tabular-aug-22-nn-optuna-wandb.ipynb

{
 "cells": [
  {
   "cell_type": "markdown",
   "id": "8a0b025a",
   "metadata": {
    "papermill": {
     "duration": 0.009943,
     "end_time": "2022-08-17T12:16:44.284893",
     "exception": false,
     "start_time": "2022-08-17T12:16:44.274950",
     "status": "completed"
    },
    "tags": []
   },
   "source": [
    "# Creating Neural Networks on the shoulders of giants that are on the shoulders of other giants\n",
    "\n",
    "This notebook is a modified version of the one created by @delai50 (https://www.kaggle.com/code/delai50/standing-on-the-head-of-giants-more-fe)\n",
    "The basis of that notebook is the one created by @maxsarmento (https://www.kaggle.com/code/maxsarmento/lb-0-58978-standing-on-the-shoulder-of-giants/notebook) which in turn is basically the one suggested by @desalegngeb  (https://www.kaggle.com/code/desalegngeb/tps08-logisticregression-and-some-fe/notebook?scriptVersionId=102691691) so credits for them.\n",
    "\n",
    "In this version I added a function to create a NN using keras and hyperparameter tuning using optuna.\n",
    "At the end optuna suggests 0 hidden layers, so the model collapses into a perceptron.\n",
    "Overall the code is more generic to be adaptable also to situations in which it doesn't collapse to a perceptron."
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 1,
   "id": "317ef4f6",
   "metadata": {
    "execution": {
     "iopub.execute_input": "2022-08-17T12:16:44.302543Z",
     "iopub.status.busy": "2022-08-17T12:16:44.301927Z",
     "iopub.status.idle": "2022-08-17T12:16:58.736538Z",
     "shell.execute_reply": "2022-08-17T12:16:58.735282Z"
    },
    "papermill": {
     "duration": 14.447215,
     "end_time": "2022-08-17T12:16:58.740147",
     "exception": false,
     "start_time": "2022-08-17T12:16:44.292932",
     "status": "completed"
    },
    "tags": []
   },
   "outputs": [
    {
     "name": "stderr",
     "output_type": "stream",
     "text": [
      "\u001b[34m\u001b[1mwandb\u001b[0m: W&B API key is configured. Use \u001b[1m`wandb login --relogin`\u001b[0m to force relogin\n",
      "\u001b[34m\u001b[1mwandb\u001b[0m: \u001b[33mWARNING\u001b[0m If you're specifying your api key in code, ensure this code is not shared publicly.\n",
      "\u001b[34m\u001b[1mwandb\u001b[0m: \u001b[33mWARNING\u001b[0m Consider setting the WANDB_API_KEY environment variable, or running `wandb login` from the command line.\n",
      "\u001b[34m\u001b[1mwandb\u001b[0m: Appending key for api.wandb.ai to your netrc file: /root/.netrc\n",
      "\u001b[34m\u001b[1mwandb\u001b[0m: Currently logged in as: \u001b[33mjgraham20\u001b[0m. Use \u001b[1m`wandb login --relogin`\u001b[0m to force relogin\n"
     ]
    },
    {
     "data": {
      "text/html": [
       "wandb version 0.13.1 is available!  To upgrade, please run:\n",
       " $ pip install wandb --upgrade"
      ],
      "text/plain": [
       "<IPython.core.display.HTML object>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    },
    {
     "data": {
      "text/html": [
       "Tracking run with wandb version 0.12.21"
      ],
      "text/plain": [
       "<IPython.core.display.HTML object>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    },
    {
     "data": {
      "text/html": [
       "Run data is saved locally in <code>/kaggle/working/wandb/run-20220817_121654-2f5uo590</code>"
      ],
      "text/plain": [
       "<IPython.core.display.HTML object>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    },
    {
     "data": {
      "text/html": [
       "Syncing run <strong><a href=\"https://wandb.ai/jgraham20/aug22_tabular/runs/2f5uo590\" target=\"_blank\">swept-gorge-5</a></strong> to <a href=\"https://wandb.ai/jgraham20/aug22_tabular\" target=\"_blank\">Weights & Biases</a> (<a href=\"https://wandb.me/run\" target=\"_blank\">docs</a>)<br/>"
      ],
      "text/plain": [
       "<IPython.core.display.HTML object>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    },
    {
     "data": {
      "text/html": [
       "<button onClick=\"this.nextSibling.style.display='block';this.style.display='none';\">Display W&B run</button><iframe src=\"https://wandb.ai/jgraham20/aug22_tabular/runs/2f5uo590?jupyter=true\" style=\"border:none;width:100%;height:420px;display:none;\"></iframe>"
      ],
      "text/plain": [
       "<wandb.sdk.wandb_run.Run at 0x7f8ccce751d0>"
      ]
     },
     "execution_count": 1,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "#True-> run optuna parameter search (takes from 10 to 12h on CPU for 800 parameters configuration)\n",
    "#False-> use params_LR to train an ensemble of NN \n",
    "optimizing=False\n",
    "#How many\n",
    "if optimizing:\n",
    "    splits = 5\n",
    "else:\n",
    "    splits = 50\n",
    "n_trials=800\n",
    "\n",
    "#Parameters for the NN (and optimizer)\n",
    "params_LR = {\n",
    "    'n_layers': 0, \n",
    "    'dropout': 0.19334570992451758, \n",
    "    'reduction': 3, \n",
    "    'initial_size': 256, \n",
    "    'regularizer_l1': 4.093055122216991e-05, \n",
    "    'regularizer_l2': 0.00010688801483338637, \n",
    "    'lr':  0.008913875891778679, \n",
    "    'batch_size': 128\n",
    "}\n",
    "#score :  0.59321\n",
    "\n",
    "#Configuration of the experiment.\n",
    "class CFG:\n",
    "    INPUT_PATH = \"/kaggle/input/tabular-playground-series-aug-2022/\"\n",
    "    OUT_PATH = \"/kaggle/working/\"\n",
    "    N_SPLITS = splits\n",
    "    SEED = 2747902\n",
    "    INFER_MODE = \"fold\"\n",
    "    WANDB_PROJECT = 'aug22_tabular'\n",
    "    \n",
    "import wandb\n",
    "from wandb.keras import WandbCallback\n",
    "from kaggle_secrets import UserSecretsClient\n",
    "\n",
    "user_secrets = UserSecretsClient()\n",
    "wb_key = user_secrets.get_secret(\"WANDB_API_KEY\")\n",
    "\n",
    "wandb.login(key=wb_key)\n",
    "\n",
    "wandb.init(project=CFG.WANDB_PROJECT)\n"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 2,
   "id": "52426ecd",
   "metadata": {
    "_cell_guid": "b1076dfc-b9ad-4769-8c92-a6c4dae69d19",
    "_uuid": "8f2839f25d086af736a60e9eeb907d3b93b6e0e5",
    "execution": {
     "iopub.execute_input": "2022-08-17T12:16:58.758841Z",
     "iopub.status.busy": "2022-08-17T12:16:58.757967Z",
     "iopub.status.idle": "2022-08-17T12:17:33.113593Z",
     "shell.execute_reply": "2022-08-17T12:17:33.112202Z"
    },
    "papermill": {
     "duration": 34.368764,
     "end_time": "2022-08-17T12:17:33.117147",
     "exception": false,
     "start_time": "2022-08-17T12:16:58.748383",
     "status": "completed"
    },
    "tags": []
   },
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "Collecting feature_engine\r\n",
      "  Downloading feature_engine-1.4.0-py2.py3-none-any.whl (276 kB)\r\n",
      "\u001b[2K     \u001b[90m━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━\u001b[0m \u001b[32m276.4/276.4 kB\u001b[0m \u001b[31m883.4 kB/s\u001b[0m eta \u001b[36m0:00:00\u001b[0m\r\n",
      "\u001b[?25hRequirement already satisfied: statsmodels>=0.11.1 in /opt/conda/lib/python3.7/site-packages (from feature_engine) (0.13.2)\r\n",
      "Requirement already satisfied: scipy>=1.4.1 in /opt/conda/lib/python3.7/site-packages (from feature_engine) (1.7.3)\r\n",
      "Requirement already satisfied: numpy>=1.18.2 in /opt/conda/lib/python3.7/site-packages (from feature_engine) (1.21.6)\r\n",
      "Requirement already satisfied: pandas>=1.0.3 in /opt/conda/lib/python3.7/site-packages (from feature_engine) (1.3.5)\r\n",
      "Requirement already satisfied: scikit-learn>=1.0.0 in /opt/conda/lib/python3.7/site-packages (from feature_engine) (1.0.2)\r\n",
      "Requirement already satisfied: python-dateutil>=2.7.3 in /opt/conda/lib/python3.7/site-packages (from pandas>=1.0.3->feature_engine) (2.8.2)\r\n",
      "Requirement already satisfied: pytz>=2017.3 in /opt/conda/lib/python3.7/site-packages (from pandas>=1.0.3->feature_engine) (2022.1)\r\n",
      "Requirement already satisfied: joblib>=0.11 in /opt/conda/lib/python3.7/site-packages (from scikit-learn>=1.0.0->feature_engine) (1.0.1)\r\n",
      "Requirement already satisfied: threadpoolctl>=2.0.0 in /opt/conda/lib/python3.7/site-packages (from scikit-learn>=1.0.0->feature_engine) (3.1.0)\r\n",
      "Requirement already satisfied: packaging>=21.3 in /opt/conda/lib/python3.7/site-packages (from statsmodels>=0.11.1->feature_engine) (21.3)\r\n",
      "Requirement already satisfied: patsy>=0.5.2 in /opt/conda/lib/python3.7/site-packages (from statsmodels>=0.11.1->feature_engine) (0.5.2)\r\n",
      "Requirement already satisfied: pyparsing!=3.0.5,>=2.0.2 in /opt/conda/lib/python3.7/site-packages (from packaging>=21.3->statsmodels>=0.11.1->feature_engine) (3.0.9)\r\n",
      "Requirement already satisfied: six in /opt/conda/lib/python3.7/site-packages (from patsy>=0.5.2->statsmodels>=0.11.1->feature_engine) (1.16.0)\r\n",
      "Installing collected packages: feature_engine\r\n",
      "Successfully installed feature_engine-1.4.0\r\n",
      "\u001b[33mWARNING: Running pip as the 'root' user can result in broken permissions and conflicting behaviour with the system package manager. It is recommended to use a virtual environment instead: https://pip.pypa.io/warnings/venv\u001b[0m\u001b[33m\r\n",
      "\u001b[0mCloning into 'kuma_utils'...\r\n",
      "remote: Enumerating objects: 915, done.\u001b[K\r\n",
      "remote: Counting objects: 100% (120/120), done.\u001b[K\r\n",
      "remote: Compressing objects: 100% (24/24), done.\u001b[K\r\n",
      "remote: Total 915 (delta 104), reused 102 (delta 96), pack-reused 795\u001b[K\r\n",
      "Receiving objects: 100% (915/915), 679.99 KiB | 1.99 MiB/s, done.\r\n",
      "Resolving deltas: 100% (592/592), done.\r\n"
     ]
    },
    {
     "data": {
      "text/html": [
       "<style type='text/css'>\n",
       ".datatable table.frame { margin-bottom: 0; }\n",
       ".datatable table.frame thead { border-bottom: none; }\n",
       ".datatable table.frame tr.coltypes td {  color: #FFFFFF;  line-height: 6px;  padding: 0 0.5em;}\n",
       ".datatable .bool    { background: #DDDD99; }\n",
       ".datatable .object  { background: #565656; }\n",
       ".datatable .int     { background: #5D9E5D; }\n",
       ".datatable .float   { background: #4040CC; }\n",
       ".datatable .str     { background: #CC4040; }\n",
       ".datatable .time    { background: #40CC40; }\n",
       ".datatable .row_index {  background: var(--jp-border-color3);  border-right: 1px solid var(--jp-border-color0);  color: var(--jp-ui-font-color3);  font-size: 9px;}\n",
       ".datatable .frame tbody td { text-align: left; }\n",
       ".datatable .frame tr.coltypes .row_index {  background: var(--jp-border-color0);}\n",
       ".datatable th:nth-child(2) { padding-left: 12px; }\n",
       ".datatable .hellipsis {  color: var(--jp-cell-editor-border-color);}\n",
       ".datatable .vellipsis {  background: var(--jp-layout-color0);  color: var(--jp-cell-editor-border-color);}\n",
       ".datatable .na {  color: var(--jp-cell-editor-border-color);  font-size: 80%;}\n",
       ".datatable .sp {  opacity: 0.25;}\n",
       ".datatable .footer { font-size: 9px; }\n",
       ".datatable .frame_dimensions {  background: var(--jp-border-color3);  border-top: 1px solid var(--jp-border-color0);  color: var(--jp-ui-font-color3);  display: inline-block;  opacity: 0.6;  padding: 1px 10px 1px 5px;}\n",
       "</style>\n"
      ],
      "text/plain": [
       "<IPython.core.display.HTML object>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "Collecting miceforest\r\n",
      "  Downloading miceforest-5.6.2-py3-none-any.whl (57 kB)\r\n",
      "\u001b[2K     \u001b[90m━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━\u001b[0m \u001b[32m57.9/57.9 kB\u001b[0m \u001b[31m406.8 kB/s\u001b[0m eta \u001b[36m0:00:00\u001b[0m\r\n",
      "\u001b[?25hRequirement already satisfied: numpy in /opt/conda/lib/python3.7/site-packages (from miceforest) (1.21.6)\r\n",
      "Requirement already satisfied: lightgbm>=3.3.1 in /opt/conda/lib/python3.7/site-packages (from miceforest) (3.3.2)\r\n",
      "Requirement already satisfied: dill in /opt/conda/lib/python3.7/site-packages (from miceforest) (0.3.5.1)\r\n",
      "Collecting blosc\r\n",
      "  Downloading blosc-1.10.6-cp37-cp37m-manylinux_2_5_x86_64.manylinux1_x86_64.manylinux_2_12_x86_64.manylinux2010_x86_64.whl (2.6 MB)\r\n",
      "\u001b[2K     \u001b[90m━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━\u001b[0m \u001b[32m2.6/2.6 MB\u001b[0m \u001b[31m5.5 MB/s\u001b[0m eta \u001b[36m0:00:00\u001b[0m\r\n",
      "\u001b[?25hRequirement already satisfied: wheel in /opt/conda/lib/python3.7/site-packages (from lightgbm>=3.3.1->miceforest) (0.37.1)\r\n",
      "Requirement already satisfied: scipy in /opt/conda/lib/python3.7/site-packages (from lightgbm>=3.3.1->miceforest) (1.7.3)\r\n",
      "Requirement already satisfied: scikit-learn!=0.22.0 in /opt/conda/lib/python3.7/site-packages (from lightgbm>=3.3.1->miceforest) (1.0.2)\r\n",
      "Requirement already satisfied: joblib>=0.11 in /opt/conda/lib/python3.7/site-packages (from scikit-learn!=0.22.0->lightgbm>=3.3.1->miceforest) (1.0.1)\r\n",
      "Requirement already satisfied: threadpoolctl>=2.0.0 in /opt/conda/lib/python3.7/site-packages (from scikit-learn!=0.22.0->lightgbm>=3.3.1->miceforest) (3.1.0)\r\n",
      "Installing collected packages: blosc, miceforest\r\n",
      "Successfully installed blosc-1.10.6 miceforest-5.6.2\r\n",
      "\u001b[33mWARNING: Running pip as the 'root' user can result in broken permissions and conflicting behaviour with the system package manager. It is recommended to use a virtual environment instead: https://pip.pypa.io/warnings/venv\u001b[0m\u001b[33m\r\n",
      "\u001b[0m"
     ]
    }
   ],
   "source": [
    "# IMPORTS\n",
    "import os\n",
    "import sys\n",
    "import joblib\n",
    "\n",
    "import numpy as np \n",
    "import pandas as pd\n",
    "\n",
    "from sklearn.preprocessing import KBinsDiscretizer\n",
    "from sklearn.model_selection import StratifiedKFold, GroupKFold\n",
    "from sklearn.linear_model import LogisticRegression\n",
    "from sklearn.metrics import roc_auc_score, log_loss\n",
    "\n",
    "!pip install feature_engine\n",
    "from feature_engine.encoding import WoEEncoder\n",
    "\n",
    "!git clone https://github.com/analokmaus/kuma_utils.git\n",
    "sys.path.append(\"kuma_utils/\")\n",
    "from kuma_utils.preprocessing.imputer import LGBMImputer\n",
    "\n",
    "!pip install miceforest\n",
    "import miceforest as mf  \n",
    "\n",
    "import warnings\n",
    "warnings.filterwarnings(\"ignore\")\n",
    "\n",
    "import gc\n",
    "gc.enable()\n",
    "import tensorflow as tf\n",
    "from tensorflow.keras.layers import Input,Dense,Dropout#,BatchNormalization\n",
    "from tensorflow.keras import regularizers\n",
    "\n",
    "from sklearn.preprocessing import RobustScaler"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 3,
   "id": "d9212c00",
   "metadata": {
    "execution": {
     "iopub.execute_input": "2022-08-17T12:17:33.136278Z",
     "iopub.status.busy": "2022-08-17T12:17:33.135831Z",
     "iopub.status.idle": "2022-08-17T12:17:33.150831Z",
     "shell.execute_reply": "2022-08-17T12:17:33.148632Z"
    },
    "papermill": {
     "duration": 0.029646,
     "end_time": "2022-08-17T12:17:33.155054",
     "exception": false,
     "start_time": "2022-08-17T12:17:33.125408",
     "status": "completed"
    },
    "tags": []
   },
   "outputs": [],
   "source": [
    "def create_model(n_features,initial_size,n_layers,dropout,reduction,regularizer_l1,regularizer_l2,lr,**kwargs):\n",
    "    inputs=Input(shape=(None,n_features),name=\"inputs\")\n",
    "    x=inputs\n",
    "    for i in range(n_layers):\n",
    "        x=Dense(initial_size//(reduction**i),activation=\"relu\",name=f\"dense_{i}\",\n",
    "                kernel_regularizer=regularizers.L1L2(l1=regularizer_l1, l2=regularizer_l2))(x)\n",
    "        x=Dropout(dropout,name=f\"dropout_{i}\")(x)\n",
    "        \n",
    "    output=Dense(1,activation=\"sigmoid\",name=\"failure_rate\",\n",
    "                 kernel_regularizer=regularizers.L1L2(l1=regularizer_l1, l2=regularizer_l2))(x)\n",
    "    model=tf.keras.Model(inputs=inputs,outputs=output)\n",
    "    \n",
    "    model.compile(tf.keras.optimizers.Adam(learning_rate=lr),\n",
    "                  loss=\"binary_crossentropy\",\n",
    "                  metrics=[tf.keras.metrics.AUC(name=\"auc\")])\n",
    "    return model"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 4,
   "id": "e585dc54",
   "metadata": {
    "execution": {
     "iopub.execute_input": "2022-08-17T12:17:33.177307Z",
     "iopub.status.busy": "2022-08-17T12:17:33.176954Z",
     "iopub.status.idle": "2022-08-17T12:17:33.188505Z",
     "shell.execute_reply": "2022-08-17T12:17:33.186937Z"
    },
    "papermill": {
     "duration": 0.024897,
     "end_time": "2022-08-17T12:17:33.192609",
     "exception": false,
     "start_time": "2022-08-17T12:17:33.167712",
     "status": "completed"
    },
    "tags": []
   },
   "outputs": [],
   "source": [
    "# CREATE FOLDS\n",
    "def create_folds(df_train):\n",
    "    cv = StratifiedKFold(n_splits=CFG.N_SPLITS, shuffle=True, random_state=CFG.SEED)\n",
    "#     cv = GroupKFold()\n",
    "    df_train[\"fold\"] = -1\n",
    "    for fold, (_, val_idx) in enumerate(cv.split(df_train, df_train[\"failure\"])):\n",
    "        df_train.loc[val_idx, \"fold\"] = fold\n",
    "    return df_train\n"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 5,
   "id": "76a0763c",
   "metadata": {
    "execution": {
     "iopub.execute_input": "2022-08-17T12:17:33.213690Z",
     "iopub.status.busy": "2022-08-17T12:17:33.213371Z",
     "iopub.status.idle": "2022-08-17T12:17:33.229018Z",
     "shell.execute_reply": "2022-08-17T12:17:33.227408Z"
    },
    "papermill": {
     "duration": 0.028692,
     "end_time": "2022-08-17T12:17:33.232290",
     "exception": false,
     "start_time": "2022-08-17T12:17:33.203598",
     "status": "completed"
    },
    "tags": []
   },
   "outputs": [],
   "source": [
    "# CROSSVALIDATION\n",
    "def crossvalidation(df_train, df_test, features, params):\n",
    "    \n",
    "    scalers=[]\n",
    "    score_train_list = []\n",
    "    score_val_list = []\n",
    "    \n",
    "    oofs = df_train[[\"failure\", \"fold\"]].copy()\n",
    "    oofs[\"preds\"] = None\n",
    "    models=[]\n",
    "    for fold in range(CFG.N_SPLITS):\n",
    "\n",
    "        train_idx = df_train[\"fold\"]!=fold\n",
    "        val_idx = df_train[\"fold\"]==fold\n",
    "        scaler = RobustScaler()\n",
    "        X_train_cv = df_train.loc[train_idx][features]\n",
    "        X_train_cv=scaler.fit_transform(X_train_cv)\n",
    "        \n",
    "        X_val_cv = df_train.loc[val_idx][features]\n",
    "        X_val_cv=scaler.transform(X_val_cv)\n",
    "        \n",
    "        scalers.append(scaler)\n",
    "        \n",
    "        y_train_cv = df_train.loc[train_idx][\"failure\"]\n",
    "        y_val_cv = df_train.loc[val_idx][\"failure\"]\n",
    "        \n",
    "        model = create_model(len(features),**params)\n",
    "        \n",
    "        model.fit(X_train_cv, y_train_cv,\n",
    "                  validation_data=(X_val_cv,y_val_cv),\n",
    "                  epochs=100,callbacks=[WandbCallback(), tf.keras.callbacks.EarlyStopping(\n",
    "                                        monitor=\"val_auc\",\n",
    "                                        patience=5,\n",
    "                                        restore_best_weights=True,\n",
    "                                        mode=\"max\")\n",
    "                                       ]\n",
    "                  )\n",
    "        \n",
    "        models.append(model)\n",
    "        \n",
    "        y_train_cv_pred = model.predict(X_train_cv)\n",
    "        y_val_cv_pred = model.predict(X_val_cv)\n",
    "        \n",
    "        oofs.loc[val_idx, \"preds\"] = y_val_cv_pred\n",
    "\n",
    "        score_train = roc_auc_score(y_train_cv, y_train_cv_pred)\n",
    "        score_val = roc_auc_score(y_val_cv, y_val_cv_pred)\n",
    "        \n",
    "        print(f\"Train score: {score_train:.7f} / val score: {score_val:.7f} for split {fold}\")\n",
    "        \n",
    "        score_train_list.append(score_train)\n",
    "        score_val_list.append(score_val)\n",
    "    \n",
    "    oofs.to_csv(os.path.join(CFG.OUT_PATH, f\"oofs_seed{CFG.SEED}.csv\"))\n",
    "    \n",
    "    score_train_avg = np.mean(score_train_list)\n",
    "    score_val_avg = np.mean(score_val_list)\n",
    "    score_val_ove = roc_auc_score(oofs[\"failure\"], oofs[\"preds\"])\n",
    "        \n",
    "    print(f\"Train avg score: {score_train_avg:.7f} / val avg score: {score_val_avg:.7f}\")\n",
    "    print(f\"OOFs overall score: {score_val_ove:.7f}\")\n",
    "    return models,scalers"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 6,
   "id": "ad068b3f",
   "metadata": {
    "execution": {
     "iopub.execute_input": "2022-08-17T12:17:33.255786Z",
     "iopub.status.busy": "2022-08-17T12:17:33.255442Z",
     "iopub.status.idle": "2022-08-17T12:17:33.271515Z",
     "shell.execute_reply": "2022-08-17T12:17:33.269924Z"
    },
    "papermill": {
     "duration": 0.030111,
     "end_time": "2022-08-17T12:17:33.276169",
     "exception": false,
     "start_time": "2022-08-17T12:17:33.246058",
     "status": "completed"
    },
    "tags": []
   },
   "outputs": [],
   "source": [
    "# CROSSVALIDATION\n",
    "def crossvalidation_optimize(trial,df_train, df_test, features):\n",
    "    param_grid = {\n",
    "        \"n_layers\":trial.suggest_int(\"n_layers\",0,2),\n",
    "        \"dropout\":trial.suggest_float(\"dropout\",0.05,0.8),\n",
    "        \"reduction\":trial.suggest_int(\"reduction\",1,4),\n",
    "        \"initial_size\":trial.suggest_categorical(\"initial_size\", [64,128,256]),\n",
    "        \"regularizer_l1\":trial.suggest_float(\"regularizer_l1\",1e-5,0.1,log=True),\n",
    "        \"regularizer_l2\":trial.suggest_float(\"regularizer_l2\",1e-5,0.1,log=True),\n",
    "        \"lr\":trial.suggest_float(\"lr\",0.0000001,0.1,log=True),\n",
    "        \"batch_size\":trial.suggest_categorical(\"batch_size\", [16,32,64,128,256,512,1024,2048]),\n",
    "    }\n",
    "    print(param_grid)\n",
    "    score_val=0\n",
    "    \n",
    "    oofs = df_train[[\"failure\", \"fold\"]].copy()\n",
    "    oofs[\"preds\"] = None\n",
    "    models=[]\n",
    "    for fold in range(CFG.N_SPLITS):\n",
    "\n",
    "        train_idx = df_train[\"fold\"]!=fold\n",
    "        val_idx = df_train[\"fold\"]==fold\n",
    "        \n",
    "        scaler = RobustScaler()\n",
    "        \n",
    "        X_train_cv = df_train.loc[train_idx][features]\n",
    "        X_train_cv=scaler.fit_transform(X_train_cv)\n",
    "        \n",
    "        X_val_cv = df_train.loc[val_idx][features]\n",
    "        X_val_cv=scaler.transform(X_val_cv)\n",
    "        \n",
    "        y_train_cv = df_train.loc[train_idx][\"failure\"]\n",
    "        y_val_cv = df_train.loc[val_idx][\"failure\"]\n",
    "        \n",
    "        \n",
    "        \n",
    "        \n",
    "        model = create_model(len(features),**param_grid)\n",
    "\n",
    "        model.fit(X_train_cv, y_train_cv,\n",
    "                  validation_data=(X_val_cv,y_val_cv),\n",
    "                  epochs=100,callbacks=[WandbCallback(), tf.keras.callbacks.EarlyStopping(\n",
    "                                        monitor=\"val_auc\",\n",
    "                                        patience=5,\n",
    "                                        restore_best_weights=True, mode=\"max\"\n",
    "                                        )\n",
    "                                       ],\n",
    "                  verbose=0,\n",
    "                  batch_size=param_grid[\"batch_size\"]\n",
    "                  )\n",
    "        \n",
    "        models.append(model)\n",
    "        \n",
    "        y_val_cv_pred = model.predict(X_val_cv)\n",
    "        \n",
    "        oofs.loc[val_idx, \"preds\"] = y_val_cv_pred\n",
    "\n",
    "        score_val += roc_auc_score(y_val_cv, y_val_cv_pred)\n",
    "        \n",
    "    print(\"score : \",score_val/CFG.N_SPLITS,\" \")\n",
    "    \n",
    "    return score_val/CFG.N_SPLITS\n",
    "   "
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 7,
   "id": "065090da",
   "metadata": {
    "execution": {
     "iopub.execute_input": "2022-08-17T12:17:33.298666Z",
     "iopub.status.busy": "2022-08-17T12:17:33.298315Z",
     "iopub.status.idle": "2022-08-17T12:17:33.306929Z",
     "shell.execute_reply": "2022-08-17T12:17:33.305447Z"
    },
    "papermill": {
     "duration": 0.022166,
     "end_time": "2022-08-17T12:17:33.310960",
     "exception": false,
     "start_time": "2022-08-17T12:17:33.288794",
     "status": "completed"
    },
    "tags": []
   },
   "outputs": [],
   "source": [
    " \n",
    "# INFERENCE\n",
    "def inference(df_train, df_test, features, params,models,scalers):\n",
    "    \n",
    "    X_train = df_train[features]\n",
    "    y_train = df_train[\"failure\"]\n",
    "    X_test = df_test[features]\n",
    "    y_test_pred = np.zeros(len(X_test))\n",
    "\n",
    "    \n",
    "    for fold in range(CFG.N_SPLITS):\n",
    "        scaler=scalers[fold]\n",
    "        model = models[fold]\n",
    "        y_test_pred += model.predict(scaler.transform(X_test)).reshape(-1) / CFG.N_SPLITS\n",
    "    \n",
    "    \n",
    "            \n",
    "    sub[\"failure\"] = y_test_pred\n",
    "    sub.to_csv(os.path.join(CFG.OUT_PATH, f\"submission.csv\"), index=False)\n",
    "    "
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 8,
   "id": "30fe4330",
   "metadata": {
    "execution": {
     "iopub.execute_input": "2022-08-17T12:17:33.334366Z",
     "iopub.status.busy": "2022-08-17T12:17:33.334030Z",
     "iopub.status.idle": "2022-08-17T12:17:33.343904Z",
     "shell.execute_reply": "2022-08-17T12:17:33.342477Z"
    },
    "papermill": {
     "duration": 0.021694,
     "end_time": "2022-08-17T12:17:33.346770",
     "exception": false,
     "start_time": "2022-08-17T12:17:33.325076",
     "status": "completed"
    },
    "tags": []
   },
   "outputs": [],
   "source": [
    "# Missing value imputation\n",
    "imptr = LGBMImputer(n_iter=50)\n",
    "def impute_nans(df_train, df_test):\n",
    "    nan_features = [col for col in df_train.columns if df_train[col].isnull().any()]\n",
    "    for pc in df_train[\"product_code\"].unique():\n",
    "\n",
    "        df_train.loc[(df_train[\"product_code\"]==pc),nan_features] = \\\n",
    "                    imptr.fit_transform(df_train.loc[(df_train[\"product_code\"]==pc),nan_features])\n",
    "\n",
    "    nan_features = [col for col in df_test.columns if df_test[col].isnull().any()]\n",
    "    for pc in df_test[\"product_code\"].unique():\n",
    "\n",
    "        df_test.loc[(df_test[\"product_code\"]==pc),nan_features] = \\\n",
    "            imptr.fit_transform(df_test.loc[(df_test[\"product_code\"]==pc),nan_features])\n",
    "\n",
    "    return df_train, df_test"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 9,
   "id": "c8d68247",
   "metadata": {
    "execution": {
     "iopub.execute_input": "2022-08-17T12:17:33.372615Z",
     "iopub.status.busy": "2022-08-17T12:17:33.372265Z",
     "iopub.status.idle": "2022-08-17T12:17:33.380549Z",
     "shell.execute_reply": "2022-08-17T12:17:33.379204Z"
    },
    "papermill": {
     "duration": 0.024288,
     "end_time": "2022-08-17T12:17:33.387474",
     "exception": false,
     "start_time": "2022-08-17T12:17:33.363186",
     "status": "completed"
    },
    "tags": []
   },
   "outputs": [],
   "source": [
    "\n",
    "\n",
    "def mice_impute(df_train, df_test):\n",
    "    \n",
    "    print(f\"Running MICE imputer.\")\n",
    "    \n",
    "    train_kernel = mf.ImputationKernel(  \n",
    "        data=df_train, \n",
    "        datasets=4, \n",
    "        save_all_iterations=True,  \n",
    "        random_state=CFG.SEED  \n",
    "    )\n",
    "\n",
    "    test_kernel = mf.ImputationKernel(  \n",
    "        data=df_test, \n",
    "        datasets=4, \n",
    "        save_all_iterations=True,  \n",
    "        random_state=CFG.SEED  \n",
    "    )\n",
    "    train_kernel.mice(3,verbose=True)\n",
    "    test_kernel.mice(3,verbose=True)\n",
    "\n",
    "    df_train = train_kernel.complete_data()\n",
    "    df_test = test_kernel.complete_data()\n",
    "    \n",
    "    return df_train, df_test\n"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 10,
   "id": "ddcfd200",
   "metadata": {
    "execution": {
     "iopub.execute_input": "2022-08-17T12:17:33.407806Z",
     "iopub.status.busy": "2022-08-17T12:17:33.407467Z",
     "iopub.status.idle": "2022-08-17T12:17:33.425788Z",
     "shell.execute_reply": "2022-08-17T12:17:33.424257Z"
    },
    "papermill": {
     "duration": 0.032445,
     "end_time": "2022-08-17T12:17:33.429779",
     "exception": false,
     "start_time": "2022-08-17T12:17:33.397334",
     "status": "completed"
    },
    "tags": []
   },
   "outputs": [],
   "source": [
    "# PREPROCESSING\n",
    "def preprocessing(df_train, df_test):\n",
    "    \n",
    "    df_test = df_test.drop(['id', 'product_code'], axis=1)\n",
    "    df_train = df_train.drop(['id', 'product_code'], axis=1)\n",
    "    \n",
    "    # Missing indicator\n",
    "    for df in [df_train, df_test]:\n",
    "        df[\"m_3_missing\"] = df[\"measurement_3\"].isnull().astype(int)\n",
    "        df[\"m_5_missing\"] = df[\"measurement_5\"].isnull().astype(int)\n",
    "    \n",
    "    # WoE encoding\n",
    "    woe_encoder = WoEEncoder(variables=[\"attribute_0\"])\n",
    "    df_train[\"attribute_0\"] = woe_encoder.fit_transform(df_train[\"attribute_0\"].to_frame(), df_train[\"failure\"])\n",
    "    df_test[\"attribute_0\"] = woe_encoder.transform(df_test[\"attribute_0\"].to_frame())\n",
    "    \n",
    "    woe_encoder = WoEEncoder(variables=[\"attribute_1\"])\n",
    "    df_train[\"attribute_1\"] = woe_encoder.fit_transform(df_train[\"attribute_1\"].to_frame(), df_train[\"failure\"])\n",
    "    df_test[\"attribute_1\"] = woe_encoder.transform(df_test[\"attribute_1\"].to_frame())\n",
    "    \n",
    "    #df_train, df_test = impute_nans(df_train, df_test)\n",
    "    df_train, df_test = mice_impute(df_train, df_test)\n",
    "    \n",
    "    # Area\n",
    "    for df in [df_train, df_test]:\n",
    "        df[\"attribute_2*3\"] = df[\"attribute_2\"] * df[\"attribute_3\"]\n",
    "    \n",
    "    # Aggregations\n",
    "    meas_gr1_cols = [f\"measurement_{i:d}\" for i in list(range(3, 5)) + list(range(9, 17))]\n",
    "    meas_gr2_cols = [f\"measurement_{i:d}\" for i in list(range(5, 9))]\n",
    "    for df in [df_train, df_test]:\n",
    "        df[\"meas_gr1_avg\"] = np.mean(df[meas_gr1_cols], axis=1)\n",
    "        df[\"meas_gr1_std\"] = np.std(df[meas_gr1_cols], axis=1)\n",
    "        df[\"meas_gr2_avg\"] = np.mean(df[meas_gr2_cols], axis=1)\n",
    "    \n",
    "    for df in [df_train, df_test]:\n",
    "        df[\"meas17/meas_gr2_avg\"] = df[\"measurement_17\"] / df[\"meas_gr2_avg\"]\n",
    "        \n",
    "    features = [\"attribute_0\", \"measurement_0\", \"measurement_1\", \"measurement_2\", \"m_3_missing\", \"m_5_missing\",\n",
    "               \"meas_gr1_avg\", \"meas_gr1_std\", \"attribute_2*3\", \"loading\", \"measurement_17\", \"meas17/meas_gr2_avg\"]\n",
    "    \n",
    "    return df_train, df_test, features"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 11,
   "id": "fc3de6a3",
   "metadata": {
    "execution": {
     "iopub.execute_input": "2022-08-17T12:17:33.453881Z",
     "iopub.status.busy": "2022-08-17T12:17:33.453515Z",
     "iopub.status.idle": "2022-08-17T12:17:33.710900Z",
     "shell.execute_reply": "2022-08-17T12:17:33.709419Z"
    },
    "papermill": {
     "duration": 0.270313,
     "end_time": "2022-08-17T12:17:33.714248",
     "exception": false,
     "start_time": "2022-08-17T12:17:33.443935",
     "status": "completed"
    },
    "tags": []
   },
   "outputs": [],
   "source": [
    "df_train = pd.read_csv(os.path.join(CFG.INPUT_PATH, \"train.csv\"))\n",
    "df_test = pd.read_csv(os.path.join(CFG.INPUT_PATH, \"test.csv\"))\n",
    "sub = pd.read_csv(os.path.join(CFG.INPUT_PATH, \"sample_submission.csv\"))"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 12,
   "id": "a3325549",
   "metadata": {
    "execution": {
     "iopub.execute_input": "2022-08-17T12:17:33.733512Z",
     "iopub.status.busy": "2022-08-17T12:17:33.733177Z",
     "iopub.status.idle": "2022-08-17T12:17:33.743226Z",
     "shell.execute_reply": "2022-08-17T12:17:33.741792Z"
    },
    "papermill": {
     "duration": 0.022613,
     "end_time": "2022-08-17T12:17:33.746147",
     "exception": false,
     "start_time": "2022-08-17T12:17:33.723534",
     "status": "completed"
    },
    "tags": []
   },
   "outputs": [
    {
     "data": {
      "text/plain": [
       "Index(['id', 'product_code', 'loading', 'attribute_0', 'attribute_1',\n",
       "       'attribute_2', 'attribute_3', 'measurement_0', 'measurement_1',\n",
       "       'measurement_2', 'measurement_3', 'measurement_4', 'measurement_5',\n",
       "       'measurement_6', 'measurement_7', 'measurement_8', 'measurement_9',\n",
       "       'measurement_10', 'measurement_11', 'measurement_12', 'measurement_13',\n",
       "       'measurement_14', 'measurement_15', 'measurement_16', 'measurement_17',\n",
       "       'failure'],\n",
       "      dtype='object')"
      ]
     },
     "execution_count": 12,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "df_train.columns"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 13,
   "id": "c07a6609",
   "metadata": {
    "execution": {
     "iopub.execute_input": "2022-08-17T12:17:33.764570Z",
     "iopub.status.busy": "2022-08-17T12:17:33.764204Z",
     "iopub.status.idle": "2022-08-17T12:17:33.831923Z",
     "shell.execute_reply": "2022-08-17T12:17:33.830551Z"
    },
    "papermill": {
     "duration": 0.080056,
     "end_time": "2022-08-17T12:17:33.834782",
     "exception": false,
     "start_time": "2022-08-17T12:17:33.754726",
     "status": "completed"
    },
    "tags": []
   },
   "outputs": [],
   "source": [
    "df_train = create_folds(df_train)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 14,
   "id": "4fef1943",
   "metadata": {
    "execution": {
     "iopub.execute_input": "2022-08-17T12:17:33.855145Z",
     "iopub.status.busy": "2022-08-17T12:17:33.853003Z",
     "iopub.status.idle": "2022-08-17T12:23:37.788016Z",
     "shell.execute_reply": "2022-08-17T12:23:37.786612Z"
    },
    "papermill": {
     "duration": 363.947518,
     "end_time": "2022-08-17T12:23:37.791017",
     "exception": false,
     "start_time": "2022-08-17T12:17:33.843499",
     "status": "completed"
    },
    "tags": []
   },
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "Running MICE imputer.\n",
      "Initialized logger with name mice 1-3\n",
      "Dataset 0\n",
      "1  | loading | measurement_3 | measurement_4 | measurement_5 | measurement_6 | measurement_7 | measurement_8 | measurement_9 | measurement_10 | measurement_11 | measurement_12 | measurement_13 | measurement_14 | measurement_15 | measurement_16 | measurement_17\n",
      "2  | loading | measurement_3 | measurement_4 | measurement_5 | measurement_6 | measurement_7 | measurement_8 | measurement_9 | measurement_10 | measurement_11 | measurement_12 | measurement_13 | measurement_14 | measurement_15 | measurement_16 | measurement_17\n",
