testing-fcfl.ipynb

{
 "cells": [
  {
   "cell_type": "code",
   "execution_count": 13,
   "metadata": {},
   "outputs": [],
   "source": [
    "#! pip install -r requirements.txt\n",
    "\n",
    "from src.ExperimentSettings import SETTINGS_DEFINITIONS, ExperimentSettings\n",
    "from src.Experiment import FCFLExperiment"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 14,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "{'id': 0,\n",
       " 'group_name': None,\n",
       " 'algorithm': 'FCFL',\n",
       " 'model': 'CNN',\n",
       " 'batch_size': 10,\n",
       " 'client_fraction': 0.2,\n",
       " 'dataset': 'FEMNIST',\n",
       " 'n_epochs': 3,\n",
       " 'learning_rate': 0.1,\n",
       " 'n_clients': 367,\n",
       " 'partition_strategy': 'non-iid',\n",
       " 'n_rounds': 1,\n",
       " 'seed': 0,\n",
       " 'target_accuracy': 0.8,\n",
       " 'job_dir': None,\n",
       " 'global_weight_delta_norm_threshold': None,\n",
       " 'max_client_weight_delta_norm_threshold': None,\n",
       " 'empirical_risk_approximation_error_bound': None,\n",
       " 'n_clusters': 4,\n",
       " 'n_pre_cluster_rounds': 1,\n",
       " 'cluster_algorithm': 'hierarchical',\n",
       " 'cluster_dist_metric': 'manhattan',\n",
       " 'cluster_hierarchical_linkage': 'average',\n",
       " 'cluster_hierarchical_dist_threshold': 1000.0,\n",
       " 'use_gpu': True}"
      ]
     },
     "execution_count": 14,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "# Get default setting values from SETTINGS_DEFINITIONS as a dict\n",
    "values = list(map(lambda name: SETTINGS_DEFINITIONS[name]['default'], SETTINGS_DEFINITIONS.keys()))\n",
    "args = dict(zip(SETTINGS_DEFINITIONS.keys(), values))\n",
    "\n",
    "# Overwrite specific settings\n",
    "args['algorithm'] = 'FCFL'\n",
    "args['dataset'] = 'FEMNIST'\n",
    "args['model'] = 'CNN'\n",
    "args['learning_rate'] = 0.1\n",
    "# args['n_clients'] = 100\n",
    "args['n_clients'] = 367\n",
    "# args['client_fraction'] = 1.0\n",
    "args['client_fraction'] = 0.2\n",
    "args['batch_size'] = 10\n",
    "args['n_epochs'] = 3\n",
    "args['use_gpu'] = True\n",
    "# args['partition_strategy'] = 'clustered'\n",
    "args['partition_strategy'] = 'non-iid'\n",
    "\n",
    "# One of target_accuracy or n_rounds MUST be set below\n",
    "args['target_accuracy'] = 0.80\n",
    "args['n_pre_cluster_rounds'] = 1\n",
    "args['n_rounds'] = 1\n",
    "\n",
    "args['cluster_dist_metric'] = 'manhattan'\n",
    "args['cluster_algorithm'] = 'hierarchical'\n",
    "args['cluster_hierarchical_linkage'] = 'average'\n",
    "# args['cluster_hierarchical_dist_threshold'] = 0.015\n",
    "args['cluster_hierarchical_dist_threshold'] = 1000.0\n",
    "\n",
    "args"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 15,
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "Loading FEMNIST dataset from cache..\n"
     ]
    }
   ],
   "source": [
    "# Set up the experiment with the parsed arguments\n",
    "settings = ExperimentSettings(**args)\n",
    "# clients = [0,1,2,3,30,31,32,55,56,57] # subset of clients\n",
    "clients = None # all clients\n",
    "experiment = FCFLExperiment(settings, clients)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 16,
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "EXPERIMENT SETTINGS\n",
      "algorithm: FCFL\n",
      "batch_size: 10\n",
      "client_fraction: 0.2\n",
      "cluster_algorithm: hierarchical\n",
      "cluster_dist_metric: manhattan\n",
      "cluster_hierarchical_dist_threshold: 1000.0\n",
      "cluster_hierarchical_linkage: average\n",
      "dataset: FEMNIST\n",
      "empirical_risk_approximation_error_bound: None\n",
      "global_weight_delta_norm_threshold: None\n",
      "group_name: None\n",
      "id: 0\n",
      "job_dir: None\n",
      "learning_rate: 0.1\n",
      "max_client_weight_delta_norm_threshold: None\n",
      "model: CNN\n",
      "n_clients: 367\n",
      "n_clusters: 4\n",
      "n_epochs: 3\n",
      "n_pre_cluster_rounds: 1\n",
      "n_rounds: 1\n",
      "partition_strategy: non-iid\n",
      "seed: 0\n",
      "target_accuracy: 0.8\n",
      "use_gpu: True\n",
      "Using device: cpu\n",
      "\n",
      "Running FCFL with 367 client idxs: [0, 1, 2, 3, 4, 5, 6, 7, 8, 9, 10, 11, 12, 13, 14, 15, 16, 17, 18, 19, 20, 21, 22, 23, 24, 25, 26, 27, 28, 29, 30, 31, 32, 33, 34, 35, 36, 37, 38, 39, 40, 41, 42, 43, 44, 45, 46, 47, 48, 49, 50, 51, 52, 53, 54, 55, 56, 57, 58, 59, 60, 61, 62, 63, 64, 65, 66, 67, 68, 69, 70, 71, 72, 73, 74, 75, 76, 77, 78, 79, 80, 81, 82, 83, 84, 85, 86, 87, 88, 89, 90, 91, 92, 93, 94, 95, 96, 97, 98, 99, 100, 101, 102, 103, 104, 105, 106, 107, 108, 109, 110, 111, 112, 113, 114, 115, 116, 117, 118, 119, 120, 121, 122, 123, 124, 125, 126, 127, 128, 129, 130, 131, 132, 133, 134, 135, 136, 137, 138, 139, 140, 141, 142, 143, 144, 145, 146, 147, 148, 149, 150, 151, 152, 153, 154, 155, 156, 157, 158, 159, 160, 161, 162, 163, 164, 165, 166, 167, 168, 169, 170, 171, 172, 173, 174, 175, 176, 177, 178, 179, 180, 181, 182, 183, 184, 185, 186, 187, 188, 189, 190, 191, 192, 193, 194, 195, 196, 197, 198, 199, 200, 201, 202, 203, 204, 205, 206, 207, 208, 209, 210, 211, 212, 213, 214, 215, 216, 217, 218, 219, 220, 221, 222, 223, 224, 225, 226, 227, 228, 229, 230, 231, 232, 233, 234, 235, 236, 237, 238, 239, 240, 241, 242, 243, 244, 245, 246, 247, 248, 249, 250, 251, 252, 253, 254, 255, 256, 257, 258, 259, 260, 261, 262, 263, 264, 265, 266, 267, 268, 269, 270, 271, 272, 273, 274, 275, 276, 277, 278, 279, 280, 281, 282, 283, 284, 285, 286, 287, 288, 289, 290, 291, 292, 293, 294, 295, 296, 297, 298, 299, 300, 301, 302, 303, 304, 305, 306, 307, 308, 309, 310, 311, 312, 313, 314, 315, 316, 317, 318, 319, 320, 321, 322, 323, 324, 325, 326, 327, 328, 329, 330, 331, 332, 333, 334, 335, 336, 337, 338, 339, 340, 341, 342, 343, 344, 345, 346, 347, 348, 349, 350, 351, 352, 353, 354, 355, 356, 357, 358, 359, 360, 361, 362, 363, 364, 365, 366]\n",
      "Running learning for 1 communication rounds prior to clustering\n",
      "\n",
      "Communication round 1\n",
      "LOCAL TRAINING: Client #106, Epoch 1, #examples 162, Loss 4.025761085398057, Accuracy 0.04705882423064288\n",
      "LOCAL TRAINING: Client #106, Epoch 2, #examples 162, Loss 3.789903584648581, Accuracy 0.07058823634596433\n",
      "LOCAL TRAINING: Client #106, Epoch 3, #examples 162, Loss 3.5489099306218765, Accuracy 0.06470588331713396\n",
      "LOCAL TRAINING: Client #259, Epoch 1, #examples 281, Loss 4.001218590243109, Accuracy 0.02758620730761824\n",
      "LOCAL TRAINING: Client #259, Epoch 2, #examples 281, Loss 4.01915925946729, Accuracy 0.04137931096142736\n",
      "LOCAL TRAINING: Client #259, Epoch 3, #examples 281, Loss 3.8484830363043425, Accuracy 0.05862069052868876\n",
      "LOCAL TRAINING: Client #45, Epoch 1, #examples 317, Loss 3.939572051167488, Accuracy 0.058928572572767735\n",
      "LOCAL TRAINING: Client #45, Epoch 2, #examples 317, Loss 3.8000086173415184, Accuracy 0.10758928791619837\n",
      "LOCAL TRAINING: Client #45, Epoch 3, #examples 317, Loss 3.750340022146702, Accuracy 0.07633928721770644\n",
      "LOCAL TRAINING: Client #26, Epoch 1, #examples 228, Loss 4.008986151736716, Accuracy 0.03478260921395343\n",
      "LOCAL TRAINING: Client #26, Epoch 2, #examples 228, Loss 3.8562510220900825, Accuracy 0.06521739260010097\n",
      "LOCAL TRAINING: Client #26, Epoch 3, #examples 228, Loss 3.786247263783994, Accuracy 0.05543478319178457\n",
      "LOCAL TRAINING: Client #78, Epoch 1, #examples 156, Loss 4.056648567318916, Accuracy 0.05000000074505806\n",
      "LOCAL TRAINING: Client #78, Epoch 2, #examples 156, Loss 3.9039346128702164, Accuracy 0.06666666781529784\n",
      "LOCAL TRAINING: Client #78, Epoch 3, #examples 156, Loss 3.7251675873994827, Accuracy 0.08541666809469461\n",
      "LOCAL TRAINING: Client #347, Epoch 1, #examples 154, Loss 3.840477094054222, Accuracy 0.03125000046566129\n",
      "LOCAL TRAINING: Client #347, Epoch 2, #examples 154, Loss 3.7600158005952835, Accuracy 0.05625000083819032\n",
      "LOCAL TRAINING: Client #347, Epoch 3, #examples 154, Loss 3.607801243662834, Accuracy 0.05625000083819032\n",
      "LOCAL TRAINING: Client #90, Epoch 1, #examples 79, Loss 3.9516237676143646, Accuracy 0.05138888955116272\n",
      "LOCAL TRAINING: Client #90, Epoch 2, #examples 79, Loss 3.8673534989356995, Accuracy 0.07500000111758709\n",
      "LOCAL TRAINING: Client #90, Epoch 3, #examples 79, Loss 3.8745898008346558, Accuracy 0.10277777910232544\n",
      "LOCAL TRAINING: Client #311, Epoch 1, #examples 156, Loss 4.076413407921791, Accuracy 0.05625000083819032\n",
      "LOCAL TRAINING: Client #311, Epoch 2, #examples 156, Loss 3.8916871547698975, Accuracy 0.0750000006519258\n",
      "LOCAL TRAINING: Client #311, Epoch 3, #examples 156, Loss 3.753581792116165, Accuracy 0.08125000167638063\n",
      "LOCAL TRAINING: Client #239, Epoch 1, #examples 297, Loss 3.9399495840072634, Accuracy 0.06333333452542624\n",
      "LOCAL TRAINING: Client #239, Epoch 2, #examples 297, Loss 3.8145106474558514, Accuracy 0.040000000844399135\n",
      "LOCAL TRAINING: Client #239, Epoch 3, #examples 297, Loss 3.7849546988805134, Accuracy 0.060000001142422356\n",
      "LOCAL TRAINING: Client #6, Epoch 1, #examples 141, Loss 3.989412450790405, Accuracy 0.026666667064030966\n",
      "LOCAL TRAINING: Client #6, Epoch 2, #examples 141, Loss 4.348331960042318, Accuracy 0.04666666736205419\n",
      "LOCAL TRAINING: Client #6, Epoch 3, #examples 141, Loss 3.8689485867818196, Accuracy 0.07333333492279052\n",
      "LOCAL TRAINING: Client #120, Epoch 1, #examples 150, Loss 3.896051629384359, Accuracy 0.10000000248352686\n",
      "LOCAL TRAINING: Client #120, Epoch 2, #examples 150, Loss 3.9531935532887776, Accuracy 0.07333333442608515\n",
      "LOCAL TRAINING: Client #120, Epoch 3, #examples 150, Loss 3.8099211692810058, Accuracy 0.07333333492279052\n",
      "LOCAL TRAINING: Client #141, Epoch 1, #examples 162, Loss 4.0113292722141045, Accuracy 0.04705882466891233\n",
      "LOCAL TRAINING: Client #141, Epoch 2, #examples 162, Loss 3.814936034819659, Accuracy 0.0941176488995552\n",
      "LOCAL TRAINING: Client #141, Epoch 3, #examples 162, Loss 4.215255667181576, Accuracy 0.04117647120181252\n",
      "LOCAL TRAINING: Client #263, Epoch 1, #examples 311, Loss 3.9532028883695602, Accuracy 0.037500000558793545\n",
      "LOCAL TRAINING: Client #263, Epoch 2, #examples 311, Loss 3.8523600846529007, Accuracy 0.05312500079162419\n",
      "LOCAL TRAINING: Client #263, Epoch 3, #examples 311, Loss 3.8210351541638374, Accuracy 0.05312500079162419\n",
      "LOCAL TRAINING: Client #286, Epoch 1, #examples 149, Loss 3.9158090114593507, Accuracy 0.10000000149011612\n",
      "LOCAL TRAINING: Client #286, Epoch 2, #examples 149, Loss 4.022465419769287, Accuracy 0.16666667113701503\n",
      "LOCAL TRAINING: Client #286, Epoch 3, #examples 149, Loss 3.535874128341675, Accuracy 0.11407407621542613\n",
      "LOCAL TRAINING: Client #299, Epoch 1, #examples 351, Loss 3.9614780677689447, Accuracy 0.06388888984090751\n",
      "LOCAL TRAINING: Client #299, Epoch 2, #examples 351, Loss 3.920425640212165, Accuracy 0.05555555638339785\n",
      "LOCAL TRAINING: Client #299, Epoch 3, #examples 351, Loss 3.695358415444692, Accuracy 0.0777777795576387\n",
      "LOCAL TRAINING: Client #210, Epoch 1, #examples 341, Loss 3.979864127295358, Accuracy 0.0571428582072258\n",
      "LOCAL TRAINING: Client #210, Epoch 2, #examples 341, Loss 3.9884523051125664, Accuracy 0.06571428669350488\n",
      "LOCAL TRAINING: Client #210, Epoch 3, #examples 341, Loss 3.7138142449515206, Accuracy 0.07428571560553142\n",
      "LOCAL TRAINING: Client #294, Epoch 1, #examples 121, Loss 4.123697941119854, Accuracy 0.07692307864244168\n",
      "LOCAL TRAINING: Client #294, Epoch 2, #examples 121, Loss 4.110772059513972, Accuracy 0.03846153903466005\n",
      "LOCAL TRAINING: Client #294, Epoch 3, #examples 121, Loss 3.907003952906682, Accuracy 0.07692307864244168\n",
      "LOCAL TRAINING: Client #101, Epoch 1, #examples 160, Loss 3.981458008289337, Accuracy 0.05000000074505806\n",
      "LOCAL TRAINING: Client #101, Epoch 2, #examples 160, Loss 3.8018883019685745, Accuracy 0.06875000102445483\n",
      "LOCAL TRAINING: Client #101, Epoch 3, #examples 160, Loss 3.687374010682106, Accuracy 0.08750000176951289\n",
      "LOCAL TRAINING: Client #221, Epoch 1, #examples 165, Loss 3.9456401292015526, Accuracy 0.08235294240362503\n",
      "LOCAL TRAINING: Client #221, Epoch 2, #examples 165, Loss 3.7988407191108253, Accuracy 0.04117647120181252\n",
      "LOCAL TRAINING: Client #221, Epoch 3, #examples 165, Loss 3.5272611449746525, Accuracy 0.04705882423064288\n",
      "LOCAL TRAINING: Client #140, Epoch 1, #examples 153, Loss 4.030180439352989, Accuracy 0.05000000074505806\n",
      "LOCAL TRAINING: Client #140, Epoch 2, #examples 153, Loss 3.8354964554309845, Accuracy 0.018750000279396772\n",
