12:07:07,285 | 2719366172.py:31 | [(6, 0.8488371968269348), (7, 0.7193675637245178), (10, 0.8549618124961853), (11, 0.8385826945304871), (13, 0.6239669322967529), (14, 0.6666666865348816), (16, 0.7954545617103577)]\n",
      "INFO flower 2022-04-16 12:07:07,285 | 2719366172.py:37 | Aggregated accuracy: 0.7639767783028739 +- 0.08709473793150072\n",
      "DEBUG flower 2022-04-16 12:07:07,287 | server.py:265 | fit_round: strategy sampled 7 clients (out of 7)\n",
      "DEBUG flower 2022-04-16 12:07:12,099 | server.py:277 | fit_round received 7 results and 0 failures\n",
      "DEBUG flower 2022-04-16 12:07:12,115 | server.py:211 | evaluate_round: strategy sampled 7 clients (out of 7)\n"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "Saving round 25 aggregated_weights...\n"
     ]
    },
    {
     "name": "stderr",
     "output_type": "stream",
     "text": [
      "DEBUG flower 2022-04-16 12:07:13,897 | server.py:223 | evaluate_round received 7 results and 0 failures\n",
      "INFO flower 2022-04-16 12:07:13,897 | 2719366172.py:15 | round-25-EVALUATION\n",
      "INFO flower 2022-04-16 12:07:13,899 | 2719366172.py:31 | [(6, 0.8488371968269348), (7, 0.7193675637245178), (10, 0.8549618124961853), (11, 0.834645688533783), (13, 0.6239669322967529), (14, 0.6666666865348816), (16, 0.7954545617103577)]\n",
      "INFO flower 2022-04-16 12:07:13,900 | 2719366172.py:37 | Aggregated accuracy: 0.7634143488747733 +- 0.08662257333358735\n",
      "DEBUG flower 2022-04-16 12:07:13,901 | server.py:265 | fit_round: strategy sampled 7 clients (out of 7)\n",
      "DEBUG flower 2022-04-16 12:07:18,363 | server.py:277 | fit_round received 7 results and 0 failures\n",
      "DEBUG flower 2022-04-16 12:07:18,379 | server.py:211 | evaluate_round: strategy sampled 7 clients (out of 7)\n"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "Saving round 26 aggregated_weights...\n"
     ]
    },
    {
     "name": "stderr",
     "output_type": "stream",
     "text": [
      "DEBUG flower 2022-04-16 12:07:20,030 | server.py:223 | evaluate_round received 7 results and 0 failures\n",
      "INFO flower 2022-04-16 12:07:20,030 | 2719366172.py:15 | round-26-EVALUATION\n",
      "INFO flower 2022-04-16 12:07:20,033 | 2719366172.py:31 | [(6, 0.8488371968269348), (7, 0.7193675637245178), (10, 0.8549618124961853), (11, 0.834645688533783), (13, 0.6280992031097412), (14, 0.6666666865348816), (16, 0.7954545617103577)]\n",
      "INFO flower 2022-04-16 12:07:20,034 | 2719366172.py:37 | Aggregated accuracy: 0.7640046732766288 +- 0.08567918465278397\n",
      "DEBUG flower 2022-04-16 12:07:20,034 | server.py:265 | fit_round: strategy sampled 7 clients (out of 7)\n",
      "DEBUG flower 2022-04-16 12:07:24,344 | server.py:277 | fit_round received 7 results and 0 failures\n",
      "DEBUG flower 2022-04-16 12:07:24,360 | server.py:211 | evaluate_round: strategy sampled 7 clients (out of 7)\n"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "Saving round 27 aggregated_weights...\n"
     ]
    },
    {
     "name": "stderr",
     "output_type": "stream",
     "text": [
      "DEBUG flower 2022-04-16 12:07:26,060 | server.py:223 | evaluate_round received 7 results and 0 failures\n",
      "INFO flower 2022-04-16 12:07:26,060 | 2719366172.py:15 | round-27-EVALUATION\n",
      "INFO flower 2022-04-16 12:07:26,062 | 2719366172.py:31 | [(6, 0.8488371968269348), (7, 0.7193675637245178), (10, 0.8587786555290222), (11, 0.8425197005271912), (13, 0.6280992031097412), (14, 0.6666666865348816), (16, 0.7954545617103577)]\n",
      "INFO flower 2022-04-16 12:07:26,063 | 2719366172.py:37 | Aggregated accuracy: 0.7656747954232352 +- 0.08721917927025252\n",
      "DEBUG flower 2022-04-16 12:07:26,063 | server.py:265 | fit_round: strategy sampled 7 clients (out of 7)\n",
      "DEBUG flower 2022-04-16 12:07:30,259 | server.py:277 | fit_round received 7 results and 0 failures\n",
      "DEBUG flower 2022-04-16 12:07:30,274 | server.py:211 | evaluate_round: strategy sampled 7 clients (out of 7)\n"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "Saving round 28 aggregated_weights...\n"
     ]
    },
    {
     "name": "stderr",
     "output_type": "stream",
     "text": [
      "DEBUG flower 2022-04-16 12:07:31,866 | server.py:223 | evaluate_round received 7 results and 0 failures\n",
      "INFO flower 2022-04-16 12:07:31,866 | 2719366172.py:15 | round-28-EVALUATION\n",
      "INFO flower 2022-04-16 12:07:31,868 | 2719366172.py:31 | [(6, 0.8488371968269348), (7, 0.7193675637245178), (10, 0.8625954389572144), (11, 0.8425197005271912), (13, 0.6280992031097412), (14, 0.6666666865348816), (16, 0.7954545617103577)]\n",
      "INFO flower 2022-04-16 12:07:31,869 | 2719366172.py:37 | Aggregated accuracy: 0.7662200501986912 +- 0.08780945107372858\n",
      "DEBUG flower 2022-04-16 12:07:31,869 | server.py:265 | fit_round: strategy sampled 7 clients (out of 7)\n",
      "DEBUG flower 2022-04-16 12:07:36,053 | server.py:277 | fit_round received 7 results and 0 failures\n",
      "DEBUG flower 2022-04-16 12:07:36,069 | server.py:211 | evaluate_round: strategy sampled 7 clients (out of 7)\n"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "Saving round 29 aggregated_weights...\n"
     ]
    },
    {
     "name": "stderr",
     "output_type": "stream",
     "text": [
      "DEBUG flower 2022-04-16 12:07:37,652 | server.py:223 | evaluate_round received 7 results and 0 failures\n",
      "INFO flower 2022-04-16 12:07:37,653 | 2719366172.py:15 | round-29-EVALUATION\n",
      "INFO flower 2022-04-16 12:07:37,655 | 2719366172.py:31 | [(6, 0.8488371968269348), (7, 0.7154150009155273), (10, 0.8664122223854065), (11, 0.8425197005271912), (13, 0.6280992031097412), (14, 0.6666666865348816), (16, 0.7954545617103577)]\n",
      "INFO flower 2022-04-16 12:07:37,655 | 2719366172.py:37 | Aggregated accuracy: 0.7662006531442914 +- 0.08872891991449874\n",
      "DEBUG flower 2022-04-16 12:07:37,656 | server.py:265 | fit_round: strategy sampled 7 clients (out of 7)\n",
      "DEBUG flower 2022-04-16 12:07:41,848 | server.py:277 | fit_round received 7 results and 0 failures\n",
      "DEBUG flower 2022-04-16 12:07:41,863 | server.py:211 | evaluate_round: strategy sampled 7 clients (out of 7)\n"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "Saving round 30 aggregated_weights...\n"
     ]
    },
    {
     "name": "stderr",
     "output_type": "stream",
     "text": [
      "DEBUG flower 2022-04-16 12:07:43,623 | server.py:223 | evaluate_round received 7 results and 0 failures\n",
      "INFO flower 2022-04-16 12:07:43,624 | 2719366172.py:15 | round-30-EVALUATION\n",
      "INFO flower 2022-04-16 12:07:43,626 | 2719366172.py:31 | [(6, 0.8488371968269348), (7, 0.7154150009155273), (10, 0.8702290058135986), (11, 0.8267716765403748), (13, 0.6363636255264282), (14, 0.6666666865348816), (16, 0.7992424368858337)]\n",
      "INFO flower 2022-04-16 12:07:43,627 | 2719366172.py:37 | Aggregated accuracy: 0.7662179470062256 +- 0.08598600341864378\n",
      "DEBUG flower 2022-04-16 12:07:43,627 | server.py:265 | fit_round: strategy sampled 7 clients (out of 7)\n",
      "DEBUG flower 2022-04-16 12:07:47,857 | server.py:277 | fit_round received 7 results and 0 failures\n",
      "DEBUG flower 2022-04-16 12:07:47,872 | server.py:211 | evaluate_round: strategy sampled 7 clients (out of 7)\n"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "Saving round 31 aggregated_weights...\n"
     ]
    },
    {
     "name": "stderr",
     "output_type": "stream",
     "text": [
      "DEBUG flower 2022-04-16 12:07:49,500 | server.py:223 | evaluate_round received 7 results and 0 failures\n",
      "INFO flower 2022-04-16 12:07:49,501 | 2719366172.py:15 | round-31-EVALUATION\n",
      "INFO flower 2022-04-16 12:07:49,503 | 2719366172.py:31 | [(6, 0.8488371968269348), (7, 0.7154150009155273), (10, 0.8740457892417908), (11, 0.8267716765403748), (13, 0.6404958963394165), (14, 0.6708333492279053), (16, 0.8030303120613098)]\n",
      "INFO flower 2022-04-16 12:07:49,504 | 2719366172.py:37 | Aggregated accuracy: 0.7684898887361798 +- 0.0852925647384864\n",
      "DEBUG flower 2022-04-16 12:07:49,504 | server.py:265 | fit_round: strategy sampled 7 clients (out of 7)\n",
      "DEBUG flower 2022-04-16 12:07:54,082 | server.py:277 | fit_round received 7 results and 0 failures\n",
      "DEBUG flower 2022-04-16 12:07:54,098 | server.py:211 | evaluate_round: strategy sampled 7 clients (out of 7)\n"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "Saving round 32 aggregated_weights...\n"
     ]
    },
    {
     "name": "stderr",
     "output_type": "stream",
     "text": [
      "DEBUG flower 2022-04-16 12:07:55,784 | server.py:223 | evaluate_round received 7 results and 0 failures\n",
      "INFO flower 2022-04-16 12:07:55,784 | 2719366172.py:15 | round-32-EVALUATION\n",
      "INFO flower 2022-04-16 12:07:55,787 | 2719366172.py:31 | [(6, 0.8488371968269348), (7, 0.7154150009155273), (10, 0.8816794157028198), (11, 0.8228346705436707), (13, 0.6404958963394165), (14, 0.6708333492279053), (16, 0.8068181872367859)]\n",
      "INFO flower 2022-04-16 12:07:55,787 | 2719366172.py:37 | Aggregated accuracy: 0.7695591023990086 +- 0.086535026515765\n",
      "DEBUG flower 2022-04-16 12:07:55,788 | server.py:265 | fit_round: strategy sampled 7 clients (out of 7)\n",
      "DEBUG flower 2022-04-16 12:08:00,303 | server.py:277 | fit_round received 7 results and 0 failures\n",
      "DEBUG flower 2022-04-16 12:08:00,319 | server.py:211 | evaluate_round: strategy sampled 7 clients (out of 7)\n"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "Saving round 33 aggregated_weights...\n"
     ]
    },
    {
     "name": "stderr",
     "output_type": "stream",
     "text": [
      "DEBUG flower 2022-04-16 12:08:01,985 | server.py:223 | evaluate_round received 7 results and 0 failures\n",
      "INFO flower 2022-04-16 12:08:01,985 | 2719366172.py:15 | round-33-EVALUATION\n",
      "INFO flower 2022-04-16 12:08:01,987 | 2719366172.py:31 | [(6, 0.8488371968269348), (7, 0.7154150009155273), (10, 0.8740457892417908), (11, 0.8110235929489136), (13, 0.64462810754776), (14, 0.6708333492279053), (16, 0.810606062412262)]\n",
      "INFO flower 2022-04-16 12:08:01,988 | 2719366172.py:37 | Aggregated accuracy: 0.7679127284458706 +- 0.08355817357234287\n",
      "DEBUG flower 2022-04-16 12:08:01,988 | server.py:265 | fit_round: strategy sampled 7 clients (out of 7)\n",
      "DEBUG flower 2022-04-16 12:08:06,308 | server.py:277 | fit_round received 7 results and 0 failures\n",
      "DEBUG flower 2022-04-16 12:08:06,323 | server.py:211 | evaluate_round: strategy sampled 7 clients (out of 7)\n"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "Saving round 34 aggregated_weights...\n"
     ]
    },
    {
     "name": "stderr",
     "output_type": "stream",
     "text": [
      "DEBUG flower 2022-04-16 12:08:08,117 | server.py:223 | evaluate_round received 7 results and 0 failures\n",
      "INFO flower 2022-04-16 12:08:08,117 | 2719366172.py:15 | round-34-EVALUATION\n",
      "INFO flower 2022-04-16 12:08:08,119 | 2719366172.py:31 | [(6, 0.8488371968269348), (7, 0.7193675637245178), (10, 0.8778625726699829), (11, 0.8110235929489136), (13, 0.6528925895690918), (14, 0.6708333492279053), (16, 0.8181818127632141)]\n",
      "INFO flower 2022-04-16 12:08:08,120 | 2719366172.py:37 | Aggregated accuracy: 0.77128552539008 +- 0.08276844310983553\n",
      "DEBUG flower 2022-04-16 12:08:08,121 | server.py:265 | fit_round: strategy sampled 7 clients (out of 7)\n",
      "DEBUG flower 2022-04-16 12:08:12,543 | server.py:277 | fit_round received 7 results and 0 failures\n",
      "DEBUG flower 2022-04-16 12:08:12,558 | server.py:211 | evaluate_round: strategy sampled 7 clients (out of 7)\n"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "Saving round 35 aggregated_weights...\n"
     ]
    },
    {
     "name": "stderr",
     "output_type": "stream",
     "text": [
      "DEBUG flower 2022-04-16 12:08:14,242 | server.py:223 | evaluate_round received 7 results and 0 failures\n",
      "INFO flower 2022-04-16 12:08:14,243 | 2719366172.py:15 | round-35-EVALUATION\n",
      "INFO flower 2022-04-16 12:08:14,245 | 2719366172.py:31 | [(6, 0.8488371968269348), (7, 0.7193675637245178), (10, 0.8740457892417908), (11, 0.8110235929489136), (13, 0.6652892827987671), (14, 0.675000011920929), (16, 0.8257575631141663)]\n",
      "INFO flower 2022-04-16 12:08:14,245 | 2719366172.py:37 | Aggregated accuracy: 0.7741887143680027 +- 0.07951893684971109\n",
      "DEBUG flower 2022-04-16 12:08:14,246 | server.py:265 | fit_round: strategy sampled 7 clients (out of 7)\n",
      "DEBUG flower 2022-04-16 12:08:18,747 | server.py:277 | fit_round received 7 results and 0 failures\n",
      "DEBUG flower 2022-04-16 12:08:18,762 | server.py:211 | evaluate_round: strategy sampled 7 clients (out of 7)\n"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "Saving round 36 aggregated_weights...\n"
     ]
    },
    {
     "name": "stderr",
     "output_type": "stream",
     "text": [
      "DEBUG flower 2022-04-16 12:08:20,572 | server.py:223 | evaluate_round received 7 results and 0 failures\n",
      "INFO flower 2022-04-16 12:08:20,573 | 2719366172.py:15 | round-36-EVALUATION\n",
      "INFO flower 2022-04-16 12:08:20,575 | 2719366172.py:31 | [(6, 0.8488371968269348), (7, 0.7193675637245178), (10, 0.8740457892417908), (11, 0.8149606585502625), (13, 0.6694214940071106), (14, 0.675000011920929), (16, 0.8295454382896423)]\n",
      "INFO flower 2022-04-16 12:08:20,576 | 2719366172.py:37 | Aggregated accuracy: 0.7758825932230268 +- 0.07934589086996412\n",
      "DEBUG flower 2022-04-16 12:08:20,576 | server.py:265 | fit_round: strategy sampled 7 clients (out of 7)\n",
      "DEBUG flower 2022-04-16 12:08:24,877 | server.py:277 | fit_round received 7 results and 0 failures\n",
      "DEBUG flower 2022-04-16 12:08:24,893 | server.py:211 | evaluate_round: strategy sampled 7 clients (out of 7)\n"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "Saving round 37 aggregated_weights...\n"
     ]
    },
    {
     "name": "stderr",
     "output_type": "stream",
     "text": [
      "DEBUG flower 2022-04-16 12:08:26,505 | server.py:223 | evaluate_round received 7 results and 0 failures\n",
      "INFO flower 2022-04-16 12:08:26,506 | 2719366172.py:15 | round-37-EVALUATION\n",
      "INFO flower 2022-04-16 12:08:26,508 | 2719366172.py:31 | [(6, 0.8488371968269348), (7, 0.7154150009155273), (10, 0.8702290058135986), (11, 0.8110235929489136), (13, 0.6776859760284424), (14, 0.6791666746139526), (16, 0.8371211886405945)]\n",
      "INFO flower 2022-04-16 12:08:26,509 | 2719366172.py:37 | Aggregated accuracy: 0.7770683765411377 +- 0.07732279914372445\n",
      "DEBUG flower 2022-04-16 12:08:26,509 | server.py:265 | fit_round: strategy sampled 7 clients (out of 7)\n",
      "DEBUG flower 2022-04-16 12:08:31,180 | server.py:277 | fit_round received 7 results and 0 failures\n",
      "DEBUG flower 2022-04-16 12:08:31,197 | server.py:211 | evaluate_round: strategy sampled 7 clients (out of 7)\n"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "Saving round 38 aggregated_weights...\n"
     ]
    },
    {
     "name": "stderr",
     "output_type": "stream",
     "text": [
      "DEBUG flower 2022-04-16 12:08:33,100 | server.py:223 | evaluate_round received 7 results and 0 failures\n",
      "INFO flower 2022-04-16 12:08:33,100 | 2719366172.py:15 | round-38-EVALUATION\n",
      "INFO flower 2022-04-16 12:08:33,102 | 2719366172.py:31 | [(6, 0.8488371968269348), (7, 0.7193675637245178), (10, 0.8740457892417908), (11, 0.8110235929489136), (13, 0.6859503984451294), (14, 0.6791666746139526), (16, 0.8371211886405945)]\n",
      "INFO flower 2022-04-16 12:08:33,103 | 2719366172.py:37 | Aggregated accuracy: 0.7793589149202619 +- 0.07605878000548405\n",
      "DEBUG flower 2022-04-16 12:08:33,103 | server.py:265 | fit_round: strategy sampled 7 clients (out of 7)\n",
      "DEBUG flower 2022-04-16 12:08:37,480 | server.py:277 | fit_round received 7 results and 0 failures\n",
      "DEBUG flower 2022-04-16 12:08:37,496 | server.py:211 | evaluate_round: strategy sampled 7 clients (out of 7)\n"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "Saving round 39 aggregated_weights...\n"
     ]
    },
    {
     "name": "stderr",
     "output_type": "stream",
     "text": [
      "DEBUG flower 2022-04-16 12:08:39,122 | server.py:223 | evaluate_round received 7 results and 0 failures\n",
      "INFO flower 2022-04-16 12:08:39,123 | 2719366172.py:15 | round-39-EVALUATION\n",
      "INFO flower 2022-04-16 12:08:39,125 | 2719366172.py:31 | [(6, 0.8488371968269348), (7, 0.7154150009155273), (10, 0.8625954389572144), (11, 0.8149606585502625), (13, 0.6859503984451294), (14, 0.6791666746139526), (16, 0.8409090638160706)]\n",
      "INFO flower 2022-04-16 12:08:39,126 | 2719366172.py:37 | Aggregated accuracy: 0.778262061732156 +- 0.07526666314469904\n",
      "DEBUG flower 2022-04-16 12:08:39,126 | server.py:265 | fit_round: strategy sampled 7 clients (out of 7)\n",
      "DEBUG flower 2022-04-16 12:08:43,380 | server.py:277 | fit_round received 7 results and 0 failures\n",
      "DEBUG flower 2022-04-16 12:08:43,396 | server.py:211 | evaluate_round: strategy sampled 7 clients (out of 7)\n"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "Saving round 40 aggregated_weights...\n"
     ]
    },
    {
     "name": "stderr",
     "output_type": "stream",
     "text": [
      "DEBUG flower 2022-04-16 12:08:45,076 | server.py:223 | evaluate_round received 7 results and 0 failures\n",
      "INFO flower 2022-04-16 12:08:45,076 | 2719366172.py:15 | round-40-EVALUATION\n",
      "INFO flower 2022-04-16 12:08:45,078 | 2719366172.py:31 | [(6, 0.8488371968269348), (7, 0.7154150009155273), (10, 0.8664122223854065), (11, 0.8149606585502625), (13, 0.6859503984451294), (14, 0.6791666746139526), (16, 0.8409090638160706)]\n",
      "INFO flower 2022-04-16 12:08:45,079 | 2719366172.py:37 | Aggregated accuracy: 0.7788073165076119 +- 0.0758868944606586\n",
      "DEBUG flower 2022-04-16 12:08:45,080 | server.py:265 | fit_round: strategy sampled 7 clients (out of 7)\n",
      "DEBUG flower 2022-04-16 12:08:49,397 | server.py:277 | fit_round received 7 results and 0 failures\n",
      "DEBUG flower 2022-04-16 12:08:49,413 | server.py:211 | evaluate_round: strategy sampled 7 clients (out of 7)\n"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "Saving round 41 aggregated_weights...\n"
     ]
    },
    {
     "name": "stderr",
     "output_type": "stream",
     "text": [
      "DEBUG flower 2022-04-16 12:08:51,082 | server.py:223 | evaluate_round received 7 results and 0 failures\n",
      "INFO flower 2022-04-16 12:08:51,083 | 2719366172.py:15 | round-41-EVALUATION\n",
      "INFO flower 2022-04-16 12:08:51,085 | 2719366172.py:31 | [(6, 0.8488371968269348), (7, 0.7233201861381531), (10, 0.8625954389572144), (11, 0.8188976645469666), (13, 0.6942148804664612), (14, 0.6791666746139526), (16, 0.8371211886405945)]\n",
      "INFO flower 2022-04-16 12:08:51,086 | 2719366172.py:37 | Aggregated accuracy: 0.780593318598611 +- 0.0727746110113148\n",
      "DEBUG flower 2022-04-16 12:08:51,086 | server.py:265 | fit_round: strategy sampled 7 clients (out of 7)\n",
      "DEBUG flower 2022-04-16 12:08:55,553 | server.py:277 | fit_round received 7 results and 0 failures\n",
      "DEBUG flower 2022-04-16 12:08:55,569 | server.py:211 | evaluate_round: strategy sampled 7 clients (out of 7)\n"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "Saving round 42 aggregated_weights...\n"
     ]
    },
    {
     "name": "stderr",
     "output_type": "stream",
     "text": [
      "DEBUG flower 2022-04-16 12:08:57,340 | server.py:223 | evaluate_round received 7 results and 0 failures\n",
      "INFO flower 2022-04-16 12:08:57,340 | 2719366172.py:15 | round-42-EVALUATION\n",
      "INFO flower 2022-04-16 12:08:57,342 | 2719366172.py:31 | [(6, 0.8488371968269348), (7, 0.7272727489471436), (10, 0.8511450290679932), (11, 0.8149606585502625), (13, 0.6942148804664612), (14, 0.6791666746139526), (16, 0.8409090638160706)]\n",
      "INFO flower 2022-04-16 12:08:57,343 | 2719366172.py:37 | Aggregated accuracy: 0.7795008931841169 +- 0.07074824785450906\n",
      "DEBUG flower 2022-04-16 12:08:57,343 | server.py:265 | fit_round: strategy sampled 7 clients (out of 7)\n",
      "DEBUG flower 2022-04-16 12:09:01,703 | server.py:277 | fit_round received 7 results and 0 failures\n",
      "DEBUG flower 2022-04-16 12:09:01,718 | server.py:211 | evaluate_round: strategy sampled 7 clients (out of 7)\n"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "Saving round 43 aggregated_weights...\n"
     ]
    },
    {
     "name": "stderr",
     "output_type": "stream",
     "text": [
      "DEBUG flower 2022-04-16 12:09:03,400 | server.py:223 | evaluate_round received 7 results and 0 failures\n",
      "INFO flower 2022-04-16 12:09:03,401 | 2719366172.py:15 | round-43-EVALUATION\n",
      "INFO flower 2022-04-16 12:09:03,403 | 2719366172.py:31 | [(6, 0.8488371968269348), (7, 0.7272727489471436), (10, 0.8511450290679932), (11, 0.8188976645469666), (13, 0.702479362487793), (14, 0.6875), (16, 0.8409090638160706)]\n",
      "INFO flower 2022-04-16 12:09:03,404 | 2719366172.py:37 | Aggregated accuracy: 0.7824344379561288 +- 0.06795743837872613\n",
      "DEBUG flower 2022-04-16 12:09:03,404 | server.py:265 | fit_round: strategy sampled 7 clients (out of 7)\n",
      "DEBUG flower 2022-04-16 12:09:07,773 | server.py:277 | fit_round received 7 results and 0 failures\n",
      "DEBUG flower 2022-04-16 12:09:07,788 | server.py:211 | evaluate_round: strategy sampled 7 clients (out of 7)\n"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "Saving round 44 aggregated_weights...\n"
     ]
    },
    {
     "name": "stderr",
     "output_type": "stream",
     "text": [
      "DEBUG flower 2022-04-16 12:09:09,450 | server.py:223 | evaluate_round received 7 results and 0 failures\n",
      "INFO flower 2022-04-16 12:09:09,451 | 2719366172.py:15 | round-44-EVALUATION\n",
      "INFO flower 2022-04-16 12:09:09,453 | 2719366172.py:31 | [(6, 0.8488371968269348), (7, 0.7233201861381531), (10, 0.8511450290679932), (11, 0.8188976645469666), (13, 0.71074378490448), (14, 0.6916666626930237), (16, 0.8409090638160706)]\n",
      "INFO flower 2022-04-16 12:09:09,454 | 2719366172.py:37 | Aggregated accuracy: 0.7836456554276603 +- 0.06626988615212823\n",
      "DEBUG flower 2022-04-16 12:09:09,454 | server.py:265 | fit_round: strategy sampled 7 clients (out of 7)\n",
      "DEBUG flower 2022-04-16 12:09:13,864 | server.py:277 | fit_round received 7 results and 0 failures\n",
      "DEBUG flower 2022-04-16 12:09:13,880 | server.py:211 | evaluate_round: strategy sampled 7 clients (out of 7)\n"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "Saving round 45 aggregated_weights...\n"
     ]
    },
    {
     "name": "stderr",
     "output_type": "stream",
     "text": [
      "DEBUG flower 2022-04-16 12:09:15,702 | server.py:223 | evaluate_round received 7 results and 0 failures\n",
      "INFO flower 2022-04-16 12:09:15,702 | 2719366172.py:15 | round-45-EVALUATION\n",
      "INFO flower 2022-04-16 12:09:15,705 | 2719366172.py:31 | [(6, 0.8488371968269348), (7, 0.7233201861381531), (10, 0.8511450290679932), (11, 0.8149606585502625), (13, 0.7066115736961365), (14, 0.6958333253860474), (16, 0.8409090638160706)]\n",
      "INFO flower 2022-04-16 12:09:15,705 | 2719366172.py:37 | Aggregated accuracy: 0.7830881476402283 +- 0.06584404894326466\n",
      "DEBUG flower 2022-04-16 12:09:15,706 | server.py:265 | fit_round: strategy sampled 7 clients (out of 7)\n",
      "DEBUG flower 2022-04-16 12:09:20,065 | server.py:277 | fit_round received 7 results and 0 failures\n",
      "DEBUG flower 2022-04-16 12:09:20,080 | server.py:211 | evaluate_round: strategy sampled 7 clients (out of 7)\n"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "Saving round 46 aggregated_weights...\n"
     ]
    },
    {
     "name": "stderr",
     "output_type": "stream",
     "text": [
      "DEBUG flower 2022-04-16 12:09:21,750 | server.py:223 | evaluate_round received 7 results and 0 failures\n",
      "INFO flower 2022-04-16 12:09:21,750 | 2719366172.py:15 | round-46-EVALUATION\n",
      "INFO flower 2022-04-16 12:09:21,753 | 2719366172.py:31 | [(6, 0.8488371968269348), (7, 0.7272727489471436), (10, 0.8587786555290222), (11, 0.8070865869522095), (13, 0.71074378490448), (14, 0.6958333253860474), (16, 0.8446969985961914)]\n",
      "INFO flower 2022-04-16 12:09:21,753 | 2719366172.py:37 | Aggregated accuracy: 0.7847498995917184 +- 0.06586426050123816\n",
      "DEBUG flower 2022-04-16 12:09:21,754 | server.py:265 | fit_round: strategy sampled 7 clients (out of 7)\n",
      "DEBUG flower 2022-04-16 12:09:26,165 | server.py:277 | fit_round received 7 results and 0 failures\n",
      "DEBUG flower 2022-04-16 12:09:26,180 | server.py:211 | evaluate_round: strategy sampled 7 clients (out of 7)\n"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "Saving round 47 aggregated_weights...\n"
     ]
    },
    {
     "name": "stderr",
     "output_type": "stream",
     "text": [
      "DEBUG flower 2022-04-16 12:09:27,985 | server.py:223 | evaluate_round received 7 results and 0 failures\n",
      "INFO flower 2022-04-16 12:09:27,985 | 2719366172.py:15 | round-47-EVALUATION\n",
      "INFO flower 2022-04-16 12:09:27,988 | 2719366172.py:31 | [(6, 0.8488371968269348), (7, 0.7272727489471436), (10, 0.8587786555290222), (11, 0.8110235929489136), (13, 0.71074378490448), (14, 0.6958333253860474), (16, 0.8446969985961914)]\n",
      "INFO flower 2022-04-16 12:09:27,988 | 2719366172.py:37 | Aggregated accuracy: 0.785312329019819 +- 0.06606908803018373\n",
      "DEBUG flower 2022-04-16 12:09:27,989 | server.py:265 | fit_round: strategy sampled 7 clients (out of 7)\n",
      "DEBUG flower 2022-04-16 12:09:32,522 | server.py:277 | fit_round received 7 results and 0 failures\n",
      "DEBUG flower 2022-04-16 12:09:32,537 | server.py:211 | evaluate_round: strategy sampled 7 clients (out of 7)\n"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "Saving round 48 aggregated_weights...\n"
     ]
    },
    {
     "name": "stderr",
     "output_type": "stream",
     "text": [
      "DEBUG flower 2022-04-16 12:09:34,509 | server.py:223 | evaluate_round received 7 results and 0 failures\n",
      "INFO flower 2022-04-16 12:09:34,509 | 2719366172.py:15 | round-48-EVALUATION\n",
      "INFO flower 2022-04-16 12:09:34,512 | 2719366172.py:31 | [(6, 0.8488371968269348), (7, 0.7351778745651245), (10, 0.8587786555290222), (11, 0.8070865869522095), (13, 0.7190082669258118), (14, 0.6958333253860474), (16, 0.8484848737716675)]\n",