      "3  | loading | measurement_3 | measurement_4 | measurement_5 | measurement_6 | measurement_7 | measurement_8 | measurement_9 | measurement_10 | measurement_11 | measurement_12 | measurement_13 | measurement_14 | measurement_15 | measurement_16 | measurement_17\n",
      "Dataset 1\n",
      "1  | loading | measurement_3 | measurement_4 | measurement_5 | measurement_6 | measurement_7 | measurement_8 | measurement_9 | measurement_10 | measurement_11 | measurement_12 | measurement_13 | measurement_14 | measurement_15 | measurement_16 | measurement_17\n",
      "2  | loading | measurement_3 | measurement_4 | measurement_5 | measurement_6 | measurement_7 | measurement_8 | measurement_9 | measurement_10 | measurement_11 | measurement_12 | measurement_13 | measurement_14 | measurement_15 | measurement_16 | measurement_17\n",
      "3  | loading | measurement_3 | measurement_4 | measurement_5 | measurement_6 | measurement_7 | measurement_8 | measurement_9 | measurement_10 | measurement_11 | measurement_12 | measurement_13 | measurement_14 | measurement_15 | measurement_16 | measurement_17\n",
      "Dataset 2\n",
      "1  | loading | measurement_3 | measurement_4 | measurement_5 | measurement_6 | measurement_7 | measurement_8 | measurement_9 | measurement_10 | measurement_11 | measurement_12 | measurement_13 | measurement_14 | measurement_15 | measurement_16 | measurement_17\n",
      "2  | loading | measurement_3 | measurement_4 | measurement_5 | measurement_6 | measurement_7 | measurement_8 | measurement_9 | measurement_10 | measurement_11 | measurement_12 | measurement_13 | measurement_14 | measurement_15 | measurement_16 | measurement_17\n",
      "3  | loading | measurement_3 | measurement_4 | measurement_5 | measurement_6 | measurement_7 | measurement_8 | measurement_9 | measurement_10 | measurement_11 | measurement_12 | measurement_13 | measurement_14 | measurement_15 | measurement_16 | measurement_17\n",
      "Dataset 3\n",
      "1  | loading | measurement_3 | measurement_4 | measurement_5 | measurement_6 | measurement_7 | measurement_8 | measurement_9 | measurement_10 | measurement_11 | measurement_12 | measurement_13 | measurement_14 | measurement_15 | measurement_16 | measurement_17\n",
      "2  | loading | measurement_3 | measurement_4 | measurement_5 | measurement_6 | measurement_7 | measurement_8 | measurement_9 | measurement_10 | measurement_11 | measurement_12 | measurement_13 | measurement_14 | measurement_15 | measurement_16 | measurement_17\n",
      "3  | loading | measurement_3 | measurement_4 | measurement_5 | measurement_6 | measurement_7 | measurement_8 | measurement_9 | measurement_10 | measurement_11 | measurement_12 | measurement_13 | measurement_14 | measurement_15 | measurement_16 | measurement_17\n",
      "Initialized logger with name mice 1-3\n",
      "Dataset 0\n",
      "1  | loading | measurement_3 | measurement_4 | measurement_5 | measurement_6 | measurement_7 | measurement_8 | measurement_9 | measurement_10 | measurement_11 | measurement_12 | measurement_13 | measurement_14 | measurement_15 | measurement_16 | measurement_17 | attribute_1\n",
      "2  | loading | measurement_3 | measurement_4 | measurement_5 | measurement_6 | measurement_7 | measurement_8 | measurement_9 | measurement_10 | measurement_11 | measurement_12 | measurement_13 | measurement_14 | measurement_15 | measurement_16 | measurement_17 | attribute_1\n",
      "3  | loading | measurement_3 | measurement_4 | measurement_5 | measurement_6 | measurement_7 | measurement_8 | measurement_9 | measurement_10 | measurement_11 | measurement_12 | measurement_13 | measurement_14 | measurement_15 | measurement_16 | measurement_17 | attribute_1\n",
      "Dataset 1\n",
      "1  | loading | measurement_3 | measurement_4 | measurement_5 | measurement_6 | measurement_7 | measurement_8 | measurement_9 | measurement_10 | measurement_11 | measurement_12 | measurement_13 | measurement_14 | measurement_15 | measurement_16 | measurement_17 | attribute_1\n",
      "2  | loading | measurement_3 | measurement_4 | measurement_5 | measurement_6 | measurement_7 | measurement_8 | measurement_9 | measurement_10 | measurement_11 | measurement_12 | measurement_13 | measurement_14 | measurement_15 | measurement_16 | measurement_17 | attribute_1\n",
      "3  | loading | measurement_3 | measurement_4 | measurement_5 | measurement_6 | measurement_7 | measurement_8 | measurement_9 | measurement_10 | measurement_11 | measurement_12 | measurement_13 | measurement_14 | measurement_15 | measurement_16 | measurement_17 | attribute_1\n",
      "Dataset 2\n",
      "1  | loading | measurement_3 | measurement_4 | measurement_5 | measurement_6 | measurement_7 | measurement_8 | measurement_9 | measurement_10 | measurement_11 | measurement_12 | measurement_13 | measurement_14 | measurement_15 | measurement_16 | measurement_17 | attribute_1\n",
      "2  | loading | measurement_3 | measurement_4 | measurement_5 | measurement_6 | measurement_7 | measurement_8 | measurement_9 | measurement_10 | measurement_11 | measurement_12 | measurement_13 | measurement_14 | measurement_15 | measurement_16 | measurement_17 | attribute_1\n",
      "3  | loading | measurement_3 | measurement_4 | measurement_5 | measurement_6 | measurement_7 | measurement_8 | measurement_9 | measurement_10 | measurement_11 | measurement_12 | measurement_13 | measurement_14 | measurement_15 | measurement_16 | measurement_17 | attribute_1\n",
      "Dataset 3\n",
      "1  | loading | measurement_3 | measurement_4 | measurement_5 | measurement_6 | measurement_7 | measurement_8 | measurement_9 | measurement_10 | measurement_11 | measurement_12 | measurement_13 | measurement_14 | measurement_15 | measurement_16 | measurement_17 | attribute_1\n",
      "2  | loading | measurement_3 | measurement_4 | measurement_5 | measurement_6 | measurement_7 | measurement_8 | measurement_9 | measurement_10 | measurement_11 | measurement_12 | measurement_13 | measurement_14 | measurement_15 | measurement_16 | measurement_17 | attribute_1\n",
      "3  | loading | measurement_3 | measurement_4 | measurement_5 | measurement_6 | measurement_7 | measurement_8 | measurement_9 | measurement_10 | measurement_11 | measurement_12 | measurement_13 | measurement_14 | measurement_15 | measurement_16 | measurement_17 | attribute_1\n"
     ]
    }
   ],
   "source": [
    "df_train, df_test, features = preprocessing(df_train, df_test)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 15,
   "id": "8297f632",
   "metadata": {
    "execution": {
     "iopub.execute_input": "2022-08-17T12:23:37.860024Z",
     "iopub.status.busy": "2022-08-17T12:23:37.859578Z",
     "iopub.status.idle": "2022-08-17T12:23:37.870333Z",
     "shell.execute_reply": "2022-08-17T12:23:37.868873Z"
    },
    "papermill": {
     "duration": 0.051682,
     "end_time": "2022-08-17T12:23:37.873951",
     "exception": false,
     "start_time": "2022-08-17T12:23:37.822269",
     "status": "completed"
    },
    "tags": []
   },
   "outputs": [
    {
     "data": {
      "text/plain": [
       "[]"
      ]
     },
     "execution_count": 15,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "list_str_obj_cols = df_train.columns[df_train.dtypes == \"object\"].tolist()\n",
    "list_str_obj_cols"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 16,
   "id": "287bddeb",
   "metadata": {
    "execution": {
     "iopub.execute_input": "2022-08-17T12:23:37.943084Z",
     "iopub.status.busy": "2022-08-17T12:23:37.942727Z",
     "iopub.status.idle": "2022-08-17T12:23:37.955651Z",
     "shell.execute_reply": "2022-08-17T12:23:37.954020Z"
    },
    "papermill": {
     "duration": 0.04776,
     "end_time": "2022-08-17T12:23:37.959930",
     "exception": false,
     "start_time": "2022-08-17T12:23:37.912170",
     "status": "completed"
    },
    "tags": []
   },
   "outputs": [],
   "source": [
    "if optimizing:\n",
    "    import optuna\n",
    "    from optuna.integration.wandb import WeightsAndBiasesCallback\n",
    "    \n",
    "    wandb_kwargs = {\"project\": CFG.WANDB_PROJECT}\n",
    "    wandbc = WeightsAndBiasesCallback(wandb_kwargs=wandb_kwargs)\n",
    "    \n",
    "    study = optuna.create_study(direction=\"maximize\", study_name=\"NN classifier\")\n",
    "    optuna.logging.set_verbosity(optuna.logging.WARNING)\n",
    "    func = lambda trial: crossvalidation_optimize(trial, df_train, df_test, features)\n",
    "    study.optimize(func, n_trials=n_trials, callbacks=[wandbc])\n",
    "    \n",
    "    print(f\"\\tBest value: {study.best_value:.5f}\")\n",
    "    print(f\"\\tBest params:\")\n",
    "\n",
    "    for key, value in study.best_params.items():\n",
    "        print(f\"\\t\\t{key}: {value}\")"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 17,
   "id": "5fee493d",
   "metadata": {
    "execution": {
     "iopub.execute_input": "2022-08-17T12:23:38.022599Z",
     "iopub.status.busy": "2022-08-17T12:23:38.022254Z",
     "iopub.status.idle": "2022-08-17T13:05:50.556343Z",
     "shell.execute_reply": "2022-08-17T13:05:50.555005Z"
    },
    "papermill": {
     "duration": 2532.567856,
     "end_time": "2022-08-17T13:05:50.559487",
     "exception": false,
     "start_time": "2022-08-17T12:23:37.991631",
     "status": "completed"
    },
    "tags": []
   },
   "outputs": [
    {
     "name": "stderr",
     "output_type": "stream",
     "text": [
      "2022-08-17 12:23:38.186867: I tensorflow/stream_executor/cuda/cuda_gpu_executor.cc:937] successful NUMA node read from SysFS had negative value (-1), but there must be at least one NUMA node, so returning NUMA node zero\n",
      "2022-08-17 12:23:38.195822: I tensorflow/stream_executor/cuda/cuda_gpu_executor.cc:937] successful NUMA node read from SysFS had negative value (-1), but there must be at least one NUMA node, so returning NUMA node zero\n",
      "2022-08-17 12:23:38.199949: I tensorflow/stream_executor/cuda/cuda_gpu_executor.cc:937] successful NUMA node read from SysFS had negative value (-1), but there must be at least one NUMA node, so returning NUMA node zero\n",
      "2022-08-17 12:23:38.205319: I tensorflow/core/platform/cpu_feature_guard.cc:142] This TensorFlow binary is optimized with oneAPI Deep Neural Network Library (oneDNN) to use the following CPU instructions in performance-critical operations:  AVX2 FMA\n",
      "To enable them in other operations, rebuild TensorFlow with the appropriate compiler flags.\n",
      "2022-08-17 12:23:38.205795: I tensorflow/stream_executor/cuda/cuda_gpu_executor.cc:937] successful NUMA node read from SysFS had negative value (-1), but there must be at least one NUMA node, so returning NUMA node zero\n",
      "2022-08-17 12:23:38.210381: I tensorflow/stream_executor/cuda/cuda_gpu_executor.cc:937] successful NUMA node read from SysFS had negative value (-1), but there must be at least one NUMA node, so returning NUMA node zero\n",
      "2022-08-17 12:23:38.214357: I tensorflow/stream_executor/cuda/cuda_gpu_executor.cc:937] successful NUMA node read from SysFS had negative value (-1), but there must be at least one NUMA node, so returning NUMA node zero\n",
      "2022-08-17 12:23:41.220970: I tensorflow/stream_executor/cuda/cuda_gpu_executor.cc:937] successful NUMA node read from SysFS had negative value (-1), but there must be at least one NUMA node, so returning NUMA node zero\n",
      "2022-08-17 12:23:41.224919: I tensorflow/stream_executor/cuda/cuda_gpu_executor.cc:937] successful NUMA node read from SysFS had negative value (-1), but there must be at least one NUMA node, so returning NUMA node zero\n",
      "2022-08-17 12:23:41.228711: I tensorflow/stream_executor/cuda/cuda_gpu_executor.cc:937] successful NUMA node read from SysFS had negative value (-1), but there must be at least one NUMA node, so returning NUMA node zero\n",
      "2022-08-17 12:23:41.232540: I tensorflow/core/common_runtime/gpu/gpu_device.cc:1510] Created device /job:localhost/replica:0/task:0/device:GPU:0 with 15385 MB memory:  -> device: 0, name: Tesla P100-PCIE-16GB, pci bus id: 0000:00:04.0, compute capability: 6.0\n",
      "\u001b[34m\u001b[1mwandb\u001b[0m: \u001b[33mWARNING\u001b[0m The save_model argument by default saves the model in the HDF5 format that cannot save custom objects like subclassed models and custom layers. This behavior will be deprecated in a future release in favor of the SavedModel format. Meanwhile, the HDF5 model is saved as W&B files and the SavedModel as W&B Artifacts.\n",
      "2022-08-17 12:23:42.711473: I tensorflow/stream_executor/cuda/cuda_gpu_executor.cc:937] successful NUMA node read from SysFS had negative value (-1), but there must be at least one NUMA node, so returning NUMA node zero\n",
      "2022-08-17 12:23:42.712733: I tensorflow/core/grappler/devices.cc:66] Number of eligible GPUs (core count >= 8, compute capability >= 0.0): 1\n",
      "2022-08-17 12:23:42.712959: I tensorflow/core/grappler/clusters/single_machine.cc:357] Starting new session\n",
      "2022-08-17 12:23:42.713741: I tensorflow/stream_executor/cuda/cuda_gpu_executor.cc:937] successful NUMA node read from SysFS had negative value (-1), but there must be at least one NUMA node, so returning NUMA node zero\n",
      "2022-08-17 12:23:42.714940: I tensorflow/stream_executor/cuda/cuda_gpu_executor.cc:937] successful NUMA node read from SysFS had negative value (-1), but there must be at least one NUMA node, so returning NUMA node zero\n",
      "2022-08-17 12:23:42.716160: I tensorflow/stream_executor/cuda/cuda_gpu_executor.cc:937] successful NUMA node read from SysFS had negative value (-1), but there must be at least one NUMA node, so returning NUMA node zero\n",
      "2022-08-17 12:23:42.717379: I tensorflow/stream_executor/cuda/cuda_gpu_executor.cc:937] successful NUMA node read from SysFS had negative value (-1), but there must be at least one NUMA node, so returning NUMA node zero\n",
      "2022-08-17 12:23:42.718608: I tensorflow/stream_executor/cuda/cuda_gpu_executor.cc:937] successful NUMA node read from SysFS had negative value (-1), but there must be at least one NUMA node, so returning NUMA node zero\n",
      "2022-08-17 12:23:42.719572: I tensorflow/core/common_runtime/gpu/gpu_device.cc:1510] Created device /job:localhost/replica:0/task:0/device:GPU:0 with 15385 MB memory:  -> device: 0, name: Tesla P100-PCIE-16GB, pci bus id: 0000:00:04.0, compute capability: 6.0\n",
      "2022-08-17 12:23:42.735393: I tensorflow/core/grappler/optimizers/meta_optimizer.cc:1137] Optimization results for grappler item: graph_to_optimize\n",
      "  function_optimizer: function_optimizer did nothing. time = 1.361ms.\n",
      "  function_optimizer: function_optimizer did nothing. time = 0.003ms.\n",
      "\n",
      "Incomplete shape.\n",
      "Incomplete shape.\n",
      "2022-08-17 12:23:42.832660: I tensorflow/compiler/mlir/mlir_graph_optimization_pass.cc:185] None of the MLIR Optimization Passes are enabled (registered 2)\n"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "Epoch 1/100\n",
      "814/814 [==============================] - 6s 5ms/step - loss: 0.5264 - auc: 0.5602 - val_loss: 0.5089 - val_auc: 0.5944\n",
      "Epoch 2/100\n",
      "814/814 [==============================] - 3s 4ms/step - loss: 0.5098 - auc: 0.5851 - val_loss: 0.5131 - val_auc: 0.5829\n",
      "Epoch 3/100\n",
      "814/814 [==============================] - 4s 5ms/step - loss: 0.5101 - auc: 0.5857 - val_loss: 0.5108 - val_auc: 0.5904\n",
      "Epoch 4/100\n",
      "814/814 [==============================] - 3s 4ms/step - loss: 0.5100 - auc: 0.5869 - val_loss: 0.5117 - val_auc: 0.5918\n",
      "Epoch 5/100\n",
      "814/814 [==============================] - 4s 5ms/step - loss: 0.5098 - auc: 0.5862 - val_loss: 0.5086 - val_auc: 0.5987\n",
      "Epoch 6/100\n",
      "814/814 [==============================] - 4s 5ms/step - loss: 0.5099 - auc: 0.5860 - val_loss: 0.5086 - val_auc: 0.5887\n",
      "Epoch 7/100\n",
      "814/814 [==============================] - 3s 4ms/step - loss: 0.5099 - auc: 0.5853 - val_loss: 0.5108 - val_auc: 0.5938\n",
      "Epoch 8/100\n",
      "814/814 [==============================] - 3s 4ms/step - loss: 0.5097 - auc: 0.5867 - val_loss: 0.5101 - val_auc: 0.5878\n",
      "Epoch 9/100\n",
      "814/814 [==============================] - 4s 5ms/step - loss: 0.5097 - auc: 0.5865 - val_loss: 0.5098 - val_auc: 0.5986\n",
      "Epoch 10/100\n",
      "814/814 [==============================] - 3s 4ms/step - loss: 0.5098 - auc: 0.5864 - val_loss: 0.5079 - val_auc: 0.6054\n",
      "Epoch 11/100\n",
      "814/814 [==============================] - 4s 4ms/step - loss: 0.5093 - auc: 0.5869 - val_loss: 0.5105 - val_auc: 0.5930\n",
      "Epoch 12/100\n",
      "814/814 [==============================] - 4s 5ms/step - loss: 0.5096 - auc: 0.5876 - val_loss: 0.5083 - val_auc: 0.6043\n",
      "Epoch 13/100\n",
      "814/814 [==============================] - 3s 4ms/step - loss: 0.5097 - auc: 0.5870 - val_loss: 0.5107 - val_auc: 0.5862\n",
      "Epoch 14/100\n",
      "814/814 [==============================] - 4s 5ms/step - loss: 0.5098 - auc: 0.5862 - val_loss: 0.5069 - val_auc: 0.6089\n",
      "Epoch 15/100\n",
      "814/814 [==============================] - 4s 5ms/step - loss: 0.5099 - auc: 0.5859 - val_loss: 0.5082 - val_auc: 0.6042\n",
      "Epoch 16/100\n",
      "814/814 [==============================] - 3s 4ms/step - loss: 0.5097 - auc: 0.5857 - val_loss: 0.5096 - val_auc: 0.5941\n",
      "Epoch 17/100\n",
      "814/814 [==============================] - 3s 4ms/step - loss: 0.5098 - auc: 0.5858 - val_loss: 0.5094 - val_auc: 0.5968\n",
      "Epoch 18/100\n",
      "814/814 [==============================] - 4s 5ms/step - loss: 0.5097 - auc: 0.5868 - val_loss: 0.5062 - val_auc: 0.6023\n",
      "Epoch 19/100\n",
      "814/814 [==============================] - 3s 4ms/step - loss: 0.5098 - auc: 0.5874 - val_loss: 0.5117 - val_auc: 0.5799\n",
      "Train score: 0.5910286 / val score: 0.6086552 for split 0\n",
      "Epoch 1/100\n"
     ]
    },
    {
     "name": "stderr",
     "output_type": "stream",
     "text": [
      "2022-08-17 12:25:07.021090: I tensorflow/stream_executor/cuda/cuda_gpu_executor.cc:937] successful NUMA node read from SysFS had negative value (-1), but there must be at least one NUMA node, so returning NUMA node zero\n",
      "2022-08-17 12:25:07.022064: I tensorflow/core/grappler/devices.cc:66] Number of eligible GPUs (core count >= 8, compute capability >= 0.0): 1\n",
      "2022-08-17 12:25:07.022213: I tensorflow/core/grappler/clusters/single_machine.cc:357] Starting new session\n",
      "2022-08-17 12:25:07.022702: I tensorflow/stream_executor/cuda/cuda_gpu_executor.cc:937] successful NUMA node read from SysFS had negative value (-1), but there must be at least one NUMA node, so returning NUMA node zero\n",
      "2022-08-17 12:25:07.023608: I tensorflow/stream_executor/cuda/cuda_gpu_executor.cc:937] successful NUMA node read from SysFS had negative value (-1), but there must be at least one NUMA node, so returning NUMA node zero\n",
      "2022-08-17 12:25:07.024520: I tensorflow/stream_executor/cuda/cuda_gpu_executor.cc:937] successful NUMA node read from SysFS had negative value (-1), but there must be at least one NUMA node, so returning NUMA node zero\n",
      "2022-08-17 12:25:07.025500: I tensorflow/stream_executor/cuda/cuda_gpu_executor.cc:937] successful NUMA node read from SysFS had negative value (-1), but there must be at least one NUMA node, so returning NUMA node zero\n",
      "2022-08-17 12:25:07.026402: I tensorflow/stream_executor/cuda/cuda_gpu_executor.cc:937] successful NUMA node read from SysFS had negative value (-1), but there must be at least one NUMA node, so returning NUMA node zero\n",
      "2022-08-17 12:25:07.027194: I tensorflow/core/common_runtime/gpu/gpu_device.cc:1510] Created device /job:localhost/replica:0/task:0/device:GPU:0 with 15385 MB memory:  -> device: 0, name: Tesla P100-PCIE-16GB, pci bus id: 0000:00:04.0, compute capability: 6.0\n",
      "2022-08-17 12:25:07.028676: I tensorflow/core/grappler/optimizers/meta_optimizer.cc:1137] Optimization results for grappler item: graph_to_optimize\n",
      "  function_optimizer: function_optimizer did nothing. time = 0.006ms.\n",
      "  function_optimizer: function_optimizer did nothing. time = 0.001ms.\n",
      "\n",
      "Incomplete shape.\n",
      "Incomplete shape.\n"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "814/814 [==============================] - 5s 5ms/step - loss: 0.5285 - auc: 0.5596 - val_loss: 0.5051 - val_auc: 0.6313\n",
      "Epoch 2/100\n",
      "814/814 [==============================] - 3s 4ms/step - loss: 0.5099 - auc: 0.5847 - val_loss: 0.5024 - val_auc: 0.6343\n",
      "Epoch 3/100\n",
      "814/814 [==============================] - 3s 4ms/step - loss: 0.5097 - auc: 0.5865 - val_loss: 0.5060 - val_auc: 0.6184\n",
      "Epoch 4/100\n",
      "814/814 [==============================] - 4s 5ms/step - loss: 0.5101 - auc: 0.5840 - val_loss: 0.5051 - val_auc: 0.6275\n",
      "Epoch 5/100\n",
      "814/814 [==============================] - 3s 4ms/step - loss: 0.5099 - auc: 0.5849 - val_loss: 0.5034 - val_auc: 0.6299\n",
      "Epoch 6/100\n",
      "814/814 [==============================] - 4s 5ms/step - loss: 0.5101 - auc: 0.5853 - val_loss: 0.5048 - val_auc: 0.6255\n",
      "Epoch 7/100\n",
      "814/814 [==============================] - 4s 5ms/step - loss: 0.5099 - auc: 0.5858 - val_loss: 0.5033 - val_auc: 0.6252\n",
      "Train score: 0.5887337 / val score: 0.6340423 for split 1\n"
     ]
    },
    {
     "name": "stderr",
     "output_type": "stream",
     "text": [
      "2022-08-17 12:25:35.116823: I tensorflow/stream_executor/cuda/cuda_gpu_executor.cc:937] successful NUMA node read from SysFS had negative value (-1), but there must be at least one NUMA node, so returning NUMA node zero\n",
      "2022-08-17 12:25:35.117972: I tensorflow/core/grappler/devices.cc:66] Number of eligible GPUs (core count >= 8, compute capability >= 0.0): 1\n",
      "2022-08-17 12:25:35.118142: I tensorflow/core/grappler/clusters/single_machine.cc:357] Starting new session\n",
      "2022-08-17 12:25:35.118833: I tensorflow/stream_executor/cuda/cuda_gpu_executor.cc:937] successful NUMA node read from SysFS had negative value (-1), but there must be at least one NUMA node, so returning NUMA node zero\n",
      "2022-08-17 12:25:35.120016: I tensorflow/stream_executor/cuda/cuda_gpu_executor.cc:937] successful NUMA node read from SysFS had negative value (-1), but there must be at least one NUMA node, so returning NUMA node zero\n",
      "2022-08-17 12:25:35.121235: I tensorflow/stream_executor/cuda/cuda_gpu_executor.cc:937] successful NUMA node read from SysFS had negative value (-1), but there must be at least one NUMA node, so returning NUMA node zero\n",
      "2022-08-17 12:25:35.122459: I tensorflow/stream_executor/cuda/cuda_gpu_executor.cc:937] successful NUMA node read from SysFS had negative value (-1), but there must be at least one NUMA node, so returning NUMA node zero\n",
      "2022-08-17 12:25:35.123695: I tensorflow/stream_executor/cuda/cuda_gpu_executor.cc:937] successful NUMA node read from SysFS had negative value (-1), but there must be at least one NUMA node, so returning NUMA node zero\n",
      "2022-08-17 12:25:35.124775: I tensorflow/core/common_runtime/gpu/gpu_device.cc:1510] Created device /job:localhost/replica:0/task:0/device:GPU:0 with 15385 MB memory:  -> device: 0, name: Tesla P100-PCIE-16GB, pci bus id: 0000:00:04.0, compute capability: 6.0\n",
      "2022-08-17 12:25:35.127167: I tensorflow/core/grappler/optimizers/meta_optimizer.cc:1137] Optimization results for grappler item: graph_to_optimize\n",
      "  function_optimizer: function_optimizer did nothing. time = 0.009ms.\n",
      "  function_optimizer: function_optimizer did nothing. time = 0.003ms.\n",
      "\n",
      "Incomplete shape.\n",
      "Incomplete shape.\n"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "Epoch 1/100\n",
      "814/814 [==============================] - 4s 5ms/step - loss: 0.5262 - auc: 0.5634 - val_loss: 0.5123 - val_auc: 0.5624\n",
      "Epoch 2/100\n",
      "814/814 [==============================] - 3s 4ms/step - loss: 0.5095 - auc: 0.5880 - val_loss: 0.5094 - val_auc: 0.5777\n",
      "Epoch 3/100\n",
      "814/814 [==============================] - 4s 5ms/step - loss: 0.5098 - auc: 0.5868 - val_loss: 0.5121 - val_auc: 0.5671\n",
      "Epoch 4/100\n",
      "814/814 [==============================] - 3s 4ms/step - loss: 0.5095 - auc: 0.5876 - val_loss: 0.5097 - val_auc: 0.5865\n",
      "Epoch 5/100\n",
      "814/814 [==============================] - 3s 4ms/step - loss: 0.5097 - auc: 0.5874 - val_loss: 0.5102 - val_auc: 0.5787\n",
      "Epoch 6/100\n",
      "814/814 [==============================] - 4s 5ms/step - loss: 0.5096 - auc: 0.5868 - val_loss: 0.5108 - val_auc: 0.5707\n",
      "Epoch 7/100\n",
      "814/814 [==============================] - 4s 4ms/step - loss: 0.5096 - auc: 0.5868 - val_loss: 0.5104 - val_auc: 0.5688\n",
      "Epoch 8/100\n",
      "814/814 [==============================] - 4s 5ms/step - loss: 0.5097 - auc: 0.5863 - val_loss: 0.5120 - val_auc: 0.5639\n",
      "Epoch 9/100\n",
      "814/814 [==============================] - 4s 5ms/step - loss: 0.5097 - auc: 0.5870 - val_loss: 0.5105 - val_auc: 0.5785\n",
      "Train score: 0.5838242 / val score: 0.5869010 for split 2\n",
      "Epoch 1/100\n"
     ]
    },
    {
     "name": "stderr",
     "output_type": "stream",
     "text": [
      "2022-08-17 12:26:10.294234: I tensorflow/stream_executor/cuda/cuda_gpu_executor.cc:937] successful NUMA node read from SysFS had negative value (-1), but there must be at least one NUMA node, so returning NUMA node zero\n",
      "2022-08-17 12:26:10.295190: I tensorflow/core/grappler/devices.cc:66] Number of eligible GPUs (core count >= 8, compute capability >= 0.0): 1\n",
      "2022-08-17 12:26:10.295331: I tensorflow/core/grappler/clusters/single_machine.cc:357] Starting new session\n",
      "2022-08-17 12:26:10.295908: I tensorflow/stream_executor/cuda/cuda_gpu_executor.cc:937] successful NUMA node read from SysFS had negative value (-1), but there must be at least one NUMA node, so returning NUMA node zero\n",
      "2022-08-17 12:26:10.296943: I tensorflow/stream_executor/cuda/cuda_gpu_executor.cc:937] successful NUMA node read from SysFS had negative value (-1), but there must be at least one NUMA node, so returning NUMA node zero\n",
      "2022-08-17 12:26:10.297918: I tensorflow/stream_executor/cuda/cuda_gpu_executor.cc:937] successful NUMA node read from SysFS had negative value (-1), but there must be at least one NUMA node, so returning NUMA node zero\n",
      "2022-08-17 12:26:10.298924: I tensorflow/stream_executor/cuda/cuda_gpu_executor.cc:937] successful NUMA node read from SysFS had negative value (-1), but there must be at least one NUMA node, so returning NUMA node zero\n",
      "2022-08-17 12:26:10.299903: I tensorflow/stream_executor/cuda/cuda_gpu_executor.cc:937] successful NUMA node read from SysFS had negative value (-1), but there must be at least one NUMA node, so returning NUMA node zero\n",
      "2022-08-17 12:26:10.300647: I tensorflow/core/common_runtime/gpu/gpu_device.cc:1510] Created device /job:localhost/replica:0/task:0/device:GPU:0 with 15385 MB memory:  -> device: 0, name: Tesla P100-PCIE-16GB, pci bus id: 0000:00:04.0, compute capability: 6.0\n",
      "2022-08-17 12:26:10.302645: I tensorflow/core/grappler/optimizers/meta_optimizer.cc:1137] Optimization results for grappler item: graph_to_optimize\n",
      "  function_optimizer: function_optimizer did nothing. time = 0.007ms.\n",
      "  function_optimizer: function_optimizer did nothing. time = 0.002ms.\n",
      "\n",
      "Incomplete shape.\n",
      "Incomplete shape.\n"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "814/814 [==============================] - 4s 5ms/step - loss: 0.5313 - auc: 0.5574 - val_loss: 0.5077 - val_auc: 0.5909\n",
      "Epoch 2/100\n",
      "814/814 [==============================] - 4s 5ms/step - loss: 0.5099 - auc: 0.5871 - val_loss: 0.5107 - val_auc: 0.5706\n",
      "Epoch 3/100\n",
      "814/814 [==============================] - 3s 4ms/step - loss: 0.5095 - auc: 0.5873 - val_loss: 0.5087 - val_auc: 0.5823\n",
      "Epoch 4/100\n",
      "814/814 [==============================] - 3s 4ms/step - loss: 0.5099 - auc: 0.5858 - val_loss: 0.5092 - val_auc: 0.5844\n",
      "Epoch 5/100\n",
      "814/814 [==============================] - 4s 5ms/step - loss: 0.5097 - auc: 0.5870 - val_loss: 0.5079 - val_auc: 0.5926\n",
      "Epoch 6/100\n",
      "814/814 [==============================] - 3s 4ms/step - loss: 0.5096 - auc: 0.5884 - val_loss: 0.5101 - val_auc: 0.5800\n",
      "Epoch 7/100\n",
      "814/814 [==============================] - 3s 4ms/step - loss: 0.5097 - auc: 0.5884 - val_loss: 0.5109 - val_auc: 0.5726\n",
      "Epoch 8/100\n",
      "814/814 [==============================] - 4s 5ms/step - loss: 0.5098 - auc: 0.5856 - val_loss: 0.5078 - val_auc: 0.5886\n",
      "Epoch 9/100\n",
      "814/814 [==============================] - 3s 4ms/step - loss: 0.5097 - auc: 0.5878 - val_loss: 0.5086 - val_auc: 0.5816\n",
      "Epoch 10/100\n",
      "814/814 [==============================] - 3s 4ms/step - loss: 0.5095 - auc: 0.5873 - val_loss: 0.5119 - val_auc: 0.5657\n",
      "Train score: 0.5910002 / val score: 0.5940609 for split 3\n"
     ]
    },
    {
     "name": "stderr",
     "output_type": "stream",
     "text": [
      "2022-08-17 12:26:48.057110: I tensorflow/stream_executor/cuda/cuda_gpu_executor.cc:937] successful NUMA node read from SysFS had negative value (-1), but there must be at least one NUMA node, so returning NUMA node zero\n",
      "2022-08-17 12:26:48.058012: I tensorflow/core/grappler/devices.cc:66] Number of eligible GPUs (core count >= 8, compute capability >= 0.0): 1\n",
      "2022-08-17 12:26:48.058140: I tensorflow/core/grappler/clusters/single_machine.cc:357] Starting new session\n",
      "2022-08-17 12:26:48.058670: I tensorflow/stream_executor/cuda/cuda_gpu_executor.cc:937] successful NUMA node read from SysFS had negative value (-1), but there must be at least one NUMA node, so returning NUMA node zero\n",
      "2022-08-17 12:26:48.059697: I tensorflow/stream_executor/cuda/cuda_gpu_executor.cc:937] successful NUMA node read from SysFS had negative value (-1), but there must be at least one NUMA node, so returning NUMA node zero\n",
      "2022-08-17 12:26:48.060593: I tensorflow/stream_executor/cuda/cuda_gpu_executor.cc:937] successful NUMA node read from SysFS had negative value (-1), but there must be at least one NUMA node, so returning NUMA node zero\n",
      "2022-08-17 12:26:48.061552: I tensorflow/stream_executor/cuda/cuda_gpu_executor.cc:937] successful NUMA node read from SysFS had negative value (-1), but there must be at least one NUMA node, so returning NUMA node zero\n",
      "2022-08-17 12:26:48.062567: I tensorflow/stream_executor/cuda/cuda_gpu_executor.cc:937] successful NUMA node read from SysFS had negative value (-1), but there must be at least one NUMA node, so returning NUMA node zero\n",
      "2022-08-17 12:26:48.063445: I tensorflow/core/common_runtime/gpu/gpu_device.cc:1510] Created device /job:localhost/replica:0/task:0/device:GPU:0 with 15385 MB memory:  -> device: 0, name: Tesla P100-PCIE-16GB, pci bus id: 0000:00:04.0, compute capability: 6.0\n",
      "2022-08-17 12:26:48.064978: I tensorflow/core/grappler/optimizers/meta_optimizer.cc:1137] Optimization results for grappler item: graph_to_optimize\n",
      "  function_optimizer: function_optimizer did nothing. time = 0.007ms.\n",
      "  function_optimizer: function_optimizer did nothing. time = 0.006ms.\n",
      "\n",
      "Incomplete shape.\n",
      "Incomplete shape.\n"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "Epoch 1/100\n",
      "814/814 [==============================] - 5s 6ms/step - loss: 0.5299 - auc: 0.5595 - val_loss: 0.5180 - val_auc: 0.5483\n",
      "Epoch 2/100\n",
      "814/814 [==============================] - 3s 4ms/step - loss: 0.5093 - auc: 0.5886 - val_loss: 0.5159 - val_auc: 0.5477\n",
      "Epoch 3/100\n",
      "814/814 [==============================] - 4s 5ms/step - loss: 0.5097 - auc: 0.5859 - val_loss: 0.5181 - val_auc: 0.5521\n",
      "Epoch 4/100\n",
      "814/814 [==============================] - 4s 4ms/step - loss: 0.5093 - auc: 0.5882 - val_loss: 0.5212 - val_auc: 0.5379\n",
      "Epoch 5/100\n",
      "814/814 [==============================] - 3s 4ms/step - loss: 0.5100 - auc: 0.5860 - val_loss: 0.5171 - val_auc: 0.5524\n",
      "Epoch 6/100\n",
      "814/814 [==============================] - 3s 4ms/step - loss: 0.5096 - auc: 0.5877 - val_loss: 0.5189 - val_auc: 0.5430\n",
      "Epoch 7/100\n",
      "814/814 [==============================] - 4s 5ms/step - loss: 0.5093 - auc: 0.5890 - val_loss: 0.5177 - val_auc: 0.5534\n",
      "Epoch 8/100\n",
      "814/814 [==============================] - 3s 4ms/step - loss: 0.5097 - auc: 0.5872 - val_loss: 0.5172 - val_auc: 0.5435\n",
      "Epoch 9/100\n",
      "814/814 [==============================] - 3s 4ms/step - loss: 0.5095 - auc: 0.5879 - val_loss: 0.5217 - val_auc: 0.5404\n",
      "Epoch 10/100\n",
      "814/814 [==============================] - 4s 5ms/step - loss: 0.5096 - auc: 0.5869 - val_loss: 0.5194 - val_auc: 0.5403\n",
      "Epoch 11/100\n",
      "814/814 [==============================] - 3s 4ms/step - loss: 0.5095 - auc: 0.5888 - val_loss: 0.5194 - val_auc: 0.5442\n",
      "Epoch 12/100\n",
      "814/814 [==============================] - 4s 5ms/step - loss: 0.5095 - auc: 0.5866 - val_loss: 0.5229 - val_auc: 0.5464\n",
      "Train score: 0.5860218 / val score: 0.5543751 for split 4\n",
      "Epoch 1/100\n"
     ]
    },
    {
     "name": "stderr",
     "output_type": "stream",
     "text": [
      "2022-08-17 12:27:35.122799: I tensorflow/stream_executor/cuda/cuda_gpu_executor.cc:937] successful NUMA node read from SysFS had negative value (-1), but there must be at least one NUMA node, so returning NUMA node zero\n",
      "2022-08-17 12:27:35.123781: I tensorflow/core/grappler/devices.cc:66] Number of eligible GPUs (core count >= 8, compute capability >= 0.0): 1\n",
      "2022-08-17 12:27:35.123929: I tensorflow/core/grappler/clusters/single_machine.cc:357] Starting new session\n",
      "2022-08-17 12:27:35.124494: I tensorflow/stream_executor/cuda/cuda_gpu_executor.cc:937] successful NUMA node read from SysFS had negative value (-1), but there must be at least one NUMA node, so returning NUMA node zero\n",
      "2022-08-17 12:27:35.125424: I tensorflow/stream_executor/cuda/cuda_gpu_executor.cc:937] successful NUMA node read from SysFS had negative value (-1), but there must be at least one NUMA node, so returning NUMA node zero\n",
      "2022-08-17 12:27:35.126407: I tensorflow/stream_executor/cuda/cuda_gpu_executor.cc:937] successful NUMA node read from SysFS had negative value (-1), but there must be at least one NUMA node, so returning NUMA node zero\n",
      "2022-08-17 12:27:35.127402: I tensorflow/stream_executor/cuda/cuda_gpu_executor.cc:937] successful NUMA node read from SysFS had negative value (-1), but there must be at least one NUMA node, so returning NUMA node zero\n",
      "2022-08-17 12:27:35.128531: I tensorflow/stream_executor/cuda/cuda_gpu_executor.cc:937] successful NUMA node read from SysFS had negative value (-1), but there must be at least one NUMA node, so returning NUMA node zero\n",
      "2022-08-17 12:27:35.129447: I tensorflow/core/common_runtime/gpu/gpu_device.cc:1510] Created device /job:localhost/replica:0/task:0/device:GPU:0 with 15385 MB memory:  -> device: 0, name: Tesla P100-PCIE-16GB, pci bus id: 0000:00:04.0, compute capability: 6.0\n",
