knn.ipynb

{
 "cells": [
  {
   "cell_type": "code",
   "execution_count": 1,
   "metadata": {},
   "outputs": [],
   "source": [
    "# mengimportkan berbagai library yang di perlukan untuk memanipulasi\n",
    "# gambar, pemrosesan data, pembuatan model, visualisasi, dan evaluasi model.\n",
    "\n",
    "import tensorflow as tf\n",
    "import os\n",
    "import numpy as np\n",
    "import pandas as pd\n",
    "import cv2\n",
    "import matplotlib.pyplot as plt\n",
    "import pickle\n",
    "from keras.applications.vgg16 import VGG16, preprocess_input\n",
    "from keras.models import Model\n",
    "from sklearn.neighbors import KNeighborsClassifier\n",
    "from sklearn.model_selection import train_test_split, GridSearchCV, KFold\n",
    "from sklearn.metrics import accuracy_score, confusion_matrix, ConfusionMatrixDisplay, classification_report, precision_score, recall_score, f1_score\n",
    "from tensorflow.keras.preprocessing.image import img_to_array\n",
    "from sklearn.decomposition import PCA\n",
    "from sklearn.preprocessing import LabelEncoder\n",
    "from sklearn.metrics import roc_curve, auc\n",
    "from tensorflow.keras.preprocessing.image import ImageDataGenerator, img_to_array, load_img\n",
    "# import shutil\n",
    "# from sklearn.utils import resample\n",
    "# import seaborn as sns\n"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 2,
   "metadata": {},
   "outputs": [],
   "source": [
    "# membuat definisi fungsi untuk memuat dan memproses gambar\n",
    "\n",
    "img_width, img_height = 128, 128\n",
    "img_size= (img_width, img_height)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 3,
   "metadata": {},
   "outputs": [],
   "source": [
    "# Fungsi untuk memuat dan memproses gambar dengan mengubah ukurannya\n",
    "# dan menormalkan nilainya\n",
    "\n",
    "def load_and_preprocess_image(image_path, img_size=(img_width, img_height)):\n",
    "    img = cv2.imread(image_path)\n",
    "    img_resized = cv2.resize(img, img_size)\n",
    "    img_array = img_to_array(img_resized)\n",
    "    img_array = np.expand_dims(img_array, axis=0)\n",
    "    img_array = preprocess_input(img_array)\n",
    "    return img_array"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 4,
   "metadata": {},
   "outputs": [],
   "source": [
    "# Fungsi untuk mengekstrak fitur menggunakan VGG16\n",
    "def extract_features(model, image_path, img_size):\n",
    "    img_array = load_and_preprocess_image(image_path, img_size)\n",
    "    features = model.predict(img_array)\n",
    "    return features.flatten()\n",
    "\n"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 5,
   "metadata": {},
   "outputs": [],
   "source": [
    "# memuat dataset dan mengektraski fitur\n",
    "\n",
    "base_dir = \"D:\\\\penelitian arya\\\\dataset penelitian\\\\Train\"\n",
    "img_size = (img_width, img_height) \n",
    "\n",
    "# Memuat model VGG16 pra-terlatih\n",
    "base_model = VGG16(weights='imagenet', include_top=False, input_shape=(128, 128, 3))\n",
    "feature_extractor= Model(inputs=base_model.input, outputs=base_model.output)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 6,
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "\u001b[1m1/1\u001b[0m \u001b[32m━━━━━━━━━━━━━━━━━━━━\u001b[0m\u001b[37m\u001b[0m \u001b[1m0s\u001b[0m 265ms/step\n",
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      "\u001b[1m1/1\u001b[0m \u001b[32m━━━━━━━━━━━━━━━━━━━━\u001b[0m\u001b[37m\u001b[0m \u001b[1m0s\u001b[0m 61ms/step\n",
      "\u001b[1m1/1\u001b[0m \u001b[32m━━━━━━━━━━━━━━━━━━━━\u001b[0m\u001b[37m\u001b[0m \u001b[1m0s\u001b[0m 47ms/step\n",
      "\u001b[1m1/1\u001b[0m \u001b[32m━━━━━━━━━━━━━━━━━━━━\u001b[0m\u001b[37m\u001b[0m \u001b[1m0s\u001b[0m 64ms/step\n",
      "\u001b[1m1/1\u001b[0m \u001b[32m━━━━━━━━━━━━━━━━━━━━\u001b[0m\u001b[37m\u001b[0m \u001b[1m0s\u001b[0m 64ms/step\n",
      "\u001b[1m1/1\u001b[0m \u001b[32m━━━━━━━━━━━━━━━━━━━━\u001b[0m\u001b[37m\u001b[0m \u001b[1m0s\u001b[0m 69ms/step\n",
      "\u001b[1m1/1\u001b[0m \u001b[32m━━━━━━━━━━━━━━━━━━━━\u001b[0m\u001b[37m\u001b[0m \u001b[1m0s\u001b[0m 56ms/step\n",
      "\u001b[1m1/1\u001b[0m \u001b[32m━━━━━━━━━━━━━━━━━━━━\u001b[0m\u001b[37m\u001b[0m \u001b[1m0s\u001b[0m 61ms/step\n",
      "\u001b[1m1/1\u001b[0m \u001b[32m━━━━━━━━━━━━━━━━━━━━\u001b[0m\u001b[37m\u001b[0m \u001b[1m0s\u001b[0m 56ms/step\n",
      "\u001b[1m1/1\u001b[0m \u001b[32m━━━━━━━━━━━━━━━━━━━━\u001b[0m\u001b[37m\u001b[0m \u001b[1m0s\u001b[0m 47ms/step\n",
      "\u001b[1m1/1\u001b[0m \u001b[32m━━━━━━━━━━━━━━━━━━━━\u001b[0m\u001b[37m\u001b[0m \u001b[1m0s\u001b[0m 65ms/step\n",
      "\u001b[1m1/1\u001b[0m \u001b[32m━━━━━━━━━━━━━━━━━━━━\u001b[0m\u001b[37m\u001b[0m \u001b[1m0s\u001b[0m 66ms/step\n",
      "\u001b[1m1/1\u001b[0m \u001b[32m━━━━━━━━━━━━━━━━━━━━\u001b[0m\u001b[37m\u001b[0m \u001b[1m0s\u001b[0m 47ms/step\n",
      "\u001b[1m1/1\u001b[0m \u001b[32m━━━━━━━━━━━━━━━━━━━━\u001b[0m\u001b[37m\u001b[0m \u001b[1m0s\u001b[0m 60ms/step\n",
      "\u001b[1m1/1\u001b[0m \u001b[32m━━━━━━━━━━━━━━━━━━━━\u001b[0m\u001b[37m\u001b[0m \u001b[1m0s\u001b[0m 75ms/step\n",
      "\u001b[1m1/1\u001b[0m \u001b[32m━━━━━━━━━━━━━━━━━━━━\u001b[0m\u001b[37m\u001b[0m \u001b[1m0s\u001b[0m 53ms/step\n",
      "\u001b[1m1/1\u001b[0m \u001b[32m━━━━━━━━━━━━━━━━━━━━\u001b[0m\u001b[37m\u001b[0m \u001b[1m0s\u001b[0m 47ms/step\n",
      "\u001b[1m1/1\u001b[0m \u001b[32m━━━━━━━━━━━━━━━━━━━━\u001b[0m\u001b[37m\u001b[0m \u001b[1m0s\u001b[0m 62ms/step\n",
      "\u001b[1m1/1\u001b[0m \u001b[32m━━━━━━━━━━━━━━━━━━━━\u001b[0m\u001b[37m\u001b[0m \u001b[1m0s\u001b[0m 62ms/step\n",
      "\u001b[1m1/1\u001b[0m \u001b[32m━━━━━━━━━━━━━━━━━━━━\u001b[0m\u001b[37m\u001b[0m \u001b[1m0s\u001b[0m 53ms/step\n",
      "\u001b[1m1/1\u001b[0m \u001b[32m━━━━━━━━━━━━━━━━━━━━\u001b[0m\u001b[37m\u001b[0m \u001b[1m0s\u001b[0m 47ms/step\n",
      "\u001b[1m1/1\u001b[0m \u001b[32m━━━━━━━━━━━━━━━━━━━━\u001b[0m\u001b[37m\u001b[0m \u001b[1m0s\u001b[0m 55ms/step\n",
      "\u001b[1m1/1\u001b[0m \u001b[32m━━━━━━━━━━━━━━━━━━━━\u001b[0m\u001b[37m\u001b[0m \u001b[1m0s\u001b[0m 47ms/step\n",
      "\u001b[1m1/1\u001b[0m \u001b[32m━━━━━━━━━━━━━━━━━━━━\u001b[0m\u001b[37m\u001b[0m \u001b[1m0s\u001b[0m 65ms/step\n",
      "\u001b[1m1/1\u001b[0m \u001b[32m━━━━━━━━━━━━━━━━━━━━\u001b[0m\u001b[37m\u001b[0m \u001b[1m0s\u001b[0m 49ms/step\n",
      "\u001b[1m1/1\u001b[0m \u001b[32m━━━━━━━━━━━━━━━━━━━━\u001b[0m\u001b[37m\u001b[0m \u001b[1m0s\u001b[0m 67ms/step\n",
      "\u001b[1m1/1\u001b[0m \u001b[32m━━━━━━━━━━━━━━━━━━━━\u001b[0m\u001b[37m\u001b[0m \u001b[1m0s\u001b[0m 58ms/step\n",
      "\u001b[1m1/1\u001b[0m \u001b[32m━━━━━━━━━━━━━━━━━━━━\u001b[0m\u001b[37m\u001b[0m \u001b[1m0s\u001b[0m 46ms/step\n",
      "\u001b[1m1/1\u001b[0m \u001b[32m━━━━━━━━━━━━━━━━━━━━\u001b[0m\u001b[37m\u001b[0m \u001b[1m0s\u001b[0m 62ms/step\n",
      "\u001b[1m1/1\u001b[0m \u001b[32m━━━━━━━━━━━━━━━━━━━━\u001b[0m\u001b[37m\u001b[0m \u001b[1m0s\u001b[0m 68ms/step\n",
      "\u001b[1m1/1\u001b[0m \u001b[32m━━━━━━━━━━━━━━━━━━━━\u001b[0m\u001b[37m\u001b[0m \u001b[1m0s\u001b[0m 61ms/step\n",
      "\u001b[1m1/1\u001b[0m \u001b[32m━━━━━━━━━━━━━━━━━━━━\u001b[0m\u001b[37m\u001b[0m \u001b[1m0s\u001b[0m 58ms/step\n",
      "\u001b[1m1/1\u001b[0m \u001b[32m━━━━━━━━━━━━━━━━━━━━\u001b[0m\u001b[37m\u001b[0m \u001b[1m0s\u001b[0m 56ms/step\n",
      "\u001b[1m1/1\u001b[0m \u001b[32m━━━━━━━━━━━━━━━━━━━━\u001b[0m\u001b[37m\u001b[0m \u001b[1m0s\u001b[0m 64ms/step\n",
      "\u001b[1m1/1\u001b[0m \u001b[32m━━━━━━━━━━━━━━━━━━━━\u001b[0m\u001b[37m\u001b[0m \u001b[1m0s\u001b[0m 47ms/step\n",
      "\u001b[1m1/1\u001b[0m \u001b[32m━━━━━━━━━━━━━━━━━━━━\u001b[0m\u001b[37m\u001b[0m \u001b[1m0s\u001b[0m 62ms/step\n",
      "\u001b[1m1/1\u001b[0m \u001b[32m━━━━━━━━━━━━━━━━━━━━\u001b[0m\u001b[37m\u001b[0m \u001b[1m0s\u001b[0m 53ms/step\n",
      "\u001b[1m1/1\u001b[0m \u001b[32m━━━━━━━━━━━━━━━━━━━━\u001b[0m\u001b[37m\u001b[0m \u001b[1m0s\u001b[0m 47ms/step\n",
      "\u001b[1m1/1\u001b[0m \u001b[32m━━━━━━━━━━━━━━━━━━━━\u001b[0m\u001b[37m\u001b[0m \u001b[1m0s\u001b[0m 54ms/step\n",
      "\u001b[1m1/1\u001b[0m \u001b[32m━━━━━━━━━━━━━━━━━━━━\u001b[0m\u001b[37m\u001b[0m \u001b[1m0s\u001b[0m 59ms/step\n",
      "\u001b[1m1/1\u001b[0m \u001b[32m━━━━━━━━━━━━━━━━━━━━\u001b[0m\u001b[37m\u001b[0m \u001b[1m0s\u001b[0m 68ms/step\n",
      "\u001b[1m1/1\u001b[0m \u001b[32m━━━━━━━━━━━━━━━━━━━━\u001b[0m\u001b[37m\u001b[0m \u001b[1m0s\u001b[0m 66ms/step\n",
      "\u001b[1m1/1\u001b[0m \u001b[32m━━━━━━━━━━━━━━━━━━━━\u001b[0m\u001b[37m\u001b[0m \u001b[1m0s\u001b[0m 56ms/step\n",
      "\u001b[1m1/1\u001b[0m \u001b[32m━━━━━━━━━━━━━━━━━━━━\u001b[0m\u001b[37m\u001b[0m \u001b[1m0s\u001b[0m 66ms/step\n",
      "\u001b[1m1/1\u001b[0m \u001b[32m━━━━━━━━━━━━━━━━━━━━\u001b[0m\u001b[37m\u001b[0m \u001b[1m0s\u001b[0m 68ms/step\n",
      "\u001b[1m1/1\u001b[0m \u001b[32m━━━━━━━━━━━━━━━━━━━━\u001b[0m\u001b[37m\u001b[0m \u001b[1m0s\u001b[0m 57ms/step\n",
      "\u001b[1m1/1\u001b[0m \u001b[32m━━━━━━━━━━━━━━━━━━━━\u001b[0m\u001b[37m\u001b[0m \u001b[1m0s\u001b[0m 55ms/step\n",
      "\u001b[1m1/1\u001b[0m \u001b[32m━━━━━━━━━━━━━━━━━━━━\u001b[0m\u001b[37m\u001b[0m \u001b[1m0s\u001b[0m 62ms/step\n",
      "\u001b[1m1/1\u001b[0m \u001b[32m━━━━━━━━━━━━━━━━━━━━\u001b[0m\u001b[37m\u001b[0m \u001b[1m0s\u001b[0m 49ms/step\n",
      "\u001b[1m1/1\u001b[0m \u001b[32m━━━━━━━━━━━━━━━━━━━━\u001b[0m\u001b[37m\u001b[0m \u001b[1m0s\u001b[0m 62ms/step\n",
      "\u001b[1m1/1\u001b[0m \u001b[32m━━━━━━━━━━━━━━━━━━━━\u001b[0m\u001b[37m\u001b[0m \u001b[1m0s\u001b[0m 53ms/step\n",
      "\u001b[1m1/1\u001b[0m \u001b[32m━━━━━━━━━━━━━━━━━━━━\u001b[0m\u001b[37m\u001b[0m \u001b[1m0s\u001b[0m 56ms/step\n",
      "\u001b[1m1/1\u001b[0m \u001b[32m━━━━━━━━━━━━━━━━━━━━\u001b[0m\u001b[37m\u001b[0m \u001b[1m0s\u001b[0m 53ms/step\n",
      "\u001b[1m1/1\u001b[0m \u001b[32m━━━━━━━━━━━━━━━━━━━━\u001b[0m\u001b[37m\u001b[0m \u001b[1m0s\u001b[0m 53ms/step\n",
      "\u001b[1m1/1\u001b[0m \u001b[32m━━━━━━━━━━━━━━━━━━━━\u001b[0m\u001b[37m\u001b[0m \u001b[1m0s\u001b[0m 62ms/step\n",
      "\u001b[1m1/1\u001b[0m \u001b[32m━━━━━━━━━━━━━━━━━━━━\u001b[0m\u001b[37m\u001b[0m \u001b[1m0s\u001b[0m 47ms/step\n",
      "\u001b[1m1/1\u001b[0m \u001b[32m━━━━━━━━━━━━━━━━━━━━\u001b[0m\u001b[37m\u001b[0m \u001b[1m0s\u001b[0m 62ms/step\n",
      "\u001b[1m1/1\u001b[0m \u001b[32m━━━━━━━━━━━━━━━━━━━━\u001b[0m\u001b[37m\u001b[0m \u001b[1m0s\u001b[0m 71ms/step\n",
      "\u001b[1m1/1\u001b[0m \u001b[32m━━━━━━━━━━━━━━━━━━━━\u001b[0m\u001b[37m\u001b[0m \u001b[1m0s\u001b[0m 72ms/step\n",
      "\u001b[1m1/1\u001b[0m \u001b[32m━━━━━━━━━━━━━━━━━━━━\u001b[0m\u001b[37m\u001b[0m \u001b[1m0s\u001b[0m 67ms/step\n",
      "\u001b[1m1/1\u001b[0m \u001b[32m━━━━━━━━━━━━━━━━━━━━\u001b[0m\u001b[37m\u001b[0m \u001b[1m0s\u001b[0m 70ms/step\n",
      "\u001b[1m1/1\u001b[0m \u001b[32m━━━━━━━━━━━━━━━━━━━━\u001b[0m\u001b[37m\u001b[0m \u001b[1m0s\u001b[0m 54ms/step\n",
      "\u001b[1m1/1\u001b[0m \u001b[32m━━━━━━━━━━━━━━━━━━━━\u001b[0m\u001b[37m\u001b[0m \u001b[1m0s\u001b[0m 58ms/step\n",
      "\u001b[1m1/1\u001b[0m \u001b[32m━━━━━━━━━━━━━━━━━━━━\u001b[0m\u001b[37m\u001b[0m \u001b[1m0s\u001b[0m 65ms/step\n",
      "\u001b[1m1/1\u001b[0m \u001b[32m━━━━━━━━━━━━━━━━━━━━\u001b[0m\u001b[37m\u001b[0m \u001b[1m0s\u001b[0m 64ms/step\n",
      "\u001b[1m1/1\u001b[0m \u001b[32m━━━━━━━━━━━━━━━━━━━━\u001b[0m\u001b[37m\u001b[0m \u001b[1m0s\u001b[0m 55ms/step\n",
      "\u001b[1m1/1\u001b[0m \u001b[32m━━━━━━━━━━━━━━━━━━━━\u001b[0m\u001b[37m\u001b[0m \u001b[1m0s\u001b[0m 63ms/step\n",
      "\u001b[1m1/1\u001b[0m \u001b[32m━━━━━━━━━━━━━━━━━━━━\u001b[0m\u001b[37m\u001b[0m \u001b[1m0s\u001b[0m 56ms/step\n",
      "\u001b[1m1/1\u001b[0m \u001b[32m━━━━━━━━━━━━━━━━━━━━\u001b[0m\u001b[37m\u001b[0m \u001b[1m0s\u001b[0m 47ms/step\n",
      "\u001b[1m1/1\u001b[0m \u001b[32m━━━━━━━━━━━━━━━━━━━━\u001b[0m\u001b[37m\u001b[0m \u001b[1m0s\u001b[0m 70ms/step\n",
      "\u001b[1m1/1\u001b[0m \u001b[32m━━━━━━━━━━━━━━━━━━━━\u001b[0m\u001b[37m\u001b[0m \u001b[1m0s\u001b[0m 47ms/step\n",
      "\u001b[1m1/1\u001b[0m \u001b[32m━━━━━━━━━━━━━━━━━━━━\u001b[0m\u001b[37m\u001b[0m \u001b[1m0s\u001b[0m 59ms/step\n",
      "\u001b[1m1/1\u001b[0m \u001b[32m━━━━━━━━━━━━━━━━━━━━\u001b[0m\u001b[37m\u001b[0m \u001b[1m0s\u001b[0m 47ms/step\n",
      "\u001b[1m1/1\u001b[0m \u001b[32m━━━━━━━━━━━━━━━━━━━━\u001b[0m\u001b[37m\u001b[0m \u001b[1m0s\u001b[0m 47ms/step\n",
      "\u001b[1m1/1\u001b[0m \u001b[32m━━━━━━━━━━━━━━━━━━━━\u001b[0m\u001b[37m\u001b[0m \u001b[1m0s\u001b[0m 48ms/step\n",
      "\u001b[1m1/1\u001b[0m \u001b[32m━━━━━━━━━━━━━━━━━━━━\u001b[0m\u001b[37m\u001b[0m \u001b[1m0s\u001b[0m 67ms/step\n",
      "\u001b[1m1/1\u001b[0m \u001b[32m━━━━━━━━━━━━━━━━━━━━\u001b[0m\u001b[37m\u001b[0m \u001b[1m0s\u001b[0m 57ms/step\n",
      "\u001b[1m1/1\u001b[0m \u001b[32m━━━━━━━━━━━━━━━━━━━━\u001b[0m\u001b[37m\u001b[0m \u001b[1m0s\u001b[0m 47ms/step\n",
      "\u001b[1m1/1\u001b[0m \u001b[32m━━━━━━━━━━━━━━━━━━━━\u001b[0m\u001b[37m\u001b[0m \u001b[1m0s\u001b[0m 55ms/step\n",
      "\u001b[1m1/1\u001b[0m \u001b[32m━━━━━━━━━━━━━━━━━━━━\u001b[0m\u001b[37m\u001b[0m \u001b[1m0s\u001b[0m 47ms/step\n",
      "\u001b[1m1/1\u001b[0m \u001b[32m━━━━━━━━━━━━━━━━━━━━\u001b[0m\u001b[37m\u001b[0m \u001b[1m0s\u001b[0m 62ms/step\n",
      "\u001b[1m1/1\u001b[0m \u001b[32m━━━━━━━━━━━━━━━━━━━━\u001b[0m\u001b[37m\u001b[0m \u001b[1m0s\u001b[0m 60ms/step\n",
      "\u001b[1m1/1\u001b[0m \u001b[32m━━━━━━━━━━━━━━━━━━━━\u001b[0m\u001b[37m\u001b[0m \u001b[1m0s\u001b[0m 48ms/step\n",
      "\u001b[1m1/1\u001b[0m \u001b[32m━━━━━━━━━━━━━━━━━━━━\u001b[0m\u001b[37m\u001b[0m \u001b[1m0s\u001b[0m 62ms/step\n",
      "\u001b[1m1/1\u001b[0m \u001b[32m━━━━━━━━━━━━━━━━━━━━\u001b[0m\u001b[37m\u001b[0m \u001b[1m0s\u001b[0m 47ms/step\n",
      "\u001b[1m1/1\u001b[0m \u001b[32m━━━━━━━━━━━━━━━━━━━━\u001b[0m\u001b[37m\u001b[0m \u001b[1m0s\u001b[0m 62ms/step\n",
      "\u001b[1m1/1\u001b[0m \u001b[32m━━━━━━━━━━━━━━━━━━━━\u001b[0m\u001b[37m\u001b[0m \u001b[1m0s\u001b[0m 47ms/step\n",
      "\u001b[1m1/1\u001b[0m \u001b[32m━━━━━━━━━━━━━━━━━━━━\u001b[0m\u001b[37m\u001b[0m \u001b[1m0s\u001b[0m 76ms/step\n",
      "\u001b[1m1/1\u001b[0m \u001b[32m━━━━━━━━━━━━━━━━━━━━\u001b[0m\u001b[37m\u001b[0m \u001b[1m0s\u001b[0m 60ms/step\n",
      "\u001b[1m1/1\u001b[0m \u001b[32m━━━━━━━━━━━━━━━━━━━━\u001b[0m\u001b[37m\u001b[0m \u001b[1m0s\u001b[0m 52ms/step\n",
      "\u001b[1m1/1\u001b[0m \u001b[32m━━━━━━━━━━━━━━━━━━━━\u001b[0m\u001b[37m\u001b[0m \u001b[1m0s\u001b[0m 47ms/step\n",
      "\u001b[1m1/1\u001b[0m \u001b[32m━━━━━━━━━━━━━━━━━━━━\u001b[0m\u001b[37m\u001b[0m \u001b[1m0s\u001b[0m 62ms/step\n",
      "\u001b[1m1/1\u001b[0m \u001b[32m━━━━━━━━━━━━━━━━━━━━\u001b[0m\u001b[37m\u001b[0m \u001b[1m0s\u001b[0m 62ms/step\n",
      "\u001b[1m1/1\u001b[0m \u001b[32m━━━━━━━━━━━━━━━━━━━━\u001b[0m\u001b[37m\u001b[0m \u001b[1m0s\u001b[0m 58ms/step\n",
      "\u001b[1m1/1\u001b[0m \u001b[32m━━━━━━━━━━━━━━━━━━━━\u001b[0m\u001b[37m\u001b[0m \u001b[1m0s\u001b[0m 52ms/step\n",
      "\u001b[1m1/1\u001b[0m \u001b[32m━━━━━━━━━━━━━━━━━━━━\u001b[0m\u001b[37m\u001b[0m \u001b[1m0s\u001b[0m 60ms/step\n",
      "\u001b[1m1/1\u001b[0m \u001b[32m━━━━━━━━━━━━━━━━━━━━\u001b[0m\u001b[37m\u001b[0m \u001b[1m0s\u001b[0m 60ms/step\n",
      "\u001b[1m1/1\u001b[0m \u001b[32m━━━━━━━━━━━━━━━━━━━━\u001b[0m\u001b[37m\u001b[0m \u001b[1m0s\u001b[0m 58ms/step\n",
      "\u001b[1m1/1\u001b[0m \u001b[32m━━━━━━━━━━━━━━━━━━━━\u001b[0m\u001b[37m\u001b[0m \u001b[1m0s\u001b[0m 55ms/step\n",
      "\u001b[1m1/1\u001b[0m \u001b[32m━━━━━━━━━━━━━━━━━━━━\u001b[0m\u001b[37m\u001b[0m \u001b[1m0s\u001b[0m 69ms/step\n",
      "\u001b[1m1/1\u001b[0m \u001b[32m━━━━━━━━━━━━━━━━━━━━\u001b[0m\u001b[37m\u001b[0m \u001b[1m0s\u001b[0m 47ms/step\n",
      "\u001b[1m1/1\u001b[0m \u001b[32m━━━━━━━━━━━━━━━━━━━━\u001b[0m\u001b[37m\u001b[0m \u001b[1m0s\u001b[0m 47ms/step\n",
      "\u001b[1m1/1\u001b[0m \u001b[32m━━━━━━━━━━━━━━━━━━━━\u001b[0m\u001b[37m\u001b[0m \u001b[1m0s\u001b[0m 56ms/step\n",
      "\u001b[1m1/1\u001b[0m \u001b[32m━━━━━━━━━━━━━━━━━━━━\u001b[0m\u001b[37m\u001b[0m \u001b[1m0s\u001b[0m 70ms/step\n",
      "\u001b[1m1/1\u001b[0m \u001b[32m━━━━━━━━━━━━━━━━━━━━\u001b[0m\u001b[37m\u001b[0m \u001b[1m0s\u001b[0m 56ms/step\n",
      "\u001b[1m1/1\u001b[0m \u001b[32m━━━━━━━━━━━━━━━━━━━━\u001b[0m\u001b[37m\u001b[0m \u001b[1m0s\u001b[0m 48ms/step\n",
      "\u001b[1m1/1\u001b[0m \u001b[32m━━━━━━━━━━━━━━━━━━━━\u001b[0m\u001b[37m\u001b[0m \u001b[1m0s\u001b[0m 56ms/step\n",
      "\u001b[1m1/1\u001b[0m \u001b[32m━━━━━━━━━━━━━━━━━━━━\u001b[0m\u001b[37m\u001b[0m \u001b[1m0s\u001b[0m 62ms/step\n",
      "\u001b[1m1/1\u001b[0m \u001b[32m━━━━━━━━━━━━━━━━━━━━\u001b[0m\u001b[37m\u001b[0m \u001b[1m0s\u001b[0m 62ms/step\n",
      "\u001b[1m1/1\u001b[0m \u001b[32m━━━━━━━━━━━━━━━━━━━━\u001b[0m\u001b[37m\u001b[0m \u001b[1m0s\u001b[0m 58ms/step\n",
      "\u001b[1m1/1\u001b[0m \u001b[32m━━━━━━━━━━━━━━━━━━━━\u001b[0m\u001b[37m\u001b[0m \u001b[1m0s\u001b[0m 52ms/step\n",
      "\u001b[1m1/1\u001b[0m \u001b[32m━━━━━━━━━━━━━━━━━━━━\u001b[0m\u001b[37m\u001b[0m \u001b[1m0s\u001b[0m 59ms/step\n",
      "\u001b[1m1/1\u001b[0m \u001b[32m━━━━━━━━━━━━━━━━━━━━\u001b[0m\u001b[37m\u001b[0m \u001b[1m0s\u001b[0m 66ms/step\n",
      "\u001b[1m1/1\u001b[0m \u001b[32m━━━━━━━━━━━━━━━━━━━━\u001b[0m\u001b[37m\u001b[0m \u001b[1m0s\u001b[0m 54ms/step\n",
      "\u001b[1m1/1\u001b[0m \u001b[32m━━━━━━━━━━━━━━━━━━━━\u001b[0m\u001b[37m\u001b[0m \u001b[1m0s\u001b[0m 54ms/step\n",
      "\u001b[1m1/1\u001b[0m \u001b[32m━━━━━━━━━━━━━━━━━━━━\u001b[0m\u001b[37m\u001b[0m \u001b[1m0s\u001b[0m 49ms/step\n",
      "\u001b[1m1/1\u001b[0m \u001b[32m━━━━━━━━━━━━━━━━━━━━\u001b[0m\u001b[37m\u001b[0m \u001b[1m0s\u001b[0m 56ms/step\n",
      "\u001b[1m1/1\u001b[0m \u001b[32m━━━━━━━━━━━━━━━━━━━━\u001b[0m\u001b[37m\u001b[0m \u001b[1m0s\u001b[0m 62ms/step\n",
      "\u001b[1m1/1\u001b[0m \u001b[32m━━━━━━━━━━━━━━━━━━━━\u001b[0m\u001b[37m\u001b[0m \u001b[1m0s\u001b[0m 48ms/step\n",
      "\u001b[1m1/1\u001b[0m \u001b[32m━━━━━━━━━━━━━━━━━━━━\u001b[0m\u001b[37m\u001b[0m \u001b[1m0s\u001b[0m 76ms/step\n",
      "\u001b[1m1/1\u001b[0m \u001b[32m━━━━━━━━━━━━━━━━━━━━\u001b[0m\u001b[37m\u001b[0m \u001b[1m0s\u001b[0m 52ms/step\n",
      "\u001b[1m1/1\u001b[0m \u001b[32m━━━━━━━━━━━━━━━━━━━━\u001b[0m\u001b[37m\u001b[0m \u001b[1m0s\u001b[0m 63ms/step\n",
      "\u001b[1m1/1\u001b[0m \u001b[32m━━━━━━━━━━━━━━━━━━━━\u001b[0m\u001b[37m\u001b[0m \u001b[1m0s\u001b[0m 59ms/step\n",
      "\u001b[1m1/1\u001b[0m \u001b[32m━━━━━━━━━━━━━━━━━━━━\u001b[0m\u001b[37m\u001b[0m \u001b[1m0s\u001b[0m 46ms/step\n",
      "\u001b[1m1/1\u001b[0m \u001b[32m━━━━━━━━━━━━━━━━━━━━\u001b[0m\u001b[37m\u001b[0m \u001b[1m0s\u001b[0m 60ms/step\n",
      "\u001b[1m1/1\u001b[0m \u001b[32m━━━━━━━━━━━━━━━━━━━━\u001b[0m\u001b[37m\u001b[0m \u001b[1m0s\u001b[0m 62ms/step\n",
      "\u001b[1m1/1\u001b[0m \u001b[32m━━━━━━━━━━━━━━━━━━━━\u001b[0m\u001b[37m\u001b[0m \u001b[1m0s\u001b[0m 43ms/step\n",
      "\u001b[1m1/1\u001b[0m \u001b[32m━━━━━━━━━━━━━━━━━━━━\u001b[0m\u001b[37m\u001b[0m \u001b[1m0s\u001b[0m 62ms/step\n",
      "\u001b[1m1/1\u001b[0m \u001b[32m━━━━━━━━━━━━━━━━━━━━\u001b[0m\u001b[37m\u001b[0m \u001b[1m0s\u001b[0m 62ms/step\n",
      "\u001b[1m1/1\u001b[0m \u001b[32m━━━━━━━━━━━━━━━━━━━━\u001b[0m\u001b[37m\u001b[0m \u001b[1m0s\u001b[0m 50ms/step\n",
      "\u001b[1m1/1\u001b[0m \u001b[32m━━━━━━━━━━━━━━━━━━━━\u001b[0m\u001b[37m\u001b[0m \u001b[1m0s\u001b[0m 62ms/step\n",
      "\u001b[1m1/1\u001b[0m \u001b[32m━━━━━━━━━━━━━━━━━━━━\u001b[0m\u001b[37m\u001b[0m \u001b[1m0s\u001b[0m 58ms/step\n",
      "\u001b[1m1/1\u001b[0m \u001b[32m━━━━━━━━━━━━━━━━━━━━\u001b[0m\u001b[37m\u001b[0m \u001b[1m0s\u001b[0m 60ms/step\n",
      "\u001b[1m1/1\u001b[0m \u001b[32m━━━━━━━━━━━━━━━━━━━━\u001b[0m\u001b[37m\u001b[0m \u001b[1m0s\u001b[0m 74ms/step\n",
      "\u001b[1m1/1\u001b[0m \u001b[32m━━━━━━━━━━━━━━━━━━━━\u001b[0m\u001b[37m\u001b[0m \u001b[1m0s\u001b[0m 55ms/step\n",
      "\u001b[1m1/1\u001b[0m \u001b[32m━━━━━━━━━━━━━━━━━━━━\u001b[0m\u001b[37m\u001b[0m \u001b[1m0s\u001b[0m 67ms/step\n",
      "\u001b[1m1/1\u001b[0m \u001b[32m━━━━━━━━━━━━━━━━━━━━\u001b[0m\u001b[37m\u001b[0m \u001b[1m0s\u001b[0m 49ms/step\n",
      "\u001b[1m1/1\u001b[0m \u001b[32m━━━━━━━━━━━━━━━━━━━━\u001b[0m\u001b[37m\u001b[0m \u001b[1m0s\u001b[0m 64ms/step\n",
      "\u001b[1m1/1\u001b[0m \u001b[32m━━━━━━━━━━━━━━━━━━━━\u001b[0m\u001b[37m\u001b[0m \u001b[1m0s\u001b[0m 58ms/step\n",
      "\u001b[1m1/1\u001b[0m \u001b[32m━━━━━━━━━━━━━━━━━━━━\u001b[0m\u001b[37m\u001b[0m \u001b[1m0s\u001b[0m 56ms/step\n",
      "\u001b[1m1/1\u001b[0m \u001b[32m━━━━━━━━━━━━━━━━━━━━\u001b[0m\u001b[37m\u001b[0m \u001b[1m0s\u001b[0m 54ms/step\n",
      "\u001b[1m1/1\u001b[0m \u001b[32m━━━━━━━━━━━━━━━━━━━━\u001b[0m\u001b[37m\u001b[0m \u001b[1m0s\u001b[0m 57ms/step\n",
      "\u001b[1m1/1\u001b[0m \u001b[32m━━━━━━━━━━━━━━━━━━━━\u001b[0m\u001b[37m\u001b[0m \u001b[1m0s\u001b[0m 50ms/step\n",
      "\u001b[1m1/1\u001b[0m \u001b[32m━━━━━━━━━━━━━━━━━━━━\u001b[0m\u001b[37m\u001b[0m \u001b[1m0s\u001b[0m 47ms/step\n",
      "\u001b[1m1/1\u001b[0m \u001b[32m━━━━━━━━━━━━━━━━━━━━\u001b[0m\u001b[37m\u001b[0m \u001b[1m0s\u001b[0m 62ms/step\n",
      "\u001b[1m1/1\u001b[0m \u001b[32m━━━━━━━━━━━━━━━━━━━━\u001b[0m\u001b[37m\u001b[0m \u001b[1m0s\u001b[0m 48ms/step\n",
      "\u001b[1m1/1\u001b[0m \u001b[32m━━━━━━━━━━━━━━━━━━━━\u001b[0m\u001b[37m\u001b[0m \u001b[1m0s\u001b[0m 48ms/step\n",
      "\u001b[1m1/1\u001b[0m \u001b[32m━━━━━━━━━━━━━━━━━━━━\u001b[0m\u001b[37m\u001b[0m \u001b[1m0s\u001b[0m 69ms/step\n",
      "\u001b[1m1/1\u001b[0m \u001b[32m━━━━━━━━━━━━━━━━━━━━\u001b[0m\u001b[37m\u001b[0m \u001b[1m0s\u001b[0m 47ms/step\n",
      "\u001b[1m1/1\u001b[0m \u001b[32m━━━━━━━━━━━━━━━━━━━━\u001b[0m\u001b[37m\u001b[0m \u001b[1m0s\u001b[0m 62ms/step\n",
      "\u001b[1m1/1\u001b[0m \u001b[32m━━━━━━━━━━━━━━━━━━━━\u001b[0m\u001b[37m\u001b[0m \u001b[1m0s\u001b[0m 62ms/step\n",
      "\u001b[1m1/1\u001b[0m \u001b[32m━━━━━━━━━━━━━━━━━━━━\u001b[0m\u001b[37m\u001b[0m \u001b[1m0s\u001b[0m 62ms/step\n",
      "\u001b[1m1/1\u001b[0m \u001b[32m━━━━━━━━━━━━━━━━━━━━\u001b[0m\u001b[37m\u001b[0m \u001b[1m0s\u001b[0m 47ms/step\n",
      "\u001b[1m1/1\u001b[0m \u001b[32m━━━━━━━━━━━━━━━━━━━━\u001b[0m\u001b[37m\u001b[0m \u001b[1m0s\u001b[0m 67ms/step\n",
      "\u001b[1m1/1\u001b[0m \u001b[32m━━━━━━━━━━━━━━━━━━━━\u001b[0m\u001b[37m\u001b[0m \u001b[1m0s\u001b[0m 47ms/step\n",
      "\u001b[1m1/1\u001b[0m \u001b[32m━━━━━━━━━━━━━━━━━━━━\u001b[0m\u001b[37m\u001b[0m \u001b[1m0s\u001b[0m 62ms/step\n",
      "\u001b[1m1/1\u001b[0m \u001b[32m━━━━━━━━━━━━━━━━━━━━\u001b[0m\u001b[37m\u001b[0m \u001b[1m0s\u001b[0m 48ms/step\n",
      "\u001b[1m1/1\u001b[0m \u001b[32m━━━━━━━━━━━━━━━━━━━━\u001b[0m\u001b[37m\u001b[0m \u001b[1m0s\u001b[0m 47ms/step\n",
      "\u001b[1m1/1\u001b[0m \u001b[32m━━━━━━━━━━━━━━━━━━━━\u001b[0m\u001b[37m\u001b[0m \u001b[1m0s\u001b[0m 54ms/step\n",
      "\u001b[1m1/1\u001b[0m \u001b[32m━━━━━━━━━━━━━━━━━━━━\u001b[0m\u001b[37m\u001b[0m \u001b[1m0s\u001b[0m 55ms/step\n",
      "\u001b[1m1/1\u001b[0m \u001b[32m━━━━━━━━━━━━━━━━━━━━\u001b[0m\u001b[37m\u001b[0m \u001b[1m0s\u001b[0m 45ms/step\n",
      "\u001b[1m1/1\u001b[0m \u001b[32m━━━━━━━━━━━━━━━━━━━━\u001b[0m\u001b[37m\u001b[0m \u001b[1m0s\u001b[0m 62ms/step\n",
      "\u001b[1m1/1\u001b[0m \u001b[32m━━━━━━━━━━━━━━━━━━━━\u001b[0m\u001b[37m\u001b[0m \u001b[1m0s\u001b[0m 64ms/step\n",
      "\u001b[1m1/1\u001b[0m \u001b[32m━━━━━━━━━━━━━━━━━━━━\u001b[0m\u001b[37m\u001b[0m \u001b[1m0s\u001b[0m 62ms/step\n",
      "\u001b[1m1/1\u001b[0m \u001b[32m━━━━━━━━━━━━━━━━━━━━\u001b[0m\u001b[37m\u001b[0m \u001b[1m0s\u001b[0m 59ms/step\n",
      "\u001b[1m1/1\u001b[0m \u001b[32m━━━━━━━━━━━━━━━━━━━━\u001b[0m\u001b[37m\u001b[0m \u001b[1m0s\u001b[0m 55ms/step\n",
      "\u001b[1m1/1\u001b[0m \u001b[32m━━━━━━━━━━━━━━━━━━━━\u001b[0m\u001b[37m\u001b[0m \u001b[1m0s\u001b[0m 47ms/step\n",
      "\u001b[1m1/1\u001b[0m \u001b[32m━━━━━━━━━━━━━━━━━━━━\u001b[0m\u001b[37m\u001b[0m \u001b[1m0s\u001b[0m 47ms/step\n",
      "\u001b[1m1/1\u001b[0m \u001b[32m━━━━━━━━━━━━━━━━━━━━\u001b[0m\u001b[37m\u001b[0m \u001b[1m0s\u001b[0m 62ms/step\n",
      "\u001b[1m1/1\u001b[0m \u001b[32m━━━━━━━━━━━━━━━━━━━━\u001b[0m\u001b[37m\u001b[0m \u001b[1m0s\u001b[0m 48ms/step\n",
      "\u001b[1m1/1\u001b[0m \u001b[32m━━━━━━━━━━━━━━━━━━━━\u001b[0m\u001b[37m\u001b[0m \u001b[1m0s\u001b[0m 48ms/step\n",
      "\u001b[1m1/1\u001b[0m \u001b[32m━━━━━━━━━━━━━━━━━━━━\u001b[0m\u001b[37m\u001b[0m \u001b[1m0s\u001b[0m 46ms/step\n",
      "\u001b[1m1/1\u001b[0m \u001b[32m━━━━━━━━━━━━━━━━━━━━\u001b[0m\u001b[37m\u001b[0m \u001b[1m0s\u001b[0m 59ms/step\n",
      "\u001b[1m1/1\u001b[0m \u001b[32m━━━━━━━━━━━━━━━━━━━━\u001b[0m\u001b[37m\u001b[0m \u001b[1m0s\u001b[0m 47ms/step\n",
      "\u001b[1m1/1\u001b[0m \u001b[32m━━━━━━━━━━━━━━━━━━━━\u001b[0m\u001b[37m\u001b[0m \u001b[1m0s\u001b[0m 62ms/step\n",
      "\u001b[1m1/1\u001b[0m \u001b[32m━━━━━━━━━━━━━━━━━━━━\u001b[0m\u001b[37m\u001b[0m \u001b[1m0s\u001b[0m 71ms/step\n",
      "\u001b[1m1/1\u001b[0m \u001b[32m━━━━━━━━━━━━━━━━━━━━\u001b[0m\u001b[37m\u001b[0m \u001b[1m0s\u001b[0m 59ms/step\n",
      "\u001b[1m1/1\u001b[0m \u001b[32m━━━━━━━━━━━━━━━━━━━━\u001b[0m\u001b[37m\u001b[0m \u001b[1m0s\u001b[0m 57ms/step\n",
      "\u001b[1m1/1\u001b[0m \u001b[32m━━━━━━━━━━━━━━━━━━━━\u001b[0m\u001b[37m\u001b[0m \u001b[1m0s\u001b[0m 52ms/step\n",
      "\u001b[1m1/1\u001b[0m \u001b[32m━━━━━━━━━━━━━━━━━━━━\u001b[0m\u001b[37m\u001b[0m \u001b[1m0s\u001b[0m 70ms/step\n",
      "\u001b[1m1/1\u001b[0m \u001b[32m━━━━━━━━━━━━━━━━━━━━\u001b[0m\u001b[37m\u001b[0m \u001b[1m0s\u001b[0m 69ms/step\n",
      "\u001b[1m1/1\u001b[0m \u001b[32m━━━━━━━━━━━━━━━━━━━━\u001b[0m\u001b[37m\u001b[0m \u001b[1m0s\u001b[0m 60ms/step\n",
      "\u001b[1m1/1\u001b[0m \u001b[32m━━━━━━━━━━━━━━━━━━━━\u001b[0m\u001b[37m\u001b[0m \u001b[1m0s\u001b[0m 60ms/step\n",
      "\u001b[1m1/1\u001b[0m \u001b[32m━━━━━━━━━━━━━━━━━━━━\u001b[0m\u001b[37m\u001b[0m \u001b[1m0s\u001b[0m 62ms/step\n",
      "\u001b[1m1/1\u001b[0m \u001b[32m━━━━━━━━━━━━━━━━━━━━\u001b[0m\u001b[37m\u001b[0m \u001b[1m0s\u001b[0m 49ms/step\n",
      "\u001b[1m1/1\u001b[0m \u001b[32m━━━━━━━━━━━━━━━━━━━━\u001b[0m\u001b[37m\u001b[0m \u001b[1m0s\u001b[0m 65ms/step\n",
      "\u001b[1m1/1\u001b[0m \u001b[32m━━━━━━━━━━━━━━━━━━━━\u001b[0m\u001b[37m\u001b[0m \u001b[1m0s\u001b[0m 61ms/step\n",
      "\u001b[1m1/1\u001b[0m \u001b[32m━━━━━━━━━━━━━━━━━━━━\u001b[0m\u001b[37m\u001b[0m \u001b[1m0s\u001b[0m 62ms/step\n",
      "\u001b[1m1/1\u001b[0m \u001b[32m━━━━━━━━━━━━━━━━━━━━\u001b[0m\u001b[37m\u001b[0m \u001b[1m0s\u001b[0m 67ms/step\n",
      "\u001b[1m1/1\u001b[0m \u001b[32m━━━━━━━━━━━━━━━━━━━━\u001b[0m\u001b[37m\u001b[0m \u001b[1m0s\u001b[0m 67ms/step\n",