      "INFO flower 2022-04-16 12:09:34,512 | 2719366172.py:37 | Aggregated accuracy: 0.7876009685652596 +- 0.06411721169383526\n",
      "DEBUG flower 2022-04-16 12:09:34,513 | server.py:265 | fit_round: strategy sampled 7 clients (out of 7)\n",
      "DEBUG flower 2022-04-16 12:09:38,978 | server.py:277 | fit_round received 7 results and 0 failures\n",
      "DEBUG flower 2022-04-16 12:09:38,994 | server.py:211 | evaluate_round: strategy sampled 7 clients (out of 7)\n"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "Saving round 49 aggregated_weights...\n"
     ]
    },
    {
     "name": "stderr",
     "output_type": "stream",
     "text": [
      "DEBUG flower 2022-04-16 12:09:40,871 | server.py:223 | evaluate_round received 7 results and 0 failures\n",
      "INFO flower 2022-04-16 12:09:40,871 | 2719366172.py:15 | round-49-EVALUATION\n",
      "INFO flower 2022-04-16 12:09:40,874 | 2719366172.py:31 | [(6, 0.8488371968269348), (7, 0.7272727489471436), (10, 0.8549618124961853), (11, 0.7913385629653931), (13, 0.7231404781341553), (14, 0.6958333253860474), (16, 0.8484848737716675)]\n",
      "INFO flower 2022-04-16 12:09:40,874 | 2719366172.py:37 | Aggregated accuracy: 0.7842669997896466 +- 0.06341058978805772\n",
      "DEBUG flower 2022-04-16 12:09:40,875 | server.py:265 | fit_round: strategy sampled 7 clients (out of 7)\n",
      "DEBUG flower 2022-04-16 12:09:45,530 | server.py:277 | fit_round received 7 results and 0 failures\n",
      "DEBUG flower 2022-04-16 12:09:45,546 | server.py:211 | evaluate_round: strategy sampled 7 clients (out of 7)\n"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "Saving round 50 aggregated_weights...\n"
     ]
    },
    {
     "name": "stderr",
     "output_type": "stream",
     "text": [
      "DEBUG flower 2022-04-16 12:09:47,301 | server.py:223 | evaluate_round received 7 results and 0 failures\n",
      "INFO flower 2022-04-16 12:09:47,301 | 2719366172.py:15 | round-50-EVALUATION\n",
      "INFO flower 2022-04-16 12:09:47,303 | 2719366172.py:31 | [(6, 0.8488371968269348), (7, 0.731225311756134), (10, 0.8549618124961853), (11, 0.7913385629653931), (13, 0.7272727489471436), (14, 0.6958333253860474), (16, 0.8484848737716675)]\n",
      "INFO flower 2022-04-16 12:09:47,304 | 2719366172.py:37 | Aggregated accuracy: 0.785421976021358 +- 0.06235148240872614\n",
      "DEBUG flower 2022-04-16 12:09:47,304 | server.py:265 | fit_round: strategy sampled 7 clients (out of 7)\n",
      "DEBUG flower 2022-04-16 12:09:51,982 | server.py:277 | fit_round received 7 results and 0 failures\n",
      "DEBUG flower 2022-04-16 12:09:51,999 | server.py:211 | evaluate_round: strategy sampled 7 clients (out of 7)\n"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "Saving round 51 aggregated_weights...\n"
     ]
    },
    {
     "name": "stderr",
     "output_type": "stream",
     "text": [
      "DEBUG flower 2022-04-16 12:09:53,785 | server.py:223 | evaluate_round received 7 results and 0 failures\n",
      "INFO flower 2022-04-16 12:09:53,786 | 2719366172.py:15 | round-51-EVALUATION\n",
      "INFO flower 2022-04-16 12:09:53,788 | 2719366172.py:31 | [(6, 0.8488371968269348), (7, 0.731225311756134), (10, 0.847328245639801), (11, 0.787401556968689), (13, 0.7314049601554871), (14, 0.6958333253860474), (16, 0.8484848737716675)]\n",
      "INFO flower 2022-04-16 12:09:53,789 | 2719366172.py:37 | Aggregated accuracy: 0.7843593529292515 +- 0.06060181848947652\n",
      "DEBUG flower 2022-04-16 12:09:53,789 | server.py:265 | fit_round: strategy sampled 7 clients (out of 7)\n",
      "DEBUG flower 2022-04-16 12:09:58,380 | server.py:277 | fit_round received 7 results and 0 failures\n",
      "DEBUG flower 2022-04-16 12:09:58,397 | server.py:211 | evaluate_round: strategy sampled 7 clients (out of 7)\n"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "Saving round 52 aggregated_weights...\n"
     ]
    },
    {
     "name": "stderr",
     "output_type": "stream",
     "text": [
      "DEBUG flower 2022-04-16 12:10:00,133 | server.py:223 | evaluate_round received 7 results and 0 failures\n",
      "INFO flower 2022-04-16 12:10:00,133 | 2719366172.py:15 | round-52-EVALUATION\n",
      "INFO flower 2022-04-16 12:10:00,136 | 2719366172.py:31 | [(6, 0.8488371968269348), (7, 0.7272727489471436), (10, 0.847328245639801), (11, 0.787401556968689), (13, 0.7355371713638306), (14, 0.699999988079071), (16, 0.8484848737716675)]\n",
      "INFO flower 2022-04-16 12:10:00,136 | 2719366172.py:37 | Aggregated accuracy: 0.7849802545138768 +- 0.05976155095175408\n",
      "DEBUG flower 2022-04-16 12:10:00,137 | server.py:265 | fit_round: strategy sampled 7 clients (out of 7)\n",
      "DEBUG flower 2022-04-16 12:10:04,704 | server.py:277 | fit_round received 7 results and 0 failures\n",
      "DEBUG flower 2022-04-16 12:10:04,720 | server.py:211 | evaluate_round: strategy sampled 7 clients (out of 7)\n"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "Saving round 53 aggregated_weights...\n"
     ]
    },
    {
     "name": "stderr",
     "output_type": "stream",
     "text": [
      "DEBUG flower 2022-04-16 12:10:06,606 | server.py:223 | evaluate_round received 7 results and 0 failures\n",
      "INFO flower 2022-04-16 12:10:06,606 | 2719366172.py:15 | round-53-EVALUATION\n",
      "INFO flower 2022-04-16 12:10:06,608 | 2719366172.py:31 | [(6, 0.8488371968269348), (7, 0.731225311756134), (10, 0.847328245639801), (11, 0.787401556968689), (13, 0.7396694421768188), (14, 0.699999988079071), (16, 0.8484848737716675)]\n",
      "INFO flower 2022-04-16 12:10:06,610 | 2719366172.py:37 | Aggregated accuracy: 0.786135230745588 +- 0.05874722112559674\n",
      "DEBUG flower 2022-04-16 12:10:06,611 | server.py:265 | fit_round: strategy sampled 7 clients (out of 7)\n",
      "DEBUG flower 2022-04-16 12:10:11,045 | server.py:277 | fit_round received 7 results and 0 failures\n",
      "DEBUG flower 2022-04-16 12:10:11,061 | server.py:211 | evaluate_round: strategy sampled 7 clients (out of 7)\n"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "Saving round 54 aggregated_weights...\n"
     ]
    },
    {
     "name": "stderr",
     "output_type": "stream",
     "text": [
      "DEBUG flower 2022-04-16 12:10:12,913 | server.py:223 | evaluate_round received 7 results and 0 failures\n",
      "INFO flower 2022-04-16 12:10:12,913 | 2719366172.py:15 | round-54-EVALUATION\n",
      "INFO flower 2022-04-16 12:10:12,915 | 2719366172.py:31 | [(6, 0.8488371968269348), (7, 0.731225311756134), (10, 0.847328245639801), (11, 0.7834645509719849), (13, 0.7438016533851624), (14, 0.7041666507720947), (16, 0.8560606241226196)]\n",
      "INFO flower 2022-04-16 12:10:12,916 | 2719366172.py:37 | Aggregated accuracy: 0.7878406047821045 +- 0.05864972995418896\n",
      "DEBUG flower 2022-04-16 12:10:12,916 | server.py:265 | fit_round: strategy sampled 7 clients (out of 7)\n",
      "DEBUG flower 2022-04-16 12:10:17,507 | server.py:277 | fit_round received 7 results and 0 failures\n",
      "DEBUG flower 2022-04-16 12:10:17,523 | server.py:211 | evaluate_round: strategy sampled 7 clients (out of 7)\n"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "Saving round 55 aggregated_weights...\n"
     ]
    },
    {
     "name": "stderr",
     "output_type": "stream",
     "text": [
      "DEBUG flower 2022-04-16 12:10:19,262 | server.py:223 | evaluate_round received 7 results and 0 failures\n",
      "INFO flower 2022-04-16 12:10:19,262 | 2719366172.py:15 | round-55-EVALUATION\n",
      "INFO flower 2022-04-16 12:10:19,265 | 2719366172.py:31 | [(6, 0.8488371968269348), (7, 0.731225311756134), (10, 0.8435114622116089), (11, 0.787401556968689), (13, 0.7438016533851624), (14, 0.7041666507720947), (16, 0.8560606241226196)]\n",
      "INFO flower 2022-04-16 12:10:19,265 | 2719366172.py:37 | Aggregated accuracy: 0.7878577794347491 +- 0.05808865339076801\n",
      "DEBUG flower 2022-04-16 12:10:19,266 | server.py:265 | fit_round: strategy sampled 7 clients (out of 7)\n",
      "DEBUG flower 2022-04-16 12:10:23,827 | server.py:277 | fit_round received 7 results and 0 failures\n",
      "DEBUG flower 2022-04-16 12:10:23,844 | server.py:211 | evaluate_round: strategy sampled 7 clients (out of 7)\n"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "Saving round 56 aggregated_weights...\n"
     ]
    },
    {
     "name": "stderr",
     "output_type": "stream",
     "text": [
      "DEBUG flower 2022-04-16 12:10:25,649 | server.py:223 | evaluate_round received 7 results and 0 failures\n",
      "INFO flower 2022-04-16 12:10:25,650 | 2719366172.py:15 | round-56-EVALUATION\n",
      "INFO flower 2022-04-16 12:10:25,652 | 2719366172.py:31 | [(6, 0.8488371968269348), (7, 0.7351778745651245), (10, 0.8435114622116089), (11, 0.787401556968689), (13, 0.7438016533851624), (14, 0.699999988079071), (16, 0.8560606241226196)]\n",
      "INFO flower 2022-04-16 12:10:25,653 | 2719366172.py:37 | Aggregated accuracy: 0.78782719373703 +- 0.05843526025519592\n",
      "DEBUG flower 2022-04-16 12:10:25,653 | server.py:265 | fit_round: strategy sampled 7 clients (out of 7)\n",
      "DEBUG flower 2022-04-16 12:10:30,227 | server.py:277 | fit_round received 7 results and 0 failures\n",
      "DEBUG flower 2022-04-16 12:10:30,243 | server.py:211 | evaluate_round: strategy sampled 7 clients (out of 7)\n"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "Saving round 57 aggregated_weights...\n"
     ]
    },
    {
     "name": "stderr",
     "output_type": "stream",
     "text": [
      "DEBUG flower 2022-04-16 12:10:32,112 | server.py:223 | evaluate_round received 7 results and 0 failures\n",
      "INFO flower 2022-04-16 12:10:32,113 | 2719366172.py:15 | round-57-EVALUATION\n",
      "INFO flower 2022-04-16 12:10:32,115 | 2719366172.py:31 | [(6, 0.8488371968269348), (7, 0.7351778745651245), (10, 0.8435114622116089), (11, 0.7834645509719849), (13, 0.7520661354064941), (14, 0.7041666507720947), (16, 0.8598484992980957)]\n",
      "INFO flower 2022-04-16 12:10:32,116 | 2719366172.py:37 | Aggregated accuracy: 0.7895817671503339 +- 0.05739263292136917\n",
      "DEBUG flower 2022-04-16 12:10:32,116 | server.py:265 | fit_round: strategy sampled 7 clients (out of 7)\n",
      "DEBUG flower 2022-04-16 12:10:36,667 | server.py:277 | fit_round received 7 results and 0 failures\n",
      "DEBUG flower 2022-04-16 12:10:36,682 | server.py:211 | evaluate_round: strategy sampled 7 clients (out of 7)\n"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "Saving round 58 aggregated_weights...\n"
     ]
    },
    {
     "name": "stderr",
     "output_type": "stream",
     "text": [
      "DEBUG flower 2022-04-16 12:10:38,427 | server.py:223 | evaluate_round received 7 results and 0 failures\n",
      "INFO flower 2022-04-16 12:10:38,427 | 2719366172.py:15 | round-58-EVALUATION\n",
      "INFO flower 2022-04-16 12:10:38,429 | 2719366172.py:31 | [(6, 0.8488371968269348), (7, 0.7351778745651245), (10, 0.8435114622116089), (11, 0.7795275449752808), (13, 0.7561983466148376), (14, 0.7041666507720947), (16, 0.8636363744735718)]\n",
      "INFO flower 2022-04-16 12:10:38,430 | 2719366172.py:37 | Aggregated accuracy: 0.7901507786342076 +- 0.05778346548896946\n",
      "DEBUG flower 2022-04-16 12:10:38,431 | server.py:265 | fit_round: strategy sampled 7 clients (out of 7)\n",
      "DEBUG flower 2022-04-16 12:10:43,115 | server.py:277 | fit_round received 7 results and 0 failures\n",
      "DEBUG flower 2022-04-16 12:10:43,131 | server.py:211 | evaluate_round: strategy sampled 7 clients (out of 7)\n"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "Saving round 59 aggregated_weights...\n"
     ]
    },
    {
     "name": "stderr",
     "output_type": "stream",
     "text": [
      "DEBUG flower 2022-04-16 12:10:44,850 | server.py:223 | evaluate_round received 7 results and 0 failures\n",
      "INFO flower 2022-04-16 12:10:44,850 | 2719366172.py:15 | round-59-EVALUATION\n",
      "INFO flower 2022-04-16 12:10:44,853 | 2719366172.py:31 | [(6, 0.8488371968269348), (7, 0.739130437374115), (10, 0.847328245639801), (11, 0.7795275449752808), (13, 0.7603305578231812), (14, 0.7083333134651184), (16, 0.8636363744735718)]\n",
      "INFO flower 2022-04-16 12:10:44,853 | 2719366172.py:37 | Aggregated accuracy: 0.7924462386540004 +- 0.056538076605819325\n",
      "DEBUG flower 2022-04-16 12:10:44,854 | server.py:265 | fit_round: strategy sampled 7 clients (out of 7)\n",
      "DEBUG flower 2022-04-16 12:10:49,513 | server.py:277 | fit_round received 7 results and 0 failures\n",
      "DEBUG flower 2022-04-16 12:10:49,530 | server.py:211 | evaluate_round: strategy sampled 7 clients (out of 7)\n"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "Saving round 60 aggregated_weights...\n"
     ]
    },
    {
     "name": "stderr",
     "output_type": "stream",
     "text": [
      "DEBUG flower 2022-04-16 12:10:51,265 | server.py:223 | evaluate_round received 7 results and 0 failures\n",
      "INFO flower 2022-04-16 12:10:51,266 | 2719366172.py:15 | round-60-EVALUATION\n",
      "INFO flower 2022-04-16 12:10:51,268 | 2719366172.py:31 | [(6, 0.8488371968269348), (7, 0.7430830001831055), (10, 0.847328245639801), (11, 0.7755905389785767), (13, 0.7603305578231812), (14, 0.7083333134651184), (16, 0.8636363744735718)]\n",
      "INFO flower 2022-04-16 12:10:51,269 | 2719366172.py:37 | Aggregated accuracy: 0.7924484610557556 +- 0.056172254616398694\n",
      "DEBUG flower 2022-04-16 12:10:51,269 | server.py:265 | fit_round: strategy sampled 7 clients (out of 7)\n",
      "DEBUG flower 2022-04-16 12:10:55,793 | server.py:277 | fit_round received 7 results and 0 failures\n",
      "DEBUG flower 2022-04-16 12:10:55,810 | server.py:211 | evaluate_round: strategy sampled 7 clients (out of 7)\n"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "Saving round 61 aggregated_weights...\n"
     ]
    },
    {
     "name": "stderr",
     "output_type": "stream",
     "text": [
      "DEBUG flower 2022-04-16 12:10:57,489 | server.py:223 | evaluate_round received 7 results and 0 failures\n",
      "INFO flower 2022-04-16 12:10:57,489 | 2719366172.py:15 | round-61-EVALUATION\n",
      "INFO flower 2022-04-16 12:10:57,492 | 2719366172.py:31 | [(6, 0.8488371968269348), (7, 0.747035562992096), (10, 0.8435114622116089), (11, 0.7716535329818726), (13, 0.7685950398445129), (14, 0.7083333134651184), (16, 0.8636363744735718)]\n",
      "INFO flower 2022-04-16 12:10:57,494 | 2719366172.py:37 | Aggregated accuracy: 0.7930860689708165 +- 0.054760644001923174\n",
      "DEBUG flower 2022-04-16 12:10:57,494 | server.py:265 | fit_round: strategy sampled 7 clients (out of 7)\n",
      "DEBUG flower 2022-04-16 12:11:02,132 | server.py:277 | fit_round received 7 results and 0 failures\n",
      "DEBUG flower 2022-04-16 12:11:02,148 | server.py:211 | evaluate_round: strategy sampled 7 clients (out of 7)\n"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "Saving round 62 aggregated_weights...\n"
     ]
    },
    {
     "name": "stderr",
     "output_type": "stream",
     "text": [
      "DEBUG flower 2022-04-16 12:11:04,003 | server.py:223 | evaluate_round received 7 results and 0 failures\n",
      "INFO flower 2022-04-16 12:11:04,003 | 2719366172.py:15 | round-62-EVALUATION\n",
      "INFO flower 2022-04-16 12:11:04,005 | 2719366172.py:31 | [(6, 0.8488371968269348), (7, 0.747035562992096), (10, 0.8435114622116089), (11, 0.7716535329818726), (13, 0.7727272510528564), (14, 0.7083333134651184), (16, 0.8636363744735718)]\n",
      "INFO flower 2022-04-16 12:11:04,006 | 2719366172.py:37 | Aggregated accuracy: 0.7936763848577227 +- 0.054515172946836436\n",
      "DEBUG flower 2022-04-16 12:11:04,007 | server.py:265 | fit_round: strategy sampled 7 clients (out of 7)\n",
      "DEBUG flower 2022-04-16 12:11:08,541 | server.py:277 | fit_round received 7 results and 0 failures\n",
      "DEBUG flower 2022-04-16 12:11:08,557 | server.py:211 | evaluate_round: strategy sampled 7 clients (out of 7)\n"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "Saving round 63 aggregated_weights...\n"
     ]
    },
    {
     "name": "stderr",
     "output_type": "stream",
     "text": [
      "DEBUG flower 2022-04-16 12:11:10,266 | server.py:223 | evaluate_round received 7 results and 0 failures\n",
      "INFO flower 2022-04-16 12:11:10,266 | 2719366172.py:15 | round-63-EVALUATION\n",
      "INFO flower 2022-04-16 12:11:10,269 | 2719366172.py:31 | [(6, 0.8488371968269348), (7, 0.747035562992096), (10, 0.8435114622116089), (11, 0.7716535329818726), (13, 0.7727272510528564), (14, 0.7124999761581421), (16, 0.8636363744735718)]\n",
      "INFO flower 2022-04-16 12:11:10,269 | 2719366172.py:37 | Aggregated accuracy: 0.7942716223852975 +- 0.053595066284930916\n",
      "DEBUG flower 2022-04-16 12:11:10,270 | server.py:265 | fit_round: strategy sampled 7 clients (out of 7)\n",
      "DEBUG flower 2022-04-16 12:11:14,776 | server.py:277 | fit_round received 7 results and 0 failures\n",
      "DEBUG flower 2022-04-16 12:11:14,793 | server.py:211 | evaluate_round: strategy sampled 7 clients (out of 7)\n"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "Saving round 64 aggregated_weights...\n"
     ]
    },
    {
     "name": "stderr",
     "output_type": "stream",
     "text": [
      "DEBUG flower 2022-04-16 12:11:16,512 | server.py:223 | evaluate_round received 7 results and 0 failures\n",
      "INFO flower 2022-04-16 12:11:16,513 | 2719366172.py:15 | round-64-EVALUATION\n",
      "INFO flower 2022-04-16 12:11:16,515 | 2719366172.py:31 | [(6, 0.8488371968269348), (7, 0.7509881258010864), (10, 0.8435114622116089), (11, 0.7716535329818726), (13, 0.7727272510528564), (14, 0.7124999761581421), (16, 0.8636363744735718)]\n",
      "INFO flower 2022-04-16 12:11:16,515 | 2719366172.py:37 | Aggregated accuracy: 0.7948362742151532 +- 0.053113089398723556\n",
      "DEBUG flower 2022-04-16 12:11:16,516 | server.py:265 | fit_round: strategy sampled 7 clients (out of 7)\n",
      "DEBUG flower 2022-04-16 12:11:21,140 | server.py:277 | fit_round received 7 results and 0 failures\n",
      "DEBUG flower 2022-04-16 12:11:21,158 | server.py:211 | evaluate_round: strategy sampled 7 clients (out of 7)\n"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "Saving round 65 aggregated_weights...\n"
     ]
    },
    {
     "name": "stderr",
     "output_type": "stream",
     "text": [
      "DEBUG flower 2022-04-16 12:11:22,850 | server.py:223 | evaluate_round received 7 results and 0 failures\n",
      "INFO flower 2022-04-16 12:11:22,850 | 2719366172.py:15 | round-65-EVALUATION\n",
      "INFO flower 2022-04-16 12:11:22,852 | 2719366172.py:31 | [(6, 0.8488371968269348), (7, 0.747035562992096), (10, 0.8435114622116089), (11, 0.7716535329818726), (13, 0.7727272510528564), (14, 0.7166666388511658), (16, 0.8636363744735718)]\n",
      "INFO flower 2022-04-16 12:11:22,853 | 2719366172.py:37 | Aggregated accuracy: 0.7948668599128723 +- 0.05269923976035699\n",
      "DEBUG flower 2022-04-16 12:11:22,853 | server.py:265 | fit_round: strategy sampled 7 clients (out of 7)\n",
      "DEBUG flower 2022-04-16 12:11:27,444 | server.py:277 | fit_round received 7 results and 0 failures\n",
      "DEBUG flower 2022-04-16 12:11:27,460 | server.py:211 | evaluate_round: strategy sampled 7 clients (out of 7)\n"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "Saving round 66 aggregated_weights...\n"
     ]
    },
    {
     "name": "stderr",
     "output_type": "stream",
     "text": [
      "DEBUG flower 2022-04-16 12:11:29,330 | server.py:223 | evaluate_round received 7 results and 0 failures\n",
      "INFO flower 2022-04-16 12:11:29,330 | 2719366172.py:15 | round-66-EVALUATION\n",
      "INFO flower 2022-04-16 12:11:29,332 | 2719366172.py:31 | [(6, 0.8488371968269348), (7, 0.747035562992096), (10, 0.8435114622116089), (11, 0.7795275449752808), (13, 0.7727272510528564), (14, 0.7166666388511658), (16, 0.8636363744735718)]\n",
      "INFO flower 2022-04-16 12:11:29,333 | 2719366172.py:37 | Aggregated accuracy: 0.7959917187690735 +- 0.0522740689370684\n",
      "DEBUG flower 2022-04-16 12:11:29,333 | server.py:265 | fit_round: strategy sampled 7 clients (out of 7)\n",
      "DEBUG flower 2022-04-16 12:11:33,916 | server.py:277 | fit_round received 7 results and 0 failures\n",
      "DEBUG flower 2022-04-16 12:11:33,932 | server.py:211 | evaluate_round: strategy sampled 7 clients (out of 7)\n"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "Saving round 67 aggregated_weights...\n"
     ]
    },
    {
     "name": "stderr",
     "output_type": "stream",
     "text": [
      "DEBUG flower 2022-04-16 12:11:35,667 | server.py:223 | evaluate_round received 7 results and 0 failures\n",
      "INFO flower 2022-04-16 12:11:35,668 | 2719366172.py:15 | round-67-EVALUATION\n",
      "INFO flower 2022-04-16 12:11:35,670 | 2719366172.py:31 | [(6, 0.8488371968269348), (7, 0.7430830001831055), (10, 0.8435114622116089), (11, 0.7755905389785767), (13, 0.7727272510528564), (14, 0.7166666388511658), (16, 0.8636363744735718)]\n",
      "INFO flower 2022-04-16 12:11:35,671 | 2719366172.py:37 | Aggregated accuracy: 0.7948646375111171 +- 0.05300528576015365\n",
      "DEBUG flower 2022-04-16 12:11:35,671 | server.py:265 | fit_round: strategy sampled 7 clients (out of 7)\n",
      "DEBUG flower 2022-04-16 12:11:40,190 | server.py:277 | fit_round received 7 results and 0 failures\n",
      "DEBUG flower 2022-04-16 12:11:40,206 | server.py:211 | evaluate_round: strategy sampled 7 clients (out of 7)\n"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "Saving round 68 aggregated_weights...\n"
     ]
    },
    {
     "name": "stderr",
     "output_type": "stream",
     "text": [
      "DEBUG flower 2022-04-16 12:11:41,956 | server.py:223 | evaluate_round received 7 results and 0 failures\n",
      "INFO flower 2022-04-16 12:11:41,956 | 2719366172.py:15 | round-68-EVALUATION\n",
      "INFO flower 2022-04-16 12:11:41,959 | 2719366172.py:31 | [(6, 0.8488371968269348), (7, 0.739130437374115), (10, 0.8435114622116089), (11, 0.7716535329818726), (13, 0.7727272510528564), (14, 0.7208333611488342), (16, 0.8636363744735718)]\n",
      "INFO flower 2022-04-16 12:11:41,959 | 2719366172.py:37 | Aggregated accuracy: 0.7943328022956848 +- 0.052945892561460844\n",
      "DEBUG flower 2022-04-16 12:11:41,960 | server.py:265 | fit_round: strategy sampled 7 clients (out of 7)\n",
      "DEBUG flower 2022-04-16 12:11:46,660 | server.py:277 | fit_round received 7 results and 0 failures\n",
      "DEBUG flower 2022-04-16 12:11:46,677 | server.py:211 | evaluate_round: strategy sampled 7 clients (out of 7)\n"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "Saving round 69 aggregated_weights...\n"
     ]
    },
    {
     "name": "stderr",
     "output_type": "stream",
     "text": [
      "DEBUG flower 2022-04-16 12:11:48,441 | server.py:223 | evaluate_round received 7 results and 0 failures\n",
      "INFO flower 2022-04-16 12:11:48,441 | 2719366172.py:15 | round-69-EVALUATION\n",
      "INFO flower 2022-04-16 12:11:48,443 | 2719366172.py:31 | [(6, 0.8488371968269348), (7, 0.739130437374115), (10, 0.8435114622116089), (11, 0.7716535329818726), (13, 0.7727272510528564), (14, 0.7208333611488342), (16, 0.8636363744735718)]\n",
      "INFO flower 2022-04-16 12:11:48,444 | 2719366172.py:37 | Aggregated accuracy: 0.7943328022956848 +- 0.052945892561460844\n",
      "DEBUG flower 2022-04-16 12:11:48,444 | server.py:265 | fit_round: strategy sampled 7 clients (out of 7)\n",
      "DEBUG flower 2022-04-16 12:11:53,143 | server.py:277 | fit_round received 7 results and 0 failures\n",
      "DEBUG flower 2022-04-16 12:11:53,159 | server.py:211 | evaluate_round: strategy sampled 7 clients (out of 7)\n"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "Saving round 70 aggregated_weights...\n"
     ]
    },
    {
     "name": "stderr",
     "output_type": "stream",
     "text": [
      "DEBUG flower 2022-04-16 12:11:55,051 | server.py:223 | evaluate_round received 7 results and 0 failures\n",
      "INFO flower 2022-04-16 12:11:55,051 | 2719366172.py:15 | round-70-EVALUATION\n",
      "INFO flower 2022-04-16 12:11:55,054 | 2719366172.py:31 | [(6, 0.8488371968269348), (7, 0.739130437374115), (10, 0.8435114622116089), (11, 0.7716535329818726), (13, 0.7727272510528564), (14, 0.7208333611488342), (16, 0.8636363744735718)]\n",
      "INFO flower 2022-04-16 12:11:55,054 | 2719366172.py:37 | Aggregated accuracy: 0.7943328022956848 +- 0.052945892561460844\n",
      "DEBUG flower 2022-04-16 12:11:55,055 | server.py:265 | fit_round: strategy sampled 7 clients (out of 7)\n",
      "DEBUG flower 2022-04-16 12:11:59,633 | server.py:277 | fit_round received 7 results and 0 failures\n",
      "DEBUG flower 2022-04-16 12:11:59,649 | server.py:211 | evaluate_round: strategy sampled 7 clients (out of 7)\n"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "Saving round 71 aggregated_weights...\n"
     ]
    },
    {
     "name": "stderr",
     "output_type": "stream",
     "text": [
      "DEBUG flower 2022-04-16 12:12:01,412 | server.py:223 | evaluate_round received 7 results and 0 failures\n",
      "INFO flower 2022-04-16 12:12:01,412 | 2719366172.py:15 | round-71-EVALUATION\n",
      "INFO flower 2022-04-16 12:12:01,415 | 2719366172.py:31 | [(6, 0.8488371968269348), (7, 0.739130437374115), (10, 0.8435114622116089), (11, 0.7716535329818726), (13, 0.7727272510528564), (14, 0.7208333611488342), (16, 0.8636363744735718)]\n",
      "INFO flower 2022-04-16 12:12:01,415 | 2719366172.py:37 | Aggregated accuracy: 0.7943328022956848 +- 0.052945892561460844\n",
      "DEBUG flower 2022-04-16 12:12:01,415 | server.py:265 | fit_round: strategy sampled 7 clients (out of 7)\n",
      "DEBUG flower 2022-04-16 12:12:05,990 | server.py:277 | fit_round received 7 results and 0 failures\n",
      "DEBUG flower 2022-04-16 12:12:06,006 | server.py:211 | evaluate_round: strategy sampled 7 clients (out of 7)\n"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "Saving round 72 aggregated_weights...\n"
     ]
    },
    {
     "name": "stderr",
     "output_type": "stream",
     "text": [
      "DEBUG flower 2022-04-16 12:12:07,727 | server.py:223 | evaluate_round received 7 results and 0 failures\n",
      "INFO flower 2022-04-16 12:12:07,728 | 2719366172.py:15 | round-72-EVALUATION\n",
      "INFO flower 2022-04-16 12:12:07,731 | 2719366172.py:31 | [(6, 0.8488371968269348), (7, 0.739130437374115), (10, 0.8435114622116089), (11, 0.7716535329818726), (13, 0.7727272510528564), (14, 0.7208333611488342), (16, 0.8636363744735718)]\n",
      "INFO flower 2022-04-16 12:12:07,731 | 2719366172.py:37 | Aggregated accuracy: 0.7943328022956848 +- 0.052945892561460844\n",
      "DEBUG flower 2022-04-16 12:12:07,732 | server.py:265 | fit_round: strategy sampled 7 clients (out of 7)\n",