      "2022-08-17 12:27:35.131014: I tensorflow/core/grappler/optimizers/meta_optimizer.cc:1137] Optimization results for grappler item: graph_to_optimize\n",
      "  function_optimizer: function_optimizer did nothing. time = 0.007ms.\n",
      "  function_optimizer: function_optimizer did nothing. time = 0.002ms.\n",
      "\n",
      "Incomplete shape.\n",
      "Incomplete shape.\n"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "814/814 [==============================] - 4s 4ms/step - loss: 0.5305 - auc: 0.5506 - val_loss: 0.5081 - val_auc: 0.6060\n",
      "Epoch 2/100\n",
      "814/814 [==============================] - 3s 4ms/step - loss: 0.5099 - auc: 0.5842 - val_loss: 0.5089 - val_auc: 0.6011\n",
      "Epoch 3/100\n",
      "814/814 [==============================] - 4s 5ms/step - loss: 0.5097 - auc: 0.5866 - val_loss: 0.5055 - val_auc: 0.6143\n",
      "Epoch 4/100\n",
      "814/814 [==============================] - 3s 4ms/step - loss: 0.5101 - auc: 0.5850 - val_loss: 0.5082 - val_auc: 0.6070\n",
      "Epoch 5/100\n",
      "814/814 [==============================] - 3s 4ms/step - loss: 0.5098 - auc: 0.5869 - val_loss: 0.5072 - val_auc: 0.6108\n",
      "Epoch 6/100\n",
      "814/814 [==============================] - 4s 5ms/step - loss: 0.5098 - auc: 0.5864 - val_loss: 0.5114 - val_auc: 0.5904\n",
      "Epoch 7/100\n",
      "814/814 [==============================] - 3s 4ms/step - loss: 0.5095 - auc: 0.5878 - val_loss: 0.5076 - val_auc: 0.6070\n",
      "Epoch 8/100\n",
      "814/814 [==============================] - 3s 4ms/step - loss: 0.5099 - auc: 0.5857 - val_loss: 0.5070 - val_auc: 0.6018\n",
      "Train score: 0.5880687 / val score: 0.6148436 for split 5\n"
     ]
    },
    {
     "name": "stderr",
     "output_type": "stream",
     "text": [
      "2022-08-17 12:28:18.063942: I tensorflow/stream_executor/cuda/cuda_gpu_executor.cc:937] successful NUMA node read from SysFS had negative value (-1), but there must be at least one NUMA node, so returning NUMA node zero\n",
      "2022-08-17 12:28:18.065011: I tensorflow/core/grappler/devices.cc:66] Number of eligible GPUs (core count >= 8, compute capability >= 0.0): 1\n",
      "2022-08-17 12:28:18.065179: I tensorflow/core/grappler/clusters/single_machine.cc:357] Starting new session\n",
      "2022-08-17 12:28:18.065874: I tensorflow/stream_executor/cuda/cuda_gpu_executor.cc:937] successful NUMA node read from SysFS had negative value (-1), but there must be at least one NUMA node, so returning NUMA node zero\n",
      "2022-08-17 12:28:18.066948: I tensorflow/stream_executor/cuda/cuda_gpu_executor.cc:937] successful NUMA node read from SysFS had negative value (-1), but there must be at least one NUMA node, so returning NUMA node zero\n",
      "2022-08-17 12:28:18.067973: I tensorflow/stream_executor/cuda/cuda_gpu_executor.cc:937] successful NUMA node read from SysFS had negative value (-1), but there must be at least one NUMA node, so returning NUMA node zero\n",
      "2022-08-17 12:28:18.069343: I tensorflow/stream_executor/cuda/cuda_gpu_executor.cc:937] successful NUMA node read from SysFS had negative value (-1), but there must be at least one NUMA node, so returning NUMA node zero\n",
      "2022-08-17 12:28:18.070382: I tensorflow/stream_executor/cuda/cuda_gpu_executor.cc:937] successful NUMA node read from SysFS had negative value (-1), but there must be at least one NUMA node, so returning NUMA node zero\n",
      "2022-08-17 12:28:18.071254: I tensorflow/core/common_runtime/gpu/gpu_device.cc:1510] Created device /job:localhost/replica:0/task:0/device:GPU:0 with 15385 MB memory:  -> device: 0, name: Tesla P100-PCIE-16GB, pci bus id: 0000:00:04.0, compute capability: 6.0\n",
      "2022-08-17 12:28:18.073002: I tensorflow/core/grappler/optimizers/meta_optimizer.cc:1137] Optimization results for grappler item: graph_to_optimize\n",
      "  function_optimizer: function_optimizer did nothing. time = 0.008ms.\n",
      "  function_optimizer: function_optimizer did nothing. time = 0.003ms.\n",
      "\n",
      "Incomplete shape.\n",
      "Incomplete shape.\n"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "Epoch 1/100\n",
      "814/814 [==============================] - 4s 5ms/step - loss: 0.5272 - auc: 0.5587 - val_loss: 0.5083 - val_auc: 0.5873\n",
      "Epoch 2/100\n",
      "814/814 [==============================] - 3s 4ms/step - loss: 0.5097 - auc: 0.5870 - val_loss: 0.5062 - val_auc: 0.5929\n",
      "Epoch 3/100\n",
      "814/814 [==============================] - 4s 5ms/step - loss: 0.5101 - auc: 0.5851 - val_loss: 0.5064 - val_auc: 0.5886\n",
      "Epoch 4/100\n",
      "814/814 [==============================] - 3s 4ms/step - loss: 0.5100 - auc: 0.5849 - val_loss: 0.5085 - val_auc: 0.5810\n",
      "Epoch 5/100\n",
      "814/814 [==============================] - 3s 4ms/step - loss: 0.5100 - auc: 0.5859 - val_loss: 0.5093 - val_auc: 0.5778\n",
      "Epoch 6/100\n",
      "814/814 [==============================] - 4s 5ms/step - loss: 0.5099 - auc: 0.5857 - val_loss: 0.5104 - val_auc: 0.5804\n",
      "Epoch 7/100\n",
      "814/814 [==============================] - 3s 4ms/step - loss: 0.5098 - auc: 0.5859 - val_loss: 0.5085 - val_auc: 0.5807\n",
      "Train score: 0.5912064 / val score: 0.5941876 for split 6\n",
      "Epoch 1/100\n"
     ]
    },
    {
     "name": "stderr",
     "output_type": "stream",
     "text": [
      "2022-08-17 12:29:00.869763: I tensorflow/stream_executor/cuda/cuda_gpu_executor.cc:937] successful NUMA node read from SysFS had negative value (-1), but there must be at least one NUMA node, so returning NUMA node zero\n",
      "2022-08-17 12:29:00.870644: I tensorflow/core/grappler/devices.cc:66] Number of eligible GPUs (core count >= 8, compute capability >= 0.0): 1\n",
      "2022-08-17 12:29:00.870770: I tensorflow/core/grappler/clusters/single_machine.cc:357] Starting new session\n",
      "2022-08-17 12:29:00.871309: I tensorflow/stream_executor/cuda/cuda_gpu_executor.cc:937] successful NUMA node read from SysFS had negative value (-1), but there must be at least one NUMA node, so returning NUMA node zero\n",
      "2022-08-17 12:29:00.872258: I tensorflow/stream_executor/cuda/cuda_gpu_executor.cc:937] successful NUMA node read from SysFS had negative value (-1), but there must be at least one NUMA node, so returning NUMA node zero\n",
      "2022-08-17 12:29:00.873218: I tensorflow/stream_executor/cuda/cuda_gpu_executor.cc:937] successful NUMA node read from SysFS had negative value (-1), but there must be at least one NUMA node, so returning NUMA node zero\n",
      "2022-08-17 12:29:00.874166: I tensorflow/stream_executor/cuda/cuda_gpu_executor.cc:937] successful NUMA node read from SysFS had negative value (-1), but there must be at least one NUMA node, so returning NUMA node zero\n",
      "2022-08-17 12:29:00.875054: I tensorflow/stream_executor/cuda/cuda_gpu_executor.cc:937] successful NUMA node read from SysFS had negative value (-1), but there must be at least one NUMA node, so returning NUMA node zero\n",
      "2022-08-17 12:29:00.875789: I tensorflow/core/common_runtime/gpu/gpu_device.cc:1510] Created device /job:localhost/replica:0/task:0/device:GPU:0 with 15385 MB memory:  -> device: 0, name: Tesla P100-PCIE-16GB, pci bus id: 0000:00:04.0, compute capability: 6.0\n",
      "2022-08-17 12:29:00.877373: I tensorflow/core/grappler/optimizers/meta_optimizer.cc:1137] Optimization results for grappler item: graph_to_optimize\n",
      "  function_optimizer: function_optimizer did nothing. time = 0.006ms.\n",
      "  function_optimizer: function_optimizer did nothing. time = 0.001ms.\n",
      "\n",
      "Incomplete shape.\n",
      "Incomplete shape.\n"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "814/814 [==============================] - 5s 5ms/step - loss: 0.5245 - auc: 0.5640 - val_loss: 0.5094 - val_auc: 0.6010\n",
      "Epoch 2/100\n",
      "814/814 [==============================] - 3s 4ms/step - loss: 0.5100 - auc: 0.5855 - val_loss: 0.5104 - val_auc: 0.5902\n",
      "Epoch 3/100\n",
      "814/814 [==============================] - 4s 4ms/step - loss: 0.5099 - auc: 0.5861 - val_loss: 0.5090 - val_auc: 0.6089\n",
      "Epoch 4/100\n",
      "814/814 [==============================] - 3s 4ms/step - loss: 0.5098 - auc: 0.5863 - val_loss: 0.5116 - val_auc: 0.5979\n",
      "Epoch 5/100\n",
      "814/814 [==============================] - 3s 4ms/step - loss: 0.5099 - auc: 0.5851 - val_loss: 0.5076 - val_auc: 0.6132\n",
      "Epoch 6/100\n",
      "814/814 [==============================] - 4s 5ms/step - loss: 0.5099 - auc: 0.5854 - val_loss: 0.5083 - val_auc: 0.6111\n",
      "Epoch 7/100\n",
      "814/814 [==============================] - 4s 4ms/step - loss: 0.5092 - auc: 0.5885 - val_loss: 0.5081 - val_auc: 0.6083\n",
      "Epoch 8/100\n",
      "814/814 [==============================] - 3s 4ms/step - loss: 0.5097 - auc: 0.5870 - val_loss: 0.5088 - val_auc: 0.6051\n",
      "Epoch 9/100\n",
      "814/814 [==============================] - 4s 5ms/step - loss: 0.5095 - auc: 0.5882 - val_loss: 0.5112 - val_auc: 0.5848\n",
      "Epoch 10/100\n",
      "814/814 [==============================] - 4s 5ms/step - loss: 0.5101 - auc: 0.5840 - val_loss: 0.5097 - val_auc: 0.5975\n",
      "Train score: 0.5904554 / val score: 0.6138509 for split 7\n",
      "Epoch 1/100\n"
     ]
    },
    {
     "name": "stderr",
     "output_type": "stream",
     "text": [
      "2022-08-17 12:29:44.744660: I tensorflow/stream_executor/cuda/cuda_gpu_executor.cc:937] successful NUMA node read from SysFS had negative value (-1), but there must be at least one NUMA node, so returning NUMA node zero\n",
      "2022-08-17 12:29:44.745613: I tensorflow/core/grappler/devices.cc:66] Number of eligible GPUs (core count >= 8, compute capability >= 0.0): 1\n",
      "2022-08-17 12:29:44.745744: I tensorflow/core/grappler/clusters/single_machine.cc:357] Starting new session\n",
      "2022-08-17 12:29:44.746265: I tensorflow/stream_executor/cuda/cuda_gpu_executor.cc:937] successful NUMA node read from SysFS had negative value (-1), but there must be at least one NUMA node, so returning NUMA node zero\n",
      "2022-08-17 12:29:44.747301: I tensorflow/stream_executor/cuda/cuda_gpu_executor.cc:937] successful NUMA node read from SysFS had negative value (-1), but there must be at least one NUMA node, so returning NUMA node zero\n",
      "2022-08-17 12:29:44.748198: I tensorflow/stream_executor/cuda/cuda_gpu_executor.cc:937] successful NUMA node read from SysFS had negative value (-1), but there must be at least one NUMA node, so returning NUMA node zero\n",
      "2022-08-17 12:29:44.749169: I tensorflow/stream_executor/cuda/cuda_gpu_executor.cc:937] successful NUMA node read from SysFS had negative value (-1), but there must be at least one NUMA node, so returning NUMA node zero\n",
      "2022-08-17 12:29:44.750103: I tensorflow/stream_executor/cuda/cuda_gpu_executor.cc:937] successful NUMA node read from SysFS had negative value (-1), but there must be at least one NUMA node, so returning NUMA node zero\n",
      "2022-08-17 12:29:44.750909: I tensorflow/core/common_runtime/gpu/gpu_device.cc:1510] Created device /job:localhost/replica:0/task:0/device:GPU:0 with 15385 MB memory:  -> device: 0, name: Tesla P100-PCIE-16GB, pci bus id: 0000:00:04.0, compute capability: 6.0\n",
      "2022-08-17 12:29:44.752529: I tensorflow/core/grappler/optimizers/meta_optimizer.cc:1137] Optimization results for grappler item: graph_to_optimize\n",
      "  function_optimizer: function_optimizer did nothing. time = 0.007ms.\n",
      "  function_optimizer: function_optimizer did nothing. time = 0.002ms.\n",
      "\n",
      "Incomplete shape.\n",
      "Incomplete shape.\n"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "814/814 [==============================] - 5s 5ms/step - loss: 0.5248 - auc: 0.5600 - val_loss: 0.5114 - val_auc: 0.5689\n",
      "Epoch 2/100\n",
      "814/814 [==============================] - 3s 4ms/step - loss: 0.5099 - auc: 0.5854 - val_loss: 0.5069 - val_auc: 0.5983\n",
      "Epoch 3/100\n",
      "814/814 [==============================] - 4s 5ms/step - loss: 0.5100 - auc: 0.5860 - val_loss: 0.5048 - val_auc: 0.6053\n",
      "Epoch 4/100\n",
      "814/814 [==============================] - 4s 5ms/step - loss: 0.5099 - auc: 0.5853 - val_loss: 0.5050 - val_auc: 0.6066\n",
      "Epoch 5/100\n",
      "814/814 [==============================] - 4s 5ms/step - loss: 0.5098 - auc: 0.5851 - val_loss: 0.5044 - val_auc: 0.6112\n",
      "Epoch 6/100\n",
      "814/814 [==============================] - 4s 5ms/step - loss: 0.5098 - auc: 0.5861 - val_loss: 0.5092 - val_auc: 0.5858\n",
      "Epoch 7/100\n",
      "814/814 [==============================] - 3s 4ms/step - loss: 0.5099 - auc: 0.5851 - val_loss: 0.5036 - val_auc: 0.6112\n",
      "Epoch 8/100\n",
      "814/814 [==============================] - 3s 4ms/step - loss: 0.5097 - auc: 0.5864 - val_loss: 0.5064 - val_auc: 0.6001\n",
      "Epoch 9/100\n",
      "814/814 [==============================] - 4s 5ms/step - loss: 0.5099 - auc: 0.5849 - val_loss: 0.5039 - val_auc: 0.6172\n",
      "Epoch 10/100\n",
      "814/814 [==============================] - 4s 4ms/step - loss: 0.5099 - auc: 0.5848 - val_loss: 0.5072 - val_auc: 0.5956\n",
      "Epoch 11/100\n",
      "814/814 [==============================] - 3s 4ms/step - loss: 0.5098 - auc: 0.5860 - val_loss: 0.5074 - val_auc: 0.5935\n",
      "Epoch 12/100\n",
      "814/814 [==============================] - 4s 5ms/step - loss: 0.5098 - auc: 0.5866 - val_loss: 0.5058 - val_auc: 0.6040\n",
      "Epoch 13/100\n",
      "814/814 [==============================] - 4s 4ms/step - loss: 0.5098 - auc: 0.5866 - val_loss: 0.5094 - val_auc: 0.5901\n",
      "Epoch 14/100\n",
      "814/814 [==============================] - 4s 5ms/step - loss: 0.5101 - auc: 0.5843 - val_loss: 0.5076 - val_auc: 0.6001\n",
      "Train score: 0.5901346 / val score: 0.6150126 for split 8\n",
      "Epoch 1/100\n"
     ]
    },
    {
     "name": "stderr",
     "output_type": "stream",
     "text": [
      "2022-08-17 12:31:09.158453: I tensorflow/stream_executor/cuda/cuda_gpu_executor.cc:937] successful NUMA node read from SysFS had negative value (-1), but there must be at least one NUMA node, so returning NUMA node zero\n",
      "2022-08-17 12:31:09.159336: I tensorflow/core/grappler/devices.cc:66] Number of eligible GPUs (core count >= 8, compute capability >= 0.0): 1\n",
      "2022-08-17 12:31:09.159462: I tensorflow/core/grappler/clusters/single_machine.cc:357] Starting new session\n",
      "2022-08-17 12:31:09.160020: I tensorflow/stream_executor/cuda/cuda_gpu_executor.cc:937] successful NUMA node read from SysFS had negative value (-1), but there must be at least one NUMA node, so returning NUMA node zero\n",
      "2022-08-17 12:31:09.160939: I tensorflow/stream_executor/cuda/cuda_gpu_executor.cc:937] successful NUMA node read from SysFS had negative value (-1), but there must be at least one NUMA node, so returning NUMA node zero\n",
      "2022-08-17 12:31:09.161815: I tensorflow/stream_executor/cuda/cuda_gpu_executor.cc:937] successful NUMA node read from SysFS had negative value (-1), but there must be at least one NUMA node, so returning NUMA node zero\n",
      "2022-08-17 12:31:09.162851: I tensorflow/stream_executor/cuda/cuda_gpu_executor.cc:937] successful NUMA node read from SysFS had negative value (-1), but there must be at least one NUMA node, so returning NUMA node zero\n",
      "2022-08-17 12:31:09.163766: I tensorflow/stream_executor/cuda/cuda_gpu_executor.cc:937] successful NUMA node read from SysFS had negative value (-1), but there must be at least one NUMA node, so returning NUMA node zero\n",
      "2022-08-17 12:31:09.164585: I tensorflow/core/common_runtime/gpu/gpu_device.cc:1510] Created device /job:localhost/replica:0/task:0/device:GPU:0 with 15385 MB memory:  -> device: 0, name: Tesla P100-PCIE-16GB, pci bus id: 0000:00:04.0, compute capability: 6.0\n",
      "2022-08-17 12:31:09.166074: I tensorflow/core/grappler/optimizers/meta_optimizer.cc:1137] Optimization results for grappler item: graph_to_optimize\n",
      "  function_optimizer: function_optimizer did nothing. time = 0.007ms.\n",
      "  function_optimizer: function_optimizer did nothing. time = 0.001ms.\n",
      "\n",
      "Incomplete shape.\n",
      "Incomplete shape.\n"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "814/814 [==============================] - 5s 5ms/step - loss: 0.5232 - auc: 0.5707 - val_loss: 0.5208 - val_auc: 0.5493\n",
      "Epoch 2/100\n",
      "814/814 [==============================] - 3s 4ms/step - loss: 0.5099 - auc: 0.5850 - val_loss: 0.5190 - val_auc: 0.5511\n",
      "Epoch 3/100\n",
      "814/814 [==============================] - 3s 4ms/step - loss: 0.5095 - auc: 0.5872 - val_loss: 0.5192 - val_auc: 0.5412\n",
      "Epoch 4/100\n",
      "814/814 [==============================] - 4s 5ms/step - loss: 0.5094 - auc: 0.5879 - val_loss: 0.5216 - val_auc: 0.5467\n",
      "Epoch 5/100\n",
      "814/814 [==============================] - 3s 4ms/step - loss: 0.5095 - auc: 0.5877 - val_loss: 0.5197 - val_auc: 0.5460\n",
      "Epoch 6/100\n",
      "814/814 [==============================] - 3s 4ms/step - loss: 0.5095 - auc: 0.5860 - val_loss: 0.5187 - val_auc: 0.5379\n",
      "Epoch 7/100\n",
      "814/814 [==============================] - 3s 4ms/step - loss: 0.5094 - auc: 0.5874 - val_loss: 0.5175 - val_auc: 0.5448\n",
      "Train score: 0.5935107 / val score: 0.5512704 for split 9\n",
      "Epoch 1/100\n"
     ]
    },
    {
     "name": "stderr",
     "output_type": "stream",
     "text": [
      "2022-08-17 12:31:52.621157: I tensorflow/stream_executor/cuda/cuda_gpu_executor.cc:937] successful NUMA node read from SysFS had negative value (-1), but there must be at least one NUMA node, so returning NUMA node zero\n",
      "2022-08-17 12:31:52.622167: I tensorflow/core/grappler/devices.cc:66] Number of eligible GPUs (core count >= 8, compute capability >= 0.0): 1\n",
      "2022-08-17 12:31:52.622288: I tensorflow/core/grappler/clusters/single_machine.cc:357] Starting new session\n",
      "2022-08-17 12:31:52.622854: I tensorflow/stream_executor/cuda/cuda_gpu_executor.cc:937] successful NUMA node read from SysFS had negative value (-1), but there must be at least one NUMA node, so returning NUMA node zero\n",
      "2022-08-17 12:31:52.623936: I tensorflow/stream_executor/cuda/cuda_gpu_executor.cc:937] successful NUMA node read from SysFS had negative value (-1), but there must be at least one NUMA node, so returning NUMA node zero\n",
      "2022-08-17 12:31:52.624903: I tensorflow/stream_executor/cuda/cuda_gpu_executor.cc:937] successful NUMA node read from SysFS had negative value (-1), but there must be at least one NUMA node, so returning NUMA node zero\n",
      "2022-08-17 12:31:52.625837: I tensorflow/stream_executor/cuda/cuda_gpu_executor.cc:937] successful NUMA node read from SysFS had negative value (-1), but there must be at least one NUMA node, so returning NUMA node zero\n",
      "2022-08-17 12:31:52.626768: I tensorflow/stream_executor/cuda/cuda_gpu_executor.cc:937] successful NUMA node read from SysFS had negative value (-1), but there must be at least one NUMA node, so returning NUMA node zero\n",
      "2022-08-17 12:31:52.627645: I tensorflow/core/common_runtime/gpu/gpu_device.cc:1510] Created device /job:localhost/replica:0/task:0/device:GPU:0 with 15385 MB memory:  -> device: 0, name: Tesla P100-PCIE-16GB, pci bus id: 0000:00:04.0, compute capability: 6.0\n",
      "2022-08-17 12:31:52.629178: I tensorflow/core/grappler/optimizers/meta_optimizer.cc:1137] Optimization results for grappler item: graph_to_optimize\n",
      "  function_optimizer: function_optimizer did nothing. time = 0.006ms.\n",
      "  function_optimizer: function_optimizer did nothing. time = 0.001ms.\n",
      "\n",
      "Incomplete shape.\n",
      "Incomplete shape.\n"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "814/814 [==============================] - 5s 5ms/step - loss: 0.5286 - auc: 0.5606 - val_loss: 0.4998 - val_auc: 0.6176\n",
      "Epoch 2/100\n",
      "814/814 [==============================] - 4s 4ms/step - loss: 0.5100 - auc: 0.5856 - val_loss: 0.4993 - val_auc: 0.6229\n",
      "Epoch 3/100\n",
      "814/814 [==============================] - 3s 4ms/step - loss: 0.5099 - auc: 0.5857 - val_loss: 0.4971 - val_auc: 0.6358\n",
      "Epoch 4/100\n",
      "814/814 [==============================] - 3s 4ms/step - loss: 0.5098 - auc: 0.5862 - val_loss: 0.4958 - val_auc: 0.6521\n",
      "Epoch 5/100\n",
      "814/814 [==============================] - 4s 5ms/step - loss: 0.5100 - auc: 0.5853 - val_loss: 0.4940 - val_auc: 0.6603\n",
      "Epoch 6/100\n",
      "814/814 [==============================] - 4s 5ms/step - loss: 0.5101 - auc: 0.5847 - val_loss: 0.4992 - val_auc: 0.6282\n",
      "Epoch 7/100\n",
      "814/814 [==============================] - 3s 4ms/step - loss: 0.5099 - auc: 0.5839 - val_loss: 0.4961 - val_auc: 0.6297\n",
      "Epoch 8/100\n",
      "814/814 [==============================] - 4s 5ms/step - loss: 0.5101 - auc: 0.5855 - val_loss: 0.4933 - val_auc: 0.6551\n",
      "Epoch 9/100\n",
      "814/814 [==============================] - 4s 5ms/step - loss: 0.5099 - auc: 0.5862 - val_loss: 0.4975 - val_auc: 0.6362\n",
      "Epoch 10/100\n",
      "814/814 [==============================] - 3s 4ms/step - loss: 0.5100 - auc: 0.5850 - val_loss: 0.4945 - val_auc: 0.6452\n",
      "Train score: 0.5870685 / val score: 0.6605487 for split 10\n",
      "Epoch 1/100\n"
     ]
    },
    {
     "name": "stderr",
     "output_type": "stream",
     "text": [
      "2022-08-17 12:32:31.391637: I tensorflow/stream_executor/cuda/cuda_gpu_executor.cc:937] successful NUMA node read from SysFS had negative value (-1), but there must be at least one NUMA node, so returning NUMA node zero\n",
      "2022-08-17 12:32:31.392735: I tensorflow/core/grappler/devices.cc:66] Number of eligible GPUs (core count >= 8, compute capability >= 0.0): 1\n",
      "2022-08-17 12:32:31.392915: I tensorflow/core/grappler/clusters/single_machine.cc:357] Starting new session\n",
      "2022-08-17 12:32:31.393628: I tensorflow/stream_executor/cuda/cuda_gpu_executor.cc:937] successful NUMA node read from SysFS had negative value (-1), but there must be at least one NUMA node, so returning NUMA node zero\n",
      "2022-08-17 12:32:31.394594: I tensorflow/stream_executor/cuda/cuda_gpu_executor.cc:937] successful NUMA node read from SysFS had negative value (-1), but there must be at least one NUMA node, so returning NUMA node zero\n",
      "2022-08-17 12:32:31.395508: I tensorflow/stream_executor/cuda/cuda_gpu_executor.cc:937] successful NUMA node read from SysFS had negative value (-1), but there must be at least one NUMA node, so returning NUMA node zero\n",
      "2022-08-17 12:32:31.396468: I tensorflow/stream_executor/cuda/cuda_gpu_executor.cc:937] successful NUMA node read from SysFS had negative value (-1), but there must be at least one NUMA node, so returning NUMA node zero\n",
      "2022-08-17 12:32:31.397382: I tensorflow/stream_executor/cuda/cuda_gpu_executor.cc:937] successful NUMA node read from SysFS had negative value (-1), but there must be at least one NUMA node, so returning NUMA node zero\n",
      "2022-08-17 12:32:31.398271: I tensorflow/core/common_runtime/gpu/gpu_device.cc:1510] Created device /job:localhost/replica:0/task:0/device:GPU:0 with 15385 MB memory:  -> device: 0, name: Tesla P100-PCIE-16GB, pci bus id: 0000:00:04.0, compute capability: 6.0\n",
      "2022-08-17 12:32:31.399736: I tensorflow/core/grappler/optimizers/meta_optimizer.cc:1137] Optimization results for grappler item: graph_to_optimize\n",
      "  function_optimizer: function_optimizer did nothing. time = 0.006ms.\n",
      "  function_optimizer: function_optimizer did nothing. time = 0.001ms.\n",
      "\n",
      "Incomplete shape.\n",
      "Incomplete shape.\n"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "814/814 [==============================] - 5s 5ms/step - loss: 0.5297 - auc: 0.5622 - val_loss: 0.5041 - val_auc: 0.6095\n",
      "Epoch 2/100\n",
      "814/814 [==============================] - 3s 4ms/step - loss: 0.5099 - auc: 0.5858 - val_loss: 0.5009 - val_auc: 0.6253\n",
      "Epoch 3/100\n",
      "814/814 [==============================] - 4s 4ms/step - loss: 0.5100 - auc: 0.5850 - val_loss: 0.5045 - val_auc: 0.6077\n",
      "Epoch 4/100\n",
      "814/814 [==============================] - 3s 4ms/step - loss: 0.5098 - auc: 0.5862 - val_loss: 0.5031 - val_auc: 0.6135\n",
      "Epoch 5/100\n",
      "814/814 [==============================] - 3s 4ms/step - loss: 0.5098 - auc: 0.5866 - val_loss: 0.5028 - val_auc: 0.6154\n",
      "Epoch 6/100\n",
      "814/814 [==============================] - 4s 5ms/step - loss: 0.5101 - auc: 0.5855 - val_loss: 0.5042 - val_auc: 0.6129\n",
      "Epoch 7/100\n",
      "814/814 [==============================] - 5s 6ms/step - loss: 0.5096 - auc: 0.5867 - val_loss: 0.5007 - val_auc: 0.6265\n",
      "Epoch 8/100\n",
      "814/814 [==============================] - 3s 4ms/step - loss: 0.5099 - auc: 0.5864 - val_loss: 0.5028 - val_auc: 0.6188\n",
      "Epoch 9/100\n",
      "814/814 [==============================] - 4s 5ms/step - loss: 0.5098 - auc: 0.5880 - val_loss: 0.5018 - val_auc: 0.6218\n",
      "Epoch 10/100\n",
      "814/814 [==============================] - 3s 4ms/step - loss: 0.5096 - auc: 0.5871 - val_loss: 0.5015 - val_auc: 0.6161\n",
      "Epoch 11/100\n",
      "814/814 [==============================] - 3s 4ms/step - loss: 0.5097 - auc: 0.5871 - val_loss: 0.5041 - val_auc: 0.6150\n",
      "Epoch 12/100\n",
      "814/814 [==============================] - 4s 5ms/step - loss: 0.5099 - auc: 0.5860 - val_loss: 0.5034 - val_auc: 0.6150\n",
      "Train score: 0.5910520 / val score: 0.6261220 for split 11\n",
      "Epoch 1/100\n"
     ]
    },
    {
     "name": "stderr",
     "output_type": "stream",
     "text": [
      "2022-08-17 12:33:55.468482: I tensorflow/stream_executor/cuda/cuda_gpu_executor.cc:937] successful NUMA node read from SysFS had negative value (-1), but there must be at least one NUMA node, so returning NUMA node zero\n",
      "2022-08-17 12:33:55.469315: I tensorflow/core/grappler/devices.cc:66] Number of eligible GPUs (core count >= 8, compute capability >= 0.0): 1\n",
      "2022-08-17 12:33:55.469431: I tensorflow/core/grappler/clusters/single_machine.cc:357] Starting new session\n",
      "2022-08-17 12:33:55.470008: I tensorflow/stream_executor/cuda/cuda_gpu_executor.cc:937] successful NUMA node read from SysFS had negative value (-1), but there must be at least one NUMA node, so returning NUMA node zero\n",
      "2022-08-17 12:33:55.470980: I tensorflow/stream_executor/cuda/cuda_gpu_executor.cc:937] successful NUMA node read from SysFS had negative value (-1), but there must be at least one NUMA node, so returning NUMA node zero\n",
      "2022-08-17 12:33:55.471882: I tensorflow/stream_executor/cuda/cuda_gpu_executor.cc:937] successful NUMA node read from SysFS had negative value (-1), but there must be at least one NUMA node, so returning NUMA node zero\n",
      "2022-08-17 12:33:55.472877: I tensorflow/stream_executor/cuda/cuda_gpu_executor.cc:937] successful NUMA node read from SysFS had negative value (-1), but there must be at least one NUMA node, so returning NUMA node zero\n",
      "2022-08-17 12:33:55.473743: I tensorflow/stream_executor/cuda/cuda_gpu_executor.cc:937] successful NUMA node read from SysFS had negative value (-1), but there must be at least one NUMA node, so returning NUMA node zero\n",
      "2022-08-17 12:33:55.474497: I tensorflow/core/common_runtime/gpu/gpu_device.cc:1510] Created device /job:localhost/replica:0/task:0/device:GPU:0 with 15385 MB memory:  -> device: 0, name: Tesla P100-PCIE-16GB, pci bus id: 0000:00:04.0, compute capability: 6.0\n",
      "2022-08-17 12:33:55.476062: I tensorflow/core/grappler/optimizers/meta_optimizer.cc:1137] Optimization results for grappler item: graph_to_optimize\n",
      "  function_optimizer: function_optimizer did nothing. time = 0.012ms.\n",
      "  function_optimizer: function_optimizer did nothing. time = 0.001ms.\n",
      "\n",
      "Incomplete shape.\n",
      "Incomplete shape.\n"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "814/814 [==============================] - 5s 5ms/step - loss: 0.5266 - auc: 0.5655 - val_loss: 0.5072 - val_auc: 0.6107\n",
      "Epoch 2/100\n",
      "814/814 [==============================] - 3s 4ms/step - loss: 0.5098 - auc: 0.5868 - val_loss: 0.5086 - val_auc: 0.5972\n",
      "Epoch 3/100\n",
      "814/814 [==============================] - 4s 5ms/step - loss: 0.5096 - auc: 0.5876 - val_loss: 0.5076 - val_auc: 0.6127\n",
      "Epoch 4/100\n",
      "814/814 [==============================] - 4s 5ms/step - loss: 0.5096 - auc: 0.5878 - val_loss: 0.5086 - val_auc: 0.5930\n",
      "Epoch 5/100\n",
      "814/814 [==============================] - 3s 4ms/step - loss: 0.5095 - auc: 0.5883 - val_loss: 0.5078 - val_auc: 0.6013\n",
      "Epoch 6/100\n",
      "814/814 [==============================] - 3s 4ms/step - loss: 0.5098 - auc: 0.5865 - val_loss: 0.5108 - val_auc: 0.5935\n",
      "Epoch 7/100\n",
      "814/814 [==============================] - 4s 5ms/step - loss: 0.5098 - auc: 0.5850 - val_loss: 0.5108 - val_auc: 0.5888\n",
      "Epoch 8/100\n",
      "814/814 [==============================] - 3s 4ms/step - loss: 0.5098 - auc: 0.5866 - val_loss: 0.5124 - val_auc: 0.5781\n",
      "Train score: 0.5888149 / val score: 0.6153716 for split 12\n",
      "Epoch 1/100\n"
     ]
    },
    {
     "name": "stderr",
     "output_type": "stream",
     "text": [
      "2022-08-17 12:34:26.934538: I tensorflow/stream_executor/cuda/cuda_gpu_executor.cc:937] successful NUMA node read from SysFS had negative value (-1), but there must be at least one NUMA node, so returning NUMA node zero\n",
      "2022-08-17 12:34:26.935350: I tensorflow/core/grappler/devices.cc:66] Number of eligible GPUs (core count >= 8, compute capability >= 0.0): 1\n",
      "2022-08-17 12:34:26.935474: I tensorflow/core/grappler/clusters/single_machine.cc:357] Starting new session\n",
      "2022-08-17 12:34:26.935975: I tensorflow/stream_executor/cuda/cuda_gpu_executor.cc:937] successful NUMA node read from SysFS had negative value (-1), but there must be at least one NUMA node, so returning NUMA node zero\n",
      "2022-08-17 12:34:26.936827: I tensorflow/stream_executor/cuda/cuda_gpu_executor.cc:937] successful NUMA node read from SysFS had negative value (-1), but there must be at least one NUMA node, so returning NUMA node zero\n",
      "2022-08-17 12:34:26.937676: I tensorflow/stream_executor/cuda/cuda_gpu_executor.cc:937] successful NUMA node read from SysFS had negative value (-1), but there must be at least one NUMA node, so returning NUMA node zero\n",
      "2022-08-17 12:34:26.938613: I tensorflow/stream_executor/cuda/cuda_gpu_executor.cc:937] successful NUMA node read from SysFS had negative value (-1), but there must be at least one NUMA node, so returning NUMA node zero\n",
      "2022-08-17 12:34:26.939549: I tensorflow/stream_executor/cuda/cuda_gpu_executor.cc:937] successful NUMA node read from SysFS had negative value (-1), but there must be at least one NUMA node, so returning NUMA node zero\n",
      "2022-08-17 12:34:26.940284: I tensorflow/core/common_runtime/gpu/gpu_device.cc:1510] Created device /job:localhost/replica:0/task:0/device:GPU:0 with 15385 MB memory:  -> device: 0, name: Tesla P100-PCIE-16GB, pci bus id: 0000:00:04.0, compute capability: 6.0\n",
      "2022-08-17 12:34:26.942503: I tensorflow/core/grappler/optimizers/meta_optimizer.cc:1137] Optimization results for grappler item: graph_to_optimize\n",
      "  function_optimizer: function_optimizer did nothing. time = 0.006ms.\n",
      "  function_optimizer: function_optimizer did nothing. time = 0.001ms.\n",
      "\n",
      "Incomplete shape.\n",
      "Incomplete shape.\n"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "814/814 [==============================] - 5s 5ms/step - loss: 0.5272 - auc: 0.5608 - val_loss: 0.5017 - val_auc: 0.6241\n",
      "Epoch 2/100\n",
      "814/814 [==============================] - 3s 4ms/step - loss: 0.5099 - auc: 0.5855 - val_loss: 0.5021 - val_auc: 0.6286\n",
      "Epoch 3/100\n",
      "814/814 [==============================] - 3s 4ms/step - loss: 0.5100 - auc: 0.5856 - val_loss: 0.5039 - val_auc: 0.6122\n",
      "Epoch 4/100\n",
      "814/814 [==============================] - 3s 4ms/step - loss: 0.5097 - auc: 0.5849 - val_loss: 0.5009 - val_auc: 0.6325\n",
      "Epoch 5/100\n",
      "814/814 [==============================] - 4s 5ms/step - loss: 0.5101 - auc: 0.5854 - val_loss: 0.5045 - val_auc: 0.6106\n",
      "Epoch 6/100\n",
      "814/814 [==============================] - 3s 4ms/step - loss: 0.5099 - auc: 0.5854 - val_loss: 0.5041 - val_auc: 0.6283\n",
      "Epoch 7/100\n",
      "814/814 [==============================] - 4s 4ms/step - loss: 0.5100 - auc: 0.5847 - val_loss: 0.5052 - val_auc: 0.6056\n",
      "Epoch 8/100\n",
      "814/814 [==============================] - 4s 5ms/step - loss: 0.5099 - auc: 0.5847 - val_loss: 0.5028 - val_auc: 0.6142\n",
      "Epoch 9/100\n",
      "814/814 [==============================] - 4s 5ms/step - loss: 0.5099 - auc: 0.5868 - val_loss: 0.5043 - val_auc: 0.6065\n",
      "Train score: 0.5879916 / val score: 0.6322259 for split 13\n",
      "Epoch 1/100\n"
     ]
    },
    {
     "name": "stderr",
     "output_type": "stream",
     "text": [
      "2022-08-17 12:35:10.384649: I tensorflow/stream_executor/cuda/cuda_gpu_executor.cc:937] successful NUMA node read from SysFS had negative value (-1), but there must be at least one NUMA node, so returning NUMA node zero\n",
      "2022-08-17 12:35:10.385677: I tensorflow/core/grappler/devices.cc:66] Number of eligible GPUs (core count >= 8, compute capability >= 0.0): 1\n",
      "2022-08-17 12:35:10.385825: I tensorflow/core/grappler/clusters/single_machine.cc:357] Starting new session\n",
      "2022-08-17 12:35:10.386520: I tensorflow/stream_executor/cuda/cuda_gpu_executor.cc:937] successful NUMA node read from SysFS had negative value (-1), but there must be at least one NUMA node, so returning NUMA node zero\n",
      "2022-08-17 12:35:10.387502: I tensorflow/stream_executor/cuda/cuda_gpu_executor.cc:937] successful NUMA node read from SysFS had negative value (-1), but there must be at least one NUMA node, so returning NUMA node zero\n",
      "2022-08-17 12:35:10.388419: I tensorflow/stream_executor/cuda/cuda_gpu_executor.cc:937] successful NUMA node read from SysFS had negative value (-1), but there must be at least one NUMA node, so returning NUMA node zero\n",
      "2022-08-17 12:35:10.389511: I tensorflow/stream_executor/cuda/cuda_gpu_executor.cc:937] successful NUMA node read from SysFS had negative value (-1), but there must be at least one NUMA node, so returning NUMA node zero\n",
      "2022-08-17 12:35:10.390526: I tensorflow/stream_executor/cuda/cuda_gpu_executor.cc:937] successful NUMA node read from SysFS had negative value (-1), but there must be at least one NUMA node, so returning NUMA node zero\n",
      "2022-08-17 12:35:10.391317: I tensorflow/core/common_runtime/gpu/gpu_device.cc:1510] Created device /job:localhost/replica:0/task:0/device:GPU:0 with 15385 MB memory:  -> device: 0, name: Tesla P100-PCIE-16GB, pci bus id: 0000:00:04.0, compute capability: 6.0\n",