      "LOCAL TRAINING: Client #140, Epoch 3, #examples 153, Loss 3.7879499047994614, Accuracy 0.05625000083819032\n",
      "LOCAL TRAINING: Client #142, Epoch 1, #examples 96, Loss 3.873860716819763, Accuracy 0.06666666865348816\n",
      "LOCAL TRAINING: Client #142, Epoch 2, #examples 96, Loss 4.117255210876465, Accuracy 0.08666666820645333\n",
      "LOCAL TRAINING: Client #142, Epoch 3, #examples 96, Loss 3.907428503036499, Accuracy 0.05000000149011612\n",
      "LOCAL TRAINING: Client #199, Epoch 1, #examples 118, Loss 4.082593818505605, Accuracy 0.08333333457509677\n",
      "LOCAL TRAINING: Client #199, Epoch 2, #examples 118, Loss 3.9553584853808084, Accuracy 0.06666666828095913\n",
      "LOCAL TRAINING: Client #199, Epoch 3, #examples 118, Loss 3.913279434045156, Accuracy 0.10208333532015483\n",
      "LOCAL TRAINING: Client #59, Epoch 1, #examples 148, Loss 4.051631848017375, Accuracy 0.05333333412806193\n",
      "LOCAL TRAINING: Client #59, Epoch 2, #examples 148, Loss 3.8673624992370605, Accuracy 0.06833333422740301\n",
      "LOCAL TRAINING: Client #59, Epoch 3, #examples 148, Loss 3.6706589221954347, Accuracy 0.04000000059604645\n",
      "LOCAL TRAINING: Client #293, Epoch 1, #examples 156, Loss 3.9232308715581894, Accuracy 0.08125000167638063\n",
      "LOCAL TRAINING: Client #293, Epoch 2, #examples 156, Loss 3.9663434624671936, Accuracy 0.07500000111758709\n",
      "LOCAL TRAINING: Client #293, Epoch 3, #examples 156, Loss 3.7470480501651764, Accuracy 0.08125000074505806\n",
      "LOCAL TRAINING: Client #302, Epoch 1, #examples 340, Loss 4.129856972133412, Accuracy 0.06176470746012295\n",
      "LOCAL TRAINING: Client #302, Epoch 2, #examples 340, Loss 3.959783483954037, Accuracy 0.058823530507438326\n",
      "LOCAL TRAINING: Client #302, Epoch 3, #examples 340, Loss 3.783940455492805, Accuracy 0.06764705983154914\n",
      "LOCAL TRAINING: Client #254, Epoch 1, #examples 356, Loss 4.000776807467143, Accuracy 0.044444445313678846\n",
      "LOCAL TRAINING: Client #254, Epoch 2, #examples 356, Loss 3.8463998238245645, Accuracy 0.07129629742768076\n",
      "LOCAL TRAINING: Client #254, Epoch 3, #examples 356, Loss 3.753680878215366, Accuracy 0.08611111239426666\n",
      "LOCAL TRAINING: Client #68, Epoch 1, #examples 267, Loss 4.049066914452447, Accuracy 0.033333333830038704\n",
      "LOCAL TRAINING: Client #68, Epoch 2, #examples 267, Loss 3.80499169561598, Accuracy 0.059259260418238466\n",
      "LOCAL TRAINING: Client #68, Epoch 3, #examples 267, Loss 3.9143542360376427, Accuracy 0.04814814941750632\n",
      "LOCAL TRAINING: Client #332, Epoch 1, #examples 141, Loss 4.14985187848409, Accuracy 0.04666666736205419\n",
      "LOCAL TRAINING: Client #332, Epoch 2, #examples 141, Loss 3.97607208887736, Accuracy 0.09333333472410837\n",
      "LOCAL TRAINING: Client #332, Epoch 3, #examples 141, Loss 3.7641613483428955, Accuracy 0.10666666726271311\n",
      "LOCAL TRAINING: Client #113, Epoch 1, #examples 154, Loss 3.903986230492592, Accuracy 0.07812500093132257\n",
      "LOCAL TRAINING: Client #113, Epoch 2, #examples 154, Loss 3.897710844874382, Accuracy 0.06875000149011612\n",
      "LOCAL TRAINING: Client #113, Epoch 3, #examples 154, Loss 3.5743749290704727, Accuracy 0.05000000074505806\n",
      "LOCAL TRAINING: Client #191, Epoch 1, #examples 92, Loss 3.8925856828689573, Accuracy 0.030000000447034835\n",
      "LOCAL TRAINING: Client #191, Epoch 2, #examples 92, Loss 3.562303304672241, Accuracy 0.09000000208616257\n",
      "LOCAL TRAINING: Client #191, Epoch 3, #examples 92, Loss 3.982373762130737, Accuracy 0.06000000089406967\n",
      "LOCAL TRAINING: Client #124, Epoch 1, #examples 153, Loss 3.9473234862089157, Accuracy 0.05625000083819032\n",
      "LOCAL TRAINING: Client #124, Epoch 2, #examples 153, Loss 3.7593023777008057, Accuracy 0.09791666874662042\n",
      "LOCAL TRAINING: Client #124, Epoch 3, #examples 153, Loss 3.9751392751932144, Accuracy 0.07708333525806665\n",
      "LOCAL TRAINING: Client #102, Epoch 1, #examples 151, Loss 4.030202269554138, Accuracy 0.0875000013038516\n",
      "LOCAL TRAINING: Client #102, Epoch 2, #examples 151, Loss 3.8981972336769104, Accuracy 0.10625000158324838\n",
      "LOCAL TRAINING: Client #102, Epoch 3, #examples 151, Loss 3.658835008740425, Accuracy 0.08125000121071935\n",
      "LOCAL TRAINING: Client #15, Epoch 1, #examples 101, Loss 4.097196860746904, Accuracy 0.06363636458461935\n",
      "LOCAL TRAINING: Client #15, Epoch 2, #examples 101, Loss 4.018899028951472, Accuracy 0.14545454694466156\n",
      "LOCAL TRAINING: Client #15, Epoch 3, #examples 101, Loss 3.9318913329731333, Accuracy 0.07272727381099355\n",
      "LOCAL TRAINING: Client #37, Epoch 1, #examples 246, Loss 4.031639423370361, Accuracy 0.028000000417232513\n",
      "LOCAL TRAINING: Client #37, Epoch 2, #examples 246, Loss 3.8902157592773436, Accuracy 0.06000000089406967\n",
      "LOCAL TRAINING: Client #37, Epoch 3, #examples 246, Loss 3.7189461994171142, Accuracy 0.06000000089406967\n",
      "LOCAL TRAINING: Client #54, Epoch 1, #examples 156, Loss 4.029694646596909, Accuracy 0.037500000558793545\n",
      "LOCAL TRAINING: Client #54, Epoch 2, #examples 156, Loss 3.766818955540657, Accuracy 0.09375000139698386\n",
      "LOCAL TRAINING: Client #54, Epoch 3, #examples 156, Loss 3.683678761124611, Accuracy 0.06875000102445483\n",
      "LOCAL TRAINING: Client #5, Epoch 1, #examples 124, Loss 3.9644967959477353, Accuracy 0.03846153903466005\n",
      "LOCAL TRAINING: Client #5, Epoch 2, #examples 124, Loss 4.122538970066951, Accuracy 0.06923077026238808\n",
      "LOCAL TRAINING: Client #5, Epoch 3, #examples 124, Loss 4.033237915772658, Accuracy 0.09615384787321091\n",
      "LOCAL TRAINING: Client #60, Epoch 1, #examples 149, Loss 3.9309019724527996, Accuracy 0.0800000011920929\n",
      "LOCAL TRAINING: Client #60, Epoch 2, #examples 149, Loss 3.761277707417806, Accuracy 0.06740740835666656\n",
      "LOCAL TRAINING: Client #60, Epoch 3, #examples 149, Loss 3.6413535118103026, Accuracy 0.06666666815678278\n",
      "LOCAL TRAINING: Client #132, Epoch 1, #examples 236, Loss 3.997826894124349, Accuracy 0.037500000558793545\n",
      "LOCAL TRAINING: Client #132, Epoch 2, #examples 236, Loss 3.926369865735372, Accuracy 0.04583333401630322\n",
      "LOCAL TRAINING: Client #132, Epoch 3, #examples 236, Loss 3.8563255965709686, Accuracy 0.033333333830038704\n",
      "LOCAL TRAINING: Client #264, Epoch 1, #examples 291, Loss 3.9920101960500083, Accuracy 0.026666667064030966\n",
      "LOCAL TRAINING: Client #264, Epoch 2, #examples 291, Loss 3.8356170018513995, Accuracy 0.016666666915019352\n",
      "LOCAL TRAINING: Client #264, Epoch 3, #examples 291, Loss 3.9639116684595743, Accuracy 0.026666667064030966\n",
      "LOCAL TRAINING: Client #64, Epoch 1, #examples 144, Loss 4.102751795450846, Accuracy 0.04333333373069763\n",
      "LOCAL TRAINING: Client #64, Epoch 2, #examples 144, Loss 3.990520413716634, Accuracy 0.03333333432674408\n",
      "LOCAL TRAINING: Client #64, Epoch 3, #examples 144, Loss 3.8880707263946532, Accuracy 0.04000000059604645\n",
      "LOCAL TRAINING: Client #206, Epoch 1, #examples 265, Loss 4.031802195089835, Accuracy 0.06296296390118422\n",
      "LOCAL TRAINING: Client #206, Epoch 2, #examples 265, Loss 3.95031060995879, Accuracy 0.029629630071145517\n",
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      "LOCAL TRAINING: Client #159, Epoch 1, #examples 292, Loss 4.0131732304890955, Accuracy 0.020000000298023225\n",
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      "LOCAL TRAINING: Client #114, Epoch 1, #examples 133, Loss 4.037273798670087, Accuracy 0.05000000074505806\n",
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      "LOCAL TRAINING: Client #295, Epoch 1, #examples 168, Loss 4.093807108262006, Accuracy 0.04705882466891233\n",
      "LOCAL TRAINING: Client #295, Epoch 2, #examples 168, Loss 3.9462636078105255, Accuracy 0.07941176567007513\n",
      "LOCAL TRAINING: Client #295, Epoch 3, #examples 168, Loss 3.68862478873309, Accuracy 0.06617647190304364\n",
      "CLUSTER: 1, MEAN TEST ACCURACY: 0.09158795950705902, 10th percentile: 0.0, 90th percentile: 0.20000000298023224, % clients reaching target accuracy: 0.0\n",
      "GLOBAL WEIGHTS DELTA NORM: 1.2260942459106445\n",
      "58s elapsed\n",
      "Training complete in 1 communication rounds\n",
      "\n",
      "Running 1 round of training on all client in cluster to obtain client weight updates\n",
      "LOCAL TRAINING: Client #0, Epoch 1, #examples 136, Loss 3.719107593808855, Accuracy 0.07619047750319753\n",
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      "LOCAL TRAINING: Client #1, Epoch 1, #examples 134, Loss 3.622457895960127, Accuracy 0.10714285927159446\n",
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      "LOCAL TRAINING: Client #2, Epoch 1, #examples 153, Loss 3.521236404776573, Accuracy 0.06250000093132257\n",
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      "LOCAL TRAINING: Client #4, Epoch 3, #examples 156, Loss 3.3782080560922623, Accuracy 0.07291666837409139\n",
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      "LOCAL TRAINING: Client #5, Epoch 3, #examples 124, Loss 3.504592492030217, Accuracy 0.09615384730008933\n",
      "LOCAL TRAINING: Client #6, Epoch 1, #examples 141, Loss 3.62894180615743, Accuracy 0.07333333442608515\n",
      "LOCAL TRAINING: Client #6, Epoch 2, #examples 141, Loss 4.160389757156372, Accuracy 0.04000000059604645\n",
      "LOCAL TRAINING: Client #6, Epoch 3, #examples 141, Loss 3.706337245305379, Accuracy 0.08666666895151139\n",
      "LOCAL TRAINING: Client #7, Epoch 1, #examples 153, Loss 3.7037303894758224, Accuracy 0.08333333488553762\n",
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      "LOCAL TRAINING: Client #8, Epoch 1, #examples 128, Loss 3.7443678562457743, Accuracy 0.07115384707084069\n",
      "LOCAL TRAINING: Client #8, Epoch 2, #examples 128, Loss 3.7001420167776256, Accuracy 0.030769231227728035\n",
      "LOCAL TRAINING: Client #8, Epoch 3, #examples 128, Loss 3.535159000983605, Accuracy 0.06346153926390868\n",
      "LOCAL TRAINING: Client #9, Epoch 1, #examples 162, Loss 3.61874880510218, Accuracy 0.08823529587072484\n",
      "LOCAL TRAINING: Client #9, Epoch 2, #examples 162, Loss 3.529529473360847, Accuracy 0.07647058937479467\n",
      "LOCAL TRAINING: Client #9, Epoch 3, #examples 162, Loss 3.2240670007817886, Accuracy 0.18823529648430207\n",
      "LOCAL TRAINING: Client #10, Epoch 1, #examples 57, Loss 3.8468616803487143, Accuracy 0.05000000074505806\n",
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      "LOCAL TRAINING: Client #11, Epoch 1, #examples 90, Loss 3.88139361805386, Accuracy 0.12222222404347526\n",
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      "LOCAL TRAINING: Client #12, Epoch 2, #examples 94, Loss 3.876572322845459, Accuracy 0.010000000149011612\n",
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      "LOCAL TRAINING: Client #13, Epoch 2, #examples 139, Loss 3.6012288502284457, Accuracy 0.09285714477300644\n",
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      "LOCAL TRAINING: Client #14, Epoch 1, #examples 126, Loss 3.6792248579171987, Accuracy 0.06666666785111794\n",
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      "LOCAL TRAINING: Client #15, Epoch 1, #examples 101, Loss 3.8378098877993496, Accuracy 0.045454546131870964\n",
      "LOCAL TRAINING: Client #15, Epoch 2, #examples 101, Loss 3.6458144838159736, Accuracy 0.07272727381099355\n",
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      "LOCAL TRAINING: Client #16, Epoch 1, #examples 138, Loss 3.6067382948739186, Accuracy 0.04285714349576405\n",
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      "LOCAL TRAINING: Client #16, Epoch 3, #examples 138, Loss 3.2489741700036183, Accuracy 0.05892857217362949\n",
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      "LOCAL TRAINING: Client #17, Epoch 3, #examples 134, Loss 3.3897648879459927, Accuracy 0.1178571448794433\n",
      "LOCAL TRAINING: Client #18, Epoch 1, #examples 107, Loss 3.7446784756400366, Accuracy 0.08181818303736774\n",
      "LOCAL TRAINING: Client #18, Epoch 2, #examples 107, Loss 3.5217267816716973, Accuracy 0.08961039171977477\n",
      "LOCAL TRAINING: Client #18, Epoch 3, #examples 107, Loss 3.329740871082653, Accuracy 0.07662337815219705\n",
      "LOCAL TRAINING: Client #19, Epoch 1, #examples 156, Loss 3.6562907993793488, Accuracy 0.08750000223517418\n",
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      "LOCAL TRAINING: Client #19, Epoch 3, #examples 156, Loss 3.325504869222641, Accuracy 0.0854166685603559\n",
      "LOCAL TRAINING: Client #20, Epoch 1, #examples 143, Loss 3.649861129124959, Accuracy 0.10000000198682149\n",
      "LOCAL TRAINING: Client #20, Epoch 2, #examples 143, Loss 3.596686363220215, Accuracy 0.10000000149011612\n",