      "DEBUG flower 2022-04-16 12:12:12,358 | server.py:277 | fit_round received 7 results and 0 failures\n",
      "DEBUG flower 2022-04-16 12:12:12,374 | server.py:211 | evaluate_round: strategy sampled 7 clients (out of 7)\n"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "Saving round 73 aggregated_weights...\n"
     ]
    },
    {
     "name": "stderr",
     "output_type": "stream",
     "text": [
      "DEBUG flower 2022-04-16 12:12:14,119 | server.py:223 | evaluate_round received 7 results and 0 failures\n",
      "INFO flower 2022-04-16 12:12:14,120 | 2719366172.py:15 | round-73-EVALUATION\n",
      "INFO flower 2022-04-16 12:12:14,122 | 2719366172.py:31 | [(6, 0.8488371968269348), (7, 0.7430830001831055), (10, 0.8435114622116089), (11, 0.7716535329818726), (13, 0.7768595218658447), (14, 0.7208333611488342), (16, 0.8712121248245239)]\n",
      "INFO flower 2022-04-16 12:12:14,123 | 2719366172.py:37 | Aggregated accuracy: 0.7965700285775321 +- 0.053603089500313554\n",
      "DEBUG flower 2022-04-16 12:12:14,123 | server.py:265 | fit_round: strategy sampled 7 clients (out of 7)\n",
      "DEBUG flower 2022-04-16 12:12:18,733 | server.py:277 | fit_round received 7 results and 0 failures\n",
      "DEBUG flower 2022-04-16 12:12:18,749 | server.py:211 | evaluate_round: strategy sampled 7 clients (out of 7)\n"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "Saving round 74 aggregated_weights...\n"
     ]
    },
    {
     "name": "stderr",
     "output_type": "stream",
     "text": [
      "DEBUG flower 2022-04-16 12:12:20,456 | server.py:223 | evaluate_round received 7 results and 0 failures\n",
      "INFO flower 2022-04-16 12:12:20,456 | 2719366172.py:15 | round-74-EVALUATION\n",
      "INFO flower 2022-04-16 12:12:20,459 | 2719366172.py:31 | [(6, 0.8488371968269348), (7, 0.747035562992096), (10, 0.8396946787834167), (11, 0.7716535329818726), (13, 0.7809917330741882), (14, 0.7208333611488342), (16, 0.8712121248245239)]\n",
      "INFO flower 2022-04-16 12:12:20,459 | 2719366172.py:37 | Aggregated accuracy: 0.7971797415188381 +- 0.052390912152012\n",
      "DEBUG flower 2022-04-16 12:12:20,460 | server.py:265 | fit_round: strategy sampled 7 clients (out of 7)\n",
      "DEBUG flower 2022-04-16 12:12:25,011 | server.py:277 | fit_round received 7 results and 0 failures\n",
      "DEBUG flower 2022-04-16 12:12:25,042 | server.py:211 | evaluate_round: strategy sampled 7 clients (out of 7)\n"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "Saving round 75 aggregated_weights...\n"
     ]
    },
    {
     "name": "stderr",
     "output_type": "stream",
     "text": [
      "DEBUG flower 2022-04-16 12:12:26,921 | server.py:223 | evaluate_round received 7 results and 0 failures\n",
      "INFO flower 2022-04-16 12:12:26,921 | 2719366172.py:15 | round-75-EVALUATION\n",
      "INFO flower 2022-04-16 12:12:26,923 | 2719366172.py:31 | [(6, 0.8488371968269348), (7, 0.747035562992096), (10, 0.8396946787834167), (11, 0.7716535329818726), (13, 0.7809917330741882), (14, 0.7208333611488342), (16, 0.8712121248245239)]\n",
      "INFO flower 2022-04-16 12:12:26,924 | 2719366172.py:37 | Aggregated accuracy: 0.7971797415188381 +- 0.052390912152012\n",
      "DEBUG flower 2022-04-16 12:12:26,924 | server.py:265 | fit_round: strategy sampled 7 clients (out of 7)\n",
      "DEBUG flower 2022-04-16 12:12:31,510 | server.py:277 | fit_round received 7 results and 0 failures\n",
      "DEBUG flower 2022-04-16 12:12:31,527 | server.py:211 | evaluate_round: strategy sampled 7 clients (out of 7)\n"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "Saving round 76 aggregated_weights...\n"
     ]
    },
    {
     "name": "stderr",
     "output_type": "stream",
     "text": [
      "DEBUG flower 2022-04-16 12:12:33,261 | server.py:223 | evaluate_round received 7 results and 0 failures\n",
      "INFO flower 2022-04-16 12:12:33,261 | 2719366172.py:15 | round-76-EVALUATION\n",
      "INFO flower 2022-04-16 12:12:33,263 | 2719366172.py:31 | [(6, 0.8488371968269348), (7, 0.747035562992096), (10, 0.8396946787834167), (11, 0.7677165269851685), (13, 0.7809917330741882), (14, 0.7208333611488342), (16, 0.8712121248245239)]\n",
      "INFO flower 2022-04-16 12:12:33,264 | 2719366172.py:37 | Aggregated accuracy: 0.7966173120907375 +- 0.05268224576674235\n",
      "DEBUG flower 2022-04-16 12:12:33,264 | server.py:265 | fit_round: strategy sampled 7 clients (out of 7)\n",
      "DEBUG flower 2022-04-16 12:12:37,796 | server.py:277 | fit_round received 7 results and 0 failures\n",
      "DEBUG flower 2022-04-16 12:12:37,812 | server.py:211 | evaluate_round: strategy sampled 7 clients (out of 7)\n"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "Saving round 77 aggregated_weights...\n"
     ]
    },
    {
     "name": "stderr",
     "output_type": "stream",
     "text": [
      "DEBUG flower 2022-04-16 12:12:39,531 | server.py:223 | evaluate_round received 7 results and 0 failures\n",
      "INFO flower 2022-04-16 12:12:39,532 | 2719366172.py:15 | round-77-EVALUATION\n",
      "INFO flower 2022-04-16 12:12:39,534 | 2719366172.py:31 | [(6, 0.8488371968269348), (7, 0.747035562992096), (10, 0.8396946787834167), (11, 0.7637795209884644), (13, 0.7851239442825317), (14, 0.7208333611488342), (16, 0.8712121248245239)]\n",
      "INFO flower 2022-04-16 12:12:39,535 | 2719366172.py:37 | Aggregated accuracy: 0.7966451985495431 +- 0.052859560046734796\n",
      "DEBUG flower 2022-04-16 12:12:39,535 | server.py:265 | fit_round: strategy sampled 7 clients (out of 7)\n",
      "DEBUG flower 2022-04-16 12:12:44,136 | server.py:277 | fit_round received 7 results and 0 failures\n",
      "DEBUG flower 2022-04-16 12:12:44,153 | server.py:211 | evaluate_round: strategy sampled 7 clients (out of 7)\n"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "Saving round 78 aggregated_weights...\n"
     ]
    },
    {
     "name": "stderr",
     "output_type": "stream",
     "text": [
      "DEBUG flower 2022-04-16 12:12:45,851 | server.py:223 | evaluate_round received 7 results and 0 failures\n",
      "INFO flower 2022-04-16 12:12:45,851 | 2719366172.py:15 | round-78-EVALUATION\n",
      "INFO flower 2022-04-16 12:12:45,853 | 2719366172.py:31 | [(6, 0.8488371968269348), (7, 0.747035562992096), (10, 0.8396946787834167), (11, 0.7637795209884644), (13, 0.7851239442825317), (14, 0.7208333611488342), (16, 0.8712121248245239)]\n",
      "INFO flower 2022-04-16 12:12:45,854 | 2719366172.py:37 | Aggregated accuracy: 0.7966451985495431 +- 0.052859560046734796\n",
      "DEBUG flower 2022-04-16 12:12:45,854 | server.py:265 | fit_round: strategy sampled 7 clients (out of 7)\n",
      "DEBUG flower 2022-04-16 12:12:50,375 | server.py:277 | fit_round received 7 results and 0 failures\n",
      "DEBUG flower 2022-04-16 12:12:50,391 | server.py:211 | evaluate_round: strategy sampled 7 clients (out of 7)\n"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "Saving round 79 aggregated_weights...\n"
     ]
    },
    {
     "name": "stderr",
     "output_type": "stream",
     "text": [
      "DEBUG flower 2022-04-16 12:12:52,268 | server.py:223 | evaluate_round received 7 results and 0 failures\n",
      "INFO flower 2022-04-16 12:12:52,268 | 2719366172.py:15 | round-79-EVALUATION\n",
      "INFO flower 2022-04-16 12:12:52,270 | 2719366172.py:31 | [(6, 0.8488371968269348), (7, 0.7509881258010864), (10, 0.8396946787834167), (11, 0.7637795209884644), (13, 0.7851239442825317), (14, 0.7250000238418579), (16, 0.8712121248245239)]\n",
      "INFO flower 2022-04-16 12:12:52,271 | 2719366172.py:37 | Aggregated accuracy: 0.7978050879069737 +- 0.05149003084610307\n",
      "DEBUG flower 2022-04-16 12:12:52,271 | server.py:265 | fit_round: strategy sampled 7 clients (out of 7)\n",
      "DEBUG flower 2022-04-16 12:12:56,875 | server.py:277 | fit_round received 7 results and 0 failures\n",
      "DEBUG flower 2022-04-16 12:12:56,891 | server.py:211 | evaluate_round: strategy sampled 7 clients (out of 7)\n"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "Saving round 80 aggregated_weights...\n"
     ]
    },
    {
     "name": "stderr",
     "output_type": "stream",
     "text": [
      "DEBUG flower 2022-04-16 12:12:58,643 | server.py:223 | evaluate_round received 7 results and 0 failures\n",
      "INFO flower 2022-04-16 12:12:58,644 | 2719366172.py:15 | round-80-EVALUATION\n",
      "INFO flower 2022-04-16 12:12:58,646 | 2719366172.py:31 | [(6, 0.8488371968269348), (7, 0.7509881258010864), (10, 0.8396946787834167), (11, 0.7637795209884644), (13, 0.7851239442825317), (14, 0.7208333611488342), (16, 0.8674242496490479)]\n",
      "INFO flower 2022-04-16 12:12:58,647 | 2719366172.py:37 | Aggregated accuracy: 0.7966687253543309 +- 0.05159156586113906\n",
      "DEBUG flower 2022-04-16 12:12:58,648 | server.py:265 | fit_round: strategy sampled 7 clients (out of 7)\n",
      "DEBUG flower 2022-04-16 12:13:03,188 | server.py:277 | fit_round received 7 results and 0 failures\n",
      "DEBUG flower 2022-04-16 12:13:03,205 | server.py:211 | evaluate_round: strategy sampled 7 clients (out of 7)\n"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "Saving round 81 aggregated_weights...\n"
     ]
    },
    {
     "name": "stderr",
     "output_type": "stream",
     "text": [
      "DEBUG flower 2022-04-16 12:13:04,936 | server.py:223 | evaluate_round received 7 results and 0 failures\n",
      "INFO flower 2022-04-16 12:13:04,936 | 2719366172.py:15 | round-81-EVALUATION\n",
      "INFO flower 2022-04-16 12:13:04,939 | 2719366172.py:31 | [(6, 0.8488371968269348), (7, 0.7509881258010864), (10, 0.8396946787834167), (11, 0.7637795209884644), (13, 0.7933884263038635), (14, 0.7208333611488342), (16, 0.8674242496490479)]\n",
      "INFO flower 2022-04-16 12:13:04,939 | 2719366172.py:37 | Aggregated accuracy: 0.7978493656430926 +- 0.051408099261072995\n",
      "DEBUG flower 2022-04-16 12:13:04,940 | server.py:265 | fit_round: strategy sampled 7 clients (out of 7)\n",
      "DEBUG flower 2022-04-16 12:13:09,508 | server.py:277 | fit_round received 7 results and 0 failures\n",
      "DEBUG flower 2022-04-16 12:13:09,524 | server.py:211 | evaluate_round: strategy sampled 7 clients (out of 7)\n"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "Saving round 82 aggregated_weights...\n"
     ]
    },
    {
     "name": "stderr",
     "output_type": "stream",
     "text": [
      "DEBUG flower 2022-04-16 12:13:11,210 | server.py:223 | evaluate_round received 7 results and 0 failures\n",
      "INFO flower 2022-04-16 12:13:11,211 | 2719366172.py:15 | round-82-EVALUATION\n",
      "INFO flower 2022-04-16 12:13:11,213 | 2719366172.py:31 | [(6, 0.8527131676673889), (7, 0.7549406886100769), (10, 0.8396946787834167), (11, 0.7637795209884644), (13, 0.797520637512207), (14, 0.7208333611488342), (16, 0.8674242496490479)]\n",
      "INFO flower 2022-04-16 12:13:11,214 | 2719366172.py:37 | Aggregated accuracy: 0.7995580434799194 +- 0.051429252819664054\n",
      "DEBUG flower 2022-04-16 12:13:11,214 | server.py:265 | fit_round: strategy sampled 7 clients (out of 7)\n",
      "DEBUG flower 2022-04-16 12:13:15,750 | server.py:277 | fit_round received 7 results and 0 failures\n",
      "DEBUG flower 2022-04-16 12:13:15,765 | server.py:211 | evaluate_round: strategy sampled 7 clients (out of 7)\n"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "Saving round 83 aggregated_weights...\n"
     ]
    },
    {
     "name": "stderr",
     "output_type": "stream",
     "text": [
      "DEBUG flower 2022-04-16 12:13:17,463 | server.py:223 | evaluate_round received 7 results and 0 failures\n",
      "INFO flower 2022-04-16 12:13:17,464 | 2719366172.py:15 | round-83-EVALUATION\n",
      "INFO flower 2022-04-16 12:13:17,466 | 2719366172.py:31 | [(6, 0.8527131676673889), (7, 0.7588932514190674), (10, 0.8396946787834167), (11, 0.7637795209884644), (13, 0.797520637512207), (14, 0.7208333611488342), (16, 0.8674242496490479)]\n",
      "INFO flower 2022-04-16 12:13:17,466 | 2719366172.py:37 | Aggregated accuracy: 0.8001226953097752 +- 0.050955809223105435\n",
      "DEBUG flower 2022-04-16 12:13:17,467 | server.py:265 | fit_round: strategy sampled 7 clients (out of 7)\n",
      "DEBUG flower 2022-04-16 12:13:22,029 | server.py:277 | fit_round received 7 results and 0 failures\n",
      "DEBUG flower 2022-04-16 12:13:22,045 | server.py:211 | evaluate_round: strategy sampled 7 clients (out of 7)\n"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "Saving round 84 aggregated_weights...\n"
     ]
    },
    {
     "name": "stderr",
     "output_type": "stream",
     "text": [
      "DEBUG flower 2022-04-16 12:13:23,994 | server.py:223 | evaluate_round received 7 results and 0 failures\n",
      "INFO flower 2022-04-16 12:13:23,994 | 2719366172.py:15 | round-84-EVALUATION\n",
      "INFO flower 2022-04-16 12:13:23,996 | 2719366172.py:31 | [(6, 0.8527131676673889), (7, 0.7588932514190674), (10, 0.8396946787834167), (11, 0.7677165269851685), (13, 0.797520637512207), (14, 0.7208333611488342), (16, 0.8636363744735718)]\n",
      "INFO flower 2022-04-16 12:13:23,997 | 2719366172.py:37 | Aggregated accuracy: 0.8001439997128078 +- 0.04987023149864724\n",
      "DEBUG flower 2022-04-16 12:13:23,997 | server.py:265 | fit_round: strategy sampled 7 clients (out of 7)\n",
      "DEBUG flower 2022-04-16 12:13:28,448 | server.py:277 | fit_round received 7 results and 0 failures\n",
      "DEBUG flower 2022-04-16 12:13:28,465 | server.py:211 | evaluate_round: strategy sampled 7 clients (out of 7)\n"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "Saving round 85 aggregated_weights...\n"
     ]
    },
    {
     "name": "stderr",
     "output_type": "stream",
     "text": [
      "DEBUG flower 2022-04-16 12:13:30,367 | server.py:223 | evaluate_round received 7 results and 0 failures\n",
      "INFO flower 2022-04-16 12:13:30,367 | 2719366172.py:15 | round-85-EVALUATION\n",
      "INFO flower 2022-04-16 12:13:30,370 | 2719366172.py:31 | [(6, 0.8527131676673889), (7, 0.7588932514190674), (10, 0.8396946787834167), (11, 0.7716535329818726), (13, 0.797520637512207), (14, 0.7208333611488342), (16, 0.8636363744735718)]\n",
      "INFO flower 2022-04-16 12:13:30,370 | 2719366172.py:37 | Aggregated accuracy: 0.8007064291409084 +- 0.04952233456750925\n",
      "DEBUG flower 2022-04-16 12:13:30,371 | server.py:265 | fit_round: strategy sampled 7 clients (out of 7)\n",
      "DEBUG flower 2022-04-16 12:13:35,011 | server.py:277 | fit_round received 7 results and 0 failures\n",
      "DEBUG flower 2022-04-16 12:13:35,027 | server.py:211 | evaluate_round: strategy sampled 7 clients (out of 7)\n"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "Saving round 86 aggregated_weights...\n"
     ]
    },
    {
     "name": "stderr",
     "output_type": "stream",
     "text": [
      "DEBUG flower 2022-04-16 12:13:36,773 | server.py:223 | evaluate_round received 7 results and 0 failures\n",
      "INFO flower 2022-04-16 12:13:36,774 | 2719366172.py:15 | round-86-EVALUATION\n",
      "INFO flower 2022-04-16 12:13:36,776 | 2719366172.py:31 | [(6, 0.8527131676673889), (7, 0.7628458738327026), (10, 0.8396946787834167), (11, 0.7716535329818726), (13, 0.797520637512207), (14, 0.7250000238418579), (16, 0.8636363744735718)]\n",
      "INFO flower 2022-04-16 12:13:36,777 | 2719366172.py:37 | Aggregated accuracy: 0.8018663270132882 +- 0.04809907399684655\n",
      "DEBUG flower 2022-04-16 12:13:36,777 | server.py:265 | fit_round: strategy sampled 7 clients (out of 7)\n",
      "DEBUG flower 2022-04-16 12:13:41,313 | server.py:277 | fit_round received 7 results and 0 failures\n",
      "DEBUG flower 2022-04-16 12:13:41,331 | server.py:211 | evaluate_round: strategy sampled 7 clients (out of 7)\n"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "Saving round 87 aggregated_weights...\n"
     ]
    },
    {
     "name": "stderr",
     "output_type": "stream",
     "text": [
      "DEBUG flower 2022-04-16 12:13:43,086 | server.py:223 | evaluate_round received 7 results and 0 failures\n",
      "INFO flower 2022-04-16 12:13:43,086 | 2719366172.py:15 | round-87-EVALUATION\n",
      "INFO flower 2022-04-16 12:13:43,088 | 2719366172.py:31 | [(6, 0.8527131676673889), (7, 0.7628458738327026), (10, 0.8396946787834167), (11, 0.7677165269851685), (13, 0.797520637512207), (14, 0.7250000238418579), (16, 0.8636363744735718)]\n",
      "INFO flower 2022-04-16 12:13:43,089 | 2719366172.py:37 | Aggregated accuracy: 0.8013038975851876 +- 0.04847065101131303\n",
      "DEBUG flower 2022-04-16 12:13:43,090 | server.py:265 | fit_round: strategy sampled 7 clients (out of 7)\n",
      "DEBUG flower 2022-04-16 12:13:47,781 | server.py:277 | fit_round received 7 results and 0 failures\n",
      "DEBUG flower 2022-04-16 12:13:47,796 | server.py:211 | evaluate_round: strategy sampled 7 clients (out of 7)\n"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "Saving round 88 aggregated_weights...\n"
     ]
    },
    {
     "name": "stderr",
     "output_type": "stream",
     "text": [
      "DEBUG flower 2022-04-16 12:13:49,602 | server.py:223 | evaluate_round received 7 results and 0 failures\n",
      "INFO flower 2022-04-16 12:13:49,603 | 2719366172.py:15 | round-88-EVALUATION\n",
      "INFO flower 2022-04-16 12:13:49,605 | 2719366172.py:31 | [(6, 0.8527131676673889), (7, 0.7628458738327026), (10, 0.8396946787834167), (11, 0.7637795209884644), (13, 0.797520637512207), (14, 0.7250000238418579), (16, 0.8636363744735718)]\n",
      "INFO flower 2022-04-16 12:13:49,606 | 2719366172.py:37 | Aggregated accuracy: 0.800741468157087 +- 0.04887824691931989\n",
      "DEBUG flower 2022-04-16 12:13:49,607 | server.py:265 | fit_round: strategy sampled 7 clients (out of 7)\n",
      "DEBUG flower 2022-04-16 12:13:54,331 | server.py:277 | fit_round received 7 results and 0 failures\n",
      "DEBUG flower 2022-04-16 12:13:54,347 | server.py:211 | evaluate_round: strategy sampled 7 clients (out of 7)\n"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "Saving round 89 aggregated_weights...\n"
     ]
    },
    {
     "name": "stderr",
     "output_type": "stream",
     "text": [
      "DEBUG flower 2022-04-16 12:13:56,203 | server.py:223 | evaluate_round received 7 results and 0 failures\n",
      "INFO flower 2022-04-16 12:13:56,204 | 2719366172.py:15 | round-89-EVALUATION\n",
      "INFO flower 2022-04-16 12:13:56,206 | 2719366172.py:31 | [(6, 0.8527131676673889), (7, 0.7628458738327026), (10, 0.8396946787834167), (11, 0.7637795209884644), (13, 0.7933884263038635), (14, 0.7250000238418579), (16, 0.8636363744735718)]\n",
      "INFO flower 2022-04-16 12:13:56,207 | 2719366172.py:37 | Aggregated accuracy: 0.8001511522701809 +- 0.04893849685044916\n",
      "DEBUG flower 2022-04-16 12:13:56,207 | server.py:265 | fit_round: strategy sampled 7 clients (out of 7)\n",
      "DEBUG flower 2022-04-16 12:14:00,671 | server.py:277 | fit_round received 7 results and 0 failures\n",
      "DEBUG flower 2022-04-16 12:14:00,687 | server.py:211 | evaluate_round: strategy sampled 7 clients (out of 7)\n"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "Saving round 90 aggregated_weights...\n"
     ]
    },
    {
     "name": "stderr",
     "output_type": "stream",
     "text": [
      "DEBUG flower 2022-04-16 12:14:02,535 | server.py:223 | evaluate_round received 7 results and 0 failures\n",
      "INFO flower 2022-04-16 12:14:02,535 | 2719366172.py:15 | round-90-EVALUATION\n",
      "INFO flower 2022-04-16 12:14:02,537 | 2719366172.py:31 | [(6, 0.8527131676673889), (7, 0.7628458738327026), (10, 0.8358778357505798), (11, 0.7637795209884644), (13, 0.78925621509552), (14, 0.7250000238418579), (16, 0.8636363744735718)]\n",
      "INFO flower 2022-04-16 12:14:02,538 | 2719366172.py:37 | Aggregated accuracy: 0.7990155730928693 +- 0.04861140247535151\n",
      "DEBUG flower 2022-04-16 12:14:02,538 | server.py:265 | fit_round: strategy sampled 7 clients (out of 7)\n",
      "DEBUG flower 2022-04-16 12:14:07,109 | server.py:277 | fit_round received 7 results and 0 failures\n",
      "DEBUG flower 2022-04-16 12:14:07,125 | server.py:211 | evaluate_round: strategy sampled 7 clients (out of 7)\n"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "Saving round 91 aggregated_weights...\n"
     ]
    },
    {
     "name": "stderr",
     "output_type": "stream",
     "text": [
      "DEBUG flower 2022-04-16 12:14:08,822 | server.py:223 | evaluate_round received 7 results and 0 failures\n",
      "INFO flower 2022-04-16 12:14:08,823 | 2719366172.py:15 | round-91-EVALUATION\n",
      "INFO flower 2022-04-16 12:14:08,826 | 2719366172.py:31 | [(6, 0.8527131676673889), (7, 0.7628458738327026), (10, 0.8358778357505798), (11, 0.7637795209884644), (13, 0.78925621509552), (14, 0.7250000238418579), (16, 0.8636363744735718)]\n",
      "INFO flower 2022-04-16 12:14:08,827 | 2719366172.py:37 | Aggregated accuracy: 0.7990155730928693 +- 0.04861140247535151\n",
      "DEBUG flower 2022-04-16 12:14:08,827 | server.py:265 | fit_round: strategy sampled 7 clients (out of 7)\n",
      "DEBUG flower 2022-04-16 12:14:13,345 | server.py:277 | fit_round received 7 results and 0 failures\n",
      "DEBUG flower 2022-04-16 12:14:13,362 | server.py:211 | evaluate_round: strategy sampled 7 clients (out of 7)\n"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "Saving round 92 aggregated_weights...\n"
     ]
    },
    {
     "name": "stderr",
     "output_type": "stream",
     "text": [
      "DEBUG flower 2022-04-16 12:14:15,117 | server.py:223 | evaluate_round received 7 results and 0 failures\n",
      "INFO flower 2022-04-16 12:14:15,117 | 2719366172.py:15 | round-92-EVALUATION\n",
      "INFO flower 2022-04-16 12:14:15,120 | 2719366172.py:31 | [(6, 0.8527131676673889), (7, 0.7628458738327026), (10, 0.8358778357505798), (11, 0.7637795209884644), (13, 0.78925621509552), (14, 0.7250000238418579), (16, 0.8636363744735718)]\n",
      "INFO flower 2022-04-16 12:14:15,121 | 2719366172.py:37 | Aggregated accuracy: 0.7990155730928693 +- 0.04861140247535151\n",
      "DEBUG flower 2022-04-16 12:14:15,121 | server.py:265 | fit_round: strategy sampled 7 clients (out of 7)\n",
      "DEBUG flower 2022-04-16 12:14:19,701 | server.py:277 | fit_round received 7 results and 0 failures\n",
      "DEBUG flower 2022-04-16 12:14:19,717 | server.py:211 | evaluate_round: strategy sampled 7 clients (out of 7)\n"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "Saving round 93 aggregated_weights...\n"
     ]
    },
    {
     "name": "stderr",
     "output_type": "stream",
     "text": [
      "DEBUG flower 2022-04-16 12:14:21,446 | server.py:223 | evaluate_round received 7 results and 0 failures\n",
      "INFO flower 2022-04-16 12:14:21,447 | 2719366172.py:15 | round-93-EVALUATION\n",
      "INFO flower 2022-04-16 12:14:21,449 | 2719366172.py:31 | [(6, 0.8527131676673889), (7, 0.7628458738327026), (10, 0.8358778357505798), (11, 0.7637795209884644), (13, 0.78925621509552), (14, 0.7250000238418579), (16, 0.8636363744735718)]\n",
      "INFO flower 2022-04-16 12:14:21,450 | 2719366172.py:37 | Aggregated accuracy: 0.7990155730928693 +- 0.04861140247535151\n",
      "DEBUG flower 2022-04-16 12:14:21,450 | server.py:265 | fit_round: strategy sampled 7 clients (out of 7)\n",
      "DEBUG flower 2022-04-16 12:14:25,997 | server.py:277 | fit_round received 7 results and 0 failures\n",
      "DEBUG flower 2022-04-16 12:14:26,013 | server.py:211 | evaluate_round: strategy sampled 7 clients (out of 7)\n"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "Saving round 94 aggregated_weights...\n"
     ]
    },
    {
     "name": "stderr",
     "output_type": "stream",
     "text": [
      "DEBUG flower 2022-04-16 12:14:27,899 | server.py:223 | evaluate_round received 7 results and 0 failures\n",
      "INFO flower 2022-04-16 12:14:27,899 | 2719366172.py:15 | round-94-EVALUATION\n",
      "INFO flower 2022-04-16 12:14:27,902 | 2719366172.py:31 | [(6, 0.8527131676673889), (7, 0.7628458738327026), (10, 0.8358778357505798), (11, 0.7637795209884644), (13, 0.78925621509552), (14, 0.7250000238418579), (16, 0.8636363744735718)]\n",
      "INFO flower 2022-04-16 12:14:27,903 | 2719366172.py:37 | Aggregated accuracy: 0.7990155730928693 +- 0.04861140247535151\n",
      "DEBUG flower 2022-04-16 12:14:27,903 | server.py:265 | fit_round: strategy sampled 7 clients (out of 7)\n",
      "DEBUG flower 2022-04-16 12:14:32,311 | server.py:277 | fit_round received 7 results and 0 failures\n",
      "DEBUG flower 2022-04-16 12:14:32,327 | server.py:211 | evaluate_round: strategy sampled 7 clients (out of 7)\n"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "Saving round 95 aggregated_weights...\n"
     ]
    },
    {
     "name": "stderr",
     "output_type": "stream",
     "text": [
      "DEBUG flower 2022-04-16 12:14:34,135 | server.py:223 | evaluate_round received 7 results and 0 failures\n",
      "INFO flower 2022-04-16 12:14:34,136 | 2719366172.py:15 | round-95-EVALUATION\n",
      "INFO flower 2022-04-16 12:14:34,138 | 2719366172.py:31 | [(6, 0.8527131676673889), (7, 0.7628458738327026), (10, 0.8358778357505798), (11, 0.7637795209884644), (13, 0.78925621509552), (14, 0.7250000238418579), (16, 0.8598484992980957)]\n",
      "INFO flower 2022-04-16 12:14:34,139 | 2719366172.py:37 | Aggregated accuracy: 0.7984744480678013 +- 0.0479050047786559\n",
      "DEBUG flower 2022-04-16 12:14:34,139 | server.py:265 | fit_round: strategy sampled 7 clients (out of 7)\n",
      "DEBUG flower 2022-04-16 12:14:38,678 | server.py:277 | fit_round received 7 results and 0 failures\n",
      "DEBUG flower 2022-04-16 12:14:38,694 | server.py:211 | evaluate_round: strategy sampled 7 clients (out of 7)\n"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "Saving round 96 aggregated_weights...\n"
     ]
    },
    {
     "name": "stderr",
     "output_type": "stream",
     "text": [
      "DEBUG flower 2022-04-16 12:14:40,550 | server.py:223 | evaluate_round received 7 results and 0 failures\n",
      "INFO flower 2022-04-16 12:14:40,551 | 2719366172.py:15 | round-96-EVALUATION\n",
      "INFO flower 2022-04-16 12:14:40,553 | 2719366172.py:31 | [(6, 0.8527131676673889), (7, 0.7628458738327026), (10, 0.8358778357505798), (11, 0.7637795209884644), (13, 0.78925621509552), (14, 0.7208333611488342), (16, 0.8598484992980957)]\n",
      "INFO flower 2022-04-16 12:14:40,554 | 2719366172.py:37 | Aggregated accuracy: 0.7978792105402265 +- 0.04883118673922345\n",
      "DEBUG flower 2022-04-16 12:14:40,555 | server.py:265 | fit_round: strategy sampled 7 clients (out of 7)\n",
      "DEBUG flower 2022-04-16 12:14:44,960 | server.py:277 | fit_round received 7 results and 0 failures\n",
      "DEBUG flower 2022-04-16 12:14:44,976 | server.py:211 | evaluate_round: strategy sampled 7 clients (out of 7)\n"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "Saving round 97 aggregated_weights...\n"