      "2022-08-17 12:35:10.393065: I tensorflow/core/grappler/optimizers/meta_optimizer.cc:1137] Optimization results for grappler item: graph_to_optimize\n",
      "  function_optimizer: function_optimizer did nothing. time = 0.029ms.\n",
      "  function_optimizer: function_optimizer did nothing. time = 0.004ms.\n",
      "\n",
      "Incomplete shape.\n",
      "Incomplete shape.\n"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "814/814 [==============================] - 4s 5ms/step - loss: 0.5308 - auc: 0.5648 - val_loss: 0.5027 - val_auc: 0.6354\n",
      "Epoch 2/100\n",
      "814/814 [==============================] - 4s 5ms/step - loss: 0.5098 - auc: 0.5850 - val_loss: 0.5036 - val_auc: 0.6277\n",
      "Epoch 3/100\n",
      "814/814 [==============================] - 3s 4ms/step - loss: 0.5099 - auc: 0.5868 - val_loss: 0.5056 - val_auc: 0.6170\n",
      "Epoch 4/100\n",
      "814/814 [==============================] - 4s 5ms/step - loss: 0.5096 - auc: 0.5865 - val_loss: 0.5015 - val_auc: 0.6271\n",
      "Epoch 5/100\n",
      "814/814 [==============================] - 4s 5ms/step - loss: 0.5096 - auc: 0.5873 - val_loss: 0.5070 - val_auc: 0.6137\n",
      "Epoch 6/100\n",
      "814/814 [==============================] - 4s 5ms/step - loss: 0.5100 - auc: 0.5845 - val_loss: 0.5012 - val_auc: 0.6340\n",
      "Train score: 0.5911923 / val score: 0.6346548 for split 14\n",
      "Epoch 1/100\n"
     ]
    },
    {
     "name": "stderr",
     "output_type": "stream",
     "text": [
      "2022-08-17 12:35:53.516018: I tensorflow/stream_executor/cuda/cuda_gpu_executor.cc:937] successful NUMA node read from SysFS had negative value (-1), but there must be at least one NUMA node, so returning NUMA node zero\n",
      "2022-08-17 12:35:53.517176: I tensorflow/core/grappler/devices.cc:66] Number of eligible GPUs (core count >= 8, compute capability >= 0.0): 1\n",
      "2022-08-17 12:35:53.517304: I tensorflow/core/grappler/clusters/single_machine.cc:357] Starting new session\n",
      "2022-08-17 12:35:53.517879: I tensorflow/stream_executor/cuda/cuda_gpu_executor.cc:937] successful NUMA node read from SysFS had negative value (-1), but there must be at least one NUMA node, so returning NUMA node zero\n",
      "2022-08-17 12:35:53.519007: I tensorflow/stream_executor/cuda/cuda_gpu_executor.cc:937] successful NUMA node read from SysFS had negative value (-1), but there must be at least one NUMA node, so returning NUMA node zero\n",
      "2022-08-17 12:35:53.520024: I tensorflow/stream_executor/cuda/cuda_gpu_executor.cc:937] successful NUMA node read from SysFS had negative value (-1), but there must be at least one NUMA node, so returning NUMA node zero\n",
      "2022-08-17 12:35:53.521119: I tensorflow/stream_executor/cuda/cuda_gpu_executor.cc:937] successful NUMA node read from SysFS had negative value (-1), but there must be at least one NUMA node, so returning NUMA node zero\n",
      "2022-08-17 12:35:53.522079: I tensorflow/stream_executor/cuda/cuda_gpu_executor.cc:937] successful NUMA node read from SysFS had negative value (-1), but there must be at least one NUMA node, so returning NUMA node zero\n",
      "2022-08-17 12:35:53.522898: I tensorflow/core/common_runtime/gpu/gpu_device.cc:1510] Created device /job:localhost/replica:0/task:0/device:GPU:0 with 15385 MB memory:  -> device: 0, name: Tesla P100-PCIE-16GB, pci bus id: 0000:00:04.0, compute capability: 6.0\n",
      "2022-08-17 12:35:53.524426: I tensorflow/core/grappler/optimizers/meta_optimizer.cc:1137] Optimization results for grappler item: graph_to_optimize\n",
      "  function_optimizer: function_optimizer did nothing. time = 0.007ms.\n",
      "  function_optimizer: function_optimizer did nothing. time = 0.001ms.\n",
      "\n",
      "Incomplete shape.\n",
      "Incomplete shape.\n"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "814/814 [==============================] - 4s 4ms/step - loss: 0.5295 - auc: 0.5648 - val_loss: 0.5141 - val_auc: 0.5440\n",
      "Epoch 2/100\n",
      "814/814 [==============================] - 4s 5ms/step - loss: 0.5098 - auc: 0.5865 - val_loss: 0.5139 - val_auc: 0.5668\n",
      "Epoch 3/100\n",
      "814/814 [==============================] - 4s 5ms/step - loss: 0.5093 - auc: 0.5886 - val_loss: 0.5122 - val_auc: 0.5632\n",
      "Epoch 4/100\n",
      "814/814 [==============================] - 4s 5ms/step - loss: 0.5094 - auc: 0.5877 - val_loss: 0.5159 - val_auc: 0.5514\n",
      "Epoch 5/100\n",
      "814/814 [==============================] - 4s 5ms/step - loss: 0.5099 - auc: 0.5860 - val_loss: 0.5125 - val_auc: 0.5732\n",
      "Epoch 6/100\n",
      "814/814 [==============================] - 3s 4ms/step - loss: 0.5095 - auc: 0.5880 - val_loss: 0.5133 - val_auc: 0.5649\n",
      "Epoch 7/100\n",
      "814/814 [==============================] - 3s 4ms/step - loss: 0.5093 - auc: 0.5882 - val_loss: 0.5111 - val_auc: 0.5762\n",
      "Epoch 8/100\n",
      "814/814 [==============================] - 4s 5ms/step - loss: 0.5096 - auc: 0.5881 - val_loss: 0.5122 - val_auc: 0.5658\n",
      "Epoch 9/100\n",
      "814/814 [==============================] - 3s 4ms/step - loss: 0.5097 - auc: 0.5864 - val_loss: 0.5153 - val_auc: 0.5536\n",
      "Epoch 10/100\n",
      "814/814 [==============================] - 3s 4ms/step - loss: 0.5097 - auc: 0.5868 - val_loss: 0.5122 - val_auc: 0.5631\n",
      "Epoch 11/100\n",
      "814/814 [==============================] - 4s 5ms/step - loss: 0.5097 - auc: 0.5859 - val_loss: 0.5128 - val_auc: 0.5616\n",
      "Epoch 12/100\n",
      "814/814 [==============================] - 4s 4ms/step - loss: 0.5096 - auc: 0.5872 - val_loss: 0.5146 - val_auc: 0.5620\n",
      "Train score: 0.5878284 / val score: 0.5760872 for split 15\n",
      "Epoch 1/100\n"
     ]
    },
    {
     "name": "stderr",
     "output_type": "stream",
     "text": [
      "2022-08-17 12:37:17.667618: I tensorflow/stream_executor/cuda/cuda_gpu_executor.cc:937] successful NUMA node read from SysFS had negative value (-1), but there must be at least one NUMA node, so returning NUMA node zero\n",
      "2022-08-17 12:37:17.668502: I tensorflow/core/grappler/devices.cc:66] Number of eligible GPUs (core count >= 8, compute capability >= 0.0): 1\n",
      "2022-08-17 12:37:17.668640: I tensorflow/core/grappler/clusters/single_machine.cc:357] Starting new session\n",
      "2022-08-17 12:37:17.669147: I tensorflow/stream_executor/cuda/cuda_gpu_executor.cc:937] successful NUMA node read from SysFS had negative value (-1), but there must be at least one NUMA node, so returning NUMA node zero\n",
      "2022-08-17 12:37:17.670148: I tensorflow/stream_executor/cuda/cuda_gpu_executor.cc:937] successful NUMA node read from SysFS had negative value (-1), but there must be at least one NUMA node, so returning NUMA node zero\n",
      "2022-08-17 12:37:17.671156: I tensorflow/stream_executor/cuda/cuda_gpu_executor.cc:937] successful NUMA node read from SysFS had negative value (-1), but there must be at least one NUMA node, so returning NUMA node zero\n",
      "2022-08-17 12:37:17.672346: I tensorflow/stream_executor/cuda/cuda_gpu_executor.cc:937] successful NUMA node read from SysFS had negative value (-1), but there must be at least one NUMA node, so returning NUMA node zero\n",
      "2022-08-17 12:37:17.673261: I tensorflow/stream_executor/cuda/cuda_gpu_executor.cc:937] successful NUMA node read from SysFS had negative value (-1), but there must be at least one NUMA node, so returning NUMA node zero\n",
      "2022-08-17 12:37:17.674044: I tensorflow/core/common_runtime/gpu/gpu_device.cc:1510] Created device /job:localhost/replica:0/task:0/device:GPU:0 with 15385 MB memory:  -> device: 0, name: Tesla P100-PCIE-16GB, pci bus id: 0000:00:04.0, compute capability: 6.0\n",
      "2022-08-17 12:37:17.675648: I tensorflow/core/grappler/optimizers/meta_optimizer.cc:1137] Optimization results for grappler item: graph_to_optimize\n",
      "  function_optimizer: function_optimizer did nothing. time = 0.007ms.\n",
      "  function_optimizer: function_optimizer did nothing. time = 0.001ms.\n",
      "\n",
      "Incomplete shape.\n",
      "Incomplete shape.\n"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "814/814 [==============================] - 5s 5ms/step - loss: 0.5282 - auc: 0.5572 - val_loss: 0.5108 - val_auc: 0.5817\n",
      "Epoch 2/100\n",
      "814/814 [==============================] - 4s 5ms/step - loss: 0.5098 - auc: 0.5868 - val_loss: 0.5115 - val_auc: 0.5800\n",
      "Epoch 3/100\n",
      "814/814 [==============================] - 4s 5ms/step - loss: 0.5096 - auc: 0.5861 - val_loss: 0.5120 - val_auc: 0.5790\n",
      "Epoch 4/100\n",
      "814/814 [==============================] - 3s 4ms/step - loss: 0.5098 - auc: 0.5870 - val_loss: 0.5102 - val_auc: 0.5813\n",
      "Epoch 5/100\n",
      "814/814 [==============================] - 3s 4ms/step - loss: 0.5101 - auc: 0.5839 - val_loss: 0.5104 - val_auc: 0.5835\n",
      "Epoch 6/100\n",
      "814/814 [==============================] - 4s 5ms/step - loss: 0.5098 - auc: 0.5854 - val_loss: 0.5108 - val_auc: 0.5881\n",
      "Epoch 7/100\n",
      "814/814 [==============================] - 3s 4ms/step - loss: 0.5094 - auc: 0.5874 - val_loss: 0.5167 - val_auc: 0.5443\n",
      "Epoch 8/100\n",
      "814/814 [==============================] - 3s 4ms/step - loss: 0.5097 - auc: 0.5857 - val_loss: 0.5119 - val_auc: 0.5851\n",
      "Epoch 9/100\n",
      "814/814 [==============================] - 4s 5ms/step - loss: 0.5096 - auc: 0.5879 - val_loss: 0.5122 - val_auc: 0.5720\n",
      "Epoch 10/100\n",
      "814/814 [==============================] - 3s 4ms/step - loss: 0.5096 - auc: 0.5864 - val_loss: 0.5127 - val_auc: 0.5754\n",
      "Epoch 11/100\n",
      "814/814 [==============================] - 3s 4ms/step - loss: 0.5098 - auc: 0.5855 - val_loss: 0.5115 - val_auc: 0.5803\n",
      "Train score: 0.5927099 / val score: 0.5863729 for split 16\n",
      "Epoch 1/100\n"
     ]
    },
    {
     "name": "stderr",
     "output_type": "stream",
     "text": [
      "2022-08-17 12:38:01.161120: I tensorflow/stream_executor/cuda/cuda_gpu_executor.cc:937] successful NUMA node read from SysFS had negative value (-1), but there must be at least one NUMA node, so returning NUMA node zero\n",
      "2022-08-17 12:38:01.162016: I tensorflow/core/grappler/devices.cc:66] Number of eligible GPUs (core count >= 8, compute capability >= 0.0): 1\n",
      "2022-08-17 12:38:01.162130: I tensorflow/core/grappler/clusters/single_machine.cc:357] Starting new session\n",
      "2022-08-17 12:38:01.162769: I tensorflow/stream_executor/cuda/cuda_gpu_executor.cc:937] successful NUMA node read from SysFS had negative value (-1), but there must be at least one NUMA node, so returning NUMA node zero\n",
      "2022-08-17 12:38:01.163803: I tensorflow/stream_executor/cuda/cuda_gpu_executor.cc:937] successful NUMA node read from SysFS had negative value (-1), but there must be at least one NUMA node, so returning NUMA node zero\n",
      "2022-08-17 12:38:01.164691: I tensorflow/stream_executor/cuda/cuda_gpu_executor.cc:937] successful NUMA node read from SysFS had negative value (-1), but there must be at least one NUMA node, so returning NUMA node zero\n",
      "2022-08-17 12:38:01.165625: I tensorflow/stream_executor/cuda/cuda_gpu_executor.cc:937] successful NUMA node read from SysFS had negative value (-1), but there must be at least one NUMA node, so returning NUMA node zero\n",
      "2022-08-17 12:38:01.166547: I tensorflow/stream_executor/cuda/cuda_gpu_executor.cc:937] successful NUMA node read from SysFS had negative value (-1), but there must be at least one NUMA node, so returning NUMA node zero\n",
      "2022-08-17 12:38:01.167381: I tensorflow/core/common_runtime/gpu/gpu_device.cc:1510] Created device /job:localhost/replica:0/task:0/device:GPU:0 with 15385 MB memory:  -> device: 0, name: Tesla P100-PCIE-16GB, pci bus id: 0000:00:04.0, compute capability: 6.0\n",
      "2022-08-17 12:38:01.168806: I tensorflow/core/grappler/optimizers/meta_optimizer.cc:1137] Optimization results for grappler item: graph_to_optimize\n",
      "  function_optimizer: function_optimizer did nothing. time = 0.006ms.\n",
      "  function_optimizer: function_optimizer did nothing. time = 0.001ms.\n",
      "\n",
      "Incomplete shape.\n",
      "Incomplete shape.\n"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "814/814 [==============================] - 4s 5ms/step - loss: 0.5256 - auc: 0.5596 - val_loss: 0.5122 - val_auc: 0.5648\n",
      "Epoch 2/100\n",
      "814/814 [==============================] - 3s 4ms/step - loss: 0.5101 - auc: 0.5858 - val_loss: 0.5125 - val_auc: 0.5682\n",
      "Epoch 3/100\n",
      "814/814 [==============================] - 4s 5ms/step - loss: 0.5098 - auc: 0.5855 - val_loss: 0.5091 - val_auc: 0.5820\n",
      "Epoch 4/100\n",
      "814/814 [==============================] - 3s 4ms/step - loss: 0.5101 - auc: 0.5851 - val_loss: 0.5104 - val_auc: 0.5693\n",
      "Epoch 5/100\n",
      "814/814 [==============================] - 3s 4ms/step - loss: 0.5100 - auc: 0.5864 - val_loss: 0.5155 - val_auc: 0.5459\n",
      "Epoch 6/100\n",
      "814/814 [==============================] - 4s 5ms/step - loss: 0.5101 - auc: 0.5846 - val_loss: 0.5088 - val_auc: 0.5784\n",
      "Epoch 7/100\n",
      "814/814 [==============================] - 4s 4ms/step - loss: 0.5100 - auc: 0.5853 - val_loss: 0.5109 - val_auc: 0.5705\n",
      "Epoch 8/100\n",
      "814/814 [==============================] - 3s 4ms/step - loss: 0.5094 - auc: 0.5889 - val_loss: 0.5120 - val_auc: 0.5683\n",
      "Train score: 0.5863615 / val score: 0.5831204 for split 17\n",
      "Epoch 1/100\n"
     ]
    },
    {
     "name": "stderr",
     "output_type": "stream",
     "text": [
      "2022-08-17 12:38:31.931345: I tensorflow/stream_executor/cuda/cuda_gpu_executor.cc:937] successful NUMA node read from SysFS had negative value (-1), but there must be at least one NUMA node, so returning NUMA node zero\n",
      "2022-08-17 12:38:31.932354: I tensorflow/core/grappler/devices.cc:66] Number of eligible GPUs (core count >= 8, compute capability >= 0.0): 1\n",
      "2022-08-17 12:38:31.932472: I tensorflow/core/grappler/clusters/single_machine.cc:357] Starting new session\n",
      "2022-08-17 12:38:31.933005: I tensorflow/stream_executor/cuda/cuda_gpu_executor.cc:937] successful NUMA node read from SysFS had negative value (-1), but there must be at least one NUMA node, so returning NUMA node zero\n",
      "2022-08-17 12:38:31.933972: I tensorflow/stream_executor/cuda/cuda_gpu_executor.cc:937] successful NUMA node read from SysFS had negative value (-1), but there must be at least one NUMA node, so returning NUMA node zero\n",
      "2022-08-17 12:38:31.934903: I tensorflow/stream_executor/cuda/cuda_gpu_executor.cc:937] successful NUMA node read from SysFS had negative value (-1), but there must be at least one NUMA node, so returning NUMA node zero\n",
      "2022-08-17 12:38:31.935996: I tensorflow/stream_executor/cuda/cuda_gpu_executor.cc:937] successful NUMA node read from SysFS had negative value (-1), but there must be at least one NUMA node, so returning NUMA node zero\n",
      "2022-08-17 12:38:31.936929: I tensorflow/stream_executor/cuda/cuda_gpu_executor.cc:937] successful NUMA node read from SysFS had negative value (-1), but there must be at least one NUMA node, so returning NUMA node zero\n",
      "2022-08-17 12:38:31.937653: I tensorflow/core/common_runtime/gpu/gpu_device.cc:1510] Created device /job:localhost/replica:0/task:0/device:GPU:0 with 15385 MB memory:  -> device: 0, name: Tesla P100-PCIE-16GB, pci bus id: 0000:00:04.0, compute capability: 6.0\n",
      "2022-08-17 12:38:31.939288: I tensorflow/core/grappler/optimizers/meta_optimizer.cc:1137] Optimization results for grappler item: graph_to_optimize\n",
      "  function_optimizer: function_optimizer did nothing. time = 0.007ms.\n",
      "  function_optimizer: function_optimizer did nothing. time = 0.001ms.\n",
      "\n",
      "Incomplete shape.\n",
      "Incomplete shape.\n"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "814/814 [==============================] - 5s 5ms/step - loss: 0.5321 - auc: 0.5593 - val_loss: 0.5068 - val_auc: 0.5967\n",
      "Epoch 2/100\n",
      "814/814 [==============================] - 3s 4ms/step - loss: 0.5097 - auc: 0.5868 - val_loss: 0.5080 - val_auc: 0.5912\n",
      "Epoch 3/100\n",
      "814/814 [==============================] - 3s 4ms/step - loss: 0.5099 - auc: 0.5849 - val_loss: 0.5075 - val_auc: 0.5879\n",
      "Epoch 4/100\n",
      "814/814 [==============================] - 4s 4ms/step - loss: 0.5099 - auc: 0.5862 - val_loss: 0.5082 - val_auc: 0.5884\n",
      "Epoch 5/100\n",
      "814/814 [==============================] - 4s 5ms/step - loss: 0.5098 - auc: 0.5862 - val_loss: 0.5077 - val_auc: 0.5880\n",
      "Epoch 6/100\n",
      "814/814 [==============================] - 3s 4ms/step - loss: 0.5099 - auc: 0.5846 - val_loss: 0.5072 - val_auc: 0.5911\n",
      "Train score: 0.5896489 / val score: 0.5959829 for split 18\n",
      "Epoch 1/100\n"
     ]
    },
    {
     "name": "stderr",
     "output_type": "stream",
     "text": [
      "2022-08-17 12:39:15.087887: I tensorflow/stream_executor/cuda/cuda_gpu_executor.cc:937] successful NUMA node read from SysFS had negative value (-1), but there must be at least one NUMA node, so returning NUMA node zero\n",
      "2022-08-17 12:39:15.088773: I tensorflow/core/grappler/devices.cc:66] Number of eligible GPUs (core count >= 8, compute capability >= 0.0): 1\n",
      "2022-08-17 12:39:15.088905: I tensorflow/core/grappler/clusters/single_machine.cc:357] Starting new session\n",
      "2022-08-17 12:39:15.089407: I tensorflow/stream_executor/cuda/cuda_gpu_executor.cc:937] successful NUMA node read from SysFS had negative value (-1), but there must be at least one NUMA node, so returning NUMA node zero\n",
      "2022-08-17 12:39:15.090375: I tensorflow/stream_executor/cuda/cuda_gpu_executor.cc:937] successful NUMA node read from SysFS had negative value (-1), but there must be at least one NUMA node, so returning NUMA node zero\n",
      "2022-08-17 12:39:15.091244: I tensorflow/stream_executor/cuda/cuda_gpu_executor.cc:937] successful NUMA node read from SysFS had negative value (-1), but there must be at least one NUMA node, so returning NUMA node zero\n",
      "2022-08-17 12:39:15.092301: I tensorflow/stream_executor/cuda/cuda_gpu_executor.cc:937] successful NUMA node read from SysFS had negative value (-1), but there must be at least one NUMA node, so returning NUMA node zero\n",
      "2022-08-17 12:39:15.093258: I tensorflow/stream_executor/cuda/cuda_gpu_executor.cc:937] successful NUMA node read from SysFS had negative value (-1), but there must be at least one NUMA node, so returning NUMA node zero\n",
      "2022-08-17 12:39:15.094012: I tensorflow/core/common_runtime/gpu/gpu_device.cc:1510] Created device /job:localhost/replica:0/task:0/device:GPU:0 with 15385 MB memory:  -> device: 0, name: Tesla P100-PCIE-16GB, pci bus id: 0000:00:04.0, compute capability: 6.0\n",
      "2022-08-17 12:39:15.095610: I tensorflow/core/grappler/optimizers/meta_optimizer.cc:1137] Optimization results for grappler item: graph_to_optimize\n",
      "  function_optimizer: function_optimizer did nothing. time = 0.006ms.\n",
      "  function_optimizer: function_optimizer did nothing. time = 0.002ms.\n",
      "\n",
      "Incomplete shape.\n",
      "Incomplete shape.\n"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "814/814 [==============================] - 5s 5ms/step - loss: 0.5304 - auc: 0.5606 - val_loss: 0.5158 - val_auc: 0.5599\n",
      "Epoch 2/100\n",
      "814/814 [==============================] - 4s 5ms/step - loss: 0.5095 - auc: 0.5895 - val_loss: 0.5170 - val_auc: 0.5521\n",
      "Epoch 3/100\n",
      "814/814 [==============================] - 3s 4ms/step - loss: 0.5099 - auc: 0.5859 - val_loss: 0.5132 - val_auc: 0.5697\n",
      "Epoch 4/100\n",
      "814/814 [==============================] - 4s 4ms/step - loss: 0.5099 - auc: 0.5853 - val_loss: 0.5119 - val_auc: 0.5786\n",
      "Epoch 5/100\n",
      "814/814 [==============================] - 3s 4ms/step - loss: 0.5096 - auc: 0.5877 - val_loss: 0.5153 - val_auc: 0.5512\n",
      "Epoch 6/100\n",
      "814/814 [==============================] - 3s 4ms/step - loss: 0.5094 - auc: 0.5878 - val_loss: 0.5155 - val_auc: 0.5686\n",
      "Epoch 7/100\n",
      "814/814 [==============================] - 4s 4ms/step - loss: 0.5096 - auc: 0.5880 - val_loss: 0.5100 - val_auc: 0.5894\n",
      "Epoch 8/100\n",
      "814/814 [==============================] - 3s 4ms/step - loss: 0.5095 - auc: 0.5872 - val_loss: 0.5123 - val_auc: 0.5743\n",
      "Epoch 9/100\n",
      "814/814 [==============================] - 4s 5ms/step - loss: 0.5100 - auc: 0.5850 - val_loss: 0.5152 - val_auc: 0.5640\n",
      "Epoch 10/100\n",
      "814/814 [==============================] - 4s 5ms/step - loss: 0.5096 - auc: 0.5869 - val_loss: 0.5134 - val_auc: 0.5682\n",
      "Epoch 11/100\n",
      "814/814 [==============================] - 3s 4ms/step - loss: 0.5097 - auc: 0.5873 - val_loss: 0.5151 - val_auc: 0.5609\n",
      "Epoch 12/100\n",
      "814/814 [==============================] - 3s 4ms/step - loss: 0.5091 - auc: 0.5888 - val_loss: 0.5145 - val_auc: 0.5665\n",
      "Train score: 0.5878115 / val score: 0.5893932 for split 19\n"
     ]
    },
    {
     "name": "stderr",
     "output_type": "stream",
     "text": [
      "2022-08-17 12:40:01.100536: I tensorflow/stream_executor/cuda/cuda_gpu_executor.cc:937] successful NUMA node read from SysFS had negative value (-1), but there must be at least one NUMA node, so returning NUMA node zero\n",
      "2022-08-17 12:40:01.101693: I tensorflow/core/grappler/devices.cc:66] Number of eligible GPUs (core count >= 8, compute capability >= 0.0): 1\n",
      "2022-08-17 12:40:01.101872: I tensorflow/core/grappler/clusters/single_machine.cc:357] Starting new session\n",
      "2022-08-17 12:40:01.105074: I tensorflow/stream_executor/cuda/cuda_gpu_executor.cc:937] successful NUMA node read from SysFS had negative value (-1), but there must be at least one NUMA node, so returning NUMA node zero\n",
      "2022-08-17 12:40:01.106823: I tensorflow/stream_executor/cuda/cuda_gpu_executor.cc:937] successful NUMA node read from SysFS had negative value (-1), but there must be at least one NUMA node, so returning NUMA node zero\n",
      "2022-08-17 12:40:01.108011: I tensorflow/stream_executor/cuda/cuda_gpu_executor.cc:937] successful NUMA node read from SysFS had negative value (-1), but there must be at least one NUMA node, so returning NUMA node zero\n",
      "2022-08-17 12:40:01.109300: I tensorflow/stream_executor/cuda/cuda_gpu_executor.cc:937] successful NUMA node read from SysFS had negative value (-1), but there must be at least one NUMA node, so returning NUMA node zero\n",
      "2022-08-17 12:40:01.110699: I tensorflow/stream_executor/cuda/cuda_gpu_executor.cc:937] successful NUMA node read from SysFS had negative value (-1), but there must be at least one NUMA node, so returning NUMA node zero\n",
      "2022-08-17 12:40:01.111673: I tensorflow/core/common_runtime/gpu/gpu_device.cc:1510] Created device /job:localhost/replica:0/task:0/device:GPU:0 with 15385 MB memory:  -> device: 0, name: Tesla P100-PCIE-16GB, pci bus id: 0000:00:04.0, compute capability: 6.0\n",
      "2022-08-17 12:40:01.118941: I tensorflow/core/grappler/optimizers/meta_optimizer.cc:1137] Optimization results for grappler item: graph_to_optimize\n",
      "  function_optimizer: function_optimizer did nothing. time = 0.065ms.\n",
      "  function_optimizer: function_optimizer did nothing. time = 0.009ms.\n",
      "\n",
      "Incomplete shape.\n",
      "Incomplete shape.\n"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "Epoch 1/100\n",
      "814/814 [==============================] - 5s 5ms/step - loss: 0.5286 - auc: 0.5665 - val_loss: 0.5160 - val_auc: 0.5446\n",
      "Epoch 2/100\n",
      "814/814 [==============================] - 3s 4ms/step - loss: 0.5095 - auc: 0.5888 - val_loss: 0.5148 - val_auc: 0.5485\n",
      "Epoch 3/100\n",
      "814/814 [==============================] - 4s 5ms/step - loss: 0.5096 - auc: 0.5884 - val_loss: 0.5181 - val_auc: 0.5308\n",
      "Epoch 4/100\n",
      "814/814 [==============================] - 3s 4ms/step - loss: 0.5096 - auc: 0.5882 - val_loss: 0.5149 - val_auc: 0.5465\n",
      "Epoch 5/100\n",
      "814/814 [==============================] - 4s 4ms/step - loss: 0.5096 - auc: 0.5886 - val_loss: 0.5112 - val_auc: 0.5675\n",
      "Epoch 6/100\n",
      "814/814 [==============================] - 4s 5ms/step - loss: 0.5097 - auc: 0.5871 - val_loss: 0.5174 - val_auc: 0.5404\n",
      "Epoch 7/100\n",
      "814/814 [==============================] - 3s 4ms/step - loss: 0.5095 - auc: 0.5875 - val_loss: 0.5200 - val_auc: 0.5271\n",
      "Epoch 8/100\n",
      "814/814 [==============================] - 3s 4ms/step - loss: 0.5098 - auc: 0.5866 - val_loss: 0.5123 - val_auc: 0.5614\n",
      "Epoch 9/100\n",
      "814/814 [==============================] - 4s 5ms/step - loss: 0.5095 - auc: 0.5887 - val_loss: 0.5160 - val_auc: 0.5458\n",
      "Epoch 10/100\n",
      "814/814 [==============================] - 4s 5ms/step - loss: 0.5099 - auc: 0.5869 - val_loss: 0.5107 - val_auc: 0.5740\n",
      "Epoch 11/100\n",
      "814/814 [==============================] - 3s 4ms/step - loss: 0.5097 - auc: 0.5869 - val_loss: 0.5170 - val_auc: 0.5458\n",
      "Epoch 12/100\n",
      "814/814 [==============================] - 4s 5ms/step - loss: 0.5096 - auc: 0.5875 - val_loss: 0.5143 - val_auc: 0.5574\n",
      "Epoch 13/100\n",
      "814/814 [==============================] - 3s 4ms/step - loss: 0.5097 - auc: 0.5869 - val_loss: 0.5123 - val_auc: 0.5633\n",
      "Epoch 14/100\n",
      "814/814 [==============================] - 4s 5ms/step - loss: 0.5096 - auc: 0.5874 - val_loss: 0.5155 - val_auc: 0.5479\n",
      "Epoch 15/100\n",
      "814/814 [==============================] - 4s 5ms/step - loss: 0.5097 - auc: 0.5874 - val_loss: 0.5142 - val_auc: 0.5481\n",
      "Train score: 0.5894883 / val score: 0.5742414 for split 20\n",
      "Epoch 1/100\n"
     ]
    },
    {
     "name": "stderr",
     "output_type": "stream",
     "text": [
      "2022-08-17 12:41:25.361504: I tensorflow/stream_executor/cuda/cuda_gpu_executor.cc:937] successful NUMA node read from SysFS had negative value (-1), but there must be at least one NUMA node, so returning NUMA node zero\n",
      "2022-08-17 12:41:25.362353: I tensorflow/core/grappler/devices.cc:66] Number of eligible GPUs (core count >= 8, compute capability >= 0.0): 1\n",
      "2022-08-17 12:41:25.362473: I tensorflow/core/grappler/clusters/single_machine.cc:357] Starting new session\n",
      "2022-08-17 12:41:25.363005: I tensorflow/stream_executor/cuda/cuda_gpu_executor.cc:937] successful NUMA node read from SysFS had negative value (-1), but there must be at least one NUMA node, so returning NUMA node zero\n",
      "2022-08-17 12:41:25.364001: I tensorflow/stream_executor/cuda/cuda_gpu_executor.cc:937] successful NUMA node read from SysFS had negative value (-1), but there must be at least one NUMA node, so returning NUMA node zero\n",
      "2022-08-17 12:41:25.365006: I tensorflow/stream_executor/cuda/cuda_gpu_executor.cc:937] successful NUMA node read from SysFS had negative value (-1), but there must be at least one NUMA node, so returning NUMA node zero\n",
      "2022-08-17 12:41:25.365979: I tensorflow/stream_executor/cuda/cuda_gpu_executor.cc:937] successful NUMA node read from SysFS had negative value (-1), but there must be at least one NUMA node, so returning NUMA node zero\n",
      "2022-08-17 12:41:25.366986: I tensorflow/stream_executor/cuda/cuda_gpu_executor.cc:937] successful NUMA node read from SysFS had negative value (-1), but there must be at least one NUMA node, so returning NUMA node zero\n",
      "2022-08-17 12:41:25.367753: I tensorflow/core/common_runtime/gpu/gpu_device.cc:1510] Created device /job:localhost/replica:0/task:0/device:GPU:0 with 15385 MB memory:  -> device: 0, name: Tesla P100-PCIE-16GB, pci bus id: 0000:00:04.0, compute capability: 6.0\n",
      "2022-08-17 12:41:25.369210: I tensorflow/core/grappler/optimizers/meta_optimizer.cc:1137] Optimization results for grappler item: graph_to_optimize\n",
      "  function_optimizer: function_optimizer did nothing. time = 0.02ms.\n",
      "  function_optimizer: function_optimizer did nothing. time = 0.001ms.\n",
      "\n",
      "Incomplete shape.\n",
      "Incomplete shape.\n"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "814/814 [==============================] - 5s 5ms/step - loss: 0.5255 - auc: 0.5612 - val_loss: 0.5094 - val_auc: 0.5841\n",
      "Epoch 2/100\n",
      "814/814 [==============================] - 3s 4ms/step - loss: 0.5101 - auc: 0.5853 - val_loss: 0.5075 - val_auc: 0.5948\n",
      "Epoch 3/100\n",
      "814/814 [==============================] - 3s 4ms/step - loss: 0.5099 - auc: 0.5858 - val_loss: 0.5054 - val_auc: 0.6091\n",
      "Epoch 4/100\n",
      "814/814 [==============================] - 4s 4ms/step - loss: 0.5101 - auc: 0.5835 - val_loss: 0.5079 - val_auc: 0.5955\n",
      "Epoch 5/100\n",
      "814/814 [==============================] - 3s 4ms/step - loss: 0.5097 - auc: 0.5866 - val_loss: 0.5085 - val_auc: 0.5886\n",
      "Epoch 6/100\n",
      "814/814 [==============================] - 3s 4ms/step - loss: 0.5100 - auc: 0.5853 - val_loss: 0.5066 - val_auc: 0.5937\n",
      "Epoch 7/100\n",
      "814/814 [==============================] - 3s 4ms/step - loss: 0.5097 - auc: 0.5855 - val_loss: 0.5094 - val_auc: 0.5947\n",
      "Epoch 8/100\n",
      "814/814 [==============================] - 4s 5ms/step - loss: 0.5100 - auc: 0.5855 - val_loss: 0.5051 - val_auc: 0.6060\n",
      "Train score: 0.5832360 / val score: 0.6091163 for split 21\n"
     ]
    },
    {
     "name": "stderr",
     "output_type": "stream",
     "text": [
      "2022-08-17 12:41:56.647500: I tensorflow/stream_executor/cuda/cuda_gpu_executor.cc:937] successful NUMA node read from SysFS had negative value (-1), but there must be at least one NUMA node, so returning NUMA node zero\n",
      "2022-08-17 12:41:56.648393: I tensorflow/core/grappler/devices.cc:66] Number of eligible GPUs (core count >= 8, compute capability >= 0.0): 1\n",
      "2022-08-17 12:41:56.648561: I tensorflow/core/grappler/clusters/single_machine.cc:357] Starting new session\n",
      "2022-08-17 12:41:56.649143: I tensorflow/stream_executor/cuda/cuda_gpu_executor.cc:937] successful NUMA node read from SysFS had negative value (-1), but there must be at least one NUMA node, so returning NUMA node zero\n",
      "2022-08-17 12:41:56.650114: I tensorflow/stream_executor/cuda/cuda_gpu_executor.cc:937] successful NUMA node read from SysFS had negative value (-1), but there must be at least one NUMA node, so returning NUMA node zero\n",
      "2022-08-17 12:41:56.650999: I tensorflow/stream_executor/cuda/cuda_gpu_executor.cc:937] successful NUMA node read from SysFS had negative value (-1), but there must be at least one NUMA node, so returning NUMA node zero\n",
      "2022-08-17 12:41:56.651972: I tensorflow/stream_executor/cuda/cuda_gpu_executor.cc:937] successful NUMA node read from SysFS had negative value (-1), but there must be at least one NUMA node, so returning NUMA node zero\n",
      "2022-08-17 12:41:56.652946: I tensorflow/stream_executor/cuda/cuda_gpu_executor.cc:937] successful NUMA node read from SysFS had negative value (-1), but there must be at least one NUMA node, so returning NUMA node zero\n",
      "2022-08-17 12:41:56.653765: I tensorflow/core/common_runtime/gpu/gpu_device.cc:1510] Created device /job:localhost/replica:0/task:0/device:GPU:0 with 15385 MB memory:  -> device: 0, name: Tesla P100-PCIE-16GB, pci bus id: 0000:00:04.0, compute capability: 6.0\n",
      "2022-08-17 12:41:56.655442: I tensorflow/core/grappler/optimizers/meta_optimizer.cc:1137] Optimization results for grappler item: graph_to_optimize\n",
      "  function_optimizer: function_optimizer did nothing. time = 0.007ms.\n",
      "  function_optimizer: function_optimizer did nothing. time = 0.002ms.\n",
      "\n",
      "Incomplete shape.\n",
      "Incomplete shape.\n"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "Epoch 1/100\n",
      "814/814 [==============================] - 5s 5ms/step - loss: 0.5243 - auc: 0.5631 - val_loss: 0.5129 - val_auc: 0.5647\n",
      "Epoch 2/100\n",
      "814/814 [==============================] - 4s 5ms/step - loss: 0.5098 - auc: 0.5865 - val_loss: 0.5160 - val_auc: 0.5506\n",
      "Epoch 3/100\n",
      "814/814 [==============================] - 3s 4ms/step - loss: 0.5097 - auc: 0.5873 - val_loss: 0.5149 - val_auc: 0.5613\n",
      "Epoch 4/100\n",
      "814/814 [==============================] - 3s 4ms/step - loss: 0.5098 - auc: 0.5873 - val_loss: 0.5145 - val_auc: 0.5600\n",
      "Epoch 5/100\n",
      "814/814 [==============================] - 4s 5ms/step - loss: 0.5097 - auc: 0.5866 - val_loss: 0.5137 - val_auc: 0.5601\n",
      "Epoch 6/100\n",
      "814/814 [==============================] - 3s 4ms/step - loss: 0.5097 - auc: 0.5858 - val_loss: 0.5142 - val_auc: 0.5690\n",
      "Epoch 7/100\n",
      "814/814 [==============================] - 3s 4ms/step - loss: 0.5094 - auc: 0.5886 - val_loss: 0.5138 - val_auc: 0.5672\n",
      "Epoch 8/100\n",
      "814/814 [==============================] - 4s 5ms/step - loss: 0.5095 - auc: 0.5875 - val_loss: 0.5141 - val_auc: 0.5549\n",
      "Epoch 9/100\n",
      "814/814 [==============================] - 3s 4ms/step - loss: 0.5098 - auc: 0.5862 - val_loss: 0.5112 - val_auc: 0.5787\n",
      "Epoch 10/100\n",
      "814/814 [==============================] - 5s 6ms/step - loss: 0.5094 - auc: 0.5868 - val_loss: 0.5151 - val_auc: 0.5546\n",
      "Epoch 11/100\n",
      "814/814 [==============================] - 4s 4ms/step - loss: 0.5095 - auc: 0.5880 - val_loss: 0.5146 - val_auc: 0.5647\n",
      "Epoch 12/100\n",
      "814/814 [==============================] - 3s 4ms/step - loss: 0.5096 - auc: 0.5880 - val_loss: 0.5148 - val_auc: 0.5549\n",
      "Epoch 13/100\n",
      "814/814 [==============================] - 3s 4ms/step - loss: 0.5096 - auc: 0.5888 - val_loss: 0.5114 - val_auc: 0.5764\n",
      "Epoch 14/100\n",
      "814/814 [==============================] - 4s 5ms/step - loss: 0.5096 - auc: 0.5869 - val_loss: 0.5160 - val_auc: 0.5585\n",
      "Train score: 0.5887322 / val score: 0.5798366 for split 22\n",
      "Epoch 1/100\n"
     ]
    },
    {
     "name": "stderr",
     "output_type": "stream",
     "text": [
      "2022-08-17 12:42:50.672035: I tensorflow/stream_executor/cuda/cuda_gpu_executor.cc:937] successful NUMA node read from SysFS had negative value (-1), but there must be at least one NUMA node, so returning NUMA node zero\n",
      "2022-08-17 12:42:50.672985: I tensorflow/core/grappler/devices.cc:66] Number of eligible GPUs (core count >= 8, compute capability >= 0.0): 1\n",
      "2022-08-17 12:42:50.673134: I tensorflow/core/grappler/clusters/single_machine.cc:357] Starting new session\n",
      "2022-08-17 12:42:50.673752: I tensorflow/stream_executor/cuda/cuda_gpu_executor.cc:937] successful NUMA node read from SysFS had negative value (-1), but there must be at least one NUMA node, so returning NUMA node zero\n",
      "2022-08-17 12:42:50.674837: I tensorflow/stream_executor/cuda/cuda_gpu_executor.cc:937] successful NUMA node read from SysFS had negative value (-1), but there must be at least one NUMA node, so returning NUMA node zero\n",