      "\u001b[1m1/1\u001b[0m \u001b[32m━━━━━━━━━━━━━━━━━━━━\u001b[0m\u001b[37m\u001b[0m \u001b[1m0s\u001b[0m 68ms/step\n",
      "\u001b[1m1/1\u001b[0m \u001b[32m━━━━━━━━━━━━━━━━━━━━\u001b[0m\u001b[37m\u001b[0m \u001b[1m0s\u001b[0m 54ms/step\n",
      "\u001b[1m1/1\u001b[0m \u001b[32m━━━━━━━━━━━━━━━━━━━━\u001b[0m\u001b[37m\u001b[0m \u001b[1m0s\u001b[0m 62ms/step\n",
      "\u001b[1m1/1\u001b[0m \u001b[32m━━━━━━━━━━━━━━━━━━━━\u001b[0m\u001b[37m\u001b[0m \u001b[1m0s\u001b[0m 67ms/step\n",
      "\u001b[1m1/1\u001b[0m \u001b[32m━━━━━━━━━━━━━━━━━━━━\u001b[0m\u001b[37m\u001b[0m \u001b[1m0s\u001b[0m 42ms/step\n",
      "\u001b[1m1/1\u001b[0m \u001b[32m━━━━━━━━━━━━━━━━━━━━\u001b[0m\u001b[37m\u001b[0m \u001b[1m0s\u001b[0m 73ms/step\n",
      "\u001b[1m1/1\u001b[0m \u001b[32m━━━━━━━━━━━━━━━━━━━━\u001b[0m\u001b[37m\u001b[0m \u001b[1m0s\u001b[0m 74ms/step\n",
      "\u001b[1m1/1\u001b[0m \u001b[32m━━━━━━━━━━━━━━━━━━━━\u001b[0m\u001b[37m\u001b[0m \u001b[1m0s\u001b[0m 71ms/step\n",
      "\u001b[1m1/1\u001b[0m \u001b[32m━━━━━━━━━━━━━━━━━━━━\u001b[0m\u001b[37m\u001b[0m \u001b[1m0s\u001b[0m 65ms/step\n",
      "\u001b[1m1/1\u001b[0m \u001b[32m━━━━━━━━━━━━━━━━━━━━\u001b[0m\u001b[37m\u001b[0m \u001b[1m0s\u001b[0m 62ms/step\n",
      "\u001b[1m1/1\u001b[0m \u001b[32m━━━━━━━━━━━━━━━━━━━━\u001b[0m\u001b[37m\u001b[0m \u001b[1m0s\u001b[0m 43ms/step\n",
      "\u001b[1m1/1\u001b[0m \u001b[32m━━━━━━━━━━━━━━━━━━━━\u001b[0m\u001b[37m\u001b[0m \u001b[1m0s\u001b[0m 62ms/step\n",
      "\u001b[1m1/1\u001b[0m \u001b[32m━━━━━━━━━━━━━━━━━━━━\u001b[0m\u001b[37m\u001b[0m \u001b[1m0s\u001b[0m 47ms/step\n",
      "\u001b[1m1/1\u001b[0m \u001b[32m━━━━━━━━━━━━━━━━━━━━\u001b[0m\u001b[37m\u001b[0m \u001b[1m0s\u001b[0m 58ms/step\n",
      "\u001b[1m1/1\u001b[0m \u001b[32m━━━━━━━━━━━━━━━━━━━━\u001b[0m\u001b[37m\u001b[0m \u001b[1m0s\u001b[0m 56ms/step\n",
      "\u001b[1m1/1\u001b[0m \u001b[32m━━━━━━━━━━━━━━━━━━━━\u001b[0m\u001b[37m\u001b[0m \u001b[1m0s\u001b[0m 65ms/step\n",
      "\u001b[1m1/1\u001b[0m \u001b[32m━━━━━━━━━━━━━━━━━━━━\u001b[0m\u001b[37m\u001b[0m \u001b[1m0s\u001b[0m 57ms/step\n",
      "\u001b[1m1/1\u001b[0m \u001b[32m━━━━━━━━━━━━━━━━━━━━\u001b[0m\u001b[37m\u001b[0m \u001b[1m0s\u001b[0m 54ms/step\n",
      "\u001b[1m1/1\u001b[0m \u001b[32m━━━━━━━━━━━━━━━━━━━━\u001b[0m\u001b[37m\u001b[0m \u001b[1m0s\u001b[0m 57ms/step\n",
      "\u001b[1m1/1\u001b[0m \u001b[32m━━━━━━━━━━━━━━━━━━━━\u001b[0m\u001b[37m\u001b[0m \u001b[1m0s\u001b[0m 62ms/step\n",
      "\u001b[1m1/1\u001b[0m \u001b[32m━━━━━━━━━━━━━━━━━━━━\u001b[0m\u001b[37m\u001b[0m \u001b[1m0s\u001b[0m 54ms/step\n",
      "\u001b[1m1/1\u001b[0m \u001b[32m━━━━━━━━━━━━━━━━━━━━\u001b[0m\u001b[37m\u001b[0m \u001b[1m0s\u001b[0m 57ms/step\n",
      "\u001b[1m1/1\u001b[0m \u001b[32m━━━━━━━━━━━━━━━━━━━━\u001b[0m\u001b[37m\u001b[0m \u001b[1m0s\u001b[0m 62ms/step\n",
      "\u001b[1m1/1\u001b[0m \u001b[32m━━━━━━━━━━━━━━━━━━━━\u001b[0m\u001b[37m\u001b[0m \u001b[1m0s\u001b[0m 66ms/step\n",
      "\u001b[1m1/1\u001b[0m \u001b[32m━━━━━━━━━━━━━━━━━━━━\u001b[0m\u001b[37m\u001b[0m \u001b[1m0s\u001b[0m 45ms/step\n",
      "\u001b[1m1/1\u001b[0m \u001b[32m━━━━━━━━━━━━━━━━━━━━\u001b[0m\u001b[37m\u001b[0m \u001b[1m0s\u001b[0m 62ms/step\n",
      "\u001b[1m1/1\u001b[0m \u001b[32m━━━━━━━━━━━━━━━━━━━━\u001b[0m\u001b[37m\u001b[0m \u001b[1m0s\u001b[0m 78ms/step\n",
      "\u001b[1m1/1\u001b[0m \u001b[32m━━━━━━━━━━━━━━━━━━━━\u001b[0m\u001b[37m\u001b[0m \u001b[1m0s\u001b[0m 42ms/step\n",
      "\u001b[1m1/1\u001b[0m \u001b[32m━━━━━━━━━━━━━━━━━━━━\u001b[0m\u001b[37m\u001b[0m \u001b[1m0s\u001b[0m 47ms/step\n",
      "\u001b[1m1/1\u001b[0m \u001b[32m━━━━━━━━━━━━━━━━━━━━\u001b[0m\u001b[37m\u001b[0m \u001b[1m0s\u001b[0m 51ms/step\n",
      "\u001b[1m1/1\u001b[0m \u001b[32m━━━━━━━━━━━━━━━━━━━━\u001b[0m\u001b[37m\u001b[0m \u001b[1m0s\u001b[0m 52ms/step\n",
      "\u001b[1m1/1\u001b[0m \u001b[32m━━━━━━━━━━━━━━━━━━━━\u001b[0m\u001b[37m\u001b[0m \u001b[1m0s\u001b[0m 62ms/step\n",
      "\u001b[1m1/1\u001b[0m \u001b[32m━━━━━━━━━━━━━━━━━━━━\u001b[0m\u001b[37m\u001b[0m \u001b[1m0s\u001b[0m 64ms/step\n",
      "\u001b[1m1/1\u001b[0m \u001b[32m━━━━━━━━━━━━━━━━━━━━\u001b[0m\u001b[37m\u001b[0m \u001b[1m0s\u001b[0m 69ms/step\n",
      "\u001b[1m1/1\u001b[0m \u001b[32m━━━━━━━━━━━━━━━━━━━━\u001b[0m\u001b[37m\u001b[0m \u001b[1m0s\u001b[0m 50ms/step\n",
      "\u001b[1m1/1\u001b[0m \u001b[32m━━━━━━━━━━━━━━━━━━━━\u001b[0m\u001b[37m\u001b[0m \u001b[1m0s\u001b[0m 64ms/step\n",
      "\u001b[1m1/1\u001b[0m \u001b[32m━━━━━━━━━━━━━━━━━━━━\u001b[0m\u001b[37m\u001b[0m \u001b[1m0s\u001b[0m 58ms/step\n",
      "\u001b[1m1/1\u001b[0m \u001b[32m━━━━━━━━━━━━━━━━━━━━\u001b[0m\u001b[37m\u001b[0m \u001b[1m0s\u001b[0m 64ms/step\n",
      "\u001b[1m1/1\u001b[0m \u001b[32m━━━━━━━━━━━━━━━━━━━━\u001b[0m\u001b[37m\u001b[0m \u001b[1m0s\u001b[0m 52ms/step\n",
      "\u001b[1m1/1\u001b[0m \u001b[32m━━━━━━━━━━━━━━━━━━━━\u001b[0m\u001b[37m\u001b[0m \u001b[1m0s\u001b[0m 48ms/step\n",
      "\u001b[1m1/1\u001b[0m \u001b[32m━━━━━━━━━━━━━━━━━━━━\u001b[0m\u001b[37m\u001b[0m \u001b[1m0s\u001b[0m 66ms/step\n",
      "\u001b[1m1/1\u001b[0m \u001b[32m━━━━━━━━━━━━━━━━━━━━\u001b[0m\u001b[37m\u001b[0m \u001b[1m0s\u001b[0m 57ms/step\n",
      "\u001b[1m1/1\u001b[0m \u001b[32m━━━━━━━━━━━━━━━━━━━━\u001b[0m\u001b[37m\u001b[0m \u001b[1m0s\u001b[0m 47ms/step\n",
      "\u001b[1m1/1\u001b[0m \u001b[32m━━━━━━━━━━━━━━━━━━━━\u001b[0m\u001b[37m\u001b[0m \u001b[1m0s\u001b[0m 47ms/step\n",
      "\u001b[1m1/1\u001b[0m \u001b[32m━━━━━━━━━━━━━━━━━━━━\u001b[0m\u001b[37m\u001b[0m \u001b[1m0s\u001b[0m 56ms/step\n",
      "\u001b[1m1/1\u001b[0m \u001b[32m━━━━━━━━━━━━━━━━━━━━\u001b[0m\u001b[37m\u001b[0m \u001b[1m0s\u001b[0m 62ms/step\n",
      "\u001b[1m1/1\u001b[0m \u001b[32m━━━━━━━━━━━━━━━━━━━━\u001b[0m\u001b[37m\u001b[0m \u001b[1m0s\u001b[0m 62ms/step\n",
      "\u001b[1m1/1\u001b[0m \u001b[32m━━━━━━━━━━━━━━━━━━━━\u001b[0m\u001b[37m\u001b[0m \u001b[1m0s\u001b[0m 47ms/step\n",
      "\u001b[1m1/1\u001b[0m \u001b[32m━━━━━━━━━━━━━━━━━━━━\u001b[0m\u001b[37m\u001b[0m \u001b[1m0s\u001b[0m 62ms/step\n",
      "\u001b[1m1/1\u001b[0m \u001b[32m━━━━━━━━━━━━━━━━━━━━\u001b[0m\u001b[37m\u001b[0m \u001b[1m0s\u001b[0m 48ms/step\n",
      "\u001b[1m1/1\u001b[0m \u001b[32m━━━━━━━━━━━━━━━━━━━━\u001b[0m\u001b[37m\u001b[0m \u001b[1m0s\u001b[0m 50ms/step\n",
      "\u001b[1m1/1\u001b[0m \u001b[32m━━━━━━━━━━━━━━━━━━━━\u001b[0m\u001b[37m\u001b[0m \u001b[1m0s\u001b[0m 47ms/step\n",
      "\u001b[1m1/1\u001b[0m \u001b[32m━━━━━━━━━━━━━━━━━━━━\u001b[0m\u001b[37m\u001b[0m \u001b[1m0s\u001b[0m 47ms/step\n",
      "\u001b[1m1/1\u001b[0m \u001b[32m━━━━━━━━━━━━━━━━━━━━\u001b[0m\u001b[37m\u001b[0m \u001b[1m0s\u001b[0m 48ms/step\n",
      "\u001b[1m1/1\u001b[0m \u001b[32m━━━━━━━━━━━━━━━━━━━━\u001b[0m\u001b[37m\u001b[0m \u001b[1m0s\u001b[0m 47ms/step\n",
      "\u001b[1m1/1\u001b[0m \u001b[32m━━━━━━━━━━━━━━━━━━━━\u001b[0m\u001b[37m\u001b[0m \u001b[1m0s\u001b[0m 69ms/step\n",
      "\u001b[1m1/1\u001b[0m \u001b[32m━━━━━━━━━━━━━━━━━━━━\u001b[0m\u001b[37m\u001b[0m \u001b[1m0s\u001b[0m 59ms/step\n",
      "\u001b[1m1/1\u001b[0m \u001b[32m━━━━━━━━━━━━━━━━━━━━\u001b[0m\u001b[37m\u001b[0m \u001b[1m0s\u001b[0m 47ms/step\n",
      "\u001b[1m1/1\u001b[0m \u001b[32m━━━━━━━━━━━━━━━━━━━━\u001b[0m\u001b[37m\u001b[0m \u001b[1m0s\u001b[0m 47ms/step\n",
      "\u001b[1m1/1\u001b[0m \u001b[32m━━━━━━━━━━━━━━━━━━━━\u001b[0m\u001b[37m\u001b[0m \u001b[1m0s\u001b[0m 62ms/step\n",
      "\u001b[1m1/1\u001b[0m \u001b[32m━━━━━━━━━━━━━━━━━━━━\u001b[0m\u001b[37m\u001b[0m \u001b[1m0s\u001b[0m 48ms/step\n",
      "\u001b[1m1/1\u001b[0m \u001b[32m━━━━━━━━━━━━━━━━━━━━\u001b[0m\u001b[37m\u001b[0m \u001b[1m0s\u001b[0m 62ms/step\n",
      "\u001b[1m1/1\u001b[0m \u001b[32m━━━━━━━━━━━━━━━━━━━━\u001b[0m\u001b[37m\u001b[0m \u001b[1m0s\u001b[0m 55ms/step\n",
      "\u001b[1m1/1\u001b[0m \u001b[32m━━━━━━━━━━━━━━━━━━━━\u001b[0m\u001b[37m\u001b[0m \u001b[1m0s\u001b[0m 62ms/step\n",
      "\u001b[1m1/1\u001b[0m \u001b[32m━━━━━━━━━━━━━━━━━━━━\u001b[0m\u001b[37m\u001b[0m \u001b[1m0s\u001b[0m 47ms/step\n",
      "\u001b[1m1/1\u001b[0m \u001b[32m━━━━━━━━━━━━━━━━━━━━\u001b[0m\u001b[37m\u001b[0m \u001b[1m0s\u001b[0m 47ms/step\n",
      "\u001b[1m1/1\u001b[0m \u001b[32m━━━━━━━━━━━━━━━━━━━━\u001b[0m\u001b[37m\u001b[0m \u001b[1m0s\u001b[0m 47ms/step\n",
      "\u001b[1m1/1\u001b[0m \u001b[32m━━━━━━━━━━━━━━━━━━━━\u001b[0m\u001b[37m\u001b[0m \u001b[1m0s\u001b[0m 62ms/step\n",
      "\u001b[1m1/1\u001b[0m \u001b[32m━━━━━━━━━━━━━━━━━━━━\u001b[0m\u001b[37m\u001b[0m \u001b[1m0s\u001b[0m 55ms/step\n",
      "\u001b[1m1/1\u001b[0m \u001b[32m━━━━━━━━━━━━━━━━━━━━\u001b[0m\u001b[37m\u001b[0m \u001b[1m0s\u001b[0m 47ms/step\n",
      "\u001b[1m1/1\u001b[0m \u001b[32m━━━━━━━━━━━━━━━━━━━━\u001b[0m\u001b[37m\u001b[0m \u001b[1m0s\u001b[0m 47ms/step\n",
      "\u001b[1m1/1\u001b[0m \u001b[32m━━━━━━━━━━━━━━━━━━━━\u001b[0m\u001b[37m\u001b[0m \u001b[1m0s\u001b[0m 61ms/step\n",
      "\u001b[1m1/1\u001b[0m \u001b[32m━━━━━━━━━━━━━━━━━━━━\u001b[0m\u001b[37m\u001b[0m \u001b[1m0s\u001b[0m 47ms/step\n",
      "\u001b[1m1/1\u001b[0m \u001b[32m━━━━━━━━━━━━━━━━━━━━\u001b[0m\u001b[37m\u001b[0m \u001b[1m0s\u001b[0m 64ms/step\n",
      "\u001b[1m1/1\u001b[0m \u001b[32m━━━━━━━━━━━━━━━━━━━━\u001b[0m\u001b[37m\u001b[0m \u001b[1m0s\u001b[0m 45ms/step\n",
      "\u001b[1m1/1\u001b[0m \u001b[32m━━━━━━━━━━━━━━━━━━━━\u001b[0m\u001b[37m\u001b[0m \u001b[1m0s\u001b[0m 62ms/step\n",
      "\u001b[1m1/1\u001b[0m \u001b[32m━━━━━━━━━━━━━━━━━━━━\u001b[0m\u001b[37m\u001b[0m \u001b[1m0s\u001b[0m 62ms/step\n",
      "\u001b[1m1/1\u001b[0m \u001b[32m━━━━━━━━━━━━━━━━━━━━\u001b[0m\u001b[37m\u001b[0m \u001b[1m0s\u001b[0m 47ms/step\n",
      "\u001b[1m1/1\u001b[0m \u001b[32m━━━━━━━━━━━━━━━━━━━━\u001b[0m\u001b[37m\u001b[0m \u001b[1m0s\u001b[0m 62ms/step\n",
      "\u001b[1m1/1\u001b[0m \u001b[32m━━━━━━━━━━━━━━━━━━━━\u001b[0m\u001b[37m\u001b[0m \u001b[1m0s\u001b[0m 47ms/step\n",
      "\u001b[1m1/1\u001b[0m \u001b[32m━━━━━━━━━━━━━━━━━━━━\u001b[0m\u001b[37m\u001b[0m \u001b[1m0s\u001b[0m 48ms/step\n",
      "\u001b[1m1/1\u001b[0m \u001b[32m━━━━━━━━━━━━━━━━━━━━\u001b[0m\u001b[37m\u001b[0m \u001b[1m0s\u001b[0m 64ms/step\n",
      "\u001b[1m1/1\u001b[0m \u001b[32m━━━━━━━━━━━━━━━━━━━━\u001b[0m\u001b[37m\u001b[0m \u001b[1m0s\u001b[0m 62ms/step\n",
      "\u001b[1m1/1\u001b[0m \u001b[32m━━━━━━━━━━━━━━━━━━━━\u001b[0m\u001b[37m\u001b[0m \u001b[1m0s\u001b[0m 47ms/step\n",
      "\u001b[1m1/1\u001b[0m \u001b[32m━━━━━━━━━━━━━━━━━━━━\u001b[0m\u001b[37m\u001b[0m \u001b[1m0s\u001b[0m 62ms/step\n",
      "\u001b[1m1/1\u001b[0m \u001b[32m━━━━━━━━━━━━━━━━━━━━\u001b[0m\u001b[37m\u001b[0m \u001b[1m0s\u001b[0m 47ms/step\n",
      "\u001b[1m1/1\u001b[0m \u001b[32m━━━━━━━━━━━━━━━━━━━━\u001b[0m\u001b[37m\u001b[0m \u001b[1m0s\u001b[0m 47ms/step\n",
      "\u001b[1m1/1\u001b[0m \u001b[32m━━━━━━━━━━━━━━━━━━━━\u001b[0m\u001b[37m\u001b[0m \u001b[1m0s\u001b[0m 58ms/step\n",
      "\u001b[1m1/1\u001b[0m \u001b[32m━━━━━━━━━━━━━━━━━━━━\u001b[0m\u001b[37m\u001b[0m \u001b[1m0s\u001b[0m 62ms/step\n",
      "\u001b[1m1/1\u001b[0m \u001b[32m━━━━━━━━━━━━━━━━━━━━\u001b[0m\u001b[37m\u001b[0m \u001b[1m0s\u001b[0m 48ms/step\n",
      "\u001b[1m1/1\u001b[0m \u001b[32m━━━━━━━━━━━━━━━━━━━━\u001b[0m\u001b[37m\u001b[0m \u001b[1m0s\u001b[0m 62ms/step\n",
      "\u001b[1m1/1\u001b[0m \u001b[32m━━━━━━━━━━━━━━━━━━━━\u001b[0m\u001b[37m\u001b[0m \u001b[1m0s\u001b[0m 47ms/step\n",
      "\u001b[1m1/1\u001b[0m \u001b[32m━━━━━━━━━━━━━━━━━━━━\u001b[0m\u001b[37m\u001b[0m \u001b[1m0s\u001b[0m 47ms/step\n",
      "\u001b[1m1/1\u001b[0m \u001b[32m━━━━━━━━━━━━━━━━━━━━\u001b[0m\u001b[37m\u001b[0m \u001b[1m0s\u001b[0m 47ms/step\n",
      "\u001b[1m1/1\u001b[0m \u001b[32m━━━━━━━━━━━━━━━━━━━━\u001b[0m\u001b[37m\u001b[0m \u001b[1m0s\u001b[0m 47ms/step\n",
      "\u001b[1m1/1\u001b[0m \u001b[32m━━━━━━━━━━━━━━━━━━━━\u001b[0m\u001b[37m\u001b[0m \u001b[1m0s\u001b[0m 52ms/step\n",
      "\u001b[1m1/1\u001b[0m \u001b[32m━━━━━━━━━━━━━━━━━━━━\u001b[0m\u001b[37m\u001b[0m \u001b[1m0s\u001b[0m 67ms/step\n",
      "\u001b[1m1/1\u001b[0m \u001b[32m━━━━━━━━━━━━━━━━━━━━\u001b[0m\u001b[37m\u001b[0m \u001b[1m0s\u001b[0m 61ms/step\n",
      "\u001b[1m1/1\u001b[0m \u001b[32m━━━━━━━━━━━━━━━━━━━━\u001b[0m\u001b[37m\u001b[0m \u001b[1m0s\u001b[0m 59ms/step\n",
      "\u001b[1m1/1\u001b[0m \u001b[32m━━━━━━━━━━━━━━━━━━━━\u001b[0m\u001b[37m\u001b[0m \u001b[1m0s\u001b[0m 62ms/step\n",
      "\u001b[1m1/1\u001b[0m \u001b[32m━━━━━━━━━━━━━━━━━━━━\u001b[0m\u001b[37m\u001b[0m \u001b[1m0s\u001b[0m 47ms/step\n",
      "\u001b[1m1/1\u001b[0m \u001b[32m━━━━━━━━━━━━━━━━━━━━\u001b[0m\u001b[37m\u001b[0m \u001b[1m0s\u001b[0m 47ms/step\n",
      "\u001b[1m1/1\u001b[0m \u001b[32m━━━━━━━━━━━━━━━━━━━━\u001b[0m\u001b[37m\u001b[0m \u001b[1m0s\u001b[0m 63ms/step\n",
      "\u001b[1m1/1\u001b[0m \u001b[32m━━━━━━━━━━━━━━━━━━━━\u001b[0m\u001b[37m\u001b[0m \u001b[1m0s\u001b[0m 49ms/step\n",
      "\u001b[1m1/1\u001b[0m \u001b[32m━━━━━━━━━━━━━━━━━━━━\u001b[0m\u001b[37m\u001b[0m \u001b[1m0s\u001b[0m 48ms/step\n",
      "\u001b[1m1/1\u001b[0m \u001b[32m━━━━━━━━━━━━━━━━━━━━\u001b[0m\u001b[37m\u001b[0m \u001b[1m0s\u001b[0m 62ms/step\n",
      "\u001b[1m1/1\u001b[0m \u001b[32m━━━━━━━━━━━━━━━━━━━━\u001b[0m\u001b[37m\u001b[0m \u001b[1m0s\u001b[0m 62ms/step\n",
      "\u001b[1m1/1\u001b[0m \u001b[32m━━━━━━━━━━━━━━━━━━━━\u001b[0m\u001b[37m\u001b[0m \u001b[1m0s\u001b[0m 47ms/step\n",
      "\u001b[1m1/1\u001b[0m \u001b[32m━━━━━━━━━━━━━━━━━━━━\u001b[0m\u001b[37m\u001b[0m \u001b[1m0s\u001b[0m 57ms/step\n",
      "\u001b[1m1/1\u001b[0m \u001b[32m━━━━━━━━━━━━━━━━━━━━\u001b[0m\u001b[37m\u001b[0m \u001b[1m0s\u001b[0m 62ms/step\n",
      "\u001b[1m1/1\u001b[0m \u001b[32m━━━━━━━━━━━━━━━━━━━━\u001b[0m\u001b[37m\u001b[0m \u001b[1m0s\u001b[0m 47ms/step\n",
      "\u001b[1m1/1\u001b[0m \u001b[32m━━━━━━━━━━━━━━━━━━━━\u001b[0m\u001b[37m\u001b[0m \u001b[1m0s\u001b[0m 48ms/step\n",
      "\u001b[1m1/1\u001b[0m \u001b[32m━━━━━━━━━━━━━━━━━━━━\u001b[0m\u001b[37m\u001b[0m \u001b[1m0s\u001b[0m 62ms/step\n",
      "\u001b[1m1/1\u001b[0m \u001b[32m━━━━━━━━━━━━━━━━━━━━\u001b[0m\u001b[37m\u001b[0m \u001b[1m0s\u001b[0m 47ms/step\n",
      "\u001b[1m1/1\u001b[0m \u001b[32m━━━━━━━━━━━━━━━━━━━━\u001b[0m\u001b[37m\u001b[0m \u001b[1m0s\u001b[0m 62ms/step\n",
      "\u001b[1m1/1\u001b[0m \u001b[32m━━━━━━━━━━━━━━━━━━━━\u001b[0m\u001b[37m\u001b[0m \u001b[1m0s\u001b[0m 65ms/step\n",
      "\u001b[1m1/1\u001b[0m \u001b[32m━━━━━━━━━━━━━━━━━━━━\u001b[0m\u001b[37m\u001b[0m \u001b[1m0s\u001b[0m 62ms/step\n",
      "\u001b[1m1/1\u001b[0m \u001b[32m━━━━━━━━━━━━━━━━━━━━\u001b[0m\u001b[37m\u001b[0m \u001b[1m0s\u001b[0m 48ms/step\n",
      "\u001b[1m1/1\u001b[0m \u001b[32m━━━━━━━━━━━━━━━━━━━━\u001b[0m\u001b[37m\u001b[0m \u001b[1m0s\u001b[0m 65ms/step\n",
      "\u001b[1m1/1\u001b[0m \u001b[32m━━━━━━━━━━━━━━━━━━━━\u001b[0m\u001b[37m\u001b[0m \u001b[1m0s\u001b[0m 47ms/step\n",
      "\u001b[1m1/1\u001b[0m \u001b[32m━━━━━━━━━━━━━━━━━━━━\u001b[0m\u001b[37m\u001b[0m \u001b[1m0s\u001b[0m 58ms/step\n",
      "\u001b[1m1/1\u001b[0m \u001b[32m━━━━━━━━━━━━━━━━━━━━\u001b[0m\u001b[37m\u001b[0m \u001b[1m0s\u001b[0m 47ms/step\n",
      "\u001b[1m1/1\u001b[0m \u001b[32m━━━━━━━━━━━━━━━━━━━━\u001b[0m\u001b[37m\u001b[0m \u001b[1m0s\u001b[0m 50ms/step\n",
      "\u001b[1m1/1\u001b[0m \u001b[32m━━━━━━━━━━━━━━━━━━━━\u001b[0m\u001b[37m\u001b[0m \u001b[1m0s\u001b[0m 47ms/step\n",
      "\u001b[1m1/1\u001b[0m \u001b[32m━━━━━━━━━━━━━━━━━━━━\u001b[0m\u001b[37m\u001b[0m \u001b[1m0s\u001b[0m 48ms/step\n",
      "\u001b[1m1/1\u001b[0m \u001b[32m━━━━━━━━━━━━━━━━━━━━\u001b[0m\u001b[37m\u001b[0m \u001b[1m0s\u001b[0m 47ms/step\n",
      "\u001b[1m1/1\u001b[0m \u001b[32m━━━━━━━━━━━━━━━━━━━━\u001b[0m\u001b[37m\u001b[0m \u001b[1m0s\u001b[0m 47ms/step\n",
      "\u001b[1m1/1\u001b[0m \u001b[32m━━━━━━━━━━━━━━━━━━━━\u001b[0m\u001b[37m\u001b[0m \u001b[1m0s\u001b[0m 63ms/step\n",
      "\u001b[1m1/1\u001b[0m \u001b[32m━━━━━━━━━━━━━━━━━━━━\u001b[0m\u001b[37m\u001b[0m \u001b[1m0s\u001b[0m 48ms/step\n",
      "\u001b[1m1/1\u001b[0m \u001b[32m━━━━━━━━━━━━━━━━━━━━\u001b[0m\u001b[37m\u001b[0m \u001b[1m0s\u001b[0m 62ms/step\n",
      "\u001b[1m1/1\u001b[0m \u001b[32m━━━━━━━━━━━━━━━━━━━━\u001b[0m\u001b[37m\u001b[0m \u001b[1m0s\u001b[0m 62ms/step\n",
      "\u001b[1m1/1\u001b[0m \u001b[32m━━━━━━━━━━━━━━━━━━━━\u001b[0m\u001b[37m\u001b[0m \u001b[1m0s\u001b[0m 58ms/step\n",
      "\u001b[1m1/1\u001b[0m \u001b[32m━━━━━━━━━━━━━━━━━━━━\u001b[0m\u001b[37m\u001b[0m \u001b[1m0s\u001b[0m 78ms/step\n",
      "\u001b[1m1/1\u001b[0m \u001b[32m━━━━━━━━━━━━━━━━━━━━\u001b[0m\u001b[37m\u001b[0m \u001b[1m0s\u001b[0m 56ms/step\n",
      "\u001b[1m1/1\u001b[0m \u001b[32m━━━━━━━━━━━━━━━━━━━━\u001b[0m\u001b[37m\u001b[0m \u001b[1m0s\u001b[0m 62ms/step\n",
      "\u001b[1m1/1\u001b[0m \u001b[32m━━━━━━━━━━━━━━━━━━━━\u001b[0m\u001b[37m\u001b[0m \u001b[1m0s\u001b[0m 57ms/step\n",
      "\u001b[1m1/1\u001b[0m \u001b[32m━━━━━━━━━━━━━━━━━━━━\u001b[0m\u001b[37m\u001b[0m \u001b[1m0s\u001b[0m 59ms/step\n",
      "\u001b[1m1/1\u001b[0m \u001b[32m━━━━━━━━━━━━━━━━━━━━\u001b[0m\u001b[37m\u001b[0m \u001b[1m0s\u001b[0m 40ms/step\n",
      "\u001b[1m1/1\u001b[0m \u001b[32m━━━━━━━━━━━━━━━━━━━━\u001b[0m\u001b[37m\u001b[0m \u001b[1m0s\u001b[0m 38ms/step\n",
      "\u001b[1m1/1\u001b[0m \u001b[32m━━━━━━━━━━━━━━━━━━━━\u001b[0m\u001b[37m\u001b[0m \u001b[1m0s\u001b[0m 49ms/step\n",
      "\u001b[1m1/1\u001b[0m \u001b[32m━━━━━━━━━━━━━━━━━━━━\u001b[0m\u001b[37m\u001b[0m \u001b[1m0s\u001b[0m 55ms/step\n",
      "\u001b[1m1/1\u001b[0m \u001b[32m━━━━━━━━━━━━━━━━━━━━\u001b[0m\u001b[37m\u001b[0m \u001b[1m0s\u001b[0m 47ms/step\n",
      "\u001b[1m1/1\u001b[0m \u001b[32m━━━━━━━━━━━━━━━━━━━━\u001b[0m\u001b[37m\u001b[0m \u001b[1m0s\u001b[0m 57ms/step\n",
      "\u001b[1m1/1\u001b[0m \u001b[32m━━━━━━━━━━━━━━━━━━━━\u001b[0m\u001b[37m\u001b[0m \u001b[1m0s\u001b[0m 62ms/step\n",
      "\u001b[1m1/1\u001b[0m \u001b[32m━━━━━━━━━━━━━━━━━━━━\u001b[0m\u001b[37m\u001b[0m \u001b[1m0s\u001b[0m 60ms/step\n",
      "\u001b[1m1/1\u001b[0m \u001b[32m━━━━━━━━━━━━━━━━━━━━\u001b[0m\u001b[37m\u001b[0m \u001b[1m0s\u001b[0m 62ms/step\n",
      "\u001b[1m1/1\u001b[0m \u001b[32m━━━━━━━━━━━━━━━━━━━━\u001b[0m\u001b[37m\u001b[0m \u001b[1m0s\u001b[0m 54ms/step\n",
      "\u001b[1m1/1\u001b[0m \u001b[32m━━━━━━━━━━━━━━━━━━━━\u001b[0m\u001b[37m\u001b[0m \u001b[1m0s\u001b[0m 48ms/step\n",
      "\u001b[1m1/1\u001b[0m \u001b[32m━━━━━━━━━━━━━━━━━━━━\u001b[0m\u001b[37m\u001b[0m \u001b[1m0s\u001b[0m 62ms/step\n",
      "\u001b[1m1/1\u001b[0m \u001b[32m━━━━━━━━━━━━━━━━━━━━\u001b[0m\u001b[37m\u001b[0m \u001b[1m0s\u001b[0m 62ms/step\n",
      "\u001b[1m1/1\u001b[0m \u001b[32m━━━━━━━━━━━━━━━━━━━━\u001b[0m\u001b[37m\u001b[0m \u001b[1m0s\u001b[0m 48ms/step\n",
      "\u001b[1m1/1\u001b[0m \u001b[32m━━━━━━━━━━━━━━━━━━━━\u001b[0m\u001b[37m\u001b[0m \u001b[1m0s\u001b[0m 57ms/step\n",
      "\u001b[1m1/1\u001b[0m \u001b[32m━━━━━━━━━━━━━━━━━━━━\u001b[0m\u001b[37m\u001b[0m \u001b[1m0s\u001b[0m 40ms/step\n",
      "\u001b[1m1/1\u001b[0m \u001b[32m━━━━━━━━━━━━━━━━━━━━\u001b[0m\u001b[37m\u001b[0m \u001b[1m0s\u001b[0m 62ms/step\n",
      "\u001b[1m1/1\u001b[0m \u001b[32m━━━━━━━━━━━━━━━━━━━━\u001b[0m\u001b[37m\u001b[0m \u001b[1m0s\u001b[0m 62ms/step\n",
      "\u001b[1m1/1\u001b[0m \u001b[32m━━━━━━━━━━━━━━━━━━━━\u001b[0m\u001b[37m\u001b[0m \u001b[1m0s\u001b[0m 57ms/step\n",
      "\u001b[1m1/1\u001b[0m \u001b[32m━━━━━━━━━━━━━━━━━━━━\u001b[0m\u001b[37m\u001b[0m \u001b[1m0s\u001b[0m 55ms/step\n",
      "\u001b[1m1/1\u001b[0m \u001b[32m━━━━━━━━━━━━━━━━━━━━\u001b[0m\u001b[37m\u001b[0m \u001b[1m0s\u001b[0m 60ms/step\n",
      "\u001b[1m1/1\u001b[0m \u001b[32m━━━━━━━━━━━━━━━━━━━━\u001b[0m\u001b[37m\u001b[0m \u001b[1m0s\u001b[0m 55ms/step\n",
      "\u001b[1m1/1\u001b[0m \u001b[32m━━━━━━━━━━━━━━━━━━━━\u001b[0m\u001b[37m\u001b[0m \u001b[1m0s\u001b[0m 56ms/step\n",
      "\u001b[1m1/1\u001b[0m \u001b[32m━━━━━━━━━━━━━━━━━━━━\u001b[0m\u001b[37m\u001b[0m \u001b[1m0s\u001b[0m 66ms/step\n",
      "\u001b[1m1/1\u001b[0m \u001b[32m━━━━━━━━━━━━━━━━━━━━\u001b[0m\u001b[37m\u001b[0m \u001b[1m0s\u001b[0m 56ms/step\n",
      "\u001b[1m1/1\u001b[0m \u001b[32m━━━━━━━━━━━━━━━━━━━━\u001b[0m\u001b[37m\u001b[0m \u001b[1m0s\u001b[0m 63ms/step\n",
      "\u001b[1m1/1\u001b[0m \u001b[32m━━━━━━━━━━━━━━━━━━━━\u001b[0m\u001b[37m\u001b[0m \u001b[1m0s\u001b[0m 54ms/step\n",
      "\u001b[1m1/1\u001b[0m \u001b[32m━━━━━━━━━━━━━━━━━━━━\u001b[0m\u001b[37m\u001b[0m \u001b[1m0s\u001b[0m 39ms/step\n",
      "\u001b[1m1/1\u001b[0m \u001b[32m━━━━━━━━━━━━━━━━━━━━\u001b[0m\u001b[37m\u001b[0m \u001b[1m0s\u001b[0m 61ms/step\n",
      "\u001b[1m1/1\u001b[0m \u001b[32m━━━━━━━━━━━━━━━━━━━━\u001b[0m\u001b[37m\u001b[0m \u001b[1m0s\u001b[0m 66ms/step\n",
      "\u001b[1m1/1\u001b[0m \u001b[32m━━━━━━━━━━━━━━━━━━━━\u001b[0m\u001b[37m\u001b[0m \u001b[1m0s\u001b[0m 48ms/step\n",
      "\u001b[1m1/1\u001b[0m \u001b[32m━━━━━━━━━━━━━━━━━━━━\u001b[0m\u001b[37m\u001b[0m \u001b[1m0s\u001b[0m 69ms/step\n",
      "\u001b[1m1/1\u001b[0m \u001b[32m━━━━━━━━━━━━━━━━━━━━\u001b[0m\u001b[37m\u001b[0m \u001b[1m0s\u001b[0m 56ms/step\n",
      "\u001b[1m1/1\u001b[0m \u001b[32m━━━━━━━━━━━━━━━━━━━━\u001b[0m\u001b[37m\u001b[0m \u001b[1m0s\u001b[0m 56ms/step\n",
      "\u001b[1m1/1\u001b[0m \u001b[32m━━━━━━━━━━━━━━━━━━━━\u001b[0m\u001b[37m\u001b[0m \u001b[1m0s\u001b[0m 60ms/step\n",
      "\u001b[1m1/1\u001b[0m \u001b[32m━━━━━━━━━━━━━━━━━━━━\u001b[0m\u001b[37m\u001b[0m \u001b[1m0s\u001b[0m 57ms/step\n",
      "\u001b[1m1/1\u001b[0m \u001b[32m━━━━━━━━━━━━━━━━━━━━\u001b[0m\u001b[37m\u001b[0m \u001b[1m0s\u001b[0m 56ms/step\n",
      "\u001b[1m1/1\u001b[0m \u001b[32m━━━━━━━━━━━━━━━━━━━━\u001b[0m\u001b[37m\u001b[0m \u001b[1m0s\u001b[0m 66ms/step\n",
      "\u001b[1m1/1\u001b[0m \u001b[32m━━━━━━━━━━━━━━━━━━━━\u001b[0m\u001b[37m\u001b[0m \u001b[1m0s\u001b[0m 55ms/step\n",
      "\u001b[1m1/1\u001b[0m \u001b[32m━━━━━━━━━━━━━━━━━━━━\u001b[0m\u001b[37m\u001b[0m \u001b[1m0s\u001b[0m 65ms/step\n",
      "\u001b[1m1/1\u001b[0m \u001b[32m━━━━━━━━━━━━━━━━━━━━\u001b[0m\u001b[37m\u001b[0m \u001b[1m0s\u001b[0m 48ms/step\n",
      "\u001b[1m1/1\u001b[0m \u001b[32m━━━━━━━━━━━━━━━━━━━━\u001b[0m\u001b[37m\u001b[0m \u001b[1m0s\u001b[0m 58ms/step\n",
      "\u001b[1m1/1\u001b[0m \u001b[32m━━━━━━━━━━━━━━━━━━━━\u001b[0m\u001b[37m\u001b[0m \u001b[1m0s\u001b[0m 46ms/step\n",
      "\u001b[1m1/1\u001b[0m \u001b[32m━━━━━━━━━━━━━━━━━━━━\u001b[0m\u001b[37m\u001b[0m \u001b[1m0s\u001b[0m 48ms/step\n",
      "\u001b[1m1/1\u001b[0m \u001b[32m━━━━━━━━━━━━━━━━━━━━\u001b[0m\u001b[37m\u001b[0m \u001b[1m0s\u001b[0m 47ms/step\n",
      "\u001b[1m1/1\u001b[0m \u001b[32m━━━━━━━━━━━━━━━━━━━━\u001b[0m\u001b[37m\u001b[0m \u001b[1m0s\u001b[0m 54ms/step\n",
      "\u001b[1m1/1\u001b[0m \u001b[32m━━━━━━━━━━━━━━━━━━━━\u001b[0m\u001b[37m\u001b[0m \u001b[1m0s\u001b[0m 62ms/step\n",
      "\u001b[1m1/1\u001b[0m \u001b[32m━━━━━━━━━━━━━━━━━━━━\u001b[0m\u001b[37m\u001b[0m \u001b[1m0s\u001b[0m 54ms/step\n",
      "\u001b[1m1/1\u001b[0m \u001b[32m━━━━━━━━━━━━━━━━━━━━\u001b[0m\u001b[37m\u001b[0m \u001b[1m0s\u001b[0m 56ms/step\n",
      "\u001b[1m1/1\u001b[0m \u001b[32m━━━━━━━━━━━━━━━━━━━━\u001b[0m\u001b[37m\u001b[0m \u001b[1m0s\u001b[0m 62ms/step\n",
      "\u001b[1m1/1\u001b[0m \u001b[32m━━━━━━━━━━━━━━━━━━━━\u001b[0m\u001b[37m\u001b[0m \u001b[1m0s\u001b[0m 47ms/step\n",
      "\u001b[1m1/1\u001b[0m \u001b[32m━━━━━━━━━━━━━━━━━━━━\u001b[0m\u001b[37m\u001b[0m \u001b[1m0s\u001b[0m 48ms/step\n",
      "\u001b[1m1/1\u001b[0m \u001b[32m━━━━━━━━━━━━━━━━━━━━\u001b[0m\u001b[37m\u001b[0m \u001b[1m0s\u001b[0m 62ms/step\n",
      "\u001b[1m1/1\u001b[0m \u001b[32m━━━━━━━━━━━━━━━━━━━━\u001b[0m\u001b[37m\u001b[0m \u001b[1m0s\u001b[0m 62ms/step\n",
      "\u001b[1m1/1\u001b[0m \u001b[32m━━━━━━━━━━━━━━━━━━━━\u001b[0m\u001b[37m\u001b[0m \u001b[1m0s\u001b[0m 43ms/step\n",
      "\u001b[1m1/1\u001b[0m \u001b[32m━━━━━━━━━━━━━━━━━━━━\u001b[0m\u001b[37m\u001b[0m \u001b[1m0s\u001b[0m 62ms/step\n",
      "\u001b[1m1/1\u001b[0m \u001b[32m━━━━━━━━━━━━━━━━━━━━\u001b[0m\u001b[37m\u001b[0m \u001b[1m0s\u001b[0m 53ms/step\n",
      "\u001b[1m1/1\u001b[0m \u001b[32m━━━━━━━━━━━━━━━━━━━━\u001b[0m\u001b[37m\u001b[0m \u001b[1m0s\u001b[0m 42ms/step\n",
      "\u001b[1m1/1\u001b[0m \u001b[32m━━━━━━━━━━━━━━━━━━━━\u001b[0m\u001b[37m\u001b[0m \u001b[1m0s\u001b[0m 53ms/step\n",
      "\u001b[1m1/1\u001b[0m \u001b[32m━━━━━━━━━━━━━━━━━━━━\u001b[0m\u001b[37m\u001b[0m \u001b[1m0s\u001b[0m 40ms/step\n",
      "\u001b[1m1/1\u001b[0m \u001b[32m━━━━━━━━━━━━━━━━━━━━\u001b[0m\u001b[37m\u001b[0m \u001b[1m0s\u001b[0m 52ms/step\n",
      "\u001b[1m1/1\u001b[0m \u001b[32m━━━━━━━━━━━━━━━━━━━━\u001b[0m\u001b[37m\u001b[0m \u001b[1m0s\u001b[0m 65ms/step\n",
      "\u001b[1m1/1\u001b[0m \u001b[32m━━━━━━━━━━━━━━━━━━━━\u001b[0m\u001b[37m\u001b[0m \u001b[1m0s\u001b[0m 54ms/step\n",
      "\u001b[1m1/1\u001b[0m \u001b[32m━━━━━━━━━━━━━━━━━━━━\u001b[0m\u001b[37m\u001b[0m \u001b[1m0s\u001b[0m 53ms/step\n",
      "\u001b[1m1/1\u001b[0m \u001b[32m━━━━━━━━━━━━━━━━━━━━\u001b[0m\u001b[37m\u001b[0m \u001b[1m0s\u001b[0m 67ms/step\n",
      "\u001b[1m1/1\u001b[0m \u001b[32m━━━━━━━━━━━━━━━━━━━━\u001b[0m\u001b[37m\u001b[0m \u001b[1m0s\u001b[0m 67ms/step\n",
      "\u001b[1m1/1\u001b[0m \u001b[32m━━━━━━━━━━━━━━━━━━━━\u001b[0m\u001b[37m\u001b[0m \u001b[1m0s\u001b[0m 39ms/step\n",
      "\u001b[1m1/1\u001b[0m \u001b[32m━━━━━━━━━━━━━━━━━━━━\u001b[0m\u001b[37m\u001b[0m \u001b[1m0s\u001b[0m 54ms/step\n",
      "\u001b[1m1/1\u001b[0m \u001b[32m━━━━━━━━━━━━━━━━━━━━\u001b[0m\u001b[37m\u001b[0m \u001b[1m0s\u001b[0m 54ms/step\n",
      "\u001b[1m1/1\u001b[0m \u001b[32m━━━━━━━━━━━━━━━━━━━━\u001b[0m\u001b[37m\u001b[0m \u001b[1m0s\u001b[0m 55ms/step\n",
      "\u001b[1m1/1\u001b[0m \u001b[32m━━━━━━━━━━━━━━━━━━━━\u001b[0m\u001b[37m\u001b[0m \u001b[1m0s\u001b[0m 62ms/step\n",
      "\u001b[1m1/1\u001b[0m \u001b[32m━━━━━━━━━━━━━━━━━━━━\u001b[0m\u001b[37m\u001b[0m \u001b[1m0s\u001b[0m 54ms/step\n",
      "\u001b[1m1/1\u001b[0m \u001b[32m━━━━━━━━━━━━━━━━━━━━\u001b[0m\u001b[37m\u001b[0m \u001b[1m0s\u001b[0m 44ms/step\n",
      "\u001b[1m1/1\u001b[0m \u001b[32m━━━━━━━━━━━━━━━━━━━━\u001b[0m\u001b[37m\u001b[0m \u001b[1m0s\u001b[0m 54ms/step\n",
      "\u001b[1m1/1\u001b[0m \u001b[32m━━━━━━━━━━━━━━━━━━━━\u001b[0m\u001b[37m\u001b[0m \u001b[1m0s\u001b[0m 54ms/step\n",
      "\u001b[1m1/1\u001b[0m \u001b[32m━━━━━━━━━━━━━━━━━━━━\u001b[0m\u001b[37m\u001b[0m \u001b[1m0s\u001b[0m 54ms/step\n",
      "\u001b[1m1/1\u001b[0m \u001b[32m━━━━━━━━━━━━━━━━━━━━\u001b[0m\u001b[37m\u001b[0m \u001b[1m0s\u001b[0m 54ms/step\n",
      "\u001b[1m1/1\u001b[0m \u001b[32m━━━━━━━━━━━━━━━━━━━━\u001b[0m\u001b[37m\u001b[0m \u001b[1m0s\u001b[0m 42ms/step\n",
      "\u001b[1m1/1\u001b[0m \u001b[32m━━━━━━━━━━━━━━━━━━━━\u001b[0m\u001b[37m\u001b[0m \u001b[1m0s\u001b[0m 53ms/step\n",