     ]
    },
    {
     "name": "stderr",
     "output_type": "stream",
     "text": [
      "DEBUG flower 2022-04-16 12:14:46,822 | server.py:223 | evaluate_round received 7 results and 0 failures\n",
      "INFO flower 2022-04-16 12:14:46,822 | 2719366172.py:15 | round-97-EVALUATION\n",
      "INFO flower 2022-04-16 12:14:46,825 | 2719366172.py:31 | [(6, 0.8527131676673889), (7, 0.7628458738327026), (10, 0.8358778357505798), (11, 0.7637795209884644), (13, 0.78925621509552), (14, 0.7208333611488342), (16, 0.8598484992980957)]\n",
      "INFO flower 2022-04-16 12:14:46,825 | 2719366172.py:37 | Aggregated accuracy: 0.7978792105402265 +- 0.04883118673922345\n",
      "DEBUG flower 2022-04-16 12:14:46,826 | server.py:265 | fit_round: strategy sampled 7 clients (out of 7)\n",
      "DEBUG flower 2022-04-16 12:14:51,452 | server.py:277 | fit_round received 7 results and 0 failures\n",
      "DEBUG flower 2022-04-16 12:14:51,468 | server.py:211 | evaluate_round: strategy sampled 7 clients (out of 7)\n"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "Saving round 98 aggregated_weights...\n"
     ]
    },
    {
     "name": "stderr",
     "output_type": "stream",
     "text": [
      "DEBUG flower 2022-04-16 12:14:53,197 | server.py:223 | evaluate_round received 7 results and 0 failures\n",
      "INFO flower 2022-04-16 12:14:53,197 | 2719366172.py:15 | round-98-EVALUATION\n",
      "INFO flower 2022-04-16 12:14:53,200 | 2719366172.py:31 | [(6, 0.8527131676673889), (7, 0.7628458738327026), (10, 0.8358778357505798), (11, 0.7637795209884644), (13, 0.7933884263038635), (14, 0.7208333611488342), (16, 0.8598484992980957)]\n",
      "INFO flower 2022-04-16 12:14:53,200 | 2719366172.py:37 | Aggregated accuracy: 0.7984695264271328 +- 0.04874828256494227\n",
      "DEBUG flower 2022-04-16 12:14:53,201 | server.py:265 | fit_round: strategy sampled 7 clients (out of 7)\n",
      "DEBUG flower 2022-04-16 12:14:57,730 | server.py:277 | fit_round received 7 results and 0 failures\n",
      "DEBUG flower 2022-04-16 12:14:57,747 | server.py:211 | evaluate_round: strategy sampled 7 clients (out of 7)\n"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "Saving round 99 aggregated_weights...\n"
     ]
    },
    {
     "name": "stderr",
     "output_type": "stream",
     "text": [
      "DEBUG flower 2022-04-16 12:14:59,487 | server.py:223 | evaluate_round received 7 results and 0 failures\n",
      "INFO flower 2022-04-16 12:14:59,487 | 2719366172.py:15 | round-99-EVALUATION\n",
      "INFO flower 2022-04-16 12:14:59,489 | 2719366172.py:31 | [(6, 0.8527131676673889), (7, 0.7628458738327026), (10, 0.8358778357505798), (11, 0.7637795209884644), (13, 0.7933884263038635), (14, 0.7208333611488342), (16, 0.8598484992980957)]\n",
      "INFO flower 2022-04-16 12:14:59,490 | 2719366172.py:37 | Aggregated accuracy: 0.7984695264271328 +- 0.04874828256494228\n",
      "DEBUG flower 2022-04-16 12:14:59,490 | server.py:265 | fit_round: strategy sampled 7 clients (out of 7)\n",
      "DEBUG flower 2022-04-16 12:15:04,070 | server.py:277 | fit_round received 7 results and 0 failures\n",
      "DEBUG flower 2022-04-16 12:15:04,086 | server.py:211 | evaluate_round: strategy sampled 7 clients (out of 7)\n"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "Saving round 100 aggregated_weights...\n"
     ]
    },
    {
     "name": "stderr",
     "output_type": "stream",
     "text": [
      "DEBUG flower 2022-04-16 12:15:05,766 | server.py:223 | evaluate_round received 7 results and 0 failures\n",
      "INFO flower 2022-04-16 12:15:05,767 | 2719366172.py:15 | round-100-EVALUATION\n",
      "INFO flower 2022-04-16 12:15:05,769 | 2719366172.py:31 | [(6, 0.8527131676673889), (7, 0.7628458738327026), (10, 0.8358778357505798), (11, 0.7637795209884644), (13, 0.7933884263038635), (14, 0.7208333611488342), (16, 0.8598484992980957)]\n",
      "INFO flower 2022-04-16 12:15:05,770 | 2719366172.py:37 | Aggregated accuracy: 0.7984695264271328 +- 0.04874828256494228\n",
      "INFO flower 2022-04-16 12:15:05,770 | server.py:182 | FL finished in 628.8897949999998\n",
      "INFO flower 2022-04-16 12:15:05,771 | app.py:149 | app_fit: losses_distributed [(1, 0.6282893546677819), (2, 0.6017715529204087), (3, 0.5780110102350673), (4, 0.5576047005454363), (5, 0.5401674204133556), (6, 0.525337027447814), (7, 0.5126744228033312), (8, 0.5017837634277559), (9, 0.49240895122440936), (10, 0.4842318810787298), (11, 0.47710570822445203), (12, 0.47089605720044525), (13, 0.4654872454429708), (14, 0.46074919632041916), (15, 0.45669330773350886), (16, 0.4531990902207359), (17, 0.4501912521562937), (18, 0.44753326417629286), (19, 0.4451770746499485), (20, 0.4431204291904168), (21, 0.44130735278331285), (22, 0.4396598307816107), (23, 0.4382003094944252), (24, 0.43690583830960916), (25, 0.43572405110088636), (26, 0.43463473974212846), (27, 0.433628799178408), (28, 0.432675605968641), (29, 0.4317891809204777), (30, 0.4309528146970763), (31, 0.43015401849488516), (32, 0.42938665579216534), (33, 0.42865050427334095), (34, 0.4279453578939293), (35, 0.42726727736850145), (36, 0.42661357450404547), (37, 0.42599664138523924), (38, 0.42537519421472564), (39, 0.4248379778875447), (40, 0.4243040079123814), (41, 0.423773478701904), (42, 0.4233299872327913), (43, 0.42289059675149976), (44, 0.4224693730465114), (45, 0.4220727420565911), (46, 0.4216748466951593), (47, 0.42134029775841114), (48, 0.4210016940921562), (49, 0.4206613571510702), (50, 0.4203599659453928), (51, 0.42002911673248383), (52, 0.4196970131325977), (53, 0.41936356989058543), (54, 0.41901816100773004), (55, 0.4187169607520709), (56, 0.41840458141500103), (57, 0.4181140713347464), (58, 0.41784309507155915), (59, 0.4175976900750476), (60, 0.417330565556119), (61, 0.41705646897464976), (62, 0.41681160852186977), (63, 0.416560650039916), (64, 0.41633009271842236), (65, 0.4160918595423755), (66, 0.41586958656052847), (67, 0.4156819267993718), (68, 0.4154631027849932), (69, 0.41527918376158807), (70, 0.4151178863985822), (71, 0.41497928717683685), (72, 0.41481488213590223), (73, 0.4146300280625311), (74, 0.4144589746664018), (75, 0.41426144178076374), (76, 0.4140580504611597), (77, 0.41389044371285955), (78, 0.4137656342425188), (79, 0.41366426294561304), (80, 0.41354879526788074), (81, 0.4134505630144613), (82, 0.4133851740297058), (83, 0.41330864499399234), (84, 0.4132153588503145), (85, 0.4130866375940369), (86, 0.41299402696966653), (87, 0.4128987254292294), (88, 0.4128004255364725), (89, 0.41269314500886173), (90, 0.4126429953819873), (91, 0.4125893024220281), (92, 0.4125255572210915), (93, 0.4125025400117636), (94, 0.4124772288472519), (95, 0.41246660032718785), (96, 0.4124660457989219), (97, 0.4124486146172224), (98, 0.4124262136923547), (99, 0.4124325342051941), (100, 0.4124234615243631)]\n",
      "INFO flower 2022-04-16 12:15:05,771 | app.py:150 | app_fit: metrics_distributed {}\n",
      "INFO flower 2022-04-16 12:15:05,772 | app.py:151 | app_fit: losses_centralized []\n",
      "INFO flower 2022-04-16 12:15:05,772 | app.py:152 | app_fit: metrics_centralized {}\n",
      "INFO flower 2022-04-16 12:15:11,033 | app.py:144 | Ray initialized with resources: {'object_store_memory': 6205999104.0, 'memory': 12411998208.0, 'node:127.0.0.1': 1.0, 'GPU': 1.0, 'CPU': 8.0}\n",
      "INFO flower 2022-04-16 12:15:11,034 | app.py:153 | Starting Flower simulation running: {'num_rounds': 100}\n",
      "INFO flower 2022-04-16 12:15:11,034 | server.py:128 | Initializing global parameters\n",
      "INFO flower 2022-04-16 12:15:11,035 | server.py:323 | Using initial parameters provided by strategy\n",
      "INFO flower 2022-04-16 12:15:11,035 | server.py:130 | Evaluating initial parameters\n",
      "INFO flower 2022-04-16 12:15:11,035 | server.py:143 | FL starting\n",
      "DEBUG flower 2022-04-16 12:15:11,036 | server.py:265 | fit_round: strategy sampled 7 clients (out of 7)\n",
      "DEBUG flower 2022-04-16 12:15:18,970 | server.py:277 | fit_round received 7 results and 0 failures\n",
      "DEBUG flower 2022-04-16 12:15:18,986 | server.py:211 | evaluate_round: strategy sampled 7 clients (out of 7)\n"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "Saving round 1 aggregated_weights...\n"
     ]
    },
    {
     "name": "stderr",
     "output_type": "stream",
     "text": [
      "DEBUG flower 2022-04-16 12:15:20,647 | server.py:223 | evaluate_round received 7 results and 0 failures\n",
      "INFO flower 2022-04-16 12:15:20,648 | 2719366172.py:15 | round-1-EVALUATION\n",
      "INFO flower 2022-04-16 12:15:20,650 | 2719366172.py:31 | [(9, 0.311740905046463), (15, 0.46332046389579773), (17, 0.2579365074634552), (18, 0.5662650465965271), (19, 0.8712121248245239), (20, 0.2666666805744171), (21, 0.3375527560710907)]\n",
      "INFO flower 2022-04-16 12:15:20,650 | 2719366172.py:37 | Aggregated accuracy: 0.439242069210325 +- 0.2044378947172924\n",
      "DEBUG flower 2022-04-16 12:15:20,651 | server.py:265 | fit_round: strategy sampled 7 clients (out of 7)\n",
      "DEBUG flower 2022-04-16 12:15:25,017 | server.py:277 | fit_round received 7 results and 0 failures\n",
      "DEBUG flower 2022-04-16 12:15:25,032 | server.py:211 | evaluate_round: strategy sampled 7 clients (out of 7)\n"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "Saving round 2 aggregated_weights...\n"
     ]
    },
    {
     "name": "stderr",
     "output_type": "stream",
     "text": [
      "DEBUG flower 2022-04-16 12:15:26,862 | server.py:223 | evaluate_round received 7 results and 0 failures\n",
      "INFO flower 2022-04-16 12:15:26,863 | 2719366172.py:15 | round-2-EVALUATION\n",
      "INFO flower 2022-04-16 12:15:26,865 | 2719366172.py:31 | [(9, 0.41295546293258667), (15, 0.4749034643173218), (17, 0.3452380895614624), (18, 0.6064257025718689), (19, 0.8939393758773804), (20, 0.32549020648002625), (21, 0.4261603355407715)]\n",
      "INFO flower 2022-04-16 12:15:26,866 | 2719366172.py:37 | Aggregated accuracy: 0.4978732338973454 +- 0.18304831549432185\n",
      "DEBUG flower 2022-04-16 12:15:26,866 | server.py:265 | fit_round: strategy sampled 7 clients (out of 7)\n",
      "DEBUG flower 2022-04-16 12:15:31,429 | server.py:277 | fit_round received 7 results and 0 failures\n",
      "DEBUG flower 2022-04-16 12:15:31,444 | server.py:211 | evaluate_round: strategy sampled 7 clients (out of 7)\n"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "Saving round 3 aggregated_weights...\n"
     ]
    },
    {
     "name": "stderr",
     "output_type": "stream",
     "text": [
      "DEBUG flower 2022-04-16 12:15:33,145 | server.py:223 | evaluate_round received 7 results and 0 failures\n",
      "INFO flower 2022-04-16 12:15:33,146 | 2719366172.py:15 | round-3-EVALUATION\n",
      "INFO flower 2022-04-16 12:15:33,148 | 2719366172.py:31 | [(9, 0.5263158082962036), (15, 0.5868725776672363), (17, 0.567460298538208), (18, 0.7670682668685913), (19, 0.7878788113594055), (20, 0.4117647111415863), (21, 0.552742600440979)]\n",
      "INFO flower 2022-04-16 12:15:33,149 | 2719366172.py:37 | Aggregated accuracy: 0.6000147249017443 +- 0.12394501045371308\n",
      "DEBUG flower 2022-04-16 12:15:33,149 | server.py:265 | fit_round: strategy sampled 7 clients (out of 7)\n",
      "DEBUG flower 2022-04-16 12:15:37,670 | server.py:277 | fit_round received 7 results and 0 failures\n",
      "DEBUG flower 2022-04-16 12:15:37,686 | server.py:211 | evaluate_round: strategy sampled 7 clients (out of 7)\n"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "Saving round 4 aggregated_weights...\n"
     ]
    },
    {
     "name": "stderr",
     "output_type": "stream",
     "text": [
      "DEBUG flower 2022-04-16 12:15:39,372 | server.py:223 | evaluate_round received 7 results and 0 failures\n",
      "INFO flower 2022-04-16 12:15:39,373 | 2719366172.py:15 | round-4-EVALUATION\n",
      "INFO flower 2022-04-16 12:15:39,375 | 2719366172.py:31 | [(9, 0.6680161952972412), (15, 0.7142857313156128), (17, 0.761904776096344), (18, 0.8353413939476013), (19, 0.6628788113594055), (20, 0.6509804129600525), (21, 0.746835470199585)]\n",
      "INFO flower 2022-04-16 12:15:39,376 | 2719366172.py:37 | Aggregated accuracy: 0.7200346844536918 +- 0.06157606661922333\n",
      "DEBUG flower 2022-04-16 12:15:39,376 | server.py:265 | fit_round: strategy sampled 7 clients (out of 7)\n",
      "DEBUG flower 2022-04-16 12:15:43,915 | server.py:277 | fit_round received 7 results and 0 failures\n",
      "DEBUG flower 2022-04-16 12:15:43,931 | server.py:211 | evaluate_round: strategy sampled 7 clients (out of 7)\n"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "Saving round 5 aggregated_weights...\n"
     ]
    },
    {
     "name": "stderr",
     "output_type": "stream",
     "text": [
      "DEBUG flower 2022-04-16 12:15:45,784 | server.py:223 | evaluate_round received 7 results and 0 failures\n",
      "INFO flower 2022-04-16 12:15:45,784 | 2719366172.py:15 | round-5-EVALUATION\n",
      "INFO flower 2022-04-16 12:15:45,787 | 2719366172.py:31 | [(9, 0.6761133670806885), (15, 0.7722007632255554), (17, 0.8452380895614624), (18, 0.8393574357032776), (19, 0.5719696879386902), (20, 0.7215686440467834), (21, 0.8354430198669434)]\n",
      "INFO flower 2022-04-16 12:15:45,787 | 2719366172.py:37 | Aggregated accuracy: 0.7516987153462001 +- 0.0947105346772165\n",
      "DEBUG flower 2022-04-16 12:15:45,788 | server.py:265 | fit_round: strategy sampled 7 clients (out of 7)\n",
      "DEBUG flower 2022-04-16 12:15:50,317 | server.py:277 | fit_round received 7 results and 0 failures\n",
      "DEBUG flower 2022-04-16 12:15:50,333 | server.py:211 | evaluate_round: strategy sampled 7 clients (out of 7)\n"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "Saving round 6 aggregated_weights...\n"
     ]
    },
    {
     "name": "stderr",
     "output_type": "stream",
     "text": [
      "DEBUG flower 2022-04-16 12:15:52,199 | server.py:223 | evaluate_round received 7 results and 0 failures\n",
      "INFO flower 2022-04-16 12:15:52,199 | 2719366172.py:15 | round-6-EVALUATION\n",
      "INFO flower 2022-04-16 12:15:52,201 | 2719366172.py:31 | [(9, 0.6842105388641357), (15, 0.7722007632255554), (17, 0.8730158805847168), (18, 0.8433734774589539), (19, 0.5340909361839294), (20, 0.7411764860153198), (21, 0.8354430198669434)]\n",
      "INFO flower 2022-04-16 12:15:52,202 | 2719366172.py:37 | Aggregated accuracy: 0.754787300314222 +- 0.10856683288846193\n",
      "DEBUG flower 2022-04-16 12:15:52,202 | server.py:265 | fit_round: strategy sampled 7 clients (out of 7)\n",
      "DEBUG flower 2022-04-16 12:15:56,717 | server.py:277 | fit_round received 7 results and 0 failures\n",
      "DEBUG flower 2022-04-16 12:15:56,734 | server.py:211 | evaluate_round: strategy sampled 7 clients (out of 7)\n"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "Saving round 7 aggregated_weights...\n"
     ]
    },
    {
     "name": "stderr",
     "output_type": "stream",
     "text": [
      "DEBUG flower 2022-04-16 12:15:58,515 | server.py:223 | evaluate_round received 7 results and 0 failures\n",
      "INFO flower 2022-04-16 12:15:58,516 | 2719366172.py:15 | round-7-EVALUATION\n",
      "INFO flower 2022-04-16 12:15:58,518 | 2719366172.py:31 | [(9, 0.7044534683227539), (15, 0.7876448035240173), (17, 0.8769841194152832), (18, 0.8433734774589539), (19, 0.5075757503509521), (20, 0.7568627595901489), (21, 0.8438818454742432)]\n",
      "INFO flower 2022-04-16 12:15:58,518 | 2719366172.py:37 | Aggregated accuracy: 0.760110889162336 +- 0.11664965574366894\n",
      "DEBUG flower 2022-04-16 12:15:58,519 | server.py:265 | fit_round: strategy sampled 7 clients (out of 7)\n",
      "DEBUG flower 2022-04-16 12:16:03,066 | server.py:277 | fit_round received 7 results and 0 failures\n",
      "DEBUG flower 2022-04-16 12:16:03,082 | server.py:211 | evaluate_round: strategy sampled 7 clients (out of 7)\n"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "Saving round 8 aggregated_weights...\n"
     ]
    },
    {
     "name": "stderr",
     "output_type": "stream",
     "text": [
      "DEBUG flower 2022-04-16 12:16:04,812 | server.py:223 | evaluate_round received 7 results and 0 failures\n",
      "INFO flower 2022-04-16 12:16:04,813 | 2719366172.py:15 | round-8-EVALUATION\n",
      "INFO flower 2022-04-16 12:16:04,815 | 2719366172.py:31 | [(9, 0.7085019946098328), (15, 0.7837837934494019), (17, 0.9047619104385376), (18, 0.8433734774589539), (19, 0.4886363744735718), (20, 0.7686274647712708), (21, 0.8607594966888428)]\n",
      "INFO flower 2022-04-16 12:16:04,816 | 2719366172.py:37 | Aggregated accuracy: 0.7654920731272016 +- 0.12805068603430758\n",
      "DEBUG flower 2022-04-16 12:16:04,816 | server.py:265 | fit_round: strategy sampled 7 clients (out of 7)\n",
      "DEBUG flower 2022-04-16 12:16:09,263 | server.py:277 | fit_round received 7 results and 0 failures\n",
      "DEBUG flower 2022-04-16 12:16:09,279 | server.py:211 | evaluate_round: strategy sampled 7 clients (out of 7)\n"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "Saving round 9 aggregated_weights...\n"
     ]
    },
    {
     "name": "stderr",
     "output_type": "stream",
     "text": [
      "DEBUG flower 2022-04-16 12:16:11,110 | server.py:223 | evaluate_round received 7 results and 0 failures\n",
      "INFO flower 2022-04-16 12:16:11,111 | 2719366172.py:15 | round-9-EVALUATION\n",
      "INFO flower 2022-04-16 12:16:11,113 | 2719366172.py:31 | [(9, 0.7044534683227539), (15, 0.7876448035240173), (17, 0.908730149269104), (18, 0.8433734774589539), (19, 0.4848484992980957), (20, 0.7686274647712708), (21, 0.8565400838851929)]\n",
      "INFO flower 2022-04-16 12:16:11,114 | 2719366172.py:37 | Aggregated accuracy: 0.7648882780756269 +- 0.1297563369408207\n",
      "DEBUG flower 2022-04-16 12:16:11,114 | server.py:265 | fit_round: strategy sampled 7 clients (out of 7)\n",
      "DEBUG flower 2022-04-16 12:16:15,493 | server.py:277 | fit_round received 7 results and 0 failures\n",
      "DEBUG flower 2022-04-16 12:16:15,509 | server.py:211 | evaluate_round: strategy sampled 7 clients (out of 7)\n"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "Saving round 10 aggregated_weights...\n"
     ]
    },
    {
     "name": "stderr",
     "output_type": "stream",
     "text": [
      "DEBUG flower 2022-04-16 12:16:17,379 | server.py:223 | evaluate_round received 7 results and 0 failures\n",
      "INFO flower 2022-04-16 12:16:17,379 | 2719366172.py:15 | round-10-EVALUATION\n",
      "INFO flower 2022-04-16 12:16:17,381 | 2719366172.py:31 | [(9, 0.71659916639328), (15, 0.7876448035240173), (17, 0.9126983880996704), (18, 0.8313252925872803), (19, 0.4886363744735718), (20, 0.7803921699523926), (21, 0.852320671081543)]\n",
      "INFO flower 2022-04-16 12:16:17,382 | 2719366172.py:37 | Aggregated accuracy: 0.7670881237302508 +- 0.12721041977065978\n",
      "DEBUG flower 2022-04-16 12:16:17,382 | server.py:265 | fit_round: strategy sampled 7 clients (out of 7)\n",
      "DEBUG flower 2022-04-16 12:16:21,873 | server.py:277 | fit_round received 7 results and 0 failures\n",
      "DEBUG flower 2022-04-16 12:16:21,889 | server.py:211 | evaluate_round: strategy sampled 7 clients (out of 7)\n"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "Saving round 11 aggregated_weights...\n"
     ]
    },
    {
     "name": "stderr",
     "output_type": "stream",
     "text": [
      "DEBUG flower 2022-04-16 12:16:23,590 | server.py:223 | evaluate_round received 7 results and 0 failures\n",
      "INFO flower 2022-04-16 12:16:23,590 | 2719366172.py:15 | round-11-EVALUATION\n",
      "INFO flower 2022-04-16 12:16:23,593 | 2719366172.py:31 | [(9, 0.7246963381767273), (15, 0.7876448035240173), (17, 0.9166666865348816), (18, 0.8313252925872803), (19, 0.48106059432029724), (20, 0.7764706015586853), (21, 0.8565400838851929)]\n",
      "INFO flower 2022-04-16 12:16:23,594 | 2719366172.py:37 | Aggregated accuracy: 0.767772057226726 +- 0.1301745850611817\n",
      "DEBUG flower 2022-04-16 12:16:23,594 | server.py:265 | fit_round: strategy sampled 7 clients (out of 7)\n",
      "DEBUG flower 2022-04-16 12:16:28,093 | server.py:277 | fit_round received 7 results and 0 failures\n",
      "DEBUG flower 2022-04-16 12:16:28,108 | server.py:211 | evaluate_round: strategy sampled 7 clients (out of 7)\n"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "Saving round 12 aggregated_weights...\n"
     ]
    },
    {
     "name": "stderr",
     "output_type": "stream",
     "text": [
      "DEBUG flower 2022-04-16 12:16:29,799 | server.py:223 | evaluate_round received 7 results and 0 failures\n",
      "INFO flower 2022-04-16 12:16:29,799 | 2719366172.py:15 | round-12-EVALUATION\n",
      "INFO flower 2022-04-16 12:16:29,801 | 2719366172.py:31 | [(9, 0.7246963381767273), (15, 0.7915058135986328), (17, 0.920634925365448), (18, 0.823293149471283), (19, 0.48106059432029724), (20, 0.7921568751335144), (21, 0.852320671081543)]\n",
      "INFO flower 2022-04-16 12:16:29,802 | 2719366172.py:37 | Aggregated accuracy: 0.769381195306778 +- 0.13027272603293133\n",
      "DEBUG flower 2022-04-16 12:16:29,803 | server.py:265 | fit_round: strategy sampled 7 clients (out of 7)\n",
      "DEBUG flower 2022-04-16 12:16:34,274 | server.py:277 | fit_round received 7 results and 0 failures\n",
      "DEBUG flower 2022-04-16 12:16:34,289 | server.py:211 | evaluate_round: strategy sampled 7 clients (out of 7)\n"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "Saving round 13 aggregated_weights...\n"
     ]
    },
    {
     "name": "stderr",
     "output_type": "stream",
     "text": [
      "DEBUG flower 2022-04-16 12:16:36,126 | server.py:223 | evaluate_round received 7 results and 0 failures\n",
      "INFO flower 2022-04-16 12:16:36,127 | 2719366172.py:15 | round-13-EVALUATION\n",
      "INFO flower 2022-04-16 12:16:36,129 | 2719366172.py:31 | [(9, 0.7287449240684509), (15, 0.7915058135986328), (17, 0.920634925365448), (18, 0.8192771077156067), (19, 0.48106059432029724), (20, 0.7960784435272217), (21, 0.852320671081543)]\n",
      "INFO flower 2022-04-16 12:16:36,130 | 2719366172.py:37 | Aggregated accuracy: 0.7699460685253143 +- 0.12995951748347132\n",
      "DEBUG flower 2022-04-16 12:16:36,130 | server.py:265 | fit_round: strategy sampled 7 clients (out of 7)\n",
      "DEBUG flower 2022-04-16 12:16:40,628 | server.py:277 | fit_round received 7 results and 0 failures\n",
      "DEBUG flower 2022-04-16 12:16:40,644 | server.py:211 | evaluate_round: strategy sampled 7 clients (out of 7)\n"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "Saving round 14 aggregated_weights...\n"
     ]
    },
    {
     "name": "stderr",
     "output_type": "stream",
     "text": [
      "DEBUG flower 2022-04-16 12:16:42,357 | server.py:223 | evaluate_round received 7 results and 0 failures\n",
      "INFO flower 2022-04-16 12:16:42,357 | 2719366172.py:15 | round-14-EVALUATION\n",
      "INFO flower 2022-04-16 12:16:42,359 | 2719366172.py:31 | [(9, 0.7287449240684509), (15, 0.7876448035240173), (17, 0.920634925365448), (18, 0.8112449645996094), (19, 0.4886363744735718), (20, 0.7921568751335144), (21, 0.8565400838851929)]\n",
      "INFO flower 2022-04-16 12:16:42,360 | 2719366172.py:37 | Aggregated accuracy: 0.7693718501499721 +- 0.12736235664123954\n",
      "DEBUG flower 2022-04-16 12:16:42,361 | server.py:265 | fit_round: strategy sampled 7 clients (out of 7)\n",
      "DEBUG flower 2022-04-16 12:16:46,872 | server.py:277 | fit_round received 7 results and 0 failures\n",
      "DEBUG flower 2022-04-16 12:16:46,888 | server.py:211 | evaluate_round: strategy sampled 7 clients (out of 7)\n"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "Saving round 15 aggregated_weights...\n"
     ]
    },
    {
     "name": "stderr",
     "output_type": "stream",
     "text": [
      "DEBUG flower 2022-04-16 12:16:48,575 | server.py:223 | evaluate_round received 7 results and 0 failures\n",
      "INFO flower 2022-04-16 12:16:48,576 | 2719366172.py:15 | round-15-EVALUATION\n",
      "INFO flower 2022-04-16 12:16:48,578 | 2719366172.py:31 | [(9, 0.7408906817436218), (15, 0.7915058135986328), (17, 0.9166666865348816), (18, 0.8072289228439331), (19, 0.4886363744735718), (20, 0.7960784435272217), (21, 0.8565400838851929)]\n",
      "INFO flower 2022-04-16 12:16:48,579 | 2719366172.py:37 | Aggregated accuracy: 0.7710781438010079 +- 0.12622745140067945\n",
      "DEBUG flower 2022-04-16 12:16:48,579 | server.py:265 | fit_round: strategy sampled 7 clients (out of 7)\n",
      "DEBUG flower 2022-04-16 12:16:53,068 | server.py:277 | fit_round received 7 results and 0 failures\n",
      "DEBUG flower 2022-04-16 12:16:53,084 | server.py:211 | evaluate_round: strategy sampled 7 clients (out of 7)\n"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "Saving round 16 aggregated_weights...\n"
     ]
    },
    {
     "name": "stderr",
     "output_type": "stream",
     "text": [
      "DEBUG flower 2022-04-16 12:16:54,816 | server.py:223 | evaluate_round received 7 results and 0 failures\n",
      "INFO flower 2022-04-16 12:16:54,816 | 2719366172.py:15 | round-16-EVALUATION\n",
      "INFO flower 2022-04-16 12:16:54,819 | 2719366172.py:31 | [(9, 0.7408906817436218), (15, 0.7876448035240173), (17, 0.9166666865348816), (18, 0.7991967797279358), (19, 0.5037878751754761), (20, 0.800000011920929), (21, 0.8565400838851929)]\n",
      "INFO flower 2022-04-16 12:16:54,819 | 2719366172.py:37 | Aggregated accuracy: 0.7721038460731506 +- 0.12115477671495754\n",
      "DEBUG flower 2022-04-16 12:16:54,820 | server.py:265 | fit_round: strategy sampled 7 clients (out of 7)\n",
      "DEBUG flower 2022-04-16 12:16:59,318 | server.py:277 | fit_round received 7 results and 0 failures\n",
      "DEBUG flower 2022-04-16 12:16:59,334 | server.py:211 | evaluate_round: strategy sampled 7 clients (out of 7)\n"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "Saving round 17 aggregated_weights...\n"
     ]
    },
    {
     "name": "stderr",
     "output_type": "stream",
     "text": [
      "DEBUG flower 2022-04-16 12:17:01,209 | server.py:223 | evaluate_round received 7 results and 0 failures\n",
      "INFO flower 2022-04-16 12:17:01,210 | 2719366172.py:15 | round-17-EVALUATION\n",
      "INFO flower 2022-04-16 12:17:01,212 | 2719366172.py:31 | [(9, 0.7449392676353455), (15, 0.7915058135986328), (17, 0.920634925365448), (18, 0.8032128810882568), (19, 0.5), (20, 0.800000011920929), (21, 0.8607594966888428)]\n",
      "INFO flower 2022-04-16 12:17:01,212 | 2719366172.py:37 | Aggregated accuracy: 0.7744360566139221 +- 0.12351058560863937\n",
      "DEBUG flower 2022-04-16 12:17:01,213 | server.py:265 | fit_round: strategy sampled 7 clients (out of 7)\n",
      "DEBUG flower 2022-04-16 12:17:05,749 | server.py:277 | fit_round received 7 results and 0 failures\n",