      "2022-08-17 12:42:50.675772: I tensorflow/stream_executor/cuda/cuda_gpu_executor.cc:937] successful NUMA node read from SysFS had negative value (-1), but there must be at least one NUMA node, so returning NUMA node zero\n",
      "2022-08-17 12:42:50.676797: I tensorflow/stream_executor/cuda/cuda_gpu_executor.cc:937] successful NUMA node read from SysFS had negative value (-1), but there must be at least one NUMA node, so returning NUMA node zero\n",
      "2022-08-17 12:42:50.677709: I tensorflow/stream_executor/cuda/cuda_gpu_executor.cc:937] successful NUMA node read from SysFS had negative value (-1), but there must be at least one NUMA node, so returning NUMA node zero\n",
      "2022-08-17 12:42:50.678449: I tensorflow/core/common_runtime/gpu/gpu_device.cc:1510] Created device /job:localhost/replica:0/task:0/device:GPU:0 with 15385 MB memory:  -> device: 0, name: Tesla P100-PCIE-16GB, pci bus id: 0000:00:04.0, compute capability: 6.0\n",
      "2022-08-17 12:42:50.680280: I tensorflow/core/grappler/optimizers/meta_optimizer.cc:1137] Optimization results for grappler item: graph_to_optimize\n",
      "  function_optimizer: function_optimizer did nothing. time = 0.007ms.\n",
      "  function_optimizer: function_optimizer did nothing. time = 0.002ms.\n",
      "\n",
      "Incomplete shape.\n",
      "Incomplete shape.\n"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "814/814 [==============================] - 4s 5ms/step - loss: 0.5281 - auc: 0.5618 - val_loss: 0.5115 - val_auc: 0.5875\n",
      "Epoch 2/100\n",
      "814/814 [==============================] - 4s 5ms/step - loss: 0.5098 - auc: 0.5857 - val_loss: 0.5103 - val_auc: 0.5885\n",
      "Epoch 3/100\n",
      "814/814 [==============================] - 3s 4ms/step - loss: 0.5093 - auc: 0.5877 - val_loss: 0.5103 - val_auc: 0.5916\n",
      "Epoch 4/100\n",
      "814/814 [==============================] - 4s 5ms/step - loss: 0.5098 - auc: 0.5862 - val_loss: 0.5097 - val_auc: 0.5990\n",
      "Epoch 5/100\n",
      "814/814 [==============================] - 4s 5ms/step - loss: 0.5097 - auc: 0.5846 - val_loss: 0.5106 - val_auc: 0.5914\n",
      "Epoch 6/100\n",
      "814/814 [==============================] - 3s 4ms/step - loss: 0.5100 - auc: 0.5854 - val_loss: 0.5105 - val_auc: 0.5827\n",
      "Epoch 7/100\n",
      "814/814 [==============================] - 3s 4ms/step - loss: 0.5097 - auc: 0.5866 - val_loss: 0.5093 - val_auc: 0.6030\n",
      "Epoch 8/100\n",
      "814/814 [==============================] - 4s 5ms/step - loss: 0.5101 - auc: 0.5841 - val_loss: 0.5103 - val_auc: 0.5912\n",
      "Epoch 9/100\n",
      "814/814 [==============================] - 4s 5ms/step - loss: 0.5097 - auc: 0.5863 - val_loss: 0.5070 - val_auc: 0.6135\n",
      "Epoch 10/100\n",
      "814/814 [==============================] - 3s 4ms/step - loss: 0.5096 - auc: 0.5868 - val_loss: 0.5089 - val_auc: 0.5989\n",
      "Epoch 11/100\n",
      "814/814 [==============================] - 4s 5ms/step - loss: 0.5097 - auc: 0.5856 - val_loss: 0.5115 - val_auc: 0.5948\n",
      "Epoch 12/100\n",
      "814/814 [==============================] - 3s 4ms/step - loss: 0.5097 - auc: 0.5865 - val_loss: 0.5081 - val_auc: 0.6065\n",
      "Epoch 13/100\n",
      "814/814 [==============================] - 4s 5ms/step - loss: 0.5097 - auc: 0.5868 - val_loss: 0.5100 - val_auc: 0.5980\n",
      "Epoch 14/100\n",
      "814/814 [==============================] - 4s 5ms/step - loss: 0.5098 - auc: 0.5857 - val_loss: 0.5091 - val_auc: 0.6009\n",
      "Train score: 0.5900195 / val score: 0.6132447 for split 23\n",
      "Epoch 1/100\n"
     ]
    },
    {
     "name": "stderr",
     "output_type": "stream",
     "text": [
      "2022-08-17 12:43:45.187763: I tensorflow/stream_executor/cuda/cuda_gpu_executor.cc:937] successful NUMA node read from SysFS had negative value (-1), but there must be at least one NUMA node, so returning NUMA node zero\n",
      "2022-08-17 12:43:45.188823: I tensorflow/core/grappler/devices.cc:66] Number of eligible GPUs (core count >= 8, compute capability >= 0.0): 1\n",
      "2022-08-17 12:43:45.188980: I tensorflow/core/grappler/clusters/single_machine.cc:357] Starting new session\n",
      "2022-08-17 12:43:45.189535: I tensorflow/stream_executor/cuda/cuda_gpu_executor.cc:937] successful NUMA node read from SysFS had negative value (-1), but there must be at least one NUMA node, so returning NUMA node zero\n",
      "2022-08-17 12:43:45.190484: I tensorflow/stream_executor/cuda/cuda_gpu_executor.cc:937] successful NUMA node read from SysFS had negative value (-1), but there must be at least one NUMA node, so returning NUMA node zero\n",
      "2022-08-17 12:43:45.191383: I tensorflow/stream_executor/cuda/cuda_gpu_executor.cc:937] successful NUMA node read from SysFS had negative value (-1), but there must be at least one NUMA node, so returning NUMA node zero\n",
      "2022-08-17 12:43:45.192335: I tensorflow/stream_executor/cuda/cuda_gpu_executor.cc:937] successful NUMA node read from SysFS had negative value (-1), but there must be at least one NUMA node, so returning NUMA node zero\n",
      "2022-08-17 12:43:45.193253: I tensorflow/stream_executor/cuda/cuda_gpu_executor.cc:937] successful NUMA node read from SysFS had negative value (-1), but there must be at least one NUMA node, so returning NUMA node zero\n",
      "2022-08-17 12:43:45.194022: I tensorflow/core/common_runtime/gpu/gpu_device.cc:1510] Created device /job:localhost/replica:0/task:0/device:GPU:0 with 15385 MB memory:  -> device: 0, name: Tesla P100-PCIE-16GB, pci bus id: 0000:00:04.0, compute capability: 6.0\n",
      "2022-08-17 12:43:45.197239: I tensorflow/core/grappler/optimizers/meta_optimizer.cc:1137] Optimization results for grappler item: graph_to_optimize\n",
      "  function_optimizer: function_optimizer did nothing. time = 0.007ms.\n",
      "  function_optimizer: function_optimizer did nothing. time = 0.001ms.\n",
      "\n",
      "Incomplete shape.\n",
      "Incomplete shape.\n"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "814/814 [==============================] - 4s 4ms/step - loss: 0.5282 - auc: 0.5592 - val_loss: 0.5062 - val_auc: 0.6040\n",
      "Epoch 2/100\n",
      "814/814 [==============================] - 4s 5ms/step - loss: 0.5097 - auc: 0.5876 - val_loss: 0.5089 - val_auc: 0.5908\n",
      "Epoch 3/100\n",
      "814/814 [==============================] - 3s 4ms/step - loss: 0.5099 - auc: 0.5859 - val_loss: 0.5049 - val_auc: 0.6004\n",
      "Epoch 4/100\n",
      "814/814 [==============================] - 3s 4ms/step - loss: 0.5100 - auc: 0.5842 - val_loss: 0.5046 - val_auc: 0.6001\n",
      "Epoch 5/100\n",
      "814/814 [==============================] - 4s 5ms/step - loss: 0.5097 - auc: 0.5859 - val_loss: 0.5027 - val_auc: 0.6148\n",
      "Epoch 6/100\n",
      "814/814 [==============================] - 4s 4ms/step - loss: 0.5098 - auc: 0.5855 - val_loss: 0.5075 - val_auc: 0.5907\n",
      "Epoch 7/100\n",
      "814/814 [==============================] - 4s 5ms/step - loss: 0.5094 - auc: 0.5875 - val_loss: 0.5029 - val_auc: 0.6144\n",
      "Epoch 8/100\n",
      "814/814 [==============================] - 5s 6ms/step - loss: 0.5100 - auc: 0.5857 - val_loss: 0.5026 - val_auc: 0.6186\n",
      "Epoch 9/100\n",
      "814/814 [==============================] - 3s 4ms/step - loss: 0.5099 - auc: 0.5859 - val_loss: 0.5064 - val_auc: 0.5975\n",
      "Epoch 10/100\n",
      "814/814 [==============================] - 3s 4ms/step - loss: 0.5102 - auc: 0.5835 - val_loss: 0.5037 - val_auc: 0.6146\n",
      "Epoch 11/100\n",
      "814/814 [==============================] - 4s 5ms/step - loss: 0.5098 - auc: 0.5877 - val_loss: 0.5026 - val_auc: 0.6189\n",
      "Epoch 12/100\n",
      "814/814 [==============================] - 3s 4ms/step - loss: 0.5099 - auc: 0.5846 - val_loss: 0.5036 - val_auc: 0.6073\n",
      "Epoch 13/100\n",
      "814/814 [==============================] - 3s 4ms/step - loss: 0.5099 - auc: 0.5866 - val_loss: 0.5030 - val_auc: 0.6115\n",
      "Epoch 14/100\n",
      "814/814 [==============================] - 4s 5ms/step - loss: 0.5097 - auc: 0.5867 - val_loss: 0.5048 - val_auc: 0.6013\n",
      "Epoch 15/100\n",
      "814/814 [==============================] - 3s 4ms/step - loss: 0.5096 - auc: 0.5870 - val_loss: 0.5073 - val_auc: 0.5880\n",
      "Epoch 16/100\n",
      "814/814 [==============================] - 4s 5ms/step - loss: 0.5099 - auc: 0.5859 - val_loss: 0.5033 - val_auc: 0.6116\n",
      "Train score: 0.5846869 / val score: 0.6170132 for split 24\n",
      "Epoch 1/100\n"
     ]
    },
    {
     "name": "stderr",
     "output_type": "stream",
     "text": [
      "2022-08-17 12:44:46.518703: I tensorflow/stream_executor/cuda/cuda_gpu_executor.cc:937] successful NUMA node read from SysFS had negative value (-1), but there must be at least one NUMA node, so returning NUMA node zero\n",
      "2022-08-17 12:44:46.519590: I tensorflow/core/grappler/devices.cc:66] Number of eligible GPUs (core count >= 8, compute capability >= 0.0): 1\n",
      "2022-08-17 12:44:46.519698: I tensorflow/core/grappler/clusters/single_machine.cc:357] Starting new session\n",
      "2022-08-17 12:44:46.520209: I tensorflow/stream_executor/cuda/cuda_gpu_executor.cc:937] successful NUMA node read from SysFS had negative value (-1), but there must be at least one NUMA node, so returning NUMA node zero\n",
      "2022-08-17 12:44:46.521284: I tensorflow/stream_executor/cuda/cuda_gpu_executor.cc:937] successful NUMA node read from SysFS had negative value (-1), but there must be at least one NUMA node, so returning NUMA node zero\n",
      "2022-08-17 12:44:46.522192: I tensorflow/stream_executor/cuda/cuda_gpu_executor.cc:937] successful NUMA node read from SysFS had negative value (-1), but there must be at least one NUMA node, so returning NUMA node zero\n",
      "2022-08-17 12:44:46.523191: I tensorflow/stream_executor/cuda/cuda_gpu_executor.cc:937] successful NUMA node read from SysFS had negative value (-1), but there must be at least one NUMA node, so returning NUMA node zero\n",
      "2022-08-17 12:44:46.524204: I tensorflow/stream_executor/cuda/cuda_gpu_executor.cc:937] successful NUMA node read from SysFS had negative value (-1), but there must be at least one NUMA node, so returning NUMA node zero\n",
      "2022-08-17 12:44:46.525009: I tensorflow/core/common_runtime/gpu/gpu_device.cc:1510] Created device /job:localhost/replica:0/task:0/device:GPU:0 with 15385 MB memory:  -> device: 0, name: Tesla P100-PCIE-16GB, pci bus id: 0000:00:04.0, compute capability: 6.0\n",
      "2022-08-17 12:44:46.526515: I tensorflow/core/grappler/optimizers/meta_optimizer.cc:1137] Optimization results for grappler item: graph_to_optimize\n",
      "  function_optimizer: function_optimizer did nothing. time = 0.007ms.\n",
      "  function_optimizer: function_optimizer did nothing. time = 0.002ms.\n",
      "\n",
      "Incomplete shape.\n",
      "Incomplete shape.\n"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "814/814 [==============================] - 5s 5ms/step - loss: 0.5242 - auc: 0.5650 - val_loss: 0.5143 - val_auc: 0.5806\n",
      "Epoch 2/100\n",
      "814/814 [==============================] - 3s 4ms/step - loss: 0.5096 - auc: 0.5879 - val_loss: 0.5144 - val_auc: 0.5653\n",
      "Epoch 3/100\n",
      "814/814 [==============================] - 3s 4ms/step - loss: 0.5094 - auc: 0.5868 - val_loss: 0.5119 - val_auc: 0.5804\n",
      "Epoch 4/100\n",
      "814/814 [==============================] - 4s 5ms/step - loss: 0.5099 - auc: 0.5849 - val_loss: 0.5115 - val_auc: 0.5851\n",
      "Epoch 5/100\n",
      "814/814 [==============================] - 4s 4ms/step - loss: 0.5097 - auc: 0.5858 - val_loss: 0.5104 - val_auc: 0.5892\n",
      "Epoch 6/100\n",
      "814/814 [==============================] - 4s 4ms/step - loss: 0.5099 - auc: 0.5849 - val_loss: 0.5101 - val_auc: 0.5926\n",
      "Epoch 7/100\n",
      "814/814 [==============================] - 4s 4ms/step - loss: 0.5096 - auc: 0.5882 - val_loss: 0.5109 - val_auc: 0.5872\n",
      "Epoch 8/100\n",
      "814/814 [==============================] - 4s 5ms/step - loss: 0.5096 - auc: 0.5862 - val_loss: 0.5165 - val_auc: 0.5703\n",
      "Epoch 9/100\n",
      "814/814 [==============================] - 5s 6ms/step - loss: 0.5098 - auc: 0.5865 - val_loss: 0.5135 - val_auc: 0.5742\n",
      "Epoch 10/100\n",
      "814/814 [==============================] - 4s 5ms/step - loss: 0.5094 - auc: 0.5873 - val_loss: 0.5122 - val_auc: 0.5850\n",
      "Epoch 11/100\n",
      "814/814 [==============================] - 3s 4ms/step - loss: 0.5091 - auc: 0.5903 - val_loss: 0.5117 - val_auc: 0.5930\n",
      "Epoch 12/100\n",
      "814/814 [==============================] - 4s 5ms/step - loss: 0.5099 - auc: 0.5864 - val_loss: 0.5139 - val_auc: 0.5820\n",
      "Epoch 13/100\n",
      "814/814 [==============================] - 4s 5ms/step - loss: 0.5098 - auc: 0.5866 - val_loss: 0.5091 - val_auc: 0.6013\n",
      "Epoch 14/100\n",
      "814/814 [==============================] - 3s 4ms/step - loss: 0.5098 - auc: 0.5876 - val_loss: 0.5125 - val_auc: 0.5785\n",
      "Epoch 15/100\n",
      "814/814 [==============================] - 4s 5ms/step - loss: 0.5096 - auc: 0.5872 - val_loss: 0.5090 - val_auc: 0.5998\n",
      "Epoch 16/100\n",
      "814/814 [==============================] - 3s 4ms/step - loss: 0.5097 - auc: 0.5870 - val_loss: 0.5105 - val_auc: 0.5899\n",
      "Epoch 17/100\n",
      "814/814 [==============================] - 4s 5ms/step - loss: 0.5094 - auc: 0.5873 - val_loss: 0.5107 - val_auc: 0.5863\n",
      "Epoch 18/100\n",
      "814/814 [==============================] - 4s 5ms/step - loss: 0.5098 - auc: 0.5861 - val_loss: 0.5094 - val_auc: 0.6009\n",
      "Train score: 0.5915396 / val score: 0.6010713 for split 25\n",
      "Epoch 1/100\n"
     ]
    },
    {
     "name": "stderr",
     "output_type": "stream",
     "text": [
      "2022-08-17 12:45:56.301934: I tensorflow/stream_executor/cuda/cuda_gpu_executor.cc:937] successful NUMA node read from SysFS had negative value (-1), but there must be at least one NUMA node, so returning NUMA node zero\n",
      "2022-08-17 12:45:56.302921: I tensorflow/core/grappler/devices.cc:66] Number of eligible GPUs (core count >= 8, compute capability >= 0.0): 1\n",
      "2022-08-17 12:45:56.303044: I tensorflow/core/grappler/clusters/single_machine.cc:357] Starting new session\n",
      "2022-08-17 12:45:56.303629: I tensorflow/stream_executor/cuda/cuda_gpu_executor.cc:937] successful NUMA node read from SysFS had negative value (-1), but there must be at least one NUMA node, so returning NUMA node zero\n",
      "2022-08-17 12:45:56.304546: I tensorflow/stream_executor/cuda/cuda_gpu_executor.cc:937] successful NUMA node read from SysFS had negative value (-1), but there must be at least one NUMA node, so returning NUMA node zero\n",
      "2022-08-17 12:45:56.305382: I tensorflow/stream_executor/cuda/cuda_gpu_executor.cc:937] successful NUMA node read from SysFS had negative value (-1), but there must be at least one NUMA node, so returning NUMA node zero\n",
      "2022-08-17 12:45:56.306309: I tensorflow/stream_executor/cuda/cuda_gpu_executor.cc:937] successful NUMA node read from SysFS had negative value (-1), but there must be at least one NUMA node, so returning NUMA node zero\n",
      "2022-08-17 12:45:56.307225: I tensorflow/stream_executor/cuda/cuda_gpu_executor.cc:937] successful NUMA node read from SysFS had negative value (-1), but there must be at least one NUMA node, so returning NUMA node zero\n",
      "2022-08-17 12:45:56.308024: I tensorflow/core/common_runtime/gpu/gpu_device.cc:1510] Created device /job:localhost/replica:0/task:0/device:GPU:0 with 15385 MB memory:  -> device: 0, name: Tesla P100-PCIE-16GB, pci bus id: 0000:00:04.0, compute capability: 6.0\n",
      "2022-08-17 12:45:56.309717: I tensorflow/core/grappler/optimizers/meta_optimizer.cc:1137] Optimization results for grappler item: graph_to_optimize\n",
      "  function_optimizer: function_optimizer did nothing. time = 0.007ms.\n",
      "  function_optimizer: function_optimizer did nothing. time = 0.001ms.\n",
      "\n",
      "Incomplete shape.\n",
      "Incomplete shape.\n"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "814/814 [==============================] - 4s 5ms/step - loss: 0.5275 - auc: 0.5611 - val_loss: 0.5104 - val_auc: 0.5691\n",
      "Epoch 2/100\n",
      "814/814 [==============================] - 3s 4ms/step - loss: 0.5100 - auc: 0.5857 - val_loss: 0.5072 - val_auc: 0.5853\n",
      "Epoch 3/100\n",
      "814/814 [==============================] - 4s 5ms/step - loss: 0.5098 - auc: 0.5874 - val_loss: 0.5075 - val_auc: 0.5875\n",
      "Epoch 4/100\n",
      "814/814 [==============================] - 4s 4ms/step - loss: 0.5097 - auc: 0.5858 - val_loss: 0.5076 - val_auc: 0.5916\n",
      "Epoch 5/100\n",
      "814/814 [==============================] - 3s 4ms/step - loss: 0.5100 - auc: 0.5856 - val_loss: 0.5080 - val_auc: 0.5845\n",
      "Epoch 6/100\n",
      "814/814 [==============================] - 4s 4ms/step - loss: 0.5096 - auc: 0.5876 - val_loss: 0.5075 - val_auc: 0.5891\n",
      "Epoch 7/100\n",
      "814/814 [==============================] - 4s 4ms/step - loss: 0.5096 - auc: 0.5871 - val_loss: 0.5074 - val_auc: 0.5873\n",
      "Epoch 8/100\n",
      "814/814 [==============================] - 4s 5ms/step - loss: 0.5099 - auc: 0.5856 - val_loss: 0.5090 - val_auc: 0.5752\n",
      "Epoch 9/100\n",
      "814/814 [==============================] - 3s 4ms/step - loss: 0.5097 - auc: 0.5872 - val_loss: 0.5092 - val_auc: 0.5769\n",
      "Train score: 0.5915627 / val score: 0.5906127 for split 26\n",
      "Epoch 1/100\n"
     ]
    },
    {
     "name": "stderr",
     "output_type": "stream",
     "text": [
      "2022-08-17 12:46:31.541069: I tensorflow/stream_executor/cuda/cuda_gpu_executor.cc:937] successful NUMA node read from SysFS had negative value (-1), but there must be at least one NUMA node, so returning NUMA node zero\n",
      "2022-08-17 12:46:31.541951: I tensorflow/core/grappler/devices.cc:66] Number of eligible GPUs (core count >= 8, compute capability >= 0.0): 1\n",
      "2022-08-17 12:46:31.542103: I tensorflow/core/grappler/clusters/single_machine.cc:357] Starting new session\n",
      "2022-08-17 12:46:31.542695: I tensorflow/stream_executor/cuda/cuda_gpu_executor.cc:937] successful NUMA node read from SysFS had negative value (-1), but there must be at least one NUMA node, so returning NUMA node zero\n",
      "2022-08-17 12:46:31.543569: I tensorflow/stream_executor/cuda/cuda_gpu_executor.cc:937] successful NUMA node read from SysFS had negative value (-1), but there must be at least one NUMA node, so returning NUMA node zero\n",
      "2022-08-17 12:46:31.544459: I tensorflow/stream_executor/cuda/cuda_gpu_executor.cc:937] successful NUMA node read from SysFS had negative value (-1), but there must be at least one NUMA node, so returning NUMA node zero\n",
      "2022-08-17 12:46:31.545592: I tensorflow/stream_executor/cuda/cuda_gpu_executor.cc:937] successful NUMA node read from SysFS had negative value (-1), but there must be at least one NUMA node, so returning NUMA node zero\n",
      "2022-08-17 12:46:31.546525: I tensorflow/stream_executor/cuda/cuda_gpu_executor.cc:937] successful NUMA node read from SysFS had negative value (-1), but there must be at least one NUMA node, so returning NUMA node zero\n",
      "2022-08-17 12:46:31.547267: I tensorflow/core/common_runtime/gpu/gpu_device.cc:1510] Created device /job:localhost/replica:0/task:0/device:GPU:0 with 15385 MB memory:  -> device: 0, name: Tesla P100-PCIE-16GB, pci bus id: 0000:00:04.0, compute capability: 6.0\n",
      "2022-08-17 12:46:31.549190: I tensorflow/core/grappler/optimizers/meta_optimizer.cc:1137] Optimization results for grappler item: graph_to_optimize\n",
      "  function_optimizer: function_optimizer did nothing. time = 0.007ms.\n",
      "  function_optimizer: function_optimizer did nothing. time = 0.001ms.\n",
      "\n",
      "Incomplete shape.\n",
      "Incomplete shape.\n"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "814/814 [==============================] - 4s 4ms/step - loss: 0.5290 - auc: 0.5588 - val_loss: 0.5080 - val_auc: 0.6004\n",
      "Epoch 2/100\n",
      "814/814 [==============================] - 4s 4ms/step - loss: 0.5099 - auc: 0.5854 - val_loss: 0.5156 - val_auc: 0.5708\n",
      "Epoch 3/100\n",
      "814/814 [==============================] - 4s 5ms/step - loss: 0.5097 - auc: 0.5867 - val_loss: 0.5076 - val_auc: 0.6028\n",
      "Epoch 4/100\n",
      "814/814 [==============================] - 3s 4ms/step - loss: 0.5097 - auc: 0.5868 - val_loss: 0.5161 - val_auc: 0.5556\n",
      "Epoch 5/100\n",
      "814/814 [==============================] - 4s 4ms/step - loss: 0.5097 - auc: 0.5860 - val_loss: 0.5079 - val_auc: 0.6022\n",
      "Epoch 6/100\n",
      "814/814 [==============================] - 3s 4ms/step - loss: 0.5095 - auc: 0.5883 - val_loss: 0.5075 - val_auc: 0.6025\n",
      "Epoch 7/100\n",
      "814/814 [==============================] - 4s 5ms/step - loss: 0.5099 - auc: 0.5847 - val_loss: 0.5095 - val_auc: 0.5971\n",
      "Epoch 8/100\n",
      "814/814 [==============================] - 4s 5ms/step - loss: 0.5099 - auc: 0.5851 - val_loss: 0.5102 - val_auc: 0.5950\n",
      "Train score: 0.5855685 / val score: 0.6037388 for split 27\n"
     ]
    },
    {
     "name": "stderr",
     "output_type": "stream",
     "text": [
      "2022-08-17 12:47:14.827000: I tensorflow/stream_executor/cuda/cuda_gpu_executor.cc:937] successful NUMA node read from SysFS had negative value (-1), but there must be at least one NUMA node, so returning NUMA node zero\n",
      "2022-08-17 12:47:14.827833: I tensorflow/core/grappler/devices.cc:66] Number of eligible GPUs (core count >= 8, compute capability >= 0.0): 1\n",
      "2022-08-17 12:47:14.827990: I tensorflow/core/grappler/clusters/single_machine.cc:357] Starting new session\n",
      "2022-08-17 12:47:14.828568: I tensorflow/stream_executor/cuda/cuda_gpu_executor.cc:937] successful NUMA node read from SysFS had negative value (-1), but there must be at least one NUMA node, so returning NUMA node zero\n",
      "2022-08-17 12:47:14.829519: I tensorflow/stream_executor/cuda/cuda_gpu_executor.cc:937] successful NUMA node read from SysFS had negative value (-1), but there must be at least one NUMA node, so returning NUMA node zero\n",
      "2022-08-17 12:47:14.830431: I tensorflow/stream_executor/cuda/cuda_gpu_executor.cc:937] successful NUMA node read from SysFS had negative value (-1), but there must be at least one NUMA node, so returning NUMA node zero\n",
      "2022-08-17 12:47:14.831365: I tensorflow/stream_executor/cuda/cuda_gpu_executor.cc:937] successful NUMA node read from SysFS had negative value (-1), but there must be at least one NUMA node, so returning NUMA node zero\n",
      "2022-08-17 12:47:14.832332: I tensorflow/stream_executor/cuda/cuda_gpu_executor.cc:937] successful NUMA node read from SysFS had negative value (-1), but there must be at least one NUMA node, so returning NUMA node zero\n",
      "2022-08-17 12:47:14.833083: I tensorflow/core/common_runtime/gpu/gpu_device.cc:1510] Created device /job:localhost/replica:0/task:0/device:GPU:0 with 15385 MB memory:  -> device: 0, name: Tesla P100-PCIE-16GB, pci bus id: 0000:00:04.0, compute capability: 6.0\n",
      "2022-08-17 12:47:14.835670: I tensorflow/core/grappler/optimizers/meta_optimizer.cc:1137] Optimization results for grappler item: graph_to_optimize\n",
      "  function_optimizer: function_optimizer did nothing. time = 0.007ms.\n",
      "  function_optimizer: function_optimizer did nothing. time = 0.001ms.\n",
      "\n",
      "Incomplete shape.\n",
      "Incomplete shape.\n"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "Epoch 1/100\n",
      "814/814 [==============================] - 4s 4ms/step - loss: 0.5253 - auc: 0.5675 - val_loss: 0.5212 - val_auc: 0.5285\n",
      "Epoch 2/100\n",
      "814/814 [==============================] - 4s 5ms/step - loss: 0.5095 - auc: 0.5886 - val_loss: 0.5255 - val_auc: 0.5206\n",
      "Epoch 3/100\n",
      "814/814 [==============================] - 3s 4ms/step - loss: 0.5094 - auc: 0.5874 - val_loss: 0.5191 - val_auc: 0.5316\n",
      "Epoch 4/100\n",
      "814/814 [==============================] - 4s 5ms/step - loss: 0.5095 - auc: 0.5884 - val_loss: 0.5208 - val_auc: 0.5315\n",
      "Epoch 5/100\n",
      "814/814 [==============================] - 4s 5ms/step - loss: 0.5095 - auc: 0.5880 - val_loss: 0.5224 - val_auc: 0.5350\n",
      "Epoch 6/100\n",
      "814/814 [==============================] - 3s 4ms/step - loss: 0.5095 - auc: 0.5877 - val_loss: 0.5210 - val_auc: 0.5221\n",
      "Epoch 7/100\n",
      "814/814 [==============================] - 3s 4ms/step - loss: 0.5094 - auc: 0.5880 - val_loss: 0.5206 - val_auc: 0.5388\n",
      "Epoch 8/100\n",
      "814/814 [==============================] - 4s 4ms/step - loss: 0.5094 - auc: 0.5875 - val_loss: 0.5179 - val_auc: 0.5459\n",
      "Epoch 9/100\n",
      "814/814 [==============================] - 4s 5ms/step - loss: 0.5094 - auc: 0.5883 - val_loss: 0.5214 - val_auc: 0.5376\n",
      "Epoch 10/100\n",
      "814/814 [==============================] - 4s 4ms/step - loss: 0.5097 - auc: 0.5878 - val_loss: 0.5207 - val_auc: 0.5384\n",
      "Epoch 11/100\n",
      "814/814 [==============================] - 4s 5ms/step - loss: 0.5093 - auc: 0.5880 - val_loss: 0.5212 - val_auc: 0.5268\n",
      "Epoch 12/100\n",
      "814/814 [==============================] - 3s 4ms/step - loss: 0.5097 - auc: 0.5862 - val_loss: 0.5220 - val_auc: 0.5288\n",
      "Epoch 13/100\n",
      "814/814 [==============================] - 4s 5ms/step - loss: 0.5094 - auc: 0.5869 - val_loss: 0.5207 - val_auc: 0.5309\n",
      "Train score: 0.5902939 / val score: 0.5467672 for split 28\n"
     ]
    },
    {
     "name": "stderr",
     "output_type": "stream",
     "text": [
      "2022-08-17 12:48:04.408831: I tensorflow/stream_executor/cuda/cuda_gpu_executor.cc:937] successful NUMA node read from SysFS had negative value (-1), but there must be at least one NUMA node, so returning NUMA node zero\n",
      "2022-08-17 12:48:04.409940: I tensorflow/core/grappler/devices.cc:66] Number of eligible GPUs (core count >= 8, compute capability >= 0.0): 1\n",
      "2022-08-17 12:48:04.410076: I tensorflow/core/grappler/clusters/single_machine.cc:357] Starting new session\n",
      "2022-08-17 12:48:04.410928: I tensorflow/stream_executor/cuda/cuda_gpu_executor.cc:937] successful NUMA node read from SysFS had negative value (-1), but there must be at least one NUMA node, so returning NUMA node zero\n",
      "2022-08-17 12:48:04.412194: I tensorflow/stream_executor/cuda/cuda_gpu_executor.cc:937] successful NUMA node read from SysFS had negative value (-1), but there must be at least one NUMA node, so returning NUMA node zero\n",
      "2022-08-17 12:48:04.413468: I tensorflow/stream_executor/cuda/cuda_gpu_executor.cc:937] successful NUMA node read from SysFS had negative value (-1), but there must be at least one NUMA node, so returning NUMA node zero\n",
      "2022-08-17 12:48:04.414743: I tensorflow/stream_executor/cuda/cuda_gpu_executor.cc:937] successful NUMA node read from SysFS had negative value (-1), but there must be at least one NUMA node, so returning NUMA node zero\n",
      "2022-08-17 12:48:04.415866: I tensorflow/stream_executor/cuda/cuda_gpu_executor.cc:937] successful NUMA node read from SysFS had negative value (-1), but there must be at least one NUMA node, so returning NUMA node zero\n",
      "2022-08-17 12:48:04.416836: I tensorflow/core/common_runtime/gpu/gpu_device.cc:1510] Created device /job:localhost/replica:0/task:0/device:GPU:0 with 15385 MB memory:  -> device: 0, name: Tesla P100-PCIE-16GB, pci bus id: 0000:00:04.0, compute capability: 6.0\n",
      "2022-08-17 12:48:04.419042: I tensorflow/core/grappler/optimizers/meta_optimizer.cc:1137] Optimization results for grappler item: graph_to_optimize\n",
      "  function_optimizer: function_optimizer did nothing. time = 0.008ms.\n",
      "  function_optimizer: function_optimizer did nothing. time = 0.002ms.\n",
      "\n",
      "Incomplete shape.\n",
      "Incomplete shape.\n"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "Epoch 1/100\n",
      "814/814 [==============================] - 5s 5ms/step - loss: 0.5253 - auc: 0.5617 - val_loss: 0.5108 - val_auc: 0.5621\n",
      "Epoch 2/100\n",
      "814/814 [==============================] - 3s 4ms/step - loss: 0.5097 - auc: 0.5873 - val_loss: 0.5114 - val_auc: 0.5657\n",
      "Epoch 3/100\n",
      "814/814 [==============================] - 3s 4ms/step - loss: 0.5096 - auc: 0.5875 - val_loss: 0.5085 - val_auc: 0.5802\n",
      "Epoch 4/100\n",
      "814/814 [==============================] - 4s 4ms/step - loss: 0.5099 - auc: 0.5860 - val_loss: 0.5115 - val_auc: 0.5571\n",
      "Epoch 5/100\n",
      "814/814 [==============================] - 4s 5ms/step - loss: 0.5100 - auc: 0.5841 - val_loss: 0.5100 - val_auc: 0.5775\n",
      "Epoch 6/100\n",
      "814/814 [==============================] - 3s 4ms/step - loss: 0.5096 - auc: 0.5864 - val_loss: 0.5131 - val_auc: 0.5552\n",
      "Epoch 7/100\n",
      "814/814 [==============================] - 4s 4ms/step - loss: 0.5093 - auc: 0.5899 - val_loss: 0.5132 - val_auc: 0.5549\n",
      "Epoch 8/100\n",
      "814/814 [==============================] - 3s 4ms/step - loss: 0.5096 - auc: 0.5863 - val_loss: 0.5118 - val_auc: 0.5622\n",
      "Train score: 0.5895547 / val score: 0.5809798 for split 29\n",
      "Epoch 1/100\n"
     ]
    },
    {
     "name": "stderr",
     "output_type": "stream",
     "text": [
      "2022-08-17 12:48:35.457068: I tensorflow/stream_executor/cuda/cuda_gpu_executor.cc:937] successful NUMA node read from SysFS had negative value (-1), but there must be at least one NUMA node, so returning NUMA node zero\n",
      "2022-08-17 12:48:35.457869: I tensorflow/core/grappler/devices.cc:66] Number of eligible GPUs (core count >= 8, compute capability >= 0.0): 1\n",
      "2022-08-17 12:48:35.457982: I tensorflow/core/grappler/clusters/single_machine.cc:357] Starting new session\n",
      "2022-08-17 12:48:35.458489: I tensorflow/stream_executor/cuda/cuda_gpu_executor.cc:937] successful NUMA node read from SysFS had negative value (-1), but there must be at least one NUMA node, so returning NUMA node zero\n",
      "2022-08-17 12:48:35.459386: I tensorflow/stream_executor/cuda/cuda_gpu_executor.cc:937] successful NUMA node read from SysFS had negative value (-1), but there must be at least one NUMA node, so returning NUMA node zero\n",
      "2022-08-17 12:48:35.460227: I tensorflow/stream_executor/cuda/cuda_gpu_executor.cc:937] successful NUMA node read from SysFS had negative value (-1), but there must be at least one NUMA node, so returning NUMA node zero\n",
      "2022-08-17 12:48:35.461146: I tensorflow/stream_executor/cuda/cuda_gpu_executor.cc:937] successful NUMA node read from SysFS had negative value (-1), but there must be at least one NUMA node, so returning NUMA node zero\n",
      "2022-08-17 12:48:35.462008: I tensorflow/stream_executor/cuda/cuda_gpu_executor.cc:937] successful NUMA node read from SysFS had negative value (-1), but there must be at least one NUMA node, so returning NUMA node zero\n",
      "2022-08-17 12:48:35.462772: I tensorflow/core/common_runtime/gpu/gpu_device.cc:1510] Created device /job:localhost/replica:0/task:0/device:GPU:0 with 15385 MB memory:  -> device: 0, name: Tesla P100-PCIE-16GB, pci bus id: 0000:00:04.0, compute capability: 6.0\n",
      "2022-08-17 12:48:35.464132: I tensorflow/core/grappler/optimizers/meta_optimizer.cc:1137] Optimization results for grappler item: graph_to_optimize\n",
      "  function_optimizer: function_optimizer did nothing. time = 0.006ms.\n",
      "  function_optimizer: function_optimizer did nothing. time = 0.001ms.\n",
      "\n",
      "Incomplete shape.\n",
      "Incomplete shape.\n"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "814/814 [==============================] - 6s 6ms/step - loss: 0.5246 - auc: 0.5651 - val_loss: 0.5005 - val_auc: 0.6383\n",
      "Epoch 2/100\n",
      "814/814 [==============================] - 3s 4ms/step - loss: 0.5098 - auc: 0.5855 - val_loss: 0.4996 - val_auc: 0.6475\n",
      "Epoch 3/100\n",
      "814/814 [==============================] - 3s 4ms/step - loss: 0.5099 - auc: 0.5851 - val_loss: 0.5046 - val_auc: 0.6252\n",
      "Epoch 4/100\n",
      "814/814 [==============================] - 4s 4ms/step - loss: 0.5097 - auc: 0.5860 - val_loss: 0.5030 - val_auc: 0.6301\n",
      "Epoch 5/100\n",
      "814/814 [==============================] - 4s 5ms/step - loss: 0.5101 - auc: 0.5844 - val_loss: 0.5006 - val_auc: 0.6450\n",
      "Epoch 6/100\n",
      "814/814 [==============================] - 3s 4ms/step - loss: 0.5097 - auc: 0.5871 - val_loss: 0.5013 - val_auc: 0.6395\n",
      "Epoch 7/100\n",
      "814/814 [==============================] - 4s 5ms/step - loss: 0.5097 - auc: 0.5864 - val_loss: 0.5043 - val_auc: 0.6186\n",
      "Train score: 0.5872377 / val score: 0.6473938 for split 30\n",
      "Epoch 1/100\n"
     ]
    },
    {
     "name": "stderr",
     "output_type": "stream",
     "text": [
      "2022-08-17 12:49:18.907388: I tensorflow/stream_executor/cuda/cuda_gpu_executor.cc:937] successful NUMA node read from SysFS had negative value (-1), but there must be at least one NUMA node, so returning NUMA node zero\n",
      "2022-08-17 12:49:18.908330: I tensorflow/core/grappler/devices.cc:66] Number of eligible GPUs (core count >= 8, compute capability >= 0.0): 1\n",
      "2022-08-17 12:49:18.908468: I tensorflow/core/grappler/clusters/single_machine.cc:357] Starting new session\n",
      "2022-08-17 12:49:18.909052: I tensorflow/stream_executor/cuda/cuda_gpu_executor.cc:937] successful NUMA node read from SysFS had negative value (-1), but there must be at least one NUMA node, so returning NUMA node zero\n",
      "2022-08-17 12:49:18.909969: I tensorflow/stream_executor/cuda/cuda_gpu_executor.cc:937] successful NUMA node read from SysFS had negative value (-1), but there must be at least one NUMA node, so returning NUMA node zero\n",
      "2022-08-17 12:49:18.910950: I tensorflow/stream_executor/cuda/cuda_gpu_executor.cc:937] successful NUMA node read from SysFS had negative value (-1), but there must be at least one NUMA node, so returning NUMA node zero\n",
      "2022-08-17 12:49:18.911973: I tensorflow/stream_executor/cuda/cuda_gpu_executor.cc:937] successful NUMA node read from SysFS had negative value (-1), but there must be at least one NUMA node, so returning NUMA node zero\n",
      "2022-08-17 12:49:18.912843: I tensorflow/stream_executor/cuda/cuda_gpu_executor.cc:937] successful NUMA node read from SysFS had negative value (-1), but there must be at least one NUMA node, so returning NUMA node zero\n",
      "2022-08-17 12:49:18.913627: I tensorflow/core/common_runtime/gpu/gpu_device.cc:1510] Created device /job:localhost/replica:0/task:0/device:GPU:0 with 15385 MB memory:  -> device: 0, name: Tesla P100-PCIE-16GB, pci bus id: 0000:00:04.0, compute capability: 6.0\n",
      "2022-08-17 12:49:18.916088: I tensorflow/core/grappler/optimizers/meta_optimizer.cc:1137] Optimization results for grappler item: graph_to_optimize\n",
      "  function_optimizer: function_optimizer did nothing. time = 0.007ms.\n",
      "  function_optimizer: function_optimizer did nothing. time = 0.001ms.\n",
      "\n",
      "Incomplete shape.\n",