      "LOCAL TRAINING: Client #20, Epoch 3, #examples 143, Loss 3.3761356830596925, Accuracy 0.10666666875282924\n",
      "LOCAL TRAINING: Client #21, Epoch 1, #examples 155, Loss 3.6501918137073517, Accuracy 0.08125000167638063\n",
      "LOCAL TRAINING: Client #21, Epoch 2, #examples 155, Loss 3.4230568408966064, Accuracy 0.08125000121071935\n",
      "LOCAL TRAINING: Client #21, Epoch 3, #examples 155, Loss 3.3345827162265778, Accuracy 0.08125000121071935\n",
      "LOCAL TRAINING: Client #22, Epoch 1, #examples 330, Loss 3.7811459844762627, Accuracy 0.06969697073553548\n",
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      "LOCAL TRAINING: Client #22, Epoch 3, #examples 330, Loss 3.446426622795336, Accuracy 0.11818182084596518\n",
      "LOCAL TRAINING: Client #23, Epoch 1, #examples 272, Loss 3.850520806653159, Accuracy 0.07500000138367925\n",
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      "LOCAL TRAINING: Client #23, Epoch 3, #examples 272, Loss 3.650910266808101, Accuracy 0.12500000266092165\n",
      "LOCAL TRAINING: Client #24, Epoch 1, #examples 359, Loss 3.8044005698627896, Accuracy 0.047222222925888166\n",
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      "LOCAL TRAINING: Client #320, Epoch 2, #examples 333, Loss 3.7164865451700546, Accuracy 0.05294117725947324\n",
      "LOCAL TRAINING: Client #320, Epoch 3, #examples 333, Loss 3.646451241829816, Accuracy 0.08627451145473648\n",
      "LOCAL TRAINING: Client #321, Epoch 1, #examples 307, Loss 3.867992224231843, Accuracy 0.04009216663337523\n",
      "LOCAL TRAINING: Client #321, Epoch 2, #examples 307, Loss 3.79873598775556, Accuracy 0.03225806499681165\n",
      "LOCAL TRAINING: Client #321, Epoch 3, #examples 307, Loss 3.707397814719908, Accuracy 0.05299539263209989\n",
      "LOCAL TRAINING: Client #322, Epoch 1, #examples 285, Loss 3.8182989564435235, Accuracy 0.05862069052868876\n",
      "LOCAL TRAINING: Client #322, Epoch 2, #examples 285, Loss 3.7441175395044786, Accuracy 0.051724138958700774\n",
      "LOCAL TRAINING: Client #322, Epoch 3, #examples 285, Loss 3.668165453549089, Accuracy 0.06551724286942646\n",
      "LOCAL TRAINING: Client #323, Epoch 1, #examples 266, Loss 3.904472792590106, Accuracy 0.029629630071145517\n",
      "LOCAL TRAINING: Client #323, Epoch 2, #examples 266, Loss 3.7508440017700195, Accuracy 0.033333334105986136\n",
      "LOCAL TRAINING: Client #323, Epoch 3, #examples 266, Loss 3.6388619210984974, Accuracy 0.06666666793602484\n",
      "LOCAL TRAINING: Client #324, Epoch 1, #examples 128, Loss 3.7576612692612867, Accuracy 0.07115384764396228\n",
      "LOCAL TRAINING: Client #324, Epoch 2, #examples 128, Loss 3.3896077963022084, Accuracy 0.10000000263635929\n",
      "LOCAL TRAINING: Client #324, Epoch 3, #examples 128, Loss 3.0724197717813344, Accuracy 0.12307692491091214\n",
      "LOCAL TRAINING: Client #325, Epoch 1, #examples 358, Loss 3.81550841861301, Accuracy 0.047222222925888166\n",
      "LOCAL TRAINING: Client #325, Epoch 2, #examples 358, Loss 3.613817916976081, Accuracy 0.084722223588162\n",
      "LOCAL TRAINING: Client #325, Epoch 3, #examples 358, Loss 3.3841141131189136, Accuracy 0.13125000211099783\n",
      "LOCAL TRAINING: Client #326, Epoch 1, #examples 162, Loss 3.694197696797988, Accuracy 0.10000000149011612\n",
      "LOCAL TRAINING: Client #326, Epoch 2, #examples 162, Loss 3.40431669179131, Accuracy 0.08823529499418595\n",
      "LOCAL TRAINING: Client #326, Epoch 3, #examples 162, Loss 3.252007680780747, Accuracy 0.16470588436898062\n",
      "LOCAL TRAINING: Client #327, Epoch 1, #examples 154, Loss 3.5836935490369797, Accuracy 0.08437500149011612\n",
      "LOCAL TRAINING: Client #327, Epoch 2, #examples 154, Loss 3.498250126838684, Accuracy 0.0687500019557774\n",
      "LOCAL TRAINING: Client #327, Epoch 3, #examples 154, Loss 3.322997137904167, Accuracy 0.08750000176951289\n",
      "LOCAL TRAINING: Client #328, Epoch 1, #examples 160, Loss 3.646516293287277, Accuracy 0.06250000093132257\n",
      "LOCAL TRAINING: Client #328, Epoch 2, #examples 160, Loss 3.514129400253296, Accuracy 0.0687500019557774\n",
      "LOCAL TRAINING: Client #328, Epoch 3, #examples 160, Loss 3.35567706823349, Accuracy 0.09375000232830644\n",
      "LOCAL TRAINING: Client #329, Epoch 1, #examples 155, Loss 3.669608622789383, Accuracy 0.05625000083819032\n",
      "LOCAL TRAINING: Client #329, Epoch 2, #examples 155, Loss 3.567423954606056, Accuracy 0.05625000083819032\n",
      "LOCAL TRAINING: Client #329, Epoch 3, #examples 155, Loss 3.3816771656274796, Accuracy 0.16250000381842256\n",
      "LOCAL TRAINING: Client #330, Epoch 1, #examples 163, Loss 3.735224022584803, Accuracy 0.04117647120181252\n",
      "LOCAL TRAINING: Client #330, Epoch 2, #examples 163, Loss 3.575827528448666, Accuracy 0.08235294284189448\n",
      "LOCAL TRAINING: Client #330, Epoch 3, #examples 163, Loss 3.5643572246327118, Accuracy 0.07058823678423376\n",
      "LOCAL TRAINING: Client #331, Epoch 1, #examples 162, Loss 3.660347854389864, Accuracy 0.08235294240362503\n",
      "LOCAL TRAINING: Client #331, Epoch 2, #examples 162, Loss 3.5498442930333756, Accuracy 0.08235294284189448\n",
      "LOCAL TRAINING: Client #331, Epoch 3, #examples 162, Loss 3.342051898731905, Accuracy 0.07647058937479467\n",
      "LOCAL TRAINING: Client #332, Epoch 1, #examples 141, Loss 3.6705586115519204, Accuracy 0.10666666825612386\n",
      "LOCAL TRAINING: Client #332, Epoch 2, #examples 141, Loss 3.454204305013021, Accuracy 0.06000000089406967\n",
      "LOCAL TRAINING: Client #332, Epoch 3, #examples 141, Loss 3.5833117961883545, Accuracy 0.09333333522081375\n",
      "LOCAL TRAINING: Client #333, Epoch 1, #examples 156, Loss 3.637153685092926, Accuracy 0.06250000093132257\n",
      "LOCAL TRAINING: Client #333, Epoch 2, #examples 156, Loss 3.596819445490837, Accuracy 0.09375000139698386\n",
      "LOCAL TRAINING: Client #333, Epoch 3, #examples 156, Loss 3.379914402961731, Accuracy 0.11041666846722364\n",
      "LOCAL TRAINING: Client #334, Epoch 1, #examples 144, Loss 3.5618395169576007, Accuracy 0.06666666815678278\n",
      "LOCAL TRAINING: Client #334, Epoch 2, #examples 144, Loss 3.40199392636617, Accuracy 0.0800000011920929\n",
      "LOCAL TRAINING: Client #334, Epoch 3, #examples 144, Loss 3.465048821767171, Accuracy 0.10000000248352686\n",
      "LOCAL TRAINING: Client #335, Epoch 1, #examples 132, Loss 3.2936972039086476, Accuracy 0.07142857249294009\n",
      "LOCAL TRAINING: Client #335, Epoch 2, #examples 132, Loss 4.73529987675803, Accuracy 0.09285714370863778\n",
      "LOCAL TRAINING: Client #335, Epoch 3, #examples 132, Loss 3.606998562812805, Accuracy 0.07857143027441842\n",
      "LOCAL TRAINING: Client #336, Epoch 1, #examples 164, Loss 3.6397198368521297, Accuracy 0.10882353125249639\n",
      "LOCAL TRAINING: Client #336, Epoch 2, #examples 164, Loss 3.4170947074890137, Accuracy 0.10000000105184667\n",
      "LOCAL TRAINING: Client #336, Epoch 3, #examples 164, Loss 3.2829775669995476, Accuracy 0.11764706145314609\n",
      "LOCAL TRAINING: Client #337, Epoch 1, #examples 160, Loss 3.585988625884056, Accuracy 0.06250000093132257\n",
      "LOCAL TRAINING: Client #337, Epoch 2, #examples 160, Loss 3.516196683049202, Accuracy 0.05625000083819032\n",
      "LOCAL TRAINING: Client #337, Epoch 3, #examples 160, Loss 3.3147682398557663, Accuracy 0.10000000149011612\n",
      "LOCAL TRAINING: Client #338, Epoch 1, #examples 163, Loss 3.6144464436699364, Accuracy 0.07058823678423376\n",
      "LOCAL TRAINING: Client #338, Epoch 2, #examples 163, Loss 3.445362217286054, Accuracy 0.0588235302883036\n",
      "LOCAL TRAINING: Client #338, Epoch 3, #examples 163, Loss 3.3532691142138313, Accuracy 0.06470588375540341\n",
      "LOCAL TRAINING: Client #339, Epoch 1, #examples 138, Loss 3.712451389857701, Accuracy 0.08750000117080552\n",
      "LOCAL TRAINING: Client #339, Epoch 2, #examples 138, Loss 3.6042331627437045, Accuracy 0.06428571524364608\n",
      "LOCAL TRAINING: Client #339, Epoch 3, #examples 138, Loss 3.533471260751997, Accuracy 0.10714285980377879\n",
      "LOCAL TRAINING: Client #340, Epoch 1, #examples 162, Loss 3.5709754158468807, Accuracy 0.05294117725947324\n",
      "LOCAL TRAINING: Client #340, Epoch 2, #examples 162, Loss 3.751995086669922, Accuracy 0.05294117725947324\n",
      "LOCAL TRAINING: Client #340, Epoch 3, #examples 162, Loss 3.4536586509031406, Accuracy 0.08823529499418595\n",
      "LOCAL TRAINING: Client #341, Epoch 1, #examples 133, Loss 3.699833410126822, Accuracy 0.10000000255448478\n",
      "LOCAL TRAINING: Client #341, Epoch 2, #examples 133, Loss 3.265531437737601, Accuracy 0.11666666982429368\n",
      "LOCAL TRAINING: Client #341, Epoch 3, #examples 133, Loss 3.242074200085231, Accuracy 0.19523809956652777\n",
      "LOCAL TRAINING: Client #342, Epoch 1, #examples 163, Loss 3.6182868620928597, Accuracy 0.06470588331713396\n",
      "LOCAL TRAINING: Client #342, Epoch 2, #examples 163, Loss 3.4242481904871322, Accuracy 0.05294117725947324\n",
      "LOCAL TRAINING: Client #342, Epoch 3, #examples 163, Loss 3.2145404254688934, Accuracy 0.13529412053963719\n",
      "LOCAL TRAINING: Client #343, Epoch 1, #examples 153, Loss 3.5983103662729263, Accuracy 0.05000000074505806\n",
      "LOCAL TRAINING: Client #343, Epoch 2, #examples 153, Loss 3.328661248087883, Accuracy 0.09375000139698386\n",
      "LOCAL TRAINING: Client #343, Epoch 3, #examples 153, Loss 3.200492352247238, Accuracy 0.10625000158324838\n",
      "LOCAL TRAINING: Client #344, Epoch 1, #examples 166, Loss 3.717720522600062, Accuracy 0.05294117769774269\n",
      "LOCAL TRAINING: Client #344, Epoch 2, #examples 166, Loss 3.4361448287963867, Accuracy 0.11176470798604629\n",
      "LOCAL TRAINING: Client #344, Epoch 3, #examples 166, Loss 3.333362340927124, Accuracy 0.07647058937479467\n",
      "LOCAL TRAINING: Client #345, Epoch 1, #examples 27, Loss 3.546905755996704, Accuracy 0.2285714348157247\n",
      "LOCAL TRAINING: Client #345, Epoch 2, #examples 27, Loss 2.96819273630778, Accuracy 0.18095238755146661\n",
      "LOCAL TRAINING: Client #345, Epoch 3, #examples 27, Loss 3.2858633995056152, Accuracy 0.14761905123790106\n",
      "LOCAL TRAINING: Client #346, Epoch 1, #examples 131, Loss 3.6051017556871687, Accuracy 0.06428571630801473\n",
      "LOCAL TRAINING: Client #346, Epoch 2, #examples 131, Loss 3.71274048941476, Accuracy 0.06428571524364608\n",
      "LOCAL TRAINING: Client #346, Epoch 3, #examples 131, Loss 3.3743215118135725, Accuracy 0.05714285799435207\n",
      "LOCAL TRAINING: Client #347, Epoch 1, #examples 154, Loss 3.6470531970262527, Accuracy 0.06875000149011612\n",
      "LOCAL TRAINING: Client #347, Epoch 2, #examples 154, Loss 3.393213704228401, Accuracy 0.1031250013038516\n",
      "LOCAL TRAINING: Client #347, Epoch 3, #examples 154, Loss 3.2937731593847275, Accuracy 0.10312500176951289\n",
      "LOCAL TRAINING: Client #348, Epoch 1, #examples 163, Loss 3.8401146636289707, Accuracy 0.07058823634596433\n",
      "LOCAL TRAINING: Client #348, Epoch 2, #examples 163, Loss 3.494747526505414, Accuracy 0.04117647120181252\n",
      "LOCAL TRAINING: Client #348, Epoch 3, #examples 163, Loss 3.4429249202503875, Accuracy 0.08235294240362503\n",
      "LOCAL TRAINING: Client #349, Epoch 1, #examples 160, Loss 3.6219983845949173, Accuracy 0.07500000111758709\n",
      "LOCAL TRAINING: Client #349, Epoch 2, #examples 160, Loss 3.500175878405571, Accuracy 0.0437500006519258\n",
      "LOCAL TRAINING: Client #349, Epoch 3, #examples 160, Loss 3.3240537494421005, Accuracy 0.1125000030733645\n",
      "LOCAL TRAINING: Client #350, Epoch 1, #examples 158, Loss 3.6911617517471313, Accuracy 0.08281250111758709\n",
      "LOCAL TRAINING: Client #350, Epoch 2, #examples 158, Loss 3.5373035818338394, Accuracy 0.0875000013038516\n",
      "LOCAL TRAINING: Client #350, Epoch 3, #examples 158, Loss 3.42838291823864, Accuracy 0.06875000102445483\n",
      "LOCAL TRAINING: Client #351, Epoch 1, #examples 153, Loss 3.6818303763866425, Accuracy 0.06250000093132257\n",
      "LOCAL TRAINING: Client #351, Epoch 2, #examples 153, Loss 3.547818571329117, Accuracy 0.1020833351649344\n",
      "LOCAL TRAINING: Client #351, Epoch 3, #examples 153, Loss 3.483395218849182, Accuracy 0.06875000149011612\n",
      "LOCAL TRAINING: Client #352, Epoch 1, #examples 161, Loss 3.6592586881974163, Accuracy 0.07058823678423376\n",
      "LOCAL TRAINING: Client #352, Epoch 2, #examples 161, Loss 3.447021077660953, Accuracy 0.04117647120181252\n",
      "LOCAL TRAINING: Client #352, Epoch 3, #examples 161, Loss 3.5249158634858975, Accuracy 0.04117647120181252\n",
      "LOCAL TRAINING: Client #353, Epoch 1, #examples 157, Loss 3.6874729990959167, Accuracy 0.0437500006519258\n",
      "LOCAL TRAINING: Client #353, Epoch 2, #examples 157, Loss 3.613078147172928, Accuracy 0.09642857406288385\n",
      "LOCAL TRAINING: Client #353, Epoch 3, #examples 157, Loss 3.469925031065941, Accuracy 0.07142857322469354\n",
