convolutional.ipynb

{
 "cells": [
  {
   "cell_type": "code",
   "execution_count": 1,
   "id": "d3fd6289",
   "metadata": {
    "execution": {
     "iopub.execute_input": "2022-01-20T15:08:32.984556Z",
     "iopub.status.busy": "2022-01-20T15:08:32.983069Z",
     "iopub.status.idle": "2022-01-20T15:08:38.720485Z",
     "shell.execute_reply": "2022-01-20T15:08:38.719949Z",
     "shell.execute_reply.started": "2021-12-21T15:35:14.437697Z"
    },
    "papermill": {
     "duration": 5.754137,
     "end_time": "2022-01-20T15:08:38.720645",
     "exception": false,
     "start_time": "2022-01-20T15:08:32.966508",
     "status": "completed"
    },
    "tags": []
   },
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "2.6.2\n"
     ]
    }
   ],
   "source": [
    "import tensorflow as tf\n",
    "import numpy as np\n",
    "import os\n",
    "import random\n",
    "import pandas as pd\n",
    "import seaborn as sns\n",
    "import keras_tuner as kt\n",
    "from datetime import datetime\n",
    "import matplotlib.pyplot as plt\n",
    "plt.rc('font', size=16)\n",
    "from sklearn.preprocessing import MinMaxScaler\n",
    "import warnings\n",
    "warnings.filterwarnings('ignore')\n",
    "tf.get_logger().setLevel('ERROR')\n",
    "\n",
    "tfk = tf.keras\n",
    "tfkl = tf.keras.layers\n",
    "print(tf.__version__)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 2,
   "id": "9d96a5c8",
   "metadata": {
    "execution": {
     "iopub.execute_input": "2022-01-20T15:08:38.750442Z",
     "iopub.status.busy": "2022-01-20T15:08:38.749815Z",
     "iopub.status.idle": "2022-01-20T15:08:38.752368Z",
     "shell.execute_reply": "2022-01-20T15:08:38.751986Z",
     "shell.execute_reply.started": "2021-12-21T15:35:25.618144Z"
    },
    "papermill": {
     "duration": 0.019314,
     "end_time": "2022-01-20T15:08:38.752499",
     "exception": false,
     "start_time": "2022-01-20T15:08:38.733185",
     "status": "completed"
    },
    "tags": []
   },
   "outputs": [],
   "source": [
    "# Random seed for reproducibility\n",
    "seed = 42\n",
    "\n",
    "random.seed(seed)\n",
    "os.environ['PYTHONHASHSEED'] = str(seed)\n",
    "np.random.seed(seed)\n",
    "tf.random.set_seed(seed)\n",
    "tf.compat.v1.set_random_seed(seed)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 3,
   "id": "f81bb7c7",
   "metadata": {
    "execution": {
     "iopub.execute_input": "2022-01-20T15:08:38.778342Z",
     "iopub.status.busy": "2022-01-20T15:08:38.777586Z",
     "iopub.status.idle": "2022-01-20T15:08:39.011478Z",
     "shell.execute_reply": "2022-01-20T15:08:39.012174Z",
     "shell.execute_reply.started": "2021-12-21T15:35:28.578673Z"
    },
    "papermill": {
     "duration": 0.248334,
     "end_time": "2022-01-20T15:08:39.012369",
     "exception": false,
     "start_time": "2022-01-20T15:08:38.764035",
     "status": "completed"
    },
    "tags": []
   },
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "(68528, 7)\n"
     ]
    },
    {
     "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>Sponginess</th>\n",
       "      <th>Wonder level</th>\n",
       "      <th>Crunchiness</th>\n",
       "      <th>Loudness on impact</th>\n",
       "      <th>Meme creativity</th>\n",
       "      <th>Soap slipperiness</th>\n",
       "      <th>Hype root</th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>0</th>\n",
       "      <td>7.97698</td>\n",
       "      <td>4.33494</td>\n",
       "      <td>10.67282</td>\n",
       "      <td>1.76692</td>\n",
       "      <td>3.22440</td>\n",
       "      <td>51.681460</td>\n",
       "      <td>3.65434</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1</th>\n",
       "      <td>8.07824</td>\n",
       "      <td>4.44616</td>\n",
       "      <td>10.56160</td>\n",
       "      <td>1.70716</td>\n",
       "      <td>3.32566</td>\n",
       "      <td>51.563598</td>\n",
       "      <td>3.47672</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2</th>\n",
       "      <td>8.02844</td>\n",
       "      <td>4.22372</td>\n",
       "      <td>10.56160</td>\n",
       "      <td>1.64906</td>\n",
       "      <td>3.17460</td>\n",
       "      <td>50.863080</td>\n",
       "      <td>3.47672</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>3</th>\n",
       "      <td>8.02844</td>\n",
       "      <td>4.22372</td>\n",
       "      <td>10.56160</td>\n",
       "      <td>1.70716</td>\n",
       "      <td>3.17460</td>\n",
       "      <td>45.841581</td>\n",
       "      <td>3.47672</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>4</th>\n",
       "      <td>7.87572</td>\n",
       "      <td>4.44616</td>\n",
       "      <td>10.45038</td>\n",
       "      <td>1.70716</td>\n",
       "      <td>3.27586</td>\n",
       "      <td>47.126421</td>\n",
       "      <td>3.47672</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "</div>"
      ],
      "text/plain": [
       "   Sponginess  Wonder level  Crunchiness  Loudness on impact  Meme creativity  \\\n",
       "0     7.97698       4.33494     10.67282             1.76692          3.22440   \n",
       "1     8.07824       4.44616     10.56160             1.70716          3.32566   \n",
       "2     8.02844       4.22372     10.56160             1.64906          3.17460   \n",
       "3     8.02844       4.22372     10.56160             1.70716          3.17460   \n",
       "4     7.87572       4.44616     10.45038             1.70716          3.27586   \n",
       "\n",
       "   Soap slipperiness  Hype root  \n",
       "0          51.681460    3.65434  \n",
       "1          51.563598    3.47672  \n",
       "2          50.863080    3.47672  \n",
       "3          45.841581    3.47672  \n",
       "4          47.126421    3.47672  "
      ]
     },
     "execution_count": 3,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "dataset = pd.read_csv(\"../input/timeseriesdataset/Training.csv\")\n",
    "print(dataset.shape)\n",
    "dataset.head()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 4,
   "id": "020319a6",
   "metadata": {
    "execution": {
     "iopub.execute_input": "2022-01-20T15:08:39.049511Z",
     "iopub.status.busy": "2022-01-20T15:08:39.048949Z",
     "iopub.status.idle": "2022-01-20T15:08:39.066362Z",
     "shell.execute_reply": "2022-01-20T15:08:39.065687Z",
     "shell.execute_reply.started": "2021-12-21T15:35:31.28804Z"
    },
    "papermill": {
     "duration": 0.037883,
     "end_time": "2022-01-20T15:08:39.066560",
     "exception": false,
     "start_time": "2022-01-20T15:08:39.028677",