      "DEBUG flower 2022-04-16 12:17:05,764 | server.py:211 | evaluate_round: strategy sampled 7 clients (out of 7)\n"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "Saving round 18 aggregated_weights...\n"
     ]
    },
    {
     "name": "stderr",
     "output_type": "stream",
     "text": [
      "DEBUG flower 2022-04-16 12:17:07,500 | server.py:223 | evaluate_round received 7 results and 0 failures\n",
      "INFO flower 2022-04-16 12:17:07,500 | 2719366172.py:15 | round-18-EVALUATION\n",
      "INFO flower 2022-04-16 12:17:07,502 | 2719366172.py:31 | [(9, 0.7489878535270691), (15, 0.7915058135986328), (17, 0.9246031641960144), (18, 0.7911646366119385), (19, 0.5037878751754761), (20, 0.800000011920929), (21, 0.8607594966888428)]\n",
      "INFO flower 2022-04-16 12:17:07,503 | 2719366172.py:37 | Aggregated accuracy: 0.7744012645312718 +- 0.12254717749970562\n",
      "DEBUG flower 2022-04-16 12:17:07,504 | server.py:265 | fit_round: strategy sampled 7 clients (out of 7)\n",
      "DEBUG flower 2022-04-16 12:17:12,135 | server.py:277 | fit_round received 7 results and 0 failures\n",
      "DEBUG flower 2022-04-16 12:17:12,150 | server.py:211 | evaluate_round: strategy sampled 7 clients (out of 7)\n"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "Saving round 19 aggregated_weights...\n"
     ]
    },
    {
     "name": "stderr",
     "output_type": "stream",
     "text": [
      "DEBUG flower 2022-04-16 12:17:13,946 | server.py:223 | evaluate_round received 7 results and 0 failures\n",
      "INFO flower 2022-04-16 12:17:13,947 | 2719366172.py:15 | round-19-EVALUATION\n",
      "INFO flower 2022-04-16 12:17:13,949 | 2719366172.py:31 | [(9, 0.7489878535270691), (15, 0.7915058135986328), (17, 0.9246031641960144), (18, 0.7951807379722595), (19, 0.5037878751754761), (20, 0.800000011920929), (21, 0.8607594966888428)]\n",
      "INFO flower 2022-04-16 12:17:13,950 | 2719366172.py:37 | Aggregated accuracy: 0.7749749932970319 +- 0.12263368606900779\n",
      "DEBUG flower 2022-04-16 12:17:13,950 | server.py:265 | fit_round: strategy sampled 7 clients (out of 7)\n",
      "DEBUG flower 2022-04-16 12:17:18,406 | server.py:277 | fit_round received 7 results and 0 failures\n",
      "DEBUG flower 2022-04-16 12:17:18,422 | server.py:211 | evaluate_round: strategy sampled 7 clients (out of 7)\n"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "Saving round 20 aggregated_weights...\n"
     ]
    },
    {
     "name": "stderr",
     "output_type": "stream",
     "text": [
      "DEBUG flower 2022-04-16 12:17:20,274 | server.py:223 | evaluate_round received 7 results and 0 failures\n",
      "INFO flower 2022-04-16 12:17:20,275 | 2719366172.py:15 | round-20-EVALUATION\n",
      "INFO flower 2022-04-16 12:17:20,278 | 2719366172.py:31 | [(9, 0.7489878535270691), (15, 0.7953668236732483), (17, 0.9285714030265808), (18, 0.7951807379722595), (19, 0.5037878751754761), (20, 0.800000011920929), (21, 0.8607594966888428)]\n",
      "INFO flower 2022-04-16 12:17:20,278 | 2719366172.py:37 | Aggregated accuracy: 0.7760934574263436 +- 0.12341001132087223\n",
      "DEBUG flower 2022-04-16 12:17:20,279 | server.py:265 | fit_round: strategy sampled 7 clients (out of 7)\n",
      "DEBUG flower 2022-04-16 12:17:24,674 | server.py:277 | fit_round received 7 results and 0 failures\n",
      "DEBUG flower 2022-04-16 12:17:24,689 | server.py:211 | evaluate_round: strategy sampled 7 clients (out of 7)\n"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "Saving round 21 aggregated_weights...\n"
     ]
    },
    {
     "name": "stderr",
     "output_type": "stream",
     "text": [
      "DEBUG flower 2022-04-16 12:17:26,507 | server.py:223 | evaluate_round received 7 results and 0 failures\n",
      "INFO flower 2022-04-16 12:17:26,507 | 2719366172.py:15 | round-21-EVALUATION\n",
      "INFO flower 2022-04-16 12:17:26,509 | 2719366172.py:31 | [(9, 0.7489878535270691), (15, 0.7953668236732483), (17, 0.9285714030265808), (18, 0.7911646366119385), (19, 0.5075757503509521), (20, 0.800000011920929), (21, 0.8691983222961426)]\n",
      "INFO flower 2022-04-16 12:17:26,510 | 2719366172.py:37 | Aggregated accuracy: 0.77726640020098 +- 0.12300697332481877\n",
      "DEBUG flower 2022-04-16 12:17:26,510 | server.py:265 | fit_round: strategy sampled 7 clients (out of 7)\n",
      "DEBUG flower 2022-04-16 12:17:31,003 | server.py:277 | fit_round received 7 results and 0 failures\n",
      "DEBUG flower 2022-04-16 12:17:31,019 | server.py:211 | evaluate_round: strategy sampled 7 clients (out of 7)\n"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "Saving round 22 aggregated_weights...\n"
     ]
    },
    {
     "name": "stderr",
     "output_type": "stream",
     "text": [
      "DEBUG flower 2022-04-16 12:17:32,703 | server.py:223 | evaluate_round received 7 results and 0 failures\n",
      "INFO flower 2022-04-16 12:17:32,704 | 2719366172.py:15 | round-22-EVALUATION\n",
      "INFO flower 2022-04-16 12:17:32,706 | 2719366172.py:31 | [(9, 0.7489878535270691), (15, 0.7953668236732483), (17, 0.9285714030265808), (18, 0.7911646366119385), (19, 0.5037878751754761), (20, 0.800000011920929), (21, 0.8691983222961426)]\n",
      "INFO flower 2022-04-16 12:17:32,707 | 2719366172.py:37 | Aggregated accuracy: 0.776725275175912 +- 0.12419478694216844\n",
      "DEBUG flower 2022-04-16 12:17:32,707 | server.py:265 | fit_round: strategy sampled 7 clients (out of 7)\n",
      "DEBUG flower 2022-04-16 12:17:37,191 | server.py:277 | fit_round received 7 results and 0 failures\n",
      "DEBUG flower 2022-04-16 12:17:37,207 | server.py:211 | evaluate_round: strategy sampled 7 clients (out of 7)\n"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "Saving round 23 aggregated_weights...\n"
     ]
    },
    {
     "name": "stderr",
     "output_type": "stream",
     "text": [
      "DEBUG flower 2022-04-16 12:17:38,914 | server.py:223 | evaluate_round received 7 results and 0 failures\n",
      "INFO flower 2022-04-16 12:17:38,914 | 2719366172.py:15 | round-23-EVALUATION\n",
      "INFO flower 2022-04-16 12:17:38,916 | 2719366172.py:31 | [(9, 0.7489878535270691), (15, 0.7953668236732483), (17, 0.9285714030265808), (18, 0.7871485948562622), (19, 0.5151515007019043), (20, 0.7960784435272217), (21, 0.8691983222961426)]\n",
      "INFO flower 2022-04-16 12:17:38,917 | 2719366172.py:37 | Aggregated accuracy: 0.7772147059440613 +- 0.12049169283201973\n",
      "DEBUG flower 2022-04-16 12:17:38,918 | server.py:265 | fit_round: strategy sampled 7 clients (out of 7)\n",
      "DEBUG flower 2022-04-16 12:17:43,416 | server.py:277 | fit_round received 7 results and 0 failures\n",
      "DEBUG flower 2022-04-16 12:17:43,431 | server.py:211 | evaluate_round: strategy sampled 7 clients (out of 7)\n"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "Saving round 24 aggregated_weights...\n"
     ]
    },
    {
     "name": "stderr",
     "output_type": "stream",
     "text": [
      "DEBUG flower 2022-04-16 12:17:45,214 | server.py:223 | evaluate_round received 7 results and 0 failures\n",
      "INFO flower 2022-04-16 12:17:45,214 | 2719366172.py:15 | round-24-EVALUATION\n",
      "INFO flower 2022-04-16 12:17:45,217 | 2719366172.py:31 | [(9, 0.7530364394187927), (15, 0.8030887842178345), (17, 0.9285714030265808), (18, 0.7871485948562622), (19, 0.5151515007019043), (20, 0.7960784435272217), (21, 0.8691983222961426)]\n",
      "INFO flower 2022-04-16 12:17:45,217 | 2719366172.py:37 | Aggregated accuracy: 0.7788962125778198 +- 0.12055570494412489\n",
      "DEBUG flower 2022-04-16 12:17:45,218 | server.py:265 | fit_round: strategy sampled 7 clients (out of 7)\n",
      "DEBUG flower 2022-04-16 12:17:49,828 | server.py:277 | fit_round received 7 results and 0 failures\n",
      "DEBUG flower 2022-04-16 12:17:49,843 | server.py:211 | evaluate_round: strategy sampled 7 clients (out of 7)\n"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "Saving round 25 aggregated_weights...\n"
     ]
    },
    {
     "name": "stderr",
     "output_type": "stream",
     "text": [
      "DEBUG flower 2022-04-16 12:17:51,723 | server.py:223 | evaluate_round received 7 results and 0 failures\n",
      "INFO flower 2022-04-16 12:17:51,723 | 2719366172.py:15 | round-25-EVALUATION\n",
      "INFO flower 2022-04-16 12:17:51,725 | 2719366172.py:31 | [(9, 0.7530364394187927), (15, 0.8030887842178345), (17, 0.9285714030265808), (18, 0.7871485948562622), (19, 0.5151515007019043), (20, 0.7882353067398071), (21, 0.8691983222961426)]\n",
      "INFO flower 2022-04-16 12:17:51,726 | 2719366172.py:37 | Aggregated accuracy: 0.777775764465332 +- 0.1204271847297793\n",
      "DEBUG flower 2022-04-16 12:17:51,726 | server.py:265 | fit_round: strategy sampled 7 clients (out of 7)\n",
      "DEBUG flower 2022-04-16 12:17:56,369 | server.py:277 | fit_round received 7 results and 0 failures\n",
      "DEBUG flower 2022-04-16 12:17:56,385 | server.py:211 | evaluate_round: strategy sampled 7 clients (out of 7)\n"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "Saving round 26 aggregated_weights...\n"
     ]
    },
    {
     "name": "stderr",
     "output_type": "stream",
     "text": [
      "DEBUG flower 2022-04-16 12:17:58,077 | server.py:223 | evaluate_round received 7 results and 0 failures\n",
      "INFO flower 2022-04-16 12:17:58,077 | 2719366172.py:15 | round-26-EVALUATION\n",
      "INFO flower 2022-04-16 12:17:58,080 | 2719366172.py:31 | [(9, 0.7530364394187927), (15, 0.8030887842178345), (17, 0.9285714030265808), (18, 0.7871485948562622), (19, 0.5189393758773804), (20, 0.7843137383460999), (21, 0.8649789094924927)]\n",
      "INFO flower 2022-04-16 12:17:58,080 | 2719366172.py:37 | Aggregated accuracy: 0.7771538921764919 +- 0.11875584816740735\n",
      "DEBUG flower 2022-04-16 12:17:58,081 | server.py:265 | fit_round: strategy sampled 7 clients (out of 7)\n",
      "DEBUG flower 2022-04-16 12:18:02,614 | server.py:277 | fit_round received 7 results and 0 failures\n",
      "DEBUG flower 2022-04-16 12:18:02,629 | server.py:211 | evaluate_round: strategy sampled 7 clients (out of 7)\n"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "Saving round 27 aggregated_weights...\n"
     ]
    },
    {
     "name": "stderr",
     "output_type": "stream",
     "text": [
      "DEBUG flower 2022-04-16 12:18:04,363 | server.py:223 | evaluate_round received 7 results and 0 failures\n",
      "INFO flower 2022-04-16 12:18:04,363 | 2719366172.py:15 | round-27-EVALUATION\n",
      "INFO flower 2022-04-16 12:18:04,366 | 2719366172.py:31 | [(9, 0.7530364394187927), (15, 0.799227774143219), (17, 0.9285714030265808), (18, 0.7871485948562622), (19, 0.5189393758773804), (20, 0.7843137383460999), (21, 0.8649789094924927)]\n",
      "INFO flower 2022-04-16 12:18:04,366 | 2719366172.py:37 | Aggregated accuracy: 0.7766023193086896 +- 0.11864302298986029\n",
      "DEBUG flower 2022-04-16 12:18:04,367 | server.py:265 | fit_round: strategy sampled 7 clients (out of 7)\n",
      "DEBUG flower 2022-04-16 12:18:08,787 | server.py:277 | fit_round received 7 results and 0 failures\n",
      "DEBUG flower 2022-04-16 12:18:08,803 | server.py:211 | evaluate_round: strategy sampled 7 clients (out of 7)\n"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "Saving round 28 aggregated_weights...\n"
     ]
    },
    {
     "name": "stderr",
     "output_type": "stream",
     "text": [
      "DEBUG flower 2022-04-16 12:18:10,622 | server.py:223 | evaluate_round received 7 results and 0 failures\n",
      "INFO flower 2022-04-16 12:18:10,623 | 2719366172.py:15 | round-28-EVALUATION\n",
      "INFO flower 2022-04-16 12:18:10,625 | 2719366172.py:31 | [(9, 0.7530364394187927), (15, 0.799227774143219), (17, 0.9285714030265808), (18, 0.7951807379722595), (19, 0.5265151262283325), (20, 0.7764706015586853), (21, 0.8649789094924927)]\n",
      "INFO flower 2022-04-16 12:18:10,626 | 2719366172.py:37 | Aggregated accuracy: 0.7777115702629089 +- 0.11640597190662758\n",
      "DEBUG flower 2022-04-16 12:18:10,626 | server.py:265 | fit_round: strategy sampled 7 clients (out of 7)\n",
      "DEBUG flower 2022-04-16 12:18:15,021 | server.py:277 | fit_round received 7 results and 0 failures\n",
      "DEBUG flower 2022-04-16 12:18:15,036 | server.py:211 | evaluate_round: strategy sampled 7 clients (out of 7)\n"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "Saving round 29 aggregated_weights...\n"
     ]
    },
    {
     "name": "stderr",
     "output_type": "stream",
     "text": [
      "DEBUG flower 2022-04-16 12:18:16,828 | server.py:223 | evaluate_round received 7 results and 0 failures\n",
      "INFO flower 2022-04-16 12:18:16,828 | 2719366172.py:15 | round-29-EVALUATION\n",
      "INFO flower 2022-04-16 12:18:16,830 | 2719366172.py:31 | [(9, 0.7530364394187927), (15, 0.799227774143219), (17, 0.9285714030265808), (18, 0.7951807379722595), (19, 0.5265151262283325), (20, 0.7764706015586853), (21, 0.8649789094924927)]\n",
      "INFO flower 2022-04-16 12:18:16,831 | 2719366172.py:37 | Aggregated accuracy: 0.7777115702629089 +- 0.11640597190662758\n",
      "DEBUG flower 2022-04-16 12:18:16,831 | server.py:265 | fit_round: strategy sampled 7 clients (out of 7)\n",
      "DEBUG flower 2022-04-16 12:18:21,551 | server.py:277 | fit_round received 7 results and 0 failures\n",
      "DEBUG flower 2022-04-16 12:18:21,566 | server.py:211 | evaluate_round: strategy sampled 7 clients (out of 7)\n"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "Saving round 30 aggregated_weights...\n"
     ]
    },
    {
     "name": "stderr",
     "output_type": "stream",
     "text": [
      "DEBUG flower 2022-04-16 12:18:23,297 | server.py:223 | evaluate_round received 7 results and 0 failures\n",
      "INFO flower 2022-04-16 12:18:23,298 | 2719366172.py:15 | round-30-EVALUATION\n",
      "INFO flower 2022-04-16 12:18:23,300 | 2719366172.py:31 | [(9, 0.7530364394187927), (15, 0.799227774143219), (17, 0.9285714030265808), (18, 0.7991967797279358), (19, 0.5265151262283325), (20, 0.7803921699523926), (21, 0.8649789094924927)]\n",
      "INFO flower 2022-04-16 12:18:23,301 | 2719366172.py:37 | Aggregated accuracy: 0.7788455145699638 +- 0.11649987080159269\n",
      "DEBUG flower 2022-04-16 12:18:23,301 | server.py:265 | fit_round: strategy sampled 7 clients (out of 7)\n",
      "DEBUG flower 2022-04-16 12:18:27,802 | server.py:277 | fit_round received 7 results and 0 failures\n",
      "DEBUG flower 2022-04-16 12:18:27,817 | server.py:211 | evaluate_round: strategy sampled 7 clients (out of 7)\n"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "Saving round 31 aggregated_weights...\n"
     ]
    },
    {
     "name": "stderr",
     "output_type": "stream",
     "text": [
      "DEBUG flower 2022-04-16 12:18:29,558 | server.py:223 | evaluate_round received 7 results and 0 failures\n",
      "INFO flower 2022-04-16 12:18:29,558 | 2719366172.py:15 | round-31-EVALUATION\n",
      "INFO flower 2022-04-16 12:18:29,560 | 2719366172.py:31 | [(9, 0.7570850253105164), (15, 0.8030887842178345), (17, 0.9246031641960144), (18, 0.7991967797279358), (19, 0.5303030014038086), (20, 0.7803921699523926), (21, 0.8691983222961426)]\n",
      "INFO flower 2022-04-16 12:18:29,561 | 2719366172.py:37 | Aggregated accuracy: 0.7805524638720921 +- 0.11504019704958693\n",
      "DEBUG flower 2022-04-16 12:18:29,561 | server.py:265 | fit_round: strategy sampled 7 clients (out of 7)\n",
      "DEBUG flower 2022-04-16 12:18:34,039 | server.py:277 | fit_round received 7 results and 0 failures\n",
      "DEBUG flower 2022-04-16 12:18:34,055 | server.py:211 | evaluate_round: strategy sampled 7 clients (out of 7)\n"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "Saving round 32 aggregated_weights...\n"
     ]
    },
    {
     "name": "stderr",
     "output_type": "stream",
     "text": [
      "DEBUG flower 2022-04-16 12:18:35,775 | server.py:223 | evaluate_round received 7 results and 0 failures\n",
      "INFO flower 2022-04-16 12:18:35,775 | 2719366172.py:15 | round-32-EVALUATION\n",
      "INFO flower 2022-04-16 12:18:35,778 | 2719366172.py:31 | [(9, 0.7570850253105164), (15, 0.8108108043670654), (17, 0.9246031641960144), (18, 0.7991967797279358), (19, 0.5303030014038086), (20, 0.7764706015586853), (21, 0.8691983222961426)]\n",
      "INFO flower 2022-04-16 12:18:35,778 | 2719366172.py:37 | Aggregated accuracy: 0.7810953855514526 +- 0.11530207689456039\n",
      "DEBUG flower 2022-04-16 12:18:35,779 | server.py:265 | fit_round: strategy sampled 7 clients (out of 7)\n",
      "DEBUG flower 2022-04-16 12:18:40,203 | server.py:277 | fit_round received 7 results and 0 failures\n",
      "DEBUG flower 2022-04-16 12:18:40,219 | server.py:211 | evaluate_round: strategy sampled 7 clients (out of 7)\n"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "Saving round 33 aggregated_weights...\n"
     ]
    },
    {
     "name": "stderr",
     "output_type": "stream",
     "text": [
      "DEBUG flower 2022-04-16 12:18:42,041 | server.py:223 | evaluate_round received 7 results and 0 failures\n",
      "INFO flower 2022-04-16 12:18:42,042 | 2719366172.py:15 | round-33-EVALUATION\n",
      "INFO flower 2022-04-16 12:18:42,044 | 2719366172.py:31 | [(9, 0.7570850253105164), (15, 0.8108108043670654), (17, 0.9246031641960144), (18, 0.7991967797279358), (19, 0.5303030014038086), (20, 0.7686274647712708), (21, 0.8691983222961426)]\n",
      "INFO flower 2022-04-16 12:18:42,044 | 2719366172.py:37 | Aggregated accuracy: 0.7799749374389648 +- 0.11537965601017582\n",
      "DEBUG flower 2022-04-16 12:18:42,045 | server.py:265 | fit_round: strategy sampled 7 clients (out of 7)\n",
      "DEBUG flower 2022-04-16 12:18:46,530 | server.py:277 | fit_round received 7 results and 0 failures\n",
      "DEBUG flower 2022-04-16 12:18:46,545 | server.py:211 | evaluate_round: strategy sampled 7 clients (out of 7)\n"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "Saving round 34 aggregated_weights...\n"
     ]
    },
    {
     "name": "stderr",
     "output_type": "stream",
     "text": [
      "DEBUG flower 2022-04-16 12:18:48,271 | server.py:223 | evaluate_round received 7 results and 0 failures\n",
      "INFO flower 2022-04-16 12:18:48,272 | 2719366172.py:15 | round-34-EVALUATION\n",
      "INFO flower 2022-04-16 12:18:48,274 | 2719366172.py:31 | [(9, 0.7570850253105164), (15, 0.8146718144416809), (17, 0.9246031641960144), (18, 0.7991967797279358), (19, 0.5303030014038086), (20, 0.7686274647712708), (21, 0.8734177350997925)]\n",
      "INFO flower 2022-04-16 12:18:48,274 | 2719366172.py:37 | Aggregated accuracy: 0.7811292835644313 +- 0.11600596915441663\n",
      "DEBUG flower 2022-04-16 12:18:48,275 | server.py:265 | fit_round: strategy sampled 7 clients (out of 7)\n",
      "DEBUG flower 2022-04-16 12:18:52,803 | server.py:277 | fit_round received 7 results and 0 failures\n",
      "DEBUG flower 2022-04-16 12:18:52,818 | server.py:211 | evaluate_round: strategy sampled 7 clients (out of 7)\n"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "Saving round 35 aggregated_weights...\n"
     ]
    },
    {
     "name": "stderr",
     "output_type": "stream",
     "text": [
      "DEBUG flower 2022-04-16 12:18:54,557 | server.py:223 | evaluate_round received 7 results and 0 failures\n",
      "INFO flower 2022-04-16 12:18:54,558 | 2719366172.py:15 | round-35-EVALUATION\n",
      "INFO flower 2022-04-16 12:18:54,560 | 2719366172.py:31 | [(9, 0.7570850253105164), (15, 0.8108108043670654), (17, 0.9246031641960144), (18, 0.7991967797279358), (19, 0.5265151262283325), (20, 0.7647058963775635), (21, 0.8734177350997925)]\n",
      "INFO flower 2022-04-16 12:18:54,560 | 2719366172.py:37 | Aggregated accuracy: 0.7794763616153172 +- 0.1170875361586421\n",
      "DEBUG flower 2022-04-16 12:18:54,561 | server.py:265 | fit_round: strategy sampled 7 clients (out of 7)\n",
      "DEBUG flower 2022-04-16 12:18:59,026 | server.py:277 | fit_round received 7 results and 0 failures\n",
      "DEBUG flower 2022-04-16 12:18:59,041 | server.py:211 | evaluate_round: strategy sampled 7 clients (out of 7)\n"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "Saving round 36 aggregated_weights...\n"
     ]
    },
    {
     "name": "stderr",
     "output_type": "stream",
     "text": [
      "DEBUG flower 2022-04-16 12:19:00,891 | server.py:223 | evaluate_round received 7 results and 0 failures\n",
      "INFO flower 2022-04-16 12:19:00,892 | 2719366172.py:15 | round-36-EVALUATION\n",
      "INFO flower 2022-04-16 12:19:00,894 | 2719366172.py:31 | [(9, 0.7570850253105164), (15, 0.80694979429245), (17, 0.9246031641960144), (18, 0.7991967797279358), (19, 0.5303030014038086), (20, 0.7647058963775635), (21, 0.8734177350997925)]\n",
      "INFO flower 2022-04-16 12:19:00,895 | 2719366172.py:37 | Aggregated accuracy: 0.779465913772583 +- 0.11578141729316278\n",
      "DEBUG flower 2022-04-16 12:19:00,895 | server.py:265 | fit_round: strategy sampled 7 clients (out of 7)\n",
      "DEBUG flower 2022-04-16 12:19:05,290 | server.py:277 | fit_round received 7 results and 0 failures\n",
      "DEBUG flower 2022-04-16 12:19:05,306 | server.py:211 | evaluate_round: strategy sampled 7 clients (out of 7)\n"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "Saving round 37 aggregated_weights...\n"
     ]
    },
    {
     "name": "stderr",
     "output_type": "stream",
     "text": [
      "DEBUG flower 2022-04-16 12:19:07,139 | server.py:223 | evaluate_round received 7 results and 0 failures\n",
      "INFO flower 2022-04-16 12:19:07,139 | 2719366172.py:15 | round-37-EVALUATION\n",
      "INFO flower 2022-04-16 12:19:07,142 | 2719366172.py:31 | [(9, 0.7570850253105164), (15, 0.80694979429245), (17, 0.9246031641960144), (18, 0.7991967797279358), (19, 0.5340909361839294), (20, 0.7647058963775635), (21, 0.8734177350997925)]\n",
      "INFO flower 2022-04-16 12:19:07,142 | 2719366172.py:37 | Aggregated accuracy: 0.7800070473126003 +- 0.11461864039430947\n",
      "DEBUG flower 2022-04-16 12:19:07,142 | server.py:265 | fit_round: strategy sampled 7 clients (out of 7)\n",
      "DEBUG flower 2022-04-16 12:19:11,653 | server.py:277 | fit_round received 7 results and 0 failures\n",
      "DEBUG flower 2022-04-16 12:19:11,669 | server.py:211 | evaluate_round: strategy sampled 7 clients (out of 7)\n"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "Saving round 38 aggregated_weights...\n"
     ]
    },
    {
     "name": "stderr",
     "output_type": "stream",
     "text": [
      "DEBUG flower 2022-04-16 12:19:13,404 | server.py:223 | evaluate_round received 7 results and 0 failures\n",
      "INFO flower 2022-04-16 12:19:13,404 | 2719366172.py:15 | round-38-EVALUATION\n",
      "INFO flower 2022-04-16 12:19:13,406 | 2719366172.py:31 | [(9, 0.7570850253105164), (15, 0.80694979429245), (17, 0.9246031641960144), (18, 0.7991967797279358), (19, 0.5340909361839294), (20, 0.7647058963775635), (21, 0.8734177350997925)]\n",
      "INFO flower 2022-04-16 12:19:13,407 | 2719366172.py:37 | Aggregated accuracy: 0.7800070473126003 +- 0.11461864039430948\n",
      "DEBUG flower 2022-04-16 12:19:13,407 | server.py:265 | fit_round: strategy sampled 7 clients (out of 7)\n",
      "DEBUG flower 2022-04-16 12:19:17,948 | server.py:277 | fit_round received 7 results and 0 failures\n",
      "DEBUG flower 2022-04-16 12:19:17,964 | server.py:211 | evaluate_round: strategy sampled 7 clients (out of 7)\n"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "Saving round 39 aggregated_weights...\n"
     ]
    },
    {
     "name": "stderr",
     "output_type": "stream",
     "text": [
      "DEBUG flower 2022-04-16 12:19:19,693 | server.py:223 | evaluate_round received 7 results and 0 failures\n",
      "INFO flower 2022-04-16 12:19:19,693 | 2719366172.py:15 | round-39-EVALUATION\n",
      "INFO flower 2022-04-16 12:19:19,696 | 2719366172.py:31 | [(9, 0.7570850253105164), (15, 0.799227774143219), (17, 0.9246031641960144), (18, 0.7991967797279358), (19, 0.5340909361839294), (20, 0.7647058963775635), (21, 0.8734177350997925)]\n",
      "INFO flower 2022-04-16 12:19:19,697 | 2719366172.py:37 | Aggregated accuracy: 0.7789039015769958 +- 0.1143909557441118\n",
      "DEBUG flower 2022-04-16 12:19:19,697 | server.py:265 | fit_round: strategy sampled 7 clients (out of 7)\n",
      "DEBUG flower 2022-04-16 12:19:24,221 | server.py:277 | fit_round received 7 results and 0 failures\n",
      "DEBUG flower 2022-04-16 12:19:24,236 | server.py:211 | evaluate_round: strategy sampled 7 clients (out of 7)\n"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "Saving round 40 aggregated_weights...\n"
     ]
    },
    {
     "name": "stderr",
     "output_type": "stream",
     "text": [
      "DEBUG flower 2022-04-16 12:19:26,081 | server.py:223 | evaluate_round received 7 results and 0 failures\n",
      "INFO flower 2022-04-16 12:19:26,082 | 2719366172.py:15 | round-40-EVALUATION\n",
      "INFO flower 2022-04-16 12:19:26,084 | 2719366172.py:31 | [(9, 0.7651821970939636), (15, 0.799227774143219), (17, 0.9246031641960144), (18, 0.7991967797279358), (19, 0.5378788113594055), (20, 0.7647058963775635), (21, 0.8691983222961426)]\n",
      "INFO flower 2022-04-16 12:19:26,085 | 2719366172.py:37 | Aggregated accuracy: 0.7799989921706063 +- 0.1125552475876192\n",
      "DEBUG flower 2022-04-16 12:19:26,085 | server.py:265 | fit_round: strategy sampled 7 clients (out of 7)\n",
      "DEBUG flower 2022-04-16 12:19:30,626 | server.py:277 | fit_round received 7 results and 0 failures\n",
      "DEBUG flower 2022-04-16 12:19:30,642 | server.py:211 | evaluate_round: strategy sampled 7 clients (out of 7)\n"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "Saving round 41 aggregated_weights...\n"
     ]
    },
    {
     "name": "stderr",
     "output_type": "stream",
     "text": [
      "DEBUG flower 2022-04-16 12:19:32,355 | server.py:223 | evaluate_round received 7 results and 0 failures\n",
      "INFO flower 2022-04-16 12:19:32,356 | 2719366172.py:15 | round-41-EVALUATION\n",
      "INFO flower 2022-04-16 12:19:32,358 | 2719366172.py:31 | [(9, 0.7651821970939636), (15, 0.799227774143219), (17, 0.9246031641960144), (18, 0.7991967797279358), (19, 0.5378788113594055), (20, 0.7647058963775635), (21, 0.8649789094924927)]\n",
      "INFO flower 2022-04-16 12:19:32,358 | 2719366172.py:37 | Aggregated accuracy: 0.7793962189129421 +- 0.11208626067234427\n",
      "DEBUG flower 2022-04-16 12:19:32,359 | server.py:265 | fit_round: strategy sampled 7 clients (out of 7)\n",
      "DEBUG flower 2022-04-16 12:19:36,846 | server.py:277 | fit_round received 7 results and 0 failures\n",
      "DEBUG flower 2022-04-16 12:19:36,862 | server.py:211 | evaluate_round: strategy sampled 7 clients (out of 7)\n"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "Saving round 42 aggregated_weights...\n"