      "\u001b[1m1/1\u001b[0m \u001b[32m━━━━━━━━━━━━━━━━━━━━\u001b[0m\u001b[37m\u001b[0m \u001b[1m0s\u001b[0m 59ms/step\n",
      "\u001b[1m1/1\u001b[0m \u001b[32m━━━━━━━━━━━━━━━━━━━━\u001b[0m\u001b[37m\u001b[0m \u001b[1m0s\u001b[0m 53ms/step\n",
      "\u001b[1m1/1\u001b[0m \u001b[32m━━━━━━━━━━━━━━━━━━━━\u001b[0m\u001b[37m\u001b[0m \u001b[1m0s\u001b[0m 53ms/step\n",
      "\u001b[1m1/1\u001b[0m \u001b[32m━━━━━━━━━━━━━━━━━━━━\u001b[0m\u001b[37m\u001b[0m \u001b[1m0s\u001b[0m 53ms/step\n",
      "\u001b[1m1/1\u001b[0m \u001b[32m━━━━━━━━━━━━━━━━━━━━\u001b[0m\u001b[37m\u001b[0m \u001b[1m0s\u001b[0m 47ms/step\n",
      "\u001b[1m1/1\u001b[0m \u001b[32m━━━━━━━━━━━━━━━━━━━━\u001b[0m\u001b[37m\u001b[0m \u001b[1m0s\u001b[0m 55ms/step\n",
      "\u001b[1m1/1\u001b[0m \u001b[32m━━━━━━━━━━━━━━━━━━━━\u001b[0m\u001b[37m\u001b[0m \u001b[1m0s\u001b[0m 53ms/step\n",
      "\u001b[1m1/1\u001b[0m \u001b[32m━━━━━━━━━━━━━━━━━━━━\u001b[0m\u001b[37m\u001b[0m \u001b[1m0s\u001b[0m 54ms/step\n",
      "\u001b[1m1/1\u001b[0m \u001b[32m━━━━━━━━━━━━━━━━━━━━\u001b[0m\u001b[37m\u001b[0m \u001b[1m0s\u001b[0m 62ms/step\n",
      "\u001b[1m1/1\u001b[0m \u001b[32m━━━━━━━━━━━━━━━━━━━━\u001b[0m\u001b[37m\u001b[0m \u001b[1m0s\u001b[0m 52ms/step\n",
      "\u001b[1m1/1\u001b[0m \u001b[32m━━━━━━━━━━━━━━━━━━━━\u001b[0m\u001b[37m\u001b[0m \u001b[1m0s\u001b[0m 67ms/step\n",
      "\u001b[1m1/1\u001b[0m \u001b[32m━━━━━━━━━━━━━━━━━━━━\u001b[0m\u001b[37m\u001b[0m \u001b[1m0s\u001b[0m 46ms/step\n",
      "\u001b[1m1/1\u001b[0m \u001b[32m━━━━━━━━━━━━━━━━━━━━\u001b[0m\u001b[37m\u001b[0m \u001b[1m0s\u001b[0m 53ms/step\n",
      "\u001b[1m1/1\u001b[0m \u001b[32m━━━━━━━━━━━━━━━━━━━━\u001b[0m\u001b[37m\u001b[0m \u001b[1m0s\u001b[0m 54ms/step\n",
      "\u001b[1m1/1\u001b[0m \u001b[32m━━━━━━━━━━━━━━━━━━━━\u001b[0m\u001b[37m\u001b[0m \u001b[1m0s\u001b[0m 54ms/step\n",
      "\u001b[1m1/1\u001b[0m \u001b[32m━━━━━━━━━━━━━━━━━━━━\u001b[0m\u001b[37m\u001b[0m \u001b[1m0s\u001b[0m 54ms/step\n",
      "\u001b[1m1/1\u001b[0m \u001b[32m━━━━━━━━━━━━━━━━━━━━\u001b[0m\u001b[37m\u001b[0m \u001b[1m0s\u001b[0m 49ms/step\n",
      "\u001b[1m1/1\u001b[0m \u001b[32m━━━━━━━━━━━━━━━━━━━━\u001b[0m\u001b[37m\u001b[0m \u001b[1m0s\u001b[0m 43ms/step\n",
      "\u001b[1m1/1\u001b[0m \u001b[32m━━━━━━━━━━━━━━━━━━━━\u001b[0m\u001b[37m\u001b[0m \u001b[1m0s\u001b[0m 53ms/step\n",
      "\u001b[1m1/1\u001b[0m \u001b[32m━━━━━━━━━━━━━━━━━━━━\u001b[0m\u001b[37m\u001b[0m \u001b[1m0s\u001b[0m 56ms/step\n",
      "\u001b[1m1/1\u001b[0m \u001b[32m━━━━━━━━━━━━━━━━━━━━\u001b[0m\u001b[37m\u001b[0m \u001b[1m0s\u001b[0m 64ms/step\n",
      "\u001b[1m1/1\u001b[0m \u001b[32m━━━━━━━━━━━━━━━━━━━━\u001b[0m\u001b[37m\u001b[0m \u001b[1m0s\u001b[0m 49ms/step\n",
      "\u001b[1m1/1\u001b[0m \u001b[32m━━━━━━━━━━━━━━━━━━━━\u001b[0m\u001b[37m\u001b[0m \u001b[1m0s\u001b[0m 44ms/step\n",
      "\u001b[1m1/1\u001b[0m \u001b[32m━━━━━━━━━━━━━━━━━━━━\u001b[0m\u001b[37m\u001b[0m \u001b[1m0s\u001b[0m 50ms/step\n",
      "\u001b[1m1/1\u001b[0m \u001b[32m━━━━━━━━━━━━━━━━━━━━\u001b[0m\u001b[37m\u001b[0m \u001b[1m0s\u001b[0m 54ms/step\n",
      "\u001b[1m1/1\u001b[0m \u001b[32m━━━━━━━━━━━━━━━━━━━━\u001b[0m\u001b[37m\u001b[0m \u001b[1m0s\u001b[0m 56ms/step\n",
      "\u001b[1m1/1\u001b[0m \u001b[32m━━━━━━━━━━━━━━━━━━━━\u001b[0m\u001b[37m\u001b[0m \u001b[1m0s\u001b[0m 61ms/step\n",
      "\u001b[1m1/1\u001b[0m \u001b[32m━━━━━━━━━━━━━━━━━━━━\u001b[0m\u001b[37m\u001b[0m \u001b[1m0s\u001b[0m 54ms/step\n",
      "\u001b[1m1/1\u001b[0m \u001b[32m━━━━━━━━━━━━━━━━━━━━\u001b[0m\u001b[37m\u001b[0m \u001b[1m0s\u001b[0m 45ms/step\n",
      "\u001b[1m1/1\u001b[0m \u001b[32m━━━━━━━━━━━━━━━━━━━━\u001b[0m\u001b[37m\u001b[0m \u001b[1m0s\u001b[0m 50ms/step\n",
      "\u001b[1m1/1\u001b[0m \u001b[32m━━━━━━━━━━━━━━━━━━━━\u001b[0m\u001b[37m\u001b[0m \u001b[1m0s\u001b[0m 53ms/step\n",
      "\u001b[1m1/1\u001b[0m \u001b[32m━━━━━━━━━━━━━━━━━━━━\u001b[0m\u001b[37m\u001b[0m \u001b[1m0s\u001b[0m 54ms/step\n",
      "\u001b[1m1/1\u001b[0m \u001b[32m━━━━━━━━━━━━━━━━━━━━\u001b[0m\u001b[37m\u001b[0m \u001b[1m0s\u001b[0m 50ms/step\n",
      "\u001b[1m1/1\u001b[0m \u001b[32m━━━━━━━━━━━━━━━━━━━━\u001b[0m\u001b[37m\u001b[0m \u001b[1m0s\u001b[0m 53ms/step\n",
      "\u001b[1m1/1\u001b[0m \u001b[32m━━━━━━━━━━━━━━━━━━━━\u001b[0m\u001b[37m\u001b[0m \u001b[1m0s\u001b[0m 54ms/step\n",
      "\u001b[1m1/1\u001b[0m \u001b[32m━━━━━━━━━━━━━━━━━━━━\u001b[0m\u001b[37m\u001b[0m \u001b[1m0s\u001b[0m 61ms/step\n",
      "\u001b[1m1/1\u001b[0m \u001b[32m━━━━━━━━━━━━━━━━━━━━\u001b[0m\u001b[37m\u001b[0m \u001b[1m0s\u001b[0m 54ms/step\n",
      "\u001b[1m1/1\u001b[0m \u001b[32m━━━━━━━━━━━━━━━━━━━━\u001b[0m\u001b[37m\u001b[0m \u001b[1m0s\u001b[0m 43ms/step\n",
      "\u001b[1m1/1\u001b[0m \u001b[32m━━━━━━━━━━━━━━━━━━━━\u001b[0m\u001b[37m\u001b[0m \u001b[1m0s\u001b[0m 54ms/step\n",
      "\u001b[1m1/1\u001b[0m \u001b[32m━━━━━━━━━━━━━━━━━━━━\u001b[0m\u001b[37m\u001b[0m \u001b[1m0s\u001b[0m 53ms/step\n",
      "\u001b[1m1/1\u001b[0m \u001b[32m━━━━━━━━━━━━━━━━━━━━\u001b[0m\u001b[37m\u001b[0m \u001b[1m0s\u001b[0m 54ms/step\n",
      "\u001b[1m1/1\u001b[0m \u001b[32m━━━━━━━━━━━━━━━━━━━━\u001b[0m\u001b[37m\u001b[0m \u001b[1m0s\u001b[0m 52ms/step\n",
      "\u001b[1m1/1\u001b[0m \u001b[32m━━━━━━━━━━━━━━━━━━━━\u001b[0m\u001b[37m\u001b[0m \u001b[1m0s\u001b[0m 45ms/step\n",
      "\u001b[1m1/1\u001b[0m \u001b[32m━━━━━━━━━━━━━━━━━━━━\u001b[0m\u001b[37m\u001b[0m \u001b[1m0s\u001b[0m 54ms/step\n",
      "\u001b[1m1/1\u001b[0m \u001b[32m━━━━━━━━━━━━━━━━━━━━\u001b[0m\u001b[37m\u001b[0m \u001b[1m0s\u001b[0m 53ms/step\n",
      "\u001b[1m1/1\u001b[0m \u001b[32m━━━━━━━━━━━━━━━━━━━━\u001b[0m\u001b[37m\u001b[0m \u001b[1m0s\u001b[0m 57ms/step\n",
      "\u001b[1m1/1\u001b[0m \u001b[32m━━━━━━━━━━━━━━━━━━━━\u001b[0m\u001b[37m\u001b[0m \u001b[1m0s\u001b[0m 62ms/step\n",
      "\u001b[1m1/1\u001b[0m \u001b[32m━━━━━━━━━━━━━━━━━━━━\u001b[0m\u001b[37m\u001b[0m \u001b[1m0s\u001b[0m 52ms/step\n",
      "\u001b[1m1/1\u001b[0m \u001b[32m━━━━━━━━━━━━━━━━━━━━\u001b[0m\u001b[37m\u001b[0m \u001b[1m0s\u001b[0m 53ms/step\n",
      "\u001b[1m1/1\u001b[0m \u001b[32m━━━━━━━━━━━━━━━━━━━━\u001b[0m\u001b[37m\u001b[0m \u001b[1m0s\u001b[0m 54ms/step\n",
      "\u001b[1m1/1\u001b[0m \u001b[32m━━━━━━━━━━━━━━━━━━━━\u001b[0m\u001b[37m\u001b[0m \u001b[1m0s\u001b[0m 54ms/step\n",
      "\u001b[1m1/1\u001b[0m \u001b[32m━━━━━━━━━━━━━━━━━━━━\u001b[0m\u001b[37m\u001b[0m \u001b[1m0s\u001b[0m 56ms/step\n",
      "\u001b[1m1/1\u001b[0m \u001b[32m━━━━━━━━━━━━━━━━━━━━\u001b[0m\u001b[37m\u001b[0m \u001b[1m0s\u001b[0m 62ms/step\n",
      "\u001b[1m1/1\u001b[0m \u001b[32m━━━━━━━━━━━━━━━━━━━━\u001b[0m\u001b[37m\u001b[0m \u001b[1m0s\u001b[0m 52ms/step\n",
      "\u001b[1m1/1\u001b[0m \u001b[32m━━━━━━━━━━━━━━━━━━━━\u001b[0m\u001b[37m\u001b[0m \u001b[1m0s\u001b[0m 43ms/step\n",
      "\u001b[1m1/1\u001b[0m \u001b[32m━━━━━━━━━━━━━━━━━━━━\u001b[0m\u001b[37m\u001b[0m \u001b[1m0s\u001b[0m 53ms/step\n",
      "\u001b[1m1/1\u001b[0m \u001b[32m━━━━━━━━━━━━━━━━━━━━\u001b[0m\u001b[37m\u001b[0m \u001b[1m0s\u001b[0m 53ms/step\n",
      "\u001b[1m1/1\u001b[0m \u001b[32m━━━━━━━━━━━━━━━━━━━━\u001b[0m\u001b[37m\u001b[0m \u001b[1m0s\u001b[0m 57ms/step\n",
      "\u001b[1m1/1\u001b[0m \u001b[32m━━━━━━━━━━━━━━━━━━━━\u001b[0m\u001b[37m\u001b[0m \u001b[1m0s\u001b[0m 63ms/step\n",
      "\u001b[1m1/1\u001b[0m \u001b[32m━━━━━━━━━━━━━━━━━━━━\u001b[0m\u001b[37m\u001b[0m \u001b[1m0s\u001b[0m 54ms/step\n",
      "\u001b[1m1/1\u001b[0m \u001b[32m━━━━━━━━━━━━━━━━━━━━\u001b[0m\u001b[37m\u001b[0m \u001b[1m0s\u001b[0m 55ms/step\n",
      "\u001b[1m1/1\u001b[0m \u001b[32m━━━━━━━━━━━━━━━━━━━━\u001b[0m\u001b[37m\u001b[0m \u001b[1m0s\u001b[0m 72ms/step\n",
      "\u001b[1m1/1\u001b[0m \u001b[32m━━━━━━━━━━━━━━━━━━━━\u001b[0m\u001b[37m\u001b[0m \u001b[1m0s\u001b[0m 64ms/step\n",
      "\u001b[1m1/1\u001b[0m \u001b[32m━━━━━━━━━━━━━━━━━━━━\u001b[0m\u001b[37m\u001b[0m \u001b[1m0s\u001b[0m 43ms/step\n",
      "\u001b[1m1/1\u001b[0m \u001b[32m━━━━━━━━━━━━━━━━━━━━\u001b[0m\u001b[37m\u001b[0m \u001b[1m0s\u001b[0m 54ms/step\n",
      "\u001b[1m1/1\u001b[0m \u001b[32m━━━━━━━━━━━━━━━━━━━━\u001b[0m\u001b[37m\u001b[0m \u001b[1m0s\u001b[0m 54ms/step\n",
      "\u001b[1m1/1\u001b[0m \u001b[32m━━━━━━━━━━━━━━━━━━━━\u001b[0m\u001b[37m\u001b[0m \u001b[1m0s\u001b[0m 59ms/step\n",
      "\u001b[1m1/1\u001b[0m \u001b[32m━━━━━━━━━━━━━━━━━━━━\u001b[0m\u001b[37m\u001b[0m \u001b[1m0s\u001b[0m 54ms/step\n",
      "\u001b[1m1/1\u001b[0m \u001b[32m━━━━━━━━━━━━━━━━━━━━\u001b[0m\u001b[37m\u001b[0m \u001b[1m0s\u001b[0m 54ms/step\n",
      "\u001b[1m1/1\u001b[0m \u001b[32m━━━━━━━━━━━━━━━━━━━━\u001b[0m\u001b[37m\u001b[0m \u001b[1m0s\u001b[0m 59ms/step\n",
      "\u001b[1m1/1\u001b[0m \u001b[32m━━━━━━━━━━━━━━━━━━━━\u001b[0m\u001b[37m\u001b[0m \u001b[1m0s\u001b[0m 67ms/step\n",
      "\u001b[1m1/1\u001b[0m \u001b[32m━━━━━━━━━━━━━━━━━━━━\u001b[0m\u001b[37m\u001b[0m \u001b[1m0s\u001b[0m 53ms/step\n",
      "\u001b[1m1/1\u001b[0m \u001b[32m━━━━━━━━━━━━━━━━━━━━\u001b[0m\u001b[37m\u001b[0m \u001b[1m0s\u001b[0m 54ms/step\n",
      "\u001b[1m1/1\u001b[0m \u001b[32m━━━━━━━━━━━━━━━━━━━━\u001b[0m\u001b[37m\u001b[0m \u001b[1m0s\u001b[0m 54ms/step\n",
      "\u001b[1m1/1\u001b[0m \u001b[32m━━━━━━━━━━━━━━━━━━━━\u001b[0m\u001b[37m\u001b[0m \u001b[1m0s\u001b[0m 52ms/step\n",
      "\u001b[1m1/1\u001b[0m \u001b[32m━━━━━━━━━━━━━━━━━━━━\u001b[0m\u001b[37m\u001b[0m \u001b[1m0s\u001b[0m 53ms/step\n",
      "\u001b[1m1/1\u001b[0m \u001b[32m━━━━━━━━━━━━━━━━━━━━\u001b[0m\u001b[37m\u001b[0m \u001b[1m0s\u001b[0m 46ms/step\n",
      "\u001b[1m1/1\u001b[0m \u001b[32m━━━━━━━━━━━━━━━━━━━━\u001b[0m\u001b[37m\u001b[0m \u001b[1m0s\u001b[0m 51ms/step\n",
      "\u001b[1m1/1\u001b[0m \u001b[32m━━━━━━━━━━━━━━━━━━━━\u001b[0m\u001b[37m\u001b[0m \u001b[1m0s\u001b[0m 54ms/step\n",
      "\u001b[1m1/1\u001b[0m \u001b[32m━━━━━━━━━━━━━━━━━━━━\u001b[0m\u001b[37m\u001b[0m \u001b[1m0s\u001b[0m 58ms/step\n",
      "\u001b[1m1/1\u001b[0m \u001b[32m━━━━━━━━━━━━━━━━━━━━\u001b[0m\u001b[37m\u001b[0m \u001b[1m0s\u001b[0m 65ms/step\n",
      "\u001b[1m1/1\u001b[0m \u001b[32m━━━━━━━━━━━━━━━━━━━━\u001b[0m\u001b[37m\u001b[0m \u001b[1m0s\u001b[0m 48ms/step\n",
      "\u001b[1m1/1\u001b[0m \u001b[32m━━━━━━━━━━━━━━━━━━━━\u001b[0m\u001b[37m\u001b[0m \u001b[1m0s\u001b[0m 43ms/step\n",
      "\u001b[1m1/1\u001b[0m \u001b[32m━━━━━━━━━━━━━━━━━━━━\u001b[0m\u001b[37m\u001b[0m \u001b[1m0s\u001b[0m 54ms/step\n",
      "\u001b[1m1/1\u001b[0m \u001b[32m━━━━━━━━━━━━━━━━━━━━\u001b[0m\u001b[37m\u001b[0m \u001b[1m0s\u001b[0m 67ms/step\n",
      "\u001b[1m1/1\u001b[0m \u001b[32m━━━━━━━━━━━━━━━━━━━━\u001b[0m\u001b[37m\u001b[0m \u001b[1m0s\u001b[0m 67ms/step\n",
      "\u001b[1m1/1\u001b[0m \u001b[32m━━━━━━━━━━━━━━━━━━━━\u001b[0m\u001b[37m\u001b[0m \u001b[1m0s\u001b[0m 54ms/step\n",
      "\u001b[1m1/1\u001b[0m \u001b[32m━━━━━━━━━━━━━━━━━━━━\u001b[0m\u001b[37m\u001b[0m \u001b[1m0s\u001b[0m 53ms/step\n",
      "\u001b[1m1/1\u001b[0m \u001b[32m━━━━━━━━━━━━━━━━━━━━\u001b[0m\u001b[37m\u001b[0m \u001b[1m0s\u001b[0m 54ms/step\n",
      "\u001b[1m1/1\u001b[0m \u001b[32m━━━━━━━━━━━━━━━━━━━━\u001b[0m\u001b[37m\u001b[0m \u001b[1m0s\u001b[0m 61ms/step\n",
      "\u001b[1m1/1\u001b[0m \u001b[32m━━━━━━━━━━━━━━━━━━━━\u001b[0m\u001b[37m\u001b[0m \u001b[1m0s\u001b[0m 53ms/step\n",
      "\u001b[1m1/1\u001b[0m \u001b[32m━━━━━━━━━━━━━━━━━━━━\u001b[0m\u001b[37m\u001b[0m \u001b[1m0s\u001b[0m 45ms/step\n",
      "\u001b[1m1/1\u001b[0m \u001b[32m━━━━━━━━━━━━━━━━━━━━\u001b[0m\u001b[37m\u001b[0m \u001b[1m0s\u001b[0m 53ms/step\n",
      "\u001b[1m1/1\u001b[0m \u001b[32m━━━━━━━━━━━━━━━━━━━━\u001b[0m\u001b[37m\u001b[0m \u001b[1m0s\u001b[0m 54ms/step\n",
      "\u001b[1m1/1\u001b[0m \u001b[32m━━━━━━━━━━━━━━━━━━━━\u001b[0m\u001b[37m\u001b[0m \u001b[1m0s\u001b[0m 57ms/step\n",
      "\u001b[1m1/1\u001b[0m \u001b[32m━━━━━━━━━━━━━━━━━━━━\u001b[0m\u001b[37m\u001b[0m \u001b[1m0s\u001b[0m 62ms/step\n",
      "\u001b[1m1/1\u001b[0m \u001b[32m━━━━━━━━━━━━━━━━━━━━\u001b[0m\u001b[37m\u001b[0m \u001b[1m0s\u001b[0m 51ms/step\n",
      "\u001b[1m1/1\u001b[0m \u001b[32m━━━━━━━━━━━━━━━━━━━━\u001b[0m\u001b[37m\u001b[0m \u001b[1m0s\u001b[0m 54ms/step\n",
      "\u001b[1m1/1\u001b[0m \u001b[32m━━━━━━━━━━━━━━━━━━━━\u001b[0m\u001b[37m\u001b[0m \u001b[1m0s\u001b[0m 53ms/step\n",
      "\u001b[1m1/1\u001b[0m \u001b[32m━━━━━━━━━━━━━━━━━━━━\u001b[0m\u001b[37m\u001b[0m \u001b[1m0s\u001b[0m 54ms/step\n",
      "\u001b[1m1/1\u001b[0m \u001b[32m━━━━━━━━━━━━━━━━━━━━\u001b[0m\u001b[37m\u001b[0m \u001b[1m0s\u001b[0m 65ms/step\n",
      "\u001b[1m1/1\u001b[0m \u001b[32m━━━━━━━━━━━━━━━━━━━━\u001b[0m\u001b[37m\u001b[0m \u001b[1m0s\u001b[0m 47ms/step\n",
      "\u001b[1m1/1\u001b[0m \u001b[32m━━━━━━━━━━━━━━━━━━━━\u001b[0m\u001b[37m\u001b[0m \u001b[1m0s\u001b[0m 54ms/step\n",
      "\u001b[1m1/1\u001b[0m \u001b[32m━━━━━━━━━━━━━━━━━━━━\u001b[0m\u001b[37m\u001b[0m \u001b[1m0s\u001b[0m 54ms/step\n",
      "\u001b[1m1/1\u001b[0m \u001b[32m━━━━━━━━━━━━━━━━━━━━\u001b[0m\u001b[37m\u001b[0m \u001b[1m0s\u001b[0m 54ms/step\n",
      "\u001b[1m1/1\u001b[0m \u001b[32m━━━━━━━━━━━━━━━━━━━━\u001b[0m\u001b[37m\u001b[0m \u001b[1m0s\u001b[0m 57ms/step\n",
      "\u001b[1m1/1\u001b[0m \u001b[32m━━━━━━━━━━━━━━━━━━━━\u001b[0m\u001b[37m\u001b[0m \u001b[1m0s\u001b[0m 53ms/step\n",
      "\u001b[1m1/1\u001b[0m \u001b[32m━━━━━━━━━━━━━━━━━━━━\u001b[0m\u001b[37m\u001b[0m \u001b[1m0s\u001b[0m 49ms/step\n",
      "\u001b[1m1/1\u001b[0m \u001b[32m━━━━━━━━━━━━━━━━━━━━\u001b[0m\u001b[37m\u001b[0m \u001b[1m0s\u001b[0m 54ms/step\n",
      "\u001b[1m1/1\u001b[0m \u001b[32m━━━━━━━━━━━━━━━━━━━━\u001b[0m\u001b[37m\u001b[0m \u001b[1m0s\u001b[0m 68ms/step\n",
      "\u001b[1m1/1\u001b[0m \u001b[32m━━━━━━━━━━━━━━━━━━━━\u001b[0m\u001b[37m\u001b[0m \u001b[1m0s\u001b[0m 67ms/step\n",
      "\u001b[1m1/1\u001b[0m \u001b[32m━━━━━━━━━━━━━━━━━━━━\u001b[0m\u001b[37m\u001b[0m \u001b[1m0s\u001b[0m 54ms/step\n",
      "\u001b[1m1/1\u001b[0m \u001b[32m━━━━━━━━━━━━━━━━━━━━\u001b[0m\u001b[37m\u001b[0m \u001b[1m0s\u001b[0m 52ms/step\n",
      "\u001b[1m1/1\u001b[0m \u001b[32m━━━━━━━━━━━━━━━━━━━━\u001b[0m\u001b[37m\u001b[0m \u001b[1m0s\u001b[0m 58ms/step\n",
      "\u001b[1m1/1\u001b[0m \u001b[32m━━━━━━━━━━━━━━━━━━━━\u001b[0m\u001b[37m\u001b[0m \u001b[1m0s\u001b[0m 64ms/step\n",
      "\u001b[1m1/1\u001b[0m \u001b[32m━━━━━━━━━━━━━━━━━━━━\u001b[0m\u001b[37m\u001b[0m \u001b[1m0s\u001b[0m 50ms/step\n",
      "\u001b[1m1/1\u001b[0m \u001b[32m━━━━━━━━━━━━━━━━━━━━\u001b[0m\u001b[37m\u001b[0m \u001b[1m0s\u001b[0m 45ms/step\n",
      "\u001b[1m1/1\u001b[0m \u001b[32m━━━━━━━━━━━━━━━━━━━━\u001b[0m\u001b[37m\u001b[0m \u001b[1m0s\u001b[0m 54ms/step\n",
      "\u001b[1m1/1\u001b[0m \u001b[32m━━━━━━━━━━━━━━━━━━━━\u001b[0m\u001b[37m\u001b[0m \u001b[1m0s\u001b[0m 54ms/step\n",
      "\u001b[1m1/1\u001b[0m \u001b[32m━━━━━━━━━━━━━━━━━━━━\u001b[0m\u001b[37m\u001b[0m \u001b[1m0s\u001b[0m 54ms/step\n",
      "\u001b[1m1/1\u001b[0m \u001b[32m━━━━━━━━━━━━━━━━━━━━\u001b[0m\u001b[37m\u001b[0m \u001b[1m0s\u001b[0m 54ms/step\n",
      "\u001b[1m1/1\u001b[0m \u001b[32m━━━━━━━━━━━━━━━━━━━━\u001b[0m\u001b[37m\u001b[0m \u001b[1m0s\u001b[0m 54ms/step\n",
      "\u001b[1m1/1\u001b[0m \u001b[32m━━━━━━━━━━━━━━━━━━━━\u001b[0m\u001b[37m\u001b[0m \u001b[1m0s\u001b[0m 40ms/step\n",
      "\u001b[1m1/1\u001b[0m \u001b[32m━━━━━━━━━━━━━━━━━━━━\u001b[0m\u001b[37m\u001b[0m \u001b[1m0s\u001b[0m 54ms/step\n",
      "\u001b[1m1/1\u001b[0m \u001b[32m━━━━━━━━━━━━━━━━━━━━\u001b[0m\u001b[37m\u001b[0m \u001b[1m0s\u001b[0m 53ms/step\n",
      "\u001b[1m1/1\u001b[0m \u001b[32m━━━━━━━━━━━━━━━━━━━━\u001b[0m\u001b[37m\u001b[0m \u001b[1m0s\u001b[0m 62ms/step\n",
      "\u001b[1m1/1\u001b[0m \u001b[32m━━━━━━━━━━━━━━━━━━━━\u001b[0m\u001b[37m\u001b[0m \u001b[1m0s\u001b[0m 52ms/step\n",
      "\u001b[1m1/1\u001b[0m \u001b[32m━━━━━━━━━━━━━━━━━━━━\u001b[0m\u001b[37m\u001b[0m \u001b[1m0s\u001b[0m 54ms/step\n",
      "\u001b[1m1/1\u001b[0m \u001b[32m━━━━━━━━━━━━━━━━━━━━\u001b[0m\u001b[37m\u001b[0m \u001b[1m0s\u001b[0m 53ms/step\n",
      "\u001b[1m1/1\u001b[0m \u001b[32m━━━━━━━━━━━━━━━━━━━━\u001b[0m\u001b[37m\u001b[0m \u001b[1m0s\u001b[0m 54ms/step\n",
      "\u001b[1m1/1\u001b[0m \u001b[32m━━━━━━━━━━━━━━━━━━━━\u001b[0m\u001b[37m\u001b[0m \u001b[1m0s\u001b[0m 53ms/step\n",
      "\u001b[1m1/1\u001b[0m \u001b[32m━━━━━━━━━━━━━━━━━━━━\u001b[0m\u001b[37m\u001b[0m \u001b[1m0s\u001b[0m 59ms/step\n",
      "\u001b[1m1/1\u001b[0m \u001b[32m━━━━━━━━━━━━━━━━━━━━\u001b[0m\u001b[37m\u001b[0m \u001b[1m0s\u001b[0m 65ms/step\n",
      "\u001b[1m1/1\u001b[0m \u001b[32m━━━━━━━━━━━━━━━━━━━━\u001b[0m\u001b[37m\u001b[0m \u001b[1m0s\u001b[0m 49ms/step\n",
      "\u001b[1m1/1\u001b[0m \u001b[32m━━━━━━━━━━━━━━━━━━━━\u001b[0m\u001b[37m\u001b[0m \u001b[1m0s\u001b[0m 67ms/step\n",
      "\u001b[1m1/1\u001b[0m \u001b[32m━━━━━━━━━━━━━━━━━━━━\u001b[0m\u001b[37m\u001b[0m \u001b[1m0s\u001b[0m 67ms/step\n",
      "\u001b[1m1/1\u001b[0m \u001b[32m━━━━━━━━━━━━━━━━━━━━\u001b[0m\u001b[37m\u001b[0m \u001b[1m0s\u001b[0m 54ms/step\n",
      "\u001b[1m1/1\u001b[0m \u001b[32m━━━━━━━━━━━━━━━━━━━━\u001b[0m\u001b[37m\u001b[0m \u001b[1m0s\u001b[0m 54ms/step\n",
      "\u001b[1m1/1\u001b[0m \u001b[32m━━━━━━━━━━━━━━━━━━━━\u001b[0m\u001b[37m\u001b[0m \u001b[1m0s\u001b[0m 53ms/step\n",
      "\u001b[1m1/1\u001b[0m \u001b[32m━━━━━━━━━━━━━━━━━━━━\u001b[0m\u001b[37m\u001b[0m \u001b[1m0s\u001b[0m 54ms/step\n",
      "\u001b[1m1/1\u001b[0m \u001b[32m━━━━━━━━━━━━━━━━━━━━\u001b[0m\u001b[37m\u001b[0m \u001b[1m0s\u001b[0m 54ms/step\n",
      "\u001b[1m1/1\u001b[0m \u001b[32m━━━━━━━━━━━━━━━━━━━━\u001b[0m\u001b[37m\u001b[0m \u001b[1m0s\u001b[0m 56ms/step\n",
      "\u001b[1m1/1\u001b[0m \u001b[32m━━━━━━━━━━━━━━━━━━━━\u001b[0m\u001b[37m\u001b[0m \u001b[1m0s\u001b[0m 53ms/step\n",
      "\u001b[1m1/1\u001b[0m \u001b[32m━━━━━━━━━━━━━━━━━━━━\u001b[0m\u001b[37m\u001b[0m \u001b[1m0s\u001b[0m 52ms/step\n",
      "\u001b[1m1/1\u001b[0m \u001b[32m━━━━━━━━━━━━━━━━━━━━\u001b[0m\u001b[37m\u001b[0m \u001b[1m0s\u001b[0m 44ms/step\n",
      "\u001b[1m1/1\u001b[0m \u001b[32m━━━━━━━━━━━━━━━━━━━━\u001b[0m\u001b[37m\u001b[0m \u001b[1m0s\u001b[0m 54ms/step\n",
      "\u001b[1m1/1\u001b[0m \u001b[32m━━━━━━━━━━━━━━━━━━━━\u001b[0m\u001b[37m\u001b[0m \u001b[1m0s\u001b[0m 53ms/step\n",
      "\u001b[1m1/1\u001b[0m \u001b[32m━━━━━━━━━━━━━━━━━━━━\u001b[0m\u001b[37m\u001b[0m \u001b[1m0s\u001b[0m 54ms/step\n",
      "\u001b[1m1/1\u001b[0m \u001b[32m━━━━━━━━━━━━━━━━━━━━\u001b[0m\u001b[37m\u001b[0m \u001b[1m0s\u001b[0m 47ms/step\n",
      "\u001b[1m1/1\u001b[0m \u001b[32m━━━━━━━━━━━━━━━━━━━━\u001b[0m\u001b[37m\u001b[0m \u001b[1m0s\u001b[0m 42ms/step\n",
      "\u001b[1m1/1\u001b[0m \u001b[32m━━━━━━━━━━━━━━━━━━━━\u001b[0m\u001b[37m\u001b[0m \u001b[1m0s\u001b[0m 62ms/step\n",
      "\u001b[1m1/1\u001b[0m \u001b[32m━━━━━━━━━━━━━━━━━━━━\u001b[0m\u001b[37m\u001b[0m \u001b[1m0s\u001b[0m 53ms/step\n",
      "\u001b[1m1/1\u001b[0m \u001b[32m━━━━━━━━━━━━━━━━━━━━\u001b[0m\u001b[37m\u001b[0m \u001b[1m0s\u001b[0m 52ms/step\n",
      "\u001b[1m1/1\u001b[0m \u001b[32m━━━━━━━━━━━━━━━━━━━━\u001b[0m\u001b[37m\u001b[0m \u001b[1m0s\u001b[0m 44ms/step\n",
      "\u001b[1m1/1\u001b[0m \u001b[32m━━━━━━━━━━━━━━━━━━━━\u001b[0m\u001b[37m\u001b[0m \u001b[1m0s\u001b[0m 54ms/step\n",
      "\u001b[1m1/1\u001b[0m \u001b[32m━━━━━━━━━━━━━━━━━━━━\u001b[0m\u001b[37m\u001b[0m \u001b[1m0s\u001b[0m 53ms/step\n",
      "\u001b[1m1/1\u001b[0m \u001b[32m━━━━━━━━━━━━━━━━━━━━\u001b[0m\u001b[37m\u001b[0m \u001b[1m0s\u001b[0m 54ms/step\n",
      "\u001b[1m1/1\u001b[0m \u001b[32m━━━━━━━━━━━━━━━━━━━━\u001b[0m\u001b[37m\u001b[0m \u001b[1m0s\u001b[0m 64ms/step\n",
      "\u001b[1m1/1\u001b[0m \u001b[32m━━━━━━━━━━━━━━━━━━━━\u001b[0m\u001b[37m\u001b[0m \u001b[1m0s\u001b[0m 51ms/step\n",
      "\u001b[1m1/1\u001b[0m \u001b[32m━━━━━━━━━━━━━━━━━━━━\u001b[0m\u001b[37m\u001b[0m \u001b[1m0s\u001b[0m 54ms/step\n",
      "\u001b[1m1/1\u001b[0m \u001b[32m━━━━━━━━━━━━━━━━━━━━\u001b[0m\u001b[37m\u001b[0m \u001b[1m0s\u001b[0m 53ms/step\n",
      "\u001b[1m1/1\u001b[0m \u001b[32m━━━━━━━━━━━━━━━━━━━━\u001b[0m\u001b[37m\u001b[0m \u001b[1m0s\u001b[0m 55ms/step\n",
      "\u001b[1m1/1\u001b[0m \u001b[32m━━━━━━━━━━━━━━━━━━━━\u001b[0m\u001b[37m\u001b[0m \u001b[1m0s\u001b[0m 47ms/step\n",
      "\u001b[1m1/1\u001b[0m \u001b[32m━━━━━━━━━━━━━━━━━━━━\u001b[0m\u001b[37m\u001b[0m \u001b[1m0s\u001b[0m 54ms/step\n",
      "\u001b[1m1/1\u001b[0m \u001b[32m━━━━━━━━━━━━━━━━━━━━\u001b[0m\u001b[37m\u001b[0m \u001b[1m0s\u001b[0m 53ms/step\n",
      "\u001b[1m1/1\u001b[0m \u001b[32m━━━━━━━━━━━━━━━━━━━━\u001b[0m\u001b[37m\u001b[0m \u001b[1m0s\u001b[0m 53ms/step\n",
      "\u001b[1m1/1\u001b[0m \u001b[32m━━━━━━━━━━━━━━━━━━━━\u001b[0m\u001b[37m\u001b[0m \u001b[1m0s\u001b[0m 54ms/step\n",
      "\u001b[1m1/1\u001b[0m \u001b[32m━━━━━━━━━━━━━━━━━━━━\u001b[0m\u001b[37m\u001b[0m \u001b[1m0s\u001b[0m 53ms/step\n",
      "\u001b[1m1/1\u001b[0m \u001b[32m━━━━━━━━━━━━━━━━━━━━\u001b[0m\u001b[37m\u001b[0m \u001b[1m0s\u001b[0m 67ms/step\n",
      "\u001b[1m1/1\u001b[0m \u001b[32m━━━━━━━━━━━━━━━━━━━━\u001b[0m\u001b[37m\u001b[0m \u001b[1m0s\u001b[0m 49ms/step\n",
      "\u001b[1m1/1\u001b[0m \u001b[32m━━━━━━━━━━━━━━━━━━━━\u001b[0m\u001b[37m\u001b[0m \u001b[1m0s\u001b[0m 54ms/step\n",
      "\u001b[1m1/1\u001b[0m \u001b[32m━━━━━━━━━━━━━━━━━━━━\u001b[0m\u001b[37m\u001b[0m \u001b[1m0s\u001b[0m 53ms/step\n",
      "\u001b[1m1/1\u001b[0m \u001b[32m━━━━━━━━━━━━━━━━━━━━\u001b[0m\u001b[37m\u001b[0m \u001b[1m0s\u001b[0m 54ms/step\n",
      "\u001b[1m1/1\u001b[0m \u001b[32m━━━━━━━━━━━━━━━━━━━━\u001b[0m\u001b[37m\u001b[0m \u001b[1m0s\u001b[0m 56ms/step\n",
      "\u001b[1m1/1\u001b[0m \u001b[32m━━━━━━━━━━━━━━━━━━━━\u001b[0m\u001b[37m\u001b[0m \u001b[1m0s\u001b[0m 54ms/step\n",
      "\u001b[1m1/1\u001b[0m \u001b[32m━━━━━━━━━━━━━━━━━━━━\u001b[0m\u001b[37m\u001b[0m \u001b[1m0s\u001b[0m 54ms/step\n",
      "\u001b[1m1/1\u001b[0m \u001b[32m━━━━━━━━━━━━━━━━━━━━\u001b[0m\u001b[37m\u001b[0m \u001b[1m0s\u001b[0m 43ms/step\n",
      "\u001b[1m1/1\u001b[0m \u001b[32m━━━━━━━━━━━━━━━━━━━━\u001b[0m\u001b[37m\u001b[0m \u001b[1m0s\u001b[0m 54ms/step\n",
      "\u001b[1m1/1\u001b[0m \u001b[32m━━━━━━━━━━━━━━━━━━━━\u001b[0m\u001b[37m\u001b[0m \u001b[1m0s\u001b[0m 53ms/step\n",
      "\u001b[1m1/1\u001b[0m \u001b[32m━━━━━━━━━━━━━━━━━━━━\u001b[0m\u001b[37m\u001b[0m \u001b[1m0s\u001b[0m 60ms/step\n",
      "\u001b[1m1/1\u001b[0m \u001b[32m━━━━━━━━━━━━━━━━━━━━\u001b[0m\u001b[37m\u001b[0m \u001b[1m0s\u001b[0m 64ms/step\n",
      "\u001b[1m1/1\u001b[0m \u001b[32m━━━━━━━━━━━━━━━━━━━━\u001b[0m\u001b[37m\u001b[0m \u001b[1m0s\u001b[0m 51ms/step\n",
      "\u001b[1m1/1\u001b[0m \u001b[32m━━━━━━━━━━━━━━━━━━━━\u001b[0m\u001b[37m\u001b[0m \u001b[1m0s\u001b[0m 54ms/step\n",
      "\u001b[1m1/1\u001b[0m \u001b[32m━━━━━━━━━━━━━━━━━━━━\u001b[0m\u001b[37m\u001b[0m \u001b[1m0s\u001b[0m 53ms/step\n",
      "\u001b[1m1/1\u001b[0m \u001b[32m━━━━━━━━━━━━━━━━━━━━\u001b[0m\u001b[37m\u001b[0m \u001b[1m0s\u001b[0m 61ms/step\n",
      "\u001b[1m1/1\u001b[0m \u001b[32m━━━━━━━━━━━━━━━━━━━━\u001b[0m\u001b[37m\u001b[0m \u001b[1m0s\u001b[0m 50ms/step\n",
      "\u001b[1m1/1\u001b[0m \u001b[32m━━━━━━━━━━━━━━━━━━━━\u001b[0m\u001b[37m\u001b[0m \u001b[1m0s\u001b[0m 54ms/step\n",
      "\u001b[1m1/1\u001b[0m \u001b[32m━━━━━━━━━━━━━━━━━━━━\u001b[0m\u001b[37m\u001b[0m \u001b[1m0s\u001b[0m 56ms/step\n",
      "\u001b[1m1/1\u001b[0m \u001b[32m━━━━━━━━━━━━━━━━━━━━\u001b[0m\u001b[37m\u001b[0m \u001b[1m0s\u001b[0m 54ms/step\n",
      "\u001b[1m1/1\u001b[0m \u001b[32m━━━━━━━━━━━━━━━━━━━━\u001b[0m\u001b[37m\u001b[0m \u001b[1m0s\u001b[0m 66ms/step\n",
      "\u001b[1m1/1\u001b[0m \u001b[32m━━━━━━━━━━━━━━━━━━━━\u001b[0m\u001b[37m\u001b[0m \u001b[1m0s\u001b[0m 48ms/step\n",
      "\u001b[1m1/1\u001b[0m \u001b[32m━━━━━━━━━━━━━━━━━━━━\u001b[0m\u001b[37m\u001b[0m \u001b[1m0s\u001b[0m 52ms/step\n",
      "\u001b[1m1/1\u001b[0m \u001b[32m━━━━━━━━━━━━━━━━━━━━\u001b[0m\u001b[37m\u001b[0m \u001b[1m0s\u001b[0m 54ms/step\n",
      "\u001b[1m1/1\u001b[0m \u001b[32m━━━━━━━━━━━━━━━━━━━━\u001b[0m\u001b[37m\u001b[0m \u001b[1m0s\u001b[0m 64ms/step\n",
      "\u001b[1m1/1\u001b[0m \u001b[32m━━━━━━━━━━━━━━━━━━━━\u001b[0m\u001b[37m\u001b[0m \u001b[1m0s\u001b[0m 52ms/step\n",
      "\u001b[1m1/1\u001b[0m \u001b[32m━━━━━━━━━━━━━━━━━━━━\u001b[0m\u001b[37m\u001b[0m \u001b[1m0s\u001b[0m 54ms/step\n",
      "\u001b[1m1/1\u001b[0m \u001b[32m━━━━━━━━━━━━━━━━━━━━\u001b[0m\u001b[37m\u001b[0m \u001b[1m0s\u001b[0m 53ms/step\n",
      "\u001b[1m1/1\u001b[0m \u001b[32m━━━━━━━━━━━━━━━━━━━━\u001b[0m\u001b[37m\u001b[0m \u001b[1m0s\u001b[0m 62ms/step\n",
      "\u001b[1m1/1\u001b[0m \u001b[32m━━━━━━━━━━━━━━━━━━━━\u001b[0m\u001b[37m\u001b[0m \u001b[1m0s\u001b[0m 40ms/step\n",
      "\u001b[1m1/1\u001b[0m \u001b[32m━━━━━━━━━━━━━━━━━━━━\u001b[0m\u001b[37m\u001b[0m \u001b[1m0s\u001b[0m 54ms/step\n",
      "\u001b[1m1/1\u001b[0m \u001b[32m━━━━━━━━━━━━━━━━━━━━\u001b[0m\u001b[37m\u001b[0m \u001b[1m0s\u001b[0m 67ms/step\n",
      "\u001b[1m1/1\u001b[0m \u001b[32m━━━━━━━━━━━━━━━━━━━━\u001b[0m\u001b[37m\u001b[0m \u001b[1m0s\u001b[0m 44ms/step\n",
      "\u001b[1m1/1\u001b[0m \u001b[32m━━━━━━━━━━━━━━━━━━━━\u001b[0m\u001b[37m\u001b[0m \u001b[1m0s\u001b[0m 53ms/step\n",
      "\u001b[1m1/1\u001b[0m \u001b[32m━━━━━━━━━━━━━━━━━━━━\u001b[0m\u001b[37m\u001b[0m \u001b[1m0s\u001b[0m 68ms/step\n",
      "\u001b[1m1/1\u001b[0m \u001b[32m━━━━━━━━━━━━━━━━━━━━\u001b[0m\u001b[37m\u001b[0m \u001b[1m0s\u001b[0m 54ms/step\n",
      "\u001b[1m1/1\u001b[0m \u001b[32m━━━━━━━━━━━━━━━━━━━━\u001b[0m\u001b[37m\u001b[0m \u001b[1m0s\u001b[0m 54ms/step\n",
      "\u001b[1m1/1\u001b[0m \u001b[32m━━━━━━━━━━━━━━━━━━━━\u001b[0m\u001b[37m\u001b[0m \u001b[1m0s\u001b[0m 47ms/step\n",
      "\u001b[1m1/1\u001b[0m \u001b[32m━━━━━━━━━━━━━━━━━━━━\u001b[0m\u001b[37m\u001b[0m \u001b[1m0s\u001b[0m 53ms/step\n",
      "\u001b[1m1/1\u001b[0m \u001b[32m━━━━━━━━━━━━━━━━━━━━\u001b[0m\u001b[37m\u001b[0m \u001b[1m0s\u001b[0m 67ms/step\n",
      "\u001b[1m1/1\u001b[0m \u001b[32m━━━━━━━━━━━━━━━━━━━━\u001b[0m\u001b[37m\u001b[0m \u001b[1m0s\u001b[0m 68ms/step\n",
      "\u001b[1m1/1\u001b[0m \u001b[32m━━━━━━━━━━━━━━━━━━━━\u001b[0m\u001b[37m\u001b[0m \u001b[1m0s\u001b[0m 54ms/step\n",
      "\u001b[1m1/1\u001b[0m \u001b[32m━━━━━━━━━━━━━━━━━━━━\u001b[0m\u001b[37m\u001b[0m \u001b[1m0s\u001b[0m 53ms/step\n",
      "\u001b[1m1/1\u001b[0m \u001b[32m━━━━━━━━━━━━━━━━━━━━\u001b[0m\u001b[37m\u001b[0m \u001b[1m0s\u001b[0m 54ms/step\n",
      "\u001b[1m1/1\u001b[0m \u001b[32m━━━━━━━━━━━━━━━━━━━━\u001b[0m\u001b[37m\u001b[0m \u001b[1m0s\u001b[0m 53ms/step\n",
      "\u001b[1m1/1\u001b[0m \u001b[32m━━━━━━━━━━━━━━━━━━━━\u001b[0m\u001b[37m\u001b[0m \u001b[1m0s\u001b[0m 53ms/step\n",
      "\u001b[1m1/1\u001b[0m \u001b[32m━━━━━━━━━━━━━━━━━━━━\u001b[0m\u001b[37m\u001b[0m \u001b[1m0s\u001b[0m 53ms/step\n",
      "\u001b[1m1/1\u001b[0m \u001b[32m━━━━━━━━━━━━━━━━━━━━\u001b[0m\u001b[37m\u001b[0m \u001b[1m0s\u001b[0m 53ms/step\n",