      "LOCAL TRAINING: Client #354, Epoch 1, #examples 165, Loss 3.7107660069185147, Accuracy 0.07058823634596433\n",
      "LOCAL TRAINING: Client #354, Epoch 2, #examples 165, Loss 3.532474826363956, Accuracy 0.03529411817298216\n",
      "LOCAL TRAINING: Client #354, Epoch 3, #examples 165, Loss 3.43249072748072, Accuracy 0.06470588375540341\n",
      "LOCAL TRAINING: Client #355, Epoch 1, #examples 163, Loss 3.640816940980799, Accuracy 0.04705882423064288\n",
      "LOCAL TRAINING: Client #355, Epoch 2, #examples 163, Loss 3.379338629105512, Accuracy 0.07058823634596433\n",
      "LOCAL TRAINING: Client #355, Epoch 3, #examples 163, Loss 3.314689748427447, Accuracy 0.0588235302883036\n",
      "LOCAL TRAINING: Client #356, Epoch 1, #examples 108, Loss 3.8842509659853848, Accuracy 0.07272727448831905\n",
      "LOCAL TRAINING: Client #356, Epoch 2, #examples 108, Loss 3.790553569793701, Accuracy 0.03863636404275894\n",
      "LOCAL TRAINING: Client #356, Epoch 3, #examples 108, Loss 3.779409885406494, Accuracy 0.08181818371469324\n",
      "LOCAL TRAINING: Client #357, Epoch 1, #examples 148, Loss 3.618244457244873, Accuracy 0.0983333354194959\n",
      "LOCAL TRAINING: Client #357, Epoch 2, #examples 148, Loss 3.5042895317077636, Accuracy 0.10166666954755783\n",
      "LOCAL TRAINING: Client #357, Epoch 3, #examples 148, Loss 3.352915128072103, Accuracy 0.1266666700442632\n",
      "LOCAL TRAINING: Client #358, Epoch 1, #examples 142, Loss 3.6515920639038084, Accuracy 0.10000000149011612\n",
      "LOCAL TRAINING: Client #358, Epoch 2, #examples 142, Loss 3.602790530522664, Accuracy 0.07333333492279052\n",
      "LOCAL TRAINING: Client #358, Epoch 3, #examples 142, Loss 3.417105213801066, Accuracy 0.1266666680574417\n",
      "LOCAL TRAINING: Client #359, Epoch 1, #examples 117, Loss 3.837258517742157, Accuracy 0.06666666828095913\n",
      "LOCAL TRAINING: Client #359, Epoch 2, #examples 117, Loss 3.620367685953776, Accuracy 0.09880952599147956\n",
      "LOCAL TRAINING: Client #359, Epoch 3, #examples 117, Loss 3.5257606705029807, Accuracy 0.061904763182004295\n",
      "LOCAL TRAINING: Client #360, Epoch 1, #examples 126, Loss 3.6664274655855618, Accuracy 0.028205128816457894\n",
      "LOCAL TRAINING: Client #360, Epoch 2, #examples 126, Loss 3.5782356629004846, Accuracy 0.06666666842423953\n",
      "LOCAL TRAINING: Client #360, Epoch 3, #examples 126, Loss 3.4305959848257213, Accuracy 0.13333333742160064\n",
      "LOCAL TRAINING: Client #361, Epoch 1, #examples 105, Loss 3.122717510570179, Accuracy 0.06363636458461935\n",
      "LOCAL TRAINING: Client #361, Epoch 2, #examples 105, Loss 2.551979563452981, Accuracy 0.06363636458461935\n",
      "LOCAL TRAINING: Client #361, Epoch 3, #examples 105, Loss 2.7231217947873203, Accuracy 0.09090909226374193\n",
      "LOCAL TRAINING: Client #362, Epoch 1, #examples 144, Loss 3.616019090016683, Accuracy 0.05333333412806193\n",
      "LOCAL TRAINING: Client #362, Epoch 2, #examples 144, Loss 3.5404962062835694, Accuracy 0.07333333492279052\n",
      "LOCAL TRAINING: Client #362, Epoch 3, #examples 144, Loss 3.31372062365214, Accuracy 0.06666666815678278\n",
      "LOCAL TRAINING: Client #363, Epoch 1, #examples 154, Loss 3.5752921402454376, Accuracy 0.1000000019557774\n",
      "LOCAL TRAINING: Client #363, Epoch 2, #examples 154, Loss 3.425969824194908, Accuracy 0.05625000083819032\n",
      "LOCAL TRAINING: Client #363, Epoch 3, #examples 154, Loss 3.176957607269287, Accuracy 0.18750000419095159\n",
      "LOCAL TRAINING: Client #364, Epoch 1, #examples 144, Loss 3.6357102235158285, Accuracy 0.10333333512147268\n",
      "LOCAL TRAINING: Client #364, Epoch 2, #examples 144, Loss 3.4074779828389485, Accuracy 0.04666666736205419\n",
      "LOCAL TRAINING: Client #364, Epoch 3, #examples 144, Loss 3.1871330738067627, Accuracy 0.10000000149011612\n",
      "LOCAL TRAINING: Client #365, Epoch 1, #examples 144, Loss 3.5518174807230634, Accuracy 0.05333333412806193\n",
      "LOCAL TRAINING: Client #365, Epoch 2, #examples 144, Loss 3.4767707506815593, Accuracy 0.08333333532015483\n",
      "LOCAL TRAINING: Client #365, Epoch 3, #examples 144, Loss 3.2923162460327147, Accuracy 0.09666666835546493\n",
      "LOCAL TRAINING: Client #366, Epoch 1, #examples 134, Loss 3.483571478298732, Accuracy 0.10357142984867096\n",
      "LOCAL TRAINING: Client #366, Epoch 2, #examples 134, Loss 3.299341951097761, Accuracy 0.07857143080660275\n",
      "LOCAL TRAINING: Client #366, Epoch 3, #examples 134, Loss 3.223787103380476, Accuracy 0.07857142974223409\n",
      "[2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 4 2 2 2 2 2 2 2\n",
      " 2 2 2 2 2 2 2 2 2 2 2 2 2 2 0 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2\n",
      " 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2\n",
      " 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 3 2 2 2 2 2 2 2 2 2 2 2\n",
      " 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2\n",
      " 2 2 1 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2\n",
      " 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2\n",
      " 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2\n",
      " 2 2 2 2 5 0 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2\n",
      " 2 2 1 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2]\n",
      "6\n",
      "6 clusters found [[51, 301], [187, 335], [0, 1, 2, 3, 4, 5, 6, 7, 8, 9, 10, 11, 12, 13, 14, 15, 16, 17, 18, 19, 20, 21, 22, 23, 24, 25, 26, 27, 28, 30, 31, 32, 33, 34, 35, 36, 37, 38, 39, 40, 41, 42, 43, 44, 45, 46, 47, 48, 49, 50, 52, 53, 54, 55, 56, 57, 58, 59, 60, 61, 62, 63, 64, 65, 66, 67, 68, 69, 70, 71, 72, 73, 74, 75, 76, 77, 78, 79, 80, 81, 82, 83, 84, 85, 86, 87, 88, 89, 90, 91, 92, 93, 94, 95, 96, 97, 98, 99, 100, 101, 102, 103, 104, 105, 106, 107, 108, 109, 110, 111, 112, 113, 114, 115, 116, 117, 118, 119, 120, 121, 122, 123, 124, 125, 126, 127, 128, 129, 130, 131, 132, 133, 134, 135, 137, 138, 139, 140, 141, 142, 143, 144, 145, 146, 147, 148, 149, 150, 151, 152, 153, 154, 155, 156, 157, 158, 159, 160, 161, 162, 163, 164, 165, 166, 167, 168, 169, 170, 171, 172, 173, 174, 175, 176, 177, 178, 179, 180, 181, 182, 183, 184, 185, 186, 188, 189, 190, 191, 192, 193, 194, 195, 196, 197, 198, 199, 200, 201, 202, 203, 204, 205, 206, 207, 208, 209, 210, 211, 212, 213, 214, 215, 216, 217, 218, 219, 220, 221, 222, 223, 224, 225, 226, 227, 228, 229, 230, 231, 232, 233, 234, 235, 236, 237, 238, 239, 240, 241, 242, 243, 244, 245, 246, 247, 248, 249, 250, 251, 252, 253, 254, 255, 256, 257, 258, 259, 260, 261, 262, 263, 264, 265, 266, 267, 268, 269, 270, 271, 272, 273, 274, 275, 276, 277, 278, 279, 280, 281, 282, 283, 284, 285, 286, 287, 288, 289, 290, 291, 292, 293, 294, 295, 296, 297, 298, 299, 302, 303, 304, 305, 306, 307, 308, 309, 310, 311, 312, 313, 314, 315, 316, 317, 318, 319, 320, 321, 322, 323, 324, 325, 326, 327, 328, 329, 330, 331, 332, 333, 334, 336, 337, 338, 339, 340, 341, 342, 343, 344, 345, 346, 347, 348, 349, 350, 351, 352, 353, 354, 355, 356, 357, 358, 359, 360, 361, 362, 363, 364, 365, 366], [136], [29], [300]]\n",
      "\n",
      "Running FCFL with 2 client idxs: [51, 301]\n",
      "Running learning for 1 communication rounds\n",
      "\n",
      "Communication round 1\n",
      "LOCAL TRAINING: Client #301, Epoch 1, #examples 349, Loss 3.7860889775412425, Accuracy 0.02920634959425245\n",
      "LOCAL TRAINING: Client #301, Epoch 2, #examples 349, Loss 3.5962531770978656, Accuracy 0.06285714400666101\n",
      "LOCAL TRAINING: Client #301, Epoch 3, #examples 349, Loss 3.2266553401947022, Accuracy 0.1546031783734049\n",
      "CLUSTER: 1.1, MEAN TEST ACCURACY: 0.15311652794480324, 10th percentile: 0.11951219514012337, 90th percentile: 0.18672086074948313, % clients reaching target accuracy: 0.0\n",
      "GLOBAL WEIGHTS DELTA NORM: 2.76242995262146\n",
      "355s elapsed\n",
      "Training complete in 1 communication rounds\n",
      "\n",
      "Running 1 round of training on all client in cluster to obtain client weight updates\n",
      "LOCAL TRAINING: Client #51, Epoch 1, #examples 357, Loss 2.8837394648128085, Accuracy 0.20515873490108383\n",
      "LOCAL TRAINING: Client #51, Epoch 2, #examples 357, Loss 2.1606558528211384, Accuracy 0.38015873461133903\n",
      "LOCAL TRAINING: Client #51, Epoch 3, #examples 357, Loss 1.6433781998025045, Accuracy 0.5503968331548903\n",
      "LOCAL TRAINING: Client #301, Epoch 1, #examples 349, Loss 2.5067322322300503, Accuracy 0.329523814363139\n",
      "LOCAL TRAINING: Client #301, Epoch 2, #examples 349, Loss 1.9113528319767543, Accuracy 0.46380953171423506\n",
      "LOCAL TRAINING: Client #301, Epoch 3, #examples 349, Loss 1.322365437235151, Accuracy 0.6193650837455477\n",
      "[1 0]\n",
      "2\n",
      "Cluster 1.1 will not be split any further\n",
      "\n",
      "Running FCFL with 2 client idxs: [187, 335]\n",
      "Running learning for 1 communication rounds\n",
      "\n",
      "Communication round 1\n",
      "LOCAL TRAINING: Client #187, Epoch 1, #examples 121, Loss 3.3400486432589016, Accuracy 0.21538461859409624\n",
      "LOCAL TRAINING: Client #187, Epoch 2, #examples 121, Loss 3.748322633596567, Accuracy 0.17692307841319305\n",
      "LOCAL TRAINING: Client #187, Epoch 3, #examples 121, Loss 2.9620645413031945, Accuracy 0.31538461779172605\n",
      "CLUSTER: 1.2, MEAN TEST ACCURACY: 0.0555555559694767, 10th percentile: 0.01111111119389534, 90th percentile: 0.10000000074505806, % clients reaching target accuracy: 0.0\n",
      "GLOBAL WEIGHTS DELTA NORM: 2.1286003589630127\n",
      "358s elapsed\n",
      "Training complete in 1 communication rounds\n",
      "\n",
      "Running 1 round of training on all client in cluster to obtain client weight updates\n",
      "LOCAL TRAINING: Client #187, Epoch 1, #examples 121, Loss 3.1511778097886305, Accuracy 0.21538461859409624\n",
      "LOCAL TRAINING: Client #187, Epoch 2, #examples 121, Loss 2.5232563752394457, Accuracy 0.32307692961050916\n",
      "LOCAL TRAINING: Client #187, Epoch 3, #examples 121, Loss 2.8770133898808408, Accuracy 0.2769230821957955\n",
      "LOCAL TRAINING: Client #335, Epoch 1, #examples 132, Loss 3.407773188182286, Accuracy 0.10714285980377879\n",
      "LOCAL TRAINING: Client #335, Epoch 2, #examples 132, Loss 2.6889039278030396, Accuracy 0.17857143176453455\n",
      "LOCAL TRAINING: Client #335, Epoch 3, #examples 132, Loss 2.674444692475455, Accuracy 0.2785714359155723\n",
      "[0 0]\n",
      "1\n",
      "Cluster 1.2 will not be split any further\n",
      "\n",
      "Running FCFL with 360 client idxs: [0, 1, 2, 3, 4, 5, 6, 7, 8, 9, 10, 11, 12, 13, 14, 15, 16, 17, 18, 19, 20, 21, 22, 23, 24, 25, 26, 27, 28, 30, 31, 32, 33, 34, 35, 36, 37, 38, 39, 40, 41, 42, 43, 44, 45, 46, 47, 48, 49, 50, 52, 53, 54, 55, 56, 57, 58, 59, 60, 61, 62, 63, 64, 65, 66, 67, 68, 69, 70, 71, 72, 73, 74, 75, 76, 77, 78, 79, 80, 81, 82, 83, 84, 85, 86, 87, 88, 89, 90, 91, 92, 93, 94, 95, 96, 97, 98, 99, 100, 101, 102, 103, 104, 105, 106, 107, 108, 109, 110, 111, 112, 113, 114, 115, 116, 117, 118, 119, 120, 121, 122, 123, 124, 125, 126, 127, 128, 129, 130, 131, 132, 133, 134, 135, 137, 138, 139, 140, 141, 142, 143, 144, 145, 146, 147, 148, 149, 150, 151, 152, 153, 154, 155, 156, 157, 158, 159, 160, 161, 162, 163, 164, 165, 166, 167, 168, 169, 170, 171, 172, 173, 174, 175, 176, 177, 178, 179, 180, 181, 182, 183, 184, 185, 186, 188, 189, 190, 191, 192, 193, 194, 195, 196, 197, 198, 199, 200, 201, 202, 203, 204, 205, 206, 207, 208, 209, 210, 211, 212, 213, 214, 215, 216, 217, 218, 219, 220, 221, 222, 223, 224, 225, 226, 227, 228, 229, 230, 231, 232, 233, 234, 235, 236, 237, 238, 239, 240, 241, 242, 243, 244, 245, 246, 247, 248, 249, 250, 251, 252, 253, 254, 255, 256, 257, 258, 259, 260, 261, 262, 263, 264, 265, 266, 267, 268, 269, 270, 271, 272, 273, 274, 275, 276, 277, 278, 279, 280, 281, 282, 283, 284, 285, 286, 287, 288, 289, 290, 291, 292, 293, 294, 295, 296, 297, 298, 299, 302, 303, 304, 305, 306, 307, 308, 309, 310, 311, 312, 313, 314, 315, 316, 317, 318, 319, 320, 321, 322, 323, 324, 325, 326, 327, 328, 329, 330, 331, 332, 333, 334, 336, 337, 338, 339, 340, 341, 342, 343, 344, 345, 346, 347, 348, 349, 350, 351, 352, 353, 354, 355, 356, 357, 358, 359, 360, 361, 362, 363, 364, 365, 366]\n",
      "Running learning for 1 communication rounds\n",
      "\n",
      "Communication round 1\n",
      "LOCAL TRAINING: Client #295, Epoch 1, #examples 168, Loss 3.3383127100327434, Accuracy 0.18676470921320074\n",
      "LOCAL TRAINING: Client #295, Epoch 2, #examples 168, Loss 2.678895817083471, Accuracy 0.3500000067493495\n",
      "LOCAL TRAINING: Client #295, Epoch 3, #examples 168, Loss 2.3228037497576546, Accuracy 0.4838235351969214\n",
      "LOCAL TRAINING: Client #238, Epoch 1, #examples 262, Loss 3.3818288290942156, Accuracy 0.18148148501360858\n",
      "LOCAL TRAINING: Client #238, Epoch 2, #examples 262, Loss 2.7299194909908153, Accuracy 0.3111111179546074\n",