     ]
    },
    {
     "name": "stderr",
     "output_type": "stream",
     "text": [
      "DEBUG flower 2022-04-16 12:19:38,628 | server.py:223 | evaluate_round received 7 results and 0 failures\n",
      "INFO flower 2022-04-16 12:19:38,628 | 2719366172.py:15 | round-42-EVALUATION\n",
      "INFO flower 2022-04-16 12:19:38,630 | 2719366172.py:31 | [(9, 0.7651821970939636), (15, 0.8030887842178345), (17, 0.9246031641960144), (18, 0.7991967797279358), (19, 0.5378788113594055), (20, 0.7607843279838562), (21, 0.8649789094924927)]\n",
      "INFO flower 2022-04-16 12:19:38,631 | 2719366172.py:37 | Aggregated accuracy: 0.7793875677245004 +- 0.11227641418284058\n",
      "DEBUG flower 2022-04-16 12:19:38,631 | server.py:265 | fit_round: strategy sampled 7 clients (out of 7)\n",
      "DEBUG flower 2022-04-16 12:19:43,141 | server.py:277 | fit_round received 7 results and 0 failures\n",
      "DEBUG flower 2022-04-16 12:19:43,157 | server.py:211 | evaluate_round: strategy sampled 7 clients (out of 7)\n"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "Saving round 43 aggregated_weights...\n"
     ]
    },
    {
     "name": "stderr",
     "output_type": "stream",
     "text": [
      "DEBUG flower 2022-04-16 12:19:44,933 | server.py:223 | evaluate_round received 7 results and 0 failures\n",
      "INFO flower 2022-04-16 12:19:44,934 | 2719366172.py:15 | round-43-EVALUATION\n",
      "INFO flower 2022-04-16 12:19:44,936 | 2719366172.py:31 | [(9, 0.7651821970939636), (15, 0.8030887842178345), (17, 0.920634925365448), (18, 0.7991967797279358), (19, 0.5378788113594055), (20, 0.7607843279838562), (21, 0.8649789094924927)]\n",
      "INFO flower 2022-04-16 12:19:44,936 | 2719366172.py:37 | Aggregated accuracy: 0.7788206764629909 +- 0.11154944406236116\n",
      "DEBUG flower 2022-04-16 12:19:44,937 | server.py:265 | fit_round: strategy sampled 7 clients (out of 7)\n",
      "DEBUG flower 2022-04-16 12:19:49,513 | server.py:277 | fit_round received 7 results and 0 failures\n",
      "DEBUG flower 2022-04-16 12:19:49,528 | server.py:211 | evaluate_round: strategy sampled 7 clients (out of 7)\n"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "Saving round 44 aggregated_weights...\n"
     ]
    },
    {
     "name": "stderr",
     "output_type": "stream",
     "text": [
      "DEBUG flower 2022-04-16 12:19:51,445 | server.py:223 | evaluate_round received 7 results and 0 failures\n",
      "INFO flower 2022-04-16 12:19:51,446 | 2719366172.py:15 | round-44-EVALUATION\n",
      "INFO flower 2022-04-16 12:19:51,448 | 2719366172.py:31 | [(9, 0.7651821970939636), (15, 0.8030887842178345), (17, 0.920634925365448), (18, 0.7991967797279358), (19, 0.5378788113594055), (20, 0.7607843279838562), (21, 0.8649789094924927)]\n",
      "INFO flower 2022-04-16 12:19:51,449 | 2719366172.py:37 | Aggregated accuracy: 0.7788206764629909 +- 0.11154944406236116\n",
      "DEBUG flower 2022-04-16 12:19:51,449 | server.py:265 | fit_round: strategy sampled 7 clients (out of 7)\n",
      "DEBUG flower 2022-04-16 12:19:56,051 | server.py:277 | fit_round received 7 results and 0 failures\n",
      "DEBUG flower 2022-04-16 12:19:56,067 | server.py:211 | evaluate_round: strategy sampled 7 clients (out of 7)\n"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "Saving round 45 aggregated_weights...\n"
     ]
    },
    {
     "name": "stderr",
     "output_type": "stream",
     "text": [
      "DEBUG flower 2022-04-16 12:19:57,852 | server.py:223 | evaluate_round received 7 results and 0 failures\n",
      "INFO flower 2022-04-16 12:19:57,852 | 2719366172.py:15 | round-45-EVALUATION\n",
      "INFO flower 2022-04-16 12:19:57,855 | 2719366172.py:31 | [(9, 0.7651821970939636), (15, 0.8030887842178345), (17, 0.920634925365448), (18, 0.7991967797279358), (19, 0.5378788113594055), (20, 0.7607843279838562), (21, 0.8607594966888428)]\n",
      "INFO flower 2022-04-16 12:19:57,855 | 2719366172.py:37 | Aggregated accuracy: 0.7782179032053266 +- 0.11109271230205513\n",
      "DEBUG flower 2022-04-16 12:19:57,856 | server.py:265 | fit_round: strategy sampled 7 clients (out of 7)\n",
      "DEBUG flower 2022-04-16 12:20:02,376 | server.py:277 | fit_round received 7 results and 0 failures\n",
      "DEBUG flower 2022-04-16 12:20:02,392 | server.py:211 | evaluate_round: strategy sampled 7 clients (out of 7)\n"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "Saving round 46 aggregated_weights...\n"
     ]
    },
    {
     "name": "stderr",
     "output_type": "stream",
     "text": [
      "DEBUG flower 2022-04-16 12:20:04,103 | server.py:223 | evaluate_round received 7 results and 0 failures\n",
      "INFO flower 2022-04-16 12:20:04,104 | 2719366172.py:15 | round-46-EVALUATION\n",
      "INFO flower 2022-04-16 12:20:04,106 | 2719366172.py:31 | [(9, 0.7651821970939636), (15, 0.8030887842178345), (17, 0.920634925365448), (18, 0.7991967797279358), (19, 0.5378788113594055), (20, 0.7568627595901489), (21, 0.8607594966888428)]\n",
      "INFO flower 2022-04-16 12:20:04,107 | 2719366172.py:37 | Aggregated accuracy: 0.7776576791490827 +- 0.11118906083350633\n",
      "DEBUG flower 2022-04-16 12:20:04,107 | server.py:265 | fit_round: strategy sampled 7 clients (out of 7)\n",
      "DEBUG flower 2022-04-16 12:20:08,554 | server.py:277 | fit_round received 7 results and 0 failures\n",
      "DEBUG flower 2022-04-16 12:20:08,569 | server.py:211 | evaluate_round: strategy sampled 7 clients (out of 7)\n"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "Saving round 47 aggregated_weights...\n"
     ]
    },
    {
     "name": "stderr",
     "output_type": "stream",
     "text": [
      "DEBUG flower 2022-04-16 12:20:10,287 | server.py:223 | evaluate_round received 7 results and 0 failures\n",
      "INFO flower 2022-04-16 12:20:10,288 | 2719366172.py:15 | round-47-EVALUATION\n",
      "INFO flower 2022-04-16 12:20:10,290 | 2719366172.py:31 | [(9, 0.7651821970939636), (15, 0.8030887842178345), (17, 0.920634925365448), (18, 0.7991967797279358), (19, 0.5378788113594055), (20, 0.7568627595901489), (21, 0.8607594966888428)]\n",
      "INFO flower 2022-04-16 12:20:10,290 | 2719366172.py:37 | Aggregated accuracy: 0.7776576791490827 +- 0.11118906083350631\n",
      "DEBUG flower 2022-04-16 12:20:10,291 | server.py:265 | fit_round: strategy sampled 7 clients (out of 7)\n",
      "DEBUG flower 2022-04-16 12:20:14,781 | server.py:277 | fit_round received 7 results and 0 failures\n",
      "DEBUG flower 2022-04-16 12:20:14,797 | server.py:211 | evaluate_round: strategy sampled 7 clients (out of 7)\n"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "Saving round 48 aggregated_weights...\n"
     ]
    },
    {
     "name": "stderr",
     "output_type": "stream",
     "text": [
      "DEBUG flower 2022-04-16 12:20:16,653 | server.py:223 | evaluate_round received 7 results and 0 failures\n",
      "INFO flower 2022-04-16 12:20:16,653 | 2719366172.py:15 | round-48-EVALUATION\n",
      "INFO flower 2022-04-16 12:20:16,655 | 2719366172.py:31 | [(9, 0.7651821970939636), (15, 0.8030887842178345), (17, 0.920634925365448), (18, 0.7991967797279358), (19, 0.5378788113594055), (20, 0.7568627595901489), (21, 0.8607594966888428)]\n",
      "INFO flower 2022-04-16 12:20:16,656 | 2719366172.py:37 | Aggregated accuracy: 0.7776576791490827 +- 0.11118906083350633\n",
      "DEBUG flower 2022-04-16 12:20:16,656 | server.py:265 | fit_round: strategy sampled 7 clients (out of 7)\n",
      "DEBUG flower 2022-04-16 12:20:21,159 | server.py:277 | fit_round received 7 results and 0 failures\n",
      "DEBUG flower 2022-04-16 12:20:21,175 | server.py:211 | evaluate_round: strategy sampled 7 clients (out of 7)\n"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "Saving round 49 aggregated_weights...\n"
     ]
    },
    {
     "name": "stderr",
     "output_type": "stream",
     "text": [
      "DEBUG flower 2022-04-16 12:20:22,844 | server.py:223 | evaluate_round received 7 results and 0 failures\n",
      "INFO flower 2022-04-16 12:20:22,845 | 2719366172.py:15 | round-49-EVALUATION\n",
      "INFO flower 2022-04-16 12:20:22,847 | 2719366172.py:31 | [(9, 0.7692307829856873), (15, 0.799227774143219), (17, 0.920634925365448), (18, 0.7991967797279358), (19, 0.5416666865348816), (20, 0.7529411911964417), (21, 0.8607594966888428)]\n",
      "INFO flower 2022-04-16 12:20:22,848 | 2719366172.py:37 | Aggregated accuracy: 0.777665376663208 +- 0.10996835415035434\n",
      "DEBUG flower 2022-04-16 12:20:22,848 | server.py:265 | fit_round: strategy sampled 7 clients (out of 7)\n",
      "DEBUG flower 2022-04-16 12:20:27,359 | server.py:277 | fit_round received 7 results and 0 failures\n",
      "DEBUG flower 2022-04-16 12:20:27,375 | server.py:211 | evaluate_round: strategy sampled 7 clients (out of 7)\n"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "Saving round 50 aggregated_weights...\n"
     ]
    },
    {
     "name": "stderr",
     "output_type": "stream",
     "text": [
      "DEBUG flower 2022-04-16 12:20:29,095 | server.py:223 | evaluate_round received 7 results and 0 failures\n",
      "INFO flower 2022-04-16 12:20:29,095 | 2719366172.py:15 | round-50-EVALUATION\n",
      "INFO flower 2022-04-16 12:20:29,098 | 2719366172.py:31 | [(9, 0.7692307829856873), (15, 0.799227774143219), (17, 0.920634925365448), (18, 0.8032128810882568), (19, 0.5416666865348816), (20, 0.7529411911964417), (21, 0.8649789094924927)]\n",
      "INFO flower 2022-04-16 12:20:29,099 | 2719366172.py:37 | Aggregated accuracy: 0.7788418786866325 +- 0.11055036163240879\n",
      "DEBUG flower 2022-04-16 12:20:29,099 | server.py:265 | fit_round: strategy sampled 7 clients (out of 7)\n",
      "DEBUG flower 2022-04-16 12:20:33,591 | server.py:277 | fit_round received 7 results and 0 failures\n",
      "DEBUG flower 2022-04-16 12:20:33,608 | server.py:211 | evaluate_round: strategy sampled 7 clients (out of 7)\n"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "Saving round 51 aggregated_weights...\n"
     ]
    },
    {
     "name": "stderr",
     "output_type": "stream",
     "text": [
      "DEBUG flower 2022-04-16 12:20:35,303 | server.py:223 | evaluate_round received 7 results and 0 failures\n",
      "INFO flower 2022-04-16 12:20:35,303 | 2719366172.py:15 | round-51-EVALUATION\n",
      "INFO flower 2022-04-16 12:20:35,305 | 2719366172.py:31 | [(9, 0.7692307829856873), (15, 0.799227774143219), (17, 0.920634925365448), (18, 0.8032128810882568), (19, 0.5378788113594055), (20, 0.7529411911964417), (21, 0.8649789094924927)]\n",
      "INFO flower 2022-04-16 12:20:35,306 | 2719366172.py:37 | Aggregated accuracy: 0.7783007536615644 +- 0.11171312464706258\n",
      "DEBUG flower 2022-04-16 12:20:35,307 | server.py:265 | fit_round: strategy sampled 7 clients (out of 7)\n",
      "DEBUG flower 2022-04-16 12:20:39,765 | server.py:277 | fit_round received 7 results and 0 failures\n",
      "DEBUG flower 2022-04-16 12:20:39,782 | server.py:211 | evaluate_round: strategy sampled 7 clients (out of 7)\n"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "Saving round 52 aggregated_weights...\n"
     ]
    },
    {
     "name": "stderr",
     "output_type": "stream",
     "text": [
      "DEBUG flower 2022-04-16 12:20:41,608 | server.py:223 | evaluate_round received 7 results and 0 failures\n",
      "INFO flower 2022-04-16 12:20:41,609 | 2719366172.py:15 | round-52-EVALUATION\n",
      "INFO flower 2022-04-16 12:20:41,611 | 2719366172.py:31 | [(9, 0.7692307829856873), (15, 0.799227774143219), (17, 0.920634925365448), (18, 0.8032128810882568), (19, 0.5378788113594055), (20, 0.7529411911964417), (21, 0.8649789094924927)]\n",
      "INFO flower 2022-04-16 12:20:41,612 | 2719366172.py:37 | Aggregated accuracy: 0.7783007536615644 +- 0.1117131246470626\n",
      "DEBUG flower 2022-04-16 12:20:41,612 | server.py:265 | fit_round: strategy sampled 7 clients (out of 7)\n",
      "DEBUG flower 2022-04-16 12:20:46,142 | server.py:277 | fit_round received 7 results and 0 failures\n",
      "DEBUG flower 2022-04-16 12:20:46,158 | server.py:211 | evaluate_round: strategy sampled 7 clients (out of 7)\n"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "Saving round 53 aggregated_weights...\n"
     ]
    },
    {
     "name": "stderr",
     "output_type": "stream",
     "text": [
      "DEBUG flower 2022-04-16 12:20:47,896 | server.py:223 | evaluate_round received 7 results and 0 failures\n",
      "INFO flower 2022-04-16 12:20:47,897 | 2719366172.py:15 | round-53-EVALUATION\n",
      "INFO flower 2022-04-16 12:20:47,899 | 2719366172.py:31 | [(9, 0.7692307829856873), (15, 0.799227774143219), (17, 0.920634925365448), (18, 0.8072289228439331), (19, 0.5416666865348816), (20, 0.7490196228027344), (21, 0.8649789094924927)]\n",
      "INFO flower 2022-04-16 12:20:47,900 | 2719366172.py:37 | Aggregated accuracy: 0.7788553748811994 +- 0.11082810098515652\n",
      "DEBUG flower 2022-04-16 12:20:47,900 | server.py:265 | fit_round: strategy sampled 7 clients (out of 7)\n",
      "DEBUG flower 2022-04-16 12:20:52,455 | server.py:277 | fit_round received 7 results and 0 failures\n",
      "DEBUG flower 2022-04-16 12:20:52,471 | server.py:211 | evaluate_round: strategy sampled 7 clients (out of 7)\n"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "Saving round 54 aggregated_weights...\n"
     ]
    },
    {
     "name": "stderr",
     "output_type": "stream",
     "text": [
      "DEBUG flower 2022-04-16 12:20:54,272 | server.py:223 | evaluate_round received 7 results and 0 failures\n",
      "INFO flower 2022-04-16 12:20:54,272 | 2719366172.py:15 | round-54-EVALUATION\n",
      "INFO flower 2022-04-16 12:20:54,274 | 2719366172.py:31 | [(9, 0.7692307829856873), (15, 0.799227774143219), (17, 0.9166666865348816), (18, 0.8072289228439331), (19, 0.5416666865348816), (20, 0.7490196228027344), (21, 0.8649789094924927)]\n",
      "INFO flower 2022-04-16 12:20:54,274 | 2719366172.py:37 | Aggregated accuracy: 0.7782884836196899 +- 0.11010925930969558\n",
      "DEBUG flower 2022-04-16 12:20:54,275 | server.py:265 | fit_round: strategy sampled 7 clients (out of 7)\n",
      "DEBUG flower 2022-04-16 12:20:58,757 | server.py:277 | fit_round received 7 results and 0 failures\n",
      "DEBUG flower 2022-04-16 12:20:58,775 | server.py:211 | evaluate_round: strategy sampled 7 clients (out of 7)\n"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "Saving round 55 aggregated_weights...\n"
     ]
    },
    {
     "name": "stderr",
     "output_type": "stream",
     "text": [
      "DEBUG flower 2022-04-16 12:21:00,530 | server.py:223 | evaluate_round received 7 results and 0 failures\n",
      "INFO flower 2022-04-16 12:21:00,531 | 2719366172.py:15 | round-55-EVALUATION\n",
      "INFO flower 2022-04-16 12:21:00,533 | 2719366172.py:31 | [(9, 0.7651821970939636), (15, 0.799227774143219), (17, 0.9126983880996704), (18, 0.8072289228439331), (19, 0.5416666865348816), (20, 0.7450980544090271), (21, 0.8649789094924927)]\n",
      "INFO flower 2022-04-16 12:21:00,534 | 2719366172.py:37 | Aggregated accuracy: 0.7765829903738839 +- 0.10960979395323374\n",
      "DEBUG flower 2022-04-16 12:21:00,534 | server.py:265 | fit_round: strategy sampled 7 clients (out of 7)\n",
      "DEBUG flower 2022-04-16 12:21:05,026 | server.py:277 | fit_round received 7 results and 0 failures\n",
      "DEBUG flower 2022-04-16 12:21:05,043 | server.py:211 | evaluate_round: strategy sampled 7 clients (out of 7)\n"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "Saving round 56 aggregated_weights...\n"
     ]
    },
    {
     "name": "stderr",
     "output_type": "stream",
     "text": [
      "DEBUG flower 2022-04-16 12:21:06,950 | server.py:223 | evaluate_round received 7 results and 0 failures\n",
      "INFO flower 2022-04-16 12:21:06,951 | 2719366172.py:15 | round-56-EVALUATION\n",
      "INFO flower 2022-04-16 12:21:06,953 | 2719366172.py:31 | [(9, 0.76113361120224), (15, 0.799227774143219), (17, 0.9126983880996704), (18, 0.8072289228439331), (19, 0.5416666865348816), (20, 0.7450980544090271), (21, 0.8649789094924927)]\n",
      "INFO flower 2022-04-16 12:21:06,954 | 2719366172.py:37 | Aggregated accuracy: 0.7760046209607806 +- 0.10967908523403574\n",
      "DEBUG flower 2022-04-16 12:21:06,954 | server.py:265 | fit_round: strategy sampled 7 clients (out of 7)\n",
      "DEBUG flower 2022-04-16 12:21:11,494 | server.py:277 | fit_round received 7 results and 0 failures\n",
      "DEBUG flower 2022-04-16 12:21:11,511 | server.py:211 | evaluate_round: strategy sampled 7 clients (out of 7)\n"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "Saving round 57 aggregated_weights...\n"
     ]
    },
    {
     "name": "stderr",
     "output_type": "stream",
     "text": [
      "DEBUG flower 2022-04-16 12:21:13,274 | server.py:223 | evaluate_round received 7 results and 0 failures\n",
      "INFO flower 2022-04-16 12:21:13,274 | 2719366172.py:15 | round-57-EVALUATION\n",
      "INFO flower 2022-04-16 12:21:13,277 | 2719366172.py:31 | [(9, 0.7570850253105164), (15, 0.799227774143219), (17, 0.9126983880996704), (18, 0.8072289228439331), (19, 0.5416666865348816), (20, 0.7450980544090271), (21, 0.8649789094924927)]\n",
      "INFO flower 2022-04-16 12:21:13,278 | 2719366172.py:37 | Aggregated accuracy: 0.7754262515476772 +- 0.10976661914815251\n",
      "DEBUG flower 2022-04-16 12:21:13,278 | server.py:265 | fit_round: strategy sampled 7 clients (out of 7)\n",
      "DEBUG flower 2022-04-16 12:21:17,779 | server.py:277 | fit_round received 7 results and 0 failures\n",
      "DEBUG flower 2022-04-16 12:21:17,795 | server.py:211 | evaluate_round: strategy sampled 7 clients (out of 7)\n"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "Saving round 58 aggregated_weights...\n"
     ]
    },
    {
     "name": "stderr",
     "output_type": "stream",
     "text": [
      "DEBUG flower 2022-04-16 12:21:19,541 | server.py:223 | evaluate_round received 7 results and 0 failures\n",
      "INFO flower 2022-04-16 12:21:19,541 | 2719366172.py:15 | round-58-EVALUATION\n",
      "INFO flower 2022-04-16 12:21:19,543 | 2719366172.py:31 | [(9, 0.7570850253105164), (15, 0.8030887842178345), (17, 0.9126983880996704), (18, 0.8112449645996094), (19, 0.5416666865348816), (20, 0.7450980544090271), (21, 0.8649789094924927)]\n",
      "INFO flower 2022-04-16 12:21:19,544 | 2719366172.py:37 | Aggregated accuracy: 0.7765515446662903 +- 0.11006646323359727\n",
      "DEBUG flower 2022-04-16 12:21:19,544 | server.py:265 | fit_round: strategy sampled 7 clients (out of 7)\n",
      "DEBUG flower 2022-04-16 12:21:24,016 | server.py:277 | fit_round received 7 results and 0 failures\n",
      "DEBUG flower 2022-04-16 12:21:24,032 | server.py:211 | evaluate_round: strategy sampled 7 clients (out of 7)\n"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "Saving round 59 aggregated_weights...\n"
     ]
    },
    {
     "name": "stderr",
     "output_type": "stream",
     "text": [
      "DEBUG flower 2022-04-16 12:21:25,776 | server.py:223 | evaluate_round received 7 results and 0 failures\n",
      "INFO flower 2022-04-16 12:21:25,776 | 2719366172.py:15 | round-59-EVALUATION\n",
      "INFO flower 2022-04-16 12:21:25,778 | 2719366172.py:31 | [(9, 0.7570850253105164), (15, 0.8030887842178345), (17, 0.908730149269104), (18, 0.8112449645996094), (19, 0.5416666865348816), (20, 0.7450980544090271), (21, 0.8649789094924927)]\n",
      "INFO flower 2022-04-16 12:21:25,779 | 2719366172.py:37 | Aggregated accuracy: 0.7759846534047808 +- 0.10937181360532569\n",
      "DEBUG flower 2022-04-16 12:21:25,780 | server.py:265 | fit_round: strategy sampled 7 clients (out of 7)\n",
      "DEBUG flower 2022-04-16 12:21:30,353 | server.py:277 | fit_round received 7 results and 0 failures\n",
      "DEBUG flower 2022-04-16 12:21:30,369 | server.py:211 | evaluate_round: strategy sampled 7 clients (out of 7)\n"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "Saving round 60 aggregated_weights...\n"
     ]
    },
    {
     "name": "stderr",
     "output_type": "stream",
     "text": [
      "DEBUG flower 2022-04-16 12:21:32,125 | server.py:223 | evaluate_round received 7 results and 0 failures\n",
      "INFO flower 2022-04-16 12:21:32,125 | 2719366172.py:15 | round-60-EVALUATION\n",
      "INFO flower 2022-04-16 12:21:32,128 | 2719366172.py:31 | [(9, 0.76113361120224), (15, 0.8030887842178345), (17, 0.908730149269104), (18, 0.8112449645996094), (19, 0.5416666865348816), (20, 0.7411764860153198), (21, 0.8649789094924927)]\n",
      "INFO flower 2022-04-16 12:21:32,128 | 2719366172.py:37 | Aggregated accuracy: 0.7760027987616402 +- 0.10945079586367129\n",
      "DEBUG flower 2022-04-16 12:21:32,129 | server.py:265 | fit_round: strategy sampled 7 clients (out of 7)\n",
      "DEBUG flower 2022-04-16 12:21:36,627 | server.py:277 | fit_round received 7 results and 0 failures\n",
      "DEBUG flower 2022-04-16 12:21:36,644 | server.py:211 | evaluate_round: strategy sampled 7 clients (out of 7)\n"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "Saving round 61 aggregated_weights...\n"
     ]
    },
    {
     "name": "stderr",
     "output_type": "stream",
     "text": [
      "DEBUG flower 2022-04-16 12:21:38,546 | server.py:223 | evaluate_round received 7 results and 0 failures\n",
      "INFO flower 2022-04-16 12:21:38,547 | 2719366172.py:15 | round-61-EVALUATION\n",
      "INFO flower 2022-04-16 12:21:38,549 | 2719366172.py:31 | [(9, 0.76113361120224), (15, 0.8030887842178345), (17, 0.908730149269104), (18, 0.8112449645996094), (19, 0.5416666865348816), (20, 0.7411764860153198), (21, 0.8691983222961426)]\n",
      "INFO flower 2022-04-16 12:21:38,549 | 2719366172.py:37 | Aggregated accuracy: 0.7766055720193046 +- 0.10994963196405454\n",
      "DEBUG flower 2022-04-16 12:21:38,550 | server.py:265 | fit_round: strategy sampled 7 clients (out of 7)\n",
      "DEBUG flower 2022-04-16 12:21:42,924 | server.py:277 | fit_round received 7 results and 0 failures\n",
      "DEBUG flower 2022-04-16 12:21:42,941 | server.py:211 | evaluate_round: strategy sampled 7 clients (out of 7)\n"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "Saving round 62 aggregated_weights...\n"
     ]
    },
    {
     "name": "stderr",
     "output_type": "stream",
     "text": [
      "DEBUG flower 2022-04-16 12:21:44,833 | server.py:223 | evaluate_round received 7 results and 0 failures\n",
      "INFO flower 2022-04-16 12:21:44,833 | 2719366172.py:15 | round-62-EVALUATION\n",
      "INFO flower 2022-04-16 12:21:44,835 | 2719366172.py:31 | [(9, 0.76113361120224), (15, 0.8030887842178345), (17, 0.908730149269104), (18, 0.8112449645996094), (19, 0.5416666865348816), (20, 0.7411764860153198), (21, 0.8691983222961426)]\n",
      "INFO flower 2022-04-16 12:21:44,836 | 2719366172.py:37 | Aggregated accuracy: 0.7766055720193046 +- 0.10994963196405451\n",
      "DEBUG flower 2022-04-16 12:21:44,837 | server.py:265 | fit_round: strategy sampled 7 clients (out of 7)\n",
      "DEBUG flower 2022-04-16 12:21:49,408 | server.py:277 | fit_round received 7 results and 0 failures\n",
      "DEBUG flower 2022-04-16 12:21:49,423 | server.py:211 | evaluate_round: strategy sampled 7 clients (out of 7)\n"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "Saving round 63 aggregated_weights...\n"
     ]
    },
    {
     "name": "stderr",
     "output_type": "stream",
     "text": [
      "DEBUG flower 2022-04-16 12:21:51,169 | server.py:223 | evaluate_round received 7 results and 0 failures\n",
      "INFO flower 2022-04-16 12:21:51,169 | 2719366172.py:15 | round-63-EVALUATION\n",
      "INFO flower 2022-04-16 12:21:51,172 | 2719366172.py:31 | [(9, 0.7570850253105164), (15, 0.8030887842178345), (17, 0.908730149269104), (18, 0.8152610659599304), (19, 0.5416666865348816), (20, 0.7372549176216125), (21, 0.8691983222961426)]\n",
      "INFO flower 2022-04-16 12:21:51,172 | 2719366172.py:37 | Aggregated accuracy: 0.7760407073157174 +- 0.1104209485886229\n",
      "DEBUG flower 2022-04-16 12:21:51,173 | server.py:265 | fit_round: strategy sampled 7 clients (out of 7)\n",
      "DEBUG flower 2022-04-16 12:21:55,801 | server.py:277 | fit_round received 7 results and 0 failures\n",
      "DEBUG flower 2022-04-16 12:21:55,817 | server.py:211 | evaluate_round: strategy sampled 7 clients (out of 7)\n"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "Saving round 64 aggregated_weights...\n"
     ]
    },
    {
     "name": "stderr",
     "output_type": "stream",
     "text": [
      "DEBUG flower 2022-04-16 12:21:57,562 | server.py:223 | evaluate_round received 7 results and 0 failures\n",
      "INFO flower 2022-04-16 12:21:57,562 | 2719366172.py:15 | round-64-EVALUATION\n",
      "INFO flower 2022-04-16 12:21:57,565 | 2719366172.py:31 | [(9, 0.7570850253105164), (15, 0.8030887842178345), (17, 0.908730149269104), (18, 0.8192771077156067), (19, 0.5416666865348816), (20, 0.7333333492279053), (21, 0.8734177350997925)]\n",
      "INFO flower 2022-04-16 12:21:57,565 | 2719366172.py:37 | Aggregated accuracy: 0.7766569767679486 +- 0.11135626080637276\n",
      "DEBUG flower 2022-04-16 12:21:57,566 | server.py:265 | fit_round: strategy sampled 7 clients (out of 7)\n",
      "DEBUG flower 2022-04-16 12:22:01,997 | server.py:277 | fit_round received 7 results and 0 failures\n",
      "DEBUG flower 2022-04-16 12:22:02,014 | server.py:211 | evaluate_round: strategy sampled 7 clients (out of 7)\n"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "Saving round 65 aggregated_weights...\n"
     ]
    },
    {
     "name": "stderr",
     "output_type": "stream",
     "text": [
      "DEBUG flower 2022-04-16 12:22:03,690 | server.py:223 | evaluate_round received 7 results and 0 failures\n",
      "INFO flower 2022-04-16 12:22:03,690 | 2719366172.py:15 | round-65-EVALUATION\n",
      "INFO flower 2022-04-16 12:22:03,693 | 2719366172.py:31 | [(9, 0.76113361120224), (15, 0.8030887842178345), (17, 0.908730149269104), (18, 0.823293149471283), (19, 0.5416666865348816), (20, 0.7333333492279053), (21, 0.8734177350997925)]\n",
      "INFO flower 2022-04-16 12:22:03,693 | 2719366172.py:37 | Aggregated accuracy: 0.777809066431863 +- 0.11148901112302935\n",
      "DEBUG flower 2022-04-16 12:22:03,693 | server.py:265 | fit_round: strategy sampled 7 clients (out of 7)\n",
      "DEBUG flower 2022-04-16 12:22:08,254 | server.py:277 | fit_round received 7 results and 0 failures\n",
      "DEBUG flower 2022-04-16 12:22:08,270 | server.py:211 | evaluate_round: strategy sampled 7 clients (out of 7)\n"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "Saving round 66 aggregated_weights...\n"
     ]
    },
    {
     "name": "stderr",
     "output_type": "stream",
     "text": [
      "DEBUG flower 2022-04-16 12:22:10,184 | server.py:223 | evaluate_round received 7 results and 0 failures\n",