      "Incomplete shape.\n"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "814/814 [==============================] - 6s 6ms/step - loss: 0.5268 - auc: 0.5657 - val_loss: 0.5150 - val_auc: 0.5727\n",
      "Epoch 2/100\n",
      "814/814 [==============================] - 3s 4ms/step - loss: 0.5097 - auc: 0.5863 - val_loss: 0.5158 - val_auc: 0.5622\n",
      "Epoch 3/100\n",
      "814/814 [==============================] - 3s 4ms/step - loss: 0.5098 - auc: 0.5861 - val_loss: 0.5154 - val_auc: 0.5630\n",
      "Epoch 4/100\n",
      "814/814 [==============================] - 4s 5ms/step - loss: 0.5095 - auc: 0.5874 - val_loss: 0.5176 - val_auc: 0.5589\n",
      "Epoch 5/100\n",
      "814/814 [==============================] - 3s 4ms/step - loss: 0.5096 - auc: 0.5874 - val_loss: 0.5153 - val_auc: 0.5715\n",
      "Epoch 6/100\n",
      "814/814 [==============================] - 3s 4ms/step - loss: 0.5096 - auc: 0.5868 - val_loss: 0.5152 - val_auc: 0.5681\n",
      "Train score: 0.5918623 / val score: 0.5729559 for split 31\n",
      "Epoch 1/100\n"
     ]
    },
    {
     "name": "stderr",
     "output_type": "stream",
     "text": [
      "2022-08-17 12:50:01.851002: I tensorflow/stream_executor/cuda/cuda_gpu_executor.cc:937] successful NUMA node read from SysFS had negative value (-1), but there must be at least one NUMA node, so returning NUMA node zero\n",
      "2022-08-17 12:50:01.851881: I tensorflow/core/grappler/devices.cc:66] Number of eligible GPUs (core count >= 8, compute capability >= 0.0): 1\n",
      "2022-08-17 12:50:01.852022: I tensorflow/core/grappler/clusters/single_machine.cc:357] Starting new session\n",
      "2022-08-17 12:50:01.852663: I tensorflow/stream_executor/cuda/cuda_gpu_executor.cc:937] successful NUMA node read from SysFS had negative value (-1), but there must be at least one NUMA node, so returning NUMA node zero\n",
      "2022-08-17 12:50:01.853586: I tensorflow/stream_executor/cuda/cuda_gpu_executor.cc:937] successful NUMA node read from SysFS had negative value (-1), but there must be at least one NUMA node, so returning NUMA node zero\n",
      "2022-08-17 12:50:01.854473: I tensorflow/stream_executor/cuda/cuda_gpu_executor.cc:937] successful NUMA node read from SysFS had negative value (-1), but there must be at least one NUMA node, so returning NUMA node zero\n",
      "2022-08-17 12:50:01.855436: I tensorflow/stream_executor/cuda/cuda_gpu_executor.cc:937] successful NUMA node read from SysFS had negative value (-1), but there must be at least one NUMA node, so returning NUMA node zero\n",
      "2022-08-17 12:50:01.856353: I tensorflow/stream_executor/cuda/cuda_gpu_executor.cc:937] successful NUMA node read from SysFS had negative value (-1), but there must be at least one NUMA node, so returning NUMA node zero\n",
      "2022-08-17 12:50:01.857153: I tensorflow/core/common_runtime/gpu/gpu_device.cc:1510] Created device /job:localhost/replica:0/task:0/device:GPU:0 with 15385 MB memory:  -> device: 0, name: Tesla P100-PCIE-16GB, pci bus id: 0000:00:04.0, compute capability: 6.0\n",
      "2022-08-17 12:50:01.858587: I tensorflow/core/grappler/optimizers/meta_optimizer.cc:1137] Optimization results for grappler item: graph_to_optimize\n",
      "  function_optimizer: function_optimizer did nothing. time = 0.007ms.\n",
      "  function_optimizer: function_optimizer did nothing. time = 0.001ms.\n",
      "\n",
      "Incomplete shape.\n",
      "Incomplete shape.\n"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "814/814 [==============================] - 7s 7ms/step - loss: 0.5278 - auc: 0.5644 - val_loss: 0.5113 - val_auc: 0.5718\n",
      "Epoch 2/100\n",
      "814/814 [==============================] - 3s 4ms/step - loss: 0.5096 - auc: 0.5866 - val_loss: 0.5074 - val_auc: 0.5879\n",
      "Epoch 3/100\n",
      "814/814 [==============================] - 4s 4ms/step - loss: 0.5099 - auc: 0.5855 - val_loss: 0.5078 - val_auc: 0.5864\n",
      "Epoch 4/100\n",
      "814/814 [==============================] - 4s 5ms/step - loss: 0.5099 - auc: 0.5858 - val_loss: 0.5080 - val_auc: 0.5848\n",
      "Epoch 5/100\n",
      "814/814 [==============================] - 3s 4ms/step - loss: 0.5098 - auc: 0.5859 - val_loss: 0.5080 - val_auc: 0.5839\n",
      "Epoch 6/100\n",
      "814/814 [==============================] - 3s 4ms/step - loss: 0.5098 - auc: 0.5873 - val_loss: 0.5098 - val_auc: 0.5819\n",
      "Epoch 7/100\n",
      "814/814 [==============================] - 4s 5ms/step - loss: 0.5096 - auc: 0.5876 - val_loss: 0.5093 - val_auc: 0.5798\n",
      "Train score: 0.5875696 / val score: 0.5880722 for split 32\n",
      "Epoch 1/100\n"
     ]
    },
    {
     "name": "stderr",
     "output_type": "stream",
     "text": [
      "2022-08-17 12:50:45.364808: I tensorflow/stream_executor/cuda/cuda_gpu_executor.cc:937] successful NUMA node read from SysFS had negative value (-1), but there must be at least one NUMA node, so returning NUMA node zero\n",
      "2022-08-17 12:50:45.365698: I tensorflow/core/grappler/devices.cc:66] Number of eligible GPUs (core count >= 8, compute capability >= 0.0): 1\n",
      "2022-08-17 12:50:45.365835: I tensorflow/core/grappler/clusters/single_machine.cc:357] Starting new session\n",
      "2022-08-17 12:50:45.366409: I tensorflow/stream_executor/cuda/cuda_gpu_executor.cc:937] successful NUMA node read from SysFS had negative value (-1), but there must be at least one NUMA node, so returning NUMA node zero\n",
      "2022-08-17 12:50:45.367351: I tensorflow/stream_executor/cuda/cuda_gpu_executor.cc:937] successful NUMA node read from SysFS had negative value (-1), but there must be at least one NUMA node, so returning NUMA node zero\n",
      "2022-08-17 12:50:45.368323: I tensorflow/stream_executor/cuda/cuda_gpu_executor.cc:937] successful NUMA node read from SysFS had negative value (-1), but there must be at least one NUMA node, so returning NUMA node zero\n",
      "2022-08-17 12:50:45.369308: I tensorflow/stream_executor/cuda/cuda_gpu_executor.cc:937] successful NUMA node read from SysFS had negative value (-1), but there must be at least one NUMA node, so returning NUMA node zero\n",
      "2022-08-17 12:50:45.370216: I tensorflow/stream_executor/cuda/cuda_gpu_executor.cc:937] successful NUMA node read from SysFS had negative value (-1), but there must be at least one NUMA node, so returning NUMA node zero\n",
      "2022-08-17 12:50:45.371015: I tensorflow/core/common_runtime/gpu/gpu_device.cc:1510] Created device /job:localhost/replica:0/task:0/device:GPU:0 with 15385 MB memory:  -> device: 0, name: Tesla P100-PCIE-16GB, pci bus id: 0000:00:04.0, compute capability: 6.0\n",
      "2022-08-17 12:50:45.372651: I tensorflow/core/grappler/optimizers/meta_optimizer.cc:1137] Optimization results for grappler item: graph_to_optimize\n",
      "  function_optimizer: function_optimizer did nothing. time = 0.007ms.\n",
      "  function_optimizer: function_optimizer did nothing. time = 0.001ms.\n",
      "\n",
      "Incomplete shape.\n",
      "Incomplete shape.\n"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "814/814 [==============================] - 6s 6ms/step - loss: 0.5324 - auc: 0.5558 - val_loss: 0.5122 - val_auc: 0.5785\n",
      "Epoch 2/100\n",
      "814/814 [==============================] - 3s 4ms/step - loss: 0.5097 - auc: 0.5876 - val_loss: 0.5154 - val_auc: 0.5588\n",
      "Epoch 3/100\n",
      "814/814 [==============================] - 3s 4ms/step - loss: 0.5095 - auc: 0.5880 - val_loss: 0.5131 - val_auc: 0.5718\n",
      "Epoch 4/100\n",
      "814/814 [==============================] - 4s 5ms/step - loss: 0.5096 - auc: 0.5860 - val_loss: 0.5129 - val_auc: 0.5796\n",
      "Epoch 5/100\n",
      "814/814 [==============================] - 4s 4ms/step - loss: 0.5098 - auc: 0.5861 - val_loss: 0.5106 - val_auc: 0.5907\n",
      "Epoch 6/100\n",
      "814/814 [==============================] - 3s 4ms/step - loss: 0.5096 - auc: 0.5870 - val_loss: 0.5103 - val_auc: 0.5864\n",
      "Epoch 7/100\n",
      "814/814 [==============================] - 3s 4ms/step - loss: 0.5097 - auc: 0.5870 - val_loss: 0.5119 - val_auc: 0.5733\n",
      "Epoch 8/100\n",
      "814/814 [==============================] - 4s 4ms/step - loss: 0.5095 - auc: 0.5878 - val_loss: 0.5090 - val_auc: 0.6048\n",
      "Epoch 9/100\n",
      "814/814 [==============================] - 4s 4ms/step - loss: 0.5097 - auc: 0.5867 - val_loss: 0.5154 - val_auc: 0.5462\n",
      "Epoch 10/100\n",
      "814/814 [==============================] - 5s 7ms/step - loss: 0.5098 - auc: 0.5862 - val_loss: 0.5142 - val_auc: 0.5724\n",
      "Epoch 11/100\n",
      "814/814 [==============================] - 3s 4ms/step - loss: 0.5097 - auc: 0.5868 - val_loss: 0.5134 - val_auc: 0.5730\n",
      "Epoch 12/100\n",
      "814/814 [==============================] - 3s 4ms/step - loss: 0.5098 - auc: 0.5869 - val_loss: 0.5140 - val_auc: 0.5664\n",
      "Epoch 13/100\n",
      "814/814 [==============================] - 4s 5ms/step - loss: 0.5094 - auc: 0.5890 - val_loss: 0.5117 - val_auc: 0.5815\n",
      "Train score: 0.5865073 / val score: 0.6056866 for split 33\n",
      "Epoch 1/100\n"
     ]
    },
    {
     "name": "stderr",
     "output_type": "stream",
     "text": [
      "2022-08-17 12:52:09.784736: I tensorflow/stream_executor/cuda/cuda_gpu_executor.cc:937] successful NUMA node read from SysFS had negative value (-1), but there must be at least one NUMA node, so returning NUMA node zero\n",
      "2022-08-17 12:52:09.785627: I tensorflow/core/grappler/devices.cc:66] Number of eligible GPUs (core count >= 8, compute capability >= 0.0): 1\n",
      "2022-08-17 12:52:09.785740: I tensorflow/core/grappler/clusters/single_machine.cc:357] Starting new session\n",
      "2022-08-17 12:52:09.786269: I tensorflow/stream_executor/cuda/cuda_gpu_executor.cc:937] successful NUMA node read from SysFS had negative value (-1), but there must be at least one NUMA node, so returning NUMA node zero\n",
      "2022-08-17 12:52:09.787195: I tensorflow/stream_executor/cuda/cuda_gpu_executor.cc:937] successful NUMA node read from SysFS had negative value (-1), but there must be at least one NUMA node, so returning NUMA node zero\n",
      "2022-08-17 12:52:09.788026: I tensorflow/stream_executor/cuda/cuda_gpu_executor.cc:937] successful NUMA node read from SysFS had negative value (-1), but there must be at least one NUMA node, so returning NUMA node zero\n",
      "2022-08-17 12:52:09.788940: I tensorflow/stream_executor/cuda/cuda_gpu_executor.cc:937] successful NUMA node read from SysFS had negative value (-1), but there must be at least one NUMA node, so returning NUMA node zero\n",
      "2022-08-17 12:52:09.789731: I tensorflow/stream_executor/cuda/cuda_gpu_executor.cc:937] successful NUMA node read from SysFS had negative value (-1), but there must be at least one NUMA node, so returning NUMA node zero\n",
      "2022-08-17 12:52:09.790518: I tensorflow/core/common_runtime/gpu/gpu_device.cc:1510] Created device /job:localhost/replica:0/task:0/device:GPU:0 with 15385 MB memory:  -> device: 0, name: Tesla P100-PCIE-16GB, pci bus id: 0000:00:04.0, compute capability: 6.0\n",
      "2022-08-17 12:52:09.791941: I tensorflow/core/grappler/optimizers/meta_optimizer.cc:1137] Optimization results for grappler item: graph_to_optimize\n",
      "  function_optimizer: function_optimizer did nothing. time = 0.007ms.\n",
      "  function_optimizer: function_optimizer did nothing. time = 0.001ms.\n",
      "\n",
      "Incomplete shape.\n",
      "Incomplete shape.\n"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "814/814 [==============================] - 5s 5ms/step - loss: 0.5253 - auc: 0.5631 - val_loss: 0.5017 - val_auc: 0.6349\n",
      "Epoch 2/100\n",
      "814/814 [==============================] - 3s 4ms/step - loss: 0.5100 - auc: 0.5854 - val_loss: 0.5047 - val_auc: 0.6223\n",
      "Epoch 3/100\n",
      "814/814 [==============================] - 4s 4ms/step - loss: 0.5099 - auc: 0.5850 - val_loss: 0.5045 - val_auc: 0.6199\n",
      "Epoch 4/100\n",
      "814/814 [==============================] - 3s 4ms/step - loss: 0.5098 - auc: 0.5869 - val_loss: 0.5084 - val_auc: 0.6011\n",
      "Epoch 5/100\n",
      "814/814 [==============================] - 3s 4ms/step - loss: 0.5099 - auc: 0.5845 - val_loss: 0.5050 - val_auc: 0.6127\n",
      "Epoch 6/100\n",
      "814/814 [==============================] - 4s 5ms/step - loss: 0.5098 - auc: 0.5866 - val_loss: 0.5027 - val_auc: 0.6326\n",
      "Train score: 0.5872206 / val score: 0.6357285 for split 34\n",
      "Epoch 1/100\n"
     ]
    },
    {
     "name": "stderr",
     "output_type": "stream",
     "text": [
      "2022-08-17 12:52:34.193267: I tensorflow/stream_executor/cuda/cuda_gpu_executor.cc:937] successful NUMA node read from SysFS had negative value (-1), but there must be at least one NUMA node, so returning NUMA node zero\n",
      "2022-08-17 12:52:34.194181: I tensorflow/core/grappler/devices.cc:66] Number of eligible GPUs (core count >= 8, compute capability >= 0.0): 1\n",
      "2022-08-17 12:52:34.194300: I tensorflow/core/grappler/clusters/single_machine.cc:357] Starting new session\n",
      "2022-08-17 12:52:34.194840: I tensorflow/stream_executor/cuda/cuda_gpu_executor.cc:937] successful NUMA node read from SysFS had negative value (-1), but there must be at least one NUMA node, so returning NUMA node zero\n",
      "2022-08-17 12:52:34.195835: I tensorflow/stream_executor/cuda/cuda_gpu_executor.cc:937] successful NUMA node read from SysFS had negative value (-1), but there must be at least one NUMA node, so returning NUMA node zero\n",
      "2022-08-17 12:52:34.196813: I tensorflow/stream_executor/cuda/cuda_gpu_executor.cc:937] successful NUMA node read from SysFS had negative value (-1), but there must be at least one NUMA node, so returning NUMA node zero\n",
      "2022-08-17 12:52:34.197813: I tensorflow/stream_executor/cuda/cuda_gpu_executor.cc:937] successful NUMA node read from SysFS had negative value (-1), but there must be at least one NUMA node, so returning NUMA node zero\n",
      "2022-08-17 12:52:34.198786: I tensorflow/stream_executor/cuda/cuda_gpu_executor.cc:937] successful NUMA node read from SysFS had negative value (-1), but there must be at least one NUMA node, so returning NUMA node zero\n",
      "2022-08-17 12:52:34.199607: I tensorflow/core/common_runtime/gpu/gpu_device.cc:1510] Created device /job:localhost/replica:0/task:0/device:GPU:0 with 15385 MB memory:  -> device: 0, name: Tesla P100-PCIE-16GB, pci bus id: 0000:00:04.0, compute capability: 6.0\n",
      "2022-08-17 12:52:34.201196: I tensorflow/core/grappler/optimizers/meta_optimizer.cc:1137] Optimization results for grappler item: graph_to_optimize\n",
      "  function_optimizer: function_optimizer did nothing. time = 0.007ms.\n",
      "  function_optimizer: function_optimizer did nothing. time = 0.001ms.\n",
      "\n",
      "Incomplete shape.\n",
      "Incomplete shape.\n"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "814/814 [==============================] - 4s 4ms/step - loss: 0.5270 - auc: 0.5656 - val_loss: 0.5188 - val_auc: 0.5542\n",
      "Epoch 2/100\n",
      "814/814 [==============================] - 4s 5ms/step - loss: 0.5098 - auc: 0.5860 - val_loss: 0.5169 - val_auc: 0.5577\n",
      "Epoch 3/100\n",
      "814/814 [==============================] - 4s 5ms/step - loss: 0.5097 - auc: 0.5866 - val_loss: 0.5148 - val_auc: 0.5669\n",
      "Epoch 4/100\n",
      "814/814 [==============================] - 4s 5ms/step - loss: 0.5092 - auc: 0.5886 - val_loss: 0.5186 - val_auc: 0.5466\n",
      "Epoch 5/100\n",
      "814/814 [==============================] - 4s 4ms/step - loss: 0.5096 - auc: 0.5865 - val_loss: 0.5193 - val_auc: 0.5515\n",
      "Epoch 6/100\n",
      "814/814 [==============================] - 3s 4ms/step - loss: 0.5099 - auc: 0.5857 - val_loss: 0.5112 - val_auc: 0.5938\n",
      "Epoch 7/100\n",
      "814/814 [==============================] - 3s 4ms/step - loss: 0.5097 - auc: 0.5858 - val_loss: 0.5161 - val_auc: 0.5599\n",
      "Epoch 8/100\n",
      "814/814 [==============================] - 4s 5ms/step - loss: 0.5094 - auc: 0.5876 - val_loss: 0.5115 - val_auc: 0.5913\n",
      "Epoch 9/100\n",
      "814/814 [==============================] - 3s 4ms/step - loss: 0.5095 - auc: 0.5869 - val_loss: 0.5160 - val_auc: 0.5575\n",
      "Epoch 10/100\n",
      "814/814 [==============================] - 4s 5ms/step - loss: 0.5098 - auc: 0.5856 - val_loss: 0.5132 - val_auc: 0.5831\n",
      "Epoch 11/100\n",
      "814/814 [==============================] - 4s 5ms/step - loss: 0.5094 - auc: 0.5891 - val_loss: 0.5127 - val_auc: 0.5942\n",
      "Epoch 12/100\n",
      "814/814 [==============================] - 3s 4ms/step - loss: 0.5096 - auc: 0.5855 - val_loss: 0.5182 - val_auc: 0.5547\n",
      "Epoch 13/100\n",
      "814/814 [==============================] - 4s 6ms/step - loss: 0.5094 - auc: 0.5878 - val_loss: 0.5111 - val_auc: 0.6016\n",
      "Epoch 14/100\n",
      "814/814 [==============================] - 4s 5ms/step - loss: 0.5097 - auc: 0.5871 - val_loss: 0.5164 - val_auc: 0.5679\n",
      "Epoch 15/100\n",
      "814/814 [==============================] - 3s 4ms/step - loss: 0.5097 - auc: 0.5869 - val_loss: 0.5117 - val_auc: 0.5920\n",
      "Epoch 16/100\n",
      "814/814 [==============================] - 3s 4ms/step - loss: 0.5097 - auc: 0.5860 - val_loss: 0.5139 - val_auc: 0.5871\n",
      "Epoch 17/100\n",
      "814/814 [==============================] - 4s 5ms/step - loss: 0.5097 - auc: 0.5865 - val_loss: 0.5172 - val_auc: 0.5602\n",
      "Epoch 18/100\n",
      "814/814 [==============================] - 3s 4ms/step - loss: 0.5098 - auc: 0.5869 - val_loss: 0.5130 - val_auc: 0.5891\n",
      "Train score: 0.5891018 / val score: 0.6024262 for split 35\n"
     ]
    },
    {
     "name": "stderr",
     "output_type": "stream",
     "text": [
      "2022-08-17 12:53:42.051082: I tensorflow/stream_executor/cuda/cuda_gpu_executor.cc:937] successful NUMA node read from SysFS had negative value (-1), but there must be at least one NUMA node, so returning NUMA node zero\n",
      "2022-08-17 12:53:42.052312: I tensorflow/core/grappler/devices.cc:66] Number of eligible GPUs (core count >= 8, compute capability >= 0.0): 1\n",
      "2022-08-17 12:53:42.056145: I tensorflow/core/grappler/clusters/single_machine.cc:357] Starting new session\n",
      "2022-08-17 12:53:42.057194: I tensorflow/stream_executor/cuda/cuda_gpu_executor.cc:937] successful NUMA node read from SysFS had negative value (-1), but there must be at least one NUMA node, so returning NUMA node zero\n",
      "2022-08-17 12:53:42.058489: I tensorflow/stream_executor/cuda/cuda_gpu_executor.cc:937] successful NUMA node read from SysFS had negative value (-1), but there must be at least one NUMA node, so returning NUMA node zero\n",
      "2022-08-17 12:53:42.059660: I tensorflow/stream_executor/cuda/cuda_gpu_executor.cc:937] successful NUMA node read from SysFS had negative value (-1), but there must be at least one NUMA node, so returning NUMA node zero\n",
      "2022-08-17 12:53:42.061046: I tensorflow/stream_executor/cuda/cuda_gpu_executor.cc:937] successful NUMA node read from SysFS had negative value (-1), but there must be at least one NUMA node, so returning NUMA node zero\n",
      "2022-08-17 12:53:42.062297: I tensorflow/stream_executor/cuda/cuda_gpu_executor.cc:937] successful NUMA node read from SysFS had negative value (-1), but there must be at least one NUMA node, so returning NUMA node zero\n",
      "2022-08-17 12:53:42.063255: I tensorflow/core/common_runtime/gpu/gpu_device.cc:1510] Created device /job:localhost/replica:0/task:0/device:GPU:0 with 15385 MB memory:  -> device: 0, name: Tesla P100-PCIE-16GB, pci bus id: 0000:00:04.0, compute capability: 6.0\n",
      "2022-08-17 12:53:42.076629: I tensorflow/core/grappler/optimizers/meta_optimizer.cc:1137] Optimization results for grappler item: graph_to_optimize\n",
      "  function_optimizer: function_optimizer did nothing. time = 0.007ms.\n",
      "  function_optimizer: function_optimizer did nothing. time = 0.001ms.\n",
      "\n",
      "Incomplete shape.\n",
      "Incomplete shape.\n"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "Epoch 1/100\n",
      "814/814 [==============================] - 5s 5ms/step - loss: 0.5266 - auc: 0.5641 - val_loss: 0.5144 - val_auc: 0.5690\n",
      "Epoch 2/100\n",
      "814/814 [==============================] - 3s 4ms/step - loss: 0.5094 - auc: 0.5879 - val_loss: 0.5143 - val_auc: 0.5677\n",
      "Epoch 3/100\n",
      "814/814 [==============================] - 4s 5ms/step - loss: 0.5096 - auc: 0.5873 - val_loss: 0.5142 - val_auc: 0.5615\n",
      "Epoch 4/100\n",
      "814/814 [==============================] - 4s 5ms/step - loss: 0.5093 - auc: 0.5877 - val_loss: 0.5124 - val_auc: 0.5820\n",
      "Epoch 5/100\n",
      "814/814 [==============================] - 3s 4ms/step - loss: 0.5097 - auc: 0.5872 - val_loss: 0.5128 - val_auc: 0.5750\n",
      "Epoch 6/100\n",
      "814/814 [==============================] - 3s 4ms/step - loss: 0.5096 - auc: 0.5873 - val_loss: 0.5139 - val_auc: 0.5628\n",
      "Epoch 7/100\n",
      "814/814 [==============================] - 4s 5ms/step - loss: 0.5099 - auc: 0.5862 - val_loss: 0.5141 - val_auc: 0.5605\n",
      "Epoch 8/100\n",
      "814/814 [==============================] - 3s 4ms/step - loss: 0.5095 - auc: 0.5872 - val_loss: 0.5153 - val_auc: 0.5564\n",
      "Epoch 9/100\n",
      "814/814 [==============================] - 4s 5ms/step - loss: 0.5095 - auc: 0.5867 - val_loss: 0.5131 - val_auc: 0.5699\n",
      "Train score: 0.5898107 / val score: 0.5816996 for split 36\n",
      "Epoch 1/100\n"
     ]
    },
    {
     "name": "stderr",
     "output_type": "stream",
     "text": [
      "2022-08-17 12:54:25.605980: I tensorflow/stream_executor/cuda/cuda_gpu_executor.cc:937] successful NUMA node read from SysFS had negative value (-1), but there must be at least one NUMA node, so returning NUMA node zero\n",
      "2022-08-17 12:54:25.606830: I tensorflow/core/grappler/devices.cc:66] Number of eligible GPUs (core count >= 8, compute capability >= 0.0): 1\n",
      "2022-08-17 12:54:25.606971: I tensorflow/core/grappler/clusters/single_machine.cc:357] Starting new session\n",
      "2022-08-17 12:54:25.607537: I tensorflow/stream_executor/cuda/cuda_gpu_executor.cc:937] successful NUMA node read from SysFS had negative value (-1), but there must be at least one NUMA node, so returning NUMA node zero\n",
      "2022-08-17 12:54:25.608410: I tensorflow/stream_executor/cuda/cuda_gpu_executor.cc:937] successful NUMA node read from SysFS had negative value (-1), but there must be at least one NUMA node, so returning NUMA node zero\n",
      "2022-08-17 12:54:25.609252: I tensorflow/stream_executor/cuda/cuda_gpu_executor.cc:937] successful NUMA node read from SysFS had negative value (-1), but there must be at least one NUMA node, so returning NUMA node zero\n",
      "2022-08-17 12:54:25.610166: I tensorflow/stream_executor/cuda/cuda_gpu_executor.cc:937] successful NUMA node read from SysFS had negative value (-1), but there must be at least one NUMA node, so returning NUMA node zero\n",
      "2022-08-17 12:54:25.611126: I tensorflow/stream_executor/cuda/cuda_gpu_executor.cc:937] successful NUMA node read from SysFS had negative value (-1), but there must be at least one NUMA node, so returning NUMA node zero\n",
      "2022-08-17 12:54:25.611943: I tensorflow/core/common_runtime/gpu/gpu_device.cc:1510] Created device /job:localhost/replica:0/task:0/device:GPU:0 with 15385 MB memory:  -> device: 0, name: Tesla P100-PCIE-16GB, pci bus id: 0000:00:04.0, compute capability: 6.0\n",
      "2022-08-17 12:54:25.613701: I tensorflow/core/grappler/optimizers/meta_optimizer.cc:1137] Optimization results for grappler item: graph_to_optimize\n",
      "  function_optimizer: function_optimizer did nothing. time = 0.007ms.\n",
      "  function_optimizer: function_optimizer did nothing. time = 0.001ms.\n",
      "\n",
      "Incomplete shape.\n",
      "Incomplete shape.\n"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "814/814 [==============================] - 6s 6ms/step - loss: 0.5304 - auc: 0.5594 - val_loss: 0.5118 - val_auc: 0.5824\n",
      "Epoch 2/100\n",
      "814/814 [==============================] - 3s 4ms/step - loss: 0.5093 - auc: 0.5882 - val_loss: 0.5130 - val_auc: 0.5823\n",
      "Epoch 3/100\n",
      "814/814 [==============================] - 3s 4ms/step - loss: 0.5097 - auc: 0.5882 - val_loss: 0.5103 - val_auc: 0.5858\n",
      "Epoch 4/100\n",
      "814/814 [==============================] - 4s 4ms/step - loss: 0.5099 - auc: 0.5860 - val_loss: 0.5130 - val_auc: 0.5798\n",
      "Epoch 5/100\n",
      "814/814 [==============================] - 3s 4ms/step - loss: 0.5098 - auc: 0.5869 - val_loss: 0.5154 - val_auc: 0.5699\n",
      "Epoch 6/100\n",
      "814/814 [==============================] - 4s 5ms/step - loss: 0.5096 - auc: 0.5875 - val_loss: 0.5112 - val_auc: 0.5884\n",
      "Epoch 7/100\n",
      "814/814 [==============================] - 4s 4ms/step - loss: 0.5095 - auc: 0.5881 - val_loss: 0.5120 - val_auc: 0.5840\n",
      "Epoch 8/100\n",
      "814/814 [==============================] - 3s 4ms/step - loss: 0.5098 - auc: 0.5867 - val_loss: 0.5092 - val_auc: 0.5998\n",
      "Epoch 9/100\n",
      "814/814 [==============================] - 3s 4ms/step - loss: 0.5098 - auc: 0.5864 - val_loss: 0.5088 - val_auc: 0.6019\n",
      "Epoch 10/100\n",
      "814/814 [==============================] - 4s 5ms/step - loss: 0.5095 - auc: 0.5877 - val_loss: 0.5118 - val_auc: 0.5843\n",
      "Epoch 11/100\n",
      "814/814 [==============================] - 4s 5ms/step - loss: 0.5099 - auc: 0.5853 - val_loss: 0.5095 - val_auc: 0.6009\n",
      "Epoch 12/100\n",
      "814/814 [==============================] - 3s 4ms/step - loss: 0.5096 - auc: 0.5871 - val_loss: 0.5099 - val_auc: 0.5923\n",
      "Epoch 13/100\n",
      "814/814 [==============================] - 4s 4ms/step - loss: 0.5099 - auc: 0.5858 - val_loss: 0.5141 - val_auc: 0.5746\n",
      "Epoch 14/100\n",
      "814/814 [==============================] - 3s 4ms/step - loss: 0.5096 - auc: 0.5873 - val_loss: 0.5092 - val_auc: 0.6062\n",
      "Epoch 15/100\n",
      "814/814 [==============================] - 4s 5ms/step - loss: 0.5100 - auc: 0.5858 - val_loss: 0.5098 - val_auc: 0.5960\n",
      "Epoch 16/100\n",
      "814/814 [==============================] - 4s 5ms/step - loss: 0.5094 - auc: 0.5873 - val_loss: 0.5080 - val_auc: 0.5995\n",
      "Epoch 17/100\n",
      "814/814 [==============================] - 4s 4ms/step - loss: 0.5096 - auc: 0.5869 - val_loss: 0.5100 - val_auc: 0.5967\n",
      "Epoch 18/100\n",
      "814/814 [==============================] - 3s 4ms/step - loss: 0.5096 - auc: 0.5873 - val_loss: 0.5092 - val_auc: 0.5927\n",
      "Epoch 19/100\n",
      "814/814 [==============================] - 3s 4ms/step - loss: 0.5098 - auc: 0.5866 - val_loss: 0.5094 - val_auc: 0.5959\n",
      "Train score: 0.5904869 / val score: 0.6064487 for split 37\n"
     ]
    },
    {
     "name": "stderr",
     "output_type": "stream",
     "text": [
      "2022-08-17 12:55:38.907886: I tensorflow/stream_executor/cuda/cuda_gpu_executor.cc:937] successful NUMA node read from SysFS had negative value (-1), but there must be at least one NUMA node, so returning NUMA node zero\n",
      "2022-08-17 12:55:38.908765: I tensorflow/core/grappler/devices.cc:66] Number of eligible GPUs (core count >= 8, compute capability >= 0.0): 1\n",
      "2022-08-17 12:55:38.908911: I tensorflow/core/grappler/clusters/single_machine.cc:357] Starting new session\n",
      "2022-08-17 12:55:38.909362: I tensorflow/stream_executor/cuda/cuda_gpu_executor.cc:937] successful NUMA node read from SysFS had negative value (-1), but there must be at least one NUMA node, so returning NUMA node zero\n",
      "2022-08-17 12:55:38.910268: I tensorflow/stream_executor/cuda/cuda_gpu_executor.cc:937] successful NUMA node read from SysFS had negative value (-1), but there must be at least one NUMA node, so returning NUMA node zero\n",
      "2022-08-17 12:55:38.911179: I tensorflow/stream_executor/cuda/cuda_gpu_executor.cc:937] successful NUMA node read from SysFS had negative value (-1), but there must be at least one NUMA node, so returning NUMA node zero\n",
      "2022-08-17 12:55:38.912231: I tensorflow/stream_executor/cuda/cuda_gpu_executor.cc:937] successful NUMA node read from SysFS had negative value (-1), but there must be at least one NUMA node, so returning NUMA node zero\n",
      "2022-08-17 12:55:38.913177: I tensorflow/stream_executor/cuda/cuda_gpu_executor.cc:937] successful NUMA node read from SysFS had negative value (-1), but there must be at least one NUMA node, so returning NUMA node zero\n",
      "2022-08-17 12:55:38.913980: I tensorflow/core/common_runtime/gpu/gpu_device.cc:1510] Created device /job:localhost/replica:0/task:0/device:GPU:0 with 15385 MB memory:  -> device: 0, name: Tesla P100-PCIE-16GB, pci bus id: 0000:00:04.0, compute capability: 6.0\n",
      "2022-08-17 12:55:38.915574: I tensorflow/core/grappler/optimizers/meta_optimizer.cc:1137] Optimization results for grappler item: graph_to_optimize\n",
      "  function_optimizer: function_optimizer did nothing. time = 0.006ms.\n",
      "  function_optimizer: function_optimizer did nothing. time = 0.001ms.\n",
      "\n",
      "Incomplete shape.\n",
      "Incomplete shape.\n"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "Epoch 1/100\n",
      "814/814 [==============================] - 4s 4ms/step - loss: 0.5284 - auc: 0.5641 - val_loss: 0.5049 - val_auc: 0.6183\n",
      "Epoch 2/100\n",
      "814/814 [==============================] - 3s 4ms/step - loss: 0.5096 - auc: 0.5864 - val_loss: 0.5066 - val_auc: 0.6114\n",
      "Epoch 3/100\n",
      "814/814 [==============================] - 4s 4ms/step - loss: 0.5099 - auc: 0.5856 - val_loss: 0.5089 - val_auc: 0.6018\n",
      "Epoch 4/100\n",
      "814/814 [==============================] - 4s 5ms/step - loss: 0.5098 - auc: 0.5853 - val_loss: 0.5080 - val_auc: 0.6023\n",
      "Epoch 5/100\n",
      "814/814 [==============================] - 3s 4ms/step - loss: 0.5095 - auc: 0.5884 - val_loss: 0.5124 - val_auc: 0.5787\n",
      "Epoch 6/100\n",
      "814/814 [==============================] - 4s 5ms/step - loss: 0.5097 - auc: 0.5858 - val_loss: 0.5075 - val_auc: 0.6086\n",
      "Train score: 0.5888579 / val score: 0.6182199 for split 38\n",
      "Epoch 1/100\n"
     ]
    },
    {
     "name": "stderr",
     "output_type": "stream",
     "text": [
      "2022-08-17 12:56:02.000592: I tensorflow/stream_executor/cuda/cuda_gpu_executor.cc:937] successful NUMA node read from SysFS had negative value (-1), but there must be at least one NUMA node, so returning NUMA node zero\n",
      "2022-08-17 12:56:02.001494: I tensorflow/core/grappler/devices.cc:66] Number of eligible GPUs (core count >= 8, compute capability >= 0.0): 1\n",
      "2022-08-17 12:56:02.001622: I tensorflow/core/grappler/clusters/single_machine.cc:357] Starting new session\n",
      "2022-08-17 12:56:02.002166: I tensorflow/stream_executor/cuda/cuda_gpu_executor.cc:937] successful NUMA node read from SysFS had negative value (-1), but there must be at least one NUMA node, so returning NUMA node zero\n",
      "2022-08-17 12:56:02.003048: I tensorflow/stream_executor/cuda/cuda_gpu_executor.cc:937] successful NUMA node read from SysFS had negative value (-1), but there must be at least one NUMA node, so returning NUMA node zero\n",
      "2022-08-17 12:56:02.003951: I tensorflow/stream_executor/cuda/cuda_gpu_executor.cc:937] successful NUMA node read from SysFS had negative value (-1), but there must be at least one NUMA node, so returning NUMA node zero\n",
      "2022-08-17 12:56:02.005001: I tensorflow/stream_executor/cuda/cuda_gpu_executor.cc:937] successful NUMA node read from SysFS had negative value (-1), but there must be at least one NUMA node, so returning NUMA node zero\n",
      "2022-08-17 12:56:02.005938: I tensorflow/stream_executor/cuda/cuda_gpu_executor.cc:937] successful NUMA node read from SysFS had negative value (-1), but there must be at least one NUMA node, so returning NUMA node zero\n",
      "2022-08-17 12:56:02.006695: I tensorflow/core/common_runtime/gpu/gpu_device.cc:1510] Created device /job:localhost/replica:0/task:0/device:GPU:0 with 15385 MB memory:  -> device: 0, name: Tesla P100-PCIE-16GB, pci bus id: 0000:00:04.0, compute capability: 6.0\n",
      "2022-08-17 12:56:02.008187: I tensorflow/core/grappler/optimizers/meta_optimizer.cc:1137] Optimization results for grappler item: graph_to_optimize\n",
      "  function_optimizer: function_optimizer did nothing. time = 0.006ms.\n",
      "  function_optimizer: function_optimizer did nothing. time = 0.001ms.\n",
      "\n",
      "Incomplete shape.\n",
      "Incomplete shape.\n"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "814/814 [==============================] - 4s 4ms/step - loss: 0.5260 - auc: 0.5608 - val_loss: 0.5052 - val_auc: 0.5913\n",
      "Epoch 2/100\n",
      "814/814 [==============================] - 4s 5ms/step - loss: 0.5096 - auc: 0.5865 - val_loss: 0.5066 - val_auc: 0.5882\n",
      "Epoch 3/100\n",
      "814/814 [==============================] - 5s 6ms/step - loss: 0.5094 - auc: 0.5891 - val_loss: 0.5092 - val_auc: 0.5716\n",
      "Epoch 4/100\n",
      "814/814 [==============================] - 3s 4ms/step - loss: 0.5100 - auc: 0.5850 - val_loss: 0.5056 - val_auc: 0.5901\n",
      "Epoch 5/100\n",
      "814/814 [==============================] - 4s 5ms/step - loss: 0.5098 - auc: 0.5863 - val_loss: 0.5069 - val_auc: 0.5905\n",
      "Epoch 6/100\n",
      "814/814 [==============================] - 4s 4ms/step - loss: 0.5098 - auc: 0.5866 - val_loss: 0.5063 - val_auc: 0.5897\n",
      "Train score: 0.5908991 / val score: 0.5898505 for split 39\n",
      "Epoch 1/100\n"
     ]
    },
    {
     "name": "stderr",
     "output_type": "stream",
     "text": [
      "2022-08-17 12:56:45.147439: I tensorflow/stream_executor/cuda/cuda_gpu_executor.cc:937] successful NUMA node read from SysFS had negative value (-1), but there must be at least one NUMA node, so returning NUMA node zero\n",
      "2022-08-17 12:56:45.148355: I tensorflow/core/grappler/devices.cc:66] Number of eligible GPUs (core count >= 8, compute capability >= 0.0): 1\n",
      "2022-08-17 12:56:45.148461: I tensorflow/core/grappler/clusters/single_machine.cc:357] Starting new session\n",
      "2022-08-17 12:56:45.148976: I tensorflow/stream_executor/cuda/cuda_gpu_executor.cc:937] successful NUMA node read from SysFS had negative value (-1), but there must be at least one NUMA node, so returning NUMA node zero\n",
      "2022-08-17 12:56:45.149899: I tensorflow/stream_executor/cuda/cuda_gpu_executor.cc:937] successful NUMA node read from SysFS had negative value (-1), but there must be at least one NUMA node, so returning NUMA node zero\n",
      "2022-08-17 12:56:45.150754: I tensorflow/stream_executor/cuda/cuda_gpu_executor.cc:937] successful NUMA node read from SysFS had negative value (-1), but there must be at least one NUMA node, so returning NUMA node zero\n",
      "2022-08-17 12:56:45.151825: I tensorflow/stream_executor/cuda/cuda_gpu_executor.cc:937] successful NUMA node read from SysFS had negative value (-1), but there must be at least one NUMA node, so returning NUMA node zero\n",
      "2022-08-17 12:56:45.152835: I tensorflow/stream_executor/cuda/cuda_gpu_executor.cc:937] successful NUMA node read from SysFS had negative value (-1), but there must be at least one NUMA node, so returning NUMA node zero\n",