     "status": "completed"
    },
    "tags": []
   },
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "<class 'pandas.core.frame.DataFrame'>\n",
      "RangeIndex: 68528 entries, 0 to 68527\n",
      "Data columns (total 7 columns):\n",
      " #   Column              Non-Null Count  Dtype  \n",
      "---  ------              --------------  -----  \n",
      " 0   Sponginess          68528 non-null  float64\n",
      " 1   Wonder level        68528 non-null  float64\n",
      " 2   Crunchiness         68528 non-null  float64\n",
      " 3   Loudness on impact  68528 non-null  float64\n",
      " 4   Meme creativity     68528 non-null  float64\n",
      " 5   Soap slipperiness   68528 non-null  float64\n",
      " 6   Hype root           68528 non-null  float64\n",
      "dtypes: float64(7)\n",
      "memory usage: 3.7 MB\n"
     ]
    }
   ],
   "source": [
    "dataset.info()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 5,
   "id": "00cca637",
   "metadata": {
    "execution": {
     "iopub.execute_input": "2022-01-20T15:08:39.105505Z",
     "iopub.status.busy": "2022-01-20T15:08:39.104887Z",
     "iopub.status.idle": "2022-01-20T15:08:40.070828Z",
     "shell.execute_reply": "2022-01-20T15:08:40.071267Z",
     "shell.execute_reply.started": "2021-12-21T15:35:35.019244Z"
    },
    "papermill": {
     "duration": 0.98928,
     "end_time": "2022-01-20T15:08:40.071415",
     "exception": false,
     "start_time": "2022-01-20T15:08:39.082135",
     "status": "completed"
    },
    "tags": []
   },
   "outputs": [
    {
     "data": {
      "image/png": "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\n",
      "text/plain": [
       "<Figure size 1224x1224 with 7 Axes>"
      ]
     },
     "metadata": {
      "needs_background": "light"
     },
     "output_type": "display_data"
    }
   ],
   "source": [
    "def inspect_dataframe(df, columns):\n",
    "    figs, axs = plt.subplots(len(columns), 1, sharex=True, figsize=(17,17))\n",
    "    for i, col in enumerate(columns):\n",
    "        axs[i].plot(df[col])\n",
    "        axs[i].set_title(col)\n",
    "    plt.show()\n",
    "inspect_dataframe(dataset, dataset.columns)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 6,
   "id": "e28f6cf0",
   "metadata": {
    "execution": {
     "iopub.execute_input": "2022-01-20T15:08:40.114710Z",
     "iopub.status.busy": "2022-01-20T15:08:40.113867Z",
     "iopub.status.idle": "2022-01-20T15:08:40.117124Z",
     "shell.execute_reply": "2022-01-20T15:08:40.117745Z",
     "shell.execute_reply.started": "2021-12-21T15:35:39.972546Z"
    },
    "papermill": {
     "duration": 0.02706,
     "end_time": "2022-01-20T15:08:40.117929",
     "exception": false,
     "start_time": "2022-01-20T15:08:40.090869",
     "status": "completed"
    },
    "tags": []
   },
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "(68528, 7)\n"
     ]
    }
   ],
   "source": [
    "print(dataset.shape)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 7,
   "id": "3f0a0865",
   "metadata": {
    "execution": {
     "iopub.execute_input": "2022-01-20T15:08:40.161669Z",
     "iopub.status.busy": "2022-01-20T15:08:40.161028Z",
     "iopub.status.idle": "2022-01-20T15:08:40.181206Z",
     "shell.execute_reply": "2022-01-20T15:08:40.181775Z",
     "shell.execute_reply.started": "2021-12-21T15:35:41.60635Z"
    },
    "papermill": {
     "duration": 0.044011,
     "end_time": "2022-01-20T15:08:40.181942",
     "exception": false,
     "start_time": "2022-01-20T15:08:40.137931",
     "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>Sponginess</th>\n",
       "      <th>Wonder level</th>\n",
       "      <th>Crunchiness</th>\n",
       "      <th>Loudness on impact</th>\n",
       "      <th>Meme creativity</th>\n",
       "      <th>Soap slipperiness</th>\n",
       "      <th>Hype root</th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>0</th>\n",
       "      <td>0.556576</td>\n",
       "      <td>0.481134</td>\n",
       "      <td>0.612986</td>\n",
       "      <td>0.468044</td>\n",
       "      <td>0.613765</td>\n",
       "      <td>0.691885</td>\n",
       "      <td>0.629100</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1</th>\n",
       "      <td>0.562874</td>\n",
       "      <td>0.485320</td>\n",
       "      <td>0.611573</td>\n",
       "      <td>0.465453</td>\n",
       "      <td>0.627575</td>\n",
       "      <td>0.690471</td>\n",
       "      <td>0.626693</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2</th>\n",
       "      <td>0.559777</td>\n",
       "      <td>0.476949</td>\n",
       "      <td>0.611573</td>\n",
       "      <td>0.462934</td>\n",
       "      <td>0.606973</td>\n",
       "      <td>0.682070</td>\n",
       "      <td>0.626693</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>3</th>\n",
       "      <td>0.559777</td>\n",
       "      <td>0.476949</td>\n",
       "      <td>0.611573</td>\n",
       "      <td>0.465453</td>\n",
       "      <td>0.606973</td>\n",
       "      <td>0.621844</td>\n",
       "      <td>0.626693</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>4</th>\n",
       "      <td>0.550279</td>\n",
       "      <td>0.485320</td>\n",
       "      <td>0.610160</td>\n",
       "      <td>0.465453</td>\n",
       "      <td>0.620783</td>\n",
       "      <td>0.637254</td>\n",
       "      <td>0.626693</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "</div>"
      ],
      "text/plain": [
       "   Sponginess  Wonder level  Crunchiness  Loudness on impact  Meme creativity  \\\n",
       "0    0.556576      0.481134     0.612986            0.468044         0.613765   \n",
       "1    0.562874      0.485320     0.611573            0.465453         0.627575   \n",
       "2    0.559777      0.476949     0.611573            0.462934         0.606973   \n",
       "3    0.559777      0.476949     0.611573            0.465453         0.606973   \n",
       "4    0.550279      0.485320     0.610160            0.465453         0.620783   \n",
       "\n",
       "   Soap slipperiness  Hype root  \n",
       "0           0.691885   0.629100  \n",
       "1           0.690471   0.626693  \n",
       "2           0.682070   0.626693  \n",
       "3           0.621844   0.626693  \n",
       "4           0.637254   0.626693  "
      ]
     },
     "execution_count": 7,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "X_min = dataset.min()\n",
    "X_max = dataset.max()\n",
    "\n",
    "dataset = (dataset-X_min)/(X_max-X_min)\n",