      "\u001b[1m1/1\u001b[0m \u001b[32m━━━━━━━━━━━━━━━━━━━━\u001b[0m\u001b[37m\u001b[0m \u001b[1m0s\u001b[0m 64ms/step\n",
      "\u001b[1m1/1\u001b[0m \u001b[32m━━━━━━━━━━━━━━━━━━━━\u001b[0m\u001b[37m\u001b[0m \u001b[1m0s\u001b[0m 51ms/step\n",
      "\u001b[1m1/1\u001b[0m \u001b[32m━━━━━━━━━━━━━━━━━━━━\u001b[0m\u001b[37m\u001b[0m \u001b[1m0s\u001b[0m 53ms/step\n",
      "\u001b[1m1/1\u001b[0m \u001b[32m━━━━━━━━━━━━━━━━━━━━\u001b[0m\u001b[37m\u001b[0m \u001b[1m0s\u001b[0m 43ms/step\n",
      "\u001b[1m1/1\u001b[0m \u001b[32m━━━━━━━━━━━━━━━━━━━━\u001b[0m\u001b[37m\u001b[0m \u001b[1m0s\u001b[0m 54ms/step\n",
      "\u001b[1m1/1\u001b[0m \u001b[32m━━━━━━━━━━━━━━━━━━━━\u001b[0m\u001b[37m\u001b[0m \u001b[1m0s\u001b[0m 48ms/step\n",
      "\u001b[1m1/1\u001b[0m \u001b[32m━━━━━━━━━━━━━━━━━━━━\u001b[0m\u001b[37m\u001b[0m \u001b[1m0s\u001b[0m 54ms/step\n",
      "\u001b[1m1/1\u001b[0m \u001b[32m━━━━━━━━━━━━━━━━━━━━\u001b[0m\u001b[37m\u001b[0m \u001b[1m0s\u001b[0m 62ms/step\n",
      "\u001b[1m1/1\u001b[0m \u001b[32m━━━━━━━━━━━━━━━━━━━━\u001b[0m\u001b[37m\u001b[0m \u001b[1m0s\u001b[0m 50ms/step\n",
      "\u001b[1m1/1\u001b[0m \u001b[32m━━━━━━━━━━━━━━━━━━━━\u001b[0m\u001b[37m\u001b[0m \u001b[1m0s\u001b[0m 54ms/step\n",
      "\u001b[1m1/1\u001b[0m \u001b[32m━━━━━━━━━━━━━━━━━━━━\u001b[0m\u001b[37m\u001b[0m \u001b[1m0s\u001b[0m 54ms/step\n",
      "\u001b[1m1/1\u001b[0m \u001b[32m━━━━━━━━━━━━━━━━━━━━\u001b[0m\u001b[37m\u001b[0m \u001b[1m0s\u001b[0m 46ms/step\n",
      "\u001b[1m1/1\u001b[0m \u001b[32m━━━━━━━━━━━━━━━━━━━━\u001b[0m\u001b[37m\u001b[0m \u001b[1m0s\u001b[0m 54ms/step\n",
      "\u001b[1m1/1\u001b[0m \u001b[32m━━━━━━━━━━━━━━━━━━━━\u001b[0m\u001b[37m\u001b[0m \u001b[1m0s\u001b[0m 54ms/step\n",
      "\u001b[1m1/1\u001b[0m \u001b[32m━━━━━━━━━━━━━━━━━━━━\u001b[0m\u001b[37m\u001b[0m \u001b[1m0s\u001b[0m 65ms/step\n",
      "\u001b[1m1/1\u001b[0m \u001b[32m━━━━━━━━━━━━━━━━━━━━\u001b[0m\u001b[37m\u001b[0m \u001b[1m0s\u001b[0m 50ms/step\n",
      "\u001b[1m1/1\u001b[0m \u001b[32m━━━━━━━━━━━━━━━━━━━━\u001b[0m\u001b[37m\u001b[0m \u001b[1m0s\u001b[0m 54ms/step\n",
      "\u001b[1m1/1\u001b[0m \u001b[32m━━━━━━━━━━━━━━━━━━━━\u001b[0m\u001b[37m\u001b[0m \u001b[1m0s\u001b[0m 48ms/step\n",
      "\u001b[1m1/1\u001b[0m \u001b[32m━━━━━━━━━━━━━━━━━━━━\u001b[0m\u001b[37m\u001b[0m \u001b[1m0s\u001b[0m 64ms/step\n",
      "\u001b[1m1/1\u001b[0m \u001b[32m━━━━━━━━━━━━━━━━━━━━\u001b[0m\u001b[37m\u001b[0m \u001b[1m0s\u001b[0m 50ms/step\n",
      "\u001b[1m1/1\u001b[0m \u001b[32m━━━━━━━━━━━━━━━━━━━━\u001b[0m\u001b[37m\u001b[0m \u001b[1m0s\u001b[0m 42ms/step\n",
      "\u001b[1m1/1\u001b[0m \u001b[32m━━━━━━━━━━━━━━━━━━━━\u001b[0m\u001b[37m\u001b[0m \u001b[1m0s\u001b[0m 53ms/step\n",
      "\u001b[1m1/1\u001b[0m \u001b[32m━━━━━━━━━━━━━━━━━━━━\u001b[0m\u001b[37m\u001b[0m \u001b[1m0s\u001b[0m 67ms/step\n",
      "\u001b[1m1/1\u001b[0m \u001b[32m━━━━━━━━━━━━━━━━━━━━\u001b[0m\u001b[37m\u001b[0m \u001b[1m0s\u001b[0m 54ms/step\n",
      "\u001b[1m1/1\u001b[0m \u001b[32m━━━━━━━━━━━━━━━━━━━━\u001b[0m\u001b[37m\u001b[0m \u001b[1m0s\u001b[0m 64ms/step\n",
      "\u001b[1m1/1\u001b[0m \u001b[32m━━━━━━━━━━━━━━━━━━━━\u001b[0m\u001b[37m\u001b[0m \u001b[1m0s\u001b[0m 54ms/step\n",
      "\u001b[1m1/1\u001b[0m \u001b[32m━━━━━━━━━━━━━━━━━━━━\u001b[0m\u001b[37m\u001b[0m \u001b[1m0s\u001b[0m 44ms/step\n",
      "\u001b[1m1/1\u001b[0m \u001b[32m━━━━━━━━━━━━━━━━━━━━\u001b[0m\u001b[37m\u001b[0m \u001b[1m0s\u001b[0m 54ms/step\n",
      "\u001b[1m1/1\u001b[0m \u001b[32m━━━━━━━━━━━━━━━━━━━━\u001b[0m\u001b[37m\u001b[0m \u001b[1m0s\u001b[0m 53ms/step\n",
      "\u001b[1m1/1\u001b[0m \u001b[32m━━━━━━━━━━━━━━━━━━━━\u001b[0m\u001b[37m\u001b[0m \u001b[1m0s\u001b[0m 66ms/step\n",
      "\u001b[1m1/1\u001b[0m \u001b[32m━━━━━━━━━━━━━━━━━━━━\u001b[0m\u001b[37m\u001b[0m \u001b[1m0s\u001b[0m 57ms/step\n",
      "\u001b[1m1/1\u001b[0m \u001b[32m━━━━━━━━━━━━━━━━━━━━\u001b[0m\u001b[37m\u001b[0m \u001b[1m0s\u001b[0m 61ms/step\n",
      "\u001b[1m1/1\u001b[0m \u001b[32m━━━━━━━━━━━━━━━━━━━━\u001b[0m\u001b[37m\u001b[0m \u001b[1m0s\u001b[0m 54ms/step\n",
      "\u001b[1m1/1\u001b[0m \u001b[32m━━━━━━━━━━━━━━━━━━━━\u001b[0m\u001b[37m\u001b[0m \u001b[1m0s\u001b[0m 53ms/step\n",
      "\u001b[1m1/1\u001b[0m \u001b[32m━━━━━━━━━━━━━━━━━━━━\u001b[0m\u001b[37m\u001b[0m \u001b[1m0s\u001b[0m 58ms/step\n",
      "\u001b[1m1/1\u001b[0m \u001b[32m━━━━━━━━━━━━━━━━━━━━\u001b[0m\u001b[37m\u001b[0m \u001b[1m0s\u001b[0m 63ms/step\n",
      "\u001b[1m1/1\u001b[0m \u001b[32m━━━━━━━━━━━━━━━━━━━━\u001b[0m\u001b[37m\u001b[0m \u001b[1m0s\u001b[0m 52ms/step\n",
      "\u001b[1m1/1\u001b[0m \u001b[32m━━━━━━━━━━━━━━━━━━━━\u001b[0m\u001b[37m\u001b[0m \u001b[1m0s\u001b[0m 46ms/step\n",
      "\u001b[1m1/1\u001b[0m \u001b[32m━━━━━━━━━━━━━━━━━━━━\u001b[0m\u001b[37m\u001b[0m \u001b[1m0s\u001b[0m 53ms/step\n",
      "\u001b[1m1/1\u001b[0m \u001b[32m━━━━━━━━━━━━━━━━━━━━\u001b[0m\u001b[37m\u001b[0m \u001b[1m0s\u001b[0m 53ms/step\n",
      "\u001b[1m1/1\u001b[0m \u001b[32m━━━━━━━━━━━━━━━━━━━━\u001b[0m\u001b[37m\u001b[0m \u001b[1m0s\u001b[0m 54ms/step\n",
      "\u001b[1m1/1\u001b[0m \u001b[32m━━━━━━━━━━━━━━━━━━━━\u001b[0m\u001b[37m\u001b[0m \u001b[1m0s\u001b[0m 57ms/step\n",
      "\u001b[1m1/1\u001b[0m \u001b[32m━━━━━━━━━━━━━━━━━━━━\u001b[0m\u001b[37m\u001b[0m \u001b[1m0s\u001b[0m 67ms/step\n",
      "\u001b[1m1/1\u001b[0m \u001b[32m━━━━━━━━━━━━━━━━━━━━\u001b[0m\u001b[37m\u001b[0m \u001b[1m0s\u001b[0m 56ms/step\n",
      "\u001b[1m1/1\u001b[0m \u001b[32m━━━━━━━━━━━━━━━━━━━━\u001b[0m\u001b[37m\u001b[0m \u001b[1m0s\u001b[0m 54ms/step\n",
      "\u001b[1m1/1\u001b[0m \u001b[32m━━━━━━━━━━━━━━━━━━━━\u001b[0m\u001b[37m\u001b[0m \u001b[1m0s\u001b[0m 54ms/step\n",
      "\u001b[1m1/1\u001b[0m \u001b[32m━━━━━━━━━━━━━━━━━━━━\u001b[0m\u001b[37m\u001b[0m \u001b[1m0s\u001b[0m 51ms/step\n",
      "\u001b[1m1/1\u001b[0m \u001b[32m━━━━━━━━━━━━━━━━━━━━\u001b[0m\u001b[37m\u001b[0m \u001b[1m0s\u001b[0m 50ms/step\n",
      "\u001b[1m1/1\u001b[0m \u001b[32m━━━━━━━━━━━━━━━━━━━━\u001b[0m\u001b[37m\u001b[0m \u001b[1m0s\u001b[0m 54ms/step\n",
      "\u001b[1m1/1\u001b[0m \u001b[32m━━━━━━━━━━━━━━━━━━━━\u001b[0m\u001b[37m\u001b[0m \u001b[1m0s\u001b[0m 54ms/step\n",
      "\u001b[1m1/1\u001b[0m \u001b[32m━━━━━━━━━━━━━━━━━━━━\u001b[0m\u001b[37m\u001b[0m \u001b[1m0s\u001b[0m 54ms/step\n",
      "\u001b[1m1/1\u001b[0m \u001b[32m━━━━━━━━━━━━━━━━━━━━\u001b[0m\u001b[37m\u001b[0m \u001b[1m0s\u001b[0m 54ms/step\n",
      "\u001b[1m1/1\u001b[0m \u001b[32m━━━━━━━━━━━━━━━━━━━━\u001b[0m\u001b[37m\u001b[0m \u001b[1m0s\u001b[0m 54ms/step\n",
      "\u001b[1m1/1\u001b[0m \u001b[32m━━━━━━━━━━━━━━━━━━━━\u001b[0m\u001b[37m\u001b[0m \u001b[1m0s\u001b[0m 65ms/step\n",
      "\u001b[1m1/1\u001b[0m \u001b[32m━━━━━━━━━━━━━━━━━━━━\u001b[0m\u001b[37m\u001b[0m \u001b[1m0s\u001b[0m 49ms/step\n",
      "\u001b[1m1/1\u001b[0m \u001b[32m━━━━━━━━━━━━━━━━━━━━\u001b[0m\u001b[37m\u001b[0m \u001b[1m0s\u001b[0m 54ms/step\n",
      "\u001b[1m1/1\u001b[0m \u001b[32m━━━━━━━━━━━━━━━━━━━━\u001b[0m\u001b[37m\u001b[0m \u001b[1m0s\u001b[0m 41ms/step\n",
      "\u001b[1m1/1\u001b[0m \u001b[32m━━━━━━━━━━━━━━━━━━━━\u001b[0m\u001b[37m\u001b[0m \u001b[1m0s\u001b[0m 53ms/step\n",
      "\u001b[1m1/1\u001b[0m \u001b[32m━━━━━━━━━━━━━━━━━━━━\u001b[0m\u001b[37m\u001b[0m \u001b[1m0s\u001b[0m 56ms/step\n",
      "\u001b[1m1/1\u001b[0m \u001b[32m━━━━━━━━━━━━━━━━━━━━\u001b[0m\u001b[37m\u001b[0m \u001b[1m0s\u001b[0m 60ms/step\n",
      "\u001b[1m1/1\u001b[0m \u001b[32m━━━━━━━━━━━━━━━━━━━━\u001b[0m\u001b[37m\u001b[0m \u001b[1m0s\u001b[0m 66ms/step\n",
      "\u001b[1m1/1\u001b[0m \u001b[32m━━━━━━━━━━━━━━━━━━━━\u001b[0m\u001b[37m\u001b[0m \u001b[1m0s\u001b[0m 54ms/step\n",
      "\u001b[1m1/1\u001b[0m \u001b[32m━━━━━━━━━━━━━━━━━━━━\u001b[0m\u001b[37m\u001b[0m \u001b[1m0s\u001b[0m 57ms/step\n",
      "\u001b[1m1/1\u001b[0m \u001b[32m━━━━━━━━━━━━━━━━━━━━\u001b[0m\u001b[37m\u001b[0m \u001b[1m0s\u001b[0m 62ms/step\n",
      "\u001b[1m1/1\u001b[0m \u001b[32m━━━━━━━━━━━━━━━━━━━━\u001b[0m\u001b[37m\u001b[0m \u001b[1m0s\u001b[0m 54ms/step\n",
      "\u001b[1m1/1\u001b[0m \u001b[32m━━━━━━━━━━━━━━━━━━━━\u001b[0m\u001b[37m\u001b[0m \u001b[1m0s\u001b[0m 55ms/step\n",
      "\u001b[1m1/1\u001b[0m \u001b[32m━━━━━━━━━━━━━━━━━━━━\u001b[0m\u001b[37m\u001b[0m \u001b[1m0s\u001b[0m 42ms/step\n",
      "\u001b[1m1/1\u001b[0m \u001b[32m━━━━━━━━━━━━━━━━━━━━\u001b[0m\u001b[37m\u001b[0m \u001b[1m0s\u001b[0m 53ms/step\n",
      "\u001b[1m1/1\u001b[0m \u001b[32m━━━━━━━━━━━━━━━━━━━━\u001b[0m\u001b[37m\u001b[0m \u001b[1m0s\u001b[0m 67ms/step\n",
      "\u001b[1m1/1\u001b[0m \u001b[32m━━━━━━━━━━━━━━━━━━━━\u001b[0m\u001b[37m\u001b[0m \u001b[1m0s\u001b[0m 46ms/step\n",
      "\u001b[1m1/1\u001b[0m \u001b[32m━━━━━━━━━━━━━━━━━━━━\u001b[0m\u001b[37m\u001b[0m \u001b[1m0s\u001b[0m 54ms/step\n",
      "\u001b[1m1/1\u001b[0m \u001b[32m━━━━━━━━━━━━━━━━━━━━\u001b[0m\u001b[37m\u001b[0m \u001b[1m0s\u001b[0m 57ms/step\n",
      "\u001b[1m1/1\u001b[0m \u001b[32m━━━━━━━━━━━━━━━━━━━━\u001b[0m\u001b[37m\u001b[0m \u001b[1m0s\u001b[0m 53ms/step\n",
      "\u001b[1m1/1\u001b[0m \u001b[32m━━━━━━━━━━━━━━━━━━━━\u001b[0m\u001b[37m\u001b[0m \u001b[1m0s\u001b[0m 57ms/step\n",
      "\u001b[1m1/1\u001b[0m \u001b[32m━━━━━━━━━━━━━━━━━━━━\u001b[0m\u001b[37m\u001b[0m \u001b[1m0s\u001b[0m 63ms/step\n",
      "\u001b[1m1/1\u001b[0m \u001b[32m━━━━━━━━━━━━━━━━━━━━\u001b[0m\u001b[37m\u001b[0m \u001b[1m0s\u001b[0m 53ms/step\n",
      "\u001b[1m1/1\u001b[0m \u001b[32m━━━━━━━━━━━━━━━━━━━━\u001b[0m\u001b[37m\u001b[0m \u001b[1m0s\u001b[0m 47ms/step\n",
      "\u001b[1m1/1\u001b[0m \u001b[32m━━━━━━━━━━━━━━━━━━━━\u001b[0m\u001b[37m\u001b[0m \u001b[1m0s\u001b[0m 42ms/step\n",
      "\u001b[1m1/1\u001b[0m \u001b[32m━━━━━━━━━━━━━━━━━━━━\u001b[0m\u001b[37m\u001b[0m \u001b[1m0s\u001b[0m 50ms/step\n",
      "\u001b[1m1/1\u001b[0m \u001b[32m━━━━━━━━━━━━━━━━━━━━\u001b[0m\u001b[37m\u001b[0m \u001b[1m0s\u001b[0m 58ms/step\n",
      "\u001b[1m1/1\u001b[0m \u001b[32m━━━━━━━━━━━━━━━━━━━━\u001b[0m\u001b[37m\u001b[0m \u001b[1m0s\u001b[0m 65ms/step\n",
      "\u001b[1m1/1\u001b[0m \u001b[32m━━━━━━━━━━━━━━━━━━━━\u001b[0m\u001b[37m\u001b[0m \u001b[1m0s\u001b[0m 51ms/step\n",
      "\u001b[1m1/1\u001b[0m \u001b[32m━━━━━━━━━━━━━━━━━━━━\u001b[0m\u001b[37m\u001b[0m \u001b[1m0s\u001b[0m 46ms/step\n",
      "\u001b[1m1/1\u001b[0m \u001b[32m━━━━━━━━━━━━━━━━━━━━\u001b[0m\u001b[37m\u001b[0m \u001b[1m0s\u001b[0m 54ms/step\n",
      "\u001b[1m1/1\u001b[0m \u001b[32m━━━━━━━━━━━━━━━━━━━━\u001b[0m\u001b[37m\u001b[0m \u001b[1m0s\u001b[0m 46ms/step\n",
      "\u001b[1m1/1\u001b[0m \u001b[32m━━━━━━━━━━━━━━━━━━━━\u001b[0m\u001b[37m\u001b[0m \u001b[1m0s\u001b[0m 41ms/step\n",
      "\u001b[1m1/1\u001b[0m \u001b[32m━━━━━━━━━━━━━━━━━━━━\u001b[0m\u001b[37m\u001b[0m \u001b[1m0s\u001b[0m 61ms/step\n",
      "\u001b[1m1/1\u001b[0m \u001b[32m━━━━━━━━━━━━━━━━━━━━\u001b[0m\u001b[37m\u001b[0m \u001b[1m0s\u001b[0m 66ms/step\n",
      "\u001b[1m1/1\u001b[0m \u001b[32m━━━━━━━━━━━━━━━━━━━━\u001b[0m\u001b[37m\u001b[0m \u001b[1m0s\u001b[0m 50ms/step\n",
      "\u001b[1m1/1\u001b[0m \u001b[32m━━━━━━━━━━━━━━━━━━━━\u001b[0m\u001b[37m\u001b[0m \u001b[1m0s\u001b[0m 45ms/step\n",
      "\u001b[1m1/1\u001b[0m \u001b[32m━━━━━━━━━━━━━━━━━━━━\u001b[0m\u001b[37m\u001b[0m \u001b[1m0s\u001b[0m 46ms/step\n",
      "\u001b[1m1/1\u001b[0m \u001b[32m━━━━━━━━━━━━━━━━━━━━\u001b[0m\u001b[37m\u001b[0m \u001b[1m0s\u001b[0m 40ms/step\n",
      "\u001b[1m1/1\u001b[0m \u001b[32m━━━━━━━━━━━━━━━━━━━━\u001b[0m\u001b[37m\u001b[0m \u001b[1m0s\u001b[0m 65ms/step\n",
      "\u001b[1m1/1\u001b[0m \u001b[32m━━━━━━━━━━━━━━━━━━━━\u001b[0m\u001b[37m\u001b[0m \u001b[1m0s\u001b[0m 63ms/step\n",
      "\u001b[1m1/1\u001b[0m \u001b[32m━━━━━━━━━━━━━━━━━━━━\u001b[0m\u001b[37m\u001b[0m \u001b[1m0s\u001b[0m 54ms/step\n",
      "\u001b[1m1/1\u001b[0m \u001b[32m━━━━━━━━━━━━━━━━━━━━\u001b[0m\u001b[37m\u001b[0m \u001b[1m0s\u001b[0m 54ms/step\n",
      "\u001b[1m1/1\u001b[0m \u001b[32m━━━━━━━━━━━━━━━━━━━━\u001b[0m\u001b[37m\u001b[0m \u001b[1m0s\u001b[0m 49ms/step\n",
      "\u001b[1m1/1\u001b[0m \u001b[32m━━━━━━━━━━━━━━━━━━━━\u001b[0m\u001b[37m\u001b[0m \u001b[1m0s\u001b[0m 42ms/step\n",
      "\u001b[1m1/1\u001b[0m \u001b[32m━━━━━━━━━━━━━━━━━━━━\u001b[0m\u001b[37m\u001b[0m \u001b[1m0s\u001b[0m 53ms/step\n",
      "\u001b[1m1/1\u001b[0m \u001b[32m━━━━━━━━━━━━━━━━━━━━\u001b[0m\u001b[37m\u001b[0m \u001b[1m0s\u001b[0m 54ms/step\n",
      "\u001b[1m1/1\u001b[0m \u001b[32m━━━━━━━━━━━━━━━━━━━━\u001b[0m\u001b[37m\u001b[0m \u001b[1m0s\u001b[0m 54ms/step\n",
      "\u001b[1m1/1\u001b[0m \u001b[32m━━━━━━━━━━━━━━━━━━━━\u001b[0m\u001b[37m\u001b[0m \u001b[1m0s\u001b[0m 53ms/step\n",
      "\u001b[1m1/1\u001b[0m \u001b[32m━━━━━━━━━━━━━━━━━━━━\u001b[0m\u001b[37m\u001b[0m \u001b[1m0s\u001b[0m 52ms/step\n",
      "\u001b[1m1/1\u001b[0m \u001b[32m━━━━━━━━━━━━━━━━━━━━\u001b[0m\u001b[37m\u001b[0m \u001b[1m0s\u001b[0m 54ms/step\n",
      "\u001b[1m1/1\u001b[0m \u001b[32m━━━━━━━━━━━━━━━━━━━━\u001b[0m\u001b[37m\u001b[0m \u001b[1m0s\u001b[0m 53ms/step\n",
      "\u001b[1m1/1\u001b[0m \u001b[32m━━━━━━━━━━━━━━━━━━━━\u001b[0m\u001b[37m\u001b[0m \u001b[1m0s\u001b[0m 53ms/step\n",
      "\u001b[1m1/1\u001b[0m \u001b[32m━━━━━━━━━━━━━━━━━━━━\u001b[0m\u001b[37m\u001b[0m \u001b[1m0s\u001b[0m 63ms/step\n",
      "\u001b[1m1/1\u001b[0m \u001b[32m━━━━━━━━━━━━━━━━━━━━\u001b[0m\u001b[37m\u001b[0m \u001b[1m0s\u001b[0m 53ms/step\n",
      "\u001b[1m1/1\u001b[0m \u001b[32m━━━━━━━━━━━━━━━━━━━━\u001b[0m\u001b[37m\u001b[0m \u001b[1m0s\u001b[0m 45ms/step\n",
      "\u001b[1m1/1\u001b[0m \u001b[32m━━━━━━━━━━━━━━━━━━━━\u001b[0m\u001b[37m\u001b[0m \u001b[1m0s\u001b[0m 54ms/step\n",
      "\u001b[1m1/1\u001b[0m \u001b[32m━━━━━━━━━━━━━━━━━━━━\u001b[0m\u001b[37m\u001b[0m \u001b[1m0s\u001b[0m 54ms/step\n",
      "\u001b[1m1/1\u001b[0m \u001b[32m━━━━━━━━━━━━━━━━━━━━\u001b[0m\u001b[37m\u001b[0m \u001b[1m0s\u001b[0m 53ms/step\n",
      "\u001b[1m1/1\u001b[0m \u001b[32m━━━━━━━━━━━━━━━━━━━━\u001b[0m\u001b[37m\u001b[0m \u001b[1m0s\u001b[0m 53ms/step\n",
      "\u001b[1m1/1\u001b[0m \u001b[32m━━━━━━━━━━━━━━━━━━━━\u001b[0m\u001b[37m\u001b[0m \u001b[1m0s\u001b[0m 54ms/step\n",
      "\u001b[1m1/1\u001b[0m \u001b[32m━━━━━━━━━━━━━━━━━━━━\u001b[0m\u001b[37m\u001b[0m \u001b[1m0s\u001b[0m 62ms/step\n",
      "\u001b[1m1/1\u001b[0m \u001b[32m━━━━━━━━━━━━━━━━━━━━\u001b[0m\u001b[37m\u001b[0m \u001b[1m0s\u001b[0m 52ms/step\n",
      "\u001b[1m1/1\u001b[0m \u001b[32m━━━━━━━━━━━━━━━━━━━━\u001b[0m\u001b[37m\u001b[0m \u001b[1m0s\u001b[0m 54ms/step\n",
      "\u001b[1m1/1\u001b[0m \u001b[32m━━━━━━━━━━━━━━━━━━━━\u001b[0m\u001b[37m\u001b[0m \u001b[1m0s\u001b[0m 67ms/step\n",
      "\u001b[1m1/1\u001b[0m \u001b[32m━━━━━━━━━━━━━━━━━━━━\u001b[0m\u001b[37m\u001b[0m \u001b[1m0s\u001b[0m 58ms/step\n",
      "\u001b[1m1/1\u001b[0m \u001b[32m━━━━━━━━━━━━━━━━━━━━\u001b[0m\u001b[37m\u001b[0m \u001b[1m0s\u001b[0m 53ms/step\n",
      "\u001b[1m1/1\u001b[0m \u001b[32m━━━━━━━━━━━━━━━━━━━━\u001b[0m\u001b[37m\u001b[0m \u001b[1m0s\u001b[0m 53ms/step\n",
      "\u001b[1m1/1\u001b[0m \u001b[32m━━━━━━━━━━━━━━━━━━━━\u001b[0m\u001b[37m\u001b[0m \u001b[1m0s\u001b[0m 49ms/step\n",
      "\u001b[1m1/1\u001b[0m \u001b[32m━━━━━━━━━━━━━━━━━━━━\u001b[0m\u001b[37m\u001b[0m \u001b[1m0s\u001b[0m 45ms/step\n",
      "\u001b[1m1/1\u001b[0m \u001b[32m━━━━━━━━━━━━━━━━━━━━\u001b[0m\u001b[37m\u001b[0m \u001b[1m0s\u001b[0m 54ms/step\n",
      "\u001b[1m1/1\u001b[0m \u001b[32m━━━━━━━━━━━━━━━━━━━━\u001b[0m\u001b[37m\u001b[0m \u001b[1m0s\u001b[0m 53ms/step\n",
      "\u001b[1m1/1\u001b[0m \u001b[32m━━━━━━━━━━━━━━━━━━━━\u001b[0m\u001b[37m\u001b[0m \u001b[1m0s\u001b[0m 54ms/step\n",
      "\u001b[1m1/1\u001b[0m \u001b[32m━━━━━━━━━━━━━━━━━━━━\u001b[0m\u001b[37m\u001b[0m \u001b[1m0s\u001b[0m 61ms/step\n",
      "\u001b[1m1/1\u001b[0m \u001b[32m━━━━━━━━━━━━━━━━━━━━\u001b[0m\u001b[37m\u001b[0m \u001b[1m0s\u001b[0m 53ms/step\n",
      "\u001b[1m1/1\u001b[0m \u001b[32m━━━━━━━━━━━━━━━━━━━━\u001b[0m\u001b[37m\u001b[0m \u001b[1m0s\u001b[0m 49ms/step\n",
      "\u001b[1m1/1\u001b[0m \u001b[32m━━━━━━━━━━━━━━━━━━━━\u001b[0m\u001b[37m\u001b[0m \u001b[1m0s\u001b[0m 47ms/step\n",
      "\u001b[1m1/1\u001b[0m \u001b[32m━━━━━━━━━━━━━━━━━━━━\u001b[0m\u001b[37m\u001b[0m \u001b[1m0s\u001b[0m 54ms/step\n",
      "\u001b[1m1/1\u001b[0m \u001b[32m━━━━━━━━━━━━━━━━━━━━\u001b[0m\u001b[37m\u001b[0m \u001b[1m0s\u001b[0m 54ms/step\n",
      "\u001b[1m1/1\u001b[0m \u001b[32m━━━━━━━━━━━━━━━━━━━━\u001b[0m\u001b[37m\u001b[0m \u001b[1m0s\u001b[0m 54ms/step\n",
      "\u001b[1m1/1\u001b[0m \u001b[32m━━━━━━━━━━━━━━━━━━━━\u001b[0m\u001b[37m\u001b[0m \u001b[1m0s\u001b[0m 53ms/step\n",
      "\u001b[1m1/1\u001b[0m \u001b[32m━━━━━━━━━━━━━━━━━━━━\u001b[0m\u001b[37m\u001b[0m \u001b[1m0s\u001b[0m 66ms/step\n",
      "\u001b[1m1/1\u001b[0m \u001b[32m━━━━━━━━━━━━━━━━━━━━\u001b[0m\u001b[37m\u001b[0m \u001b[1m0s\u001b[0m 53ms/step\n",
      "\u001b[1m1/1\u001b[0m \u001b[32m━━━━━━━━━━━━━━━━━━━━\u001b[0m\u001b[37m\u001b[0m \u001b[1m0s\u001b[0m 69ms/step\n",
      "\u001b[1m1/1\u001b[0m \u001b[32m━━━━━━━━━━━━━━━━━━━━\u001b[0m\u001b[37m\u001b[0m \u001b[1m0s\u001b[0m 56ms/step\n",
      "\u001b[1m1/1\u001b[0m \u001b[32m━━━━━━━━━━━━━━━━━━━━\u001b[0m\u001b[37m\u001b[0m \u001b[1m0s\u001b[0m 46ms/step\n",
      "\u001b[1m1/1\u001b[0m \u001b[32m━━━━━━━━━━━━━━━━━━━━\u001b[0m\u001b[37m\u001b[0m \u001b[1m0s\u001b[0m 54ms/step\n",
      "\u001b[1m1/1\u001b[0m \u001b[32m━━━━━━━━━━━━━━━━━━━━\u001b[0m\u001b[37m\u001b[0m \u001b[1m0s\u001b[0m 66ms/step\n",
      "\u001b[1m1/1\u001b[0m \u001b[32m━━━━━━━━━━━━━━━━━━━━\u001b[0m\u001b[37m\u001b[0m \u001b[1m0s\u001b[0m 53ms/step\n",
      "\u001b[1m1/1\u001b[0m \u001b[32m━━━━━━━━━━━━━━━━━━━━\u001b[0m\u001b[37m\u001b[0m \u001b[1m0s\u001b[0m 54ms/step\n",
      "\u001b[1m1/1\u001b[0m \u001b[32m━━━━━━━━━━━━━━━━━━━━\u001b[0m\u001b[37m\u001b[0m \u001b[1m0s\u001b[0m 66ms/step\n",
      "\u001b[1m1/1\u001b[0m \u001b[32m━━━━━━━━━━━━━━━━━━━━\u001b[0m\u001b[37m\u001b[0m \u001b[1m0s\u001b[0m 53ms/step\n",
      "\u001b[1m1/1\u001b[0m \u001b[32m━━━━━━━━━━━━━━━━━━━━\u001b[0m\u001b[37m\u001b[0m \u001b[1m0s\u001b[0m 55ms/step\n",
      "\u001b[1m1/1\u001b[0m \u001b[32m━━━━━━━━━━━━━━━━━━━━\u001b[0m\u001b[37m\u001b[0m \u001b[1m0s\u001b[0m 56ms/step\n",
      "\u001b[1m1/1\u001b[0m \u001b[32m━━━━━━━━━━━━━━━━━━━━\u001b[0m\u001b[37m\u001b[0m \u001b[1m0s\u001b[0m 53ms/step\n",
      "\u001b[1m1/1\u001b[0m \u001b[32m━━━━━━━━━━━━━━━━━━━━\u001b[0m\u001b[37m\u001b[0m \u001b[1m0s\u001b[0m 53ms/step\n",
      "\u001b[1m1/1\u001b[0m \u001b[32m━━━━━━━━━━━━━━━━━━━━\u001b[0m\u001b[37m\u001b[0m \u001b[1m0s\u001b[0m 62ms/step\n",
      "\u001b[1m1/1\u001b[0m \u001b[32m━━━━━━━━━━━━━━━━━━━━\u001b[0m\u001b[37m\u001b[0m \u001b[1m0s\u001b[0m 67ms/step\n",
      "\u001b[1m1/1\u001b[0m \u001b[32m━━━━━━━━━━━━━━━━━━━━\u001b[0m\u001b[37m\u001b[0m \u001b[1m0s\u001b[0m 57ms/step\n",
      "\u001b[1m1/1\u001b[0m \u001b[32m━━━━━━━━━━━━━━━━━━━━\u001b[0m\u001b[37m\u001b[0m \u001b[1m0s\u001b[0m 58ms/step\n",
      "\u001b[1m1/1\u001b[0m \u001b[32m━━━━━━━━━━━━━━━━━━━━\u001b[0m\u001b[37m\u001b[0m \u001b[1m0s\u001b[0m 61ms/step\n",
      "\u001b[1m1/1\u001b[0m \u001b[32m━━━━━━━━━━━━━━━━━━━━\u001b[0m\u001b[37m\u001b[0m \u001b[1m0s\u001b[0m 55ms/step\n",
      "\u001b[1m1/1\u001b[0m \u001b[32m━━━━━━━━━━━━━━━━━━━━\u001b[0m\u001b[37m\u001b[0m \u001b[1m0s\u001b[0m 60ms/step\n",
      "\u001b[1m1/1\u001b[0m \u001b[32m━━━━━━━━━━━━━━━━━━━━\u001b[0m\u001b[37m\u001b[0m \u001b[1m0s\u001b[0m 67ms/step\n",
      "\u001b[1m1/1\u001b[0m \u001b[32m━━━━━━━━━━━━━━━━━━━━\u001b[0m\u001b[37m\u001b[0m \u001b[1m0s\u001b[0m 54ms/step\n",
      "\u001b[1m1/1\u001b[0m \u001b[32m━━━━━━━━━━━━━━━━━━━━\u001b[0m\u001b[37m\u001b[0m \u001b[1m0s\u001b[0m 57ms/step\n",
      "\u001b[1m1/1\u001b[0m \u001b[32m━━━━━━━━━━━━━━━━━━━━\u001b[0m\u001b[37m\u001b[0m \u001b[1m0s\u001b[0m 53ms/step\n",
      "\u001b[1m1/1\u001b[0m \u001b[32m━━━━━━━━━━━━━━━━━━━━\u001b[0m\u001b[37m\u001b[0m \u001b[1m0s\u001b[0m 62ms/step\n",
      "\u001b[1m1/1\u001b[0m \u001b[32m━━━━━━━━━━━━━━━━━━━━\u001b[0m\u001b[37m\u001b[0m \u001b[1m0s\u001b[0m 64ms/step\n",
      "\u001b[1m1/1\u001b[0m \u001b[32m━━━━━━━━━━━━━━━━━━━━\u001b[0m\u001b[37m\u001b[0m \u001b[1m0s\u001b[0m 61ms/step\n",
      "\u001b[1m1/1\u001b[0m \u001b[32m━━━━━━━━━━━━━━━━━━━━\u001b[0m\u001b[37m\u001b[0m \u001b[1m0s\u001b[0m 51ms/step\n",
      "\u001b[1m1/1\u001b[0m \u001b[32m━━━━━━━━━━━━━━━━━━━━\u001b[0m\u001b[37m\u001b[0m \u001b[1m0s\u001b[0m 60ms/step\n",
      "\u001b[1m1/1\u001b[0m \u001b[32m━━━━━━━━━━━━━━━━━━━━\u001b[0m\u001b[37m\u001b[0m \u001b[1m0s\u001b[0m 60ms/step\n",
      "\u001b[1m1/1\u001b[0m \u001b[32m━━━━━━━━━━━━━━━━━━━━\u001b[0m\u001b[37m\u001b[0m \u001b[1m0s\u001b[0m 64ms/step\n",
      "\u001b[1m1/1\u001b[0m \u001b[32m━━━━━━━━━━━━━━━━━━━━\u001b[0m\u001b[37m\u001b[0m \u001b[1m0s\u001b[0m 47ms/step\n",
      "\u001b[1m1/1\u001b[0m \u001b[32m━━━━━━━━━━━━━━━━━━━━\u001b[0m\u001b[37m\u001b[0m \u001b[1m0s\u001b[0m 65ms/step\n",
      "\u001b[1m1/1\u001b[0m \u001b[32m━━━━━━━━━━━━━━━━━━━━\u001b[0m\u001b[37m\u001b[0m \u001b[1m0s\u001b[0m 59ms/step\n",
      "\u001b[1m1/1\u001b[0m \u001b[32m━━━━━━━━━━━━━━━━━━━━\u001b[0m\u001b[37m\u001b[0m \u001b[1m0s\u001b[0m 71ms/step\n",
      "\u001b[1m1/1\u001b[0m \u001b[32m━━━━━━━━━━━━━━━━━━━━\u001b[0m\u001b[37m\u001b[0m \u001b[1m0s\u001b[0m 62ms/step\n",
      "\u001b[1m1/1\u001b[0m \u001b[32m━━━━━━━━━━━━━━━━━━━━\u001b[0m\u001b[37m\u001b[0m \u001b[1m0s\u001b[0m 64ms/step\n",
      "\u001b[1m1/1\u001b[0m \u001b[32m━━━━━━━━━━━━━━━━━━━━\u001b[0m\u001b[37m\u001b[0m \u001b[1m0s\u001b[0m 47ms/step\n",
      "\u001b[1m1/1\u001b[0m \u001b[32m━━━━━━━━━━━━━━━━━━━━\u001b[0m\u001b[37m\u001b[0m \u001b[1m0s\u001b[0m 62ms/step\n",
      "\u001b[1m1/1\u001b[0m \u001b[32m━━━━━━━━━━━━━━━━━━━━\u001b[0m\u001b[37m\u001b[0m \u001b[1m0s\u001b[0m 57ms/step\n",
      "\u001b[1m1/1\u001b[0m \u001b[32m━━━━━━━━━━━━━━━━━━━━\u001b[0m\u001b[37m\u001b[0m \u001b[1m0s\u001b[0m 64ms/step\n",
      "\u001b[1m1/1\u001b[0m \u001b[32m━━━━━━━━━━━━━━━━━━━━\u001b[0m\u001b[37m\u001b[0m \u001b[1m0s\u001b[0m 68ms/step\n",
      "\u001b[1m1/1\u001b[0m \u001b[32m━━━━━━━━━━━━━━━━━━━━\u001b[0m\u001b[37m\u001b[0m \u001b[1m0s\u001b[0m 62ms/step\n",
      "\u001b[1m1/1\u001b[0m \u001b[32m━━━━━━━━━━━━━━━━━━━━\u001b[0m\u001b[37m\u001b[0m \u001b[1m0s\u001b[0m 68ms/step\n",
      "\u001b[1m1/1\u001b[0m \u001b[32m━━━━━━━━━━━━━━━━━━━━\u001b[0m\u001b[37m\u001b[0m \u001b[1m0s\u001b[0m 62ms/step\n",
      "\u001b[1m1/1\u001b[0m \u001b[32m━━━━━━━━━━━━━━━━━━━━\u001b[0m\u001b[37m\u001b[0m \u001b[1m0s\u001b[0m 49ms/step\n",
      "\u001b[1m1/1\u001b[0m \u001b[32m━━━━━━━━━━━━━━━━━━━━\u001b[0m\u001b[37m\u001b[0m \u001b[1m0s\u001b[0m 62ms/step\n",
      "\u001b[1m1/1\u001b[0m \u001b[32m━━━━━━━━━━━━━━━━━━━━\u001b[0m\u001b[37m\u001b[0m \u001b[1m0s\u001b[0m 46ms/step\n",
      "\u001b[1m1/1\u001b[0m \u001b[32m━━━━━━━━━━━━━━━━━━━━\u001b[0m\u001b[37m\u001b[0m \u001b[1m0s\u001b[0m 47ms/step\n",
      "\u001b[1m1/1\u001b[0m \u001b[32m━━━━━━━━━━━━━━━━━━━━\u001b[0m\u001b[37m\u001b[0m \u001b[1m0s\u001b[0m 47ms/step\n",
      "\u001b[1m1/1\u001b[0m \u001b[32m━━━━━━━━━━━━━━━━━━━━\u001b[0m\u001b[37m\u001b[0m \u001b[1m0s\u001b[0m 69ms/step\n",
      "\u001b[1m1/1\u001b[0m \u001b[32m━━━━━━━━━━━━━━━━━━━━\u001b[0m\u001b[37m\u001b[0m \u001b[1m0s\u001b[0m 67ms/step\n",
      "\u001b[1m1/1\u001b[0m \u001b[32m━━━━━━━━━━━━━━━━━━━━\u001b[0m\u001b[37m\u001b[0m \u001b[1m0s\u001b[0m 52ms/step\n",
      "\u001b[1m1/1\u001b[0m \u001b[32m━━━━━━━━━━━━━━━━━━━━\u001b[0m\u001b[37m\u001b[0m \u001b[1m0s\u001b[0m 62ms/step\n",
      "\u001b[1m1/1\u001b[0m \u001b[32m━━━━━━━━━━━━━━━━━━━━\u001b[0m\u001b[37m\u001b[0m \u001b[1m0s\u001b[0m 66ms/step\n",
      "\u001b[1m1/1\u001b[0m \u001b[32m━━━━━━━━━━━━━━━━━━━━\u001b[0m\u001b[37m\u001b[0m \u001b[1m0s\u001b[0m 62ms/step\n",
      "\u001b[1m1/1\u001b[0m \u001b[32m━━━━━━━━━━━━━━━━━━━━\u001b[0m\u001b[37m\u001b[0m \u001b[1m0s\u001b[0m 81ms/step\n",
      "\u001b[1m1/1\u001b[0m \u001b[32m━━━━━━━━━━━━━━━━━━━━\u001b[0m\u001b[37m\u001b[0m \u001b[1m0s\u001b[0m 67ms/step\n",
      "\u001b[1m1/1\u001b[0m \u001b[32m━━━━━━━━━━━━━━━━━━━━\u001b[0m\u001b[37m\u001b[0m \u001b[1m0s\u001b[0m 70ms/step\n",
      "\u001b[1m1/1\u001b[0m \u001b[32m━━━━━━━━━━━━━━━━━━━━\u001b[0m\u001b[37m\u001b[0m \u001b[1m0s\u001b[0m 62ms/step\n",
      "\u001b[1m1/1\u001b[0m \u001b[32m━━━━━━━━━━━━━━━━━━━━\u001b[0m\u001b[37m\u001b[0m \u001b[1m0s\u001b[0m 65ms/step\n",
      "\u001b[1m1/1\u001b[0m \u001b[32m━━━━━━━━━━━━━━━━━━━━\u001b[0m\u001b[37m\u001b[0m \u001b[1m0s\u001b[0m 65ms/step\n",
      "\u001b[1m1/1\u001b[0m \u001b[32m━━━━━━━━━━━━━━━━━━━━\u001b[0m\u001b[37m\u001b[0m \u001b[1m0s\u001b[0m 52ms/step\n",
      "\u001b[1m1/1\u001b[0m \u001b[32m━━━━━━━━━━━━━━━━━━━━\u001b[0m\u001b[37m\u001b[0m \u001b[1m0s\u001b[0m 53ms/step\n",
      "\u001b[1m1/1\u001b[0m \u001b[32m━━━━━━━━━━━━━━━━━━━━\u001b[0m\u001b[37m\u001b[0m \u001b[1m0s\u001b[0m 54ms/step\n",
      "\u001b[1m1/1\u001b[0m \u001b[32m━━━━━━━━━━━━━━━━━━━━\u001b[0m\u001b[37m\u001b[0m \u001b[1m0s\u001b[0m 67ms/step\n",
      "\u001b[1m1/1\u001b[0m \u001b[32m━━━━━━━━━━━━━━━━━━━━\u001b[0m\u001b[37m\u001b[0m \u001b[1m0s\u001b[0m 47ms/step\n",
      "\u001b[1m1/1\u001b[0m \u001b[32m━━━━━━━━━━━━━━━━━━━━\u001b[0m\u001b[37m\u001b[0m \u001b[1m0s\u001b[0m 64ms/step\n",
      "\u001b[1m1/1\u001b[0m \u001b[32m━━━━━━━━━━━━━━━━━━━━\u001b[0m\u001b[37m\u001b[0m \u001b[1m0s\u001b[0m 69ms/step\n",
      "\u001b[1m1/1\u001b[0m \u001b[32m━━━━━━━━━━━━━━━━━━━━\u001b[0m\u001b[37m\u001b[0m \u001b[1m0s\u001b[0m 67ms/step\n",
      "\u001b[1m1/1\u001b[0m \u001b[32m━━━━━━━━━━━━━━━━━━━━\u001b[0m\u001b[37m\u001b[0m \u001b[1m0s\u001b[0m 51ms/step\n",
      "\u001b[1m1/1\u001b[0m \u001b[32m━━━━━━━━━━━━━━━━━━━━\u001b[0m\u001b[37m\u001b[0m \u001b[1m0s\u001b[0m 54ms/step\n",
      "\u001b[1m1/1\u001b[0m \u001b[32m━━━━━━━━━━━━━━━━━━━━\u001b[0m\u001b[37m\u001b[0m \u001b[1m0s\u001b[0m 55ms/step\n",
      "\u001b[1m1/1\u001b[0m \u001b[32m━━━━━━━━━━━━━━━━━━━━\u001b[0m\u001b[37m\u001b[0m \u001b[1m0s\u001b[0m 62ms/step\n",
      "\u001b[1m1/1\u001b[0m \u001b[32m━━━━━━━━━━━━━━━━━━━━\u001b[0m\u001b[37m\u001b[0m \u001b[1m0s\u001b[0m 66ms/step\n",
      "\u001b[1m1/1\u001b[0m \u001b[32m━━━━━━━━━━━━━━━━━━━━\u001b[0m\u001b[37m\u001b[0m \u001b[1m0s\u001b[0m 68ms/step\n",
      "\u001b[1m1/1\u001b[0m \u001b[32m━━━━━━━━━━━━━━━━━━━━\u001b[0m\u001b[37m\u001b[0m \u001b[1m0s\u001b[0m 48ms/step\n",
      "\u001b[1m1/1\u001b[0m \u001b[32m━━━━━━━━━━━━━━━━━━━━\u001b[0m\u001b[37m\u001b[0m \u001b[1m0s\u001b[0m 57ms/step\n",
      "\u001b[1m1/1\u001b[0m \u001b[32m━━━━━━━━━━━━━━━━━━━━\u001b[0m\u001b[37m\u001b[0m \u001b[1m0s\u001b[0m 50ms/step\n",
      "\u001b[1m1/1\u001b[0m \u001b[32m━━━━━━━━━━━━━━━━━━━━\u001b[0m\u001b[37m\u001b[0m \u001b[1m0s\u001b[0m 47ms/step\n",