      "2022-08-17 12:56:45.153740: I tensorflow/core/common_runtime/gpu/gpu_device.cc:1510] Created device /job:localhost/replica:0/task:0/device:GPU:0 with 15385 MB memory:  -> device: 0, name: Tesla P100-PCIE-16GB, pci bus id: 0000:00:04.0, compute capability: 6.0\n",
      "2022-08-17 12:56:45.155290: I tensorflow/core/grappler/optimizers/meta_optimizer.cc:1137] Optimization results for grappler item: graph_to_optimize\n",
      "  function_optimizer: function_optimizer did nothing. time = 0.006ms.\n",
      "  function_optimizer: function_optimizer did nothing. time = 0.001ms.\n",
      "\n",
      "Incomplete shape.\n",
      "Incomplete shape.\n"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "814/814 [==============================] - 6s 6ms/step - loss: 0.5260 - auc: 0.5626 - val_loss: 0.5041 - val_auc: 0.6269\n",
      "Epoch 2/100\n",
      "814/814 [==============================] - 4s 5ms/step - loss: 0.5095 - auc: 0.5885 - val_loss: 0.5107 - val_auc: 0.5770\n",
      "Epoch 3/100\n",
      "814/814 [==============================] - 4s 5ms/step - loss: 0.5098 - auc: 0.5856 - val_loss: 0.5072 - val_auc: 0.6040\n",
      "Epoch 4/100\n",
      "814/814 [==============================] - 3s 4ms/step - loss: 0.5098 - auc: 0.5869 - val_loss: 0.5051 - val_auc: 0.6156\n",
      "Epoch 5/100\n",
      "814/814 [==============================] - 4s 5ms/step - loss: 0.5099 - auc: 0.5856 - val_loss: 0.5058 - val_auc: 0.6019\n",
      "Epoch 6/100\n",
      "814/814 [==============================] - 3s 4ms/step - loss: 0.5098 - auc: 0.5864 - val_loss: 0.5092 - val_auc: 0.5909\n",
      "Train score: 0.5819105 / val score: 0.6263073 for split 40\n",
      "Epoch 1/100\n"
     ]
    },
    {
     "name": "stderr",
     "output_type": "stream",
     "text": [
      "2022-08-17 12:57:10.512593: I tensorflow/stream_executor/cuda/cuda_gpu_executor.cc:937] successful NUMA node read from SysFS had negative value (-1), but there must be at least one NUMA node, so returning NUMA node zero\n",
      "2022-08-17 12:57:10.513569: I tensorflow/core/grappler/devices.cc:66] Number of eligible GPUs (core count >= 8, compute capability >= 0.0): 1\n",
      "2022-08-17 12:57:10.513685: I tensorflow/core/grappler/clusters/single_machine.cc:357] Starting new session\n",
      "2022-08-17 12:57:10.514232: I tensorflow/stream_executor/cuda/cuda_gpu_executor.cc:937] successful NUMA node read from SysFS had negative value (-1), but there must be at least one NUMA node, so returning NUMA node zero\n",
      "2022-08-17 12:57:10.515117: I tensorflow/stream_executor/cuda/cuda_gpu_executor.cc:937] successful NUMA node read from SysFS had negative value (-1), but there must be at least one NUMA node, so returning NUMA node zero\n",
      "2022-08-17 12:57:10.516020: I tensorflow/stream_executor/cuda/cuda_gpu_executor.cc:937] successful NUMA node read from SysFS had negative value (-1), but there must be at least one NUMA node, so returning NUMA node zero\n",
      "2022-08-17 12:57:10.516936: I tensorflow/stream_executor/cuda/cuda_gpu_executor.cc:937] successful NUMA node read from SysFS had negative value (-1), but there must be at least one NUMA node, so returning NUMA node zero\n",
      "2022-08-17 12:57:10.517807: I tensorflow/stream_executor/cuda/cuda_gpu_executor.cc:937] successful NUMA node read from SysFS had negative value (-1), but there must be at least one NUMA node, so returning NUMA node zero\n",
      "2022-08-17 12:57:10.518607: I tensorflow/core/common_runtime/gpu/gpu_device.cc:1510] Created device /job:localhost/replica:0/task:0/device:GPU:0 with 15385 MB memory:  -> device: 0, name: Tesla P100-PCIE-16GB, pci bus id: 0000:00:04.0, compute capability: 6.0\n",
      "2022-08-17 12:57:10.520083: I tensorflow/core/grappler/optimizers/meta_optimizer.cc:1137] Optimization results for grappler item: graph_to_optimize\n",
      "  function_optimizer: function_optimizer did nothing. time = 0.007ms.\n",
      "  function_optimizer: function_optimizer did nothing. time = 0.001ms.\n",
      "\n",
      "Incomplete shape.\n",
      "Incomplete shape.\n"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "814/814 [==============================] - 4s 4ms/step - loss: 0.5264 - auc: 0.5685 - val_loss: 0.5127 - val_auc: 0.5793\n",
      "Epoch 2/100\n",
      "814/814 [==============================] - 4s 5ms/step - loss: 0.5098 - auc: 0.5864 - val_loss: 0.5098 - val_auc: 0.5878\n",
      "Epoch 3/100\n",
      "814/814 [==============================] - 4s 5ms/step - loss: 0.5097 - auc: 0.5889 - val_loss: 0.5103 - val_auc: 0.5907\n",
      "Epoch 4/100\n",
      "814/814 [==============================] - 4s 5ms/step - loss: 0.5099 - auc: 0.5855 - val_loss: 0.5076 - val_auc: 0.6023\n",
      "Epoch 5/100\n",
      "814/814 [==============================] - 3s 4ms/step - loss: 0.5097 - auc: 0.5858 - val_loss: 0.5104 - val_auc: 0.5896\n",
      "Epoch 6/100\n",
      "814/814 [==============================] - 3s 4ms/step - loss: 0.5098 - auc: 0.5843 - val_loss: 0.5071 - val_auc: 0.6030\n",
      "Epoch 7/100\n",
      "814/814 [==============================] - 3s 4ms/step - loss: 0.5097 - auc: 0.5866 - val_loss: 0.5103 - val_auc: 0.5912\n",
      "Epoch 8/100\n",
      "814/814 [==============================] - 4s 5ms/step - loss: 0.5097 - auc: 0.5865 - val_loss: 0.5112 - val_auc: 0.5917\n",
      "Epoch 9/100\n",
      "814/814 [==============================] - 3s 4ms/step - loss: 0.5096 - auc: 0.5872 - val_loss: 0.5100 - val_auc: 0.5953\n",
      "Epoch 10/100\n",
      "814/814 [==============================] - 3s 4ms/step - loss: 0.5096 - auc: 0.5860 - val_loss: 0.5083 - val_auc: 0.5996\n",
      "Epoch 11/100\n",
      "814/814 [==============================] - 4s 4ms/step - loss: 0.5097 - auc: 0.5859 - val_loss: 0.5130 - val_auc: 0.5750\n",
      "Train score: 0.5902655 / val score: 0.6040987 for split 41\n",
      "Epoch 1/100\n"
     ]
    },
    {
     "name": "stderr",
     "output_type": "stream",
     "text": [
      "2022-08-17 12:57:53.376144: I tensorflow/stream_executor/cuda/cuda_gpu_executor.cc:937] successful NUMA node read from SysFS had negative value (-1), but there must be at least one NUMA node, so returning NUMA node zero\n",
      "2022-08-17 12:57:53.377157: I tensorflow/core/grappler/devices.cc:66] Number of eligible GPUs (core count >= 8, compute capability >= 0.0): 1\n",
      "2022-08-17 12:57:53.377298: I tensorflow/core/grappler/clusters/single_machine.cc:357] Starting new session\n",
      "2022-08-17 12:57:53.377807: I tensorflow/stream_executor/cuda/cuda_gpu_executor.cc:937] successful NUMA node read from SysFS had negative value (-1), but there must be at least one NUMA node, so returning NUMA node zero\n",
      "2022-08-17 12:57:53.378771: I tensorflow/stream_executor/cuda/cuda_gpu_executor.cc:937] successful NUMA node read from SysFS had negative value (-1), but there must be at least one NUMA node, so returning NUMA node zero\n",
      "2022-08-17 12:57:53.379752: I tensorflow/stream_executor/cuda/cuda_gpu_executor.cc:937] successful NUMA node read from SysFS had negative value (-1), but there must be at least one NUMA node, so returning NUMA node zero\n",
      "2022-08-17 12:57:53.380760: I tensorflow/stream_executor/cuda/cuda_gpu_executor.cc:937] successful NUMA node read from SysFS had negative value (-1), but there must be at least one NUMA node, so returning NUMA node zero\n",
      "2022-08-17 12:57:53.381817: I tensorflow/stream_executor/cuda/cuda_gpu_executor.cc:937] successful NUMA node read from SysFS had negative value (-1), but there must be at least one NUMA node, so returning NUMA node zero\n",
      "2022-08-17 12:57:53.382598: I tensorflow/core/common_runtime/gpu/gpu_device.cc:1510] Created device /job:localhost/replica:0/task:0/device:GPU:0 with 15385 MB memory:  -> device: 0, name: Tesla P100-PCIE-16GB, pci bus id: 0000:00:04.0, compute capability: 6.0\n",
      "2022-08-17 12:57:53.384133: I tensorflow/core/grappler/optimizers/meta_optimizer.cc:1137] Optimization results for grappler item: graph_to_optimize\n",
      "  function_optimizer: function_optimizer did nothing. time = 0.006ms.\n",
      "  function_optimizer: function_optimizer did nothing. time = 0.002ms.\n",
      "\n",
      "Incomplete shape.\n",
      "Incomplete shape.\n"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "814/814 [==============================] - 5s 6ms/step - loss: 0.5312 - auc: 0.5548 - val_loss: 0.5071 - val_auc: 0.6078\n",
      "Epoch 2/100\n",
      "814/814 [==============================] - 4s 5ms/step - loss: 0.5097 - auc: 0.5847 - val_loss: 0.5082 - val_auc: 0.5953\n",
      "Epoch 3/100\n",
      "814/814 [==============================] - 3s 4ms/step - loss: 0.5096 - auc: 0.5870 - val_loss: 0.5095 - val_auc: 0.5789\n",
      "Epoch 4/100\n",
      "814/814 [==============================] - 3s 4ms/step - loss: 0.5098 - auc: 0.5866 - val_loss: 0.5084 - val_auc: 0.5848\n",
      "Epoch 5/100\n",
      "814/814 [==============================] - 4s 5ms/step - loss: 0.5096 - auc: 0.5866 - val_loss: 0.5074 - val_auc: 0.5965\n",
      "Epoch 6/100\n",
      "814/814 [==============================] - 3s 4ms/step - loss: 0.5099 - auc: 0.5849 - val_loss: 0.5082 - val_auc: 0.5917\n",
      "Train score: 0.5860649 / val score: 0.6071262 for split 42\n",
      "Epoch 1/100\n"
     ]
    },
    {
     "name": "stderr",
     "output_type": "stream",
     "text": [
      "2022-08-17 12:58:36.486084: I tensorflow/stream_executor/cuda/cuda_gpu_executor.cc:937] successful NUMA node read from SysFS had negative value (-1), but there must be at least one NUMA node, so returning NUMA node zero\n",
      "2022-08-17 12:58:36.486965: I tensorflow/core/grappler/devices.cc:66] Number of eligible GPUs (core count >= 8, compute capability >= 0.0): 1\n",
      "2022-08-17 12:58:36.487077: I tensorflow/core/grappler/clusters/single_machine.cc:357] Starting new session\n",
      "2022-08-17 12:58:36.487569: I tensorflow/stream_executor/cuda/cuda_gpu_executor.cc:937] successful NUMA node read from SysFS had negative value (-1), but there must be at least one NUMA node, so returning NUMA node zero\n",
      "2022-08-17 12:58:36.488452: I tensorflow/stream_executor/cuda/cuda_gpu_executor.cc:937] successful NUMA node read from SysFS had negative value (-1), but there must be at least one NUMA node, so returning NUMA node zero\n",
      "2022-08-17 12:58:36.489290: I tensorflow/stream_executor/cuda/cuda_gpu_executor.cc:937] successful NUMA node read from SysFS had negative value (-1), but there must be at least one NUMA node, so returning NUMA node zero\n",
      "2022-08-17 12:58:36.490270: I tensorflow/stream_executor/cuda/cuda_gpu_executor.cc:937] successful NUMA node read from SysFS had negative value (-1), but there must be at least one NUMA node, so returning NUMA node zero\n",
      "2022-08-17 12:58:36.491158: I tensorflow/stream_executor/cuda/cuda_gpu_executor.cc:937] successful NUMA node read from SysFS had negative value (-1), but there must be at least one NUMA node, so returning NUMA node zero\n",
      "2022-08-17 12:58:36.491944: I tensorflow/core/common_runtime/gpu/gpu_device.cc:1510] Created device /job:localhost/replica:0/task:0/device:GPU:0 with 15385 MB memory:  -> device: 0, name: Tesla P100-PCIE-16GB, pci bus id: 0000:00:04.0, compute capability: 6.0\n",
      "2022-08-17 12:58:36.493479: I tensorflow/core/grappler/optimizers/meta_optimizer.cc:1137] Optimization results for grappler item: graph_to_optimize\n",
      "  function_optimizer: function_optimizer did nothing. time = 0.007ms.\n",
      "  function_optimizer: function_optimizer did nothing. time = 0.002ms.\n",
      "\n",
      "Incomplete shape.\n",
      "Incomplete shape.\n"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "814/814 [==============================] - 6s 6ms/step - loss: 0.5292 - auc: 0.5565 - val_loss: 0.5162 - val_auc: 0.5476\n",
      "Epoch 2/100\n",
      "814/814 [==============================] - 4s 4ms/step - loss: 0.5097 - auc: 0.5867 - val_loss: 0.5146 - val_auc: 0.5594\n",
      "Epoch 3/100\n",
      "814/814 [==============================] - 4s 4ms/step - loss: 0.5095 - auc: 0.5880 - val_loss: 0.5100 - val_auc: 0.5730\n",
      "Epoch 4/100\n",
      "814/814 [==============================] - 4s 5ms/step - loss: 0.5098 - auc: 0.5868 - val_loss: 0.5155 - val_auc: 0.5652\n",
      "Epoch 5/100\n",
      "814/814 [==============================] - 4s 4ms/step - loss: 0.5097 - auc: 0.5870 - val_loss: 0.5172 - val_auc: 0.5435\n",
      "Epoch 6/100\n",
      "814/814 [==============================] - 3s 4ms/step - loss: 0.5098 - auc: 0.5852 - val_loss: 0.5117 - val_auc: 0.5720\n",
      "Epoch 7/100\n",
      "814/814 [==============================] - 3s 4ms/step - loss: 0.5097 - auc: 0.5863 - val_loss: 0.5152 - val_auc: 0.5605\n",
      "Epoch 8/100\n",
      "814/814 [==============================] - 4s 5ms/step - loss: 0.5096 - auc: 0.5861 - val_loss: 0.5131 - val_auc: 0.5681\n",
      "Train score: 0.5818842 / val score: 0.5718338 for split 43\n",
      "Epoch 1/100\n"
     ]
    },
    {
     "name": "stderr",
     "output_type": "stream",
     "text": [
      "2022-08-17 12:59:08.714181: I tensorflow/stream_executor/cuda/cuda_gpu_executor.cc:937] successful NUMA node read from SysFS had negative value (-1), but there must be at least one NUMA node, so returning NUMA node zero\n",
      "2022-08-17 12:59:08.715070: I tensorflow/core/grappler/devices.cc:66] Number of eligible GPUs (core count >= 8, compute capability >= 0.0): 1\n",
      "2022-08-17 12:59:08.715183: I tensorflow/core/grappler/clusters/single_machine.cc:357] Starting new session\n",
      "2022-08-17 12:59:08.715782: I tensorflow/stream_executor/cuda/cuda_gpu_executor.cc:937] successful NUMA node read from SysFS had negative value (-1), but there must be at least one NUMA node, so returning NUMA node zero\n",
      "2022-08-17 12:59:08.716728: I tensorflow/stream_executor/cuda/cuda_gpu_executor.cc:937] successful NUMA node read from SysFS had negative value (-1), but there must be at least one NUMA node, so returning NUMA node zero\n",
      "2022-08-17 12:59:08.717699: I tensorflow/stream_executor/cuda/cuda_gpu_executor.cc:937] successful NUMA node read from SysFS had negative value (-1), but there must be at least one NUMA node, so returning NUMA node zero\n",
      "2022-08-17 12:59:08.718712: I tensorflow/stream_executor/cuda/cuda_gpu_executor.cc:937] successful NUMA node read from SysFS had negative value (-1), but there must be at least one NUMA node, so returning NUMA node zero\n",
      "2022-08-17 12:59:08.719648: I tensorflow/stream_executor/cuda/cuda_gpu_executor.cc:937] successful NUMA node read from SysFS had negative value (-1), but there must be at least one NUMA node, so returning NUMA node zero\n",
      "2022-08-17 12:59:08.720396: I tensorflow/core/common_runtime/gpu/gpu_device.cc:1510] Created device /job:localhost/replica:0/task:0/device:GPU:0 with 15385 MB memory:  -> device: 0, name: Tesla P100-PCIE-16GB, pci bus id: 0000:00:04.0, compute capability: 6.0\n",
      "2022-08-17 12:59:08.721982: I tensorflow/core/grappler/optimizers/meta_optimizer.cc:1137] Optimization results for grappler item: graph_to_optimize\n",
      "  function_optimizer: function_optimizer did nothing. time = 0.007ms.\n",
      "  function_optimizer: function_optimizer did nothing. time = 0.002ms.\n",
      "\n",
      "Incomplete shape.\n",
      "Incomplete shape.\n"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "814/814 [==============================] - 5s 5ms/step - loss: 0.5278 - auc: 0.5609 - val_loss: 0.5048 - val_auc: 0.6017\n",
      "Epoch 2/100\n",
      "814/814 [==============================] - 4s 5ms/step - loss: 0.5101 - auc: 0.5864 - val_loss: 0.5063 - val_auc: 0.5981\n",
      "Epoch 3/100\n",
      "814/814 [==============================] - 3s 4ms/step - loss: 0.5102 - auc: 0.5839 - val_loss: 0.5091 - val_auc: 0.5890\n",
      "Epoch 4/100\n",
      "814/814 [==============================] - 4s 5ms/step - loss: 0.5098 - auc: 0.5856 - val_loss: 0.5080 - val_auc: 0.5903\n",
      "Epoch 5/100\n",
      "814/814 [==============================] - 4s 4ms/step - loss: 0.5101 - auc: 0.5859 - val_loss: 0.5065 - val_auc: 0.5991\n",
      "Epoch 6/100\n",
      "814/814 [==============================] - 3s 4ms/step - loss: 0.5100 - auc: 0.5838 - val_loss: 0.5030 - val_auc: 0.6157\n",
      "Epoch 7/100\n",
      "814/814 [==============================] - 3s 4ms/step - loss: 0.5097 - auc: 0.5868 - val_loss: 0.5046 - val_auc: 0.6045\n",
      "Epoch 8/100\n",
      "814/814 [==============================] - 4s 4ms/step - loss: 0.5099 - auc: 0.5857 - val_loss: 0.5066 - val_auc: 0.5991\n",
      "Epoch 9/100\n",
      "814/814 [==============================] - 3s 4ms/step - loss: 0.5098 - auc: 0.5855 - val_loss: 0.5042 - val_auc: 0.6120\n",
      "Epoch 10/100\n",
      "814/814 [==============================] - 3s 4ms/step - loss: 0.5098 - auc: 0.5863 - val_loss: 0.5044 - val_auc: 0.6123\n",
      "Epoch 11/100\n",
      "814/814 [==============================] - 5s 6ms/step - loss: 0.5095 - auc: 0.5884 - val_loss: 0.5073 - val_auc: 0.5956\n",
      "Train score: 0.5902918 / val score: 0.6158064 for split 44\n"
     ]
    },
    {
     "name": "stderr",
     "output_type": "stream",
     "text": [
      "2022-08-17 13:00:32.301524: I tensorflow/stream_executor/cuda/cuda_gpu_executor.cc:937] successful NUMA node read from SysFS had negative value (-1), but there must be at least one NUMA node, so returning NUMA node zero\n",
      "2022-08-17 13:00:32.302409: I tensorflow/core/grappler/devices.cc:66] Number of eligible GPUs (core count >= 8, compute capability >= 0.0): 1\n",
      "2022-08-17 13:00:32.302541: I tensorflow/core/grappler/clusters/single_machine.cc:357] Starting new session\n",
      "2022-08-17 13:00:32.303083: I tensorflow/stream_executor/cuda/cuda_gpu_executor.cc:937] successful NUMA node read from SysFS had negative value (-1), but there must be at least one NUMA node, so returning NUMA node zero\n",
      "2022-08-17 13:00:32.304035: I tensorflow/stream_executor/cuda/cuda_gpu_executor.cc:937] successful NUMA node read from SysFS had negative value (-1), but there must be at least one NUMA node, so returning NUMA node zero\n",
      "2022-08-17 13:00:32.304900: I tensorflow/stream_executor/cuda/cuda_gpu_executor.cc:937] successful NUMA node read from SysFS had negative value (-1), but there must be at least one NUMA node, so returning NUMA node zero\n",
      "2022-08-17 13:00:32.305879: I tensorflow/stream_executor/cuda/cuda_gpu_executor.cc:937] successful NUMA node read from SysFS had negative value (-1), but there must be at least one NUMA node, so returning NUMA node zero\n",
      "2022-08-17 13:00:32.306909: I tensorflow/stream_executor/cuda/cuda_gpu_executor.cc:937] successful NUMA node read from SysFS had negative value (-1), but there must be at least one NUMA node, so returning NUMA node zero\n",
      "2022-08-17 13:00:32.307705: I tensorflow/core/common_runtime/gpu/gpu_device.cc:1510] Created device /job:localhost/replica:0/task:0/device:GPU:0 with 15385 MB memory:  -> device: 0, name: Tesla P100-PCIE-16GB, pci bus id: 0000:00:04.0, compute capability: 6.0\n",
      "2022-08-17 13:00:32.309347: I tensorflow/core/grappler/optimizers/meta_optimizer.cc:1137] Optimization results for grappler item: graph_to_optimize\n",
      "  function_optimizer: function_optimizer did nothing. time = 0.007ms.\n",
      "  function_optimizer: function_optimizer did nothing. time = 0.002ms.\n",
      "\n",
      "Incomplete shape.\n",
      "Incomplete shape.\n"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "Epoch 1/100\n",
      "814/814 [==============================] - 6s 6ms/step - loss: 0.5305 - auc: 0.5535 - val_loss: 0.5108 - val_auc: 0.5775\n",
      "Epoch 2/100\n",
      "814/814 [==============================] - 3s 4ms/step - loss: 0.5095 - auc: 0.5878 - val_loss: 0.5096 - val_auc: 0.5964\n",
      "Epoch 3/100\n",
      "814/814 [==============================] - 4s 5ms/step - loss: 0.5099 - auc: 0.5839 - val_loss: 0.5075 - val_auc: 0.6052\n",
      "Epoch 4/100\n",
      "814/814 [==============================] - 3s 4ms/step - loss: 0.5095 - auc: 0.5868 - val_loss: 0.5098 - val_auc: 0.5920\n",
      "Epoch 5/100\n",
      "814/814 [==============================] - 3s 4ms/step - loss: 0.5097 - auc: 0.5863 - val_loss: 0.5056 - val_auc: 0.6156\n",
      "Epoch 6/100\n",
      "814/814 [==============================] - 3s 4ms/step - loss: 0.5097 - auc: 0.5858 - val_loss: 0.5049 - val_auc: 0.6200\n",
      "Epoch 7/100\n",
      "814/814 [==============================] - 4s 5ms/step - loss: 0.5099 - auc: 0.5867 - val_loss: 0.5055 - val_auc: 0.6101\n",
      "Epoch 8/100\n",
      "814/814 [==============================] - 3s 4ms/step - loss: 0.5096 - auc: 0.5867 - val_loss: 0.5062 - val_auc: 0.6069\n",
      "Epoch 9/100\n",
      "814/814 [==============================] - 3s 4ms/step - loss: 0.5098 - auc: 0.5862 - val_loss: 0.5050 - val_auc: 0.6110\n",
      "Epoch 10/100\n",
      "814/814 [==============================] - 4s 5ms/step - loss: 0.5098 - auc: 0.5862 - val_loss: 0.5087 - val_auc: 0.5981\n",
      "Epoch 11/100\n",
      "814/814 [==============================] - 4s 5ms/step - loss: 0.5099 - auc: 0.5863 - val_loss: 0.5072 - val_auc: 0.6143\n",
      "Train score: 0.5896023 / val score: 0.6206970 for split 45\n",
      "Epoch 1/100\n"
     ]
    },
    {
     "name": "stderr",
     "output_type": "stream",
     "text": [
      "2022-08-17 13:01:16.366917: I tensorflow/stream_executor/cuda/cuda_gpu_executor.cc:937] successful NUMA node read from SysFS had negative value (-1), but there must be at least one NUMA node, so returning NUMA node zero\n",
      "2022-08-17 13:01:16.367777: I tensorflow/core/grappler/devices.cc:66] Number of eligible GPUs (core count >= 8, compute capability >= 0.0): 1\n",
      "2022-08-17 13:01:16.367913: I tensorflow/core/grappler/clusters/single_machine.cc:357] Starting new session\n",
      "2022-08-17 13:01:16.368430: I tensorflow/stream_executor/cuda/cuda_gpu_executor.cc:937] successful NUMA node read from SysFS had negative value (-1), but there must be at least one NUMA node, so returning NUMA node zero\n",
      "2022-08-17 13:01:16.369304: I tensorflow/stream_executor/cuda/cuda_gpu_executor.cc:937] successful NUMA node read from SysFS had negative value (-1), but there must be at least one NUMA node, so returning NUMA node zero\n",
      "2022-08-17 13:01:16.370132: I tensorflow/stream_executor/cuda/cuda_gpu_executor.cc:937] successful NUMA node read from SysFS had negative value (-1), but there must be at least one NUMA node, so returning NUMA node zero\n",
      "2022-08-17 13:01:16.371048: I tensorflow/stream_executor/cuda/cuda_gpu_executor.cc:937] successful NUMA node read from SysFS had negative value (-1), but there must be at least one NUMA node, so returning NUMA node zero\n",
      "2022-08-17 13:01:16.371906: I tensorflow/stream_executor/cuda/cuda_gpu_executor.cc:937] successful NUMA node read from SysFS had negative value (-1), but there must be at least one NUMA node, so returning NUMA node zero\n",
      "2022-08-17 13:01:16.372658: I tensorflow/core/common_runtime/gpu/gpu_device.cc:1510] Created device /job:localhost/replica:0/task:0/device:GPU:0 with 15385 MB memory:  -> device: 0, name: Tesla P100-PCIE-16GB, pci bus id: 0000:00:04.0, compute capability: 6.0\n",
      "2022-08-17 13:01:16.374102: I tensorflow/core/grappler/optimizers/meta_optimizer.cc:1137] Optimization results for grappler item: graph_to_optimize\n",
      "  function_optimizer: function_optimizer did nothing. time = 0.006ms.\n",
      "  function_optimizer: function_optimizer did nothing. time = 0.001ms.\n",
      "\n",
      "Incomplete shape.\n",
      "Incomplete shape.\n"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "814/814 [==============================] - 5s 5ms/step - loss: 0.5277 - auc: 0.5553 - val_loss: 0.5060 - val_auc: 0.6038\n",
      "Epoch 2/100\n",
      "814/814 [==============================] - 3s 4ms/step - loss: 0.5098 - auc: 0.5867 - val_loss: 0.5045 - val_auc: 0.6114\n",
      "Epoch 3/100\n",
      "814/814 [==============================] - 3s 4ms/step - loss: 0.5099 - auc: 0.5863 - val_loss: 0.5054 - val_auc: 0.6104\n",
      "Epoch 4/100\n",
      "814/814 [==============================] - 4s 6ms/step - loss: 0.5097 - auc: 0.5870 - val_loss: 0.5060 - val_auc: 0.6026\n",
      "Epoch 5/100\n",
      "814/814 [==============================] - 3s 4ms/step - loss: 0.5099 - auc: 0.5857 - val_loss: 0.5050 - val_auc: 0.6116\n",
      "Epoch 6/100\n",
      "814/814 [==============================] - 3s 4ms/step - loss: 0.5098 - auc: 0.5867 - val_loss: 0.5040 - val_auc: 0.6153\n",
      "Epoch 7/100\n",
      "814/814 [==============================] - 4s 5ms/step - loss: 0.5098 - auc: 0.5874 - val_loss: 0.5048 - val_auc: 0.6096\n",
      "Epoch 8/100\n",
      "814/814 [==============================] - 5s 6ms/step - loss: 0.5097 - auc: 0.5864 - val_loss: 0.5070 - val_auc: 0.6000\n",
      "Epoch 9/100\n",
      "814/814 [==============================] - 4s 5ms/step - loss: 0.5099 - auc: 0.5857 - val_loss: 0.5021 - val_auc: 0.6240\n",
      "Epoch 10/100\n",
      "814/814 [==============================] - 3s 4ms/step - loss: 0.5100 - auc: 0.5853 - val_loss: 0.5031 - val_auc: 0.6171\n",
      "Epoch 11/100\n",
      "814/814 [==============================] - 3s 4ms/step - loss: 0.5096 - auc: 0.5860 - val_loss: 0.5009 - val_auc: 0.6269\n",
      "Epoch 12/100\n",
      "814/814 [==============================] - 4s 4ms/step - loss: 0.5100 - auc: 0.5867 - val_loss: 0.5038 - val_auc: 0.6159\n",
      "Epoch 13/100\n",
      "814/814 [==============================] - 4s 5ms/step - loss: 0.5101 - auc: 0.5844 - val_loss: 0.5034 - val_auc: 0.6171\n",
      "Epoch 14/100\n",
      "814/814 [==============================] - 3s 4ms/step - loss: 0.5098 - auc: 0.5869 - val_loss: 0.5054 - val_auc: 0.6040\n",
      "Epoch 15/100\n",
      "814/814 [==============================] - 3s 4ms/step - loss: 0.5097 - auc: 0.5883 - val_loss: 0.5032 - val_auc: 0.6184\n",
      "Epoch 16/100\n",
      "814/814 [==============================] - 4s 4ms/step - loss: 0.5099 - auc: 0.5847 - val_loss: 0.5038 - val_auc: 0.6146\n",
      "Train score: 0.5885385 / val score: 0.6271118 for split 46\n",
      "Epoch 1/100\n"
     ]
    },
    {
     "name": "stderr",
     "output_type": "stream",
     "text": [
      "2022-08-17 13:02:40.437225: I tensorflow/stream_executor/cuda/cuda_gpu_executor.cc:937] successful NUMA node read from SysFS had negative value (-1), but there must be at least one NUMA node, so returning NUMA node zero\n",
      "2022-08-17 13:02:40.438168: I tensorflow/core/grappler/devices.cc:66] Number of eligible GPUs (core count >= 8, compute capability >= 0.0): 1\n",
      "2022-08-17 13:02:40.438306: I tensorflow/core/grappler/clusters/single_machine.cc:357] Starting new session\n",
      "2022-08-17 13:02:40.438840: I tensorflow/stream_executor/cuda/cuda_gpu_executor.cc:937] successful NUMA node read from SysFS had negative value (-1), but there must be at least one NUMA node, so returning NUMA node zero\n",
      "2022-08-17 13:02:40.439779: I tensorflow/stream_executor/cuda/cuda_gpu_executor.cc:937] successful NUMA node read from SysFS had negative value (-1), but there must be at least one NUMA node, so returning NUMA node zero\n",
      "2022-08-17 13:02:40.440718: I tensorflow/stream_executor/cuda/cuda_gpu_executor.cc:937] successful NUMA node read from SysFS had negative value (-1), but there must be at least one NUMA node, so returning NUMA node zero\n",
      "2022-08-17 13:02:40.441756: I tensorflow/stream_executor/cuda/cuda_gpu_executor.cc:937] successful NUMA node read from SysFS had negative value (-1), but there must be at least one NUMA node, so returning NUMA node zero\n",
      "2022-08-17 13:02:40.442716: I tensorflow/stream_executor/cuda/cuda_gpu_executor.cc:937] successful NUMA node read from SysFS had negative value (-1), but there must be at least one NUMA node, so returning NUMA node zero\n",
      "2022-08-17 13:02:40.443540: I tensorflow/core/common_runtime/gpu/gpu_device.cc:1510] Created device /job:localhost/replica:0/task:0/device:GPU:0 with 15385 MB memory:  -> device: 0, name: Tesla P100-PCIE-16GB, pci bus id: 0000:00:04.0, compute capability: 6.0\n",
      "2022-08-17 13:02:40.445148: I tensorflow/core/grappler/optimizers/meta_optimizer.cc:1137] Optimization results for grappler item: graph_to_optimize\n",
      "  function_optimizer: function_optimizer did nothing. time = 0.008ms.\n",
      "  function_optimizer: function_optimizer did nothing. time = 0.001ms.\n",
      "\n",
      "Incomplete shape.\n",
      "Incomplete shape.\n"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "814/814 [==============================] - 6s 7ms/step - loss: 0.5268 - auc: 0.5626 - val_loss: 0.5127 - val_auc: 0.5560\n",
      "Epoch 2/100\n",
      "814/814 [==============================] - 4s 5ms/step - loss: 0.5097 - auc: 0.5864 - val_loss: 0.5118 - val_auc: 0.5664\n",
      "Epoch 3/100\n",
      "814/814 [==============================] - 3s 4ms/step - loss: 0.5100 - auc: 0.5852 - val_loss: 0.5123 - val_auc: 0.5662\n",
      "Epoch 4/100\n",
      "814/814 [==============================] - 4s 5ms/step - loss: 0.5099 - auc: 0.5863 - val_loss: 0.5126 - val_auc: 0.5685\n",
      "Epoch 5/100\n",
      "814/814 [==============================] - 3s 4ms/step - loss: 0.5095 - auc: 0.5872 - val_loss: 0.5127 - val_auc: 0.5694\n",
      "Epoch 6/100\n",
      "814/814 [==============================] - 3s 4ms/step - loss: 0.5098 - auc: 0.5858 - val_loss: 0.5137 - val_auc: 0.5579\n",
      "Epoch 7/100\n",
      "814/814 [==============================] - 4s 4ms/step - loss: 0.5097 - auc: 0.5872 - val_loss: 0.5131 - val_auc: 0.5561\n",
      "Epoch 8/100\n",
      "814/814 [==============================] - 3s 4ms/step - loss: 0.5096 - auc: 0.5882 - val_loss: 0.5138 - val_auc: 0.5505\n",
      "Epoch 9/100\n",
      "814/814 [==============================] - 3s 4ms/step - loss: 0.5097 - auc: 0.5867 - val_loss: 0.5115 - val_auc: 0.5662\n",
      "Epoch 10/100\n",
      "814/814 [==============================] - 4s 5ms/step - loss: 0.5098 - auc: 0.5878 - val_loss: 0.5152 - val_auc: 0.5501\n",
      "Train score: 0.5902956 / val score: 0.5693992 for split 47\n",
      "Epoch 1/100\n"
     ]
    },
    {
     "name": "stderr",
     "output_type": "stream",
     "text": [
      "2022-08-17 13:03:23.910135: I tensorflow/stream_executor/cuda/cuda_gpu_executor.cc:937] successful NUMA node read from SysFS had negative value (-1), but there must be at least one NUMA node, so returning NUMA node zero\n",
      "2022-08-17 13:03:23.911069: I tensorflow/core/grappler/devices.cc:66] Number of eligible GPUs (core count >= 8, compute capability >= 0.0): 1\n",
      "2022-08-17 13:03:23.911222: I tensorflow/core/grappler/clusters/single_machine.cc:357] Starting new session\n",
      "2022-08-17 13:03:23.911748: I tensorflow/stream_executor/cuda/cuda_gpu_executor.cc:937] successful NUMA node read from SysFS had negative value (-1), but there must be at least one NUMA node, so returning NUMA node zero\n",
      "2022-08-17 13:03:23.912704: I tensorflow/stream_executor/cuda/cuda_gpu_executor.cc:937] successful NUMA node read from SysFS had negative value (-1), but there must be at least one NUMA node, so returning NUMA node zero\n",
      "2022-08-17 13:03:23.913653: I tensorflow/stream_executor/cuda/cuda_gpu_executor.cc:937] successful NUMA node read from SysFS had negative value (-1), but there must be at least one NUMA node, so returning NUMA node zero\n",
      "2022-08-17 13:03:23.914640: I tensorflow/stream_executor/cuda/cuda_gpu_executor.cc:937] successful NUMA node read from SysFS had negative value (-1), but there must be at least one NUMA node, so returning NUMA node zero\n",
      "2022-08-17 13:03:23.915607: I tensorflow/stream_executor/cuda/cuda_gpu_executor.cc:937] successful NUMA node read from SysFS had negative value (-1), but there must be at least one NUMA node, so returning NUMA node zero\n",
      "2022-08-17 13:03:23.916380: I tensorflow/core/common_runtime/gpu/gpu_device.cc:1510] Created device /job:localhost/replica:0/task:0/device:GPU:0 with 15385 MB memory:  -> device: 0, name: Tesla P100-PCIE-16GB, pci bus id: 0000:00:04.0, compute capability: 6.0\n",
      "2022-08-17 13:03:23.917889: I tensorflow/core/grappler/optimizers/meta_optimizer.cc:1137] Optimization results for grappler item: graph_to_optimize\n",
      "  function_optimizer: function_optimizer did nothing. time = 0.006ms.\n",
      "  function_optimizer: function_optimizer did nothing. time = 0.001ms.\n",
      "\n",
      "Incomplete shape.\n",
      "Incomplete shape.\n"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "814/814 [==============================] - 4s 4ms/step - loss: 0.5279 - auc: 0.5621 - val_loss: 0.5067 - val_auc: 0.6114\n",
      "Epoch 2/100\n",
      "814/814 [==============================] - 4s 5ms/step - loss: 0.5100 - auc: 0.5858 - val_loss: 0.5067 - val_auc: 0.6156\n",
      "Epoch 3/100\n",
      "814/814 [==============================] - 3s 4ms/step - loss: 0.5099 - auc: 0.5860 - val_loss: 0.5080 - val_auc: 0.5979\n",
      "Epoch 4/100\n",
      "814/814 [==============================] - 4s 5ms/step - loss: 0.5100 - auc: 0.5848 - val_loss: 0.5089 - val_auc: 0.6118\n",
      "Epoch 5/100\n",
      "814/814 [==============================] - 4s 5ms/step - loss: 0.5101 - auc: 0.5836 - val_loss: 0.5058 - val_auc: 0.6091\n",
      "Epoch 6/100\n",
      "814/814 [==============================] - 3s 4ms/step - loss: 0.5100 - auc: 0.5846 - val_loss: 0.5044 - val_auc: 0.6246\n",
      "Epoch 7/100\n",
      "814/814 [==============================] - 3s 4ms/step - loss: 0.5097 - auc: 0.5852 - val_loss: 0.5068 - val_auc: 0.6000\n",
      "Epoch 8/100\n",
      "814/814 [==============================] - 5s 6ms/step - loss: 0.5101 - auc: 0.5846 - val_loss: 0.5086 - val_auc: 0.6136\n",
      "Epoch 9/100\n",
      "814/814 [==============================] - 4s 5ms/step - loss: 0.5098 - auc: 0.5842 - val_loss: 0.5034 - val_auc: 0.6074\n",
      "Epoch 10/100\n",
      "814/814 [==============================] - 3s 4ms/step - loss: 0.5098 - auc: 0.5856 - val_loss: 0.5076 - val_auc: 0.6076\n",
      "Epoch 11/100\n",
      "814/814 [==============================] - 4s 5ms/step - loss: 0.5098 - auc: 0.5857 - val_loss: 0.5072 - val_auc: 0.6035\n",
      "Train score: 0.5911198 / val score: 0.6257780 for split 48\n",
      "Epoch 1/100\n"
     ]
    },
    {
     "name": "stderr",
     "output_type": "stream",
     "text": [
      "2022-08-17 13:04:48.016262: I tensorflow/stream_executor/cuda/cuda_gpu_executor.cc:937] successful NUMA node read from SysFS had negative value (-1), but there must be at least one NUMA node, so returning NUMA node zero\n",
      "2022-08-17 13:04:48.017212: I tensorflow/core/grappler/devices.cc:66] Number of eligible GPUs (core count >= 8, compute capability >= 0.0): 1\n",
      "2022-08-17 13:04:48.017363: I tensorflow/core/grappler/clusters/single_machine.cc:357] Starting new session\n",
      "2022-08-17 13:04:48.017883: I tensorflow/stream_executor/cuda/cuda_gpu_executor.cc:937] successful NUMA node read from SysFS had negative value (-1), but there must be at least one NUMA node, so returning NUMA node zero\n",
      "2022-08-17 13:04:48.018913: I tensorflow/stream_executor/cuda/cuda_gpu_executor.cc:937] successful NUMA node read from SysFS had negative value (-1), but there must be at least one NUMA node, so returning NUMA node zero\n",