    "dataset.head()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 8,
   "id": "61d742b1",
   "metadata": {
    "execution": {
     "iopub.execute_input": "2022-01-20T15:08:40.225142Z",
     "iopub.status.busy": "2022-01-20T15:08:40.223526Z",
     "iopub.status.idle": "2022-01-20T15:08:40.227091Z",
     "shell.execute_reply": "2022-01-20T15:08:40.227570Z",
     "shell.execute_reply.started": "2021-12-21T15:35:44.050105Z"
    },
    "papermill": {
     "duration": 0.025728,
     "end_time": "2022-01-20T15:08:40.227706",
     "exception": false,
     "start_time": "2022-01-20T15:08:40.201978",
     "status": "completed"
    },
    "tags": []
   },
   "outputs": [],
   "source": [
    "window = 128\n",
    "stride = 16\n",
    "telescope = 864"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 9,
   "id": "04350284",
   "metadata": {
    "execution": {
     "iopub.execute_input": "2022-01-20T15:08:40.273534Z",
     "iopub.status.busy": "2022-01-20T15:08:40.267172Z",
     "iopub.status.idle": "2022-01-20T15:08:40.276065Z",
     "shell.execute_reply": "2022-01-20T15:08:40.275622Z",
     "shell.execute_reply.started": "2021-12-21T15:37:15.36662Z"
    },
    "papermill": {
     "duration": 0.03001,
     "end_time": "2022-01-20T15:08:40.276175",
     "exception": false,
     "start_time": "2022-01-20T15:08:40.246165",
     "status": "completed"
    },
    "tags": []
   },
   "outputs": [],
   "source": [
    "def build_sequences(df, window, stride, telescope):\n",
    "    # Sanity check to avoid runtime errors\n",
    "    assert window % stride == 0\n",
    "    dataset = []\n",
    "    labels = []\n",
    "    temp_df = df.copy().values\n",
    "    temp_label = df.copy().values\n",
    "    padding_len = len(df)%window\n",
    "\n",
    "    if(padding_len != 0):\n",
    "        # Compute padding length\n",
    "        padding_len = window - len(df)%window\n",
    "        padding = np.zeros((padding_len,temp_df.shape[1]), dtype='float32')\n",
    "        temp_df = np.concatenate((padding,df))\n",
    "        padding = np.zeros((padding_len,temp_label.shape[1]), dtype='float32')\n",
    "        temp_label = np.concatenate((padding,temp_label))\n",
    "        assert len(temp_df) % window == 0\n",
    "\n",
    "    for idx in np.arange(0,len(temp_df)-window-telescope,stride):\n",
    "        dataset.append(temp_df[idx:idx+window])\n",
    "        labels.append(temp_label[idx+window:idx+window+telescope])\n",
    "\n",
    "    dataset = np.array(dataset)\n",
    "    labels = np.array(labels)\n",
    "    return dataset, labels"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 10,
   "id": "d19a47c7",
   "metadata": {
    "execution": {
     "iopub.execute_input": "2022-01-20T15:08:40.318869Z",
     "iopub.status.busy": "2022-01-20T15:08:40.317927Z",
     "iopub.status.idle": "2022-01-20T15:08:40.400395Z",
     "shell.execute_reply": "2022-01-20T15:08:40.400806Z",
     "shell.execute_reply.started": "2021-12-21T15:37:18.048225Z"
    },
    "papermill": {
     "duration": 0.105942,
     "end_time": "2022-01-20T15:08:40.400956",
     "exception": false,
     "start_time": "2022-01-20T15:08:40.295014",
     "status": "completed"
    },
    "tags": []
   },
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "(4226, 128, 7) (4226, 864, 7)\n"
     ]
    }
   ],
   "source": [
    "X_train, y_train = build_sequences(dataset, window, stride, telescope)\n",
    "print(X_train.shape, y_train.shape)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 11,
   "id": "083b01f5",
   "metadata": {
    "execution": {
     "iopub.execute_input": "2022-01-20T15:08:40.442356Z",
     "iopub.status.busy": "2022-01-20T15:08:40.441562Z",
     "iopub.status.idle": "2022-01-20T15:08:40.448198Z",
     "shell.execute_reply": "2022-01-20T15:08:40.447726Z",
     "shell.execute_reply.started": "2021-12-21T15:37:26.97693Z"
    },
    "papermill": {
     "duration": 0.028389,
     "end_time": "2022-01-20T15:08:40.448310",
     "exception": false,
     "start_time": "2022-01-20T15:08:40.419921",
     "status": "completed"
    },
    "tags": []
   },
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "(128, 7)\n",
      "(864, 7)\n",
      "864\n",
      "7\n"
     ]
    }
   ],
   "source": [
    "input_shape = X_train.shape[1:]\n",
    "output_shape = y_train.shape[1:]\n",
    "batch_size = 64\n",
    "epochs = 100\n",
    "print(input_shape)\n",
    "print(output_shape)\n",
    "print(output_shape[0])\n",
    "print(output_shape[1])"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 12,
   "id": "55106336",
   "metadata": {
    "execution": {
     "iopub.execute_input": "2022-01-20T15:08:40.496465Z",
     "iopub.status.busy": "2022-01-20T15:08:40.495588Z",
     "iopub.status.idle": "2022-01-20T15:08:40.497343Z",
     "shell.execute_reply": "2022-01-20T15:08:40.497985Z",
     "shell.execute_reply.started": "2021-12-21T15:37:36.969671Z"
    },
    "papermill": {
     "duration": 0.030836,
     "end_time": "2022-01-20T15:08:40.498120",
     "exception": false,
     "start_time": "2022-01-20T15:08:40.467284",
     "status": "completed"
    },
    "tags": []
   },
   "outputs": [],
   "source": [
    "def build_model():\n",
    "\n",
    "    telescope = output_shape[0]\n",
    "    num_channels = output_shape[1]\n",
    "    input_layer = tfkl.Input(shape=input_shape, name='Input')\n",
    "    \n",
    "    # Convolutional part\n",
    "    cnn = tfkl.Conv1D(8,3,padding='same',activation='relu')(input_layer)\n",
    "    cnn = tfkl.MaxPooling1D()(cnn)\n",
    "    cnn = tfkl.Conv1D(16,3,padding='same',activation='relu')(cnn)\n",
    "    cnn = tfkl.MaxPooling1D()(cnn)\n",
    "    cnn = tfkl.Conv1D(32,3,padding='same',activation='relu')(cnn)\n",
    "    cnn = tfkl.MaxPooling1D()(cnn)\n",
    "    cnn = tfkl.Conv1D(64,3,padding='same',activation='relu')(cnn)\n",
    "    gap = tfkl.Flatten()(cnn)\n",
    "\n",
    "    # Fully connected part\n",
    "    dense1 = tfkl.Dense(telescope*num_channels, activation='relu')(gap)\n",
    "    dense2 = tfkl.Dense(telescope*num_channels, activation='relu')(dense1)\n",
    "    output_layer = tfkl.Reshape((telescope, num_channels))(dense2)\n",
    "\n",
    "    # Connect input and output through the Model class\n",
    "    model = tfk.Model(inputs=input_layer, outputs=output_layer, name='SimpleForecasting')\n",
    "\n",
    "    # Compile the model\n",
    "    model.compile(loss=tfk.losses.MeanSquaredError(), optimizer=tfk.optimizers.Adam(), metrics=['mae', tfk.metrics.RootMeanSquaredError()])\n",