      "INFO flower 2022-04-16 12:22:10,185 | 2719366172.py:15 | round-66-EVALUATION\n",
      "INFO flower 2022-04-16 12:22:10,187 | 2719366172.py:31 | [(9, 0.76113361120224), (15, 0.80694979429245), (17, 0.908730149269104), (18, 0.823293149471283), (19, 0.5454545617103577), (20, 0.7333333492279053), (21, 0.8734177350997925)]\n",
      "INFO flower 2022-04-16 12:22:10,188 | 2719366172.py:37 | Aggregated accuracy: 0.7789017643247332 +- 0.11047672635150248\n",
      "DEBUG flower 2022-04-16 12:22:10,188 | server.py:265 | fit_round: strategy sampled 7 clients (out of 7)\n",
      "DEBUG flower 2022-04-16 12:22:14,600 | server.py:277 | fit_round received 7 results and 0 failures\n",
      "DEBUG flower 2022-04-16 12:22:14,618 | server.py:211 | evaluate_round: strategy sampled 7 clients (out of 7)\n"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "Saving round 67 aggregated_weights...\n"
     ]
    },
    {
     "name": "stderr",
     "output_type": "stream",
     "text": [
      "DEBUG flower 2022-04-16 12:22:16,473 | server.py:223 | evaluate_round received 7 results and 0 failures\n",
      "INFO flower 2022-04-16 12:22:16,473 | 2719366172.py:15 | round-67-EVALUATION\n",
      "INFO flower 2022-04-16 12:22:16,475 | 2719366172.py:31 | [(9, 0.76113361120224), (15, 0.80694979429245), (17, 0.908730149269104), (18, 0.823293149471283), (19, 0.5454545617103577), (20, 0.7333333492279053), (21, 0.8734177350997925)]\n",
      "INFO flower 2022-04-16 12:22:16,476 | 2719366172.py:37 | Aggregated accuracy: 0.7789017643247332 +- 0.11047672635150248\n",
      "DEBUG flower 2022-04-16 12:22:16,477 | server.py:265 | fit_round: strategy sampled 7 clients (out of 7)\n",
      "DEBUG flower 2022-04-16 12:22:20,989 | server.py:277 | fit_round received 7 results and 0 failures\n",
      "DEBUG flower 2022-04-16 12:22:21,005 | server.py:211 | evaluate_round: strategy sampled 7 clients (out of 7)\n"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "Saving round 68 aggregated_weights...\n"
     ]
    },
    {
     "name": "stderr",
     "output_type": "stream",
     "text": [
      "DEBUG flower 2022-04-16 12:22:22,745 | server.py:223 | evaluate_round received 7 results and 0 failures\n",
      "INFO flower 2022-04-16 12:22:22,746 | 2719366172.py:15 | round-68-EVALUATION\n",
      "INFO flower 2022-04-16 12:22:22,748 | 2719366172.py:31 | [(9, 0.76113361120224), (15, 0.8030887842178345), (17, 0.908730149269104), (18, 0.823293149471283), (19, 0.5454545617103577), (20, 0.7333333492279053), (21, 0.8734177350997925)]\n",
      "INFO flower 2022-04-16 12:22:22,749 | 2719366172.py:37 | Aggregated accuracy: 0.778350191456931 +- 0.11034487480832421\n",
      "DEBUG flower 2022-04-16 12:22:22,749 | server.py:265 | fit_round: strategy sampled 7 clients (out of 7)\n",
      "DEBUG flower 2022-04-16 12:22:27,344 | server.py:277 | fit_round received 7 results and 0 failures\n",
      "DEBUG flower 2022-04-16 12:22:27,360 | server.py:211 | evaluate_round: strategy sampled 7 clients (out of 7)\n"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "Saving round 69 aggregated_weights...\n"
     ]
    },
    {
     "name": "stderr",
     "output_type": "stream",
     "text": [
      "DEBUG flower 2022-04-16 12:22:29,058 | server.py:223 | evaluate_round received 7 results and 0 failures\n",
      "INFO flower 2022-04-16 12:22:29,059 | 2719366172.py:15 | round-69-EVALUATION\n",
      "INFO flower 2022-04-16 12:22:29,061 | 2719366172.py:31 | [(9, 0.76113361120224), (15, 0.8030887842178345), (17, 0.9047619104385376), (18, 0.823293149471283), (19, 0.5454545617103577), (20, 0.7333333492279053), (21, 0.8734177350997925)]\n",
      "INFO flower 2022-04-16 12:22:29,062 | 2719366172.py:37 | Aggregated accuracy: 0.7777833001954215 +- 0.10968179918819532\n",
      "DEBUG flower 2022-04-16 12:22:29,062 | server.py:265 | fit_round: strategy sampled 7 clients (out of 7)\n",
      "DEBUG flower 2022-04-16 12:22:33,551 | server.py:277 | fit_round received 7 results and 0 failures\n",
      "DEBUG flower 2022-04-16 12:22:33,567 | server.py:211 | evaluate_round: strategy sampled 7 clients (out of 7)\n"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "Saving round 70 aggregated_weights...\n"
     ]
    },
    {
     "name": "stderr",
     "output_type": "stream",
     "text": [
      "DEBUG flower 2022-04-16 12:22:35,286 | server.py:223 | evaluate_round received 7 results and 0 failures\n",
      "INFO flower 2022-04-16 12:22:35,287 | 2719366172.py:15 | round-70-EVALUATION\n",
      "INFO flower 2022-04-16 12:22:35,289 | 2719366172.py:31 | [(9, 0.7570850253105164), (15, 0.8030887842178345), (17, 0.9047619104385376), (18, 0.823293149471283), (19, 0.5454545617103577), (20, 0.7333333492279053), (21, 0.8734177350997925)]\n",
      "INFO flower 2022-04-16 12:22:35,289 | 2719366172.py:37 | Aggregated accuracy: 0.7772049307823181 +- 0.10977870231484049\n",
      "DEBUG flower 2022-04-16 12:22:35,290 | server.py:265 | fit_round: strategy sampled 7 clients (out of 7)\n",
      "DEBUG flower 2022-04-16 12:22:39,775 | server.py:277 | fit_round received 7 results and 0 failures\n",
      "DEBUG flower 2022-04-16 12:22:39,791 | server.py:211 | evaluate_round: strategy sampled 7 clients (out of 7)\n"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "Saving round 71 aggregated_weights...\n"
     ]
    },
    {
     "name": "stderr",
     "output_type": "stream",
     "text": [
      "DEBUG flower 2022-04-16 12:22:41,674 | server.py:223 | evaluate_round received 7 results and 0 failures\n",
      "INFO flower 2022-04-16 12:22:41,675 | 2719366172.py:15 | round-71-EVALUATION\n",
      "INFO flower 2022-04-16 12:22:41,677 | 2719366172.py:31 | [(9, 0.76113361120224), (15, 0.8030887842178345), (17, 0.9047619104385376), (18, 0.823293149471283), (19, 0.5454545617103577), (20, 0.7333333492279053), (21, 0.8734177350997925)]\n",
      "INFO flower 2022-04-16 12:22:41,678 | 2719366172.py:37 | Aggregated accuracy: 0.7777833001954215 +- 0.10968179918819532\n",
      "DEBUG flower 2022-04-16 12:22:41,678 | server.py:265 | fit_round: strategy sampled 7 clients (out of 7)\n",
      "DEBUG flower 2022-04-16 12:22:46,054 | server.py:277 | fit_round received 7 results and 0 failures\n",
      "DEBUG flower 2022-04-16 12:22:46,070 | server.py:211 | evaluate_round: strategy sampled 7 clients (out of 7)\n"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "Saving round 72 aggregated_weights...\n"
     ]
    },
    {
     "name": "stderr",
     "output_type": "stream",
     "text": [
      "DEBUG flower 2022-04-16 12:22:47,967 | server.py:223 | evaluate_round received 7 results and 0 failures\n",
      "INFO flower 2022-04-16 12:22:47,967 | 2719366172.py:15 | round-72-EVALUATION\n",
      "INFO flower 2022-04-16 12:22:47,970 | 2719366172.py:31 | [(9, 0.7570850253105164), (15, 0.80694979429245), (17, 0.908730149269104), (18, 0.823293149471283), (19, 0.5416666865348816), (20, 0.7333333492279053), (21, 0.8691983222961426)]\n",
      "INFO flower 2022-04-16 12:22:47,970 | 2719366172.py:37 | Aggregated accuracy: 0.7771794966288975 +- 0.111213009405081\n",
      "DEBUG flower 2022-04-16 12:22:47,971 | server.py:265 | fit_round: strategy sampled 7 clients (out of 7)\n",
      "DEBUG flower 2022-04-16 12:22:52,508 | server.py:277 | fit_round received 7 results and 0 failures\n",
      "DEBUG flower 2022-04-16 12:22:52,524 | server.py:211 | evaluate_round: strategy sampled 7 clients (out of 7)\n"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "Saving round 73 aggregated_weights...\n"
     ]
    },
    {
     "name": "stderr",
     "output_type": "stream",
     "text": [
      "DEBUG flower 2022-04-16 12:22:54,343 | server.py:223 | evaluate_round received 7 results and 0 failures\n",
      "INFO flower 2022-04-16 12:22:54,344 | 2719366172.py:15 | round-73-EVALUATION\n",
      "INFO flower 2022-04-16 12:22:54,346 | 2719366172.py:31 | [(9, 0.76113361120224), (15, 0.80694979429245), (17, 0.908730149269104), (18, 0.823293149471283), (19, 0.5378788113594055), (20, 0.7372549176216125), (21, 0.8691983222961426)]\n",
      "INFO flower 2022-04-16 12:22:54,347 | 2719366172.py:37 | Aggregated accuracy: 0.7777769650731768 +- 0.1120583647208499\n",
      "DEBUG flower 2022-04-16 12:22:54,347 | server.py:265 | fit_round: strategy sampled 7 clients (out of 7)\n",
      "DEBUG flower 2022-04-16 12:22:58,739 | server.py:277 | fit_round received 7 results and 0 failures\n",
      "DEBUG flower 2022-04-16 12:22:58,755 | server.py:211 | evaluate_round: strategy sampled 7 clients (out of 7)\n"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "Saving round 74 aggregated_weights...\n"
     ]
    },
    {
     "name": "stderr",
     "output_type": "stream",
     "text": [
      "DEBUG flower 2022-04-16 12:23:00,509 | server.py:223 | evaluate_round received 7 results and 0 failures\n",
      "INFO flower 2022-04-16 12:23:00,510 | 2719366172.py:15 | round-74-EVALUATION\n",
      "INFO flower 2022-04-16 12:23:00,512 | 2719366172.py:31 | [(9, 0.76113361120224), (15, 0.80694979429245), (17, 0.908730149269104), (18, 0.823293149471283), (19, 0.5378788113594055), (20, 0.7372549176216125), (21, 0.8691983222961426)]\n",
      "INFO flower 2022-04-16 12:23:00,513 | 2719366172.py:37 | Aggregated accuracy: 0.7777769650731768 +- 0.1120583647208499\n",
      "DEBUG flower 2022-04-16 12:23:00,513 | server.py:265 | fit_round: strategy sampled 7 clients (out of 7)\n",
      "DEBUG flower 2022-04-16 12:23:05,184 | server.py:277 | fit_round received 7 results and 0 failures\n",
      "DEBUG flower 2022-04-16 12:23:05,201 | server.py:211 | evaluate_round: strategy sampled 7 clients (out of 7)\n"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "Saving round 75 aggregated_weights...\n"
     ]
    },
    {
     "name": "stderr",
     "output_type": "stream",
     "text": [
      "DEBUG flower 2022-04-16 12:23:06,772 | server.py:223 | evaluate_round received 7 results and 0 failures\n",
      "INFO flower 2022-04-16 12:23:06,773 | 2719366172.py:15 | round-75-EVALUATION\n",
      "INFO flower 2022-04-16 12:23:06,775 | 2719366172.py:31 | [(9, 0.76113361120224), (15, 0.80694979429245), (17, 0.908730149269104), (18, 0.823293149471283), (19, 0.5378788113594055), (20, 0.7372549176216125), (21, 0.8691983222961426)]\n",
      "INFO flower 2022-04-16 12:23:06,776 | 2719366172.py:37 | Aggregated accuracy: 0.7777769650731768 +- 0.1120583647208499\n",
      "DEBUG flower 2022-04-16 12:23:06,776 | server.py:265 | fit_round: strategy sampled 7 clients (out of 7)\n",
      "DEBUG flower 2022-04-16 12:23:10,979 | server.py:277 | fit_round received 7 results and 0 failures\n",
      "DEBUG flower 2022-04-16 12:23:10,997 | server.py:211 | evaluate_round: strategy sampled 7 clients (out of 7)\n"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "Saving round 76 aggregated_weights...\n"
     ]
    },
    {
     "name": "stderr",
     "output_type": "stream",
     "text": [
      "DEBUG flower 2022-04-16 12:23:13,002 | server.py:223 | evaluate_round received 7 results and 0 failures\n",
      "INFO flower 2022-04-16 12:23:13,002 | 2719366172.py:15 | round-76-EVALUATION\n",
      "INFO flower 2022-04-16 12:23:13,005 | 2719366172.py:31 | [(9, 0.76113361120224), (15, 0.80694979429245), (17, 0.908730149269104), (18, 0.823293149471283), (19, 0.5378788113594055), (20, 0.7411764860153198), (21, 0.8691983222961426)]\n",
      "INFO flower 2022-04-16 12:23:13,005 | 2719366172.py:37 | Aggregated accuracy: 0.7783371891294207 +- 0.11186401279360998\n",
      "DEBUG flower 2022-04-16 12:23:13,006 | server.py:265 | fit_round: strategy sampled 7 clients (out of 7)\n",
      "DEBUG flower 2022-04-16 12:23:17,942 | server.py:277 | fit_round received 7 results and 0 failures\n",
      "DEBUG flower 2022-04-16 12:23:17,965 | server.py:211 | evaluate_round: strategy sampled 7 clients (out of 7)\n"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "Saving round 77 aggregated_weights...\n"
     ]
    },
    {
     "name": "stderr",
     "output_type": "stream",
     "text": [
      "DEBUG flower 2022-04-16 12:23:19,972 | server.py:223 | evaluate_round received 7 results and 0 failures\n",
      "INFO flower 2022-04-16 12:23:19,973 | 2719366172.py:15 | round-77-EVALUATION\n",
      "INFO flower 2022-04-16 12:23:19,976 | 2719366172.py:31 | [(9, 0.76113361120224), (15, 0.80694979429245), (17, 0.908730149269104), (18, 0.823293149471283), (19, 0.5378788113594055), (20, 0.7411764860153198), (21, 0.8691983222961426)]\n",
      "INFO flower 2022-04-16 12:23:19,976 | 2719366172.py:37 | Aggregated accuracy: 0.7783371891294207 +- 0.11186401279360998\n",
      "DEBUG flower 2022-04-16 12:23:19,977 | server.py:265 | fit_round: strategy sampled 7 clients (out of 7)\n",
      "DEBUG flower 2022-04-16 12:23:24,723 | server.py:277 | fit_round received 7 results and 0 failures\n",
      "DEBUG flower 2022-04-16 12:23:24,742 | server.py:211 | evaluate_round: strategy sampled 7 clients (out of 7)\n"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "Saving round 78 aggregated_weights...\n"
     ]
    },
    {
     "name": "stderr",
     "output_type": "stream",
     "text": [
      "DEBUG flower 2022-04-16 12:23:26,426 | server.py:223 | evaluate_round received 7 results and 0 failures\n",
      "INFO flower 2022-04-16 12:23:26,426 | 2719366172.py:15 | round-78-EVALUATION\n",
      "INFO flower 2022-04-16 12:23:26,429 | 2719366172.py:31 | [(9, 0.76113361120224), (15, 0.80694979429245), (17, 0.908730149269104), (18, 0.827309250831604), (19, 0.5340909361839294), (20, 0.7411764860153198), (21, 0.8691983222961426)]\n",
      "INFO flower 2022-04-16 12:23:26,429 | 2719366172.py:37 | Aggregated accuracy: 0.7783697928701129 +- 0.11326840384188859\n",
      "DEBUG flower 2022-04-16 12:23:26,429 | server.py:265 | fit_round: strategy sampled 7 clients (out of 7)\n",
      "DEBUG flower 2022-04-16 12:23:30,925 | server.py:277 | fit_round received 7 results and 0 failures\n",
      "DEBUG flower 2022-04-16 12:23:30,941 | server.py:211 | evaluate_round: strategy sampled 7 clients (out of 7)\n"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "Saving round 79 aggregated_weights...\n"
     ]
    },
    {
     "name": "stderr",
     "output_type": "stream",
     "text": [
      "DEBUG flower 2022-04-16 12:23:32,624 | server.py:223 | evaluate_round received 7 results and 0 failures\n",
      "INFO flower 2022-04-16 12:23:32,624 | 2719366172.py:15 | round-79-EVALUATION\n",
      "INFO flower 2022-04-16 12:23:32,627 | 2719366172.py:31 | [(9, 0.76113361120224), (15, 0.80694979429245), (17, 0.908730149269104), (18, 0.827309250831604), (19, 0.5378788113594055), (20, 0.7411764860153198), (21, 0.8691983222961426)]\n",
      "INFO flower 2022-04-16 12:23:32,627 | 2719366172.py:37 | Aggregated accuracy: 0.7789109178951809 +- 0.11210315518195685\n",
      "DEBUG flower 2022-04-16 12:23:32,628 | server.py:265 | fit_round: strategy sampled 7 clients (out of 7)\n",
      "DEBUG flower 2022-04-16 12:23:36,813 | server.py:277 | fit_round received 7 results and 0 failures\n",
      "DEBUG flower 2022-04-16 12:23:36,830 | server.py:211 | evaluate_round: strategy sampled 7 clients (out of 7)\n"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "Saving round 80 aggregated_weights...\n"
     ]
    },
    {
     "name": "stderr",
     "output_type": "stream",
     "text": [
      "DEBUG flower 2022-04-16 12:23:38,438 | server.py:223 | evaluate_round received 7 results and 0 failures\n",
      "INFO flower 2022-04-16 12:23:38,438 | 2719366172.py:15 | round-80-EVALUATION\n",
      "INFO flower 2022-04-16 12:23:38,440 | 2719366172.py:31 | [(9, 0.76113361120224), (15, 0.8108108043670654), (17, 0.908730149269104), (18, 0.827309250831604), (19, 0.5378788113594055), (20, 0.7411764860153198), (21, 0.8691983222961426)]\n",
      "INFO flower 2022-04-16 12:23:38,441 | 2719366172.py:37 | Aggregated accuracy: 0.779462490762983 +- 0.11224915930397723\n",
      "DEBUG flower 2022-04-16 12:23:38,441 | server.py:265 | fit_round: strategy sampled 7 clients (out of 7)\n",
      "DEBUG flower 2022-04-16 12:23:42,596 | server.py:277 | fit_round received 7 results and 0 failures\n",
      "DEBUG flower 2022-04-16 12:23:42,613 | server.py:211 | evaluate_round: strategy sampled 7 clients (out of 7)\n"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "Saving round 81 aggregated_weights...\n"
     ]
    },
    {
     "name": "stderr",
     "output_type": "stream",
     "text": [
      "DEBUG flower 2022-04-16 12:23:44,347 | server.py:223 | evaluate_round received 7 results and 0 failures\n",
      "INFO flower 2022-04-16 12:23:44,348 | 2719366172.py:15 | round-81-EVALUATION\n",
      "INFO flower 2022-04-16 12:23:44,350 | 2719366172.py:31 | [(9, 0.76113361120224), (15, 0.8108108043670654), (17, 0.908730149269104), (18, 0.827309250831604), (19, 0.5378788113594055), (20, 0.7411764860153198), (21, 0.8649789094924927)]\n",
      "INFO flower 2022-04-16 12:23:44,350 | 2719366172.py:37 | Aggregated accuracy: 0.7788597175053188 +- 0.1117759950036039\n",
      "DEBUG flower 2022-04-16 12:23:44,351 | server.py:265 | fit_round: strategy sampled 7 clients (out of 7)\n",
      "DEBUG flower 2022-04-16 12:23:48,487 | server.py:277 | fit_round received 7 results and 0 failures\n",
      "DEBUG flower 2022-04-16 12:23:48,505 | server.py:211 | evaluate_round: strategy sampled 7 clients (out of 7)\n"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "Saving round 82 aggregated_weights...\n"
     ]
    },
    {
     "name": "stderr",
     "output_type": "stream",
     "text": [
      "DEBUG flower 2022-04-16 12:23:50,446 | server.py:223 | evaluate_round received 7 results and 0 failures\n",
      "INFO flower 2022-04-16 12:23:50,447 | 2719366172.py:15 | round-82-EVALUATION\n",
      "INFO flower 2022-04-16 12:23:50,450 | 2719366172.py:31 | [(9, 0.76113361120224), (15, 0.8108108043670654), (17, 0.908730149269104), (18, 0.827309250831604), (19, 0.5378788113594055), (20, 0.7411764860153198), (21, 0.8649789094924927)]\n",
      "INFO flower 2022-04-16 12:23:50,450 | 2719366172.py:37 | Aggregated accuracy: 0.7788597175053188 +- 0.1117759950036039\n",
      "DEBUG flower 2022-04-16 12:23:50,450 | server.py:265 | fit_round: strategy sampled 7 clients (out of 7)\n",
      "DEBUG flower 2022-04-16 12:23:55,435 | server.py:277 | fit_round received 7 results and 0 failures\n",
      "DEBUG flower 2022-04-16 12:23:55,453 | server.py:211 | evaluate_round: strategy sampled 7 clients (out of 7)\n"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "Saving round 83 aggregated_weights...\n"
     ]
    },
    {
     "name": "stderr",
     "output_type": "stream",
     "text": [
      "DEBUG flower 2022-04-16 12:23:57,313 | server.py:223 | evaluate_round received 7 results and 0 failures\n",
      "INFO flower 2022-04-16 12:23:57,314 | 2719366172.py:15 | round-83-EVALUATION\n",
      "INFO flower 2022-04-16 12:23:57,316 | 2719366172.py:31 | [(9, 0.76113361120224), (15, 0.8108108043670654), (17, 0.908730149269104), (18, 0.8313252925872803), (19, 0.5378788113594055), (20, 0.7411764860153198), (21, 0.8649789094924927)]\n",
      "INFO flower 2022-04-16 12:23:57,316 | 2719366172.py:37 | Aggregated accuracy: 0.7794334377561297 +- 0.11203321358162532\n",
      "DEBUG flower 2022-04-16 12:23:57,317 | server.py:265 | fit_round: strategy sampled 7 clients (out of 7)\n",
      "DEBUG flower 2022-04-16 12:24:01,958 | server.py:277 | fit_round received 7 results and 0 failures\n",
      "DEBUG flower 2022-04-16 12:24:01,975 | server.py:211 | evaluate_round: strategy sampled 7 clients (out of 7)\n"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "Saving round 84 aggregated_weights...\n"
     ]
    },
    {
     "name": "stderr",
     "output_type": "stream",
     "text": [
      "DEBUG flower 2022-04-16 12:24:03,836 | server.py:223 | evaluate_round received 7 results and 0 failures\n",
      "INFO flower 2022-04-16 12:24:03,836 | 2719366172.py:15 | round-84-EVALUATION\n",
      "INFO flower 2022-04-16 12:24:03,839 | 2719366172.py:31 | [(9, 0.76113361120224), (15, 0.8108108043670654), (17, 0.908730149269104), (18, 0.8313252925872803), (19, 0.5378788113594055), (20, 0.7372549176216125), (21, 0.8649789094924927)]\n",
      "INFO flower 2022-04-16 12:24:03,839 | 2719366172.py:37 | Aggregated accuracy: 0.7788732136998858 +- 0.11223274469045462\n",
      "DEBUG flower 2022-04-16 12:24:03,840 | server.py:265 | fit_round: strategy sampled 7 clients (out of 7)\n",
      "DEBUG flower 2022-04-16 12:24:08,236 | server.py:277 | fit_round received 7 results and 0 failures\n",
      "DEBUG flower 2022-04-16 12:24:08,254 | server.py:211 | evaluate_round: strategy sampled 7 clients (out of 7)\n"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "Saving round 85 aggregated_weights...\n"
     ]
    },
    {
     "name": "stderr",
     "output_type": "stream",
     "text": [
      "DEBUG flower 2022-04-16 12:24:09,880 | server.py:223 | evaluate_round received 7 results and 0 failures\n",
      "INFO flower 2022-04-16 12:24:09,880 | 2719366172.py:15 | round-85-EVALUATION\n",
      "INFO flower 2022-04-16 12:24:09,882 | 2719366172.py:31 | [(9, 0.76113361120224), (15, 0.8108108043670654), (17, 0.908730149269104), (18, 0.8313252925872803), (19, 0.5416666865348816), (20, 0.7372549176216125), (21, 0.8649789094924927)]\n",
      "INFO flower 2022-04-16 12:24:09,883 | 2719366172.py:37 | Aggregated accuracy: 0.7794143387249538 +- 0.11107263242803699\n",
      "DEBUG flower 2022-04-16 12:24:09,883 | server.py:265 | fit_round: strategy sampled 7 clients (out of 7)\n",
      "DEBUG flower 2022-04-16 12:24:14,159 | server.py:277 | fit_round received 7 results and 0 failures\n",
      "DEBUG flower 2022-04-16 12:24:14,175 | server.py:211 | evaluate_round: strategy sampled 7 clients (out of 7)\n"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "Saving round 86 aggregated_weights...\n"
     ]
    },
    {
     "name": "stderr",
     "output_type": "stream",
     "text": [
      "DEBUG flower 2022-04-16 12:24:15,865 | server.py:223 | evaluate_round received 7 results and 0 failures\n",
      "INFO flower 2022-04-16 12:24:15,865 | 2719366172.py:15 | round-86-EVALUATION\n",
      "INFO flower 2022-04-16 12:24:15,867 | 2719366172.py:31 | [(9, 0.76113361120224), (15, 0.8108108043670654), (17, 0.908730149269104), (18, 0.8353413939476013), (19, 0.5378788113594055), (20, 0.7372549176216125), (21, 0.8649789094924927)]\n",
      "INFO flower 2022-04-16 12:24:15,868 | 2719366172.py:37 | Aggregated accuracy: 0.7794469424656459 +- 0.11250933517666865\n",
      "DEBUG flower 2022-04-16 12:24:15,868 | server.py:265 | fit_round: strategy sampled 7 clients (out of 7)\n",
      "DEBUG flower 2022-04-16 12:24:20,140 | server.py:277 | fit_round received 7 results and 0 failures\n",
      "DEBUG flower 2022-04-16 12:24:20,157 | server.py:211 | evaluate_round: strategy sampled 7 clients (out of 7)\n"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "Saving round 87 aggregated_weights...\n"
     ]
    },
    {
     "name": "stderr",
     "output_type": "stream",
     "text": [
      "DEBUG flower 2022-04-16 12:24:21,962 | server.py:223 | evaluate_round received 7 results and 0 failures\n",
      "INFO flower 2022-04-16 12:24:21,962 | 2719366172.py:15 | round-87-EVALUATION\n",
      "INFO flower 2022-04-16 12:24:21,965 | 2719366172.py:31 | [(9, 0.76113361120224), (15, 0.8108108043670654), (17, 0.908730149269104), (18, 0.8353413939476013), (19, 0.5378788113594055), (20, 0.7333333492279053), (21, 0.8649789094924927)]\n",
      "INFO flower 2022-04-16 12:24:21,965 | 2719366172.py:37 | Aggregated accuracy: 0.778886718409402 +- 0.11272758128538764\n",
      "DEBUG flower 2022-04-16 12:24:21,966 | server.py:265 | fit_round: strategy sampled 7 clients (out of 7)\n",
      "DEBUG flower 2022-04-16 12:24:26,832 | server.py:277 | fit_round received 7 results and 0 failures\n",
      "DEBUG flower 2022-04-16 12:24:26,848 | server.py:211 | evaluate_round: strategy sampled 7 clients (out of 7)\n"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "Saving round 88 aggregated_weights...\n"
     ]
    },
    {
     "name": "stderr",
     "output_type": "stream",
     "text": [
      "DEBUG flower 2022-04-16 12:24:28,605 | server.py:223 | evaluate_round received 7 results and 0 failures\n",
      "INFO flower 2022-04-16 12:24:28,606 | 2719366172.py:15 | round-88-EVALUATION\n",
      "INFO flower 2022-04-16 12:24:28,608 | 2719366172.py:31 | [(9, 0.76113361120224), (15, 0.8108108043670654), (17, 0.908730149269104), (18, 0.8353413939476013), (19, 0.5378788113594055), (20, 0.729411780834198), (21, 0.8649789094924927)]\n",
      "INFO flower 2022-04-16 12:24:28,609 | 2719366172.py:37 | Aggregated accuracy: 0.7783264943531581 +- 0.1129620771539268\n",
      "DEBUG flower 2022-04-16 12:24:28,609 | server.py:265 | fit_round: strategy sampled 7 clients (out of 7)\n",
      "DEBUG flower 2022-04-16 12:24:33,039 | server.py:277 | fit_round received 7 results and 0 failures\n",
      "DEBUG flower 2022-04-16 12:24:33,055 | server.py:211 | evaluate_round: strategy sampled 7 clients (out of 7)\n"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "Saving round 89 aggregated_weights...\n"
     ]
    },
    {
     "name": "stderr",
     "output_type": "stream",
     "text": [
      "DEBUG flower 2022-04-16 12:24:34,728 | server.py:223 | evaluate_round received 7 results and 0 failures\n",
      "INFO flower 2022-04-16 12:24:34,729 | 2719366172.py:15 | round-89-EVALUATION\n",
      "INFO flower 2022-04-16 12:24:34,731 | 2719366172.py:31 | [(9, 0.76113361120224), (15, 0.8108108043670654), (17, 0.908730149269104), (18, 0.8353413939476013), (19, 0.5378788113594055), (20, 0.729411780834198), (21, 0.8649789094924927)]\n",
      "INFO flower 2022-04-16 12:24:34,732 | 2719366172.py:37 | Aggregated accuracy: 0.7783264943531581 +- 0.11296207715392678\n",
      "DEBUG flower 2022-04-16 12:24:34,732 | server.py:265 | fit_round: strategy sampled 7 clients (out of 7)\n",
      "DEBUG flower 2022-04-16 12:24:38,993 | server.py:277 | fit_round received 7 results and 0 failures\n",
      "DEBUG flower 2022-04-16 12:24:39,009 | server.py:211 | evaluate_round: strategy sampled 7 clients (out of 7)\n"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "Saving round 90 aggregated_weights...\n"
     ]
    },
    {
     "name": "stderr",
     "output_type": "stream",
     "text": [
      "DEBUG flower 2022-04-16 12:24:40,928 | server.py:223 | evaluate_round received 7 results and 0 failures\n",
      "INFO flower 2022-04-16 12:24:40,928 | 2719366172.py:15 | round-90-EVALUATION\n",
      "INFO flower 2022-04-16 12:24:40,931 | 2719366172.py:31 | [(9, 0.7570850253105164), (15, 0.8108108043670654), (17, 0.908730149269104), (18, 0.8353413939476013), (19, 0.5340909361839294), (20, 0.729411780834198), (21, 0.8649789094924927)]\n",