      "LOCAL TRAINING: Client #238, Epoch 3, #examples 262, Loss 2.292710776682253, Accuracy 0.3629629678196377\n",
      "LOCAL TRAINING: Client #41, Epoch 1, #examples 235, Loss 3.310310512781143, Accuracy 0.1625000030423204\n",
      "LOCAL TRAINING: Client #41, Epoch 2, #examples 235, Loss 2.772182270884514, Accuracy 0.3000000047807892\n",
      "LOCAL TRAINING: Client #41, Epoch 3, #examples 235, Loss 2.2992302030324936, Accuracy 0.4458333409080903\n",
      "LOCAL TRAINING: Client #16, Epoch 1, #examples 138, Loss 3.3811738320759366, Accuracy 0.14285714711461747\n",
      "LOCAL TRAINING: Client #16, Epoch 2, #examples 138, Loss 2.8248225109917775, Accuracy 0.208928576537541\n",
      "LOCAL TRAINING: Client #16, Epoch 3, #examples 138, Loss 2.4656414900507246, Accuracy 0.391071434531893\n",
      "LOCAL TRAINING: Client #14, Epoch 1, #examples 126, Loss 3.3526476529928355, Accuracy 0.3051282110122534\n",
      "LOCAL TRAINING: Client #14, Epoch 2, #examples 126, Loss 2.635748111284696, Accuracy 0.4051282130754911\n",
      "LOCAL TRAINING: Client #14, Epoch 3, #examples 126, Loss 2.405513800107516, Accuracy 0.4692307704916367\n",
      "LOCAL TRAINING: Client #160, Epoch 1, #examples 299, Loss 3.204859177271525, Accuracy 0.1974074107905229\n",
      "LOCAL TRAINING: Client #160, Epoch 2, #examples 299, Loss 2.4484858592351277, Accuracy 0.34407407939434054\n",
      "LOCAL TRAINING: Client #160, Epoch 3, #examples 299, Loss 1.992249172925949, Accuracy 0.4059259320298831\n",
      "LOCAL TRAINING: Client #270, Epoch 1, #examples 310, Loss 3.5813952645947857, Accuracy 0.11612903494988719\n",
      "LOCAL TRAINING: Client #270, Epoch 2, #examples 310, Loss 3.0806811394230014, Accuracy 0.18709677794287283\n",
      "LOCAL TRAINING: Client #270, Epoch 3, #examples 310, Loss 2.6466259033449235, Accuracy 0.28387097437535563\n",
      "LOCAL TRAINING: Client #32, Epoch 1, #examples 112, Loss 3.237121264139811, Accuracy 0.23333333556850752\n",
      "LOCAL TRAINING: Client #32, Epoch 2, #examples 112, Loss 2.6365256905555725, Accuracy 0.35833333618938923\n",
      "LOCAL TRAINING: Client #32, Epoch 3, #examples 112, Loss 2.3033737341562905, Accuracy 0.42500000695387524\n",
      "LOCAL TRAINING: Client #255, Epoch 1, #examples 342, Loss 3.666421570096697, Accuracy 0.10285714481558118\n",
      "LOCAL TRAINING: Client #255, Epoch 2, #examples 342, Loss 2.984183502197266, Accuracy 0.22285714724234174\n",
      "LOCAL TRAINING: Client #255, Epoch 3, #examples 342, Loss 2.571177656309945, Accuracy 0.32000000604561396\n",
      "LOCAL TRAINING: Client #105, Epoch 1, #examples 153, Loss 3.7714435160160065, Accuracy 0.09583333553746343\n",
      "LOCAL TRAINING: Client #105, Epoch 2, #examples 153, Loss 3.0387419164180756, Accuracy 0.20833333814516664\n",
      "LOCAL TRAINING: Client #105, Epoch 3, #examples 153, Loss 2.6625100150704384, Accuracy 0.36041667172685266\n",
      "LOCAL TRAINING: Client #101, Epoch 1, #examples 160, Loss 3.201066493988037, Accuracy 0.2187500037252903\n",
      "LOCAL TRAINING: Client #101, Epoch 2, #examples 160, Loss 2.5144233033061028, Accuracy 0.4187500076368451\n",
      "LOCAL TRAINING: Client #101, Epoch 3, #examples 160, Loss 2.1207121163606644, Accuracy 0.5500000026077032\n",
      "LOCAL TRAINING: Client #281, Epoch 1, #examples 147, Loss 3.3192911465962727, Accuracy 0.21238095611333846\n",
      "LOCAL TRAINING: Client #281, Epoch 2, #examples 147, Loss 2.8612932920455934, Accuracy 0.3019047682483991\n",
      "LOCAL TRAINING: Client #281, Epoch 3, #examples 147, Loss 2.478187847137451, Accuracy 0.3314285765091578\n",
      "LOCAL TRAINING: Client #219, Epoch 1, #examples 164, Loss 3.3462312782511994, Accuracy 0.13529412010136774\n",
      "LOCAL TRAINING: Client #219, Epoch 2, #examples 164, Loss 2.9178909694447235, Accuracy 0.2500000035061556\n",
      "LOCAL TRAINING: Client #219, Epoch 3, #examples 164, Loss 2.5958430135951325, Accuracy 0.3823529468739734\n",
      "LOCAL TRAINING: Client #318, Epoch 1, #examples 322, Loss 3.48088398846713, Accuracy 0.1545454575256868\n",
      "LOCAL TRAINING: Client #318, Epoch 2, #examples 322, Loss 2.8198320070902505, Accuracy 0.2575757632201368\n",
      "LOCAL TRAINING: Client #318, Epoch 3, #examples 322, Loss 2.3800134911681665, Accuracy 0.3181818238261974\n",
      "LOCAL TRAINING: Client #87, Epoch 1, #examples 117, Loss 3.6409838994344077, Accuracy 0.1333333346992731\n",
      "LOCAL TRAINING: Client #87, Epoch 2, #examples 117, Loss 2.947840392589569, Accuracy 0.24166667150954405\n",
      "LOCAL TRAINING: Client #87, Epoch 3, #examples 117, Loss 2.6656753520170846, Accuracy 0.3488095309585333\n",
      "LOCAL TRAINING: Client #358, Epoch 1, #examples 142, Loss 3.1257485230763753, Accuracy 0.30000000447034836\n",
      "LOCAL TRAINING: Client #358, Epoch 2, #examples 142, Loss 2.8116781949996947, Accuracy 0.34000000556310017\n",
      "LOCAL TRAINING: Client #358, Epoch 3, #examples 142, Loss 2.3960564851760866, Accuracy 0.48666667342185976\n",
      "LOCAL TRAINING: Client #42, Epoch 1, #examples 291, Loss 3.805022048950195, Accuracy 0.08000000193715096\n",
      "LOCAL TRAINING: Client #42, Epoch 2, #examples 291, Loss 3.16641681989034, Accuracy 0.1966666708389918\n",
      "LOCAL TRAINING: Client #42, Epoch 3, #examples 291, Loss 2.963389277458191, Accuracy 0.21333333775401114\n",
      "LOCAL TRAINING: Client #150, Epoch 1, #examples 139, Loss 3.5783584799085344, Accuracy 0.14285714605024882\n",
      "LOCAL TRAINING: Client #150, Epoch 2, #examples 139, Loss 3.028821281024388, Accuracy 0.25952381427798954\n",
      "LOCAL TRAINING: Client #150, Epoch 3, #examples 139, Loss 2.726616850921086, Accuracy 0.3333333395421505\n",
      "LOCAL TRAINING: Client #11, Epoch 1, #examples 90, Loss 3.7529575294918485, Accuracy 0.13333333532015482\n",
      "LOCAL TRAINING: Client #11, Epoch 2, #examples 90, Loss 3.219204584757487, Accuracy 0.25555556101931465\n",
      "LOCAL TRAINING: Client #11, Epoch 3, #examples 90, Loss 2.9976723194122314, Accuracy 0.3888888971673118\n",
      "LOCAL TRAINING: Client #37, Epoch 1, #examples 246, Loss 3.3110922622680663, Accuracy 0.19866667032241822\n",
      "LOCAL TRAINING: Client #37, Epoch 2, #examples 246, Loss 2.753968105316162, Accuracy 0.33333333969116213\n",
      "LOCAL TRAINING: Client #37, Epoch 3, #examples 246, Loss 2.3069966936111452, Accuracy 0.4213333386182785\n",
      "LOCAL TRAINING: Client #347, Epoch 1, #examples 154, Loss 3.392119973897934, Accuracy 0.1593750030733645\n",
      "LOCAL TRAINING: Client #347, Epoch 2, #examples 154, Loss 2.742537148296833, Accuracy 0.2843750035390258\n",
      "LOCAL TRAINING: Client #347, Epoch 3, #examples 154, Loss 2.4611948430538177, Accuracy 0.500000003259629\n",
      "LOCAL TRAINING: Client #350, Epoch 1, #examples 158, Loss 3.795993000268936, Accuracy 0.08125000167638063\n",
      "LOCAL TRAINING: Client #350, Epoch 2, #examples 158, Loss 3.3152306377887726, Accuracy 0.12187500298023224\n",
      "LOCAL TRAINING: Client #350, Epoch 3, #examples 158, Loss 3.055229440331459, Accuracy 0.21093750419095159\n",
      "LOCAL TRAINING: Client #349, Epoch 1, #examples 160, Loss 3.1290673166513443, Accuracy 0.23750000400468707\n",
      "LOCAL TRAINING: Client #349, Epoch 2, #examples 160, Loss 2.551916182041168, Accuracy 0.381250009406358\n",
      "LOCAL TRAINING: Client #349, Epoch 3, #examples 160, Loss 2.230291470885277, Accuracy 0.4375000079162419\n",
      "LOCAL TRAINING: Client #97, Epoch 1, #examples 162, Loss 3.1056997355292824, Accuracy 0.3235294192152865\n",
      "LOCAL TRAINING: Client #97, Epoch 2, #examples 162, Loss 2.757891423561994, Accuracy 0.38823530077934265\n",
      "LOCAL TRAINING: Client #97, Epoch 3, #examples 162, Loss 1.9807095562710482, Accuracy 0.5647058859467506\n",
      "LOCAL TRAINING: Client #119, Epoch 1, #examples 162, Loss 3.453105702119715, Accuracy 0.16470588524551952\n",
      "LOCAL TRAINING: Client #119, Epoch 2, #examples 162, Loss 2.9651335758321427, Accuracy 0.2764705941081047\n",
      "LOCAL TRAINING: Client #119, Epoch 3, #examples 162, Loss 2.532372278325698, Accuracy 0.35882353651172977\n",
      "LOCAL TRAINING: Client #341, Epoch 1, #examples 133, Loss 3.636105145726885, Accuracy 0.09285714477300644\n",
      "LOCAL TRAINING: Client #341, Epoch 2, #examples 133, Loss 2.8144521713256836, Accuracy 0.3333333432674408\n",
      "LOCAL TRAINING: Client #341, Epoch 3, #examples 133, Loss 2.247451526778085, Accuracy 0.4976190562759127\n",
      "LOCAL TRAINING: Client #5, Epoch 1, #examples 124, Loss 3.739699308688824, Accuracy 0.11538461653085855\n",
      "LOCAL TRAINING: Client #5, Epoch 2, #examples 124, Loss 3.087801144673274, Accuracy 0.2269230828835414\n",
      "LOCAL TRAINING: Client #5, Epoch 3, #examples 124, Loss 2.8984580773573656, Accuracy 0.2576923123919047\n",
      "LOCAL TRAINING: Client #69, Epoch 1, #examples 324, Loss 3.0364528569308193, Accuracy 0.24545455091830456\n",
      "LOCAL TRAINING: Client #69, Epoch 2, #examples 324, Loss 2.2853253068345967, Accuracy 0.3954545532663663\n",
      "LOCAL TRAINING: Client #69, Epoch 3, #examples 324, Loss 1.712557408845786, Accuracy 0.5409090943408735\n",
      "LOCAL TRAINING: Client #23, Epoch 1, #examples 272, Loss 3.6217258146830966, Accuracy 0.12500000266092165\n",
      "LOCAL TRAINING: Client #23, Epoch 2, #examples 272, Loss 2.921415533338274, Accuracy 0.2535714355430433\n",
      "LOCAL TRAINING: Client #23, Epoch 3, #examples 272, Loss 2.6333886682987213, Accuracy 0.3178571497223207\n",
      "LOCAL TRAINING: Client #1, Epoch 1, #examples 134, Loss 3.052861145564488, Accuracy 0.23571429029107094\n",
      "LOCAL TRAINING: Client #1, Epoch 2, #examples 134, Loss 2.079824847834451, Accuracy 0.4607142944421087\n",
      "LOCAL TRAINING: Client #1, Epoch 3, #examples 134, Loss 1.9031761033194405, Accuracy 0.5321428605488369\n",
      "LOCAL TRAINING: Client #353, Epoch 1, #examples 157, Loss 3.4962088316679, Accuracy 0.15000000409781933\n",
      "LOCAL TRAINING: Client #353, Epoch 2, #examples 157, Loss 2.9817205369472504, Accuracy 0.2803571498952806\n",
      "LOCAL TRAINING: Client #353, Epoch 3, #examples 157, Loss 2.6375655233860016, Accuracy 0.37232143757864833\n",
      "LOCAL TRAINING: Client #264, Epoch 1, #examples 291, Loss 3.248466420173645, Accuracy 0.17666667128602664\n",
      "LOCAL TRAINING: Client #264, Epoch 2, #examples 291, Loss 2.6186529795328775, Accuracy 0.31000000685453416\n",
      "LOCAL TRAINING: Client #264, Epoch 3, #examples 291, Loss 4.153943196932475, Accuracy 0.033333333830038704\n",
      "LOCAL TRAINING: Client #224, Epoch 1, #examples 161, Loss 3.0639534697813144, Accuracy 0.25294118199278326\n",
      "LOCAL TRAINING: Client #224, Epoch 2, #examples 161, Loss 2.6872775975395653, Accuracy 0.3176470644333783\n",
      "LOCAL TRAINING: Client #224, Epoch 3, #examples 161, Loss 2.4707751624724446, Accuracy 0.3529411852359772\n",
      "LOCAL TRAINING: Client #77, Epoch 1, #examples 164, Loss 3.244730739032521, Accuracy 0.16470588480725007\n",
      "LOCAL TRAINING: Client #77, Epoch 2, #examples 164, Loss 2.5523468326119816, Accuracy 0.39705883097999234\n",
      "LOCAL TRAINING: Client #77, Epoch 3, #examples 164, Loss 2.257428625050713, Accuracy 0.47647059226737304\n",
      "LOCAL TRAINING: Client #165, Epoch 1, #examples 351, Loss 3.248929109838274, Accuracy 0.18055555928084585\n",
      "LOCAL TRAINING: Client #165, Epoch 2, #examples 351, Loss 2.982777966393365, Accuracy 0.22500000418060356\n",
      "LOCAL TRAINING: Client #165, Epoch 3, #examples 351, Loss 2.183635026216507, Accuracy 0.41666667266852325\n",
      "LOCAL TRAINING: Client #245, Epoch 1, #examples 151, Loss 2.9857472628355026, Accuracy 0.19375000428408384\n",
      "LOCAL TRAINING: Client #245, Epoch 2, #examples 151, Loss 2.993789419531822, Accuracy 0.23125000344589353\n",
      "LOCAL TRAINING: Client #245, Epoch 3, #examples 151, Loss 2.476882368326187, Accuracy 0.3437500046566129\n",
      "LOCAL TRAINING: Client #223, Epoch 1, #examples 127, Loss 3.386376270881066, Accuracy 0.2175824218071424\n",
      "LOCAL TRAINING: Client #223, Epoch 2, #examples 127, Loss 2.627732487825247, Accuracy 0.34175824660521287\n",
      "LOCAL TRAINING: Client #223, Epoch 3, #examples 127, Loss 2.452399107126089, Accuracy 0.3912087965470094\n",
      "LOCAL TRAINING: Client #283, Epoch 1, #examples 270, Loss 3.7559142642550998, Accuracy 0.10370370552495674\n",
      "LOCAL TRAINING: Client #283, Epoch 2, #examples 270, Loss 3.185189441398338, Accuracy 0.2148148191195947\n",
      "LOCAL TRAINING: Client #283, Epoch 3, #examples 270, Loss 2.720172736379835, Accuracy 0.348148154715697\n",
      "LOCAL TRAINING: Client #331, Epoch 1, #examples 162, Loss 3.1843269993277157, Accuracy 0.24705882852568345\n",
      "LOCAL TRAINING: Client #331, Epoch 2, #examples 162, Loss 2.3421818508821377, Accuracy 0.4470588279997601\n",
      "LOCAL TRAINING: Client #331, Epoch 3, #examples 162, Loss 2.1857736461302815, Accuracy 0.464705888839329\n",