    "\n",
    "    # Return the model\n",
    "    return model"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 13,
   "id": "da7be8ba",
   "metadata": {
    "execution": {
     "iopub.execute_input": "2022-01-20T15:08:40.541282Z",
     "iopub.status.busy": "2022-01-20T15:08:40.540473Z",
     "iopub.status.idle": "2022-01-20T15:08:43.711920Z",
     "shell.execute_reply": "2022-01-20T15:08:43.711479Z",
     "shell.execute_reply.started": "2021-12-21T15:37:42.261481Z"
    },
    "papermill": {
     "duration": 3.194829,
     "end_time": "2022-01-20T15:08:43.712042",
     "exception": false,
     "start_time": "2022-01-20T15:08:40.517213",
     "status": "completed"
    },
    "tags": []
   },
   "outputs": [
    {
     "name": "stderr",
     "output_type": "stream",
     "text": [
      "2022-01-20 15:08:40.616719: I tensorflow/stream_executor/cuda/cuda_gpu_executor.cc:937] successful NUMA node read from SysFS had negative value (-1), but there must be at least one NUMA node, so returning NUMA node zero\n",
      "2022-01-20 15:08:40.723746: I tensorflow/stream_executor/cuda/cuda_gpu_executor.cc:937] successful NUMA node read from SysFS had negative value (-1), but there must be at least one NUMA node, so returning NUMA node zero\n",
      "2022-01-20 15:08:40.724558: I tensorflow/stream_executor/cuda/cuda_gpu_executor.cc:937] successful NUMA node read from SysFS had negative value (-1), but there must be at least one NUMA node, so returning NUMA node zero\n",
      "2022-01-20 15:08:40.726069: 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 AVX512F FMA\n",
      "To enable them in other operations, rebuild TensorFlow with the appropriate compiler flags.\n",
      "2022-01-20 15:08:40.727165: I tensorflow/stream_executor/cuda/cuda_gpu_executor.cc:937] successful NUMA node read from SysFS had negative value (-1), but there must be at least one NUMA node, so returning NUMA node zero\n",
      "2022-01-20 15:08:40.727836: I tensorflow/stream_executor/cuda/cuda_gpu_executor.cc:937] successful NUMA node read from SysFS had negative value (-1), but there must be at least one NUMA node, so returning NUMA node zero\n",
      "2022-01-20 15:08:40.728435: I tensorflow/stream_executor/cuda/cuda_gpu_executor.cc:937] successful NUMA node read from SysFS had negative value (-1), but there must be at least one NUMA node, so returning NUMA node zero\n",
      "2022-01-20 15:08:42.532496: I tensorflow/stream_executor/cuda/cuda_gpu_executor.cc:937] successful NUMA node read from SysFS had negative value (-1), but there must be at least one NUMA node, so returning NUMA node zero\n",
      "2022-01-20 15:08:42.533283: I tensorflow/stream_executor/cuda/cuda_gpu_executor.cc:937] successful NUMA node read from SysFS had negative value (-1), but there must be at least one NUMA node, so returning NUMA node zero\n",
      "2022-01-20 15:08:42.533991: I tensorflow/stream_executor/cuda/cuda_gpu_executor.cc:937] successful NUMA node read from SysFS had negative value (-1), but there must be at least one NUMA node, so returning NUMA node zero\n",
      "2022-01-20 15:08:42.534586: I tensorflow/core/common_runtime/gpu/gpu_device.cc:1510] Created device /job:localhost/replica:0/task:0/device:GPU:0 with 15403 MB memory:  -> device: 0, name: Tesla P100-PCIE-16GB, pci bus id: 0000:00:04.0, compute capability: 6.0\n"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "Model: \"SimpleForecasting\"\n",
      "_________________________________________________________________\n",
      "Layer (type)                 Output Shape              Param #   \n",
      "=================================================================\n",
      "Input (InputLayer)           [(None, 128, 7)]          0         \n",
      "_________________________________________________________________\n",
      "conv1d (Conv1D)              (None, 128, 8)            176       \n",
      "_________________________________________________________________\n",
      "max_pooling1d (MaxPooling1D) (None, 64, 8)             0         \n",
      "_________________________________________________________________\n",
      "conv1d_1 (Conv1D)            (None, 64, 16)            400       \n",
      "_________________________________________________________________\n",
      "max_pooling1d_1 (MaxPooling1 (None, 32, 16)            0         \n",
      "_________________________________________________________________\n",
      "conv1d_2 (Conv1D)            (None, 32, 32)            1568      \n",
      "_________________________________________________________________\n",
      "max_pooling1d_2 (MaxPooling1 (None, 16, 32)            0         \n",
      "_________________________________________________________________\n",
      "conv1d_3 (Conv1D)            (None, 16, 64)            6208      \n",
      "_________________________________________________________________\n",
      "flatten (Flatten)            (None, 1024)              0         \n",
      "_________________________________________________________________\n",
      "dense (Dense)                (None, 6048)              6199200   \n",
      "_________________________________________________________________\n",
      "dense_1 (Dense)              (None, 6048)              36584352  \n",
      "_________________________________________________________________\n",
      "reshape (Reshape)            (None, 864, 7)            0         \n",
      "=================================================================\n",
      "Total params: 42,791,904\n",
      "Trainable params: 42,791,904\n",
      "Non-trainable params: 0\n",
      "_________________________________________________________________\n"
     ]
    },
    {
     "data": {
      "image/png": "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\n",
      "text/plain": [
       "<IPython.core.display.Image object>"
      ]
     },
     "execution_count": 13,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "model = build_model()\n",
    "model.summary()\n",
    "tfk.utils.plot_model(model, expand_nested=True)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 14,
   "id": "20969496",
   "metadata": {
    "execution": {
     "iopub.execute_input": "2022-01-20T15:08:43.766191Z",
     "iopub.status.busy": "2022-01-20T15:08:43.765184Z",
     "iopub.status.idle": "2022-01-20T15:10:04.024069Z",
     "shell.execute_reply": "2022-01-20T15:10:04.023441Z",
     "shell.execute_reply.started": "2021-12-21T15:37:48.776181Z"
    },
    "papermill": {