      "INFO flower 2022-04-16 12:24:40,931 | 2719366172.py:37 | Aggregated accuracy: 0.7772069999149868 +- 0.11420893612970122\n",
      "DEBUG flower 2022-04-16 12:24:40,932 | server.py:265 | fit_round: strategy sampled 7 clients (out of 7)\n",
      "DEBUG flower 2022-04-16 12:24:45,460 | server.py:277 | fit_round received 7 results and 0 failures\n",
      "DEBUG flower 2022-04-16 12:24:45,477 | server.py:211 | evaluate_round: strategy sampled 7 clients (out of 7)\n"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "Saving round 91 aggregated_weights...\n"
     ]
    },
    {
     "name": "stderr",
     "output_type": "stream",
     "text": [
      "DEBUG flower 2022-04-16 12:24:47,249 | server.py:223 | evaluate_round received 7 results and 0 failures\n",
      "INFO flower 2022-04-16 12:24:47,249 | 2719366172.py:15 | round-91-EVALUATION\n",
      "INFO flower 2022-04-16 12:24:47,251 | 2719366172.py:31 | [(9, 0.7570850253105164), (15, 0.8108108043670654), (17, 0.908730149269104), (18, 0.8353413939476013), (19, 0.5340909361839294), (20, 0.7254902124404907), (21, 0.8649789094924927)]\n",
      "INFO flower 2022-04-16 12:24:47,252 | 2719366172.py:37 | Aggregated accuracy: 0.7766467758587429 +- 0.1144513707250479\n",
      "DEBUG flower 2022-04-16 12:24:47,253 | server.py:265 | fit_round: strategy sampled 7 clients (out of 7)\n",
      "DEBUG flower 2022-04-16 12:24:51,552 | server.py:277 | fit_round received 7 results and 0 failures\n",
      "DEBUG flower 2022-04-16 12:24:51,568 | server.py:211 | evaluate_round: strategy sampled 7 clients (out of 7)\n"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "Saving round 92 aggregated_weights...\n"
     ]
    },
    {
     "name": "stderr",
     "output_type": "stream",
     "text": [
      "DEBUG flower 2022-04-16 12:24:53,459 | server.py:223 | evaluate_round received 7 results and 0 failures\n",
      "INFO flower 2022-04-16 12:24:53,460 | 2719366172.py:15 | round-92-EVALUATION\n",
      "INFO flower 2022-04-16 12:24:53,463 | 2719366172.py:31 | [(9, 0.7570850253105164), (15, 0.8108108043670654), (17, 0.9047619104385376), (18, 0.8353413939476013), (19, 0.5340909361839294), (20, 0.7254902124404907), (21, 0.8649789094924927)]\n",
      "INFO flower 2022-04-16 12:24:53,464 | 2719366172.py:37 | Aggregated accuracy: 0.7760798845972333 +- 0.11380373734944976\n",
      "DEBUG flower 2022-04-16 12:24:53,464 | server.py:265 | fit_round: strategy sampled 7 clients (out of 7)\n",
      "DEBUG flower 2022-04-16 12:24:57,729 | server.py:277 | fit_round received 7 results and 0 failures\n",
      "DEBUG flower 2022-04-16 12:24:57,744 | server.py:211 | evaluate_round: strategy sampled 7 clients (out of 7)\n"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "Saving round 93 aggregated_weights...\n"
     ]
    },
    {
     "name": "stderr",
     "output_type": "stream",
     "text": [
      "DEBUG flower 2022-04-16 12:24:59,674 | server.py:223 | evaluate_round received 7 results and 0 failures\n",
      "INFO flower 2022-04-16 12:24:59,675 | 2719366172.py:15 | round-93-EVALUATION\n",
      "INFO flower 2022-04-16 12:24:59,677 | 2719366172.py:31 | [(9, 0.7570850253105164), (15, 0.8108108043670654), (17, 0.9047619104385376), (18, 0.8353413939476013), (19, 0.5340909361839294), (20, 0.7254902124404907), (21, 0.8649789094924927)]\n",
      "INFO flower 2022-04-16 12:24:59,678 | 2719366172.py:37 | Aggregated accuracy: 0.7760798845972333 +- 0.11380373734944976\n",
      "DEBUG flower 2022-04-16 12:24:59,678 | server.py:265 | fit_round: strategy sampled 7 clients (out of 7)\n",
      "DEBUG flower 2022-04-16 12:25:04,161 | server.py:277 | fit_round received 7 results and 0 failures\n",
      "DEBUG flower 2022-04-16 12:25:04,176 | server.py:211 | evaluate_round: strategy sampled 7 clients (out of 7)\n"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "Saving round 94 aggregated_weights...\n"
     ]
    },
    {
     "name": "stderr",
     "output_type": "stream",
     "text": [
      "DEBUG flower 2022-04-16 12:25:06,041 | server.py:223 | evaluate_round received 7 results and 0 failures\n",
      "INFO flower 2022-04-16 12:25:06,041 | 2719366172.py:15 | round-94-EVALUATION\n",
      "INFO flower 2022-04-16 12:25:06,044 | 2719366172.py:31 | [(9, 0.7651821970939636), (15, 0.8108108043670654), (17, 0.9047619104385376), (18, 0.8353413939476013), (19, 0.5340909361839294), (20, 0.729411780834198), (21, 0.8649789094924927)]\n",
      "INFO flower 2022-04-16 12:25:06,044 | 2719366172.py:37 | Aggregated accuracy: 0.777796847479684 +- 0.11339875950798411\n",
      "DEBUG flower 2022-04-16 12:25:06,045 | server.py:265 | fit_round: strategy sampled 7 clients (out of 7)\n",
      "DEBUG flower 2022-04-16 12:25:10,508 | server.py:277 | fit_round received 7 results and 0 failures\n",
      "DEBUG flower 2022-04-16 12:25:10,526 | server.py:211 | evaluate_round: strategy sampled 7 clients (out of 7)\n"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "Saving round 95 aggregated_weights...\n"
     ]
    },
    {
     "name": "stderr",
     "output_type": "stream",
     "text": [
      "DEBUG flower 2022-04-16 12:25:12,289 | server.py:223 | evaluate_round received 7 results and 0 failures\n",
      "INFO flower 2022-04-16 12:25:12,289 | 2719366172.py:15 | round-95-EVALUATION\n",
      "INFO flower 2022-04-16 12:25:12,292 | 2719366172.py:31 | [(9, 0.7692307829856873), (15, 0.8108108043670654), (17, 0.9007936716079712), (18, 0.8353413939476013), (19, 0.5340909361839294), (20, 0.7254902124404907), (21, 0.8649789094924927)]\n",
      "INFO flower 2022-04-16 12:25:12,292 | 2719366172.py:37 | Aggregated accuracy: 0.777248101575034 +- 0.11296652584856907\n",
      "DEBUG flower 2022-04-16 12:25:12,292 | server.py:265 | fit_round: strategy sampled 7 clients (out of 7)\n",
      "DEBUG flower 2022-04-16 12:25:17,374 | server.py:277 | fit_round received 7 results and 0 failures\n",
      "DEBUG flower 2022-04-16 12:25:17,391 | server.py:211 | evaluate_round: strategy sampled 7 clients (out of 7)\n"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "Saving round 96 aggregated_weights...\n"
     ]
    },
    {
     "name": "stderr",
     "output_type": "stream",
     "text": [
      "DEBUG flower 2022-04-16 12:25:19,162 | server.py:223 | evaluate_round received 7 results and 0 failures\n",
      "INFO flower 2022-04-16 12:25:19,162 | 2719366172.py:15 | round-96-EVALUATION\n",
      "INFO flower 2022-04-16 12:25:19,165 | 2719366172.py:31 | [(9, 0.7692307829856873), (15, 0.8108108043670654), (17, 0.9007936716079712), (18, 0.8353413939476013), (19, 0.5340909361839294), (20, 0.7254902124404907), (21, 0.8649789094924927)]\n",
      "INFO flower 2022-04-16 12:25:19,165 | 2719366172.py:37 | Aggregated accuracy: 0.777248101575034 +- 0.11296652584856907\n",
      "DEBUG flower 2022-04-16 12:25:19,166 | server.py:265 | fit_round: strategy sampled 7 clients (out of 7)\n",
      "DEBUG flower 2022-04-16 12:25:23,704 | server.py:277 | fit_round received 7 results and 0 failures\n",
      "DEBUG flower 2022-04-16 12:25:23,720 | server.py:211 | evaluate_round: strategy sampled 7 clients (out of 7)\n"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "Saving round 97 aggregated_weights...\n"
     ]
    },
    {
     "name": "stderr",
     "output_type": "stream",
     "text": [
      "DEBUG flower 2022-04-16 12:25:25,644 | server.py:223 | evaluate_round received 7 results and 0 failures\n",
      "INFO flower 2022-04-16 12:25:25,645 | 2719366172.py:15 | round-97-EVALUATION\n",
      "INFO flower 2022-04-16 12:25:25,647 | 2719366172.py:31 | [(9, 0.7692307829856873), (15, 0.8108108043670654), (17, 0.9007936716079712), (18, 0.8353413939476013), (19, 0.5340909361839294), (20, 0.7254902124404907), (21, 0.8649789094924927)]\n",
      "INFO flower 2022-04-16 12:25:25,648 | 2719366172.py:37 | Aggregated accuracy: 0.777248101575034 +- 0.11296652584856907\n",
      "DEBUG flower 2022-04-16 12:25:25,648 | server.py:265 | fit_round: strategy sampled 7 clients (out of 7)\n",
      "DEBUG flower 2022-04-16 12:25:29,967 | server.py:277 | fit_round received 7 results and 0 failures\n",
      "DEBUG flower 2022-04-16 12:25:29,982 | server.py:211 | evaluate_round: strategy sampled 7 clients (out of 7)\n"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "Saving round 98 aggregated_weights...\n"
     ]
    },
    {
     "name": "stderr",
     "output_type": "stream",
     "text": [
      "DEBUG flower 2022-04-16 12:25:31,931 | server.py:223 | evaluate_round received 7 results and 0 failures\n",
      "INFO flower 2022-04-16 12:25:31,931 | 2719366172.py:15 | round-98-EVALUATION\n",
      "INFO flower 2022-04-16 12:25:31,934 | 2719366172.py:31 | [(9, 0.7692307829856873), (15, 0.8108108043670654), (17, 0.9007936716079712), (18, 0.8353413939476013), (19, 0.5303030014038086), (20, 0.7254902124404907), (21, 0.8649789094924927)]\n",
      "INFO flower 2022-04-16 12:25:31,934 | 2719366172.py:37 | Aggregated accuracy: 0.7767069680350167 +- 0.11413305354156401\n",
      "DEBUG flower 2022-04-16 12:25:31,935 | server.py:265 | fit_round: strategy sampled 7 clients (out of 7)\n",
      "DEBUG flower 2022-04-16 12:25:35,833 | server.py:277 | fit_round received 7 results and 0 failures\n",
      "DEBUG flower 2022-04-16 12:25:35,849 | server.py:211 | evaluate_round: strategy sampled 7 clients (out of 7)\n"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "Saving round 99 aggregated_weights...\n"
     ]
    },
    {
     "name": "stderr",
     "output_type": "stream",
     "text": [
      "DEBUG flower 2022-04-16 12:25:37,600 | server.py:223 | evaluate_round received 7 results and 0 failures\n",
      "INFO flower 2022-04-16 12:25:37,600 | 2719366172.py:15 | round-99-EVALUATION\n",
      "INFO flower 2022-04-16 12:25:37,603 | 2719366172.py:31 | [(9, 0.7692307829856873), (15, 0.8108108043670654), (17, 0.89682537317276), (18, 0.8353413939476013), (19, 0.5303030014038086), (20, 0.729411780834198), (21, 0.8649789094924927)]\n",
      "INFO flower 2022-04-16 12:25:37,603 | 2719366172.py:37 | Aggregated accuracy: 0.7767002923148019 +- 0.11328161935829142\n",
      "DEBUG flower 2022-04-16 12:25:37,604 | server.py:265 | fit_round: strategy sampled 7 clients (out of 7)\n",
      "DEBUG flower 2022-04-16 12:25:42,020 | server.py:277 | fit_round received 7 results and 0 failures\n",
      "DEBUG flower 2022-04-16 12:25:42,038 | server.py:211 | evaluate_round: strategy sampled 7 clients (out of 7)\n"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "Saving round 100 aggregated_weights...\n"
     ]
    },
    {
     "name": "stderr",
     "output_type": "stream",
     "text": [
      "DEBUG flower 2022-04-16 12:25:43,649 | server.py:223 | evaluate_round received 7 results and 0 failures\n",
      "INFO flower 2022-04-16 12:25:43,650 | 2719366172.py:15 | round-100-EVALUATION\n",
      "INFO flower 2022-04-16 12:25:43,652 | 2719366172.py:31 | [(9, 0.7692307829856873), (15, 0.8108108043670654), (17, 0.89682537317276), (18, 0.8353413939476013), (19, 0.5303030014038086), (20, 0.7254902124404907), (21, 0.8649789094924927)]\n",
      "INFO flower 2022-04-16 12:25:43,653 | 2719366172.py:37 | Aggregated accuracy: 0.776140068258558 +- 0.11352353374444786\n",
      "INFO flower 2022-04-16 12:25:43,653 | server.py:182 | FL finished in 632.6174429000002\n",
      "INFO flower 2022-04-16 12:25:43,654 | app.py:149 | app_fit: losses_distributed [(1, 0.6896496752210456), (2, 0.6787633178792619), (3, 0.666720399820054), (4, 0.6538418300166701), (5, 0.6405287610152467), (6, 0.6268029659901975), (7, 0.6128626504001196), (8, 0.5989389103444814), (9, 0.5852780391462675), (10, 0.5722899778756105), (11, 0.5602362799630947), (12, 0.5493341502788996), (13, 0.5397421748409607), (14, 0.5313961657014545), (15, 0.5243456776143472), (16, 0.5184892861936421), (17, 0.5137116051977897), (18, 0.509784893528413), (19, 0.5066216437233759), (20, 0.5041133454085343), (21, 0.5021341186961327), (22, 0.5005340427244784), (23, 0.4992644301342545), (24, 0.49825662780200225), (25, 0.4974495605758423), (26, 0.4968071672906946), (27, 0.49625453089220717), (28, 0.49577215080631776), (29, 0.49533295551958373), (30, 0.4949337646018627), (31, 0.4945823096005131), (32, 0.4942964597209502), (33, 0.49403458913144777), (34, 0.4937817766729973), (35, 0.4935580339711698), (36, 0.4933377961948793), (37, 0.49312955758075316), (38, 0.492940991745033), (39, 0.49277954128947504), (40, 0.4926204818321505), (41, 0.49245221874826145), (42, 0.4922890965903407), (43, 0.49211013504746143), (44, 0.49194545831723574), (45, 0.49181244235382254), (46, 0.4916807534981369), (47, 0.4915721869847346), (48, 0.49146184255910474), (49, 0.49138038698002756), (50, 0.49129118692178453), (51, 0.4911844796135016), (52, 0.4910720169070899), (53, 0.4909566064923579), (54, 0.4908729799417224), (55, 0.49080673843977196), (56, 0.49074962593179766), (57, 0.4907150547476026), (58, 0.490671730589204), (59, 0.49062574450697877), (60, 0.4905773277689771), (61, 0.49052079705710583), (62, 0.4904578329992105), (63, 0.4904012966074865), (64, 0.4903321076000677), (65, 0.4902935562759925), (66, 0.4902584219749719), (67, 0.49025546895869404), (68, 0.49027867431811023), (69, 0.49029222954016005), (70, 0.49032614842031874), (71, 0.4903595146474281), (72, 0.4903751538682917), (73, 0.49041021387481043), (74, 0.49043916514902985), (75, 0.4904738818963549), (76, 0.49052814266185363), (77, 0.4905487421690843), (78, 0.49059415532997636), (79, 0.4906280525218879), (80, 0.49065294787414493), (81, 0.4907417382730115), (82, 0.4907989536268902), (83, 0.4908462453990651), (84, 0.4909265659204343), (85, 0.4910032222944434), (86, 0.4910754105683693), (87, 0.4911692220584547), (88, 0.4912609051589728), (89, 0.4913341526240026), (90, 0.4914116796720995), (91, 0.49151094490266023), (92, 0.4916170912409667), (93, 0.4917097632106028), (94, 0.4918119971446537), (95, 0.49190919575404524), (96, 0.49198231807636794), (97, 0.49205977524199135), (98, 0.4921176669378546), (99, 0.4922111011741517), (100, 0.4923090531247215)]\n",
      "INFO flower 2022-04-16 12:25:43,654 | app.py:150 | app_fit: metrics_distributed {}\n",
      "INFO flower 2022-04-16 12:25:43,654 | app.py:151 | app_fit: losses_centralized []\n",
      "INFO flower 2022-04-16 12:25:43,655 | app.py:152 | app_fit: metrics_centralized {}\n"
     ]
    }
   ],
   "source": [
    "IDS_COMPANY = {\n",
    "    1: [3,4,5,12,  2,8,  1],\n",
    "    2: [13,14,    6,7,10,11,16],\n",
    "    3: [15,18,  9,17,20,21,  19]\n",
    "}\n",
    "\n",
    "for company in IDS_COMPANY:\n",
    "    CLIENTS_IDS = sorted(IDS_COMPANY[company])\n",
    "    global CURRENT_COMPANY\n",
    "    CURRENT_COMPANY = company\n",
    "    \n",
    "    # Initialize results file\n",
    "    header = CLIENTS_IDS\n",
    "    with open(f\"./results/milestone_v3-company_{CURRENT_COMPANY}.csv\", 'w', ) as f:\n",
    "        csv_writer = writer(f)\n",
    "        csv_writer.writerow(header)\n",
    "\n",
    "    # Start Flower simulation\n",
    "        # min_fit_clients y min_eval_clients se ponen al maximo de clients disponibles ya que estamos en un escenario controlado\n",
    "    fl.simulation.start_simulation(\n",
    "        client_fn=client_fn,\n",
    "        clients_ids=CLIENTS_IDS,\n",
    "        client_resources={\"num_cpus\": 6},\n",
    "        num_rounds=100,\n",
    "        strategy=SaveModelStrategy(\n",
    "            min_available_clients = len(CLIENTS_IDS),\n",
    "            min_fit_clients = len(CLIENTS_IDS),\n",
    "            min_eval_clients = len(CLIENTS_IDS),\n",
    "            on_fit_config_fn = fit_config,\n",
    "            on_evaluate_config_fn = fit_config,\n",
    "            accept_failures=False,\n",
    "            initial_parameters=parameters\n",
    "        )\n",
    "    )"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "# Results visualization\n",
    "\n",
    "Show metrics"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 71,
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "Acc máximo empresa 1: 0.73 - 69\n",
      "Acc máximo empresa 2: 0.80 - 86\n",
      "Acc máximo empresa 3: 0.78 - 34\n"
     ]
    },
    {
     "data": {
      "image/png": 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\n",
      "text/plain": [
       "<Figure size 720x432 with 1 Axes>"
      ]
     },
     "metadata": {
      "needs_background": "light"
     },
     "output_type": "display_data"
    },
    {
     "data": {
      "image/png": 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\n",
      "text/plain": [
       "<Figure size 720x432 with 1 Axes>"
      ]
     },
     "metadata": {
      "needs_background": "light"
     },
     "output_type": "display_data"
    },
    {
     "data": {
      "image/png": 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\n",
      "text/plain": [
       "<Figure size 720x432 with 1 Axes>"
      ]
     },
     "metadata": {
      "needs_background": "light"
     },
     "output_type": "display_data"
    }
   ],
   "source": [
    "import matplotlib\n",
    "\n",
    "font = {'family' : 'sans-serif',\n",
    "        'weight' : 'normal',\n",
    "        'size'   : 14}\n",
    "\n",
    "matplotlib.rc('font', **font)\n",
    "\n",
    "for company in IDS_COMPANY:\n",
    "    df = pd.read_csv(f'./results/milestone_v3-company_{company}.csv')\n",
    "    \n",
    "    print(f'Acc max company {company}: {df.mean(numeric_only=True, axis=1).max():.2f} - {df.mean(numeric_only=True, axis=1).idxmax()+1}')\n",
    "    \n",
    "    f = plt.figure(figsize=(10,6))\n",
    "    ax = f.add_subplot()\n",
    "    df.plot(ax=ax,ylim=(0,1))\n",
    "    \n",
    "    ax.set_ylabel(\"Accuracy\")\n",
    "    ax.set_xlabel(\"Federated round\")\n",
    "    \n",
    "    plt.legend(bbox_to_anchor=(0.99, 0.025), loc='lower right', borderaxespad=0, ncol=1)\n",
    "    \n",
    "    plt.savefig(f'../resources/H1-company_{company}-training-federated.pdf', bbox_inches='tight')"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "Company"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 16,
   "metadata": {},
   "outputs": [],
   "source": [
    "def prepare_model_data(client_file):\n",
    "    df = pd.read_csv(client_file)\n",
    "    \n",
    "    train, test = train_test_split(df, test_size=0.30, random_state=42)\n",
    "    \n",
    "    X_train = train[['psd_delta', 'psd_theta', 'psd_alpha', 'psd_beta', 'psd_gamma','eog_blinks', 'eog_var']]\n",
    "    X_test = test[['psd_delta', 'psd_theta', 'psd_alpha', 'psd_beta', 'psd_gamma','eog_blinks', 'eog_var']]\n",
    "    y_train = train['y_class']\n",
    "    y_test = test['y_class']\n",
    "    \n",
    "    scaler = StandardScaler()\n",
    "\n",
    "    X_train = scaler.fit_transform(X_train)\n",
    "    X_test = scaler.transform(X_test)\n",
    "    \n",
    "    return X_train, X_test, y_train, y_test\n",
    "\n",
    "def load_dataset_several_clients(clients):\n",
    "    base_path = \"./data/centralized\"\n",
    "    \n",
    "    X_train, X_val, y_train, y_val = prepare_model_data(f'{base_path}/client_{clients[0]}.csv')\n",
    "    \n",
    "    for cid in clients[1:]:\n",
    "        path = f'{base_path}/client_{cid}.csv'\n",
    "        X_train_act, X_val_act, y_train_act, y_val_act = prepare_model_data(path)\n",
    "    \n",
    "        X_train = np.vstack((X_train, X_train_act))\n",
    "        X_val = np.vstack((X_val, X_val_act))\n",
    "        y_train = np.concatenate((y_train, y_train_act))\n",
    "        y_val = np.concatenate((y_val, y_val_act))\n",
    "        \n",
    "    return X_train, X_val, y_train, y_val\n",
    "\n",
    "def setup_model(weights_path):\n",
    "    neurons = 36\n",
    "    activation = \"relu\"\n",
    "    learning_rate = 0.180165\n",
    "    optimizer = Adadelta(learning_rate=learning_rate)\n",
    "\n",
    "    input_shape = (7,)\n",
    "\n",
    "    # Create model\n",
    "    model = Sequential()\n",
    "\n",
    "    model.add(Dense(neurons, input_shape=input_shape, activation=activation))\n",
    "\n",
    "    model.add(BatchNormalization())\n",
    "\n",
    "    model.add(Dense(neurons, activation=activation))\n",
    "    model.add(Dense(neurons, activation=activation))\n",
    "    model.add(Dense(neurons, activation=activation))\n",
    "\n",
    "    model.add(Dense(1, activation='sigmoid'))\n",
    "\n",
    "    model.compile(loss='binary_crossentropy', optimizer=optimizer, metrics=['accuracy', TruePositives(), TrueNegatives(), FalsePositives(), FalseNegatives()])\n",
    "    \n",
    "    a = np.load(weights_path, allow_pickle=True)\n",
    "\n",
    "    n_elems = [252, 36,\n",
    "               36, 36, 36, 36,\n",
    "               1296, 36,\n",
    "               1296, 36,\n",
    "               1296, 36,\n",
    "               36, 1]\n",
    "\n",
    "    weights = []\n",
    "\n",
    "    for i, t in enumerate(a[\"arr_0\"][0].tensors):\n",
    "        act = np.frombuffer(t[-n_elems[i]*4:], dtype=np.float32)\n",
    "        weights.append(act)\n",
    "\n",
    "    weights[0] = weights[0].reshape(7,36)\n",
    "    weights[6] = weights[6].reshape(36,36)\n",
    "    weights[8] = weights[8].reshape(36,36)\n",
    "    weights[10] = weights[10].reshape(36,36)\n",
    "    weights[12] = weights[12].reshape(36,1)\n",
    "\n",
    "    model.set_weights(weights)\n",
    "    \n",
    "    return model\n",
    "\n",
    "def evaluate_FLmodel(KCs, UCs, company, rnd):\n",
    "    path = f\"./rounds/milestone_v3-company_{company}-round-{rnd}-weights.npz\"\n",
    "    model = setup_model(path)\n",
    "    \n",
    "    # Evaluate for known clients\n",
    "    X_train, X_val, y_train, y_val = load_dataset_several_clients(KCs)\n",
    "    res = model.evaluate(X_val, y_val, verbose=0)\n",
    "    \n",
    "    tp_k = res[2]\n",
    "    tn_k = res[3]\n",
    "    fp_k = res[4]\n",
    "    fn_k = res[5]\n",
    "    \n",
    "    k_acc = (tp_k+tn_k)/(tp_k+tn_k+fp_k+fn_k)\n",
    "    k_sens = (tp_k)/(tp_k+fn_k)\n",
    "    k_spec = (tn_k)/(tn_k+fp_k)\n",
    "    k_f1 = (tp_k)/( tp_k + (fp_k+fn_k)/2 )\n",
    "    \n",
    "    # Evaluate for known clients\n",
    "    X_train, X_val, y_train, y_val = load_dataset_several_clients(UCs)\n",
    "    res_c = model.evaluate(X_val, y_val, verbose=0)\n",
    "    \n",
    "    tp_u = res_c[2]\n",
    "    tn_u = res_c[3]\n",
    "    fp_u = res_c[4]\n",
    "    fn_u = res_c[5]\n",
    "    \n",
    "    u_acc = (tp_u+tn_u)/(tp_u+tn_u+fp_u+fn_u)\n",
    "    u_sens = (tp_u)/(tp_u+fn_u)\n",
    "    u_spec = (tn_u)/(tn_u+fp_u)\n",
    "    u_f1 = (tp_u)/( tp_u + (fp_u+fn_u)/2 )\n",
    "    \n",
    "    return k_acc, k_sens, k_spec, k_f1, u_acc, u_sens, u_spec, u_f1"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 21,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/html": [
       "<div>\n",
       "<style scoped>\n",
       "    .dataframe tbody tr th:only-of-type {\n",
       "        vertical-align: middle;\n",
       "    }\n",
       "\n",
       "    .dataframe tbody tr th {\n",
       "        vertical-align: top;\n",
       "    }\n",
       "\n",
       "    .dataframe thead th {\n",
       "        text-align: right;\n",
       "    }\n",
       "</style>\n",
       "<table border=\"1\" class=\"dataframe\">\n",
       "  <thead>\n",
       "    <tr style=\"text-align: right;\">\n",
       "      <th></th>\n",
       "      <th>Empresa</th>\n",
       "      <th>k_acc</th>\n",
       "      <th>k_sens</th>\n",
       "      <th>k_spec</th>\n",
       "      <th>k_f1</th>\n",
       "      <th>u_acc</th>\n",
       "      <th>u_sens</th>\n",
       "      <th>u_spec</th>\n",
       "      <th>u_f1</th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>0</th>\n",
       "      <td>1.0</td>\n",
       "      <td>0.74</td>\n",
       "      <td>0.74</td>\n",
       "      <td>0.75</td>\n",
       "      <td>0.76</td>\n",
       "      <td>0.67</td>\n",
       "      <td>0.65</td>\n",
       "      <td>0.70</td>\n",
       "      <td>0.70</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1</th>\n",
       "      <td>2.0</td>\n",
       "      <td>0.80</td>\n",
       "      <td>0.93</td>\n",
       "      <td>0.39</td>\n",
       "      <td>0.88</td>\n",
       "      <td>0.55</td>\n",
       "      <td>0.92</td>\n",
       "      <td>0.17</td>\n",
       "      <td>0.68</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2</th>\n",
       "      <td>3.0</td>\n",
       "      <td>0.78</td>\n",
       "      <td>0.59</td>\n",
       "      <td>0.92</td>\n",
       "      <td>0.70</td>\n",
       "      <td>0.63</td>\n",
       "      <td>0.49</td>\n",
       "      <td>0.88</td>\n",
       "      <td>0.63</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "</div>"
      ],
      "text/plain": [
       "   Empresa  k_acc  k_sens  k_spec  k_f1  u_acc  u_sens  u_spec  u_f1\n",
       "0      1.0   0.74    0.74    0.75  0.76   0.67    0.65    0.70  0.70\n",
       "1      2.0   0.80    0.93    0.39  0.88   0.55    0.92    0.17  0.68\n",
       "2      3.0   0.78    0.59    0.92  0.70   0.63    0.49    0.88  0.63"
      ]
     },
     "execution_count": 21,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "DRIVERS_IDS = {\n",
    "    1: [3,4,5,12,  2,8,  1],\n",
    "    2: [13,14,    6,7,10,11,16],\n",
    "    3: [15,18,  9,17,20,21,  19]\n",
    "}\n",
    "\n",
    "ALL_IDS = list(range(1,21+1))\n",
    "\n",
    "results_fed_company = pd.DataFrame(columns=[\"Company\", \"k_acc\", \"k_sens\", \"k_spec\", \"k_f1\", \"u_acc\", \"u_sens\", \"u_spec\", \"u_f1\"])\n",
    "\n",
    "for comp_id in DRIVERS_IDS:\n",
    "    df = pd.read_csv(f'./results/milestone_v3-company_{comp_id}.csv')\n",
    "    df[\"mean\"] = df.mean(numeric_only=True, axis=1)\n",
    "\n",
    "    best_rnd = df[\"mean\"].idxmax()+1\n",
    "    \n",
    "    KCs = DRIVERS_IDS[comp_id]\n",
    "    UCs = list(set(ALL_IDS)-set(KCs))\n",
    "    \n",
    "    k_acc, k_sens, k_spec, k_f1, u_acc, u_sens, u_spec, u_f1 = evaluate_FLmodel(KCs, UCs, comp_id, best_rnd)\n",
    "            \n",
    "    # Store results\n",
    "    fed_company = {\n",
    "        \"Empresa\": comp_id,\n",
    "        \"k_acc\": k_acc,\n",
    "        \"k_sens\": k_sens,\n",
    "        \"k_spec\": k_spec,\n",
    "        \"k_f1\": k_f1,\n",
    "        \"u_acc\": u_acc,\n",
    "        \"u_sens\": u_sens,\n",
    "        \"u_spec\": u_spec,\n",
    "        \"u_f1\": u_f1\n",
    "    }\n",
    "    results_fed_company = results_fed_company.append(fed_company, ignore_index=True)\n",
    "    \n",
    "results_fed_company.round(2)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "metadata": {},
   "outputs": [],
   "source": []
  }
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