      "LOCAL TRAINING: Client #309, Epoch 1, #examples 149, Loss 2.993334404627482, Accuracy 0.2607407440741857\n",
      "LOCAL TRAINING: Client #309, Epoch 2, #examples 149, Loss 2.2857419729232786, Accuracy 0.4222222288449605\n",
      "LOCAL TRAINING: Client #309, Epoch 3, #examples 149, Loss 1.9834361632664999, Accuracy 0.4696296374003092\n",
      "LOCAL TRAINING: Client #157, Epoch 1, #examples 144, Loss 3.638121318817139, Accuracy 0.07333333442608515\n",
      "LOCAL TRAINING: Client #157, Epoch 2, #examples 144, Loss 3.0206946849823, Accuracy 0.27666667103767395\n",
      "LOCAL TRAINING: Client #157, Epoch 3, #examples 144, Loss 2.757947540283203, Accuracy 0.3366666744152705\n",
      "LOCAL TRAINING: Client #27, Epoch 1, #examples 256, Loss 3.2724924041674686, Accuracy 0.17820513191131446\n",
      "LOCAL TRAINING: Client #27, Epoch 2, #examples 256, Loss 2.635674293224628, Accuracy 0.3012820594012737\n",
      "LOCAL TRAINING: Client #27, Epoch 3, #examples 256, Loss 2.2230820747522206, Accuracy 0.38461538977347887\n",
      "LOCAL TRAINING: Client #329, Epoch 1, #examples 155, Loss 3.3622383177280426, Accuracy 0.20625000493600965\n",
      "LOCAL TRAINING: Client #329, Epoch 2, #examples 155, Loss 2.521044820547104, Accuracy 0.4312500115483999\n",
      "LOCAL TRAINING: Client #329, Epoch 3, #examples 155, Loss 2.3241453021764755, Accuracy 0.47500000754371285\n",
      "LOCAL TRAINING: Client #175, Epoch 1, #examples 347, Loss 3.1914228303091865, Accuracy 0.20938775901283538\n",
      "LOCAL TRAINING: Client #175, Epoch 2, #examples 347, Loss 2.359940569741385, Accuracy 0.3636734768748283\n",
      "LOCAL TRAINING: Client #175, Epoch 3, #examples 347, Loss 1.768981863771166, Accuracy 0.4975510252373559\n",
      "LOCAL TRAINING: Client #204, Epoch 1, #examples 269, Loss 3.6101034305713795, Accuracy 0.1263374509634795\n",
      "LOCAL TRAINING: Client #204, Epoch 2, #examples 269, Loss 2.9537269406848483, Accuracy 0.21234568263645526\n",
      "LOCAL TRAINING: Client #204, Epoch 3, #examples 269, Loss 2.50117685618224, Accuracy 0.3082304588622517\n",
      "LOCAL TRAINING: Client #272, Epoch 1, #examples 330, Loss 3.815783674066717, Accuracy 0.09090909248951709\n",
      "LOCAL TRAINING: Client #272, Epoch 2, #examples 330, Loss 2.9344914609735664, Accuracy 0.22727273088512998\n",
      "LOCAL TRAINING: Client #272, Epoch 3, #examples 330, Loss 2.374875960928021, Accuracy 0.375757584066102\n",
      "LOCAL TRAINING: Client #142, Epoch 1, #examples 96, Loss 3.3353770971298218, Accuracy 0.24333333745598792\n",
      "LOCAL TRAINING: Client #142, Epoch 2, #examples 96, Loss 2.5307847023010255, Accuracy 0.36000000312924385\n",
      "LOCAL TRAINING: Client #142, Epoch 3, #examples 96, Loss 2.2375261425971984, Accuracy 0.4133333399891853\n",
      "LOCAL TRAINING: Client #19, Epoch 1, #examples 156, Loss 3.294262260198593, Accuracy 0.1854166709817946\n",
      "LOCAL TRAINING: Client #19, Epoch 2, #examples 156, Loss 2.7952533587813377, Accuracy 0.3583333380520344\n",
      "LOCAL TRAINING: Client #19, Epoch 3, #examples 156, Loss 2.3107283413410187, Accuracy 0.4895833386108279\n",
      "LOCAL TRAINING: Client #45, Epoch 1, #examples 317, Loss 3.525778703391552, Accuracy 0.1263392884284258\n",
      "LOCAL TRAINING: Client #45, Epoch 2, #examples 317, Loss 2.7529081627726555, Accuracy 0.30000000656582415\n",
      "LOCAL TRAINING: Client #45, Epoch 3, #examples 317, Loss 2.2167174741625786, Accuracy 0.44419643422588706\n",
      "LOCAL TRAINING: Client #88, Epoch 1, #examples 30, Loss 4.323136727015178, Accuracy 0.0\n",
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      "LOCAL TRAINING: Client #340, Epoch 1, #examples 162, Loss 3.8279182069441853, Accuracy 0.10000000192838557\n",
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      "LOCAL TRAINING: Client #340, Epoch 3, #examples 162, Loss 2.6821372018140903, Accuracy 0.3117647087749313\n",
      "LOCAL TRAINING: Client #326, Epoch 1, #examples 162, Loss 3.2924959028468415, Accuracy 0.1823529443320106\n",
      "LOCAL TRAINING: Client #326, Epoch 2, #examples 162, Loss 2.4700547036002662, Accuracy 0.4470588284380296\n",
      "LOCAL TRAINING: Client #326, Epoch 3, #examples 162, Loss 2.1327664431403663, Accuracy 0.5588235399302315\n",
      "LOCAL TRAINING: Client #61, Epoch 1, #examples 163, Loss 3.5012015735401825, Accuracy 0.17254902334774241\n",
      "LOCAL TRAINING: Client #61, Epoch 2, #examples 163, Loss 2.9021745990304386, Accuracy 0.25686275038649053\n",
      "LOCAL TRAINING: Client #61, Epoch 3, #examples 163, Loss 2.5038505231632904, Accuracy 0.386274516582489\n",
      "LOCAL TRAINING: Client #271, Epoch 1, #examples 363, Loss 3.3428501567325077, Accuracy 0.1765765807515866\n",
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      "LOCAL TRAINING: Client #271, Epoch 3, #examples 363, Loss 2.0062723900820756, Accuracy 0.4639639707433211\n",
      "LOCAL TRAINING: Client #254, Epoch 1, #examples 356, Loss 3.3703806400299072, Accuracy 0.19351852416164345\n",
      "LOCAL TRAINING: Client #254, Epoch 2, #examples 356, Loss 2.5834026535352073, Accuracy 0.3407407458871603\n",
      "LOCAL TRAINING: Client #254, Epoch 3, #examples 356, Loss 2.11912240087986, Accuracy 0.417592600815826\n",
      "LOCAL TRAINING: Client #317, Epoch 1, #examples 352, Loss 3.5516447093751697, Accuracy 0.11388889099988672\n",
      "LOCAL TRAINING: Client #317, Epoch 2, #examples 352, Loss 3.087851517730289, Accuracy 0.17222222540941504\n",
      "LOCAL TRAINING: Client #317, Epoch 3, #examples 352, Loss 2.516394015815523, Accuracy 0.363888896173901\n",
      "LOCAL TRAINING: Client #366, Epoch 1, #examples 134, Loss 2.950592279434204, Accuracy 0.2321428619325161\n",
      "LOCAL TRAINING: Client #366, Epoch 2, #examples 134, Loss 2.4150586298533847, Accuracy 0.3535714325095926\n",
      "LOCAL TRAINING: Client #366, Epoch 3, #examples 134, Loss 2.0281652978488376, Accuracy 0.4428571531815188\n",
      "LOCAL TRAINING: Client #216, Epoch 1, #examples 159, Loss 3.5574139207601547, Accuracy 0.12569444766268134\n",
      "LOCAL TRAINING: Client #216, Epoch 2, #examples 159, Loss 2.8454615622758865, Accuracy 0.290277783293277\n",
      "LOCAL TRAINING: Client #216, Epoch 3, #examples 159, Loss 2.4366263896226883, Accuracy 0.4097222313284874\n",
      "LOCAL TRAINING: Client #8, Epoch 1, #examples 128, Loss 3.45980690075801, Accuracy 0.16153846509181535\n",
      "LOCAL TRAINING: Client #8, Epoch 2, #examples 128, Loss 2.852830171585083, Accuracy 0.2826923131942749\n",
      "LOCAL TRAINING: Client #8, Epoch 3, #examples 128, Loss 2.523867808855497, Accuracy 0.3961538557822888\n",
      "LOCAL TRAINING: Client #81, Epoch 1, #examples 138, Loss 3.7141885416848317, Accuracy 0.15357143059372902\n",
      "LOCAL TRAINING: Client #81, Epoch 2, #examples 138, Loss 3.0983834266662598, Accuracy 0.21428571747882025\n",
      "LOCAL TRAINING: Client #81, Epoch 3, #examples 138, Loss 2.7150428209986006, Accuracy 0.36607143548982485\n",
      "LOCAL TRAINING: Client #355, Epoch 1, #examples 163, Loss 3.402752665912404, Accuracy 0.13529412053963719\n",
      "LOCAL TRAINING: Client #355, Epoch 2, #examples 163, Loss 2.75648271336275, Accuracy 0.27843137699015\n",
      "LOCAL TRAINING: Client #355, Epoch 3, #examples 163, Loss 2.3430373318055095, Accuracy 0.4843137308078654\n",
      "LOCAL TRAINING: Client #246, Epoch 1, #examples 159, Loss 3.4553822427988052, Accuracy 0.1944444472901523\n",
      "LOCAL TRAINING: Client #246, Epoch 2, #examples 159, Loss 2.7786998823285103, Accuracy 0.31458333879709244\n",
      "LOCAL TRAINING: Client #246, Epoch 3, #examples 159, Loss 2.3623246625065804, Accuracy 0.42847222881391644\n",
      "LOCAL TRAINING: Client #343, Epoch 1, #examples 153, Loss 3.2879405170679092, Accuracy 0.18125000270083547\n",
      "LOCAL TRAINING: Client #343, Epoch 2, #examples 153, Loss 2.524213783442974, Accuracy 0.3645833386108279\n",
      "LOCAL TRAINING: Client #343, Epoch 3, #examples 153, Loss 2.1534719094634056, Accuracy 0.4895833400078118\n",
      "LOCAL TRAINING: Client #330, Epoch 1, #examples 163, Loss 3.097347203422995, Accuracy 0.23529412509763942\n",
      "LOCAL TRAINING: Client #330, Epoch 2, #examples 163, Loss 2.701911274124594, Accuracy 0.3843137288794798\n",
      "LOCAL TRAINING: Client #330, Epoch 3, #examples 163, Loss 2.535072452881757, Accuracy 0.37843137848026615\n",
      "LOCAL TRAINING: Client #52, Epoch 1, #examples 333, Loss 3.507246024468366, Accuracy 0.1500000033308478\n",
      "LOCAL TRAINING: Client #52, Epoch 2, #examples 333, Loss 2.624684190048891, Accuracy 0.31078432040179477\n",
      "LOCAL TRAINING: Client #52, Epoch 3, #examples 333, Loss 2.094782657483045, Accuracy 0.4264705943710664\n",
      "LOCAL TRAINING: Client #123, Epoch 1, #examples 162, Loss 3.4155123233795166, Accuracy 0.15882353309322805\n",
      "LOCAL TRAINING: Client #123, Epoch 2, #examples 162, Loss 3.036755919456482, Accuracy 0.20000000473331003\n",
      "LOCAL TRAINING: Client #123, Epoch 3, #examples 162, Loss 2.718158988391652, Accuracy 0.32941177136757793\n",
      "LOCAL TRAINING: Client #235, Epoch 1, #examples 304, Loss 3.4029952095400904, Accuracy 0.1177419378392158\n",
      "LOCAL TRAINING: Client #235, Epoch 2, #examples 304, Loss 2.59565467603745, Accuracy 0.33064516753919665\n",
      "LOCAL TRAINING: Client #235, Epoch 3, #examples 304, Loss 2.036456811812616, Accuracy 0.40967742762257975\n",
      "LOCAL TRAINING: Client #163, Epoch 1, #examples 278, Loss 3.689447658402579, Accuracy 0.11607143016798156\n",
      "LOCAL TRAINING: Client #163, Epoch 2, #examples 278, Loss 3.0004932624953136, Accuracy 0.24196429018463408\n",
      "LOCAL TRAINING: Client #163, Epoch 3, #examples 278, Loss 2.463387910808836, Accuracy 0.3776785763246672\n",
      "LOCAL TRAINING: Client #40, Epoch 1, #examples 302, Loss 3.3491249392109532, Accuracy 0.17419355194414815\n",
      "LOCAL TRAINING: Client #40, Epoch 2, #examples 302, Loss 2.4697914931081955, Accuracy 0.3741935537226738\n",
      "LOCAL TRAINING: Client #40, Epoch 3, #examples 302, Loss 1.8260830025519095, Accuracy 0.5096774247865523\n",
      "LOCAL TRAINING: Client #132, Epoch 1, #examples 236, Loss 3.556769013404846, Accuracy 0.12777778040617704\n",
      "LOCAL TRAINING: Client #132, Epoch 2, #examples 236, Loss 3.1647574603557587, Accuracy 0.2152777829517921\n",
      "LOCAL TRAINING: Client #132, Epoch 3, #examples 236, Loss 2.7870368361473083, Accuracy 0.2986111165955663\n",
      "LOCAL TRAINING: Client #314, Epoch 1, #examples 154, Loss 3.6615597754716873, Accuracy 0.08750000223517418\n",
      "LOCAL TRAINING: Client #314, Epoch 2, #examples 154, Loss 3.150015711784363, Accuracy 0.140625003259629\n",
      "LOCAL TRAINING: Client #314, Epoch 3, #examples 154, Loss 2.8616321310400963, Accuracy 0.24062500335276127\n",
      "LOCAL TRAINING: Client #10, Epoch 1, #examples 57, Loss 4.120576659838359, Accuracy 0.14761905123790106\n",
      "LOCAL TRAINING: Client #10, Epoch 2, #examples 57, Loss 3.341628630956014, Accuracy 0.13333333656191826\n",
      "LOCAL TRAINING: Client #10, Epoch 3, #examples 57, Loss 3.0394728581110635, Accuracy 0.23095238829652467\n",
      "CLUSTER: 1.3, MEAN TEST ACCURACY: 0.3427523312624544, 10th percentile: 0.13851351886987687, 90th percentile: 0.5555555820465088, % clients reaching target accuracy: 0.002777777777777778\n",
      "GLOBAL WEIGHTS DELTA NORM: 2.00439453125\n",
      "413s elapsed\n",
      "Training complete in 1 communication rounds\n",
      "\n",
      "Running 1 round of training on all client in cluster to obtain client weight updates\n",
      "LOCAL TRAINING: Client #0, Epoch 1, #examples 136, Loss 2.4242738485336304, Accuracy 0.46190477322254864\n",
      "LOCAL TRAINING: Client #0, Epoch 2, #examples 136, Loss 1.7876572438648768, Accuracy 0.6071428635290691\n",
      "LOCAL TRAINING: Client #0, Epoch 3, #examples 136, Loss 1.3684451026575906, Accuracy 0.6785714243139539\n",
      "LOCAL TRAINING: Client #1, Epoch 1, #examples 134, Loss 2.100121557712555, Accuracy 0.4928571491369179\n",
      "LOCAL TRAINING: Client #1, Epoch 2, #examples 134, Loss 1.626407699925559, Accuracy 0.6035714362348829\n",
      "LOCAL TRAINING: Client #1, Epoch 3, #examples 134, Loss 1.2844071984291077, Accuracy 0.6642857151372092\n",
      "LOCAL TRAINING: Client #2, Epoch 1, #examples 153, Loss 2.2797421365976334, Accuracy 0.36458334047347307\n",
      "LOCAL TRAINING: Client #2, Epoch 2, #examples 153, Loss 1.9956230074167252, Accuracy 0.5020833434537053\n",
      "LOCAL TRAINING: Client #2, Epoch 3, #examples 153, Loss 1.604733221232891, Accuracy 0.5500000081956387\n",
      "LOCAL TRAINING: Client #3, Epoch 1, #examples 154, Loss 2.4713069945573807, Accuracy 0.40625000838190317\n",
      "LOCAL TRAINING: Client #3, Epoch 2, #examples 154, Loss 2.1827912479639053, Accuracy 0.42500000447034836\n",
      "LOCAL TRAINING: Client #3, Epoch 3, #examples 154, Loss 1.8138206750154495, Accuracy 0.5000000093132257\n",