     "duration": 80.290823,
     "end_time": "2022-01-20T15:10:04.024210",
     "exception": false,
     "start_time": "2022-01-20T15:08:43.733387",
     "status": "completed"
    },
    "tags": []
   },
   "outputs": [
    {
     "name": "stderr",
     "output_type": "stream",
     "text": [
      "2022-01-20 15:08:44.050317: 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"
     ]
    },
    {
     "name": "stderr",
     "output_type": "stream",
     "text": [
      "2022-01-20 15:08:45.588203: I tensorflow/stream_executor/cuda/cuda_dnn.cc:369] Loaded cuDNN version 8005\n"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "60/60 [==============================] - 8s 15ms/step - loss: 0.1087 - mae: 0.2457 - root_mean_squared_error: 0.3297 - val_loss: 0.0840 - val_mae: 0.2078 - val_root_mean_squared_error: 0.2898\n",
      "Epoch 2/100\n",
      "60/60 [==============================] - 1s 10ms/step - loss: 0.0747 - mae: 0.1866 - root_mean_squared_error: 0.2733 - val_loss: 0.0693 - val_mae: 0.1789 - val_root_mean_squared_error: 0.2633\n",
      "Epoch 3/100\n",
      "60/60 [==============================] - 1s 10ms/step - loss: 0.0632 - mae: 0.1655 - root_mean_squared_error: 0.2515 - val_loss: 0.0601 - val_mae: 0.1612 - val_root_mean_squared_error: 0.2451\n",
      "Epoch 4/100\n",
      "60/60 [==============================] - 1s 10ms/step - loss: 0.0585 - mae: 0.1562 - root_mean_squared_error: 0.2418 - val_loss: 0.0570 - val_mae: 0.1558 - val_root_mean_squared_error: 0.2387\n",
      "Epoch 5/100\n",
      "60/60 [==============================] - 1s 10ms/step - loss: 0.0521 - mae: 0.1434 - root_mean_squared_error: 0.2284 - val_loss: 0.0493 - val_mae: 0.1392 - val_root_mean_squared_error: 0.2220\n",
      "Epoch 6/100\n",
      "60/60 [==============================] - 1s 11ms/step - loss: 0.0460 - mae: 0.1291 - root_mean_squared_error: 0.2146 - val_loss: 0.0472 - val_mae: 0.1371 - val_root_mean_squared_error: 0.2174\n",
      "Epoch 7/100\n",
      "60/60 [==============================] - 1s 11ms/step - loss: 0.0429 - mae: 0.1227 - root_mean_squared_error: 0.2070 - val_loss: 0.0446 - val_mae: 0.1337 - val_root_mean_squared_error: 0.2112\n",
      "Epoch 8/100\n",
      "60/60 [==============================] - 1s 11ms/step - loss: 0.0400 - mae: 0.1182 - root_mean_squared_error: 0.2000 - val_loss: 0.0414 - val_mae: 0.1274 - val_root_mean_squared_error: 0.2034\n",
      "Epoch 9/100\n",
      "60/60 [==============================] - 1s 11ms/step - loss: 0.0377 - mae: 0.1134 - root_mean_squared_error: 0.1942 - val_loss: 0.0397 - val_mae: 0.1241 - val_root_mean_squared_error: 0.1993\n",
      "Epoch 10/100\n",
      "60/60 [==============================] - 1s 10ms/step - loss: 0.0363 - mae: 0.1102 - root_mean_squared_error: 0.1905 - val_loss: 0.0382 - val_mae: 0.1213 - val_root_mean_squared_error: 0.1955\n",
      "Epoch 11/100\n",
      "60/60 [==============================] - 1s 10ms/step - loss: 0.0351 - mae: 0.1080 - root_mean_squared_error: 0.1872 - val_loss: 0.0377 - val_mae: 0.1228 - val_root_mean_squared_error: 0.1942\n",
      "Epoch 12/100\n",
      "60/60 [==============================] - 1s 11ms/step - loss: 0.0340 - mae: 0.1058 - root_mean_squared_error: 0.1844 - val_loss: 0.0360 - val_mae: 0.1176 - val_root_mean_squared_error: 0.1897\n",
      "Epoch 13/100\n",
      "60/60 [==============================] - 1s 10ms/step - loss: 0.0321 - mae: 0.1027 - root_mean_squared_error: 0.1792 - val_loss: 0.0341 - val_mae: 0.1134 - val_root_mean_squared_error: 0.1846\n",
      "Epoch 14/100\n",
      "60/60 [==============================] - 1s 10ms/step - loss: 0.0309 - mae: 0.1004 - root_mean_squared_error: 0.1757 - val_loss: 0.0330 - val_mae: 0.1107 - val_root_mean_squared_error: 0.1817\n",
      "Epoch 15/100\n",
      "60/60 [==============================] - 1s 11ms/step - loss: 0.0299 - mae: 0.0985 - root_mean_squared_error: 0.1728 - val_loss: 0.0321 - val_mae: 0.1096 - val_root_mean_squared_error: 0.1791\n",
      "Epoch 16/100\n",
      "60/60 [==============================] - 1s 10ms/step - loss: 0.0291 - mae: 0.0966 - root_mean_squared_error: 0.1705 - val_loss: 0.0315 - val_mae: 0.1080 - val_root_mean_squared_error: 0.1774\n",
      "Epoch 17/100\n",
      "60/60 [==============================] - 1s 11ms/step - loss: 0.0285 - mae: 0.0957 - root_mean_squared_error: 0.1689 - val_loss: 0.0305 - val_mae: 0.1067 - val_root_mean_squared_error: 0.1748\n",
      "Epoch 18/100\n",
      "60/60 [==============================] - 1s 10ms/step - loss: 0.0273 - mae: 0.0932 - root_mean_squared_error: 0.1653 - val_loss: 0.0297 - val_mae: 0.1052 - val_root_mean_squared_error: 0.1723\n",
      "Epoch 19/100\n",
      "60/60 [==============================] - 1s 10ms/step - loss: 0.0259 - mae: 0.0912 - root_mean_squared_error: 0.1609 - val_loss: 0.0284 - val_mae: 0.1044 - val_root_mean_squared_error: 0.1686\n",
      "Epoch 20/100\n",
      "60/60 [==============================] - 1s 13ms/step - loss: 0.0244 - mae: 0.0887 - root_mean_squared_error: 0.1561 - val_loss: 0.0271 - val_mae: 0.1025 - val_root_mean_squared_error: 0.1647\n",
      "Epoch 21/100\n",
      "60/60 [==============================] - 1s 13ms/step - loss: 0.0236 - mae: 0.0877 - root_mean_squared_error: 0.1537 - val_loss: 0.0261 - val_mae: 0.0988 - val_root_mean_squared_error: 0.1614\n",
      "Epoch 22/100\n",
      "60/60 [==============================] - 1s 11ms/step - loss: 0.0225 - mae: 0.0853 - root_mean_squared_error: 0.1501 - val_loss: 0.0252 - val_mae: 0.0995 - val_root_mean_squared_error: 0.1588\n",
      "Epoch 23/100\n",
      "60/60 [==============================] - 1s 10ms/step - loss: 0.0214 - mae: 0.0837 - root_mean_squared_error: 0.1464 - val_loss: 0.0242 - val_mae: 0.0960 - val_root_mean_squared_error: 0.1556\n",
      "Epoch 24/100\n",
      "60/60 [==============================] - 1s 11ms/step - loss: 0.0204 - mae: 0.0816 - root_mean_squared_error: 0.1428 - val_loss: 0.0228 - val_mae: 0.0932 - val_root_mean_squared_error: 0.1511\n",
      "Epoch 25/100\n",
      "60/60 [==============================] - 1s 10ms/step - loss: 0.0193 - mae: 0.0794 - root_mean_squared_error: 0.1391 - val_loss: 0.0219 - val_mae: 0.0923 - val_root_mean_squared_error: 0.1481\n",
      "Epoch 26/100\n",
      "60/60 [==============================] - 1s 10ms/step - loss: 0.0184 - mae: 0.0782 - root_mean_squared_error: 0.1356 - val_loss: 0.0215 - val_mae: 0.0927 - val_root_mean_squared_error: 0.1466\n",
      "Epoch 27/100\n",