      "\u001b[1m1/1\u001b[0m \u001b[32m━━━━━━━━━━━━━━━━━━━━\u001b[0m\u001b[37m\u001b[0m \u001b[1m0s\u001b[0m 47ms/step\n",
      "\u001b[1m1/1\u001b[0m \u001b[32m━━━━━━━━━━━━━━━━━━━━\u001b[0m\u001b[37m\u001b[0m \u001b[1m0s\u001b[0m 55ms/step\n",
      "\u001b[1m1/1\u001b[0m \u001b[32m━━━━━━━━━━━━━━━━━━━━\u001b[0m\u001b[37m\u001b[0m \u001b[1m0s\u001b[0m 54ms/step\n",
      "\u001b[1m1/1\u001b[0m \u001b[32m━━━━━━━━━━━━━━━━━━━━\u001b[0m\u001b[37m\u001b[0m \u001b[1m0s\u001b[0m 64ms/step\n",
      "\u001b[1m1/1\u001b[0m \u001b[32m━━━━━━━━━━━━━━━━━━━━\u001b[0m\u001b[37m\u001b[0m \u001b[1m0s\u001b[0m 47ms/step\n",
      "\u001b[1m1/1\u001b[0m \u001b[32m━━━━━━━━━━━━━━━━━━━━\u001b[0m\u001b[37m\u001b[0m \u001b[1m0s\u001b[0m 62ms/step\n",
      "\u001b[1m1/1\u001b[0m \u001b[32m━━━━━━━━━━━━━━━━━━━━\u001b[0m\u001b[37m\u001b[0m \u001b[1m0s\u001b[0m 62ms/step\n",
      "\u001b[1m1/1\u001b[0m \u001b[32m━━━━━━━━━━━━━━━━━━━━\u001b[0m\u001b[37m\u001b[0m \u001b[1m0s\u001b[0m 62ms/step\n",
      "\u001b[1m1/1\u001b[0m \u001b[32m━━━━━━━━━━━━━━━━━━━━\u001b[0m\u001b[37m\u001b[0m \u001b[1m0s\u001b[0m 65ms/step\n",
      "\u001b[1m1/1\u001b[0m \u001b[32m━━━━━━━━━━━━━━━━━━━━\u001b[0m\u001b[37m\u001b[0m \u001b[1m0s\u001b[0m 76ms/step\n",
      "\u001b[1m1/1\u001b[0m \u001b[32m━━━━━━━━━━━━━━━━━━━━\u001b[0m\u001b[37m\u001b[0m \u001b[1m0s\u001b[0m 67ms/step\n",
      "\u001b[1m1/1\u001b[0m \u001b[32m━━━━━━━━━━━━━━━━━━━━\u001b[0m\u001b[37m\u001b[0m \u001b[1m0s\u001b[0m 54ms/step\n",
      "\u001b[1m1/1\u001b[0m \u001b[32m━━━━━━━━━━━━━━━━━━━━\u001b[0m\u001b[37m\u001b[0m \u001b[1m0s\u001b[0m 62ms/step\n",
      "\u001b[1m1/1\u001b[0m \u001b[32m━━━━━━━━━━━━━━━━━━━━\u001b[0m\u001b[37m\u001b[0m \u001b[1m0s\u001b[0m 47ms/step\n",
      "\u001b[1m1/1\u001b[0m \u001b[32m━━━━━━━━━━━━━━━━━━━━\u001b[0m\u001b[37m\u001b[0m \u001b[1m0s\u001b[0m 64ms/step\n",
      "\u001b[1m1/1\u001b[0m \u001b[32m━━━━━━━━━━━━━━━━━━━━\u001b[0m\u001b[37m\u001b[0m \u001b[1m0s\u001b[0m 47ms/step\n",
      "\u001b[1m1/1\u001b[0m \u001b[32m━━━━━━━━━━━━━━━━━━━━\u001b[0m\u001b[37m\u001b[0m \u001b[1m0s\u001b[0m 55ms/step\n",
      "\u001b[1m1/1\u001b[0m \u001b[32m━━━━━━━━━━━━━━━━━━━━\u001b[0m\u001b[37m\u001b[0m \u001b[1m0s\u001b[0m 47ms/step\n",
      "\u001b[1m1/1\u001b[0m \u001b[32m━━━━━━━━━━━━━━━━━━━━\u001b[0m\u001b[37m\u001b[0m \u001b[1m0s\u001b[0m 47ms/step\n",
      "\u001b[1m1/1\u001b[0m \u001b[32m━━━━━━━━━━━━━━━━━━━━\u001b[0m\u001b[37m\u001b[0m \u001b[1m0s\u001b[0m 64ms/step\n",
      "\u001b[1m1/1\u001b[0m \u001b[32m━━━━━━━━━━━━━━━━━━━━\u001b[0m\u001b[37m\u001b[0m \u001b[1m0s\u001b[0m 62ms/step\n",
      "\u001b[1m1/1\u001b[0m \u001b[32m━━━━━━━━━━━━━━━━━━━━\u001b[0m\u001b[37m\u001b[0m \u001b[1m0s\u001b[0m 52ms/step\n",
      "\u001b[1m1/1\u001b[0m \u001b[32m━━━━━━━━━━━━━━━━━━━━\u001b[0m\u001b[37m\u001b[0m \u001b[1m0s\u001b[0m 63ms/step\n",
      "\u001b[1m1/1\u001b[0m \u001b[32m━━━━━━━━━━━━━━━━━━━━\u001b[0m\u001b[37m\u001b[0m \u001b[1m0s\u001b[0m 47ms/step\n",
      "\u001b[1m1/1\u001b[0m \u001b[32m━━━━━━━━━━━━━━━━━━━━\u001b[0m\u001b[37m\u001b[0m \u001b[1m0s\u001b[0m 47ms/step\n",
      "\u001b[1m1/1\u001b[0m \u001b[32m━━━━━━━━━━━━━━━━━━━━\u001b[0m\u001b[37m\u001b[0m \u001b[1m0s\u001b[0m 60ms/step\n",
      "\u001b[1m1/1\u001b[0m \u001b[32m━━━━━━━━━━━━━━━━━━━━\u001b[0m\u001b[37m\u001b[0m \u001b[1m0s\u001b[0m 47ms/step\n",
      "\u001b[1m1/1\u001b[0m \u001b[32m━━━━━━━━━━━━━━━━━━━━\u001b[0m\u001b[37m\u001b[0m \u001b[1m0s\u001b[0m 62ms/step\n",
      "\u001b[1m1/1\u001b[0m \u001b[32m━━━━━━━━━━━━━━━━━━━━\u001b[0m\u001b[37m\u001b[0m \u001b[1m0s\u001b[0m 64ms/step\n",
      "\u001b[1m1/1\u001b[0m \u001b[32m━━━━━━━━━━━━━━━━━━━━\u001b[0m\u001b[37m\u001b[0m \u001b[1m0s\u001b[0m 67ms/step\n",
      "\u001b[1m1/1\u001b[0m \u001b[32m━━━━━━━━━━━━━━━━━━━━\u001b[0m\u001b[37m\u001b[0m \u001b[1m0s\u001b[0m 47ms/step\n",
      "\u001b[1m1/1\u001b[0m \u001b[32m━━━━━━━━━━━━━━━━━━━━\u001b[0m\u001b[37m\u001b[0m \u001b[1m0s\u001b[0m 47ms/step\n",
      "\u001b[1m1/1\u001b[0m \u001b[32m━━━━━━━━━━━━━━━━━━━━\u001b[0m\u001b[37m\u001b[0m \u001b[1m0s\u001b[0m 47ms/step\n",
      "\u001b[1m1/1\u001b[0m \u001b[32m━━━━━━━━━━━━━━━━━━━━\u001b[0m\u001b[37m\u001b[0m \u001b[1m0s\u001b[0m 47ms/step\n",
      "\u001b[1m1/1\u001b[0m \u001b[32m━━━━━━━━━━━━━━━━━━━━\u001b[0m\u001b[37m\u001b[0m \u001b[1m0s\u001b[0m 47ms/step\n",
      "\u001b[1m1/1\u001b[0m \u001b[32m━━━━━━━━━━━━━━━━━━━━\u001b[0m\u001b[37m\u001b[0m \u001b[1m0s\u001b[0m 62ms/step\n",
      "\u001b[1m1/1\u001b[0m \u001b[32m━━━━━━━━━━━━━━━━━━━━\u001b[0m\u001b[37m\u001b[0m \u001b[1m0s\u001b[0m 47ms/step\n",
      "\u001b[1m1/1\u001b[0m \u001b[32m━━━━━━━━━━━━━━━━━━━━\u001b[0m\u001b[37m\u001b[0m \u001b[1m0s\u001b[0m 47ms/step\n",
      "\u001b[1m1/1\u001b[0m \u001b[32m━━━━━━━━━━━━━━━━━━━━\u001b[0m\u001b[37m\u001b[0m \u001b[1m0s\u001b[0m 73ms/step\n",
      "\u001b[1m1/1\u001b[0m \u001b[32m━━━━━━━━━━━━━━━━━━━━\u001b[0m\u001b[37m\u001b[0m \u001b[1m0s\u001b[0m 64ms/step\n",
      "\u001b[1m1/1\u001b[0m \u001b[32m━━━━━━━━━━━━━━━━━━━━\u001b[0m\u001b[37m\u001b[0m \u001b[1m0s\u001b[0m 47ms/step\n",
      "\u001b[1m1/1\u001b[0m \u001b[32m━━━━━━━━━━━━━━━━━━━━\u001b[0m\u001b[37m\u001b[0m \u001b[1m0s\u001b[0m 47ms/step\n",
      "\u001b[1m1/1\u001b[0m \u001b[32m━━━━━━━━━━━━━━━━━━━━\u001b[0m\u001b[37m\u001b[0m \u001b[1m0s\u001b[0m 49ms/step\n",
      "\u001b[1m1/1\u001b[0m \u001b[32m━━━━━━━━━━━━━━━━━━━━\u001b[0m\u001b[37m\u001b[0m \u001b[1m0s\u001b[0m 62ms/step\n",
      "\u001b[1m1/1\u001b[0m \u001b[32m━━━━━━━━━━━━━━━━━━━━\u001b[0m\u001b[37m\u001b[0m \u001b[1m0s\u001b[0m 47ms/step\n",
      "\u001b[1m1/1\u001b[0m \u001b[32m━━━━━━━━━━━━━━━━━━━━\u001b[0m\u001b[37m\u001b[0m \u001b[1m0s\u001b[0m 47ms/step\n",
      "\u001b[1m1/1\u001b[0m \u001b[32m━━━━━━━━━━━━━━━━━━━━\u001b[0m\u001b[37m\u001b[0m \u001b[1m0s\u001b[0m 60ms/step\n",
      "\u001b[1m1/1\u001b[0m \u001b[32m━━━━━━━━━━━━━━━━━━━━\u001b[0m\u001b[37m\u001b[0m \u001b[1m0s\u001b[0m 47ms/step\n",
      "\u001b[1m1/1\u001b[0m \u001b[32m━━━━━━━━━━━━━━━━━━━━\u001b[0m\u001b[37m\u001b[0m \u001b[1m0s\u001b[0m 63ms/step\n",
      "\u001b[1m1/1\u001b[0m \u001b[32m━━━━━━━━━━━━━━━━━━━━\u001b[0m\u001b[37m\u001b[0m \u001b[1m0s\u001b[0m 75ms/step\n",
      "\u001b[1m1/1\u001b[0m \u001b[32m━━━━━━━━━━━━━━━━━━━━\u001b[0m\u001b[37m\u001b[0m \u001b[1m0s\u001b[0m 47ms/step\n",
      "\u001b[1m1/1\u001b[0m \u001b[32m━━━━━━━━━━━━━━━━━━━━\u001b[0m\u001b[37m\u001b[0m \u001b[1m0s\u001b[0m 47ms/step\n",
      "\u001b[1m1/1\u001b[0m \u001b[32m━━━━━━━━━━━━━━━━━━━━\u001b[0m\u001b[37m\u001b[0m \u001b[1m0s\u001b[0m 47ms/step\n",
      "\u001b[1m1/1\u001b[0m \u001b[32m━━━━━━━━━━━━━━━━━━━━\u001b[0m\u001b[37m\u001b[0m \u001b[1m0s\u001b[0m 47ms/step\n",
      "\u001b[1m1/1\u001b[0m \u001b[32m━━━━━━━━━━━━━━━━━━━━\u001b[0m\u001b[37m\u001b[0m \u001b[1m0s\u001b[0m 47ms/step\n",
      "\u001b[1m1/1\u001b[0m \u001b[32m━━━━━━━━━━━━━━━━━━━━\u001b[0m\u001b[37m\u001b[0m \u001b[1m0s\u001b[0m 67ms/step\n",
      "\u001b[1m1/1\u001b[0m \u001b[32m━━━━━━━━━━━━━━━━━━━━\u001b[0m\u001b[37m\u001b[0m \u001b[1m0s\u001b[0m 54ms/step\n",
      "\u001b[1m1/1\u001b[0m \u001b[32m━━━━━━━━━━━━━━━━━━━━\u001b[0m\u001b[37m\u001b[0m \u001b[1m0s\u001b[0m 47ms/step\n",
      "\u001b[1m1/1\u001b[0m \u001b[32m━━━━━━━━━━━━━━━━━━━━\u001b[0m\u001b[37m\u001b[0m \u001b[1m0s\u001b[0m 41ms/step\n",
      "\u001b[1m1/1\u001b[0m \u001b[32m━━━━━━━━━━━━━━━━━━━━\u001b[0m\u001b[37m\u001b[0m \u001b[1m0s\u001b[0m 62ms/step\n",
      "\u001b[1m1/1\u001b[0m \u001b[32m━━━━━━━━━━━━━━━━━━━━\u001b[0m\u001b[37m\u001b[0m \u001b[1m0s\u001b[0m 63ms/step\n",
      "\u001b[1m1/1\u001b[0m \u001b[32m━━━━━━━━━━━━━━━━━━━━\u001b[0m\u001b[37m\u001b[0m \u001b[1m0s\u001b[0m 47ms/step\n",
      "\u001b[1m1/1\u001b[0m \u001b[32m━━━━━━━━━━━━━━━━━━━━\u001b[0m\u001b[37m\u001b[0m \u001b[1m0s\u001b[0m 66ms/step\n",
      "\u001b[1m1/1\u001b[0m \u001b[32m━━━━━━━━━━━━━━━━━━━━\u001b[0m\u001b[37m\u001b[0m \u001b[1m0s\u001b[0m 66ms/step\n",
      "\u001b[1m1/1\u001b[0m \u001b[32m━━━━━━━━━━━━━━━━━━━━\u001b[0m\u001b[37m\u001b[0m \u001b[1m0s\u001b[0m 54ms/step\n",
      "\u001b[1m1/1\u001b[0m \u001b[32m━━━━━━━━━━━━━━━━━━━━\u001b[0m\u001b[37m\u001b[0m \u001b[1m0s\u001b[0m 59ms/step\n",
      "\u001b[1m1/1\u001b[0m \u001b[32m━━━━━━━━━━━━━━━━━━━━\u001b[0m\u001b[37m\u001b[0m \u001b[1m0s\u001b[0m 47ms/step\n",
      "\u001b[1m1/1\u001b[0m \u001b[32m━━━━━━━━━━━━━━━━━━━━\u001b[0m\u001b[37m\u001b[0m \u001b[1m0s\u001b[0m 71ms/step\n",
      "\u001b[1m1/1\u001b[0m \u001b[32m━━━━━━━━━━━━━━━━━━━━\u001b[0m\u001b[37m\u001b[0m \u001b[1m0s\u001b[0m 47ms/step\n",
      "\u001b[1m1/1\u001b[0m \u001b[32m━━━━━━━━━━━━━━━━━━━━\u001b[0m\u001b[37m\u001b[0m \u001b[1m0s\u001b[0m 47ms/step\n",
      "\u001b[1m1/1\u001b[0m \u001b[32m━━━━━━━━━━━━━━━━━━━━\u001b[0m\u001b[37m\u001b[0m \u001b[1m0s\u001b[0m 48ms/step\n",
      "\u001b[1m1/1\u001b[0m \u001b[32m━━━━━━━━━━━━━━━━━━━━\u001b[0m\u001b[37m\u001b[0m \u001b[1m0s\u001b[0m 62ms/step\n",
      "\u001b[1m1/1\u001b[0m \u001b[32m━━━━━━━━━━━━━━━━━━━━\u001b[0m\u001b[37m\u001b[0m \u001b[1m0s\u001b[0m 49ms/step\n",
      "\u001b[1m1/1\u001b[0m \u001b[32m━━━━━━━━━━━━━━━━━━━━\u001b[0m\u001b[37m\u001b[0m \u001b[1m0s\u001b[0m 62ms/step\n",
      "\u001b[1m1/1\u001b[0m \u001b[32m━━━━━━━━━━━━━━━━━━━━\u001b[0m\u001b[37m\u001b[0m \u001b[1m0s\u001b[0m 47ms/step\n",
      "\u001b[1m1/1\u001b[0m \u001b[32m━━━━━━━━━━━━━━━━━━━━\u001b[0m\u001b[37m\u001b[0m \u001b[1m0s\u001b[0m 47ms/step\n",
      "\u001b[1m1/1\u001b[0m \u001b[32m━━━━━━━━━━━━━━━━━━━━\u001b[0m\u001b[37m\u001b[0m \u001b[1m0s\u001b[0m 47ms/step\n",
      "\u001b[1m1/1\u001b[0m \u001b[32m━━━━━━━━━━━━━━━━━━━━\u001b[0m\u001b[37m\u001b[0m \u001b[1m0s\u001b[0m 47ms/step\n",
      "\u001b[1m1/1\u001b[0m \u001b[32m━━━━━━━━━━━━━━━━━━━━\u001b[0m\u001b[37m\u001b[0m \u001b[1m0s\u001b[0m 62ms/step\n",
      "\u001b[1m1/1\u001b[0m \u001b[32m━━━━━━━━━━━━━━━━━━━━\u001b[0m\u001b[37m\u001b[0m \u001b[1m0s\u001b[0m 62ms/step\n",
      "\u001b[1m1/1\u001b[0m \u001b[32m━━━━━━━━━━━━━━━━━━━━\u001b[0m\u001b[37m\u001b[0m \u001b[1m0s\u001b[0m 47ms/step\n",
      "\u001b[1m1/1\u001b[0m \u001b[32m━━━━━━━━━━━━━━━━━━━━\u001b[0m\u001b[37m\u001b[0m \u001b[1m0s\u001b[0m 47ms/step\n",
      "\u001b[1m1/1\u001b[0m \u001b[32m━━━━━━━━━━━━━━━━━━━━\u001b[0m\u001b[37m\u001b[0m \u001b[1m0s\u001b[0m 51ms/step\n",
      "\u001b[1m1/1\u001b[0m \u001b[32m━━━━━━━━━━━━━━━━━━━━\u001b[0m\u001b[37m\u001b[0m \u001b[1m0s\u001b[0m 57ms/step\n",
      "\u001b[1m1/1\u001b[0m \u001b[32m━━━━━━━━━━━━━━━━━━━━\u001b[0m\u001b[37m\u001b[0m \u001b[1m0s\u001b[0m 62ms/step\n",
      "\u001b[1m1/1\u001b[0m \u001b[32m━━━━━━━━━━━━━━━━━━━━\u001b[0m\u001b[37m\u001b[0m \u001b[1m0s\u001b[0m 47ms/step\n",
      "\u001b[1m1/1\u001b[0m \u001b[32m━━━━━━━━━━━━━━━━━━━━\u001b[0m\u001b[37m\u001b[0m \u001b[1m0s\u001b[0m 47ms/step\n",
      "\u001b[1m1/1\u001b[0m \u001b[32m━━━━━━━━━━━━━━━━━━━━\u001b[0m\u001b[37m\u001b[0m \u001b[1m0s\u001b[0m 62ms/step\n",
      "\u001b[1m1/1\u001b[0m \u001b[32m━━━━━━━━━━━━━━━━━━━━\u001b[0m\u001b[37m\u001b[0m \u001b[1m0s\u001b[0m 47ms/step\n",
      "\u001b[1m1/1\u001b[0m \u001b[32m━━━━━━━━━━━━━━━━━━━━\u001b[0m\u001b[37m\u001b[0m \u001b[1m0s\u001b[0m 70ms/step\n",
      "\u001b[1m1/1\u001b[0m \u001b[32m━━━━━━━━━━━━━━━━━━━━\u001b[0m\u001b[37m\u001b[0m \u001b[1m0s\u001b[0m 47ms/step\n",
      "\u001b[1m1/1\u001b[0m \u001b[32m━━━━━━━━━━━━━━━━━━━━\u001b[0m\u001b[37m\u001b[0m \u001b[1m0s\u001b[0m 48ms/step\n",
      "\u001b[1m1/1\u001b[0m \u001b[32m━━━━━━━━━━━━━━━━━━━━\u001b[0m\u001b[37m\u001b[0m \u001b[1m0s\u001b[0m 47ms/step\n",
      "\u001b[1m1/1\u001b[0m \u001b[32m━━━━━━━━━━━━━━━━━━━━\u001b[0m\u001b[37m\u001b[0m \u001b[1m0s\u001b[0m 47ms/step\n",
      "\u001b[1m1/1\u001b[0m \u001b[32m━━━━━━━━━━━━━━━━━━━━\u001b[0m\u001b[37m\u001b[0m \u001b[1m0s\u001b[0m 47ms/step\n",
      "\u001b[1m1/1\u001b[0m \u001b[32m━━━━━━━━━━━━━━━━━━━━\u001b[0m\u001b[37m\u001b[0m \u001b[1m0s\u001b[0m 53ms/step\n",
      "\u001b[1m1/1\u001b[0m \u001b[32m━━━━━━━━━━━━━━━━━━━━\u001b[0m\u001b[37m\u001b[0m \u001b[1m0s\u001b[0m 62ms/step\n",
      "\u001b[1m1/1\u001b[0m \u001b[32m━━━━━━━━━━━━━━━━━━━━\u001b[0m\u001b[37m\u001b[0m \u001b[1m0s\u001b[0m 62ms/step\n",
      "\u001b[1m1/1\u001b[0m \u001b[32m━━━━━━━━━━━━━━━━━━━━\u001b[0m\u001b[37m\u001b[0m \u001b[1m0s\u001b[0m 62ms/step\n",
      "\u001b[1m1/1\u001b[0m \u001b[32m━━━━━━━━━━━━━━━━━━━━\u001b[0m\u001b[37m\u001b[0m \u001b[1m0s\u001b[0m 48ms/step\n",
      "\u001b[1m1/1\u001b[0m \u001b[32m━━━━━━━━━━━━━━━━━━━━\u001b[0m\u001b[37m\u001b[0m \u001b[1m0s\u001b[0m 48ms/step\n",
      "\u001b[1m1/1\u001b[0m \u001b[32m━━━━━━━━━━━━━━━━━━━━\u001b[0m\u001b[37m\u001b[0m \u001b[1m0s\u001b[0m 62ms/step\n",
      "\u001b[1m1/1\u001b[0m \u001b[32m━━━━━━━━━━━━━━━━━━━━\u001b[0m\u001b[37m\u001b[0m \u001b[1m0s\u001b[0m 55ms/step\n",
      "\u001b[1m1/1\u001b[0m \u001b[32m━━━━━━━━━━━━━━━━━━━━\u001b[0m\u001b[37m\u001b[0m \u001b[1m0s\u001b[0m 47ms/step\n",
      "\u001b[1m1/1\u001b[0m \u001b[32m━━━━━━━━━━━━━━━━━━━━\u001b[0m\u001b[37m\u001b[0m \u001b[1m0s\u001b[0m 62ms/step\n",
      "\u001b[1m1/1\u001b[0m \u001b[32m━━━━━━━━━━━━━━━━━━━━\u001b[0m\u001b[37m\u001b[0m \u001b[1m0s\u001b[0m 57ms/step\n",
      "\u001b[1m1/1\u001b[0m \u001b[32m━━━━━━━━━━━━━━━━━━━━\u001b[0m\u001b[37m\u001b[0m \u001b[1m0s\u001b[0m 62ms/step\n",
      "\u001b[1m1/1\u001b[0m \u001b[32m━━━━━━━━━━━━━━━━━━━━\u001b[0m\u001b[37m\u001b[0m \u001b[1m0s\u001b[0m 62ms/step\n",
      "\u001b[1m1/1\u001b[0m \u001b[32m━━━━━━━━━━━━━━━━━━━━\u001b[0m\u001b[37m\u001b[0m \u001b[1m0s\u001b[0m 62ms/step\n",
      "\u001b[1m1/1\u001b[0m \u001b[32m━━━━━━━━━━━━━━━━━━━━\u001b[0m\u001b[37m\u001b[0m \u001b[1m0s\u001b[0m 62ms/step\n",
      "\u001b[1m1/1\u001b[0m \u001b[32m━━━━━━━━━━━━━━━━━━━━\u001b[0m\u001b[37m\u001b[0m \u001b[1m0s\u001b[0m 66ms/step\n",
      "\u001b[1m1/1\u001b[0m \u001b[32m━━━━━━━━━━━━━━━━━━━━\u001b[0m\u001b[37m\u001b[0m \u001b[1m0s\u001b[0m 47ms/step\n",
      "\u001b[1m1/1\u001b[0m \u001b[32m━━━━━━━━━━━━━━━━━━━━\u001b[0m\u001b[37m\u001b[0m \u001b[1m0s\u001b[0m 69ms/step\n",
      "\u001b[1m1/1\u001b[0m \u001b[32m━━━━━━━━━━━━━━━━━━━━\u001b[0m\u001b[37m\u001b[0m \u001b[1m0s\u001b[0m 66ms/step\n",
      "\u001b[1m1/1\u001b[0m \u001b[32m━━━━━━━━━━━━━━━━━━━━\u001b[0m\u001b[37m\u001b[0m \u001b[1m0s\u001b[0m 48ms/step\n",
      "\u001b[1m1/1\u001b[0m \u001b[32m━━━━━━━━━━━━━━━━━━━━\u001b[0m\u001b[37m\u001b[0m \u001b[1m0s\u001b[0m 64ms/step\n",
      "\u001b[1m1/1\u001b[0m \u001b[32m━━━━━━━━━━━━━━━━━━━━\u001b[0m\u001b[37m\u001b[0m \u001b[1m0s\u001b[0m 47ms/step\n",
      "\u001b[1m1/1\u001b[0m \u001b[32m━━━━━━━━━━━━━━━━━━━━\u001b[0m\u001b[37m\u001b[0m \u001b[1m0s\u001b[0m 47ms/step\n",
      "\u001b[1m1/1\u001b[0m \u001b[32m━━━━━━━━━━━━━━━━━━━━\u001b[0m\u001b[37m\u001b[0m \u001b[1m0s\u001b[0m 48ms/step\n",
      "\u001b[1m1/1\u001b[0m \u001b[32m━━━━━━━━━━━━━━━━━━━━\u001b[0m\u001b[37m\u001b[0m \u001b[1m0s\u001b[0m 47ms/step\n",
      "\u001b[1m1/1\u001b[0m \u001b[32m━━━━━━━━━━━━━━━━━━━━\u001b[0m\u001b[37m\u001b[0m \u001b[1m0s\u001b[0m 47ms/step\n",
      "\u001b[1m1/1\u001b[0m \u001b[32m━━━━━━━━━━━━━━━━━━━━\u001b[0m\u001b[37m\u001b[0m \u001b[1m0s\u001b[0m 48ms/step\n",
      "\u001b[1m1/1\u001b[0m \u001b[32m━━━━━━━━━━━━━━━━━━━━\u001b[0m\u001b[37m\u001b[0m \u001b[1m0s\u001b[0m 64ms/step\n",
      "\u001b[1m1/1\u001b[0m \u001b[32m━━━━━━━━━━━━━━━━━━━━\u001b[0m\u001b[37m\u001b[0m \u001b[1m0s\u001b[0m 47ms/step\n",
      "\u001b[1m1/1\u001b[0m \u001b[32m━━━━━━━━━━━━━━━━━━━━\u001b[0m\u001b[37m\u001b[0m \u001b[1m0s\u001b[0m 47ms/step\n",
      "\u001b[1m1/1\u001b[0m \u001b[32m━━━━━━━━━━━━━━━━━━━━\u001b[0m\u001b[37m\u001b[0m \u001b[1m0s\u001b[0m 47ms/step\n",
      "\u001b[1m1/1\u001b[0m \u001b[32m━━━━━━━━━━━━━━━━━━━━\u001b[0m\u001b[37m\u001b[0m \u001b[1m0s\u001b[0m 62ms/step\n",
      "\u001b[1m1/1\u001b[0m \u001b[32m━━━━━━━━━━━━━━━━━━━━\u001b[0m\u001b[37m\u001b[0m \u001b[1m0s\u001b[0m 62ms/step\n",
      "\u001b[1m1/1\u001b[0m \u001b[32m━━━━━━━━━━━━━━━━━━━━\u001b[0m\u001b[37m\u001b[0m \u001b[1m0s\u001b[0m 58ms/step\n",
      "\u001b[1m1/1\u001b[0m \u001b[32m━━━━━━━━━━━━━━━━━━━━\u001b[0m\u001b[37m\u001b[0m \u001b[1m0s\u001b[0m 47ms/step\n",
      "\u001b[1m1/1\u001b[0m \u001b[32m━━━━━━━━━━━━━━━━━━━━\u001b[0m\u001b[37m\u001b[0m \u001b[1m0s\u001b[0m 38ms/step\n",
      "\u001b[1m1/1\u001b[0m \u001b[32m━━━━━━━━━━━━━━━━━━━━\u001b[0m\u001b[37m\u001b[0m \u001b[1m0s\u001b[0m 68ms/step\n",
      "\u001b[1m1/1\u001b[0m \u001b[32m━━━━━━━━━━━━━━━━━━━━\u001b[0m\u001b[37m\u001b[0m \u001b[1m0s\u001b[0m 47ms/step\n",
      "\u001b[1m1/1\u001b[0m \u001b[32m━━━━━━━━━━━━━━━━━━━━\u001b[0m\u001b[37m\u001b[0m \u001b[1m0s\u001b[0m 39ms/step\n",
      "\u001b[1m1/1\u001b[0m \u001b[32m━━━━━━━━━━━━━━━━━━━━\u001b[0m\u001b[37m\u001b[0m \u001b[1m0s\u001b[0m 62ms/step\n",
      "\u001b[1m1/1\u001b[0m \u001b[32m━━━━━━━━━━━━━━━━━━━━\u001b[0m\u001b[37m\u001b[0m \u001b[1m0s\u001b[0m 64ms/step\n",
      "\u001b[1m1/1\u001b[0m \u001b[32m━━━━━━━━━━━━━━━━━━━━\u001b[0m\u001b[37m\u001b[0m \u001b[1m0s\u001b[0m 62ms/step\n",
      "\u001b[1m1/1\u001b[0m \u001b[32m━━━━━━━━━━━━━━━━━━━━\u001b[0m\u001b[37m\u001b[0m \u001b[1m0s\u001b[0m 52ms/step\n",
      "\u001b[1m1/1\u001b[0m \u001b[32m━━━━━━━━━━━━━━━━━━━━\u001b[0m\u001b[37m\u001b[0m \u001b[1m0s\u001b[0m 49ms/step\n",
      "\u001b[1m1/1\u001b[0m \u001b[32m━━━━━━━━━━━━━━━━━━━━\u001b[0m\u001b[37m\u001b[0m \u001b[1m0s\u001b[0m 64ms/step\n",
      "\u001b[1m1/1\u001b[0m \u001b[32m━━━━━━━━━━━━━━━━━━━━\u001b[0m\u001b[37m\u001b[0m \u001b[1m0s\u001b[0m 47ms/step\n",
      "\u001b[1m1/1\u001b[0m \u001b[32m━━━━━━━━━━━━━━━━━━━━\u001b[0m\u001b[37m\u001b[0m \u001b[1m0s\u001b[0m 62ms/step\n",
      "\u001b[1m1/1\u001b[0m \u001b[32m━━━━━━━━━━━━━━━━━━━━\u001b[0m\u001b[37m\u001b[0m \u001b[1m0s\u001b[0m 55ms/step\n",
      "\u001b[1m1/1\u001b[0m \u001b[32m━━━━━━━━━━━━━━━━━━━━\u001b[0m\u001b[37m\u001b[0m \u001b[1m0s\u001b[0m 47ms/step\n",
      "\u001b[1m1/1\u001b[0m \u001b[32m━━━━━━━━━━━━━━━━━━━━\u001b[0m\u001b[37m\u001b[0m \u001b[1m0s\u001b[0m 54ms/step\n",
      "\u001b[1m1/1\u001b[0m \u001b[32m━━━━━━━━━━━━━━━━━━━━\u001b[0m\u001b[37m\u001b[0m \u001b[1m0s\u001b[0m 47ms/step\n",
      "\u001b[1m1/1\u001b[0m \u001b[32m━━━━━━━━━━━━━━━━━━━━\u001b[0m\u001b[37m\u001b[0m \u001b[1m0s\u001b[0m 62ms/step\n",
      "\u001b[1m1/1\u001b[0m \u001b[32m━━━━━━━━━━━━━━━━━━━━\u001b[0m\u001b[37m\u001b[0m \u001b[1m0s\u001b[0m 55ms/step\n",
      "\u001b[1m1/1\u001b[0m \u001b[32m━━━━━━━━━━━━━━━━━━━━\u001b[0m\u001b[37m\u001b[0m \u001b[1m0s\u001b[0m 62ms/step\n",
      "\u001b[1m1/1\u001b[0m \u001b[32m━━━━━━━━━━━━━━━━━━━━\u001b[0m\u001b[37m\u001b[0m \u001b[1m0s\u001b[0m 48ms/step\n",
      "\u001b[1m1/1\u001b[0m \u001b[32m━━━━━━━━━━━━━━━━━━━━\u001b[0m\u001b[37m\u001b[0m \u001b[1m0s\u001b[0m 62ms/step\n",
      "\u001b[1m1/1\u001b[0m \u001b[32m━━━━━━━━━━━━━━━━━━━━\u001b[0m\u001b[37m\u001b[0m \u001b[1m0s\u001b[0m 47ms/step\n",
      "\u001b[1m1/1\u001b[0m \u001b[32m━━━━━━━━━━━━━━━━━━━━\u001b[0m\u001b[37m\u001b[0m \u001b[1m0s\u001b[0m 66ms/step\n",
      "\u001b[1m1/1\u001b[0m \u001b[32m━━━━━━━━━━━━━━━━━━━━\u001b[0m\u001b[37m\u001b[0m \u001b[1m0s\u001b[0m 62ms/step\n",
      "\u001b[1m1/1\u001b[0m \u001b[32m━━━━━━━━━━━━━━━━━━━━\u001b[0m\u001b[37m\u001b[0m \u001b[1m0s\u001b[0m 49ms/step\n",
      "\u001b[1m1/1\u001b[0m \u001b[32m━━━━━━━━━━━━━━━━━━━━\u001b[0m\u001b[37m\u001b[0m \u001b[1m0s\u001b[0m 64ms/step\n",
      "\u001b[1m1/1\u001b[0m \u001b[32m━━━━━━━━━━━━━━━━━━━━\u001b[0m\u001b[37m\u001b[0m \u001b[1m0s\u001b[0m 62ms/step\n",
      "\u001b[1m1/1\u001b[0m \u001b[32m━━━━━━━━━━━━━━━━━━━━\u001b[0m\u001b[37m\u001b[0m \u001b[1m0s\u001b[0m 58ms/step\n",
      "\u001b[1m1/1\u001b[0m \u001b[32m━━━━━━━━━━━━━━━━━━━━\u001b[0m\u001b[37m\u001b[0m \u001b[1m0s\u001b[0m 48ms/step\n",
      "\u001b[1m1/1\u001b[0m \u001b[32m━━━━━━━━━━━━━━━━━━━━\u001b[0m\u001b[37m\u001b[0m \u001b[1m0s\u001b[0m 74ms/step\n",
      "\u001b[1m1/1\u001b[0m \u001b[32m━━━━━━━━━━━━━━━━━━━━\u001b[0m\u001b[37m\u001b[0m \u001b[1m0s\u001b[0m 62ms/step\n",
      "\u001b[1m1/1\u001b[0m \u001b[32m━━━━━━━━━━━━━━━━━━━━\u001b[0m\u001b[37m\u001b[0m \u001b[1m0s\u001b[0m 47ms/step\n",
      "\u001b[1m1/1\u001b[0m \u001b[32m━━━━━━━━━━━━━━━━━━━━\u001b[0m\u001b[37m\u001b[0m \u001b[1m0s\u001b[0m 56ms/step\n",
      "\u001b[1m1/1\u001b[0m \u001b[32m━━━━━━━━━━━━━━━━━━━━\u001b[0m\u001b[37m\u001b[0m \u001b[1m0s\u001b[0m 65ms/step\n",
      "\u001b[1m1/1\u001b[0m \u001b[32m━━━━━━━━━━━━━━━━━━━━\u001b[0m\u001b[37m\u001b[0m \u001b[1m0s\u001b[0m 43ms/step\n",
      "\u001b[1m1/1\u001b[0m \u001b[32m━━━━━━━━━━━━━━━━━━━━\u001b[0m\u001b[37m\u001b[0m \u001b[1m0s\u001b[0m 53ms/step\n",
      "\u001b[1m1/1\u001b[0m \u001b[32m━━━━━━━━━━━━━━━━━━━━\u001b[0m\u001b[37m\u001b[0m \u001b[1m0s\u001b[0m 47ms/step\n",
      "\u001b[1m1/1\u001b[0m \u001b[32m━━━━━━━━━━━━━━━━━━━━\u001b[0m\u001b[37m\u001b[0m \u001b[1m0s\u001b[0m 47ms/step\n",
      "\u001b[1m1/1\u001b[0m \u001b[32m━━━━━━━━━━━━━━━━━━━━\u001b[0m\u001b[37m\u001b[0m \u001b[1m0s\u001b[0m 62ms/step\n",
      "\u001b[1m1/1\u001b[0m \u001b[32m━━━━━━━━━━━━━━━━━━━━\u001b[0m\u001b[37m\u001b[0m \u001b[1m0s\u001b[0m 62ms/step\n",
      "\u001b[1m1/1\u001b[0m \u001b[32m━━━━━━━━━━━━━━━━━━━━\u001b[0m\u001b[37m\u001b[0m \u001b[1m0s\u001b[0m 68ms/step\n",
      "\u001b[1m1/1\u001b[0m \u001b[32m━━━━━━━━━━━━━━━━━━━━\u001b[0m\u001b[37m\u001b[0m \u001b[1m0s\u001b[0m 49ms/step\n",
      "\u001b[1m1/1\u001b[0m \u001b[32m━━━━━━━━━━━━━━━━━━━━\u001b[0m\u001b[37m\u001b[0m \u001b[1m0s\u001b[0m 51ms/step\n",
      "\u001b[1m1/1\u001b[0m \u001b[32m━━━━━━━━━━━━━━━━━━━━\u001b[0m\u001b[37m\u001b[0m \u001b[1m0s\u001b[0m 47ms/step\n",
      "\u001b[1m1/1\u001b[0m \u001b[32m━━━━━━━━━━━━━━━━━━━━\u001b[0m\u001b[37m\u001b[0m \u001b[1m0s\u001b[0m 45ms/step\n",
      "\u001b[1m1/1\u001b[0m \u001b[32m━━━━━━━━━━━━━━━━━━━━\u001b[0m\u001b[37m\u001b[0m \u001b[1m0s\u001b[0m 64ms/step\n",
      "\u001b[1m1/1\u001b[0m \u001b[32m━━━━━━━━━━━━━━━━━━━━\u001b[0m\u001b[37m\u001b[0m \u001b[1m0s\u001b[0m 62ms/step\n",
      "\u001b[1m1/1\u001b[0m \u001b[32m━━━━━━━━━━━━━━━━━━━━\u001b[0m\u001b[37m\u001b[0m \u001b[1m0s\u001b[0m 47ms/step\n",
      "\u001b[1m1/1\u001b[0m \u001b[32m━━━━━━━━━━━━━━━━━━━━\u001b[0m\u001b[37m\u001b[0m \u001b[1m0s\u001b[0m 47ms/step\n",
      "\u001b[1m1/1\u001b[0m \u001b[32m━━━━━━━━━━━━━━━━━━━━\u001b[0m\u001b[37m\u001b[0m \u001b[1m0s\u001b[0m 69ms/step\n",
      "\u001b[1m1/1\u001b[0m \u001b[32m━━━━━━━━━━━━━━━━━━━━\u001b[0m\u001b[37m\u001b[0m \u001b[1m0s\u001b[0m 53ms/step\n",
      "\u001b[1m1/1\u001b[0m \u001b[32m━━━━━━━━━━━━━━━━━━━━\u001b[0m\u001b[37m\u001b[0m \u001b[1m0s\u001b[0m 56ms/step\n",
      "\u001b[1m1/1\u001b[0m \u001b[32m━━━━━━━━━━━━━━━━━━━━\u001b[0m\u001b[37m\u001b[0m \u001b[1m0s\u001b[0m 63ms/step\n",
      "\u001b[1m1/1\u001b[0m \u001b[32m━━━━━━━━━━━━━━━━━━━━\u001b[0m\u001b[37m\u001b[0m \u001b[1m0s\u001b[0m 67ms/step\n",
      "\u001b[1m1/1\u001b[0m \u001b[32m━━━━━━━━━━━━━━━━━━━━\u001b[0m\u001b[37m\u001b[0m \u001b[1m0s\u001b[0m 67ms/step\n",
      "\u001b[1m1/1\u001b[0m \u001b[32m━━━━━━━━━━━━━━━━━━━━\u001b[0m\u001b[37m\u001b[0m \u001b[1m0s\u001b[0m 67ms/step\n",
      "\u001b[1m1/1\u001b[0m \u001b[32m━━━━━━━━━━━━━━━━━━━━\u001b[0m\u001b[37m\u001b[0m \u001b[1m0s\u001b[0m 67ms/step\n",
      "\u001b[1m1/1\u001b[0m \u001b[32m━━━━━━━━━━━━━━━━━━━━\u001b[0m\u001b[37m\u001b[0m \u001b[1m0s\u001b[0m 66ms/step\n",
      "\u001b[1m1/1\u001b[0m \u001b[32m━━━━━━━━━━━━━━━━━━━━\u001b[0m\u001b[37m\u001b[0m \u001b[1m0s\u001b[0m 66ms/step\n",
      "\u001b[1m1/1\u001b[0m \u001b[32m━━━━━━━━━━━━━━━━━━━━\u001b[0m\u001b[37m\u001b[0m \u001b[1m0s\u001b[0m 67ms/step\n",
      "\u001b[1m1/1\u001b[0m \u001b[32m━━━━━━━━━━━━━━━━━━━━\u001b[0m\u001b[37m\u001b[0m \u001b[1m0s\u001b[0m 54ms/step\n",
      "\u001b[1m1/1\u001b[0m \u001b[32m━━━━━━━━━━━━━━━━━━━━\u001b[0m\u001b[37m\u001b[0m \u001b[1m0s\u001b[0m 68ms/step\n",
      "\u001b[1m1/1\u001b[0m \u001b[32m━━━━━━━━━━━━━━━━━━━━\u001b[0m\u001b[37m\u001b[0m \u001b[1m0s\u001b[0m 54ms/step\n",
      "\u001b[1m1/1\u001b[0m \u001b[32m━━━━━━━━━━━━━━━━━━━━\u001b[0m\u001b[37m\u001b[0m \u001b[1m0s\u001b[0m 54ms/step\n",
      "\u001b[1m1/1\u001b[0m \u001b[32m━━━━━━━━━━━━━━━━━━━━\u001b[0m\u001b[37m\u001b[0m \u001b[1m0s\u001b[0m 54ms/step\n",
      "\u001b[1m1/1\u001b[0m \u001b[32m━━━━━━━━━━━━━━━━━━━━\u001b[0m\u001b[37m\u001b[0m \u001b[1m0s\u001b[0m 54ms/step\n",
      "\u001b[1m1/1\u001b[0m \u001b[32m━━━━━━━━━━━━━━━━━━━━\u001b[0m\u001b[37m\u001b[0m \u001b[1m0s\u001b[0m 54ms/step\n",
      "\u001b[1m1/1\u001b[0m \u001b[32m━━━━━━━━━━━━━━━━━━━━\u001b[0m\u001b[37m\u001b[0m \u001b[1m0s\u001b[0m 67ms/step\n",
      "\u001b[1m1/1\u001b[0m \u001b[32m━━━━━━━━━━━━━━━━━━━━\u001b[0m\u001b[37m\u001b[0m \u001b[1m0s\u001b[0m 67ms/step\n",
      "\u001b[1m1/1\u001b[0m \u001b[32m━━━━━━━━━━━━━━━━━━━━\u001b[0m\u001b[37m\u001b[0m \u001b[1m0s\u001b[0m 69ms/step\n",
      "\u001b[1m1/1\u001b[0m \u001b[32m━━━━━━━━━━━━━━━━━━━━\u001b[0m\u001b[37m\u001b[0m \u001b[1m0s\u001b[0m 65ms/step\n",
      "\u001b[1m1/1\u001b[0m \u001b[32m━━━━━━━━━━━━━━━━━━━━\u001b[0m\u001b[37m\u001b[0m \u001b[1m0s\u001b[0m 62ms/step\n",
      "\u001b[1m1/1\u001b[0m \u001b[32m━━━━━━━━━━━━━━━━━━━━\u001b[0m\u001b[37m\u001b[0m \u001b[1m0s\u001b[0m 69ms/step\n",
      "\u001b[1m1/1\u001b[0m \u001b[32m━━━━━━━━━━━━━━━━━━━━\u001b[0m\u001b[37m\u001b[0m \u001b[1m0s\u001b[0m 58ms/step\n",
      "\u001b[1m1/1\u001b[0m \u001b[32m━━━━━━━━━━━━━━━━━━━━\u001b[0m\u001b[37m\u001b[0m \u001b[1m0s\u001b[0m 67ms/step\n",
      "\u001b[1m1/1\u001b[0m \u001b[32m━━━━━━━━━━━━━━━━━━━━\u001b[0m\u001b[37m\u001b[0m \u001b[1m0s\u001b[0m 60ms/step\n",
      "\u001b[1m1/1\u001b[0m \u001b[32m━━━━━━━━━━━━━━━━━━━━\u001b[0m\u001b[37m\u001b[0m \u001b[1m0s\u001b[0m 65ms/step\n",
      "\u001b[1m1/1\u001b[0m \u001b[32m━━━━━━━━━━━━━━━━━━━━\u001b[0m\u001b[37m\u001b[0m \u001b[1m0s\u001b[0m 63ms/step\n",
      "\u001b[1m1/1\u001b[0m \u001b[32m━━━━━━━━━━━━━━━━━━━━\u001b[0m\u001b[37m\u001b[0m \u001b[1m0s\u001b[0m 54ms/step\n",
      "\u001b[1m1/1\u001b[0m \u001b[32m━━━━━━━━━━━━━━━━━━━━\u001b[0m\u001b[37m\u001b[0m \u001b[1m0s\u001b[0m 62ms/step\n",
      "\u001b[1m1/1\u001b[0m \u001b[32m━━━━━━━━━━━━━━━━━━━━\u001b[0m\u001b[37m\u001b[0m \u001b[1m0s\u001b[0m 58ms/step\n",
      "\u001b[1m1/1\u001b[0m \u001b[32m━━━━━━━━━━━━━━━━━━━━\u001b[0m\u001b[37m\u001b[0m \u001b[1m0s\u001b[0m 67ms/step\n",
      "\u001b[1m1/1\u001b[0m \u001b[32m━━━━━━━━━━━━━━━━━━━━\u001b[0m\u001b[37m\u001b[0m \u001b[1m0s\u001b[0m 57ms/step\n",
      "\u001b[1m1/1\u001b[0m \u001b[32m━━━━━━━━━━━━━━━━━━━━\u001b[0m\u001b[37m\u001b[0m \u001b[1m0s\u001b[0m 59ms/step\n",
      "\u001b[1m1/1\u001b[0m \u001b[32m━━━━━━━━━━━━━━━━━━━━\u001b[0m\u001b[37m\u001b[0m \u001b[1m0s\u001b[0m 59ms/step\n",
      "\u001b[1m1/1\u001b[0m \u001b[32m━━━━━━━━━━━━━━━━━━━━\u001b[0m\u001b[37m\u001b[0m \u001b[1m0s\u001b[0m 56ms/step\n",
      "\u001b[1m1/1\u001b[0m \u001b[32m━━━━━━━━━━━━━━━━━━━━\u001b[0m\u001b[37m\u001b[0m \u001b[1m0s\u001b[0m 59ms/step\n",