      "LOCAL TRAINING: Client #4, Epoch 1, #examples 156, Loss 2.9105244800448418, Accuracy 0.2812500046566129\n",
      "LOCAL TRAINING: Client #4, Epoch 2, #examples 156, Loss 2.2828214317560196, Accuracy 0.38958333898335695\n",
      "LOCAL TRAINING: Client #4, Epoch 3, #examples 156, Loss 2.1541696786880493, Accuracy 0.4125000103376806\n",
      "LOCAL TRAINING: Client #5, Epoch 1, #examples 124, Loss 2.8062241260822, Accuracy 0.34230769826815677\n",
      "LOCAL TRAINING: Client #5, Epoch 2, #examples 124, Loss 2.5583399809323826, Accuracy 0.3269230838005359\n",
      "LOCAL TRAINING: Client #5, Epoch 3, #examples 124, Loss 2.3200110838963437, Accuracy 0.3884615439635057\n",
      "LOCAL TRAINING: Client #6, Epoch 1, #examples 141, Loss 2.414040279388428, Accuracy 0.49333333869775137\n",
      "LOCAL TRAINING: Client #6, Epoch 2, #examples 141, Loss 2.313397185007731, Accuracy 0.46000000834465027\n",
      "LOCAL TRAINING: Client #6, Epoch 3, #examples 141, Loss 3.62328356107076, Accuracy 0.1666666696468989\n",
      "LOCAL TRAINING: Client #7, Epoch 1, #examples 153, Loss 2.199629884213209, Accuracy 0.4500000053085387\n",
      "LOCAL TRAINING: Client #7, Epoch 2, #examples 153, Loss 1.6945884907618165, Accuracy 0.6062500076368451\n",
      "LOCAL TRAINING: Client #7, Epoch 3, #examples 153, Loss 1.3927269391715527, Accuracy 0.6625000033527613\n",
      "LOCAL TRAINING: Client #8, Epoch 1, #examples 128, Loss 2.5890202705676737, Accuracy 0.38269231697687733\n",
      "LOCAL TRAINING: Client #8, Epoch 2, #examples 128, Loss 2.18477096924415, Accuracy 0.49230770193613493\n",
      "LOCAL TRAINING: Client #8, Epoch 3, #examples 128, Loss 1.8990723995062022, Accuracy 0.5269230799033091\n",
      "LOCAL TRAINING: Client #9, Epoch 1, #examples 162, Loss 2.267185835277333, Accuracy 0.4941176500390558\n",
      "LOCAL TRAINING: Client #9, Epoch 2, #examples 162, Loss 1.7920308007913477, Accuracy 0.5823529467863195\n",
      "LOCAL TRAINING: Client #9, Epoch 3, #examples 162, Loss 1.3833146691322327, Accuracy 0.7058823599534876\n",
      "LOCAL TRAINING: Client #10, Epoch 1, #examples 57, Loss 2.7476645708084106, Accuracy 0.36190477137764293\n",
      "LOCAL TRAINING: Client #10, Epoch 2, #examples 57, Loss 2.1897650559743247, Accuracy 0.4785714348157247\n",
      "LOCAL TRAINING: Client #10, Epoch 3, #examples 57, Loss 2.1745678186416626, Accuracy 0.3547619084517161\n",
      "LOCAL TRAINING: Client #11, Epoch 1, #examples 90, Loss 2.8126456472608776, Accuracy 0.4333333406183455\n",
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      "LOCAL TRAINING: Client #12, Epoch 1, #examples 94, Loss 2.9592705965042114, Accuracy 0.27000000402331353\n",
      "LOCAL TRAINING: Client #12, Epoch 2, #examples 94, Loss 2.6413634538650514, Accuracy 0.30500000566244123\n",
      "LOCAL TRAINING: Client #12, Epoch 3, #examples 94, Loss 2.3927212595939635, Accuracy 0.3350000038743019\n",
      "LOCAL TRAINING: Client #13, Epoch 1, #examples 139, Loss 2.6304233244487216, Accuracy 0.4015873095818928\n",
      "LOCAL TRAINING: Client #13, Epoch 2, #examples 139, Loss 2.265552384512765, Accuracy 0.3880952442330973\n",
      "LOCAL TRAINING: Client #13, Epoch 3, #examples 139, Loss 2.012520466532026, Accuracy 0.4611111224762031\n",
      "LOCAL TRAINING: Client #14, Epoch 1, #examples 126, Loss 2.494202870589036, Accuracy 0.46666667266533923\n",
      "LOCAL TRAINING: Client #14, Epoch 2, #examples 126, Loss 1.9789479879232554, Accuracy 0.5820512874768331\n",
      "LOCAL TRAINING: Client #14, Epoch 3, #examples 126, Loss 1.8853837710160475, Accuracy 0.566666681606036\n",
      "LOCAL TRAINING: Client #15, Epoch 1, #examples 101, Loss 3.1497035676782783, Accuracy 0.26363636688752606\n",
      "LOCAL TRAINING: Client #15, Epoch 2, #examples 101, Loss 2.6081693172454834, Accuracy 0.2636363709514791\n",
      "LOCAL TRAINING: Client #15, Epoch 3, #examples 101, Loss 3.6633335677060215, Accuracy 0.17272727597843518\n",
      "LOCAL TRAINING: Client #16, Epoch 1, #examples 138, Loss 2.328720739909581, Accuracy 0.44821429146187647\n",
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      "LOCAL TRAINING: Client #16, Epoch 3, #examples 138, Loss 1.7005027404853277, Accuracy 0.576785717691694\n",
      "LOCAL TRAINING: Client #17, Epoch 1, #examples 134, Loss 2.4730867743492126, Accuracy 0.35000000574759077\n",
      "LOCAL TRAINING: Client #17, Epoch 2, #examples 134, Loss 2.040617993899754, Accuracy 0.48571429188762394\n",
      "LOCAL TRAINING: Client #17, Epoch 3, #examples 134, Loss 1.731967304434095, Accuracy 0.5750000072377068\n",
      "LOCAL TRAINING: Client #18, Epoch 1, #examples 107, Loss 2.5400717800313775, Accuracy 0.4558441679586064\n",
      "LOCAL TRAINING: Client #18, Epoch 2, #examples 107, Loss 2.1000551852312954, Accuracy 0.5285714417695999\n",
      "LOCAL TRAINING: Client #18, Epoch 3, #examples 107, Loss 1.8718682419170032, Accuracy 0.5155844268473712\n",
      "LOCAL TRAINING: Client #19, Epoch 1, #examples 156, Loss 2.393379718065262, Accuracy 0.46666667331010103\n",
      "LOCAL TRAINING: Client #19, Epoch 2, #examples 156, Loss 1.8698745369911194, Accuracy 0.6395833361893892\n",
      "LOCAL TRAINING: Client #19, Epoch 3, #examples 156, Loss 1.5410692542791367, Accuracy 0.6333333384245634\n",
      "LOCAL TRAINING: Client #20, Epoch 1, #examples 143, Loss 2.4691181739171344, Accuracy 0.42444444944461185\n",
      "LOCAL TRAINING: Client #20, Epoch 2, #examples 143, Loss 1.908927136659622, Accuracy 0.6000000079472859\n",
      "LOCAL TRAINING: Client #20, Epoch 3, #examples 143, Loss 1.6277079900105795, Accuracy 0.5977777858575185\n",
      "LOCAL TRAINING: Client #21, Epoch 1, #examples 155, Loss 2.560123398900032, Accuracy 0.375000006519258\n",
      "LOCAL TRAINING: Client #21, Epoch 2, #examples 155, Loss 2.294896923005581, Accuracy 0.39375000493600965\n",
      "LOCAL TRAINING: Client #21, Epoch 3, #examples 155, Loss 1.8039349168539047, Accuracy 0.5500000100582838\n",
      "LOCAL TRAINING: Client #22, Epoch 1, #examples 330, Loss 2.3492376840475835, Accuracy 0.3606060671083855\n",
      "LOCAL TRAINING: Client #22, Epoch 2, #examples 330, Loss 1.6742222598104766, Accuracy 0.542424249829668\n",
      "LOCAL TRAINING: Client #22, Epoch 3, #examples 330, Loss 1.2980532880985376, Accuracy 0.6727272768815359\n",
      "LOCAL TRAINING: Client #23, Epoch 1, #examples 272, Loss 2.7482376950127736, Accuracy 0.2750000054282801\n",
      "LOCAL TRAINING: Client #23, Epoch 2, #examples 272, Loss 2.22478095974241, Accuracy 0.4464285770165069\n",
      "LOCAL TRAINING: Client #23, Epoch 3, #examples 272, Loss 1.692251552428518, Accuracy 0.5607142938034875\n",
      "LOCAL TRAINING: Client #24, Epoch 1, #examples 359, Loss 2.8011337253782482, Accuracy 0.2370370433976253\n",
      "LOCAL TRAINING: Client #24, Epoch 2, #examples 359, Loss 2.022668957710266, Accuracy 0.46234568684465355\n",
      "LOCAL TRAINING: Client #24, Epoch 3, #examples 359, Loss 1.4362989481952455, Accuracy 0.6027777815858523\n",
      "LOCAL TRAINING: Client #25, Epoch 1, #examples 347, Loss 2.221733641624451, Accuracy 0.4138775580695697\n",
      "LOCAL TRAINING: Client #25, Epoch 2, #examples 347, Loss 1.5377515281949725, Accuracy 0.5902040932859693\n",
      "LOCAL TRAINING: Client #25, Epoch 3, #examples 347, Loss 1.054162276642663, Accuracy 0.6881632660116468\n",
      "LOCAL TRAINING: Client #26, Epoch 1, #examples 228, Loss 2.7211875604546587, Accuracy 0.2760869607977245\n",
      "LOCAL TRAINING: Client #26, Epoch 2, #examples 228, Loss 2.251248706942019, Accuracy 0.3695652228982552\n",
      "LOCAL TRAINING: Client #26, Epoch 3, #examples 228, Loss 1.7844445498093315, Accuracy 0.4934782625540443\n",
      "LOCAL TRAINING: Client #27, Epoch 1, #examples 256, Loss 2.435646598155682, Accuracy 0.3371794940187381\n",
      "LOCAL TRAINING: Client #27, Epoch 2, #examples 256, Loss 1.894023102063399, Accuracy 0.45897436571808964\n",
      "LOCAL TRAINING: Client #27, Epoch 3, #examples 256, Loss 1.5918967517522664, Accuracy 0.5551282127316182\n",
      "LOCAL TRAINING: Client #28, Epoch 1, #examples 308, Loss 2.3992410436753304, Accuracy 0.3766129074558135\n",
      "LOCAL TRAINING: Client #28, Epoch 2, #examples 308, Loss 1.7182880909212175, Accuracy 0.5661290424966043\n",
      "LOCAL TRAINING: Client #28, Epoch 3, #examples 308, Loss 1.3747091850926798, Accuracy 0.6209677438582143\n",
      "LOCAL TRAINING: Client #30, Epoch 1, #examples 216, Loss 2.8422123681415212, Accuracy 0.310606066476215\n",
      "LOCAL TRAINING: Client #30, Epoch 2, #examples 216, Loss 2.2202975262295115, Accuracy 0.4333333390002901\n",
      "LOCAL TRAINING: Client #30, Epoch 3, #examples 216, Loss 1.8026302348483692, Accuracy 0.4984848543324254\n",
      "LOCAL TRAINING: Client #31, Epoch 1, #examples 241, Loss 2.5586004114151, Accuracy 0.3120000061392784\n",
      "LOCAL TRAINING: Client #31, Epoch 2, #examples 241, Loss 2.1796802139282225, Accuracy 0.4280000054836273\n",
      "LOCAL TRAINING: Client #31, Epoch 3, #examples 241, Loss 1.602305953502655, Accuracy 0.612000002861023\n",
      "LOCAL TRAINING: Client #32, Epoch 1, #examples 112, Loss 2.2060068051020303, Accuracy 0.5250000084439913\n",
      "LOCAL TRAINING: Client #32, Epoch 2, #examples 112, Loss 2.0394781033198037, Accuracy 0.5166666731238365\n",
      "LOCAL TRAINING: Client #32, Epoch 3, #examples 112, Loss 1.491478865345319, Accuracy 0.6750000069538752\n",
      "LOCAL TRAINING: Client #33, Epoch 1, #examples 217, Loss 2.590544960715554, Accuracy 0.36298702216961165\n",
      "LOCAL TRAINING: Client #33, Epoch 2, #examples 217, Loss 2.0311846137046814, Accuracy 0.44935065744952724\n",
      "LOCAL TRAINING: Client #33, Epoch 3, #examples 217, Loss 1.6341209005225787, Accuracy 0.5577922165393829\n",
      "LOCAL TRAINING: Client #34, Epoch 1, #examples 224, Loss 2.5202023309210073, Accuracy 0.3565217457387758\n",
      "LOCAL TRAINING: Client #34, Epoch 2, #examples 224, Loss 2.0961672793263975, Accuracy 0.47826087733973627\n",
      "LOCAL TRAINING: Client #34, Epoch 3, #examples 224, Loss 1.5967666714087776, Accuracy 0.5413043570259343\n",
      "LOCAL TRAINING: Client #35, Epoch 1, #examples 294, Loss 2.3233259836832683, Accuracy 0.3933333394428094\n",
      "LOCAL TRAINING: Client #35, Epoch 2, #examples 294, Loss 1.795238345861435, Accuracy 0.521666669100523\n",
      "LOCAL TRAINING: Client #35, Epoch 3, #examples 294, Loss 1.3663600464661916, Accuracy 0.6283333371082942\n",
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      "LOCAL TRAINING: Client #339, Epoch 3, #examples 138, Loss 1.9806914670126778, Accuracy 0.5142857155629567\n",
      "LOCAL TRAINING: Client #340, Epoch 1, #examples 162, Loss 2.5396108697442448, Accuracy 0.3705882416928516\n",
      "LOCAL TRAINING: Client #340, Epoch 2, #examples 162, Loss 2.144126906114466, Accuracy 0.4941176513538641\n",
      "LOCAL TRAINING: Client #340, Epoch 3, #examples 162, Loss 1.8671679987626917, Accuracy 0.5588235333561897\n",
      "LOCAL TRAINING: Client #341, Epoch 1, #examples 133, Loss 2.5263202701296126, Accuracy 0.4238095304795674\n",
      "LOCAL TRAINING: Client #341, Epoch 2, #examples 133, Loss 1.803262621164322, Accuracy 0.5523809561772006\n",
      "LOCAL TRAINING: Client #341, Epoch 3, #examples 133, Loss 1.5799315571784973, Accuracy 0.633333336029734\n",
      "LOCAL TRAINING: Client #342, Epoch 1, #examples 163, Loss 2.1193401322645298, Accuracy 0.5450980435399448\n",
      "LOCAL TRAINING: Client #342, Epoch 2, #examples 163, Loss 1.6895764294792623, Accuracy 0.5980392221142264\n",
      "LOCAL TRAINING: Client #342, Epoch 3, #examples 163, Loss 1.371341792976155, Accuracy 0.674509816309985\n",
      "LOCAL TRAINING: Client #343, Epoch 1, #examples 153, Loss 2.0889081694185734, Accuracy 0.5375000033527613\n",
      "LOCAL TRAINING: Client #343, Epoch 2, #examples 153, Loss 1.5970413759350777, Accuracy 0.6583333406597376\n",
      "LOCAL TRAINING: Client #343, Epoch 3, #examples 153, Loss 1.405333749949932, Accuracy 0.6416666693985462\n",
      "LOCAL TRAINING: Client #344, Epoch 1, #examples 166, Loss 2.208567061844994, Accuracy 0.46078432132216063\n",
      "LOCAL TRAINING: Client #344, Epoch 2, #examples 166, Loss 1.9122131256496204, Accuracy 0.5313725585446638\n",
      "LOCAL TRAINING: Client #344, Epoch 3, #examples 166, Loss 1.597925280823427, Accuracy 0.5823529467863195\n",
      "LOCAL TRAINING: Client #345, Epoch 1, #examples 27, Loss 1.7163206338882446, Accuracy 0.4761904875437419\n",
      "LOCAL TRAINING: Client #345, Epoch 2, #examples 27, Loss 1.7449808518091838, Accuracy 0.5714285771052042\n",
      "LOCAL TRAINING: Client #345, Epoch 3, #examples 27, Loss 0.6824424068133036, Accuracy 0.7047619223594666\n",
      "LOCAL TRAINING: Client #346, Epoch 1, #examples 131, Loss 2.241640738078526, Accuracy 0.5000000063862119\n",
      "LOCAL TRAINING: Client #346, Epoch 2, #examples 131, Loss 1.9899009806769234, Accuracy 0.5642857157758304\n",
      "LOCAL TRAINING: Client #346, Epoch 3, #examples 131, Loss 2.246483734675816, Accuracy 0.5142857171595097\n",