      "60/60 [==============================] - 1s 10ms/step - loss: 0.0179 - mae: 0.0773 - root_mean_squared_error: 0.1337 - val_loss: 0.0215 - val_mae: 0.0932 - val_root_mean_squared_error: 0.1465\n",
      "Epoch 28/100\n",
      "60/60 [==============================] - 1s 11ms/step - loss: 0.0173 - mae: 0.0756 - root_mean_squared_error: 0.1317 - val_loss: 0.0206 - val_mae: 0.0902 - val_root_mean_squared_error: 0.1434\n",
      "Epoch 29/100\n",
      "60/60 [==============================] - 1s 10ms/step - loss: 0.0167 - mae: 0.0747 - root_mean_squared_error: 0.1291 - val_loss: 0.0198 - val_mae: 0.0896 - val_root_mean_squared_error: 0.1408\n",
      "Epoch 30/100\n",
      "60/60 [==============================] - 1s 10ms/step - loss: 0.0161 - mae: 0.0735 - root_mean_squared_error: 0.1268 - val_loss: 0.0196 - val_mae: 0.0899 - val_root_mean_squared_error: 0.1400\n",
      "Epoch 31/100\n",
      "60/60 [==============================] - 1s 11ms/step - loss: 0.0155 - mae: 0.0727 - root_mean_squared_error: 0.1247 - val_loss: 0.0188 - val_mae: 0.0872 - val_root_mean_squared_error: 0.1372\n",
      "Epoch 32/100\n",
      "60/60 [==============================] - 1s 11ms/step - loss: 0.0149 - mae: 0.0714 - root_mean_squared_error: 0.1220 - val_loss: 0.0179 - val_mae: 0.0856 - val_root_mean_squared_error: 0.1339\n",
      "Epoch 33/100\n",
      "60/60 [==============================] - 1s 10ms/step - loss: 0.0144 - mae: 0.0712 - root_mean_squared_error: 0.1201 - val_loss: 0.0180 - val_mae: 0.0873 - val_root_mean_squared_error: 0.1341\n",
      "Epoch 34/100\n",
      "60/60 [==============================] - 1s 11ms/step - loss: 0.0140 - mae: 0.0699 - root_mean_squared_error: 0.1184 - val_loss: 0.0180 - val_mae: 0.0871 - val_root_mean_squared_error: 0.1343\n",
      "Epoch 35/100\n",
      "60/60 [==============================] - 1s 11ms/step - loss: 0.0137 - mae: 0.0694 - root_mean_squared_error: 0.1171 - val_loss: 0.0179 - val_mae: 0.0858 - val_root_mean_squared_error: 0.1338\n",
      "Epoch 36/100\n",
      "60/60 [==============================] - 1s 10ms/step - loss: 0.0133 - mae: 0.0682 - root_mean_squared_error: 0.1153 - val_loss: 0.0167 - val_mae: 0.0843 - val_root_mean_squared_error: 0.1293\n",
      "Epoch 37/100\n",
      "60/60 [==============================] - 1s 10ms/step - loss: 0.0127 - mae: 0.0674 - root_mean_squared_error: 0.1128 - val_loss: 0.0167 - val_mae: 0.0845 - val_root_mean_squared_error: 0.1291\n",
      "Epoch 38/100\n",
      "60/60 [==============================] - 1s 11ms/step - loss: 0.0123 - mae: 0.0669 - root_mean_squared_error: 0.1108 - val_loss: 0.0163 - val_mae: 0.0833 - val_root_mean_squared_error: 0.1276\n",
      "Epoch 39/100\n",
      "60/60 [==============================] - 1s 10ms/step - loss: 0.0118 - mae: 0.0657 - root_mean_squared_error: 0.1088 - val_loss: 0.0160 - val_mae: 0.0835 - val_root_mean_squared_error: 0.1265\n",
      "Epoch 40/100\n",
      "60/60 [==============================] - 1s 11ms/step - loss: 0.0115 - mae: 0.0647 - root_mean_squared_error: 0.1072 - val_loss: 0.0158 - val_mae: 0.0826 - val_root_mean_squared_error: 0.1258\n",
      "Epoch 41/100\n",
      "60/60 [==============================] - 1s 10ms/step - loss: 0.0112 - mae: 0.0642 - root_mean_squared_error: 0.1057 - val_loss: 0.0153 - val_mae: 0.0820 - val_root_mean_squared_error: 0.1238\n",
      "Epoch 42/100\n",
      "60/60 [==============================] - 1s 10ms/step - loss: 0.0109 - mae: 0.0639 - root_mean_squared_error: 0.1045 - val_loss: 0.0155 - val_mae: 0.0826 - val_root_mean_squared_error: 0.1247\n",
      "Epoch 43/100\n",
      "60/60 [==============================] - 1s 10ms/step - loss: 0.0106 - mae: 0.0635 - root_mean_squared_error: 0.1031 - val_loss: 0.0152 - val_mae: 0.0827 - val_root_mean_squared_error: 0.1232\n",
      "Epoch 44/100\n",
      "60/60 [==============================] - 1s 10ms/step - loss: 0.0103 - mae: 0.0628 - root_mean_squared_error: 0.1015 - val_loss: 0.0147 - val_mae: 0.0814 - val_root_mean_squared_error: 0.1212\n",
      "Epoch 45/100\n",
      "60/60 [==============================] - 1s 10ms/step - loss: 0.0101 - mae: 0.0623 - root_mean_squared_error: 0.1005 - val_loss: 0.0148 - val_mae: 0.0816 - val_root_mean_squared_error: 0.1216\n",
      "Epoch 46/100\n",
      "60/60 [==============================] - 1s 10ms/step - loss: 0.0099 - mae: 0.0619 - root_mean_squared_error: 0.0997 - val_loss: 0.0146 - val_mae: 0.0820 - val_root_mean_squared_error: 0.1210\n",
      "Epoch 47/100\n",
      "60/60 [==============================] - 1s 10ms/step - loss: 0.0097 - mae: 0.0610 - root_mean_squared_error: 0.0986 - val_loss: 0.0154 - val_mae: 0.0848 - val_root_mean_squared_error: 0.1241\n",
      "Epoch 48/100\n",
      "60/60 [==============================] - 1s 10ms/step - loss: 0.0096 - mae: 0.0611 - root_mean_squared_error: 0.0981 - val_loss: 0.0141 - val_mae: 0.0809 - val_root_mean_squared_error: 0.1189\n",
      "Epoch 49/100\n",
      "60/60 [==============================] - 1s 12ms/step - loss: 0.0094 - mae: 0.0603 - root_mean_squared_error: 0.0969 - val_loss: 0.0143 - val_mae: 0.0802 - val_root_mean_squared_error: 0.1196\n",
      "Epoch 50/100\n",
      "60/60 [==============================] - 1s 11ms/step - loss: 0.0092 - mae: 0.0595 - root_mean_squared_error: 0.0957 - val_loss: 0.0146 - val_mae: 0.0828 - val_root_mean_squared_error: 0.1208\n",
      "Epoch 51/100\n",
      "60/60 [==============================] - 1s 10ms/step - loss: 0.0090 - mae: 0.0594 - root_mean_squared_error: 0.0947 - val_loss: 0.0141 - val_mae: 0.0816 - val_root_mean_squared_error: 0.1189\n",
      "Epoch 52/100\n",
      "60/60 [==============================] - 1s 10ms/step - loss: 0.0088 - mae: 0.0591 - root_mean_squared_error: 0.0941 - val_loss: 0.0147 - val_mae: 0.0838 - val_root_mean_squared_error: 0.1214\n",
      "Epoch 53/100\n",
      "60/60 [==============================] - 1s 10ms/step - loss: 0.0084 - mae: 0.0580 - root_mean_squared_error: 0.0918 - val_loss: 0.0140 - val_mae: 0.0830 - val_root_mean_squared_error: 0.1185\n",
      "Epoch 54/100\n",
      "60/60 [==============================] - 1s 11ms/step - loss: 0.0081 - mae: 0.0563 - root_mean_squared_error: 0.0899 - val_loss: 0.0138 - val_mae: 0.0808 - val_root_mean_squared_error: 0.1174\n",
      "Epoch 55/100\n",
      "60/60 [==============================] - 1s 11ms/step - loss: 0.0078 - mae: 0.0557 - root_mean_squared_error: 0.0885 - val_loss: 0.0131 - val_mae: 0.0791 - val_root_mean_squared_error: 0.1143\n",
      "Epoch 56/100\n",