      "\u001b[1m1/1\u001b[0m \u001b[32m━━━━━━━━━━━━━━━━━━━━\u001b[0m\u001b[37m\u001b[0m \u001b[1m0s\u001b[0m 66ms/step\n",
      "\u001b[1m1/1\u001b[0m \u001b[32m━━━━━━━━━━━━━━━━━━━━\u001b[0m\u001b[37m\u001b[0m \u001b[1m0s\u001b[0m 64ms/step\n",
      "\u001b[1m1/1\u001b[0m \u001b[32m━━━━━━━━━━━━━━━━━━━━\u001b[0m\u001b[37m\u001b[0m \u001b[1m0s\u001b[0m 74ms/step\n",
      "\u001b[1m1/1\u001b[0m \u001b[32m━━━━━━━━━━━━━━━━━━━━\u001b[0m\u001b[37m\u001b[0m \u001b[1m0s\u001b[0m 56ms/step\n",
      "\u001b[1m1/1\u001b[0m \u001b[32m━━━━━━━━━━━━━━━━━━━━\u001b[0m\u001b[37m\u001b[0m \u001b[1m0s\u001b[0m 58ms/step\n",
      "\u001b[1m1/1\u001b[0m \u001b[32m━━━━━━━━━━━━━━━━━━━━\u001b[0m\u001b[37m\u001b[0m \u001b[1m0s\u001b[0m 68ms/step\n",
      "\u001b[1m1/1\u001b[0m \u001b[32m━━━━━━━━━━━━━━━━━━━━\u001b[0m\u001b[37m\u001b[0m \u001b[1m0s\u001b[0m 70ms/step\n",
      "\u001b[1m1/1\u001b[0m \u001b[32m━━━━━━━━━━━━━━━━━━━━\u001b[0m\u001b[37m\u001b[0m \u001b[1m0s\u001b[0m 60ms/step\n",
      "\u001b[1m1/1\u001b[0m \u001b[32m━━━━━━━━━━━━━━━━━━━━\u001b[0m\u001b[37m\u001b[0m \u001b[1m0s\u001b[0m 53ms/step\n",
      "\u001b[1m1/1\u001b[0m \u001b[32m━━━━━━━━━━━━━━━━━━━━\u001b[0m\u001b[37m\u001b[0m \u001b[1m0s\u001b[0m 59ms/step\n",
      "\u001b[1m1/1\u001b[0m \u001b[32m━━━━━━━━━━━━━━━━━━━━\u001b[0m\u001b[37m\u001b[0m \u001b[1m0s\u001b[0m 64ms/step\n",
      "\u001b[1m1/1\u001b[0m \u001b[32m━━━━━━━━━━━━━━━━━━━━\u001b[0m\u001b[37m\u001b[0m \u001b[1m0s\u001b[0m 58ms/step\n",
      "\u001b[1m1/1\u001b[0m \u001b[32m━━━━━━━━━━━━━━━━━━━━\u001b[0m\u001b[37m\u001b[0m \u001b[1m0s\u001b[0m 57ms/step\n",
      "\u001b[1m1/1\u001b[0m \u001b[32m━━━━━━━━━━━━━━━━━━━━\u001b[0m\u001b[37m\u001b[0m \u001b[1m0s\u001b[0m 61ms/step\n",
      "\u001b[1m1/1\u001b[0m \u001b[32m━━━━━━━━━━━━━━━━━━━━\u001b[0m\u001b[37m\u001b[0m \u001b[1m0s\u001b[0m 58ms/step\n",
      "\u001b[1m1/1\u001b[0m \u001b[32m━━━━━━━━━━━━━━━━━━━━\u001b[0m\u001b[37m\u001b[0m \u001b[1m0s\u001b[0m 57ms/step\n",
      "\u001b[1m1/1\u001b[0m \u001b[32m━━━━━━━━━━━━━━━━━━━━\u001b[0m\u001b[37m\u001b[0m \u001b[1m0s\u001b[0m 59ms/step\n",
      "\u001b[1m1/1\u001b[0m \u001b[32m━━━━━━━━━━━━━━━━━━━━\u001b[0m\u001b[37m\u001b[0m \u001b[1m0s\u001b[0m 55ms/step\n",
      "\u001b[1m1/1\u001b[0m \u001b[32m━━━━━━━━━━━━━━━━━━━━\u001b[0m\u001b[37m\u001b[0m \u001b[1m0s\u001b[0m 63ms/step\n",
      "\u001b[1m1/1\u001b[0m \u001b[32m━━━━━━━━━━━━━━━━━━━━\u001b[0m\u001b[37m\u001b[0m \u001b[1m0s\u001b[0m 53ms/step\n",
      "\u001b[1m1/1\u001b[0m \u001b[32m━━━━━━━━━━━━━━━━━━━━\u001b[0m\u001b[37m\u001b[0m \u001b[1m0s\u001b[0m 54ms/step\n",
      "\u001b[1m1/1\u001b[0m \u001b[32m━━━━━━━━━━━━━━━━━━━━\u001b[0m\u001b[37m\u001b[0m \u001b[1m0s\u001b[0m 66ms/step\n",
      "\u001b[1m1/1\u001b[0m \u001b[32m━━━━━━━━━━━━━━━━━━━━\u001b[0m\u001b[37m\u001b[0m \u001b[1m0s\u001b[0m 56ms/step\n",
      "\u001b[1m1/1\u001b[0m \u001b[32m━━━━━━━━━━━━━━━━━━━━\u001b[0m\u001b[37m\u001b[0m \u001b[1m0s\u001b[0m 59ms/step\n",
      "\u001b[1m1/1\u001b[0m \u001b[32m━━━━━━━━━━━━━━━━━━━━\u001b[0m\u001b[37m\u001b[0m \u001b[1m0s\u001b[0m 52ms/step\n",
      "\u001b[1m1/1\u001b[0m \u001b[32m━━━━━━━━━━━━━━━━━━━━\u001b[0m\u001b[37m\u001b[0m \u001b[1m0s\u001b[0m 55ms/step\n",
      "\u001b[1m1/1\u001b[0m \u001b[32m━━━━━━━━━━━━━━━━━━━━\u001b[0m\u001b[37m\u001b[0m \u001b[1m0s\u001b[0m 68ms/step\n",
      "\u001b[1m1/1\u001b[0m \u001b[32m━━━━━━━━━━━━━━━━━━━━\u001b[0m\u001b[37m\u001b[0m \u001b[1m0s\u001b[0m 65ms/step\n",
      "\u001b[1m1/1\u001b[0m \u001b[32m━━━━━━━━━━━━━━━━━━━━\u001b[0m\u001b[37m\u001b[0m \u001b[1m0s\u001b[0m 60ms/step\n",
      "\u001b[1m1/1\u001b[0m \u001b[32m━━━━━━━━━━━━━━━━━━━━\u001b[0m\u001b[37m\u001b[0m \u001b[1m0s\u001b[0m 60ms/step\n",
      "\u001b[1m1/1\u001b[0m \u001b[32m━━━━━━━━━━━━━━━━━━━━\u001b[0m\u001b[37m\u001b[0m \u001b[1m0s\u001b[0m 55ms/step\n",
      "\u001b[1m1/1\u001b[0m \u001b[32m━━━━━━━━━━━━━━━━━━━━\u001b[0m\u001b[37m\u001b[0m \u001b[1m0s\u001b[0m 58ms/step\n",
      "\u001b[1m1/1\u001b[0m \u001b[32m━━━━━━━━━━━━━━━━━━━━\u001b[0m\u001b[37m\u001b[0m \u001b[1m0s\u001b[0m 47ms/step\n",
      "\u001b[1m1/1\u001b[0m \u001b[32m━━━━━━━━━━━━━━━━━━━━\u001b[0m\u001b[37m\u001b[0m \u001b[1m0s\u001b[0m 47ms/step\n",
      "\u001b[1m1/1\u001b[0m \u001b[32m━━━━━━━━━━━━━━━━━━━━\u001b[0m\u001b[37m\u001b[0m \u001b[1m0s\u001b[0m 57ms/step\n",
      "\u001b[1m1/1\u001b[0m \u001b[32m━━━━━━━━━━━━━━━━━━━━\u001b[0m\u001b[37m\u001b[0m \u001b[1m0s\u001b[0m 76ms/step\n",
      "\u001b[1m1/1\u001b[0m \u001b[32m━━━━━━━━━━━━━━━━━━━━\u001b[0m\u001b[37m\u001b[0m \u001b[1m0s\u001b[0m 62ms/step\n",
      "\u001b[1m1/1\u001b[0m \u001b[32m━━━━━━━━━━━━━━━━━━━━\u001b[0m\u001b[37m\u001b[0m \u001b[1m0s\u001b[0m 70ms/step\n",
      "\u001b[1m1/1\u001b[0m \u001b[32m━━━━━━━━━━━━━━━━━━━━\u001b[0m\u001b[37m\u001b[0m \u001b[1m0s\u001b[0m 63ms/step\n",
      "\u001b[1m1/1\u001b[0m \u001b[32m━━━━━━━━━━━━━━━━━━━━\u001b[0m\u001b[37m\u001b[0m \u001b[1m0s\u001b[0m 52ms/step\n",
      "\u001b[1m1/1\u001b[0m \u001b[32m━━━━━━━━━━━━━━━━━━━━\u001b[0m\u001b[37m\u001b[0m \u001b[1m0s\u001b[0m 62ms/step\n",
      "\u001b[1m1/1\u001b[0m \u001b[32m━━━━━━━━━━━━━━━━━━━━\u001b[0m\u001b[37m\u001b[0m \u001b[1m0s\u001b[0m 64ms/step\n",
      "\u001b[1m1/1\u001b[0m \u001b[32m━━━━━━━━━━━━━━━━━━━━\u001b[0m\u001b[37m\u001b[0m \u001b[1m0s\u001b[0m 78ms/step\n",
      "\u001b[1m1/1\u001b[0m \u001b[32m━━━━━━━━━━━━━━━━━━━━\u001b[0m\u001b[37m\u001b[0m \u001b[1m0s\u001b[0m 64ms/step\n",
      "\u001b[1m1/1\u001b[0m \u001b[32m━━━━━━━━━━━━━━━━━━━━\u001b[0m\u001b[37m\u001b[0m \u001b[1m0s\u001b[0m 68ms/step\n",
      "\u001b[1m1/1\u001b[0m \u001b[32m━━━━━━━━━━━━━━━━━━━━\u001b[0m\u001b[37m\u001b[0m \u001b[1m0s\u001b[0m 51ms/step\n",
      "\u001b[1m1/1\u001b[0m \u001b[32m━━━━━━━━━━━━━━━━━━━━\u001b[0m\u001b[37m\u001b[0m \u001b[1m0s\u001b[0m 55ms/step\n",
      "\u001b[1m1/1\u001b[0m \u001b[32m━━━━━━━━━━━━━━━━━━━━\u001b[0m\u001b[37m\u001b[0m \u001b[1m0s\u001b[0m 77ms/step\n",
      "\u001b[1m1/1\u001b[0m \u001b[32m━━━━━━━━━━━━━━━━━━━━\u001b[0m\u001b[37m\u001b[0m \u001b[1m0s\u001b[0m 66ms/step\n",
      "\u001b[1m1/1\u001b[0m \u001b[32m━━━━━━━━━━━━━━━━━━━━\u001b[0m\u001b[37m\u001b[0m \u001b[1m0s\u001b[0m 62ms/step\n",
      "\u001b[1m1/1\u001b[0m \u001b[32m━━━━━━━━━━━━━━━━━━━━\u001b[0m\u001b[37m\u001b[0m \u001b[1m0s\u001b[0m 70ms/step\n",
      "\u001b[1m1/1\u001b[0m \u001b[32m━━━━━━━━━━━━━━━━━━━━\u001b[0m\u001b[37m\u001b[0m \u001b[1m0s\u001b[0m 73ms/step\n",
      "\u001b[1m1/1\u001b[0m \u001b[32m━━━━━━━━━━━━━━━━━━━━\u001b[0m\u001b[37m\u001b[0m \u001b[1m0s\u001b[0m 83ms/step\n",
      "\u001b[1m1/1\u001b[0m \u001b[32m━━━━━━━━━━━━━━━━━━━━\u001b[0m\u001b[37m\u001b[0m \u001b[1m0s\u001b[0m 67ms/step\n",
      "\u001b[1m1/1\u001b[0m \u001b[32m━━━━━━━━━━━━━━━━━━━━\u001b[0m\u001b[37m\u001b[0m \u001b[1m0s\u001b[0m 73ms/step\n",
      "\u001b[1m1/1\u001b[0m \u001b[32m━━━━━━━━━━━━━━━━━━━━\u001b[0m\u001b[37m\u001b[0m \u001b[1m0s\u001b[0m 61ms/step\n",
      "\u001b[1m1/1\u001b[0m \u001b[32m━━━━━━━━━━━━━━━━━━━━\u001b[0m\u001b[37m\u001b[0m \u001b[1m0s\u001b[0m 62ms/step\n",
      "\u001b[1m1/1\u001b[0m \u001b[32m━━━━━━━━━━━━━━━━━━━━\u001b[0m\u001b[37m\u001b[0m \u001b[1m0s\u001b[0m 61ms/step\n",
      "\u001b[1m1/1\u001b[0m \u001b[32m━━━━━━━━━━━━━━━━━━━━\u001b[0m\u001b[37m\u001b[0m \u001b[1m0s\u001b[0m 58ms/step\n",
      "\u001b[1m1/1\u001b[0m \u001b[32m━━━━━━━━━━━━━━━━━━━━\u001b[0m\u001b[37m\u001b[0m \u001b[1m0s\u001b[0m 62ms/step\n",
      "\u001b[1m1/1\u001b[0m \u001b[32m━━━━━━━━━━━━━━━━━━━━\u001b[0m\u001b[37m\u001b[0m \u001b[1m0s\u001b[0m 65ms/step\n",
      "\u001b[1m1/1\u001b[0m \u001b[32m━━━━━━━━━━━━━━━━━━━━\u001b[0m\u001b[37m\u001b[0m \u001b[1m0s\u001b[0m 52ms/step\n",
      "\u001b[1m1/1\u001b[0m \u001b[32m━━━━━━━━━━━━━━━━━━━━\u001b[0m\u001b[37m\u001b[0m \u001b[1m0s\u001b[0m 47ms/step\n",
      "\u001b[1m1/1\u001b[0m \u001b[32m━━━━━━━━━━━━━━━━━━━━\u001b[0m\u001b[37m\u001b[0m \u001b[1m0s\u001b[0m 72ms/step\n",
      "\u001b[1m1/1\u001b[0m \u001b[32m━━━━━━━━━━━━━━━━━━━━\u001b[0m\u001b[37m\u001b[0m \u001b[1m0s\u001b[0m 61ms/step\n",
      "\u001b[1m1/1\u001b[0m \u001b[32m━━━━━━━━━━━━━━━━━━━━\u001b[0m\u001b[37m\u001b[0m \u001b[1m0s\u001b[0m 63ms/step\n",
      "\u001b[1m1/1\u001b[0m \u001b[32m━━━━━━━━━━━━━━━━━━━━\u001b[0m\u001b[37m\u001b[0m \u001b[1m0s\u001b[0m 61ms/step\n",
      "\u001b[1m1/1\u001b[0m \u001b[32m━━━━━━━━━━━━━━━━━━━━\u001b[0m\u001b[37m\u001b[0m \u001b[1m0s\u001b[0m 70ms/step\n",
      "\u001b[1m1/1\u001b[0m \u001b[32m━━━━━━━━━━━━━━━━━━━━\u001b[0m\u001b[37m\u001b[0m \u001b[1m0s\u001b[0m 67ms/step\n",
      "\u001b[1m1/1\u001b[0m \u001b[32m━━━━━━━━━━━━━━━━━━━━\u001b[0m\u001b[37m\u001b[0m \u001b[1m0s\u001b[0m 64ms/step\n",
      "\u001b[1m1/1\u001b[0m \u001b[32m━━━━━━━━━━━━━━━━━━━━\u001b[0m\u001b[37m\u001b[0m \u001b[1m0s\u001b[0m 65ms/step\n",
      "\u001b[1m1/1\u001b[0m \u001b[32m━━━━━━━━━━━━━━━━━━━━\u001b[0m\u001b[37m\u001b[0m \u001b[1m0s\u001b[0m 62ms/step\n",
      "\u001b[1m1/1\u001b[0m \u001b[32m━━━━━━━━━━━━━━━━━━━━\u001b[0m\u001b[37m\u001b[0m \u001b[1m0s\u001b[0m 60ms/step\n",
      "\u001b[1m1/1\u001b[0m \u001b[32m━━━━━━━━━━━━━━━━━━━━\u001b[0m\u001b[37m\u001b[0m \u001b[1m0s\u001b[0m 60ms/step\n",
      "\u001b[1m1/1\u001b[0m \u001b[32m━━━━━━━━━━━━━━━━━━━━\u001b[0m\u001b[37m\u001b[0m \u001b[1m0s\u001b[0m 60ms/step\n",
      "\u001b[1m1/1\u001b[0m \u001b[32m━━━━━━━━━━━━━━━━━━━━\u001b[0m\u001b[37m\u001b[0m \u001b[1m0s\u001b[0m 60ms/step\n",
      "\u001b[1m1/1\u001b[0m \u001b[32m━━━━━━━━━━━━━━━━━━━━\u001b[0m\u001b[37m\u001b[0m \u001b[1m0s\u001b[0m 60ms/step\n",
      "\u001b[1m1/1\u001b[0m \u001b[32m━━━━━━━━━━━━━━━━━━━━\u001b[0m\u001b[37m\u001b[0m \u001b[1m0s\u001b[0m 74ms/step\n",
      "\u001b[1m1/1\u001b[0m \u001b[32m━━━━━━━━━━━━━━━━━━━━\u001b[0m\u001b[37m\u001b[0m \u001b[1m0s\u001b[0m 74ms/step\n",
      "\u001b[1m1/1\u001b[0m \u001b[32m━━━━━━━━━━━━━━━━━━━━\u001b[0m\u001b[37m\u001b[0m \u001b[1m0s\u001b[0m 64ms/step\n",
      "\u001b[1m1/1\u001b[0m \u001b[32m━━━━━━━━━━━━━━━━━━━━\u001b[0m\u001b[37m\u001b[0m \u001b[1m0s\u001b[0m 59ms/step\n",
      "\u001b[1m1/1\u001b[0m \u001b[32m━━━━━━━━━━━━━━━━━━━━\u001b[0m\u001b[37m\u001b[0m \u001b[1m0s\u001b[0m 59ms/step\n",
      "\u001b[1m1/1\u001b[0m \u001b[32m━━━━━━━━━━━━━━━━━━━━\u001b[0m\u001b[37m\u001b[0m \u001b[1m0s\u001b[0m 62ms/step\n",
      "\u001b[1m1/1\u001b[0m \u001b[32m━━━━━━━━━━━━━━━━━━━━\u001b[0m\u001b[37m\u001b[0m \u001b[1m0s\u001b[0m 58ms/step\n",
      "\u001b[1m1/1\u001b[0m \u001b[32m━━━━━━━━━━━━━━━━━━━━\u001b[0m\u001b[37m\u001b[0m \u001b[1m0s\u001b[0m 57ms/step\n",
      "\u001b[1m1/1\u001b[0m \u001b[32m━━━━━━━━━━━━━━━━━━━━\u001b[0m\u001b[37m\u001b[0m \u001b[1m0s\u001b[0m 63ms/step\n",
      "\u001b[1m1/1\u001b[0m \u001b[32m━━━━━━━━━━━━━━━━━━━━\u001b[0m\u001b[37m\u001b[0m \u001b[1m0s\u001b[0m 68ms/step\n",
      "\u001b[1m1/1\u001b[0m \u001b[32m━━━━━━━━━━━━━━━━━━━━\u001b[0m\u001b[37m\u001b[0m \u001b[1m0s\u001b[0m 70ms/step\n",
      "\u001b[1m1/1\u001b[0m \u001b[32m━━━━━━━━━━━━━━━━━━━━\u001b[0m\u001b[37m\u001b[0m \u001b[1m0s\u001b[0m 57ms/step\n",
      "\u001b[1m1/1\u001b[0m \u001b[32m━━━━━━━━━━━━━━━━━━━━\u001b[0m\u001b[37m\u001b[0m \u001b[1m0s\u001b[0m 63ms/step\n",
      "\u001b[1m1/1\u001b[0m \u001b[32m━━━━━━━━━━━━━━━━━━━━\u001b[0m\u001b[37m\u001b[0m \u001b[1m0s\u001b[0m 60ms/step\n",
      "\u001b[1m1/1\u001b[0m \u001b[32m━━━━━━━━━━━━━━━━━━━━\u001b[0m\u001b[37m\u001b[0m \u001b[1m0s\u001b[0m 74ms/step\n",
      "\u001b[1m1/1\u001b[0m \u001b[32m━━━━━━━━━━━━━━━━━━━━\u001b[0m\u001b[37m\u001b[0m \u001b[1m0s\u001b[0m 57ms/step\n",
      "\u001b[1m1/1\u001b[0m \u001b[32m━━━━━━━━━━━━━━━━━━━━\u001b[0m\u001b[37m\u001b[0m \u001b[1m0s\u001b[0m 64ms/step\n",
      "\u001b[1m1/1\u001b[0m \u001b[32m━━━━━━━━━━━━━━━━━━━━\u001b[0m\u001b[37m\u001b[0m \u001b[1m0s\u001b[0m 75ms/step\n",
      "\u001b[1m1/1\u001b[0m \u001b[32m━━━━━━━━━━━━━━━━━━━━\u001b[0m\u001b[37m\u001b[0m \u001b[1m0s\u001b[0m 62ms/step\n",
      "\u001b[1m1/1\u001b[0m \u001b[32m━━━━━━━━━━━━━━━━━━━━\u001b[0m\u001b[37m\u001b[0m \u001b[1m0s\u001b[0m 62ms/step\n",
      "\u001b[1m1/1\u001b[0m \u001b[32m━━━━━━━━━━━━━━━━━━━━\u001b[0m\u001b[37m\u001b[0m \u001b[1m0s\u001b[0m 66ms/step\n",
      "\u001b[1m1/1\u001b[0m \u001b[32m━━━━━━━━━━━━━━━━━━━━\u001b[0m\u001b[37m\u001b[0m \u001b[1m0s\u001b[0m 62ms/step\n",
      "\u001b[1m1/1\u001b[0m \u001b[32m━━━━━━━━━━━━━━━━━━━━\u001b[0m\u001b[37m\u001b[0m \u001b[1m0s\u001b[0m 69ms/step\n",
      "\u001b[1m1/1\u001b[0m \u001b[32m━━━━━━━━━━━━━━━━━━━━\u001b[0m\u001b[37m\u001b[0m \u001b[1m0s\u001b[0m 61ms/step\n",
      "\u001b[1m1/1\u001b[0m \u001b[32m━━━━━━━━━━━━━━━━━━━━\u001b[0m\u001b[37m\u001b[0m \u001b[1m0s\u001b[0m 57ms/step\n",
      "\u001b[1m1/1\u001b[0m \u001b[32m━━━━━━━━━━━━━━━━━━━━\u001b[0m\u001b[37m\u001b[0m \u001b[1m0s\u001b[0m 63ms/step\n",
      "\u001b[1m1/1\u001b[0m \u001b[32m━━━━━━━━━━━━━━━━━━━━\u001b[0m\u001b[37m\u001b[0m \u001b[1m0s\u001b[0m 58ms/step\n",
      "\u001b[1m1/1\u001b[0m \u001b[32m━━━━━━━━━━━━━━━━━━━━\u001b[0m\u001b[37m\u001b[0m \u001b[1m0s\u001b[0m 67ms/step\n",
      "\u001b[1m1/1\u001b[0m \u001b[32m━━━━━━━━━━━━━━━━━━━━\u001b[0m\u001b[37m\u001b[0m \u001b[1m0s\u001b[0m 56ms/step\n",
      "\u001b[1m1/1\u001b[0m \u001b[32m━━━━━━━━━━━━━━━━━━━━\u001b[0m\u001b[37m\u001b[0m \u001b[1m0s\u001b[0m 74ms/step\n",
      "\u001b[1m1/1\u001b[0m \u001b[32m━━━━━━━━━━━━━━━━━━━━\u001b[0m\u001b[37m\u001b[0m \u001b[1m0s\u001b[0m 54ms/step\n",
      "\u001b[1m1/1\u001b[0m \u001b[32m━━━━━━━━━━━━━━━━━━━━\u001b[0m\u001b[37m\u001b[0m \u001b[1m0s\u001b[0m 65ms/step\n",
      "\u001b[1m1/1\u001b[0m \u001b[32m━━━━━━━━━━━━━━━━━━━━\u001b[0m\u001b[37m\u001b[0m \u001b[1m0s\u001b[0m 66ms/step\n",
      "\u001b[1m1/1\u001b[0m \u001b[32m━━━━━━━━━━━━━━━━━━━━\u001b[0m\u001b[37m\u001b[0m \u001b[1m0s\u001b[0m 62ms/step\n",
      "\u001b[1m1/1\u001b[0m \u001b[32m━━━━━━━━━━━━━━━━━━━━\u001b[0m\u001b[37m\u001b[0m \u001b[1m0s\u001b[0m 60ms/step\n",
      "\u001b[1m1/1\u001b[0m \u001b[32m━━━━━━━━━━━━━━━━━━━━\u001b[0m\u001b[37m\u001b[0m \u001b[1m0s\u001b[0m 62ms/step\n",
      "\u001b[1m1/1\u001b[0m \u001b[32m━━━━━━━━━━━━━━━━━━━━\u001b[0m\u001b[37m\u001b[0m \u001b[1m0s\u001b[0m 60ms/step\n",
      "\u001b[1m1/1\u001b[0m \u001b[32m━━━━━━━━━━━━━━━━━━━━\u001b[0m\u001b[37m\u001b[0m \u001b[1m0s\u001b[0m 60ms/step\n",
      "\u001b[1m1/1\u001b[0m \u001b[32m━━━━━━━━━━━━━━━━━━━━\u001b[0m\u001b[37m\u001b[0m \u001b[1m0s\u001b[0m 73ms/step\n",
      "\u001b[1m1/1\u001b[0m \u001b[32m━━━━━━━━━━━━━━━━━━━━\u001b[0m\u001b[37m\u001b[0m \u001b[1m0s\u001b[0m 68ms/step\n",
      "\u001b[1m1/1\u001b[0m \u001b[32m━━━━━━━━━━━━━━━━━━━━\u001b[0m\u001b[37m\u001b[0m \u001b[1m0s\u001b[0m 45ms/step\n",
      "\u001b[1m1/1\u001b[0m \u001b[32m━━━━━━━━━━━━━━━━━━━━\u001b[0m\u001b[37m\u001b[0m \u001b[1m0s\u001b[0m 55ms/step\n",
      "\u001b[1m1/1\u001b[0m \u001b[32m━━━━━━━━━━━━━━━━━━━━\u001b[0m\u001b[37m\u001b[0m \u001b[1m0s\u001b[0m 60ms/step\n",
      "\u001b[1m1/1\u001b[0m \u001b[32m━━━━━━━━━━━━━━━━━━━━\u001b[0m\u001b[37m\u001b[0m \u001b[1m0s\u001b[0m 74ms/step\n",
      "\u001b[1m1/1\u001b[0m \u001b[32m━━━━━━━━━━━━━━━━━━━━\u001b[0m\u001b[37m\u001b[0m \u001b[1m0s\u001b[0m 54ms/step\n",
      "\u001b[1m1/1\u001b[0m \u001b[32m━━━━━━━━━━━━━━━━━━━━\u001b[0m\u001b[37m\u001b[0m \u001b[1m0s\u001b[0m 63ms/step\n",
      "\u001b[1m1/1\u001b[0m \u001b[32m━━━━━━━━━━━━━━━━━━━━\u001b[0m\u001b[37m\u001b[0m \u001b[1m0s\u001b[0m 74ms/step\n",
      "\u001b[1m1/1\u001b[0m \u001b[32m━━━━━━━━━━━━━━━━━━━━\u001b[0m\u001b[37m\u001b[0m \u001b[1m0s\u001b[0m 56ms/step\n",
      "\u001b[1m1/1\u001b[0m \u001b[32m━━━━━━━━━━━━━━━━━━━━\u001b[0m\u001b[37m\u001b[0m \u001b[1m0s\u001b[0m 60ms/step\n",
      "\u001b[1m1/1\u001b[0m \u001b[32m━━━━━━━━━━━━━━━━━━━━\u001b[0m\u001b[37m\u001b[0m \u001b[1m0s\u001b[0m 63ms/step\n",
      "\u001b[1m1/1\u001b[0m \u001b[32m━━━━━━━━━━━━━━━━━━━━\u001b[0m\u001b[37m\u001b[0m \u001b[1m0s\u001b[0m 63ms/step\n",
      "\u001b[1m1/1\u001b[0m \u001b[32m━━━━━━━━━━━━━━━━━━━━\u001b[0m\u001b[37m\u001b[0m \u001b[1m0s\u001b[0m 60ms/step\n",
      "\u001b[1m1/1\u001b[0m \u001b[32m━━━━━━━━━━━━━━━━━━━━\u001b[0m\u001b[37m\u001b[0m \u001b[1m0s\u001b[0m 59ms/step\n",
      "\u001b[1m1/1\u001b[0m \u001b[32m━━━━━━━━━━━━━━━━━━━━\u001b[0m\u001b[37m\u001b[0m \u001b[1m0s\u001b[0m 68ms/step\n",
      "\u001b[1m1/1\u001b[0m \u001b[32m━━━━━━━━━━━━━━━━━━━━\u001b[0m\u001b[37m\u001b[0m \u001b[1m0s\u001b[0m 60ms/step\n",
      "\u001b[1m1/1\u001b[0m \u001b[32m━━━━━━━━━━━━━━━━━━━━\u001b[0m\u001b[37m\u001b[0m \u001b[1m0s\u001b[0m 63ms/step\n",
      "\u001b[1m1/1\u001b[0m \u001b[32m━━━━━━━━━━━━━━━━━━━━\u001b[0m\u001b[37m\u001b[0m \u001b[1m0s\u001b[0m 61ms/step\n",
      "\u001b[1m1/1\u001b[0m \u001b[32m━━━━━━━━━━━━━━━━━━━━\u001b[0m\u001b[37m\u001b[0m \u001b[1m0s\u001b[0m 62ms/step\n",
      "\u001b[1m1/1\u001b[0m \u001b[32m━━━━━━━━━━━━━━━━━━━━\u001b[0m\u001b[37m\u001b[0m \u001b[1m0s\u001b[0m 58ms/step\n",
      "\u001b[1m1/1\u001b[0m \u001b[32m━━━━━━━━━━━━━━━━━━━━\u001b[0m\u001b[37m\u001b[0m \u001b[1m0s\u001b[0m 60ms/step\n",
      "\u001b[1m1/1\u001b[0m \u001b[32m━━━━━━━━━━━━━━━━━━━━\u001b[0m\u001b[37m\u001b[0m \u001b[1m0s\u001b[0m 60ms/step\n",
      "\u001b[1m1/1\u001b[0m \u001b[32m━━━━━━━━━━━━━━━━━━━━\u001b[0m\u001b[37m\u001b[0m \u001b[1m0s\u001b[0m 61ms/step\n",
      "\u001b[1m1/1\u001b[0m \u001b[32m━━━━━━━━━━━━━━━━━━━━\u001b[0m\u001b[37m\u001b[0m \u001b[1m0s\u001b[0m 59ms/step\n",
      "\u001b[1m1/1\u001b[0m \u001b[32m━━━━━━━━━━━━━━━━━━━━\u001b[0m\u001b[37m\u001b[0m \u001b[1m0s\u001b[0m 60ms/step\n",
      "\u001b[1m1/1\u001b[0m \u001b[32m━━━━━━━━━━━━━━━━━━━━\u001b[0m\u001b[37m\u001b[0m \u001b[1m0s\u001b[0m 56ms/step\n",
      "\u001b[1m1/1\u001b[0m \u001b[32m━━━━━━━━━━━━━━━━━━━━\u001b[0m\u001b[37m\u001b[0m \u001b[1m0s\u001b[0m 57ms/step\n",
      "\u001b[1m1/1\u001b[0m \u001b[32m━━━━━━━━━━━━━━━━━━━━\u001b[0m\u001b[37m\u001b[0m \u001b[1m0s\u001b[0m 58ms/step\n",
      "\u001b[1m1/1\u001b[0m \u001b[32m━━━━━━━━━━━━━━━━━━━━\u001b[0m\u001b[37m\u001b[0m \u001b[1m0s\u001b[0m 59ms/step\n",
      "\u001b[1m1/1\u001b[0m \u001b[32m━━━━━━━━━━━━━━━━━━━━\u001b[0m\u001b[37m\u001b[0m \u001b[1m0s\u001b[0m 61ms/step\n",
      "\u001b[1m1/1\u001b[0m \u001b[32m━━━━━━━━━━━━━━━━━━━━\u001b[0m\u001b[37m\u001b[0m \u001b[1m0s\u001b[0m 59ms/step\n",
      "\u001b[1m1/1\u001b[0m \u001b[32m━━━━━━━━━━━━━━━━━━━━\u001b[0m\u001b[37m\u001b[0m \u001b[1m0s\u001b[0m 60ms/step\n",
      "\u001b[1m1/1\u001b[0m \u001b[32m━━━━━━━━━━━━━━━━━━━━\u001b[0m\u001b[37m\u001b[0m \u001b[1m0s\u001b[0m 55ms/step\n",
      "\u001b[1m1/1\u001b[0m \u001b[32m━━━━━━━━━━━━━━━━━━━━\u001b[0m\u001b[37m\u001b[0m \u001b[1m0s\u001b[0m 52ms/step\n",
      "\u001b[1m1/1\u001b[0m \u001b[32m━━━━━━━━━━━━━━━━━━━━\u001b[0m\u001b[37m\u001b[0m \u001b[1m0s\u001b[0m 62ms/step\n",
      "\u001b[1m1/1\u001b[0m \u001b[32m━━━━━━━━━━━━━━━━━━━━\u001b[0m\u001b[37m\u001b[0m \u001b[1m0s\u001b[0m 58ms/step\n",
      "\u001b[1m1/1\u001b[0m \u001b[32m━━━━━━━━━━━━━━━━━━━━\u001b[0m\u001b[37m\u001b[0m \u001b[1m0s\u001b[0m 73ms/step\n",
      "\u001b[1m1/1\u001b[0m \u001b[32m━━━━━━━━━━━━━━━━━━━━\u001b[0m\u001b[37m\u001b[0m \u001b[1m0s\u001b[0m 66ms/step\n",
      "\u001b[1m1/1\u001b[0m \u001b[32m━━━━━━━━━━━━━━━━━━━━\u001b[0m\u001b[37m\u001b[0m \u001b[1m0s\u001b[0m 68ms/step\n",
      "\u001b[1m1/1\u001b[0m \u001b[32m━━━━━━━━━━━━━━━━━━━━\u001b[0m\u001b[37m\u001b[0m \u001b[1m0s\u001b[0m 69ms/step\n",
      "\u001b[1m1/1\u001b[0m \u001b[32m━━━━━━━━━━━━━━━━━━━━\u001b[0m\u001b[37m\u001b[0m \u001b[1m0s\u001b[0m 79ms/step\n",
      "\u001b[1m1/1\u001b[0m \u001b[32m━━━━━━━━━━━━━━━━━━━━\u001b[0m\u001b[37m\u001b[0m \u001b[1m0s\u001b[0m 59ms/step\n",
      "\u001b[1m1/1\u001b[0m \u001b[32m━━━━━━━━━━━━━━━━━━━━\u001b[0m\u001b[37m\u001b[0m \u001b[1m0s\u001b[0m 63ms/step\n",
      "\u001b[1m1/1\u001b[0m \u001b[32m━━━━━━━━━━━━━━━━━━━━\u001b[0m\u001b[37m\u001b[0m \u001b[1m0s\u001b[0m 47ms/step\n",
      "\u001b[1m1/1\u001b[0m \u001b[32m━━━━━━━━━━━━━━━━━━━━\u001b[0m\u001b[37m\u001b[0m \u001b[1m0s\u001b[0m 69ms/step\n",
      "\u001b[1m1/1\u001b[0m \u001b[32m━━━━━━━━━━━━━━━━━━━━\u001b[0m\u001b[37m\u001b[0m \u001b[1m0s\u001b[0m 62ms/step\n",
      "\u001b[1m1/1\u001b[0m \u001b[32m━━━━━━━━━━━━━━━━━━━━\u001b[0m\u001b[37m\u001b[0m \u001b[1m0s\u001b[0m 60ms/step\n",
      "\u001b[1m1/1\u001b[0m \u001b[32m━━━━━━━━━━━━━━━━━━━━\u001b[0m\u001b[37m\u001b[0m \u001b[1m0s\u001b[0m 61ms/step\n",
      "\u001b[1m1/1\u001b[0m \u001b[32m━━━━━━━━━━━━━━━━━━━━\u001b[0m\u001b[37m\u001b[0m \u001b[1m0s\u001b[0m 60ms/step\n",
      "\u001b[1m1/1\u001b[0m \u001b[32m━━━━━━━━━━━━━━━━━━━━\u001b[0m\u001b[37m\u001b[0m \u001b[1m0s\u001b[0m 59ms/step\n",
      "\u001b[1m1/1\u001b[0m \u001b[32m━━━━━━━━━━━━━━━━━━━━\u001b[0m\u001b[37m\u001b[0m \u001b[1m0s\u001b[0m 59ms/step\n",
      "\u001b[1m1/1\u001b[0m \u001b[32m━━━━━━━━━━━━━━━━━━━━\u001b[0m\u001b[37m\u001b[0m \u001b[1m0s\u001b[0m 59ms/step\n",
      "\u001b[1m1/1\u001b[0m \u001b[32m━━━━━━━━━━━━━━━━━━━━\u001b[0m\u001b[37m\u001b[0m \u001b[1m0s\u001b[0m 59ms/step\n",
      "\u001b[1m1/1\u001b[0m \u001b[32m━━━━━━━━━━━━━━━━━━━━\u001b[0m\u001b[37m\u001b[0m \u001b[1m0s\u001b[0m 64ms/step\n",
      "\u001b[1m1/1\u001b[0m \u001b[32m━━━━━━━━━━━━━━━━━━━━\u001b[0m\u001b[37m\u001b[0m \u001b[1m0s\u001b[0m 67ms/step\n",
      "\u001b[1m1/1\u001b[0m \u001b[32m━━━━━━━━━━━━━━━━━━━━\u001b[0m\u001b[37m\u001b[0m \u001b[1m0s\u001b[0m 59ms/step\n",
      "\u001b[1m1/1\u001b[0m \u001b[32m━━━━━━━━━━━━━━━━━━━━\u001b[0m\u001b[37m\u001b[0m \u001b[1m0s\u001b[0m 63ms/step\n",
      "\u001b[1m1/1\u001b[0m \u001b[32m━━━━━━━━━━━━━━━━━━━━\u001b[0m\u001b[37m\u001b[0m \u001b[1m0s\u001b[0m 59ms/step\n",
      "\u001b[1m1/1\u001b[0m \u001b[32m━━━━━━━━━━━━━━━━━━━━\u001b[0m\u001b[37m\u001b[0m \u001b[1m0s\u001b[0m 58ms/step\n",
      "\u001b[1m1/1\u001b[0m \u001b[32m━━━━━━━━━━━━━━━━━━━━\u001b[0m\u001b[37m\u001b[0m \u001b[1m0s\u001b[0m 63ms/step\n",
      "\u001b[1m1/1\u001b[0m \u001b[32m━━━━━━━━━━━━━━━━━━━━\u001b[0m\u001b[37m\u001b[0m \u001b[1m0s\u001b[0m 64ms/step\n",
      "\u001b[1m1/1\u001b[0m \u001b[32m━━━━━━━━━━━━━━━━━━━━\u001b[0m\u001b[37m\u001b[0m \u001b[1m0s\u001b[0m 70ms/step\n",
      "\u001b[1m1/1\u001b[0m \u001b[32m━━━━━━━━━━━━━━━━━━━━\u001b[0m\u001b[37m\u001b[0m \u001b[1m0s\u001b[0m 62ms/step\n",
      "\u001b[1m1/1\u001b[0m \u001b[32m━━━━━━━━━━━━━━━━━━━━\u001b[0m\u001b[37m\u001b[0m \u001b[1m0s\u001b[0m 61ms/step\n",
      "\u001b[1m1/1\u001b[0m \u001b[32m━━━━━━━━━━━━━━━━━━━━\u001b[0m\u001b[37m\u001b[0m \u001b[1m0s\u001b[0m 61ms/step\n",
      "\u001b[1m1/1\u001b[0m \u001b[32m━━━━━━━━━━━━━━━━━━━━\u001b[0m\u001b[37m\u001b[0m \u001b[1m0s\u001b[0m 62ms/step\n",
      "\u001b[1m1/1\u001b[0m \u001b[32m━━━━━━━━━━━━━━━━━━━━\u001b[0m\u001b[37m\u001b[0m \u001b[1m0s\u001b[0m 71ms/step\n",
      "\u001b[1m1/1\u001b[0m \u001b[32m━━━━━━━━━━━━━━━━━━━━\u001b[0m\u001b[37m\u001b[0m \u001b[1m0s\u001b[0m 60ms/step\n",
      "\u001b[1m1/1\u001b[0m \u001b[32m━━━━━━━━━━━━━━━━━━━━\u001b[0m\u001b[37m\u001b[0m \u001b[1m0s\u001b[0m 62ms/step\n",
      "\u001b[1m1/1\u001b[0m \u001b[32m━━━━━━━━━━━━━━━━━━━━\u001b[0m\u001b[37m\u001b[0m \u001b[1m0s\u001b[0m 61ms/step\n",
      "\u001b[1m1/1\u001b[0m \u001b[32m━━━━━━━━━━━━━━━━━━━━\u001b[0m\u001b[37m\u001b[0m \u001b[1m0s\u001b[0m 63ms/step\n",
      "\u001b[1m1/1\u001b[0m \u001b[32m━━━━━━━━━━━━━━━━━━━━\u001b[0m\u001b[37m\u001b[0m \u001b[1m0s\u001b[0m 60ms/step\n",
      "\u001b[1m1/1\u001b[0m \u001b[32m━━━━━━━━━━━━━━━━━━━━\u001b[0m\u001b[37m\u001b[0m \u001b[1m0s\u001b[0m 58ms/step\n",
      "\u001b[1m1/1\u001b[0m \u001b[32m━━━━━━━━━━━━━━━━━━━━\u001b[0m\u001b[37m\u001b[0m \u001b[1m0s\u001b[0m 62ms/step\n",
      "\u001b[1m1/1\u001b[0m \u001b[32m━━━━━━━━━━━━━━━━━━━━\u001b[0m\u001b[37m\u001b[0m \u001b[1m0s\u001b[0m 56ms/step\n",
      "\u001b[1m1/1\u001b[0m \u001b[32m━━━━━━━━━━━━━━━━━━━━\u001b[0m\u001b[37m\u001b[0m \u001b[1m0s\u001b[0m 60ms/step\n",
      "\u001b[1m1/1\u001b[0m \u001b[32m━━━━━━━━━━━━━━━━━━━━\u001b[0m\u001b[37m\u001b[0m \u001b[1m0s\u001b[0m 50ms/step\n",
      "\u001b[1m1/1\u001b[0m \u001b[32m━━━━━━━━━━━━━━━━━━━━\u001b[0m\u001b[37m\u001b[0m \u001b[1m0s\u001b[0m 57ms/step\n",
      "\u001b[1m1/1\u001b[0m \u001b[32m━━━━━━━━━━━━━━━━━━━━\u001b[0m\u001b[37m\u001b[0m \u001b[1m0s\u001b[0m 46ms/step\n",
      "\u001b[1m1/1\u001b[0m \u001b[32m━━━━━━━━━━━━━━━━━━━━\u001b[0m\u001b[37m\u001b[0m \u001b[1m0s\u001b[0m 42ms/step\n",
      "\u001b[1m1/1\u001b[0m \u001b[32m━━━━━━━━━━━━━━━━━━━━\u001b[0m\u001b[37m\u001b[0m \u001b[1m0s\u001b[0m 47ms/step\n",
      "\u001b[1m1/1\u001b[0m \u001b[32m━━━━━━━━━━━━━━━━━━━━\u001b[0m\u001b[37m\u001b[0m \u001b[1m0s\u001b[0m 63ms/step\n",
      "\u001b[1m1/1\u001b[0m \u001b[32m━━━━━━━━━━━━━━━━━━━━\u001b[0m\u001b[37m\u001b[0m \u001b[1m0s\u001b[0m 50ms/step\n",
      "\u001b[1m1/1\u001b[0m \u001b[32m━━━━━━━━━━━━━━━━━━━━\u001b[0m\u001b[37m\u001b[0m \u001b[1m0s\u001b[0m 52ms/step\n",
      "\u001b[1m1/1\u001b[0m \u001b[32m━━━━━━━━━━━━━━━━━━━━\u001b[0m\u001b[37m\u001b[0m \u001b[1m0s\u001b[0m 54ms/step\n",
      "\u001b[1m1/1\u001b[0m \u001b[32m━━━━━━━━━━━━━━━━━━━━\u001b[0m\u001b[37m\u001b[0m \u001b[1m0s\u001b[0m 60ms/step\n",
      "\u001b[1m1/1\u001b[0m \u001b[32m━━━━━━━━━━━━━━━━━━━━\u001b[0m\u001b[37m\u001b[0m \u001b[1m0s\u001b[0m 60ms/step\n",
      "\u001b[1m1/1\u001b[0m \u001b[32m━━━━━━━━━━━━━━━━━━━━\u001b[0m\u001b[37m\u001b[0m \u001b[1m0s\u001b[0m 65ms/step\n",
      "\u001b[1m1/1\u001b[0m \u001b[32m━━━━━━━━━━━━━━━━━━━━\u001b[0m\u001b[37m\u001b[0m \u001b[1m0s\u001b[0m 47ms/step\n",
      "\u001b[1m1/1\u001b[0m \u001b[32m━━━━━━━━━━━━━━━━━━━━\u001b[0m\u001b[37m\u001b[0m \u001b[1m0s\u001b[0m 53ms/step\n",
      "\u001b[1m1/1\u001b[0m \u001b[32m━━━━━━━━━━━━━━━━━━━━\u001b[0m\u001b[37m\u001b[0m \u001b[1m0s\u001b[0m 51ms/step\n",
      "\u001b[1m1/1\u001b[0m \u001b[32m━━━━━━━━━━━━━━━━━━━━\u001b[0m\u001b[37m\u001b[0m \u001b[1m0s\u001b[0m 57ms/step\n",
      "\u001b[1m1/1\u001b[0m \u001b[32m━━━━━━━━━━━━━━━━━━━━\u001b[0m\u001b[37m\u001b[0m \u001b[1m0s\u001b[0m 80ms/step\n",
      "\u001b[1m1/1\u001b[0m \u001b[32m━━━━━━━━━━━━━━━━━━━━\u001b[0m\u001b[37m\u001b[0m \u001b[1m0s\u001b[0m 60ms/step\n",
      "\u001b[1m1/1\u001b[0m \u001b[32m━━━━━━━━━━━━━━━━━━━━\u001b[0m\u001b[37m\u001b[0m \u001b[1m0s\u001b[0m 60ms/step\n",
      "\u001b[1m1/1\u001b[0m \u001b[32m━━━━━━━━━━━━━━━━━━━━\u001b[0m\u001b[37m\u001b[0m \u001b[1m0s\u001b[0m 65ms/step\n",
      "\u001b[1m1/1\u001b[0m \u001b[32m━━━━━━━━━━━━━━━━━━━━\u001b[0m\u001b[37m\u001b[0m \u001b[1m0s\u001b[0m 62ms/step\n",
      "\u001b[1m1/1\u001b[0m \u001b[32m━━━━━━━━━━━━━━━━━━━━\u001b[0m\u001b[37m\u001b[0m \u001b[1m0s\u001b[0m 76ms/step\n",
      "\u001b[1m1/1\u001b[0m \u001b[32m━━━━━━━━━━━━━━━━━━━━\u001b[0m\u001b[37m\u001b[0m \u001b[1m0s\u001b[0m 58ms/step\n",
      "\u001b[1m1/1\u001b[0m \u001b[32m━━━━━━━━━━━━━━━━━━━━\u001b[0m\u001b[37m\u001b[0m \u001b[1m0s\u001b[0m 62ms/step\n",
      "\u001b[1m1/1\u001b[0m \u001b[32m━━━━━━━━━━━━━━━━━━━━\u001b[0m\u001b[37m\u001b[0m \u001b[1m0s\u001b[0m 57ms/step\n",