      "LOCAL TRAINING: Client #347, Epoch 1, #examples 154, Loss 2.3572182431817055, Accuracy 0.443750006146729\n",
      "LOCAL TRAINING: Client #347, Epoch 2, #examples 154, Loss 2.140831459313631, Accuracy 0.47812500409781933\n",
      "LOCAL TRAINING: Client #347, Epoch 3, #examples 154, Loss 1.6042958460748196, Accuracy 0.6187500059604645\n",
      "LOCAL TRAINING: Client #348, Epoch 1, #examples 163, Loss 2.5223914174472584, Accuracy 0.4019607897190487\n",
      "LOCAL TRAINING: Client #348, Epoch 2, #examples 163, Loss 2.0562689164105583, Accuracy 0.480392167235122\n",
      "LOCAL TRAINING: Client #348, Epoch 3, #examples 163, Loss 1.8726494592778824, Accuracy 0.5666666701436043\n",
      "LOCAL TRAINING: Client #349, Epoch 1, #examples 160, Loss 2.325742870569229, Accuracy 0.49375000689178705\n",
      "LOCAL TRAINING: Client #349, Epoch 2, #examples 160, Loss 2.0081387013196945, Accuracy 0.5000000102445483\n",
      "LOCAL TRAINING: Client #349, Epoch 3, #examples 160, Loss 1.5874101147055626, Accuracy 0.5875000078231096\n",
      "LOCAL TRAINING: Client #350, Epoch 1, #examples 158, Loss 2.9414580315351486, Accuracy 0.2875000066123903\n",
      "LOCAL TRAINING: Client #350, Epoch 2, #examples 158, Loss 2.264719933271408, Accuracy 0.4781250078231096\n",
      "LOCAL TRAINING: Client #350, Epoch 3, #examples 158, Loss 2.0304315239191055, Accuracy 0.5265625054016709\n",
      "LOCAL TRAINING: Client #351, Epoch 1, #examples 153, Loss 2.3159264884889126, Accuracy 0.48125000670552254\n",
      "LOCAL TRAINING: Client #351, Epoch 2, #examples 153, Loss 2.0372193939983845, Accuracy 0.5020833360031247\n",
      "LOCAL TRAINING: Client #351, Epoch 3, #examples 153, Loss 1.7192253395915031, Accuracy 0.5791666721925139\n",
      "LOCAL TRAINING: Client #352, Epoch 1, #examples 161, Loss 2.739644807927749, Accuracy 0.38235294862705116\n",
      "LOCAL TRAINING: Client #352, Epoch 2, #examples 161, Loss 2.6582641321070053, Accuracy 0.3705882364336182\n",
      "LOCAL TRAINING: Client #352, Epoch 3, #examples 161, Loss 1.9418212806477266, Accuracy 0.6058823571485632\n",
      "LOCAL TRAINING: Client #353, Epoch 1, #examples 157, Loss 2.6554647386074066, Accuracy 0.35446429438889027\n",
      "LOCAL TRAINING: Client #353, Epoch 2, #examples 157, Loss 2.221555892378092, Accuracy 0.5267857229337096\n",
      "LOCAL TRAINING: Client #353, Epoch 3, #examples 157, Loss 2.058638706803322, Accuracy 0.4982142955996096\n",
      "LOCAL TRAINING: Client #354, Epoch 1, #examples 165, Loss 2.5696702704710117, Accuracy 0.4176470663617639\n",
      "LOCAL TRAINING: Client #354, Epoch 2, #examples 165, Loss 2.159314849797417, Accuracy 0.48823530183118935\n",
      "LOCAL TRAINING: Client #354, Epoch 3, #examples 165, Loss 1.7862565552487093, Accuracy 0.5764705941957586\n",
      "LOCAL TRAINING: Client #355, Epoch 1, #examples 163, Loss 2.4229075838537777, Accuracy 0.41568628391798806\n",
      "LOCAL TRAINING: Client #355, Epoch 2, #examples 163, Loss 2.0455814670113956, Accuracy 0.5588235324796509\n",
      "LOCAL TRAINING: Client #355, Epoch 3, #examples 163, Loss 1.7162573302493376, Accuracy 0.617647062329685\n",
      "LOCAL TRAINING: Client #356, Epoch 1, #examples 108, Loss 3.08135601607236, Accuracy 0.29318182509053836\n",
      "LOCAL TRAINING: Client #356, Epoch 2, #examples 108, Loss 2.6894228783520786, Accuracy 0.3522727299820293\n",
      "LOCAL TRAINING: Client #356, Epoch 3, #examples 108, Loss 2.2611067186702383, Accuracy 0.4545454599640586\n",
      "LOCAL TRAINING: Client #357, Epoch 1, #examples 148, Loss 2.524826916058858, Accuracy 0.46000000834465027\n",
      "LOCAL TRAINING: Client #357, Epoch 2, #examples 148, Loss 2.1294660210609435, Accuracy 0.5433333377043407\n",
      "LOCAL TRAINING: Client #357, Epoch 3, #examples 148, Loss 1.8423550446828207, Accuracy 0.5783333321412404\n",
      "LOCAL TRAINING: Client #358, Epoch 1, #examples 142, Loss 2.5860027074813843, Accuracy 0.4200000062584877\n",
      "LOCAL TRAINING: Client #358, Epoch 2, #examples 142, Loss 2.228463967641195, Accuracy 0.5066666752099991\n",
      "LOCAL TRAINING: Client #358, Epoch 3, #examples 142, Loss 2.081299924850464, Accuracy 0.5600000033775966\n",
      "LOCAL TRAINING: Client #359, Epoch 1, #examples 117, Loss 2.927449186642965, Accuracy 0.3392857226232688\n",
      "LOCAL TRAINING: Client #359, Epoch 2, #examples 117, Loss 2.5375622510910034, Accuracy 0.40714286391933757\n",
      "LOCAL TRAINING: Client #359, Epoch 3, #examples 117, Loss 2.23333403468132, Accuracy 0.4773809611797333\n",
      "LOCAL TRAINING: Client #360, Epoch 1, #examples 126, Loss 2.609710619999812, Accuracy 0.4282051307650713\n",
      "LOCAL TRAINING: Client #360, Epoch 2, #examples 126, Loss 2.0050461063018212, Accuracy 0.5128205235187824\n",
      "LOCAL TRAINING: Client #360, Epoch 3, #examples 126, Loss 1.7776140066293569, Accuracy 0.5615384739178878\n",
      "LOCAL TRAINING: Client #361, Epoch 1, #examples 105, Loss 1.8236683715473523, Accuracy 0.4090909158641642\n",
      "LOCAL TRAINING: Client #361, Epoch 2, #examples 105, Loss 1.0006932345303623, Accuracy 0.6727272705598311\n",
      "LOCAL TRAINING: Client #361, Epoch 3, #examples 105, Loss 0.5983322073112834, Accuracy 0.7909090898253701\n",
      "LOCAL TRAINING: Client #362, Epoch 1, #examples 144, Loss 2.53783974647522, Accuracy 0.4333333363135656\n",
      "LOCAL TRAINING: Client #362, Epoch 2, #examples 144, Loss 1.9601362069447836, Accuracy 0.6100000043710073\n",
      "LOCAL TRAINING: Client #362, Epoch 3, #examples 144, Loss 1.67328482568264, Accuracy 0.5733333379030228\n",
      "LOCAL TRAINING: Client #363, Epoch 1, #examples 154, Loss 1.9880743026733398, Accuracy 0.5906250029802322\n",
      "LOCAL TRAINING: Client #363, Epoch 2, #examples 154, Loss 1.4764953926205635, Accuracy 0.6750000007450581\n",
      "LOCAL TRAINING: Client #363, Epoch 3, #examples 154, Loss 1.4637384172528982, Accuracy 0.6687500029802322\n",
      "LOCAL TRAINING: Client #364, Epoch 1, #examples 144, Loss 2.2013189514478047, Accuracy 0.43666667491197586\n",
      "LOCAL TRAINING: Client #364, Epoch 2, #examples 144, Loss 1.8230127811431884, Accuracy 0.5233333388964335\n",
      "LOCAL TRAINING: Client #364, Epoch 3, #examples 144, Loss 1.4153396844863892, Accuracy 0.6133333325386048\n",
      "LOCAL TRAINING: Client #365, Epoch 1, #examples 144, Loss 2.502811153729757, Accuracy 0.34000000754992166\n",
      "LOCAL TRAINING: Client #365, Epoch 2, #examples 144, Loss 2.174214990933736, Accuracy 0.4833333412806193\n",
      "LOCAL TRAINING: Client #365, Epoch 3, #examples 144, Loss 1.646755329767863, Accuracy 0.5433333386977514\n",
      "LOCAL TRAINING: Client #366, Epoch 1, #examples 134, Loss 2.320252401488168, Accuracy 0.44642857568604605\n",
      "LOCAL TRAINING: Client #366, Epoch 2, #examples 134, Loss 1.7017232775688171, Accuracy 0.5964285688740867\n",
      "LOCAL TRAINING: Client #366, Epoch 3, #examples 134, Loss 1.4425506038325173, Accuracy 0.6285714272941861\n",
      "[  0   0   1   1   1   1 105   0   1   0   1   1   1   1   0 131   1   1\n",
      "   1   1 158   1  86 161  99 133 100 103 159 134 127   1 117 128  89 110\n",
      " 120  63 123 157 102  91  95 118 139  87 111 124   1 125  83   1   1   1\n",
      " 155 135   1   1   1   1   1 113   3 112   1  96 108 156 104 121 151   1\n",
      "   1   8   8   1   1   1   1   1   1   1   1   1   1   1   1   1   1   1\n",
      "   1   1   1   1   0   0   8   1   1   1 162   1   1   1   1   1   1   1\n",
      "   1   1   1   1   1   1   1 160   1 150   1   1   1   1 149   1   1  88\n",
      "  55 109 141 129  66 140   1 122  92 137   1   1   1   1   1   4   1   1\n",
      "   1   1   0   1   1   1  37   1 126   1   1  93 153  74   1 152  45   1\n",
      "  81   1  69 154 115 116 101 119  58 130 143 106  49  51  85   1   1 146\n",
      "   1   1   1  79   1   1   1   1   1   1  17   1   1   1 142   1   1   1\n",
      "  84  64 138  57 136 107  59  54  77  97 114   1 144  78   1   1   0   1\n",
      "   1   1 132   4   1   4   1   0   1   0   1   1   1 145  43  75 147  28\n",
      "  90  42  47  52  98   1   0  67   1   1   0   1  76  70   1   1  53  61\n",
      "  94  80  71  25 148  65   1  41  48  44  56  21  27  46  62  68  82  72\n",
      "   1  50  60  26  32  40  13   1  24  35  30   1   1   1  34   4   1   1\n",
      "   1   1   1   1  20  23  22  31  10  29   1  15   1   1   1   0   1   1\n",
      "   8   1   1  11  39  33  19  14   9  16   6  12   3   5   1   1   1   0\n",
      "   1   0   2   1   0   1   1   1   1  73   7   1   1   1   1  36   1   1\n",
      "   1   1   1   1   1   1   1   1   1   0   1   1   1  18  18  38  17  37]\n",
      "163\n",
      "Cluster 1.3 will not be split any further\n",
      "\n",
      "Running FCFL with 1 client idxs: [136]\n",
      "Running learning for 1 communication rounds\n",
      "\n",
      "Communication round 1\n",
      "LOCAL TRAINING: Client #136, Epoch 1, #examples 342, Loss 1.927261143071311, Accuracy 0.4971428628478731\n",
      "LOCAL TRAINING: Client #136, Epoch 2, #examples 342, Loss 1.302115706886564, Accuracy 0.654285718713488\n",
      "LOCAL TRAINING: Client #136, Epoch 3, #examples 342, Loss 0.811852034500667, Accuracy 0.7799999960831233\n",
      "CLUSTER: 1.4, MEAN TEST ACCURACY: 0.2068965584039688, 10th percentile: 0.2068965584039688, 90th percentile: 0.2068965584039688, % clients reaching target accuracy: 0.0\n",
      "GLOBAL WEIGHTS DELTA NORM: 3.9944217205047607\n",
      "718s elapsed\n",
      "Training complete in 1 communication rounds\n",
      "\n",
      "Running 1 round of training on all client in cluster to obtain client weight updates\n",
      "LOCAL TRAINING: Client #136, Epoch 1, #examples 342, Loss 0.6176639318466186, Accuracy 0.8171428561210632\n",
      "LOCAL TRAINING: Client #136, Epoch 2, #examples 342, Loss 0.457708801222699, Accuracy 0.8485714265278408\n",
      "LOCAL TRAINING: Client #136, Epoch 3, #examples 342, Loss 0.3266952888241836, Accuracy 0.9171428493091038\n",
      "Cluster 1.4 will not be split any further\n",
      "\n",
      "Running FCFL with 1 client idxs: [29]\n",
      "Running learning for 1 communication rounds\n",
      "\n",
      "Communication round 1\n",
      "LOCAL TRAINING: Client #29, Epoch 1, #examples 312, Loss 1.7692295890301466, Accuracy 0.559375002514571\n",
      "LOCAL TRAINING: Client #29, Epoch 2, #examples 312, Loss 1.144331632182002, Accuracy 0.6843750062398612\n",
      "LOCAL TRAINING: Client #29, Epoch 3, #examples 312, Loss 0.869970350060612, Accuracy 0.7749999994412065\n",
      "CLUSTER: 1.5, MEAN TEST ACCURACY: 0.1111111119389534, 10th percentile: 0.1111111119389534, 90th percentile: 0.1111111119389534, % clients reaching target accuracy: 0.0\n",
      "GLOBAL WEIGHTS DELTA NORM: 3.5797665119171143\n",
      "720s elapsed\n",
      "Training complete in 1 communication rounds\n",
      "\n",
      "Running 1 round of training on all client in cluster to obtain client weight updates\n",
      "LOCAL TRAINING: Client #29, Epoch 1, #examples 312, Loss 0.7012270533014089, Accuracy 0.8218749966472387\n",
      "LOCAL TRAINING: Client #29, Epoch 2, #examples 312, Loss 0.7168337660841644, Accuracy 0.7999999960884452\n",
      "LOCAL TRAINING: Client #29, Epoch 3, #examples 312, Loss 0.43774264375679195, Accuracy 0.8937499970197678\n",
      "Cluster 1.5 will not be split any further\n",
      "\n",
      "Running FCFL with 1 client idxs: [300]\n",
      "Running learning for 1 communication rounds\n",
      "\n",
      "Communication round 1\n",
      "LOCAL TRAINING: Client #300, Epoch 1, #examples 349, Loss 1.5152519907270159, Accuracy 0.6019047641328403\n",
      "LOCAL TRAINING: Client #300, Epoch 2, #examples 349, Loss 0.7154816286904472, Accuracy 0.8139682463237218\n",
      "LOCAL TRAINING: Client #300, Epoch 3, #examples 349, Loss 0.43131054086344583, Accuracy 0.8936507872172764\n",
      "CLUSTER: 1.6, MEAN TEST ACCURACY: 0.2222222238779068, 10th percentile: 0.2222222238779068, 90th percentile: 0.2222222238779068, % clients reaching target accuracy: 0.0\n",
      "GLOBAL WEIGHTS DELTA NORM: 3.6750009059906006\n",
      "722s elapsed\n",
      "Training complete in 1 communication rounds\n",
      "\n",
      "Running 1 round of training on all client in cluster to obtain client weight updates\n",
      "LOCAL TRAINING: Client #300, Epoch 1, #examples 349, Loss 0.2827529046684504, Accuracy 0.9028571367263794\n",
      "LOCAL TRAINING: Client #300, Epoch 2, #examples 349, Loss 0.25370586908289366, Accuracy 0.9257142782211304\n",
      "LOCAL TRAINING: Client #300, Epoch 3, #examples 349, Loss 0.12083263064601592, Accuracy 0.9625396779605321\n",
      "Cluster 1.6 will not be split any further\n",
      "FCFL completed\n"
     ]
    }
   ],
   "source": [
    "experiment.run()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "metadata": {},
   "outputs": [],
   "source": []
  }
 ],
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