      "60/60 [==============================] - 1s 10ms/step - loss: 0.0076 - mae: 0.0552 - root_mean_squared_error: 0.0869 - val_loss: 0.0131 - val_mae: 0.0800 - val_root_mean_squared_error: 0.1145\n",
      "Epoch 57/100\n",
      "60/60 [==============================] - 1s 10ms/step - loss: 0.0073 - mae: 0.0546 - root_mean_squared_error: 0.0854 - val_loss: 0.0128 - val_mae: 0.0792 - val_root_mean_squared_error: 0.1132\n",
      "Epoch 58/100\n",
      "60/60 [==============================] - 1s 10ms/step - loss: 0.0071 - mae: 0.0543 - root_mean_squared_error: 0.0841 - val_loss: 0.0129 - val_mae: 0.0798 - val_root_mean_squared_error: 0.1136\n",
      "Epoch 59/100\n",
      "60/60 [==============================] - 1s 10ms/step - loss: 0.0070 - mae: 0.0540 - root_mean_squared_error: 0.0834 - val_loss: 0.0127 - val_mae: 0.0797 - val_root_mean_squared_error: 0.1129\n",
      "Epoch 60/100\n",
      "60/60 [==============================] - 1s 10ms/step - loss: 0.0069 - mae: 0.0538 - root_mean_squared_error: 0.0829 - val_loss: 0.0127 - val_mae: 0.0803 - val_root_mean_squared_error: 0.1126\n",
      "Epoch 61/100\n",
      "60/60 [==============================] - 1s 11ms/step - loss: 0.0067 - mae: 0.0534 - root_mean_squared_error: 0.0820 - val_loss: 0.0125 - val_mae: 0.0791 - val_root_mean_squared_error: 0.1119\n",
      "Epoch 62/100\n",
      "60/60 [==============================] - 1s 12ms/step - loss: 0.0067 - mae: 0.0534 - root_mean_squared_error: 0.0816 - val_loss: 0.0127 - val_mae: 0.0799 - val_root_mean_squared_error: 0.1126\n",
      "Epoch 63/100\n",
      "60/60 [==============================] - 1s 10ms/step - loss: 0.0066 - mae: 0.0532 - root_mean_squared_error: 0.0811 - val_loss: 0.0124 - val_mae: 0.0787 - val_root_mean_squared_error: 0.1116\n",
      "Epoch 64/100\n",
      "60/60 [==============================] - 1s 12ms/step - loss: 0.0065 - mae: 0.0527 - root_mean_squared_error: 0.0804 - val_loss: 0.0125 - val_mae: 0.0796 - val_root_mean_squared_error: 0.1116\n",
      "Epoch 65/100\n",
      "60/60 [==============================] - 1s 11ms/step - loss: 0.0064 - mae: 0.0526 - root_mean_squared_error: 0.0797 - val_loss: 0.0127 - val_mae: 0.0797 - val_root_mean_squared_error: 0.1126\n",
      "Epoch 66/100\n",
      "60/60 [==============================] - 1s 10ms/step - loss: 0.0062 - mae: 0.0522 - root_mean_squared_error: 0.0786 - val_loss: 0.0121 - val_mae: 0.0783 - val_root_mean_squared_error: 0.1101\n",
      "Epoch 67/100\n",
      "60/60 [==============================] - 1s 10ms/step - loss: 0.0060 - mae: 0.0518 - root_mean_squared_error: 0.0777 - val_loss: 0.0122 - val_mae: 0.0789 - val_root_mean_squared_error: 0.1103\n",
      "Epoch 68/100\n",
      "60/60 [==============================] - 1s 11ms/step - loss: 0.0060 - mae: 0.0517 - root_mean_squared_error: 0.0772 - val_loss: 0.0123 - val_mae: 0.0795 - val_root_mean_squared_error: 0.1109\n",
      "Epoch 69/100\n",
      "60/60 [==============================] - 1s 11ms/step - loss: 0.0059 - mae: 0.0513 - root_mean_squared_error: 0.0766 - val_loss: 0.0121 - val_mae: 0.0790 - val_root_mean_squared_error: 0.1099\n",
      "Epoch 70/100\n",
      "60/60 [==============================] - 1s 11ms/step - loss: 0.0058 - mae: 0.0509 - root_mean_squared_error: 0.0760 - val_loss: 0.0121 - val_mae: 0.0790 - val_root_mean_squared_error: 0.1100\n",
      "Epoch 71/100\n",
      "60/60 [==============================] - 1s 10ms/step - loss: 0.0058 - mae: 0.0510 - root_mean_squared_error: 0.0759 - val_loss: 0.0123 - val_mae: 0.0798 - val_root_mean_squared_error: 0.1108\n",
      "Epoch 72/100\n",
      "60/60 [==============================] - 1s 11ms/step - loss: 0.0056 - mae: 0.0498 - root_mean_squared_error: 0.0748 - val_loss: 0.0123 - val_mae: 0.0792 - val_root_mean_squared_error: 0.1108\n",
      "Epoch 73/100\n",
      "60/60 [==============================] - 1s 10ms/step - loss: 0.0055 - mae: 0.0496 - root_mean_squared_error: 0.0742 - val_loss: 0.0122 - val_mae: 0.0789 - val_root_mean_squared_error: 0.1105\n",
      "Epoch 74/100\n",
      "60/60 [==============================] - 1s 10ms/step - loss: 0.0054 - mae: 0.0495 - root_mean_squared_error: 0.0738 - val_loss: 0.0121 - val_mae: 0.0793 - val_root_mean_squared_error: 0.1100\n",
      "Epoch 75/100\n",
      "60/60 [==============================] - 1s 10ms/step - loss: 0.0054 - mae: 0.0492 - root_mean_squared_error: 0.0734 - val_loss: 0.0122 - val_mae: 0.0797 - val_root_mean_squared_error: 0.1105\n",
      "Epoch 76/100\n",
      "60/60 [==============================] - 1s 10ms/step - loss: 0.0053 - mae: 0.0492 - root_mean_squared_error: 0.0731 - val_loss: 0.0120 - val_mae: 0.0791 - val_root_mean_squared_error: 0.1094\n",
      "Epoch 77/100\n",
      "60/60 [==============================] - 1s 10ms/step - loss: 0.0052 - mae: 0.0490 - root_mean_squared_error: 0.0724 - val_loss: 0.0121 - val_mae: 0.0794 - val_root_mean_squared_error: 0.1100\n",
      "Epoch 78/100\n",
      "60/60 [==============================] - 1s 11ms/step - loss: 0.0052 - mae: 0.0487 - root_mean_squared_error: 0.0719 - val_loss: 0.0120 - val_mae: 0.0796 - val_root_mean_squared_error: 0.1095\n",
      "Epoch 79/100\n",
      "60/60 [==============================] - 1s 10ms/step - loss: 0.0050 - mae: 0.0485 - root_mean_squared_error: 0.0710 - val_loss: 0.0120 - val_mae: 0.0791 - val_root_mean_squared_error: 0.1096\n",
      "Epoch 80/100\n",
      "60/60 [==============================] - 1s 11ms/step - loss: 0.0050 - mae: 0.0483 - root_mean_squared_error: 0.0707 - val_loss: 0.0121 - val_mae: 0.0796 - val_root_mean_squared_error: 0.1100\n",
      "Epoch 81/100\n",
      "60/60 [==============================] - 1s 12ms/step - loss: 0.0050 - mae: 0.0484 - root_mean_squared_error: 0.0704 - val_loss: 0.0121 - val_mae: 0.0799 - val_root_mean_squared_error: 0.1098\n",
      "Epoch 82/100\n",
      "60/60 [==============================] - 1s 10ms/step - loss: 0.0048 - mae: 0.0476 - root_mean_squared_error: 0.0695 - val_loss: 0.0119 - val_mae: 0.0793 - val_root_mean_squared_error: 0.1092\n",
      "Epoch 83/100\n",
      "60/60 [==============================] - 1s 10ms/step - loss: 0.0048 - mae: 0.0475 - root_mean_squared_error: 0.0694 - val_loss: 0.0120 - val_mae: 0.0796 - val_root_mean_squared_error: 0.1094\n",
      "Epoch 84/100\n",
      "60/60 [==============================] - 1s 11ms/step - loss: 0.0048 - mae: 0.0474 - root_mean_squared_error: 0.0693 - val_loss: 0.0121 - val_mae: 0.0800 - val_root_mean_squared_error: 0.1099\n",