      "\u001b[1m1/1\u001b[0m \u001b[32m━━━━━━━━━━━━━━━━━━━━\u001b[0m\u001b[37m\u001b[0m \u001b[1m0s\u001b[0m 59ms/step\n",
      "\u001b[1m1/1\u001b[0m \u001b[32m━━━━━━━━━━━━━━━━━━━━\u001b[0m\u001b[37m\u001b[0m \u001b[1m0s\u001b[0m 61ms/step\n",
      "\u001b[1m1/1\u001b[0m \u001b[32m━━━━━━━━━━━━━━━━━━━━\u001b[0m\u001b[37m\u001b[0m \u001b[1m0s\u001b[0m 65ms/step\n",
      "\u001b[1m1/1\u001b[0m \u001b[32m━━━━━━━━━━━━━━━━━━━━\u001b[0m\u001b[37m\u001b[0m \u001b[1m0s\u001b[0m 54ms/step\n",
      "\u001b[1m1/1\u001b[0m \u001b[32m━━━━━━━━━━━━━━━━━━━━\u001b[0m\u001b[37m\u001b[0m \u001b[1m0s\u001b[0m 66ms/step\n",
      "\u001b[1m1/1\u001b[0m \u001b[32m━━━━━━━━━━━━━━━━━━━━\u001b[0m\u001b[37m\u001b[0m \u001b[1m0s\u001b[0m 68ms/step\n",
      "\u001b[1m1/1\u001b[0m \u001b[32m━━━━━━━━━━━━━━━━━━━━\u001b[0m\u001b[37m\u001b[0m \u001b[1m0s\u001b[0m 65ms/step\n",
      "\u001b[1m1/1\u001b[0m \u001b[32m━━━━━━━━━━━━━━━━━━━━\u001b[0m\u001b[37m\u001b[0m \u001b[1m0s\u001b[0m 58ms/step\n",
      "\u001b[1m1/1\u001b[0m \u001b[32m━━━━━━━━━━━━━━━━━━━━\u001b[0m\u001b[37m\u001b[0m \u001b[1m0s\u001b[0m 62ms/step\n",
      "\u001b[1m1/1\u001b[0m \u001b[32m━━━━━━━━━━━━━━━━━━━━\u001b[0m\u001b[37m\u001b[0m \u001b[1m0s\u001b[0m 58ms/step\n",
      "\u001b[1m1/1\u001b[0m \u001b[32m━━━━━━━━━━━━━━━━━━━━\u001b[0m\u001b[37m\u001b[0m \u001b[1m0s\u001b[0m 62ms/step\n",
      "\u001b[1m1/1\u001b[0m \u001b[32m━━━━━━━━━━━━━━━━━━━━\u001b[0m\u001b[37m\u001b[0m \u001b[1m0s\u001b[0m 63ms/step\n",
      "\u001b[1m1/1\u001b[0m \u001b[32m━━━━━━━━━━━━━━━━━━━━\u001b[0m\u001b[37m\u001b[0m \u001b[1m0s\u001b[0m 59ms/step\n",
      "\u001b[1m1/1\u001b[0m \u001b[32m━━━━━━━━━━━━━━━━━━━━\u001b[0m\u001b[37m\u001b[0m \u001b[1m0s\u001b[0m 59ms/step\n",
      "\u001b[1m1/1\u001b[0m \u001b[32m━━━━━━━━━━━━━━━━━━━━\u001b[0m\u001b[37m\u001b[0m \u001b[1m0s\u001b[0m 61ms/step\n",
      "\u001b[1m1/1\u001b[0m \u001b[32m━━━━━━━━━━━━━━━━━━━━\u001b[0m\u001b[37m\u001b[0m \u001b[1m0s\u001b[0m 63ms/step\n",
      "\u001b[1m1/1\u001b[0m \u001b[32m━━━━━━━━━━━━━━━━━━━━\u001b[0m\u001b[37m\u001b[0m \u001b[1m0s\u001b[0m 61ms/step\n",
      "\u001b[1m1/1\u001b[0m \u001b[32m━━━━━━━━━━━━━━━━━━━━\u001b[0m\u001b[37m\u001b[0m \u001b[1m0s\u001b[0m 58ms/step\n",
      "\u001b[1m1/1\u001b[0m \u001b[32m━━━━━━━━━━━━━━━━━━━━\u001b[0m\u001b[37m\u001b[0m \u001b[1m0s\u001b[0m 76ms/step\n",
      "\u001b[1m1/1\u001b[0m \u001b[32m━━━━━━━━━━━━━━━━━━━━\u001b[0m\u001b[37m\u001b[0m \u001b[1m0s\u001b[0m 66ms/step\n",
      "\u001b[1m1/1\u001b[0m \u001b[32m━━━━━━━━━━━━━━━━━━━━\u001b[0m\u001b[37m\u001b[0m \u001b[1m0s\u001b[0m 60ms/step\n",
      "\u001b[1m1/1\u001b[0m \u001b[32m━━━━━━━━━━━━━━━━━━━━\u001b[0m\u001b[37m\u001b[0m \u001b[1m0s\u001b[0m 61ms/step\n",
      "\u001b[1m1/1\u001b[0m \u001b[32m━━━━━━━━━━━━━━━━━━━━\u001b[0m\u001b[37m\u001b[0m \u001b[1m0s\u001b[0m 62ms/step\n",
      "\u001b[1m1/1\u001b[0m \u001b[32m━━━━━━━━━━━━━━━━━━━━\u001b[0m\u001b[37m\u001b[0m \u001b[1m0s\u001b[0m 61ms/step\n",
      "\u001b[1m1/1\u001b[0m \u001b[32m━━━━━━━━━━━━━━━━━━━━\u001b[0m\u001b[37m\u001b[0m \u001b[1m0s\u001b[0m 63ms/step\n",
      "\u001b[1m1/1\u001b[0m \u001b[32m━━━━━━━━━━━━━━━━━━━━\u001b[0m\u001b[37m\u001b[0m \u001b[1m0s\u001b[0m 65ms/step\n",
      "\u001b[1m1/1\u001b[0m \u001b[32m━━━━━━━━━━━━━━━━━━━━\u001b[0m\u001b[37m\u001b[0m \u001b[1m0s\u001b[0m 62ms/step\n",
      "\u001b[1m1/1\u001b[0m \u001b[32m━━━━━━━━━━━━━━━━━━━━\u001b[0m\u001b[37m\u001b[0m \u001b[1m0s\u001b[0m 71ms/step\n",
      "\u001b[1m1/1\u001b[0m \u001b[32m━━━━━━━━━━━━━━━━━━━━\u001b[0m\u001b[37m\u001b[0m \u001b[1m0s\u001b[0m 63ms/step\n",
      "\u001b[1m1/1\u001b[0m \u001b[32m━━━━━━━━━━━━━━━━━━━━\u001b[0m\u001b[37m\u001b[0m \u001b[1m0s\u001b[0m 63ms/step\n",
      "\u001b[1m1/1\u001b[0m \u001b[32m━━━━━━━━━━━━━━━━━━━━\u001b[0m\u001b[37m\u001b[0m \u001b[1m0s\u001b[0m 66ms/step\n",
      "\u001b[1m1/1\u001b[0m \u001b[32m━━━━━━━━━━━━━━━━━━━━\u001b[0m\u001b[37m\u001b[0m \u001b[1m0s\u001b[0m 65ms/step\n",
      "\u001b[1m1/1\u001b[0m \u001b[32m━━━━━━━━━━━━━━━━━━━━\u001b[0m\u001b[37m\u001b[0m \u001b[1m0s\u001b[0m 64ms/step\n",
      "\u001b[1m1/1\u001b[0m \u001b[32m━━━━━━━━━━━━━━━━━━━━\u001b[0m\u001b[37m\u001b[0m \u001b[1m0s\u001b[0m 69ms/step\n",
      "\u001b[1m1/1\u001b[0m \u001b[32m━━━━━━━━━━━━━━━━━━━━\u001b[0m\u001b[37m\u001b[0m \u001b[1m0s\u001b[0m 63ms/step\n",
      "\u001b[1m1/1\u001b[0m \u001b[32m━━━━━━━━━━━━━━━━━━━━\u001b[0m\u001b[37m\u001b[0m \u001b[1m0s\u001b[0m 49ms/step\n",
      "\u001b[1m1/1\u001b[0m \u001b[32m━━━━━━━━━━━━━━━━━━━━\u001b[0m\u001b[37m\u001b[0m \u001b[1m0s\u001b[0m 53ms/step\n",
      "\u001b[1m1/1\u001b[0m \u001b[32m━━━━━━━━━━━━━━━━━━━━\u001b[0m\u001b[37m\u001b[0m \u001b[1m0s\u001b[0m 69ms/step\n",
      "\u001b[1m1/1\u001b[0m \u001b[32m━━━━━━━━━━━━━━━━━━━━\u001b[0m\u001b[37m\u001b[0m \u001b[1m0s\u001b[0m 61ms/step\n",
      "\u001b[1m1/1\u001b[0m \u001b[32m━━━━━━━━━━━━━━━━━━━━\u001b[0m\u001b[37m\u001b[0m \u001b[1m0s\u001b[0m 63ms/step\n",
      "\u001b[1m1/1\u001b[0m \u001b[32m━━━━━━━━━━━━━━━━━━━━\u001b[0m\u001b[37m\u001b[0m \u001b[1m0s\u001b[0m 66ms/step\n",
      "\u001b[1m1/1\u001b[0m \u001b[32m━━━━━━━━━━━━━━━━━━━━\u001b[0m\u001b[37m\u001b[0m \u001b[1m0s\u001b[0m 76ms/step\n",
      "\u001b[1m1/1\u001b[0m \u001b[32m━━━━━━━━━━━━━━━━━━━━\u001b[0m\u001b[37m\u001b[0m \u001b[1m0s\u001b[0m 63ms/step\n",
      "\u001b[1m1/1\u001b[0m \u001b[32m━━━━━━━━━━━━━━━━━━━━\u001b[0m\u001b[37m\u001b[0m \u001b[1m0s\u001b[0m 57ms/step\n",
      "\u001b[1m1/1\u001b[0m \u001b[32m━━━━━━━━━━━━━━━━━━━━\u001b[0m\u001b[37m\u001b[0m \u001b[1m0s\u001b[0m 72ms/step\n",
      "\u001b[1m1/1\u001b[0m \u001b[32m━━━━━━━━━━━━━━━━━━━━\u001b[0m\u001b[37m\u001b[0m \u001b[1m0s\u001b[0m 58ms/step\n",
      "\u001b[1m1/1\u001b[0m \u001b[32m━━━━━━━━━━━━━━━━━━━━\u001b[0m\u001b[37m\u001b[0m \u001b[1m0s\u001b[0m 62ms/step\n",
      "\u001b[1m1/1\u001b[0m \u001b[32m━━━━━━━━━━━━━━━━━━━━\u001b[0m\u001b[37m\u001b[0m \u001b[1m0s\u001b[0m 52ms/step\n",
      "\u001b[1m1/1\u001b[0m \u001b[32m━━━━━━━━━━━━━━━━━━━━\u001b[0m\u001b[37m\u001b[0m \u001b[1m0s\u001b[0m 50ms/step\n",
      "\u001b[1m1/1\u001b[0m \u001b[32m━━━━━━━━━━━━━━━━━━━━\u001b[0m\u001b[37m\u001b[0m \u001b[1m0s\u001b[0m 53ms/step\n",
      "\u001b[1m1/1\u001b[0m \u001b[32m━━━━━━━━━━━━━━━━━━━━\u001b[0m\u001b[37m\u001b[0m \u001b[1m0s\u001b[0m 57ms/step\n",
      "\u001b[1m1/1\u001b[0m \u001b[32m━━━━━━━━━━━━━━━━━━━━\u001b[0m\u001b[37m\u001b[0m \u001b[1m0s\u001b[0m 60ms/step\n",
      "\u001b[1m1/1\u001b[0m \u001b[32m━━━━━━━━━━━━━━━━━━━━\u001b[0m\u001b[37m\u001b[0m \u001b[1m0s\u001b[0m 59ms/step\n",
      "\u001b[1m1/1\u001b[0m \u001b[32m━━━━━━━━━━━━━━━━━━━━\u001b[0m\u001b[37m\u001b[0m \u001b[1m0s\u001b[0m 57ms/step\n",
      "\u001b[1m1/1\u001b[0m \u001b[32m━━━━━━━━━━━━━━━━━━━━\u001b[0m\u001b[37m\u001b[0m \u001b[1m0s\u001b[0m 66ms/step\n",
      "\u001b[1m1/1\u001b[0m \u001b[32m━━━━━━━━━━━━━━━━━━━━\u001b[0m\u001b[37m\u001b[0m \u001b[1m0s\u001b[0m 65ms/step\n",
      "\u001b[1m1/1\u001b[0m \u001b[32m━━━━━━━━━━━━━━━━━━━━\u001b[0m\u001b[37m\u001b[0m \u001b[1m0s\u001b[0m 59ms/step\n",
      "\u001b[1m1/1\u001b[0m \u001b[32m━━━━━━━━━━━━━━━━━━━━\u001b[0m\u001b[37m\u001b[0m \u001b[1m0s\u001b[0m 62ms/step\n",
      "\u001b[1m1/1\u001b[0m \u001b[32m━━━━━━━━━━━━━━━━━━━━\u001b[0m\u001b[37m\u001b[0m \u001b[1m0s\u001b[0m 64ms/step\n",
      "\u001b[1m1/1\u001b[0m \u001b[32m━━━━━━━━━━━━━━━━━━━━\u001b[0m\u001b[37m\u001b[0m \u001b[1m0s\u001b[0m 64ms/step\n",
      "\u001b[1m1/1\u001b[0m \u001b[32m━━━━━━━━━━━━━━━━━━━━\u001b[0m\u001b[37m\u001b[0m \u001b[1m0s\u001b[0m 61ms/step\n",
      "\u001b[1m1/1\u001b[0m \u001b[32m━━━━━━━━━━━━━━━━━━━━\u001b[0m\u001b[37m\u001b[0m \u001b[1m0s\u001b[0m 70ms/step\n",
      "\u001b[1m1/1\u001b[0m \u001b[32m━━━━━━━━━━━━━━━━━━━━\u001b[0m\u001b[37m\u001b[0m \u001b[1m0s\u001b[0m 66ms/step\n",
      "\u001b[1m1/1\u001b[0m \u001b[32m━━━━━━━━━━━━━━━━━━━━\u001b[0m\u001b[37m\u001b[0m \u001b[1m0s\u001b[0m 66ms/step\n",
      "\u001b[1m1/1\u001b[0m \u001b[32m━━━━━━━━━━━━━━━━━━━━\u001b[0m\u001b[37m\u001b[0m \u001b[1m0s\u001b[0m 63ms/step\n",
      "\u001b[1m1/1\u001b[0m \u001b[32m━━━━━━━━━━━━━━━━━━━━\u001b[0m\u001b[37m\u001b[0m \u001b[1m0s\u001b[0m 61ms/step\n",
      "\u001b[1m1/1\u001b[0m \u001b[32m━━━━━━━━━━━━━━━━━━━━\u001b[0m\u001b[37m\u001b[0m \u001b[1m0s\u001b[0m 67ms/step\n",
      "\u001b[1m1/1\u001b[0m \u001b[32m━━━━━━━━━━━━━━━━━━━━\u001b[0m\u001b[37m\u001b[0m \u001b[1m0s\u001b[0m 54ms/step\n",
      "\u001b[1m1/1\u001b[0m \u001b[32m━━━━━━━━━━━━━━━━━━━━\u001b[0m\u001b[37m\u001b[0m \u001b[1m0s\u001b[0m 45ms/step\n",
      "\u001b[1m1/1\u001b[0m \u001b[32m━━━━━━━━━━━━━━━━━━━━\u001b[0m\u001b[37m\u001b[0m \u001b[1m0s\u001b[0m 52ms/step\n",
      "\u001b[1m1/1\u001b[0m \u001b[32m━━━━━━━━━━━━━━━━━━━━\u001b[0m\u001b[37m\u001b[0m \u001b[1m0s\u001b[0m 51ms/step\n",
      "\u001b[1m1/1\u001b[0m \u001b[32m━━━━━━━━━━━━━━━━━━━━\u001b[0m\u001b[37m\u001b[0m \u001b[1m0s\u001b[0m 64ms/step\n",
      "\u001b[1m1/1\u001b[0m \u001b[32m━━━━━━━━━━━━━━━━━━━━\u001b[0m\u001b[37m\u001b[0m \u001b[1m0s\u001b[0m 57ms/step\n",
      "\u001b[1m1/1\u001b[0m \u001b[32m━━━━━━━━━━━━━━━━━━━━\u001b[0m\u001b[37m\u001b[0m \u001b[1m0s\u001b[0m 74ms/step\n",
      "\u001b[1m1/1\u001b[0m \u001b[32m━━━━━━━━━━━━━━━━━━━━\u001b[0m\u001b[37m\u001b[0m \u001b[1m0s\u001b[0m 54ms/step\n",
      "\u001b[1m1/1\u001b[0m \u001b[32m━━━━━━━━━━━━━━━━━━━━\u001b[0m\u001b[37m\u001b[0m \u001b[1m0s\u001b[0m 61ms/step\n",
      "\u001b[1m1/1\u001b[0m \u001b[32m━━━━━━━━━━━━━━━━━━━━\u001b[0m\u001b[37m\u001b[0m \u001b[1m0s\u001b[0m 61ms/step\n",
      "\u001b[1m1/1\u001b[0m \u001b[32m━━━━━━━━━━━━━━━━━━━━\u001b[0m\u001b[37m\u001b[0m \u001b[1m0s\u001b[0m 68ms/step\n",
      "\u001b[1m1/1\u001b[0m \u001b[32m━━━━━━━━━━━━━━━━━━━━\u001b[0m\u001b[37m\u001b[0m \u001b[1m0s\u001b[0m 72ms/step\n",
      "\u001b[1m1/1\u001b[0m \u001b[32m━━━━━━━━━━━━━━━━━━━━\u001b[0m\u001b[37m\u001b[0m \u001b[1m0s\u001b[0m 69ms/step\n",
      "\u001b[1m1/1\u001b[0m \u001b[32m━━━━━━━━━━━━━━━━━━━━\u001b[0m\u001b[37m\u001b[0m \u001b[1m0s\u001b[0m 68ms/step\n",
      "\u001b[1m1/1\u001b[0m \u001b[32m━━━━━━━━━━━━━━━━━━━━\u001b[0m\u001b[37m\u001b[0m \u001b[1m0s\u001b[0m 64ms/step\n",
      "\u001b[1m1/1\u001b[0m \u001b[32m━━━━━━━━━━━━━━━━━━━━\u001b[0m\u001b[37m\u001b[0m \u001b[1m0s\u001b[0m 75ms/step\n",
      "\u001b[1m1/1\u001b[0m \u001b[32m━━━━━━━━━━━━━━━━━━━━\u001b[0m\u001b[37m\u001b[0m \u001b[1m0s\u001b[0m 64ms/step\n",
      "\u001b[1m1/1\u001b[0m \u001b[32m━━━━━━━━━━━━━━━━━━━━\u001b[0m\u001b[37m\u001b[0m \u001b[1m0s\u001b[0m 59ms/step\n",
      "\u001b[1m1/1\u001b[0m \u001b[32m━━━━━━━━━━━━━━━━━━━━\u001b[0m\u001b[37m\u001b[0m \u001b[1m0s\u001b[0m 61ms/step\n",
      "\u001b[1m1/1\u001b[0m \u001b[32m━━━━━━━━━━━━━━━━━━━━\u001b[0m\u001b[37m\u001b[0m \u001b[1m0s\u001b[0m 62ms/step\n",
      "\u001b[1m1/1\u001b[0m \u001b[32m━━━━━━━━━━━━━━━━━━━━\u001b[0m\u001b[37m\u001b[0m \u001b[1m0s\u001b[0m 67ms/step\n",
      "\u001b[1m1/1\u001b[0m \u001b[32m━━━━━━━━━━━━━━━━━━━━\u001b[0m\u001b[37m\u001b[0m \u001b[1m0s\u001b[0m 64ms/step\n",
      "\u001b[1m1/1\u001b[0m \u001b[32m━━━━━━━━━━━━━━━━━━━━\u001b[0m\u001b[37m\u001b[0m \u001b[1m0s\u001b[0m 62ms/step\n",
      "\u001b[1m1/1\u001b[0m \u001b[32m━━━━━━━━━━━━━━━━━━━━\u001b[0m\u001b[37m\u001b[0m \u001b[1m0s\u001b[0m 61ms/step\n",
      "\u001b[1m1/1\u001b[0m \u001b[32m━━━━━━━━━━━━━━━━━━━━\u001b[0m\u001b[37m\u001b[0m \u001b[1m0s\u001b[0m 62ms/step\n",
      "\u001b[1m1/1\u001b[0m \u001b[32m━━━━━━━━━━━━━━━━━━━━\u001b[0m\u001b[37m\u001b[0m \u001b[1m0s\u001b[0m 61ms/step\n",
      "\u001b[1m1/1\u001b[0m \u001b[32m━━━━━━━━━━━━━━━━━━━━\u001b[0m\u001b[37m\u001b[0m \u001b[1m0s\u001b[0m 61ms/step\n",
      "\u001b[1m1/1\u001b[0m \u001b[32m━━━━━━━━━━━━━━━━━━━━\u001b[0m\u001b[37m\u001b[0m \u001b[1m0s\u001b[0m 65ms/step\n",
      "\u001b[1m1/1\u001b[0m \u001b[32m━━━━━━━━━━━━━━━━━━━━\u001b[0m\u001b[37m\u001b[0m \u001b[1m0s\u001b[0m 59ms/step\n",
      "\u001b[1m1/1\u001b[0m \u001b[32m━━━━━━━━━━━━━━━━━━━━\u001b[0m\u001b[37m\u001b[0m \u001b[1m0s\u001b[0m 65ms/step\n",
      "\u001b[1m1/1\u001b[0m \u001b[32m━━━━━━━━━━━━━━━━━━━━\u001b[0m\u001b[37m\u001b[0m \u001b[1m0s\u001b[0m 69ms/step\n",
      "\u001b[1m1/1\u001b[0m \u001b[32m━━━━━━━━━━━━━━━━━━━━\u001b[0m\u001b[37m\u001b[0m \u001b[1m0s\u001b[0m 66ms/step\n",
      "\u001b[1m1/1\u001b[0m \u001b[32m━━━━━━━━━━━━━━━━━━━━\u001b[0m\u001b[37m\u001b[0m \u001b[1m0s\u001b[0m 62ms/step\n",
      "\u001b[1m1/1\u001b[0m \u001b[32m━━━━━━━━━━━━━━━━━━━━\u001b[0m\u001b[37m\u001b[0m \u001b[1m0s\u001b[0m 69ms/step\n",
      "\u001b[1m1/1\u001b[0m \u001b[32m━━━━━━━━━━━━━━━━━━━━\u001b[0m\u001b[37m\u001b[0m \u001b[1m0s\u001b[0m 64ms/step\n",
      "\u001b[1m1/1\u001b[0m \u001b[32m━━━━━━━━━━━━━━━━━━━━\u001b[0m\u001b[37m\u001b[0m \u001b[1m0s\u001b[0m 64ms/step\n",
      "\u001b[1m1/1\u001b[0m \u001b[32m━━━━━━━━━━━━━━━━━━━━\u001b[0m\u001b[37m\u001b[0m \u001b[1m0s\u001b[0m 60ms/step\n",
      "\u001b[1m1/1\u001b[0m \u001b[32m━━━━━━━━━━━━━━━━━━━━\u001b[0m\u001b[37m\u001b[0m \u001b[1m0s\u001b[0m 60ms/step\n",
      "\u001b[1m1/1\u001b[0m \u001b[32m━━━━━━━━━━━━━━━━━━━━\u001b[0m\u001b[37m\u001b[0m \u001b[1m0s\u001b[0m 54ms/step\n",
      "\u001b[1m1/1\u001b[0m \u001b[32m━━━━━━━━━━━━━━━━━━━━\u001b[0m\u001b[37m\u001b[0m \u001b[1m0s\u001b[0m 61ms/step\n",
      "\u001b[1m1/1\u001b[0m \u001b[32m━━━━━━━━━━━━━━━━━━━━\u001b[0m\u001b[37m\u001b[0m \u001b[1m0s\u001b[0m 64ms/step\n",
      "\u001b[1m1/1\u001b[0m \u001b[32m━━━━━━━━━━━━━━━━━━━━\u001b[0m\u001b[37m\u001b[0m \u001b[1m0s\u001b[0m 66ms/step\n",
      "\u001b[1m1/1\u001b[0m \u001b[32m━━━━━━━━━━━━━━━━━━━━\u001b[0m\u001b[37m\u001b[0m \u001b[1m0s\u001b[0m 59ms/step\n",
      "\u001b[1m1/1\u001b[0m \u001b[32m━━━━━━━━━━━━━━━━━━━━\u001b[0m\u001b[37m\u001b[0m \u001b[1m0s\u001b[0m 63ms/step\n",
      "\u001b[1m1/1\u001b[0m \u001b[32m━━━━━━━━━━━━━━━━━━━━\u001b[0m\u001b[37m\u001b[0m \u001b[1m0s\u001b[0m 61ms/step\n",
      "\u001b[1m1/1\u001b[0m \u001b[32m━━━━━━━━━━━━━━━━━━━━\u001b[0m\u001b[37m\u001b[0m \u001b[1m0s\u001b[0m 64ms/step\n",
      "\u001b[1m1/1\u001b[0m \u001b[32m━━━━━━━━━━━━━━━━━━━━\u001b[0m\u001b[37m\u001b[0m \u001b[1m0s\u001b[0m 44ms/step\n",
      "\u001b[1m1/1\u001b[0m \u001b[32m━━━━━━━━━━━━━━━━━━━━\u001b[0m\u001b[37m\u001b[0m \u001b[1m0s\u001b[0m 53ms/step\n",
      "\u001b[1m1/1\u001b[0m \u001b[32m━━━━━━━━━━━━━━━━━━━━\u001b[0m\u001b[37m\u001b[0m \u001b[1m0s\u001b[0m 69ms/step\n",
      "\u001b[1m1/1\u001b[0m \u001b[32m━━━━━━━━━━━━━━━━━━━━\u001b[0m\u001b[37m\u001b[0m \u001b[1m0s\u001b[0m 53ms/step\n",
      "\u001b[1m1/1\u001b[0m \u001b[32m━━━━━━━━━━━━━━━━━━━━\u001b[0m\u001b[37m\u001b[0m \u001b[1m0s\u001b[0m 68ms/step\n",
      "\u001b[1m1/1\u001b[0m \u001b[32m━━━━━━━━━━━━━━━━━━━━\u001b[0m\u001b[37m\u001b[0m \u001b[1m0s\u001b[0m 68ms/step\n",
      "\u001b[1m1/1\u001b[0m \u001b[32m━━━━━━━━━━━━━━━━━━━━\u001b[0m\u001b[37m\u001b[0m \u001b[1m0s\u001b[0m 64ms/step\n",
      "\u001b[1m1/1\u001b[0m \u001b[32m━━━━━━━━━━━━━━━━━━━━\u001b[0m\u001b[37m\u001b[0m \u001b[1m0s\u001b[0m 68ms/step\n",
      "\u001b[1m1/1\u001b[0m \u001b[32m━━━━━━━━━━━━━━━━━━━━\u001b[0m\u001b[37m\u001b[0m \u001b[1m0s\u001b[0m 69ms/step\n",
      "\u001b[1m1/1\u001b[0m \u001b[32m━━━━━━━━━━━━━━━━━━━━\u001b[0m\u001b[37m\u001b[0m \u001b[1m0s\u001b[0m 64ms/step\n",
      "\u001b[1m1/1\u001b[0m \u001b[32m━━━━━━━━━━━━━━━━━━━━\u001b[0m\u001b[37m\u001b[0m \u001b[1m0s\u001b[0m 55ms/step\n",
      "\u001b[1m1/1\u001b[0m \u001b[32m━━━━━━━━━━━━━━━━━━━━\u001b[0m\u001b[37m\u001b[0m \u001b[1m0s\u001b[0m 65ms/step\n",
      "\u001b[1m1/1\u001b[0m \u001b[32m━━━━━━━━━━━━━━━━━━━━\u001b[0m\u001b[37m\u001b[0m \u001b[1m0s\u001b[0m 62ms/step\n",
      "\u001b[1m1/1\u001b[0m \u001b[32m━━━━━━━━━━━━━━━━━━━━\u001b[0m\u001b[37m\u001b[0m \u001b[1m0s\u001b[0m 67ms/step\n",
      "\u001b[1m1/1\u001b[0m \u001b[32m━━━━━━━━━━━━━━━━━━━━\u001b[0m\u001b[37m\u001b[0m \u001b[1m0s\u001b[0m 68ms/step\n",
      "\u001b[1m1/1\u001b[0m \u001b[32m━━━━━━━━━━━━━━━━━━━━\u001b[0m\u001b[37m\u001b[0m \u001b[1m0s\u001b[0m 68ms/step\n",
      "\u001b[1m1/1\u001b[0m \u001b[32m━━━━━━━━━━━━━━━━━━━━\u001b[0m\u001b[37m\u001b[0m \u001b[1m0s\u001b[0m 64ms/step\n",
      "\u001b[1m1/1\u001b[0m \u001b[32m━━━━━━━━━━━━━━━━━━━━\u001b[0m\u001b[37m\u001b[0m \u001b[1m0s\u001b[0m 65ms/step\n",
      "\u001b[1m1/1\u001b[0m \u001b[32m━━━━━━━━━━━━━━━━━━━━\u001b[0m\u001b[37m\u001b[0m \u001b[1m0s\u001b[0m 64ms/step\n",
      "\u001b[1m1/1\u001b[0m \u001b[32m━━━━━━━━━━━━━━━━━━━━\u001b[0m\u001b[37m\u001b[0m \u001b[1m0s\u001b[0m 54ms/step\n",
      "\u001b[1m1/1\u001b[0m \u001b[32m━━━━━━━━━━━━━━━━━━━━\u001b[0m\u001b[37m\u001b[0m \u001b[1m0s\u001b[0m 65ms/step\n",
      "\u001b[1m1/1\u001b[0m \u001b[32m━━━━━━━━━━━━━━━━━━━━\u001b[0m\u001b[37m\u001b[0m \u001b[1m0s\u001b[0m 59ms/step\n",
      "\u001b[1m1/1\u001b[0m \u001b[32m━━━━━━━━━━━━━━━━━━━━\u001b[0m\u001b[37m\u001b[0m \u001b[1m0s\u001b[0m 67ms/step\n",
      "\u001b[1m1/1\u001b[0m \u001b[32m━━━━━━━━━━━━━━━━━━━━\u001b[0m\u001b[37m\u001b[0m \u001b[1m0s\u001b[0m 65ms/step\n",
      "\u001b[1m1/1\u001b[0m \u001b[32m━━━━━━━━━━━━━━━━━━━━\u001b[0m\u001b[37m\u001b[0m \u001b[1m0s\u001b[0m 59ms/step\n",
      "\u001b[1m1/1\u001b[0m \u001b[32m━━━━━━━━━━━━━━━━━━━━\u001b[0m\u001b[37m\u001b[0m \u001b[1m0s\u001b[0m 63ms/step\n",
      "\u001b[1m1/1\u001b[0m \u001b[32m━━━━━━━━━━━━━━━━━━━━\u001b[0m\u001b[37m\u001b[0m \u001b[1m0s\u001b[0m 64ms/step\n",
      "\u001b[1m1/1\u001b[0m \u001b[32m━━━━━━━━━━━━━━━━━━━━\u001b[0m\u001b[37m\u001b[0m \u001b[1m0s\u001b[0m 59ms/step\n",
      "\u001b[1m1/1\u001b[0m \u001b[32m━━━━━━━━━━━━━━━━━━━━\u001b[0m\u001b[37m\u001b[0m \u001b[1m0s\u001b[0m 55ms/step\n",
      "\u001b[1m1/1\u001b[0m \u001b[32m━━━━━━━━━━━━━━━━━━━━\u001b[0m\u001b[37m\u001b[0m \u001b[1m0s\u001b[0m 54ms/step\n",
      "\u001b[1m1/1\u001b[0m \u001b[32m━━━━━━━━━━━━━━━━━━━━\u001b[0m\u001b[37m\u001b[0m \u001b[1m0s\u001b[0m 57ms/step\n",
      "\u001b[1m1/1\u001b[0m \u001b[32m━━━━━━━━━━━━━━━━━━━━\u001b[0m\u001b[37m\u001b[0m \u001b[1m0s\u001b[0m 67ms/step\n",
      "\u001b[1m1/1\u001b[0m \u001b[32m━━━━━━━━━━━━━━━━━━━━\u001b[0m\u001b[37m\u001b[0m \u001b[1m0s\u001b[0m 66ms/step\n",
      "\u001b[1m1/1\u001b[0m \u001b[32m━━━━━━━━━━━━━━━━━━━━\u001b[0m\u001b[37m\u001b[0m \u001b[1m0s\u001b[0m 69ms/step\n",
      "\u001b[1m1/1\u001b[0m \u001b[32m━━━━━━━━━━━━━━━━━━━━\u001b[0m\u001b[37m\u001b[0m \u001b[1m0s\u001b[0m 63ms/step\n",
      "\u001b[1m1/1\u001b[0m \u001b[32m━━━━━━━━━━━━━━━━━━━━\u001b[0m\u001b[37m\u001b[0m \u001b[1m0s\u001b[0m 66ms/step\n",
      "\u001b[1m1/1\u001b[0m \u001b[32m━━━━━━━━━━━━━━━━━━━━\u001b[0m\u001b[37m\u001b[0m \u001b[1m0s\u001b[0m 79ms/step\n",
      "\u001b[1m1/1\u001b[0m \u001b[32m━━━━━━━━━━━━━━━━━━━━\u001b[0m\u001b[37m\u001b[0m \u001b[1m0s\u001b[0m 67ms/step\n",
      "\u001b[1m1/1\u001b[0m \u001b[32m━━━━━━━━━━━━━━━━━━━━\u001b[0m\u001b[37m\u001b[0m \u001b[1m0s\u001b[0m 58ms/step\n",
      "\u001b[1m1/1\u001b[0m \u001b[32m━━━━━━━━━━━━━━━━━━━━\u001b[0m\u001b[37m\u001b[0m \u001b[1m0s\u001b[0m 60ms/step\n",
      "\u001b[1m1/1\u001b[0m \u001b[32m━━━━━━━━━━━━━━━━━━━━\u001b[0m\u001b[37m\u001b[0m \u001b[1m0s\u001b[0m 58ms/step\n",
      "\u001b[1m1/1\u001b[0m \u001b[32m━━━━━━━━━━━━━━━━━━━━\u001b[0m\u001b[37m\u001b[0m \u001b[1m0s\u001b[0m 68ms/step\n",
      "\u001b[1m1/1\u001b[0m \u001b[32m━━━━━━━━━━━━━━━━━━━━\u001b[0m\u001b[37m\u001b[0m \u001b[1m0s\u001b[0m 73ms/step\n",
      "\u001b[1m1/1\u001b[0m \u001b[32m━━━━━━━━━━━━━━━━━━━━\u001b[0m\u001b[37m\u001b[0m \u001b[1m0s\u001b[0m 66ms/step\n",
      "\u001b[1m1/1\u001b[0m \u001b[32m━━━━━━━━━━━━━━━━━━━━\u001b[0m\u001b[37m\u001b[0m \u001b[1m0s\u001b[0m 70ms/step\n",
      "\u001b[1m1/1\u001b[0m \u001b[32m━━━━━━━━━━━━━━━━━━━━\u001b[0m\u001b[37m\u001b[0m \u001b[1m0s\u001b[0m 70ms/step\n",
      "\u001b[1m1/1\u001b[0m \u001b[32m━━━━━━━━━━━━━━━━━━━━\u001b[0m\u001b[37m\u001b[0m \u001b[1m0s\u001b[0m 74ms/step\n",
      "\u001b[1m1/1\u001b[0m \u001b[32m━━━━━━━━━━━━━━━━━━━━\u001b[0m\u001b[37m\u001b[0m \u001b[1m0s\u001b[0m 66ms/step\n",
      "\u001b[1m1/1\u001b[0m \u001b[32m━━━━━━━━━━━━━━━━━━━━\u001b[0m\u001b[37m\u001b[0m \u001b[1m0s\u001b[0m 58ms/step\n",
      "\u001b[1m1/1\u001b[0m \u001b[32m━━━━━━━━━━━━━━━━━━━━\u001b[0m\u001b[37m\u001b[0m \u001b[1m0s\u001b[0m 60ms/step\n",
      "\u001b[1m1/1\u001b[0m \u001b[32m━━━━━━━━━━━━━━━━━━━━\u001b[0m\u001b[37m\u001b[0m \u001b[1m0s\u001b[0m 46ms/step\n",
      "\u001b[1m1/1\u001b[0m \u001b[32m━━━━━━━━━━━━━━━━━━━━\u001b[0m\u001b[37m\u001b[0m \u001b[1m0s\u001b[0m 58ms/step\n",
      "\u001b[1m1/1\u001b[0m \u001b[32m━━━━━━━━━━━━━━━━━━━━\u001b[0m\u001b[37m\u001b[0m \u001b[1m0s\u001b[0m 53ms/step\n",
      "\u001b[1m1/1\u001b[0m \u001b[32m━━━━━━━━━━━━━━━━━━━━\u001b[0m\u001b[37m\u001b[0m \u001b[1m0s\u001b[0m 54ms/step\n",
      "\u001b[1m1/1\u001b[0m \u001b[32m━━━━━━━━━━━━━━━━━━━━\u001b[0m\u001b[37m\u001b[0m \u001b[1m0s\u001b[0m 52ms/step\n",
      "\u001b[1m1/1\u001b[0m \u001b[32m━━━━━━━━━━━━━━━━━━━━\u001b[0m\u001b[37m\u001b[0m \u001b[1m0s\u001b[0m 66ms/step\n",
      "\u001b[1m1/1\u001b[0m \u001b[32m━━━━━━━━━━━━━━━━━━━━\u001b[0m\u001b[37m\u001b[0m \u001b[1m0s\u001b[0m 56ms/step\n",
      "\u001b[1m1/1\u001b[0m \u001b[32m━━━━━━━━━━━━━━━━━━━━\u001b[0m\u001b[37m\u001b[0m \u001b[1m0s\u001b[0m 76ms/step\n",
      "\u001b[1m1/1\u001b[0m \u001b[32m━━━━━━━━━━━━━━━━━━━━\u001b[0m\u001b[37m\u001b[0m \u001b[1m0s\u001b[0m 61ms/step\n",
      "\u001b[1m1/1\u001b[0m \u001b[32m━━━━━━━━━━━━━━━━━━━━\u001b[0m\u001b[37m\u001b[0m \u001b[1m0s\u001b[0m 54ms/step\n",
      "\u001b[1m1/1\u001b[0m \u001b[32m━━━━━━━━━━━━━━━━━━━━\u001b[0m\u001b[37m\u001b[0m \u001b[1m0s\u001b[0m 67ms/step\n",
      "\u001b[1m1/1\u001b[0m \u001b[32m━━━━━━━━━━━━━━━━━━━━\u001b[0m\u001b[37m\u001b[0m \u001b[1m0s\u001b[0m 64ms/step\n",
      "\u001b[1m1/1\u001b[0m \u001b[32m━━━━━━━━━━━━━━━━━━━━\u001b[0m\u001b[37m\u001b[0m \u001b[1m0s\u001b[0m 66ms/step\n",
      "\u001b[1m1/1\u001b[0m \u001b[32m━━━━━━━━━━━━━━━━━━━━\u001b[0m\u001b[37m\u001b[0m \u001b[1m0s\u001b[0m 56ms/step\n",
      "\u001b[1m1/1\u001b[0m \u001b[32m━━━━━━━━━━━━━━━━━━━━\u001b[0m\u001b[37m\u001b[0m \u001b[1m0s\u001b[0m 59ms/step\n",
      "\u001b[1m1/1\u001b[0m \u001b[32m━━━━━━━━━━━━━━━━━━━━\u001b[0m\u001b[37m\u001b[0m \u001b[1m0s\u001b[0m 68ms/step\n",
      "\u001b[1m1/1\u001b[0m \u001b[32m━━━━━━━━━━━━━━━━━━━━\u001b[0m\u001b[37m\u001b[0m \u001b[1m0s\u001b[0m 68ms/step\n",
      "\u001b[1m1/1\u001b[0m \u001b[32m━━━━━━━━━━━━━━━━━━━━\u001b[0m\u001b[37m\u001b[0m \u001b[1m0s\u001b[0m 64ms/step\n",
      "\u001b[1m1/1\u001b[0m \u001b[32m━━━━━━━━━━━━━━━━━━━━\u001b[0m\u001b[37m\u001b[0m \u001b[1m0s\u001b[0m 62ms/step\n",
      "\u001b[1m1/1\u001b[0m \u001b[32m━━━━━━━━━━━━━━━━━━━━\u001b[0m\u001b[37m\u001b[0m \u001b[1m0s\u001b[0m 62ms/step\n",
      "\u001b[1m1/1\u001b[0m \u001b[32m━━━━━━━━━━━━━━━━━━━━\u001b[0m\u001b[37m\u001b[0m \u001b[1m0s\u001b[0m 64ms/step\n",
      "\u001b[1m1/1\u001b[0m \u001b[32m━━━━━━━━━━━━━━━━━━━━\u001b[0m\u001b[37m\u001b[0m \u001b[1m0s\u001b[0m 60ms/step\n",
      "\u001b[1m1/1\u001b[0m \u001b[32m━━━━━━━━━━━━━━━━━━━━\u001b[0m\u001b[37m\u001b[0m \u001b[1m0s\u001b[0m 67ms/step\n",
      "\u001b[1m1/1\u001b[0m \u001b[32m━━━━━━━━━━━━━━━━━━━━\u001b[0m\u001b[37m\u001b[0m \u001b[1m0s\u001b[0m 62ms/step\n",
      "\u001b[1m1/1\u001b[0m \u001b[32m━━━━━━━━━━━━━━━━━━━━\u001b[0m\u001b[37m\u001b[0m \u001b[1m0s\u001b[0m 62ms/step\n",
      "\u001b[1m1/1\u001b[0m \u001b[32m━━━━━━━━━━━━━━━━━━━━\u001b[0m\u001b[37m\u001b[0m \u001b[1m0s\u001b[0m 62ms/step\n",
      "\u001b[1m1/1\u001b[0m \u001b[32m━━━━━━━━━━━━━━━━━━━━\u001b[0m\u001b[37m\u001b[0m \u001b[1m0s\u001b[0m 67ms/step\n",
      "\u001b[1m1/1\u001b[0m \u001b[32m━━━━━━━━━━━━━━━━━━━━\u001b[0m\u001b[37m\u001b[0m \u001b[1m0s\u001b[0m 70ms/step\n",
      "\u001b[1m1/1\u001b[0m \u001b[32m━━━━━━━━━━━━━━━━━━━━\u001b[0m\u001b[37m\u001b[0m \u001b[1m0s\u001b[0m 69ms/step\n",
      "\u001b[1m1/1\u001b[0m \u001b[32m━━━━━━━━━━━━━━━━━━━━\u001b[0m\u001b[37m\u001b[0m \u001b[1m0s\u001b[0m 67ms/step\n",
      "\u001b[1m1/1\u001b[0m \u001b[32m━━━━━━━━━━━━━━━━━━━━\u001b[0m\u001b[37m\u001b[0m \u001b[1m0s\u001b[0m 65ms/step\n",
      "\u001b[1m1/1\u001b[0m \u001b[32m━━━━━━━━━━━━━━━━━━━━\u001b[0m\u001b[37m\u001b[0m \u001b[1m0s\u001b[0m 74ms/step\n",
      "\u001b[1m1/1\u001b[0m \u001b[32m━━━━━━━━━━━━━━━━━━━━\u001b[0m\u001b[37m\u001b[0m \u001b[1m0s\u001b[0m 72ms/step\n",
      "\u001b[1m1/1\u001b[0m \u001b[32m━━━━━━━━━━━━━━━━━━━━\u001b[0m\u001b[37m\u001b[0m \u001b[1m0s\u001b[0m 66ms/step\n",
      "\u001b[1m1/1\u001b[0m \u001b[32m━━━━━━━━━━━━━━━━━━━━\u001b[0m\u001b[37m\u001b[0m \u001b[1m0s\u001b[0m 77ms/step\n",
      "\u001b[1m1/1\u001b[0m \u001b[32m━━━━━━━━━━━━━━━━━━━━\u001b[0m\u001b[37m\u001b[0m \u001b[1m0s\u001b[0m 56ms/step\n",
      "\u001b[1m1/1\u001b[0m \u001b[32m━━━━━━━━━━━━━━━━━━━━\u001b[0m\u001b[37m\u001b[0m \u001b[1m0s\u001b[0m 56ms/step\n",
      "\u001b[1m1/1\u001b[0m \u001b[32m━━━━━━━━━━━━━━━━━━━━\u001b[0m\u001b[37m\u001b[0m \u001b[1m0s\u001b[0m 65ms/step\n",
      "\u001b[1m1/1\u001b[0m \u001b[32m━━━━━━━━━━━━━━━━━━━━\u001b[0m\u001b[37m\u001b[0m \u001b[1m0s\u001b[0m 63ms/step\n",
      "\u001b[1m1/1\u001b[0m \u001b[32m━━━━━━━━━━━━━━━━━━━━\u001b[0m\u001b[37m\u001b[0m \u001b[1m0s\u001b[0m 69ms/step\n",
      "\u001b[1m1/1\u001b[0m \u001b[32m━━━━━━━━━━━━━━━━━━━━\u001b[0m\u001b[37m\u001b[0m \u001b[1m0s\u001b[0m 71ms/step\n",
      "\u001b[1m1/1\u001b[0m \u001b[32m━━━━━━━━━━━━━━━━━━━━\u001b[0m\u001b[37m\u001b[0m \u001b[1m0s\u001b[0m 56ms/step\n",
      "\u001b[1m1/1\u001b[0m \u001b[32m━━━━━━━━━━━━━━━━━━━━\u001b[0m\u001b[37m\u001b[0m \u001b[1m0s\u001b[0m 55ms/step\n",
      "\u001b[1m1/1\u001b[0m \u001b[32m━━━━━━━━━━━━━━━━━━━━\u001b[0m\u001b[37m\u001b[0m \u001b[1m0s\u001b[0m 70ms/step\n",
      "\u001b[1m1/1\u001b[0m \u001b[32m━━━━━━━━━━━━━━━━━━━━\u001b[0m\u001b[37m\u001b[0m \u001b[1m0s\u001b[0m 71ms/step\n",
      "\u001b[1m1/1\u001b[0m \u001b[32m━━━━━━━━━━━━━━━━━━━━\u001b[0m\u001b[37m\u001b[0m \u001b[1m0s\u001b[0m 56ms/step\n",
      "\u001b[1m1/1\u001b[0m \u001b[32m━━━━━━━━━━━━━━━━━━━━\u001b[0m\u001b[37m\u001b[0m \u001b[1m0s\u001b[0m 57ms/step\n",
      "\u001b[1m1/1\u001b[0m \u001b[32m━━━━━━━━━━━━━━━━━━━━\u001b[0m\u001b[37m\u001b[0m \u001b[1m0s\u001b[0m 58ms/step\n",
      "\u001b[1m1/1\u001b[0m \u001b[32m━━━━━━━━━━━━━━━━━━━━\u001b[0m\u001b[37m\u001b[0m \u001b[1m0s\u001b[0m 55ms/step\n",
      "\u001b[1m1/1\u001b[0m \u001b[32m━━━━━━━━━━━━━━━━━━━━\u001b[0m\u001b[37m\u001b[0m \u001b[1m0s\u001b[0m 54ms/step\n",
      "\u001b[1m1/1\u001b[0m \u001b[32m━━━━━━━━━━━━━━━━━━━━\u001b[0m\u001b[37m\u001b[0m \u001b[1m0s\u001b[0m 54ms/step\n",
      "\u001b[1m1/1\u001b[0m \u001b[32m━━━━━━━━━━━━━━━━━━━━\u001b[0m\u001b[37m\u001b[0m \u001b[1m0s\u001b[0m 65ms/step\n",
      "\u001b[1m1/1\u001b[0m \u001b[32m━━━━━━━━━━━━━━━━━━━━\u001b[0m\u001b[37m\u001b[0m \u001b[1m0s\u001b[0m 53ms/step\n",