      "2022-08-17 13:04:48.019775: I tensorflow/stream_executor/cuda/cuda_gpu_executor.cc:937] successful NUMA node read from SysFS had negative value (-1), but there must be at least one NUMA node, so returning NUMA node zero\n",
      "2022-08-17 13:04:48.020726: I tensorflow/stream_executor/cuda/cuda_gpu_executor.cc:937] successful NUMA node read from SysFS had negative value (-1), but there must be at least one NUMA node, so returning NUMA node zero\n",
      "2022-08-17 13:04:48.021621: I tensorflow/stream_executor/cuda/cuda_gpu_executor.cc:937] successful NUMA node read from SysFS had negative value (-1), but there must be at least one NUMA node, so returning NUMA node zero\n",
      "2022-08-17 13:04:48.022369: I tensorflow/core/common_runtime/gpu/gpu_device.cc:1510] Created device /job:localhost/replica:0/task:0/device:GPU:0 with 15385 MB memory:  -> device: 0, name: Tesla P100-PCIE-16GB, pci bus id: 0000:00:04.0, compute capability: 6.0\n",
      "2022-08-17 13:04:48.023897: I tensorflow/core/grappler/optimizers/meta_optimizer.cc:1137] Optimization results for grappler item: graph_to_optimize\n",
      "  function_optimizer: function_optimizer did nothing. time = 0.006ms.\n",
      "  function_optimizer: function_optimizer did nothing. time = 0.001ms.\n",
      "\n",
      "Incomplete shape.\n",
      "Incomplete shape.\n"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "814/814 [==============================] - 7s 7ms/step - loss: 0.5264 - auc: 0.5626 - val_loss: 0.5107 - val_auc: 0.5937\n",
      "Epoch 2/100\n",
      "814/814 [==============================] - 4s 4ms/step - loss: 0.5100 - auc: 0.5859 - val_loss: 0.5108 - val_auc: 0.6049\n",
      "Epoch 3/100\n",
      "814/814 [==============================] - 3s 4ms/step - loss: 0.5098 - auc: 0.5856 - val_loss: 0.5107 - val_auc: 0.5958\n",
      "Epoch 4/100\n",
      "814/814 [==============================] - 3s 4ms/step - loss: 0.5100 - auc: 0.5852 - val_loss: 0.5099 - val_auc: 0.6024\n",
      "Epoch 5/100\n",
      "814/814 [==============================] - 4s 4ms/step - loss: 0.5097 - auc: 0.5865 - val_loss: 0.5100 - val_auc: 0.6059\n",
      "Epoch 6/100\n",
      "814/814 [==============================] - 4s 4ms/step - loss: 0.5097 - auc: 0.5848 - val_loss: 0.5094 - val_auc: 0.5984\n",
      "Epoch 7/100\n",
      "814/814 [==============================] - 3s 4ms/step - loss: 0.5095 - auc: 0.5876 - val_loss: 0.5090 - val_auc: 0.6005\n",
      "Epoch 8/100\n",
      "814/814 [==============================] - 3s 4ms/step - loss: 0.5098 - auc: 0.5863 - val_loss: 0.5101 - val_auc: 0.6105\n",
      "Epoch 9/100\n",
      "814/814 [==============================] - 4s 5ms/step - loss: 0.5096 - auc: 0.5877 - val_loss: 0.5085 - val_auc: 0.6052\n",
      "Epoch 10/100\n",
      "814/814 [==============================] - 5s 6ms/step - loss: 0.5097 - auc: 0.5859 - val_loss: 0.5104 - val_auc: 0.5877\n",
      "Epoch 11/100\n",
      "814/814 [==============================] - 4s 5ms/step - loss: 0.5096 - auc: 0.5866 - val_loss: 0.5077 - val_auc: 0.6165\n",
      "Epoch 12/100\n",
      "814/814 [==============================] - 3s 4ms/step - loss: 0.5097 - auc: 0.5861 - val_loss: 0.5087 - val_auc: 0.6075\n",
      "Epoch 13/100\n",
      "814/814 [==============================] - 3s 4ms/step - loss: 0.5102 - auc: 0.5844 - val_loss: 0.5097 - val_auc: 0.6102\n",
      "Epoch 14/100\n",
      "814/814 [==============================] - 4s 5ms/step - loss: 0.5095 - auc: 0.5874 - val_loss: 0.5110 - val_auc: 0.5976\n",
      "Epoch 15/100\n",
      "814/814 [==============================] - 3s 4ms/step - loss: 0.5097 - auc: 0.5876 - val_loss: 0.5104 - val_auc: 0.5937\n",
      "Epoch 16/100\n",
      "814/814 [==============================] - 3s 4ms/step - loss: 0.5097 - auc: 0.5855 - val_loss: 0.5117 - val_auc: 0.5912\n",
      "Train score: 0.5912491 / val score: 0.6160816 for split 49\n",
      "Train avg score: 0.5887984 / val avg score: 0.6023285\n",
      "OOFs overall score: 0.6005329\n"
     ]
    }
   ],
   "source": [
    "if not optimizing:\n",
    "    models,scalers=crossvalidation(df_train, df_test, features, params_LR)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 18,
   "id": "88cef5fc",
   "metadata": {
    "execution": {
     "iopub.execute_input": "2022-08-17T13:05:56.230830Z",
     "iopub.status.busy": "2022-08-17T13:05:56.229527Z",
     "iopub.status.idle": "2022-08-17T13:06:31.164439Z",
     "shell.execute_reply": "2022-08-17T13:06:31.163151Z"
    },
    "papermill": {
     "duration": 37.896942,
     "end_time": "2022-08-17T13:06:31.167176",
     "exception": false,
     "start_time": "2022-08-17T13:05:53.270234",
     "status": "completed"
    },
    "tags": []
   },
   "outputs": [],
   "source": [
    "if not optimizing:\n",
    "    inference(df_train, df_test, features, params_LR,models,scalers)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 19,
   "id": "7f6da220",
   "metadata": {
    "execution": {
     "iopub.execute_input": "2022-08-17T13:06:35.625111Z",
     "iopub.status.busy": "2022-08-17T13:06:35.623789Z",
     "iopub.status.idle": "2022-08-17T13:06:35.666554Z",
     "shell.execute_reply": "2022-08-17T13:06:35.665318Z"
    },
    "papermill": {
     "duration": 2.244794,
     "end_time": "2022-08-17T13:06:35.669254",
     "exception": false,
     "start_time": "2022-08-17T13:06:33.424460",
     "status": "completed"
    },
    "tags": []
   },
   "outputs": [
    {
     "data": {
      "text/html": [
       "<div>\n",
       "<style scoped>\n",
       "    .dataframe tbody tr th:only-of-type {\n",
       "        vertical-align: middle;\n",
       "    }\n",
       "\n",
       "    .dataframe tbody tr th {\n",
       "        vertical-align: top;\n",
       "    }\n",
       "\n",
       "    .dataframe thead th {\n",
       "        text-align: right;\n",
       "    }\n",
       "</style>\n",
       "<table border=\"1\" class=\"dataframe\">\n",
       "  <thead>\n",
       "    <tr style=\"text-align: right;\">\n",
       "      <th></th>\n",
       "      <th>loading</th>\n",
       "      <th>attribute_0</th>\n",
       "      <th>attribute_1</th>\n",
       "      <th>attribute_2</th>\n",
       "      <th>attribute_3</th>\n",
       "      <th>measurement_0</th>\n",
       "      <th>measurement_1</th>\n",
       "      <th>measurement_2</th>\n",
       "      <th>measurement_3</th>\n",
       "      <th>measurement_4</th>\n",
       "      <th>...</th>\n",
       "      <th>measurement_17</th>\n",
       "      <th>failure</th>\n",
       "      <th>fold</th>\n",
       "      <th>m_3_missing</th>\n",
       "      <th>m_5_missing</th>\n",
       "      <th>attribute_2*3</th>\n",
       "      <th>meas_gr1_avg</th>\n",
       "      <th>meas_gr1_std</th>\n",
       "      <th>meas_gr2_avg</th>\n",
       "      <th>meas17/meas_gr2_avg</th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>0</th>\n",
       "      <td>80.10</td>\n",
       "      <td>0.017894</td>\n",
       "      <td>0.037537</td>\n",
       "      <td>9</td>\n",
       "      <td>5</td>\n",
       "      <td>7</td>\n",
       "      <td>8</td>\n",
       "      <td>4</td>\n",
       "      <td>18.040</td>\n",
       "      <td>12.518</td>\n",
       "      <td>...</td>\n",
       "      <td>764.100</td>\n",
       "      <td>0</td>\n",
       "      <td>20</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>45</td>\n",
       "      <td>14.6809</td>\n",
       "      <td>2.127150</td>\n",
       "      <td>16.73350</td>\n",
       "      <td>45.662892</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1</th>\n",
       "      <td>84.89</td>\n",
       "      <td>0.017894</td>\n",
       "      <td>0.037537</td>\n",
       "      <td>9</td>\n",
       "      <td>5</td>\n",
       "      <td>14</td>\n",
       "      <td>3</td>\n",
       "      <td>3</td>\n",
       "      <td>18.213</td>\n",
       "      <td>11.540</td>\n",
       "      <td>...</td>\n",
       "      <td>682.057</td>\n",
       "      <td>0</td>\n",
       "      <td>16</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>45</td>\n",
       "      <td>15.0001</td>\n",
       "      <td>2.398674</td>\n",
       "      <td>16.56175</td>\n",
       "      <td>41.182665</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2</th>\n",
       "      <td>82.43</td>\n",
       "      <td>0.017894</td>\n",
       "      <td>0.037537</td>\n",
       "      <td>9</td>\n",
       "      <td>5</td>\n",
       "      <td>12</td>\n",
       "      <td>1</td>\n",
       "      <td>5</td>\n",
       "      <td>18.057</td>\n",
       "      <td>11.652</td>\n",
       "      <td>...</td>\n",
       "      <td>663.376</td>\n",
       "      <td>0</td>\n",
       "      <td>10</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>45</td>\n",
       "      <td>15.8247</td>\n",
       "      <td>2.503762</td>\n",
       "      <td>16.49600</td>\n",
       "      <td>40.214355</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>3</th>\n",
       "      <td>101.07</td>\n",
       "      <td>0.017894</td>\n",
       "      <td>0.037537</td>\n",
       "      <td>9</td>\n",
       "      <td>5</td>\n",
       "      <td>13</td>\n",
       "      <td>2</td>\n",
       "      <td>6</td>\n",
       "      <td>17.295</td>\n",
       "      <td>11.188</td>\n",
       "      <td>...</td>\n",
       "      <td>826.282</td>\n",
       "      <td>0</td>\n",
       "      <td>48</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>45</td>\n",
       "      <td>14.9835</td>\n",
       "      <td>2.657732</td>\n",
       "      <td>17.13950</td>\n",
       "      <td>48.209224</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>4</th>\n",
       "      <td>188.06</td>\n",
       "      <td>0.017894</td>\n",
       "      <td>0.037537</td>\n",
       "      <td>9</td>\n",
       "      <td>5</td>\n",
       "      <td>9</td>\n",
       "      <td>2</td>\n",
       "      <td>8</td>\n",
       "      <td>19.346</td>\n",
       "      <td>12.950</td>\n",
       "      <td>...</td>\n",
       "      <td>579.885</td>\n",
       "      <td>0</td>\n",
       "      <td>7</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>45</td>\n",
       "      <td>15.0582</td>\n",
       "      <td>3.031408</td>\n",
       "      <td>15.53375</td>\n",
       "      <td>37.330651</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>...</th>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>26565</th>\n",
       "      <td>158.95</td>\n",
       "      <td>0.017894</td>\n",
       "      <td>-0.033831</td>\n",
       "      <td>6</td>\n",
       "      <td>9</td>\n",
       "      <td>6</td>\n",
       "      <td>16</td>\n",
       "      <td>4</td>\n",
       "      <td>16.301</td>\n",
       "      <td>13.259</td>\n",
       "      <td>...</td>\n",
       "      <td>729.131</td>\n",
       "      <td>0</td>\n",
       "      <td>17</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>54</td>\n",
       "      <td>14.6996</td>\n",
       "      <td>2.904494</td>\n",
       "      <td>15.94800</td>\n",
       "      <td>45.719275</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>26566</th>\n",
       "      <td>146.02</td>\n",
       "      <td>0.017894</td>\n",
       "      <td>-0.033831</td>\n",
       "      <td>6</td>\n",
       "      <td>9</td>\n",
       "      <td>10</td>\n",
       "      <td>12</td>\n",
       "      <td>8</td>\n",
       "      <td>17.543</td>\n",
       "      <td>12.351</td>\n",
       "      <td>...</td>\n",
       "      <td>853.924</td>\n",
       "      <td>0</td>\n",
       "      <td>37</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>54</td>\n",
       "      <td>14.4502</td>\n",
       "      <td>2.920514</td>\n",
       "      <td>16.94100</td>\n",
       "      <td>50.405761</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>26567</th>\n",
       "      <td>115.62</td>\n",
       "      <td>0.017894</td>\n",
       "      <td>-0.033831</td>\n",
       "      <td>6</td>\n",
       "      <td>9</td>\n",
       "      <td>1</td>\n",
       "      <td>10</td>\n",
       "      <td>1</td>\n",
       "      <td>15.670</td>\n",
       "      <td>11.535</td>\n",
       "      <td>...</td>\n",
       "      <td>750.364</td>\n",
       "      <td>0</td>\n",
       "      <td>49</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>54</td>\n",
       "      <td>14.2516</td>\n",
       "      <td>2.680250</td>\n",
       "      <td>16.51800</td>\n",
       "      <td>45.427049</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>26568</th>\n",
       "      <td>106.38</td>\n",
       "      <td>0.017894</td>\n",
       "      <td>-0.033831</td>\n",
       "      <td>6</td>\n",
       "      <td>9</td>\n",
       "      <td>2</td>\n",
       "      <td>9</td>\n",
       "      <td>4</td>\n",
       "      <td>18.059</td>\n",
       "      <td>12.853</td>\n",
       "      <td>...</td>\n",
       "      <td>730.156</td>\n",
       "      <td>0</td>\n",
       "      <td>35</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>54</td>\n",
       "      <td>15.0357</td>\n",
       "      <td>2.178606</td>\n",
       "      <td>16.52250</td>\n",
       "      <td>44.191617</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>26569</th>\n",
       "      <td>131.20</td>\n",
       "      <td>0.017894</td>\n",
       "      <td>-0.033831</td>\n",
       "      <td>6</td>\n",
       "      <td>9</td>\n",
       "      <td>6</td>\n",
       "      <td>19</td>\n",
       "      <td>1</td>\n",
       "      <td>18.034</td>\n",
       "      <td>11.431</td>\n",
       "      <td>...</td>\n",
       "      <td>602.354</td>\n",
       "      <td>0</td>\n",
       "      <td>45</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>54</td>\n",
       "      <td>15.0046</td>\n",
       "      <td>3.062014</td>\n",
       "      <td>16.37275</td>\n",
       "      <td>36.790032</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "<p>26570 rows × 32 columns</p>\n",
       "</div>"
      ],
      "text/plain": [
       "       loading  attribute_0  attribute_1  attribute_2  attribute_3  \\\n",
       "0        80.10     0.017894     0.037537            9            5   \n",
       "1        84.89     0.017894     0.037537            9            5   \n",
       "2        82.43     0.017894     0.037537            9            5   \n",
       "3       101.07     0.017894     0.037537            9            5   \n",
       "4       188.06     0.017894     0.037537            9            5   \n",
       "...        ...          ...          ...          ...          ...   \n",
       "26565   158.95     0.017894    -0.033831            6            9   \n",
       "26566   146.02     0.017894    -0.033831            6            9   \n",
       "26567   115.62     0.017894    -0.033831            6            9   \n",
       "26568   106.38     0.017894    -0.033831            6            9   \n",
       "26569   131.20     0.017894    -0.033831            6            9   \n",
       "\n",
       "       measurement_0  measurement_1  measurement_2  measurement_3  \\\n",
       "0                  7              8              4         18.040   \n",
       "1                 14              3              3         18.213   \n",
       "2                 12              1              5         18.057   \n",
       "3                 13              2              6         17.295   \n",
       "4                  9              2              8         19.346   \n",
       "...              ...            ...            ...            ...   \n",
       "26565              6             16              4         16.301   \n",
       "26566             10             12              8         17.543   \n",
       "26567              1             10              1         15.670   \n",
       "26568              2              9              4         18.059   \n",
       "26569              6             19              1         18.034   \n",
       "\n",
       "       measurement_4  ...  measurement_17  failure  fold  m_3_missing  \\\n",
       "0             12.518  ...         764.100        0    20            0   \n",
       "1             11.540  ...         682.057        0    16            0   \n",
       "2             11.652  ...         663.376        0    10            0   \n",
       "3             11.188  ...         826.282        0    48            0   \n",
       "4             12.950  ...         579.885        0     7            0   \n",
       "...              ...  ...             ...      ...   ...          ...   \n",
       "26565         13.259  ...         729.131        0    17            0   \n",
       "26566         12.351  ...         853.924        0    37            0   \n",
       "26567         11.535  ...         750.364        0    49            0   \n",
       "26568         12.853  ...         730.156        0    35            0   \n",
       "26569         11.431  ...         602.354        0    45            0   \n",
       "\n",
       "       m_5_missing  attribute_2*3  meas_gr1_avg  meas_gr1_std  meas_gr2_avg  \\\n",
       "0                0             45       14.6809      2.127150      16.73350   \n",
       "1                0             45       15.0001      2.398674      16.56175   \n",
       "2                0             45       15.8247      2.503762      16.49600   \n",
       "3                0             45       14.9835      2.657732      17.13950   \n",
       "4                0             45       15.0582      3.031408      15.53375   \n",
       "...            ...            ...           ...           ...           ...   \n",
       "26565            0             54       14.6996      2.904494      15.94800   \n",
       "26566            0             54       14.4502      2.920514      16.94100   \n",
       "26567            0             54       14.2516      2.680250      16.51800   \n",
       "26568            0             54       15.0357      2.178606      16.52250   \n",
       "26569            0             54       15.0046      3.062014      16.37275   \n",
       "\n",
       "       meas17/meas_gr2_avg  \n",
       "0                45.662892  \n",
       "1                41.182665  \n",
       "2                40.214355  \n",
       "3                48.209224  \n",
       "4                37.330651  \n",
       "...                    ...  \n",
       "26565            45.719275  \n",
       "26566            50.405761  \n",
       "26567            45.427049  \n",
       "26568            44.191617  \n",
       "26569            36.790032  \n",
       "\n",
       "[26570 rows x 32 columns]"
      ]
     },
     "execution_count": 19,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "df_train"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "id": "b60bb5c4",
   "metadata": {
    "papermill": {
     "duration": 2.183399,
     "end_time": "2022-08-17T13:06:40.427518",
     "exception": false,
     "start_time": "2022-08-17T13:06:38.244119",
     "status": "completed"
    },
    "tags": []
   },
   "outputs": [],
   "source": []
  }
 ],
 "metadata": {
  "kernelspec": {
   "display_name": "Python 3",
   "language": "python",
   "name": "python3"
  },
  "language_info": {
   "codemirror_mode": {
    "name": "ipython",
    "version": 3
   },
   "file_extension": ".py",
   "mimetype": "text/x-python",
   "name": "python",
   "nbconvert_exporter": "python",
   "pygments_lexer": "ipython3",
   "version": "3.7.12"
  },
  "papermill": {
   "default_parameters": {},
   "duration": 3010.99584,
   "end_time": "2022-08-17T13:06:45.730746",
   "environment_variables": {},
   "exception": null,
   "input_path": "__notebook__.ipynb",
   "output_path": "__notebook__.ipynb",
   "parameters": {},
   "start_time": "2022-08-17T12:16:34.734906",
   "version": "2.3.4"
  },
  "widgets": {
   "application/vnd.jupyter.widget-state+json": {
    "state": {
     "00e0d40af2424ce18d8b0d8f94987bb4": {
      "model_module": "@jupyter-widgets/controls",
      "model_module_version": "1.5.0",
      "model_name": "FloatProgressModel",
      "state": {
       "_dom_classes": [],
       "_model_module": "@jupyter-widgets/controls",
       "_model_module_version": "1.5.0",
       "_model_name": "FloatProgressModel",
       "_view_count": null,
       "_view_module": "@jupyter-widgets/controls",
       "_view_module_version": "1.5.0",
       "_view_name": "ProgressView",
       "bar_style": "",
       "description": "",
       "description_tooltip": null,
       "layout": "IPY_MODEL_fb83653469a14097abb01c6f24029b40",
       "max": 1.0,
       "min": 0.0,
       "orientation": "horizontal",
       "style": "IPY_MODEL_2a61ffc35e2944378ee324b54b9dc0a1",
       "value": 0.0
      }
     },
     "11717abeaab64af297dd0268ded0d856": {
      "model_module": "@jupyter-widgets/controls",
      "model_module_version": "1.5.0",
      "model_name": "VBoxModel",
      "state": {
       "_dom_classes": [],
       "_model_module": "@jupyter-widgets/controls",
       "_model_module_version": "1.5.0",
       "_model_name": "VBoxModel",
       "_view_count": null,
       "_view_module": "@jupyter-widgets/controls",
       "_view_module_version": "1.5.0",
       "_view_name": "VBoxView",
       "box_style": "",
       "children": [
        "IPY_MODEL_19923d795f8242f48d3a20a62f9281ba",
        "IPY_MODEL_00e0d40af2424ce18d8b0d8f94987bb4"
       ],
       "layout": "IPY_MODEL_346ce322e7a5428c86d8ed4859590489"
      }
     },
     "19923d795f8242f48d3a20a62f9281ba": {
      "model_module": "@jupyter-widgets/controls",
      "model_module_version": "1.5.0",
      "model_name": "LabelModel",
      "state": {
       "_dom_classes": [],
       "_model_module": "@jupyter-widgets/controls",
       "_model_module_version": "1.5.0",
       "_model_name": "LabelModel",
       "_view_count": null,
       "_view_module": "@jupyter-widgets/controls",
       "_view_module_version": "1.5.0",
       "_view_name": "LabelView",
       "description": "",
       "description_tooltip": null,
       "layout": "IPY_MODEL_423b7a2e51374418984068a9a670a5c2",
       "placeholder": "​",
       "style": "IPY_MODEL_67db72520fc644178d98bd85157e45c1",
       "value": ""
      }
     },
     "2a61ffc35e2944378ee324b54b9dc0a1": {
      "model_module": "@jupyter-widgets/controls",
      "model_module_version": "1.5.0",
      "model_name": "ProgressStyleModel",
      "state": {
       "_model_module": "@jupyter-widgets/controls",
       "_model_module_version": "1.5.0",
       "_model_name": "ProgressStyleModel",
       "_view_count": null,
       "_view_module": "@jupyter-widgets/base",
       "_view_module_version": "1.2.0",
       "_view_name": "StyleView",
       "bar_color": null,
       "description_width": ""
      }
     },
     "346ce322e7a5428c86d8ed4859590489": {
      "model_module": "@jupyter-widgets/base",
      "model_module_version": "1.2.0",
      "model_name": "LayoutModel",
      "state": {
       "_model_module": "@jupyter-widgets/base",
       "_model_module_version": "1.2.0",
       "_model_name": "LayoutModel",
       "_view_count": null,
       "_view_module": "@jupyter-widgets/base",
       "_view_module_version": "1.2.0",
       "_view_name": "LayoutView",
       "align_content": null,
       "align_items": null,
       "align_self": null,
       "border": null,
       "bottom": null,
       "display": null,
       "flex": null,
       "flex_flow": null,
       "grid_area": null,
       "grid_auto_columns": null,
       "grid_auto_flow": null,
       "grid_auto_rows": null,
       "grid_column": null,
       "grid_gap": null,
       "grid_row": null,
       "grid_template_areas": null,
       "grid_template_columns": null,
       "grid_template_rows": null,
       "height": null,
       "justify_content": null,
       "justify_items": null,
       "left": null,
       "margin": null,
       "max_height": null,
       "max_width": null,
       "min_height": null,
       "min_width": null,
       "object_fit": null,
       "object_position": null,
       "order": null,
       "overflow": null,
       "overflow_x": null,
       "overflow_y": null,
       "padding": null,
       "right": null,
       "top": null,
       "visibility": null,
       "width": null
      }
     },
     "423b7a2e51374418984068a9a670a5c2": {
      "model_module": "@jupyter-widgets/base",
      "model_module_version": "1.2.0",
      "model_name": "LayoutModel",
      "state": {
       "_model_module": "@jupyter-widgets/base",
       "_model_module_version": "1.2.0",
       "_model_name": "LayoutModel",
       "_view_count": null,
       "_view_module": "@jupyter-widgets/base",
       "_view_module_version": "1.2.0",
       "_view_name": "LayoutView",
       "align_content": null,
       "align_items": null,
       "align_self": null,
       "border": null,
       "bottom": null,
       "display": null,
       "flex": null,
       "flex_flow": null,
       "grid_area": null,
       "grid_auto_columns": null,
       "grid_auto_flow": null,
       "grid_auto_rows": null,
       "grid_column": null,
       "grid_gap": null,
       "grid_row": null,
       "grid_template_areas": null,
       "grid_template_columns": null,
       "grid_template_rows": null,
       "height": null,
       "justify_content": null,
       "justify_items": null,
       "left": null,
       "margin": null,
       "max_height": null,
       "max_width": null,
       "min_height": null,
       "min_width": null,
       "object_fit": null,
       "object_position": null,
       "order": null,
       "overflow": null,
       "overflow_x": null,
       "overflow_y": null,
       "padding": null,
       "right": null,
       "top": null,
       "visibility": null,
       "width": null
      }
     },
     "5de2f8119f8046af8ca2ee368a7c9eb7": {
      "model_module": "@jupyter-widgets/controls",
      "model_module_version": "1.5.0",
      "model_name": "ProgressStyleModel",
      "state": {
       "_model_module": "@jupyter-widgets/controls",
       "_model_module_version": "1.5.0",
       "_model_name": "ProgressStyleModel",
       "_view_count": null,
       "_view_module": "@jupyter-widgets/base",
       "_view_module_version": "1.2.0",
       "_view_name": "StyleView",
       "bar_color": null,
       "description_width": ""
      }
     },
     "675197e92cea47d4a17233a3c588745d": {
      "model_module": "@jupyter-widgets/base",
      "model_module_version": "1.2.0",
      "model_name": "LayoutModel",
      "state": {
       "_model_module": "@jupyter-widgets/base",
       "_model_module_version": "1.2.0",
       "_model_name": "LayoutModel",
       "_view_count": null,
       "_view_module": "@jupyter-widgets/base",
       "_view_module_version": "1.2.0",
       "_view_name": "LayoutView",
       "align_content": null,
       "align_items": null,
       "align_self": null,
       "border": null,
       "bottom": null,
       "display": null,
       "flex": null,
       "flex_flow": null,
       "grid_area": null,
       "grid_auto_columns": null,
       "grid_auto_flow": null,
       "grid_auto_rows": null,
       "grid_column": null,
       "grid_gap": null,
       "grid_row": null,
       "grid_template_areas": null,
       "grid_template_columns": null,
       "grid_template_rows": null,
       "height": null,
       "justify_content": null,
       "justify_items": null,
       "left": null,
       "margin": null,
       "max_height": null,
       "max_width": null,
       "min_height": null,
       "min_width": null,
       "object_fit": null,
       "object_position": null,
       "order": null,
       "overflow": null,
       "overflow_x": null,
       "overflow_y": null,
       "padding": null,
       "right": null,
       "top": null,
       "visibility": null,
       "width": null
      }
     },
     "6784e084d73442d3bd2297dbde1b7719": {
      "model_module": "@jupyter-widgets/base",
      "model_module_version": "1.2.0",
      "model_name": "LayoutModel",
      "state": {
       "_model_module": "@jupyter-widgets/base",
       "_model_module_version": "1.2.0",
       "_model_name": "LayoutModel",
       "_view_count": null,
       "_view_module": "@jupyter-widgets/base",
       "_view_module_version": "1.2.0",
       "_view_name": "LayoutView",
       "align_content": null,
       "align_items": null,
       "align_self": null,
       "border": null,
       "bottom": null,
       "display": null,
       "flex": null,
       "flex_flow": null,
       "grid_area": null,
       "grid_auto_columns": null,
       "grid_auto_flow": null,
       "grid_auto_rows": null,
       "grid_column": null,
       "grid_gap": null,
       "grid_row": null,
       "grid_template_areas": null,
       "grid_template_columns": null,
       "grid_template_rows": null,
       "height": null,
       "justify_content": null,
       "justify_items": null,
       "left": null,
       "margin": null,
       "max_height": null,
       "max_width": null,
       "min_height": null,
       "min_width": null,
       "object_fit": null,
       "object_position": null,
       "order": null,
       "overflow": null,
       "overflow_x": null,
       "overflow_y": null,
       "padding": null,
       "right": null,
       "top": null,
       "visibility": null,
       "width": null
      }
     },
     "67db72520fc644178d98bd85157e45c1": {
      "model_module": "@jupyter-widgets/controls",
      "model_module_version": "1.5.0",
      "model_name": "DescriptionStyleModel",
      "state": {
       "_model_module": "@jupyter-widgets/controls",
       "_model_module_version": "1.5.0",
       "_model_name": "DescriptionStyleModel",
       "_view_count": null,
       "_view_module": "@jupyter-widgets/base",
       "_view_module_version": "1.2.0",
       "_view_name": "StyleView",
       "description_width": ""
      }
     },
     "7fa4d58970e9427cac6338503b12730c": {
      "model_module": "@jupyter-widgets/controls",
      "model_module_version": "1.5.0",
      "model_name": "DescriptionStyleModel",
      "state": {
       "_model_module": "@jupyter-widgets/controls",
       "_model_module_version": "1.5.0",
       "_model_name": "DescriptionStyleModel",
       "_view_count": null,
       "_view_module": "@jupyter-widgets/base",
       "_view_module_version": "1.2.0",
       "_view_name": "StyleView",
       "description_width": ""
      }
     },
     "ba7625e7244648eeaa6f6978205edaf5": {
      "model_module": "@jupyter-widgets/base",
      "model_module_version": "1.2.0",
      "model_name": "LayoutModel",
      "state": {
       "_model_module": "@jupyter-widgets/base",
       "_model_module_version": "1.2.0",
       "_model_name": "LayoutModel",
       "_view_count": null,
       "_view_module": "@jupyter-widgets/base",
       "_view_module_version": "1.2.0",
       "_view_name": "LayoutView",
       "align_content": null,
       "align_items": null,
       "align_self": null,
       "border": null,
       "bottom": null,
       "display": null,
       "flex": null,
       "flex_flow": null,
       "grid_area": null,
       "grid_auto_columns": null,
       "grid_auto_flow": null,
       "grid_auto_rows": null,
       "grid_column": null,
       "grid_gap": null,
       "grid_row": null,
       "grid_template_areas": null,
       "grid_template_columns": null,
       "grid_template_rows": null,
       "height": null,
       "justify_content": null,
       "justify_items": null,
       "left": null,
       "margin": null,
       "max_height": null,
       "max_width": null,
       "min_height": null,
       "min_width": null,
       "object_fit": null,
       "object_position": null,
       "order": null,
       "overflow": null,
       "overflow_x": null,
       "overflow_y": null,
       "padding": null,
       "right": null,
       "top": null,
       "visibility": null,
       "width": null
      }
     },
     "c8f06577c7c54a559fa72f1f6aca901a": {
      "model_module": "@jupyter-widgets/controls",
      "model_module_version": "1.5.0",
      "model_name": "FloatProgressModel",
      "state": {
       "_dom_classes": [],
       "_model_module": "@jupyter-widgets/controls",
       "_model_module_version": "1.5.0",
       "_model_name": "FloatProgressModel",
       "_view_count": null,
       "_view_module": "@jupyter-widgets/controls",
       "_view_module_version": "1.5.0",
       "_view_name": "ProgressView",
       "bar_style": "",
       "description": "",
       "description_tooltip": null,
       "layout": "IPY_MODEL_ba7625e7244648eeaa6f6978205edaf5",
       "max": 1.0,
       "min": 0.0,
       "orientation": "horizontal",
       "style": "IPY_MODEL_5de2f8119f8046af8ca2ee368a7c9eb7",
       "value": 0.0
      }
     },
     "d64fd5603ccd4cb2bbc84dd5d0358220": {
      "model_module": "@jupyter-widgets/controls",
      "model_module_version": "1.5.0",
      "model_name": "LabelModel",
      "state": {
       "_dom_classes": [],
       "_model_module": "@jupyter-widgets/controls",
       "_model_module_version": "1.5.0",
       "_model_name": "LabelModel",
       "_view_count": null,
       "_view_module": "@jupyter-widgets/controls",
       "_view_module_version": "1.5.0",
       "_view_name": "LabelView",
       "description": "",
       "description_tooltip": null,
       "layout": "IPY_MODEL_6784e084d73442d3bd2297dbde1b7719",
       "placeholder": "​",
       "style": "IPY_MODEL_7fa4d58970e9427cac6338503b12730c",
       "value": ""
      }
     },
     "d653ddba306f46c2af1950d423bb7c2f": {
      "model_module": "@jupyter-widgets/controls",
      "model_module_version": "1.5.0",
      "model_name": "VBoxModel",
      "state": {
       "_dom_classes": [],
       "_model_module": "@jupyter-widgets/controls",
       "_model_module_version": "1.5.0",
       "_model_name": "VBoxModel",
       "_view_count": null,
       "_view_module": "@jupyter-widgets/controls",
       "_view_module_version": "1.5.0",
       "_view_name": "VBoxView",
       "box_style": "",
       "children": [
        "IPY_MODEL_d64fd5603ccd4cb2bbc84dd5d0358220",
        "IPY_MODEL_c8f06577c7c54a559fa72f1f6aca901a"
       ],
       "layout": "IPY_MODEL_675197e92cea47d4a17233a3c588745d"
      }
     },
     "fb83653469a14097abb01c6f24029b40": {
      "model_module": "@jupyter-widgets/base",
      "model_module_version": "1.2.0",
      "model_name": "LayoutModel",
      "state": {
       "_model_module": "@jupyter-widgets/base",
       "_model_module_version": "1.2.0",
       "_model_name": "LayoutModel",
       "_view_count": null,
       "_view_module": "@jupyter-widgets/base",
       "_view_module_version": "1.2.0",
       "_view_name": "LayoutView",
       "align_content": null,
       "align_items": null,
       "align_self": null,
       "border": null,
       "bottom": null,
       "display": null,
       "flex": null,
       "flex_flow": null,
       "grid_area": null,
       "grid_auto_columns": null,
       "grid_auto_flow": null,
       "grid_auto_rows": null,
       "grid_column": null,
       "grid_gap": null,
       "grid_row": null,
       "grid_template_areas": null,
       "grid_template_columns": null,
       "grid_template_rows": null,
       "height": null,
       "justify_content": null,
       "justify_items": null,
       "left": null,
       "margin": null,
       "max_height": null,
       "max_width": null,
       "min_height": null,
       "min_width": null,
       "object_fit": null,
       "object_position": null,
       "order": null,
       "overflow": null,
       "overflow_x": null,
       "overflow_y": null,
       "padding": null,
       "right": null,
       "top": null,
       "visibility": null,
       "width": null
      }
     }
    },
    "version_major": 2,
    "version_minor": 0
   }
  }
 },
 "nbformat": 4,
 "nbformat_minor": 5
}