      "Epoch 85/100\n",
      "60/60 [==============================] - 1s 10ms/step - loss: 0.0048 - mae: 0.0473 - root_mean_squared_error: 0.0692 - val_loss: 0.0119 - val_mae: 0.0794 - val_root_mean_squared_error: 0.1092\n",
      "Epoch 86/100\n",
      "60/60 [==============================] - 1s 10ms/step - loss: 0.0048 - mae: 0.0473 - root_mean_squared_error: 0.0691 - val_loss: 0.0120 - val_mae: 0.0799 - val_root_mean_squared_error: 0.1097\n",
      "Epoch 87/100\n",
      "60/60 [==============================] - 1s 10ms/step - loss: 0.0047 - mae: 0.0471 - root_mean_squared_error: 0.0688 - val_loss: 0.0120 - val_mae: 0.0797 - val_root_mean_squared_error: 0.1094\n",
      "Epoch 88/100\n",
      "60/60 [==============================] - 1s 10ms/step - loss: 0.0047 - mae: 0.0470 - root_mean_squared_error: 0.0687 - val_loss: 0.0119 - val_mae: 0.0796 - val_root_mean_squared_error: 0.1092\n",
      "Epoch 89/100\n",
      "60/60 [==============================] - 1s 10ms/step - loss: 0.0047 - mae: 0.0470 - root_mean_squared_error: 0.0686 - val_loss: 0.0119 - val_mae: 0.0796 - val_root_mean_squared_error: 0.1092\n",
      "Epoch 90/100\n",
      "60/60 [==============================] - 1s 11ms/step - loss: 0.0047 - mae: 0.0469 - root_mean_squared_error: 0.0685 - val_loss: 0.0120 - val_mae: 0.0798 - val_root_mean_squared_error: 0.1094\n",
      "Epoch 91/100\n",
      "60/60 [==============================] - 1s 10ms/step - loss: 0.0047 - mae: 0.0469 - root_mean_squared_error: 0.0684 - val_loss: 0.0120 - val_mae: 0.0800 - val_root_mean_squared_error: 0.1095\n",
      "Epoch 92/100\n",
      "60/60 [==============================] - 1s 10ms/step - loss: 0.0047 - mae: 0.0467 - root_mean_squared_error: 0.0682 - val_loss: 0.0120 - val_mae: 0.0798 - val_root_mean_squared_error: 0.1095\n",
      "Epoch 93/100\n",
      "60/60 [==============================] - 1s 10ms/step - loss: 0.0046 - mae: 0.0467 - root_mean_squared_error: 0.0682 - val_loss: 0.0120 - val_mae: 0.0797 - val_root_mean_squared_error: 0.1095\n",
      "Epoch 94/100\n",
      "60/60 [==============================] - 1s 10ms/step - loss: 0.0046 - mae: 0.0467 - root_mean_squared_error: 0.0682 - val_loss: 0.0120 - val_mae: 0.0797 - val_root_mean_squared_error: 0.1095\n",
      "Epoch 95/100\n",
      "60/60 [==============================] - 1s 10ms/step - loss: 0.0046 - mae: 0.0466 - root_mean_squared_error: 0.0681 - val_loss: 0.0120 - val_mae: 0.0797 - val_root_mean_squared_error: 0.1094\n",
      "Epoch 96/100\n",
      "60/60 [==============================] - 1s 11ms/step - loss: 0.0046 - mae: 0.0466 - root_mean_squared_error: 0.0681 - val_loss: 0.0120 - val_mae: 0.0798 - val_root_mean_squared_error: 0.1095\n",
      "Epoch 97/100\n",
      "60/60 [==============================] - 1s 10ms/step - loss: 0.0046 - mae: 0.0465 - root_mean_squared_error: 0.0681 - val_loss: 0.0120 - val_mae: 0.0797 - val_root_mean_squared_error: 0.1094\n",
      "Epoch 98/100\n",
      "60/60 [==============================] - 1s 12ms/step - loss: 0.0046 - mae: 0.0465 - root_mean_squared_error: 0.0680 - val_loss: 0.0120 - val_mae: 0.0797 - val_root_mean_squared_error: 0.1093\n",
      "Epoch 99/100\n",
      "60/60 [==============================] - 1s 10ms/step - loss: 0.0046 - mae: 0.0465 - root_mean_squared_error: 0.0680 - val_loss: 0.0119 - val_mae: 0.0796 - val_root_mean_squared_error: 0.1093\n"
     ]
    }
   ],
   "source": [
    "history = model.fit(\n",
    "    x = X_train,\n",
    "    y = y_train,\n",
    "    validation_split = .1,\n",
    "    batch_size = batch_size,\n",
    "    epochs = epochs,\n",
    "    callbacks = [\n",
    "        tfk.callbacks.EarlyStopping(monitor='val_loss', mode='min', patience=10, restore_best_weights=True),\n",
    "        tfk.callbacks.ReduceLROnPlateau(monitor='val_loss', mode='min', patience=5, factor=0.5, min_lr=1e-5)\n",
    "    ]\n",
    ").history"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 15,
   "id": "d22633ba",
   "metadata": {
    "execution": {
     "iopub.execute_input": "2022-01-20T15:10:04.677539Z",
     "iopub.status.busy": "2022-01-20T15:10:04.670365Z",
     "iopub.status.idle": "2022-01-20T15:10:07.070760Z",
     "shell.execute_reply": "2022-01-20T15:10:07.071176Z"
    },
    "papermill": {
     "duration": 2.729525,
     "end_time": "2022-01-20T15:10:07.071319",
     "exception": false,
     "start_time": "2022-01-20T15:10:04.341794",
     "status": "completed"
    },
    "tags": []
   },
   "outputs": [
    {
     "data": {
      "image/png": "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\n",
      "text/plain": [
       "<Figure size 1080x360 with 1 Axes>"
      ]
     },
     "metadata": {
      "needs_background": "light"
     },
     "output_type": "display_data"
    }
   ],
   "source": [
    "plt.figure(figsize=(15,5))\n",
    "plt.plot(history['loss'], label='Training loss', alpha=.8, color='#F7D426')\n",
    "plt.plot(history['val_loss'], label='Validation loss', alpha=.8, color='#0E8729')\n",
    "plt.title('Loss')\n",
    "plt.legend(loc='lower right')\n",
    "plt.grid(alpha=.3)\n",
    "plt.savefig('Convolutional-graph.png')\n",
    "plt.show()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 16,
   "id": "155aefa6",
   "metadata": {
    "execution": {
     "iopub.execute_input": "2022-01-20T15:10:07.712394Z",
     "iopub.status.busy": "2022-01-20T15:10:07.711844Z",
     "iopub.status.idle": "2022-01-20T15:10:10.113907Z",
     "shell.execute_reply": "2022-01-20T15:10:10.112911Z",
     "shell.execute_reply.started": "2021-12-21T10:50:47.03173Z"
    },
    "papermill": {
     "duration": 2.725336,
     "end_time": "2022-01-20T15:10:10.114069",
     "exception": false,
     "start_time": "2022-01-20T15:10:07.388733",
     "status": "completed"
    },
    "tags": []
   },
   "outputs": [
    {
     "name": "stderr",
     "output_type": "stream",
     "text": [
      "2022-01-20 15:10:08.172893: W tensorflow/python/util/util.cc:348] Sets are not currently considered sequences, but this may change in the future, so consider avoiding using them.\n"
     ]
    }
   ],
   "source": [
    "model.save('Convolutional')"
   ]
  }
 ],
 "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": 109.403226,
   "end_time": "2022-01-20T15:10:14.171988",
   "environment_variables": {},
   "exception": null,
   "input_path": "__notebook__.ipynb",
   "output_path": "__notebook__.ipynb",
   "parameters": {},
   "start_time": "2022-01-20T15:08:24.768762",
   "version": "2.3.3"
  }
 },
 "nbformat": 4,
 "nbformat_minor": 5
}