      "\u001b[1m1/1\u001b[0m \u001b[32m━━━━━━━━━━━━━━━━━━━━\u001b[0m\u001b[37m\u001b[0m \u001b[1m0s\u001b[0m 57ms/step\n",
      "\u001b[1m1/1\u001b[0m \u001b[32m━━━━━━━━━━━━━━━━━━━━\u001b[0m\u001b[37m\u001b[0m \u001b[1m0s\u001b[0m 45ms/step\n",
      "\u001b[1m1/1\u001b[0m \u001b[32m━━━━━━━━━━━━━━━━━━━━\u001b[0m\u001b[37m\u001b[0m \u001b[1m0s\u001b[0m 53ms/step\n",
      "\u001b[1m1/1\u001b[0m \u001b[32m━━━━━━━━━━━━━━━━━━━━\u001b[0m\u001b[37m\u001b[0m \u001b[1m0s\u001b[0m 53ms/step\n",
      "\u001b[1m1/1\u001b[0m \u001b[32m━━━━━━━━━━━━━━━━━━━━\u001b[0m\u001b[37m\u001b[0m \u001b[1m0s\u001b[0m 49ms/step\n",
      "\u001b[1m1/1\u001b[0m \u001b[32m━━━━━━━━━━━━━━━━━━━━\u001b[0m\u001b[37m\u001b[0m \u001b[1m0s\u001b[0m 54ms/step\n",
      "\u001b[1m1/1\u001b[0m \u001b[32m━━━━━━━━━━━━━━━━━━━━\u001b[0m\u001b[37m\u001b[0m \u001b[1m0s\u001b[0m 72ms/step\n",
      "\u001b[1m1/1\u001b[0m \u001b[32m━━━━━━━━━━━━━━━━━━━━\u001b[0m\u001b[37m\u001b[0m \u001b[1m0s\u001b[0m 70ms/step\n",
      "\u001b[1m1/1\u001b[0m \u001b[32m━━━━━━━━━━━━━━━━━━━━\u001b[0m\u001b[37m\u001b[0m \u001b[1m0s\u001b[0m 56ms/step\n",
      "\u001b[1m1/1\u001b[0m \u001b[32m━━━━━━━━━━━━━━━━━━━━\u001b[0m\u001b[37m\u001b[0m \u001b[1m0s\u001b[0m 58ms/step\n",
      "\u001b[1m1/1\u001b[0m \u001b[32m━━━━━━━━━━━━━━━━━━━━\u001b[0m\u001b[37m\u001b[0m \u001b[1m0s\u001b[0m 78ms/step\n",
      "\u001b[1m1/1\u001b[0m \u001b[32m━━━━━━━━━━━━━━━━━━━━\u001b[0m\u001b[37m\u001b[0m \u001b[1m0s\u001b[0m 69ms/step\n",
      "\u001b[1m1/1\u001b[0m \u001b[32m━━━━━━━━━━━━━━━━━━━━\u001b[0m\u001b[37m\u001b[0m \u001b[1m0s\u001b[0m 62ms/step\n",
      "\u001b[1m1/1\u001b[0m \u001b[32m━━━━━━━━━━━━━━━━━━━━\u001b[0m\u001b[37m\u001b[0m \u001b[1m0s\u001b[0m 48ms/step\n",
      "\u001b[1m1/1\u001b[0m \u001b[32m━━━━━━━━━━━━━━━━━━━━\u001b[0m\u001b[37m\u001b[0m \u001b[1m0s\u001b[0m 47ms/step\n",
      "\u001b[1m1/1\u001b[0m \u001b[32m━━━━━━━━━━━━━━━━━━━━\u001b[0m\u001b[37m\u001b[0m \u001b[1m0s\u001b[0m 66ms/step\n",
      "\u001b[1m1/1\u001b[0m \u001b[32m━━━━━━━━━━━━━━━━━━━━\u001b[0m\u001b[37m\u001b[0m \u001b[1m0s\u001b[0m 65ms/step\n",
      "\u001b[1m1/1\u001b[0m \u001b[32m━━━━━━━━━━━━━━━━━━━━\u001b[0m\u001b[37m\u001b[0m \u001b[1m0s\u001b[0m 66ms/step\n",
      "\u001b[1m1/1\u001b[0m \u001b[32m━━━━━━━━━━━━━━━━━━━━\u001b[0m\u001b[37m\u001b[0m \u001b[1m0s\u001b[0m 55ms/step\n",
      "\u001b[1m1/1\u001b[0m \u001b[32m━━━━━━━━━━━━━━━━━━━━\u001b[0m\u001b[37m\u001b[0m \u001b[1m0s\u001b[0m 53ms/step\n",
      "\u001b[1m1/1\u001b[0m \u001b[32m━━━━━━━━━━━━━━━━━━━━\u001b[0m\u001b[37m\u001b[0m \u001b[1m0s\u001b[0m 73ms/step\n",
      "\u001b[1m1/1\u001b[0m \u001b[32m━━━━━━━━━━━━━━━━━━━━\u001b[0m\u001b[37m\u001b[0m \u001b[1m0s\u001b[0m 62ms/step\n",
      "\u001b[1m1/1\u001b[0m \u001b[32m━━━━━━━━━━━━━━━━━━━━\u001b[0m\u001b[37m\u001b[0m \u001b[1m0s\u001b[0m 52ms/step\n",
      "\u001b[1m1/1\u001b[0m \u001b[32m━━━━━━━━━━━━━━━━━━━━\u001b[0m\u001b[37m\u001b[0m \u001b[1m0s\u001b[0m 62ms/step\n",
      "\u001b[1m1/1\u001b[0m \u001b[32m━━━━━━━━━━━━━━━━━━━━\u001b[0m\u001b[37m\u001b[0m \u001b[1m0s\u001b[0m 64ms/step\n",
      "\u001b[1m1/1\u001b[0m \u001b[32m━━━━━━━━━━━━━━━━━━━━\u001b[0m\u001b[37m\u001b[0m \u001b[1m0s\u001b[0m 49ms/step\n",
      "\u001b[1m1/1\u001b[0m \u001b[32m━━━━━━━━━━━━━━━━━━━━\u001b[0m\u001b[37m\u001b[0m \u001b[1m0s\u001b[0m 58ms/step\n",
      "\u001b[1m1/1\u001b[0m \u001b[32m━━━━━━━━━━━━━━━━━━━━\u001b[0m\u001b[37m\u001b[0m \u001b[1m0s\u001b[0m 62ms/step\n",
      "\u001b[1m1/1\u001b[0m \u001b[32m━━━━━━━━━━━━━━━━━━━━\u001b[0m\u001b[37m\u001b[0m \u001b[1m0s\u001b[0m 65ms/step\n",
      "\u001b[1m1/1\u001b[0m \u001b[32m━━━━━━━━━━━━━━━━━━━━\u001b[0m\u001b[37m\u001b[0m \u001b[1m0s\u001b[0m 67ms/step\n",
      "\u001b[1m1/1\u001b[0m \u001b[32m━━━━━━━━━━━━━━━━━━━━\u001b[0m\u001b[37m\u001b[0m \u001b[1m0s\u001b[0m 62ms/step\n",
      "\u001b[1m1/1\u001b[0m \u001b[32m━━━━━━━━━━━━━━━━━━━━\u001b[0m\u001b[37m\u001b[0m \u001b[1m0s\u001b[0m 47ms/step\n",
      "\u001b[1m1/1\u001b[0m \u001b[32m━━━━━━━━━━━━━━━━━━━━\u001b[0m\u001b[37m\u001b[0m \u001b[1m0s\u001b[0m 67ms/step\n",
      "\u001b[1m1/1\u001b[0m \u001b[32m━━━━━━━━━━━━━━━━━━━━\u001b[0m\u001b[37m\u001b[0m \u001b[1m0s\u001b[0m 64ms/step\n",
      "\u001b[1m1/1\u001b[0m \u001b[32m━━━━━━━━━━━━━━━━━━━━\u001b[0m\u001b[37m\u001b[0m \u001b[1m0s\u001b[0m 57ms/step\n",
      "\u001b[1m1/1\u001b[0m \u001b[32m━━━━━━━━━━━━━━━━━━━━\u001b[0m\u001b[37m\u001b[0m \u001b[1m0s\u001b[0m 47ms/step\n",
      "\u001b[1m1/1\u001b[0m \u001b[32m━━━━━━━━━━━━━━━━━━━━\u001b[0m\u001b[37m\u001b[0m \u001b[1m0s\u001b[0m 84ms/step\n",
      "\u001b[1m1/1\u001b[0m \u001b[32m━━━━━━━━━━━━━━━━━━━━\u001b[0m\u001b[37m\u001b[0m \u001b[1m0s\u001b[0m 70ms/step\n",
      "\u001b[1m1/1\u001b[0m \u001b[32m━━━━━━━━━━━━━━━━━━━━\u001b[0m\u001b[37m\u001b[0m \u001b[1m0s\u001b[0m 63ms/step\n",
      "\u001b[1m1/1\u001b[0m \u001b[32m━━━━━━━━━━━━━━━━━━━━\u001b[0m\u001b[37m\u001b[0m \u001b[1m0s\u001b[0m 60ms/step\n",
      "\u001b[1m1/1\u001b[0m \u001b[32m━━━━━━━━━━━━━━━━━━━━\u001b[0m\u001b[37m\u001b[0m \u001b[1m0s\u001b[0m 62ms/step\n",
      "\u001b[1m1/1\u001b[0m \u001b[32m━━━━━━━━━━━━━━━━━━━━\u001b[0m\u001b[37m\u001b[0m \u001b[1m0s\u001b[0m 48ms/step\n",
      "\u001b[1m1/1\u001b[0m \u001b[32m━━━━━━━━━━━━━━━━━━━━\u001b[0m\u001b[37m\u001b[0m \u001b[1m0s\u001b[0m 65ms/step\n",
      "\u001b[1m1/1\u001b[0m \u001b[32m━━━━━━━━━━━━━━━━━━━━\u001b[0m\u001b[37m\u001b[0m \u001b[1m0s\u001b[0m 49ms/step\n",
      "\u001b[1m1/1\u001b[0m \u001b[32m━━━━━━━━━━━━━━━━━━━━\u001b[0m\u001b[37m\u001b[0m \u001b[1m0s\u001b[0m 53ms/step\n",
      "\u001b[1m1/1\u001b[0m \u001b[32m━━━━━━━━━━━━━━━━━━━━\u001b[0m\u001b[37m\u001b[0m \u001b[1m0s\u001b[0m 64ms/step\n",
      "\u001b[1m1/1\u001b[0m \u001b[32m━━━━━━━━━━━━━━━━━━━━\u001b[0m\u001b[37m\u001b[0m \u001b[1m0s\u001b[0m 62ms/step\n",
      "\u001b[1m1/1\u001b[0m \u001b[32m━━━━━━━━━━━━━━━━━━━━\u001b[0m\u001b[37m\u001b[0m \u001b[1m0s\u001b[0m 57ms/step\n",
      "\u001b[1m1/1\u001b[0m \u001b[32m━━━━━━━━━━━━━━━━━━━━\u001b[0m\u001b[37m\u001b[0m \u001b[1m0s\u001b[0m 62ms/step\n",
      "\u001b[1m1/1\u001b[0m \u001b[32m━━━━━━━━━━━━━━━━━━━━\u001b[0m\u001b[37m\u001b[0m \u001b[1m0s\u001b[0m 65ms/step\n",
      "\u001b[1m1/1\u001b[0m \u001b[32m━━━━━━━━━━━━━━━━━━━━\u001b[0m\u001b[37m\u001b[0m \u001b[1m0s\u001b[0m 64ms/step\n",
      "\u001b[1m1/1\u001b[0m \u001b[32m━━━━━━━━━━━━━━━━━━━━\u001b[0m\u001b[37m\u001b[0m \u001b[1m0s\u001b[0m 62ms/step\n",
      "\u001b[1m1/1\u001b[0m \u001b[32m━━━━━━━━━━━━━━━━━━━━\u001b[0m\u001b[37m\u001b[0m \u001b[1m0s\u001b[0m 63ms/step\n",
      "\u001b[1m1/1\u001b[0m \u001b[32m━━━━━━━━━━━━━━━━━━━━\u001b[0m\u001b[37m\u001b[0m \u001b[1m0s\u001b[0m 62ms/step\n",
      "\u001b[1m1/1\u001b[0m \u001b[32m━━━━━━━━━━━━━━━━━━━━\u001b[0m\u001b[37m\u001b[0m \u001b[1m0s\u001b[0m 67ms/step\n",
      "\u001b[1m1/1\u001b[0m \u001b[32m━━━━━━━━━━━━━━━━━━━━\u001b[0m\u001b[37m\u001b[0m \u001b[1m0s\u001b[0m 68ms/step\n",
      "\u001b[1m1/1\u001b[0m \u001b[32m━━━━━━━━━━━━━━━━━━━━\u001b[0m\u001b[37m\u001b[0m \u001b[1m0s\u001b[0m 64ms/step\n",
      "\u001b[1m1/1\u001b[0m \u001b[32m━━━━━━━━━━━━━━━━━━━━\u001b[0m\u001b[37m\u001b[0m \u001b[1m0s\u001b[0m 67ms/step\n",
      "\u001b[1m1/1\u001b[0m \u001b[32m━━━━━━━━━━━━━━━━━━━━\u001b[0m\u001b[37m\u001b[0m \u001b[1m0s\u001b[0m 63ms/step\n",
      "\u001b[1m1/1\u001b[0m \u001b[32m━━━━━━━━━━━━━━━━━━━━\u001b[0m\u001b[37m\u001b[0m \u001b[1m0s\u001b[0m 84ms/step\n",
      "\u001b[1m1/1\u001b[0m \u001b[32m━━━━━━━━━━━━━━━━━━━━\u001b[0m\u001b[37m\u001b[0m \u001b[1m0s\u001b[0m 60ms/step\n",
      "\u001b[1m1/1\u001b[0m \u001b[32m━━━━━━━━━━━━━━━━━━━━\u001b[0m\u001b[37m\u001b[0m \u001b[1m0s\u001b[0m 60ms/step\n",
      "\u001b[1m1/1\u001b[0m \u001b[32m━━━━━━━━━━━━━━━━━━━━\u001b[0m\u001b[37m\u001b[0m \u001b[1m0s\u001b[0m 62ms/step\n",
      "\u001b[1m1/1\u001b[0m \u001b[32m━━━━━━━━━━━━━━━━━━━━\u001b[0m\u001b[37m\u001b[0m \u001b[1m0s\u001b[0m 66ms/step\n",
      "\u001b[1m1/1\u001b[0m \u001b[32m━━━━━━━━━━━━━━━━━━━━\u001b[0m\u001b[37m\u001b[0m \u001b[1m0s\u001b[0m 54ms/step\n",
      "\u001b[1m1/1\u001b[0m \u001b[32m━━━━━━━━━━━━━━━━━━━━\u001b[0m\u001b[37m\u001b[0m \u001b[1m0s\u001b[0m 48ms/step\n",
      "\u001b[1m1/1\u001b[0m \u001b[32m━━━━━━━━━━━━━━━━━━━━\u001b[0m\u001b[37m\u001b[0m \u001b[1m0s\u001b[0m 62ms/step\n",
      "\u001b[1m1/1\u001b[0m \u001b[32m━━━━━━━━━━━━━━━━━━━━\u001b[0m\u001b[37m\u001b[0m \u001b[1m0s\u001b[0m 52ms/step\n",
      "\u001b[1m1/1\u001b[0m \u001b[32m━━━━━━━━━━━━━━━━━━━━\u001b[0m\u001b[37m\u001b[0m \u001b[1m0s\u001b[0m 63ms/step\n",
      "\u001b[1m1/1\u001b[0m \u001b[32m━━━━━━━━━━━━━━━━━━━━\u001b[0m\u001b[37m\u001b[0m \u001b[1m0s\u001b[0m 59ms/step\n",
      "\u001b[1m1/1\u001b[0m \u001b[32m━━━━━━━━━━━━━━━━━━━━\u001b[0m\u001b[37m\u001b[0m \u001b[1m0s\u001b[0m 62ms/step\n",
      "\u001b[1m1/1\u001b[0m \u001b[32m━━━━━━━━━━━━━━━━━━━━\u001b[0m\u001b[37m\u001b[0m \u001b[1m0s\u001b[0m 60ms/step\n",
      "\u001b[1m1/1\u001b[0m \u001b[32m━━━━━━━━━━━━━━━━━━━━\u001b[0m\u001b[37m\u001b[0m \u001b[1m0s\u001b[0m 54ms/step\n",
      "\u001b[1m1/1\u001b[0m \u001b[32m━━━━━━━━━━━━━━━━━━━━\u001b[0m\u001b[37m\u001b[0m \u001b[1m0s\u001b[0m 52ms/step\n",
      "\u001b[1m1/1\u001b[0m \u001b[32m━━━━━━━━━━━━━━━━━━━━\u001b[0m\u001b[37m\u001b[0m \u001b[1m0s\u001b[0m 67ms/step\n",
      "\u001b[1m1/1\u001b[0m \u001b[32m━━━━━━━━━━━━━━━━━━━━\u001b[0m\u001b[37m\u001b[0m \u001b[1m0s\u001b[0m 67ms/step\n",
      "\u001b[1m1/1\u001b[0m \u001b[32m━━━━━━━━━━━━━━━━━━━━\u001b[0m\u001b[37m\u001b[0m \u001b[1m0s\u001b[0m 68ms/step\n",
      "\u001b[1m1/1\u001b[0m \u001b[32m━━━━━━━━━━━━━━━━━━━━\u001b[0m\u001b[37m\u001b[0m \u001b[1m0s\u001b[0m 68ms/step\n",
      "\u001b[1m1/1\u001b[0m \u001b[32m━━━━━━━━━━━━━━━━━━━━\u001b[0m\u001b[37m\u001b[0m \u001b[1m0s\u001b[0m 59ms/step\n",
      "\u001b[1m1/1\u001b[0m \u001b[32m━━━━━━━━━━━━━━━━━━━━\u001b[0m\u001b[37m\u001b[0m \u001b[1m0s\u001b[0m 49ms/step\n",
      "\u001b[1m1/1\u001b[0m \u001b[32m━━━━━━━━━━━━━━━━━━━━\u001b[0m\u001b[37m\u001b[0m \u001b[1m0s\u001b[0m 54ms/step\n",
      "\u001b[1m1/1\u001b[0m \u001b[32m━━━━━━━━━━━━━━━━━━━━\u001b[0m\u001b[37m\u001b[0m \u001b[1m0s\u001b[0m 54ms/step\n",
      "\u001b[1m1/1\u001b[0m \u001b[32m━━━━━━━━━━━━━━━━━━━━\u001b[0m\u001b[37m\u001b[0m \u001b[1m0s\u001b[0m 78ms/step\n",
      "\u001b[1m1/1\u001b[0m \u001b[32m━━━━━━━━━━━━━━━━━━━━\u001b[0m\u001b[37m\u001b[0m \u001b[1m0s\u001b[0m 67ms/step\n",
      "\u001b[1m1/1\u001b[0m \u001b[32m━━━━━━━━━━━━━━━━━━━━\u001b[0m\u001b[37m\u001b[0m \u001b[1m0s\u001b[0m 60ms/step\n",
      "\u001b[1m1/1\u001b[0m \u001b[32m━━━━━━━━━━━━━━━━━━━━\u001b[0m\u001b[37m\u001b[0m \u001b[1m0s\u001b[0m 64ms/step\n",
      "\u001b[1m1/1\u001b[0m \u001b[32m━━━━━━━━━━━━━━━━━━━━\u001b[0m\u001b[37m\u001b[0m \u001b[1m0s\u001b[0m 67ms/step\n",
      "\u001b[1m1/1\u001b[0m \u001b[32m━━━━━━━━━━━━━━━━━━━━\u001b[0m\u001b[37m\u001b[0m \u001b[1m0s\u001b[0m 67ms/step\n",
      "\u001b[1m1/1\u001b[0m \u001b[32m━━━━━━━━━━━━━━━━━━━━\u001b[0m\u001b[37m\u001b[0m \u001b[1m0s\u001b[0m 63ms/step\n",
      "\u001b[1m1/1\u001b[0m \u001b[32m━━━━━━━━━━━━━━━━━━━━\u001b[0m\u001b[37m\u001b[0m \u001b[1m0s\u001b[0m 67ms/step\n",
      "\u001b[1m1/1\u001b[0m \u001b[32m━━━━━━━━━━━━━━━━━━━━\u001b[0m\u001b[37m\u001b[0m \u001b[1m0s\u001b[0m 74ms/step\n",
      "\u001b[1m1/1\u001b[0m \u001b[32m━━━━━━━━━━━━━━━━━━━━\u001b[0m\u001b[37m\u001b[0m \u001b[1m0s\u001b[0m 60ms/step\n",
      "\u001b[1m1/1\u001b[0m \u001b[32m━━━━━━━━━━━━━━━━━━━━\u001b[0m\u001b[37m\u001b[0m \u001b[1m0s\u001b[0m 54ms/step\n",
      "\u001b[1m1/1\u001b[0m \u001b[32m━━━━━━━━━━━━━━━━━━━━\u001b[0m\u001b[37m\u001b[0m \u001b[1m0s\u001b[0m 55ms/step\n",
      "\u001b[1m1/1\u001b[0m \u001b[32m━━━━━━━━━━━━━━━━━━━━\u001b[0m\u001b[37m\u001b[0m \u001b[1m0s\u001b[0m 52ms/step\n",
      "\u001b[1m1/1\u001b[0m \u001b[32m━━━━━━━━━━━━━━━━━━━━\u001b[0m\u001b[37m\u001b[0m \u001b[1m0s\u001b[0m 63ms/step\n",
      "\u001b[1m1/1\u001b[0m \u001b[32m━━━━━━━━━━━━━━━━━━━━\u001b[0m\u001b[37m\u001b[0m \u001b[1m0s\u001b[0m 59ms/step\n",
      "\u001b[1m1/1\u001b[0m \u001b[32m━━━━━━━━━━━━━━━━━━━━\u001b[0m\u001b[37m\u001b[0m \u001b[1m0s\u001b[0m 62ms/step\n",
      "\u001b[1m1/1\u001b[0m \u001b[32m━━━━━━━━━━━━━━━━━━━━\u001b[0m\u001b[37m\u001b[0m \u001b[1m0s\u001b[0m 53ms/step\n",
      "\u001b[1m1/1\u001b[0m \u001b[32m━━━━━━━━━━━━━━━━━━━━\u001b[0m\u001b[37m\u001b[0m \u001b[1m0s\u001b[0m 73ms/step\n",
      "\u001b[1m1/1\u001b[0m \u001b[32m━━━━━━━━━━━━━━━━━━━━\u001b[0m\u001b[37m\u001b[0m \u001b[1m0s\u001b[0m 70ms/step\n",
      "\u001b[1m1/1\u001b[0m \u001b[32m━━━━━━━━━━━━━━━━━━━━\u001b[0m\u001b[37m\u001b[0m \u001b[1m0s\u001b[0m 61ms/step\n",
      "\u001b[1m1/1\u001b[0m \u001b[32m━━━━━━━━━━━━━━━━━━━━\u001b[0m\u001b[37m\u001b[0m \u001b[1m0s\u001b[0m 70ms/step\n",
      "\u001b[1m1/1\u001b[0m \u001b[32m━━━━━━━━━━━━━━━━━━━━\u001b[0m\u001b[37m\u001b[0m \u001b[1m0s\u001b[0m 68ms/step\n",
      "\u001b[1m1/1\u001b[0m \u001b[32m━━━━━━━━━━━━━━━━━━━━\u001b[0m\u001b[37m\u001b[0m \u001b[1m0s\u001b[0m 54ms/step\n",
      "\u001b[1m1/1\u001b[0m \u001b[32m━━━━━━━━━━━━━━━━━━━━\u001b[0m\u001b[37m\u001b[0m \u001b[1m0s\u001b[0m 67ms/step\n",
      "\u001b[1m1/1\u001b[0m \u001b[32m━━━━━━━━━━━━━━━━━━━━\u001b[0m\u001b[37m\u001b[0m \u001b[1m0s\u001b[0m 67ms/step\n",
      "\u001b[1m1/1\u001b[0m \u001b[32m━━━━━━━━━━━━━━━━━━━━\u001b[0m\u001b[37m\u001b[0m \u001b[1m0s\u001b[0m 54ms/step\n",
      "\u001b[1m1/1\u001b[0m \u001b[32m━━━━━━━━━━━━━━━━━━━━\u001b[0m\u001b[37m\u001b[0m \u001b[1m0s\u001b[0m 53ms/step\n",
      "\u001b[1m1/1\u001b[0m \u001b[32m━━━━━━━━━━━━━━━━━━━━\u001b[0m\u001b[37m\u001b[0m \u001b[1m0s\u001b[0m 55ms/step\n",
      "\u001b[1m1/1\u001b[0m \u001b[32m━━━━━━━━━━━━━━━━━━━━\u001b[0m\u001b[37m\u001b[0m \u001b[1m0s\u001b[0m 54ms/step\n",
      "\u001b[1m1/1\u001b[0m \u001b[32m━━━━━━━━━━━━━━━━━━━━\u001b[0m\u001b[37m\u001b[0m \u001b[1m0s\u001b[0m 54ms/step\n",
      "\u001b[1m1/1\u001b[0m \u001b[32m━━━━━━━━━━━━━━━━━━━━\u001b[0m\u001b[37m\u001b[0m \u001b[1m0s\u001b[0m 66ms/step\n",
      "\u001b[1m1/1\u001b[0m \u001b[32m━━━━━━━━━━━━━━━━━━━━\u001b[0m\u001b[37m\u001b[0m \u001b[1m0s\u001b[0m 74ms/step\n",
      "\u001b[1m1/1\u001b[0m \u001b[32m━━━━━━━━━━━━━━━━━━━━\u001b[0m\u001b[37m\u001b[0m \u001b[1m0s\u001b[0m 54ms/step\n",
      "\u001b[1m1/1\u001b[0m \u001b[32m━━━━━━━━━━━━━━━━━━━━\u001b[0m\u001b[37m\u001b[0m \u001b[1m0s\u001b[0m 54ms/step\n",
      "\u001b[1m1/1\u001b[0m \u001b[32m━━━━━━━━━━━━━━━━━━━━\u001b[0m\u001b[37m\u001b[0m \u001b[1m0s\u001b[0m 54ms/step\n",
      "\u001b[1m1/1\u001b[0m \u001b[32m━━━━━━━━━━━━━━━━━━━━\u001b[0m\u001b[37m\u001b[0m \u001b[1m0s\u001b[0m 54ms/step\n",
      "\u001b[1m1/1\u001b[0m \u001b[32m━━━━━━━━━━━━━━━━━━━━\u001b[0m\u001b[37m\u001b[0m \u001b[1m0s\u001b[0m 67ms/step\n",
      "\u001b[1m1/1\u001b[0m \u001b[32m━━━━━━━━━━━━━━━━━━━━\u001b[0m\u001b[37m\u001b[0m \u001b[1m0s\u001b[0m 54ms/step\n",
      "\u001b[1m1/1\u001b[0m \u001b[32m━━━━━━━━━━━━━━━━━━━━\u001b[0m\u001b[37m\u001b[0m \u001b[1m0s\u001b[0m 60ms/step\n",
      "\u001b[1m1/1\u001b[0m \u001b[32m━━━━━━━━━━━━━━━━━━━━\u001b[0m\u001b[37m\u001b[0m \u001b[1m0s\u001b[0m 47ms/step\n",
      "\u001b[1m1/1\u001b[0m \u001b[32m━━━━━━━━━━━━━━━━━━━━\u001b[0m\u001b[37m\u001b[0m \u001b[1m0s\u001b[0m 47ms/step\n",
      "\u001b[1m1/1\u001b[0m \u001b[32m━━━━━━━━━━━━━━━━━━━━\u001b[0m\u001b[37m\u001b[0m \u001b[1m0s\u001b[0m 48ms/step\n",
      "\u001b[1m1/1\u001b[0m \u001b[32m━━━━━━━━━━━━━━━━━━━━\u001b[0m\u001b[37m\u001b[0m \u001b[1m0s\u001b[0m 79ms/step\n",
      "\u001b[1m1/1\u001b[0m \u001b[32m━━━━━━━━━━━━━━━━━━━━\u001b[0m\u001b[37m\u001b[0m \u001b[1m0s\u001b[0m 68ms/step\n",
      "\u001b[1m1/1\u001b[0m \u001b[32m━━━━━━━━━━━━━━━━━━━━\u001b[0m\u001b[37m\u001b[0m \u001b[1m0s\u001b[0m 62ms/step\n",
      "\u001b[1m1/1\u001b[0m \u001b[32m━━━━━━━━━━━━━━━━━━━━\u001b[0m\u001b[37m\u001b[0m \u001b[1m0s\u001b[0m 62ms/step\n",
      "\u001b[1m1/1\u001b[0m \u001b[32m━━━━━━━━━━━━━━━━━━━━\u001b[0m\u001b[37m\u001b[0m \u001b[1m0s\u001b[0m 61ms/step\n",
      "\u001b[1m1/1\u001b[0m \u001b[32m━━━━━━━━━━━━━━━━━━━━\u001b[0m\u001b[37m\u001b[0m \u001b[1m0s\u001b[0m 55ms/step\n",
      "\u001b[1m1/1\u001b[0m \u001b[32m━━━━━━━━━━━━━━━━━━━━\u001b[0m\u001b[37m\u001b[0m \u001b[1m0s\u001b[0m 47ms/step\n",
      "\u001b[1m1/1\u001b[0m \u001b[32m━━━━━━━━━━━━━━━━━━━━\u001b[0m\u001b[37m\u001b[0m \u001b[1m0s\u001b[0m 62ms/step\n",
      "\u001b[1m1/1\u001b[0m \u001b[32m━━━━━━━━━━━━━━━━━━━━\u001b[0m\u001b[37m\u001b[0m \u001b[1m0s\u001b[0m 68ms/step\n",
      "\u001b[1m1/1\u001b[0m \u001b[32m━━━━━━━━━━━━━━━━━━━━\u001b[0m\u001b[37m\u001b[0m \u001b[1m0s\u001b[0m 62ms/step\n",
      "\u001b[1m1/1\u001b[0m \u001b[32m━━━━━━━━━━━━━━━━━━━━\u001b[0m\u001b[37m\u001b[0m \u001b[1m0s\u001b[0m 62ms/step\n",
      "\u001b[1m1/1\u001b[0m \u001b[32m━━━━━━━━━━━━━━━━━━━━\u001b[0m\u001b[37m\u001b[0m \u001b[1m0s\u001b[0m 62ms/step\n",
      "\u001b[1m1/1\u001b[0m \u001b[32m━━━━━━━━━━━━━━━━━━━━\u001b[0m\u001b[37m\u001b[0m \u001b[1m0s\u001b[0m 62ms/step\n",
      "\u001b[1m1/1\u001b[0m \u001b[32m━━━━━━━━━━━━━━━━━━━━\u001b[0m\u001b[37m\u001b[0m \u001b[1m0s\u001b[0m 53ms/step\n",
      "\u001b[1m1/1\u001b[0m \u001b[32m━━━━━━━━━━━━━━━━━━━━\u001b[0m\u001b[37m\u001b[0m \u001b[1m0s\u001b[0m 62ms/step\n",
      "\u001b[1m1/1\u001b[0m \u001b[32m━━━━━━━━━━━━━━━━━━━━\u001b[0m\u001b[37m\u001b[0m \u001b[1m0s\u001b[0m 55ms/step\n",
      "\u001b[1m1/1\u001b[0m \u001b[32m━━━━━━━━━━━━━━━━━━━━\u001b[0m\u001b[37m\u001b[0m \u001b[1m0s\u001b[0m 74ms/step\n",
      "\u001b[1m1/1\u001b[0m \u001b[32m━━━━━━━━━━━━━━━━━━━━\u001b[0m\u001b[37m\u001b[0m \u001b[1m0s\u001b[0m 67ms/step\n",
      "\u001b[1m1/1\u001b[0m \u001b[32m━━━━━━━━━━━━━━━━━━━━\u001b[0m\u001b[37m\u001b[0m \u001b[1m0s\u001b[0m 44ms/step\n",
      "\u001b[1m1/1\u001b[0m \u001b[32m━━━━━━━━━━━━━━━━━━━━\u001b[0m\u001b[37m\u001b[0m \u001b[1m0s\u001b[0m 62ms/step\n",
      "\u001b[1m1/1\u001b[0m \u001b[32m━━━━━━━━━━━━━━━━━━━━\u001b[0m\u001b[37m\u001b[0m \u001b[1m0s\u001b[0m 47ms/step\n",
      "\u001b[1m1/1\u001b[0m \u001b[32m━━━━━━━━━━━━━━━━━━━━\u001b[0m\u001b[37m\u001b[0m \u001b[1m0s\u001b[0m 55ms/step\n",
      "\u001b[1m1/1\u001b[0m \u001b[32m━━━━━━━━━━━━━━━━━━━━\u001b[0m\u001b[37m\u001b[0m \u001b[1m0s\u001b[0m 52ms/step\n",
      "\u001b[1m1/1\u001b[0m \u001b[32m━━━━━━━━━━━━━━━━━━━━\u001b[0m\u001b[37m\u001b[0m \u001b[1m0s\u001b[0m 55ms/step\n",
      "\u001b[1m1/1\u001b[0m \u001b[32m━━━━━━━━━━━━━━━━━━━━\u001b[0m\u001b[37m\u001b[0m \u001b[1m0s\u001b[0m 62ms/step\n",
      "\u001b[1m1/1\u001b[0m \u001b[32m━━━━━━━━━━━━━━━━━━━━\u001b[0m\u001b[37m\u001b[0m \u001b[1m0s\u001b[0m 68ms/step\n",
      "\u001b[1m1/1\u001b[0m \u001b[32m━━━━━━━━━━━━━━━━━━━━\u001b[0m\u001b[37m\u001b[0m \u001b[1m0s\u001b[0m 66ms/step\n",
      "\u001b[1m1/1\u001b[0m \u001b[32m━━━━━━━━━━━━━━━━━━━━\u001b[0m\u001b[37m\u001b[0m \u001b[1m0s\u001b[0m 66ms/step\n",
      "\u001b[1m1/1\u001b[0m \u001b[32m━━━━━━━━━━━━━━━━━━━━\u001b[0m\u001b[37m\u001b[0m \u001b[1m0s\u001b[0m 66ms/step\n",
      "\u001b[1m1/1\u001b[0m \u001b[32m━━━━━━━━━━━━━━━━━━━━\u001b[0m\u001b[37m\u001b[0m \u001b[1m0s\u001b[0m 60ms/step\n",
      "\u001b[1m1/1\u001b[0m \u001b[32m━━━━━━━━━━━━━━━━━━━━\u001b[0m\u001b[37m\u001b[0m \u001b[1m0s\u001b[0m 62ms/step\n",
      "\u001b[1m1/1\u001b[0m \u001b[32m━━━━━━━━━━━━━━━━━━━━\u001b[0m\u001b[37m\u001b[0m \u001b[1m0s\u001b[0m 48ms/step\n",
      "\u001b[1m1/1\u001b[0m \u001b[32m━━━━━━━━━━━━━━━━━━━━\u001b[0m\u001b[37m\u001b[0m \u001b[1m0s\u001b[0m 56ms/step\n",
      "\u001b[1m1/1\u001b[0m \u001b[32m━━━━━━━━━━━━━━━━━━━━\u001b[0m\u001b[37m\u001b[0m \u001b[1m0s\u001b[0m 81ms/step\n",
      "\u001b[1m1/1\u001b[0m \u001b[32m━━━━━━━━━━━━━━━━━━━━\u001b[0m\u001b[37m\u001b[0m \u001b[1m0s\u001b[0m 68ms/step\n",
      "\u001b[1m1/1\u001b[0m \u001b[32m━━━━━━━━━━━━━━━━━━━━\u001b[0m\u001b[37m\u001b[0m \u001b[1m0s\u001b[0m 53ms/step\n",
      "\u001b[1m1/1\u001b[0m \u001b[32m━━━━━━━━━━━━━━━━━━━━\u001b[0m\u001b[37m\u001b[0m \u001b[1m0s\u001b[0m 71ms/step\n",
      "\u001b[1m1/1\u001b[0m \u001b[32m━━━━━━━━━━━━━━━━━━━━\u001b[0m\u001b[37m\u001b[0m \u001b[1m0s\u001b[0m 65ms/step\n",
      "\u001b[1m1/1\u001b[0m \u001b[32m━━━━━━━━━━━━━━━━━━━━\u001b[0m\u001b[37m\u001b[0m \u001b[1m0s\u001b[0m 62ms/step\n",
      "\u001b[1m1/1\u001b[0m \u001b[32m━━━━━━━━━━━━━━━━━━━━\u001b[0m\u001b[37m\u001b[0m \u001b[1m0s\u001b[0m 62ms/step\n",
      "\u001b[1m1/1\u001b[0m \u001b[32m━━━━━━━━━━━━━━━━━━━━\u001b[0m\u001b[37m\u001b[0m \u001b[1m0s\u001b[0m 65ms/step\n",
      "\u001b[1m1/1\u001b[0m \u001b[32m━━━━━━━━━━━━━━━━━━━━\u001b[0m\u001b[37m\u001b[0m \u001b[1m0s\u001b[0m 62ms/step\n",
      "\u001b[1m1/1\u001b[0m \u001b[32m━━━━━━━━━━━━━━━━━━━━\u001b[0m\u001b[37m\u001b[0m \u001b[1m0s\u001b[0m 47ms/step\n",
      "\u001b[1m1/1\u001b[0m \u001b[32m━━━━━━━━━━━━━━━━━━━━\u001b[0m\u001b[37m\u001b[0m \u001b[1m0s\u001b[0m 62ms/step\n",
      "\u001b[1m1/1\u001b[0m \u001b[32m━━━━━━━━━━━━━━━━━━━━\u001b[0m\u001b[37m\u001b[0m \u001b[1m0s\u001b[0m 47ms/step\n",
      "\u001b[1m1/1\u001b[0m \u001b[32m━━━━━━━━━━━━━━━━━━━━\u001b[0m\u001b[37m\u001b[0m \u001b[1m0s\u001b[0m 47ms/step\n",
      "\u001b[1m1/1\u001b[0m \u001b[32m━━━━━━━━━━━━━━━━━━━━\u001b[0m\u001b[37m\u001b[0m \u001b[1m0s\u001b[0m 47ms/step\n",
      "\u001b[1m1/1\u001b[0m \u001b[32m━━━━━━━━━━━━━━━━━━━━\u001b[0m\u001b[37m\u001b[0m \u001b[1m0s\u001b[0m 62ms/step\n",
      "\u001b[1m1/1\u001b[0m \u001b[32m━━━━━━━━━━━━━━━━━━━━\u001b[0m\u001b[37m\u001b[0m \u001b[1m0s\u001b[0m 62ms/step\n",
      "\u001b[1m1/1\u001b[0m \u001b[32m━━━━━━━━━━━━━━━━━━━━\u001b[0m\u001b[37m\u001b[0m \u001b[1m0s\u001b[0m 47ms/step\n",
      "\u001b[1m1/1\u001b[0m \u001b[32m━━━━━━━━━━━━━━━━━━━━\u001b[0m\u001b[37m\u001b[0m \u001b[1m0s\u001b[0m 48ms/step\n",
      "\u001b[1m1/1\u001b[0m \u001b[32m━━━━━━━━━━━━━━━━━━━━\u001b[0m\u001b[37m\u001b[0m \u001b[1m0s\u001b[0m 62ms/step\n",
      "\u001b[1m1/1\u001b[0m \u001b[32m━━━━━━━━━━━━━━━━━━━━\u001b[0m\u001b[37m\u001b[0m \u001b[1m0s\u001b[0m 47ms/step\n",
      "\u001b[1m1/1\u001b[0m \u001b[32m━━━━━━━━━━━━━━━━━━━━\u001b[0m\u001b[37m\u001b[0m \u001b[1m0s\u001b[0m 62ms/step\n",
      "\u001b[1m1/1\u001b[0m \u001b[32m━━━━━━━━━━━━━━━━━━━━\u001b[0m\u001b[37m\u001b[0m \u001b[1m0s\u001b[0m 55ms/step\n",
      "\u001b[1m1/1\u001b[0m \u001b[32m━━━━━━━━━━━━━━━━━━━━\u001b[0m\u001b[37m\u001b[0m \u001b[1m0s\u001b[0m 62ms/step\n",
      "\u001b[1m1/1\u001b[0m \u001b[32m━━━━━━━━━━━━━━━━━━━━\u001b[0m\u001b[37m\u001b[0m \u001b[1m0s\u001b[0m 47ms/step\n",
      "\u001b[1m1/1\u001b[0m \u001b[32m━━━━━━━━━━━━━━━━━━━━\u001b[0m\u001b[37m\u001b[0m \u001b[1m0s\u001b[0m 47ms/step\n",
      "\u001b[1m1/1\u001b[0m \u001b[32m━━━━━━━━━━━━━━━━━━━━\u001b[0m\u001b[37m\u001b[0m \u001b[1m0s\u001b[0m 62ms/step\n",
      "\u001b[1m1/1\u001b[0m \u001b[32m━━━━━━━━━━━━━━━━━━━━\u001b[0m\u001b[37m\u001b[0m \u001b[1m0s\u001b[0m 47ms/step\n",
      "\u001b[1m1/1\u001b[0m \u001b[32m━━━━━━━━━━━━━━━━━━━━\u001b[0m\u001b[37m\u001b[0m \u001b[1m0s\u001b[0m 58ms/step\n",
      "\u001b[1m1/1\u001b[0m \u001b[32m━━━━━━━━━━━━━━━━━━━━\u001b[0m\u001b[37m\u001b[0m \u001b[1m0s\u001b[0m 62ms/step\n",
      "\u001b[1m1/1\u001b[0m \u001b[32m━━━━━━━━━━━━━━━━━━━━\u001b[0m\u001b[37m\u001b[0m \u001b[1m0s\u001b[0m 47ms/step\n",
      "\u001b[1m1/1\u001b[0m \u001b[32m━━━━━━━━━━━━━━━━━━━━\u001b[0m\u001b[37m\u001b[0m \u001b[1m0s\u001b[0m 62ms/step\n",
      "\u001b[1m1/1\u001b[0m \u001b[32m━━━━━━━━━━━━━━━━━━━━\u001b[0m\u001b[37m\u001b[0m \u001b[1m0s\u001b[0m 47ms/step\n",
      "\u001b[1m1/1\u001b[0m \u001b[32m━━━━━━━━━━━━━━━━━━━━\u001b[0m\u001b[37m\u001b[0m \u001b[1m0s\u001b[0m 48ms/step\n",
      "\u001b[1m1/1\u001b[0m \u001b[32m━━━━━━━━━━━━━━━━━━━━\u001b[0m\u001b[37m\u001b[0m \u001b[1m0s\u001b[0m 62ms/step\n",
      "\u001b[1m1/1\u001b[0m \u001b[32m━━━━━━━━━━━━━━━━━━━━\u001b[0m\u001b[37m\u001b[0m \u001b[1m0s\u001b[0m 47ms/step\n",
      "\u001b[1m1/1\u001b[0m \u001b[32m━━━━━━━━━━━━━━━━━━━━\u001b[0m\u001b[37m\u001b[0m \u001b[1m0s\u001b[0m 62ms/step\n",
      "\u001b[1m1/1\u001b[0m \u001b[32m━━━━━━━━━━━━━━━━━━━━\u001b[0m\u001b[37m\u001b[0m \u001b[1m0s\u001b[0m 48ms/step\n",
      "\u001b[1m1/1\u001b[0m \u001b[32m━━━━━━━━━━━━━━━━━━━━\u001b[0m\u001b[37m\u001b[0m \u001b[1m0s\u001b[0m 59ms/step\n",
      "\u001b[1m1/1\u001b[0m \u001b[32m━━━━━━━━━━━━━━━━━━━━\u001b[0m\u001b[37m\u001b[0m \u001b[1m0s\u001b[0m 54ms/step\n",
      "\u001b[1m1/1\u001b[0m \u001b[32m━━━━━━━━━━━━━━━━━━━━\u001b[0m\u001b[37m\u001b[0m \u001b[1m0s\u001b[0m 67ms/step\n",
      "\u001b[1m1/1\u001b[0m \u001b[32m━━━━━━━━━━━━━━━━━━━━\u001b[0m\u001b[37m\u001b[0m \u001b[1m0s\u001b[0m 54ms/step\n",
      "\u001b[1m1/1\u001b[0m \u001b[32m━━━━━━━━━━━━━━━━━━━━\u001b[0m\u001b[37m\u001b[0m \u001b[1m0s\u001b[0m 67ms/step\n",
      "\u001b[1m1/1\u001b[0m \u001b[32m━━━━━━━━━━━━━━━━━━━━\u001b[0m\u001b[37m\u001b[0m \u001b[1m0s\u001b[0m 45ms/step\n",
      "\u001b[1m1/1\u001b[0m \u001b[32m━━━━━━━━━━━━━━━━━━━━\u001b[0m\u001b[37m\u001b[0m \u001b[1m0s\u001b[0m 54ms/step\n",
      "\u001b[1m1/1\u001b[0m \u001b[32m━━━━━━━━━━━━━━━━━━━━\u001b[0m\u001b[37m\u001b[0m \u001b[1m0s\u001b[0m 54ms/step\n",
      "\u001b[1m1/1\u001b[0m \u001b[32m━━━━━━━━━━━━━━━━━━━━\u001b[0m\u001b[37m\u001b[0m \u001b[1m0s\u001b[0m 40ms/step\n",
      "\u001b[1m1/1\u001b[0m \u001b[32m━━━━━━━━━━━━━━━━━━━━\u001b[0m\u001b[37m\u001b[0m \u001b[1m0s\u001b[0m 61ms/step\n",
      "\u001b[1m1/1\u001b[0m \u001b[32m━━━━━━━━━━━━━━━━━━━━\u001b[0m\u001b[37m\u001b[0m \u001b[1m0s\u001b[0m 54ms/step\n",
      "\u001b[1m1/1\u001b[0m \u001b[32m━━━━━━━━━━━━━━━━━━━━\u001b[0m\u001b[37m\u001b[0m \u001b[1m0s\u001b[0m 67ms/step\n",
      "\u001b[1m1/1\u001b[0m \u001b[32m━━━━━━━━━━━━━━━━━━━━\u001b[0m\u001b[37m\u001b[0m \u001b[1m0s\u001b[0m 54ms/step\n",
      "\u001b[1m1/1\u001b[0m \u001b[32m━━━━━━━━━━━━━━━━━━━━\u001b[0m\u001b[37m\u001b[0m \u001b[1m0s\u001b[0m 53ms/step\n",
      "\u001b[1m1/1\u001b[0m \u001b[32m━━━━━━━━━━━━━━━━━━━━\u001b[0m\u001b[37m\u001b[0m \u001b[1m0s\u001b[0m 54ms/step\n",
      "\u001b[1m1/1\u001b[0m \u001b[32m━━━━━━━━━━━━━━━━━━━━\u001b[0m\u001b[37m\u001b[0m \u001b[1m0s\u001b[0m 54ms/step\n",
      "\u001b[1m1/1\u001b[0m \u001b[32m━━━━━━━━━━━━━━━━━━━━\u001b[0m\u001b[37m\u001b[0m \u001b[1m0s\u001b[0m 44ms/step\n",
      "\u001b[1m1/1\u001b[0m \u001b[32m━━━━━━━━━━━━━━━━━━━━\u001b[0m\u001b[37m\u001b[0m \u001b[1m0s\u001b[0m 54ms/step\n",
      "\u001b[1m1/1\u001b[0m \u001b[32m━━━━━━━━━━━━━━━━━━━━\u001b[0m\u001b[37m\u001b[0m \u001b[1m0s\u001b[0m 54ms/step\n",
      "\u001b[1m1/1\u001b[0m \u001b[32m━━━━━━━━━━━━━━━━━━━━\u001b[0m\u001b[37m\u001b[0m \u001b[1m0s\u001b[0m 40ms/step\n",
      "\u001b[1m1/1\u001b[0m \u001b[32m━━━━━━━━━━━━━━━━━━━━\u001b[0m\u001b[37m\u001b[0m \u001b[1m0s\u001b[0m 59ms/step\n",
      "\u001b[1m1/1\u001b[0m \u001b[32m━━━━━━━━━━━━━━━━━━━━\u001b[0m\u001b[37m\u001b[0m \u001b[1m0s\u001b[0m 54ms/step\n",
      "\u001b[1m1/1\u001b[0m \u001b[32m━━━━━━━━━━━━━━━━━━━━\u001b[0m\u001b[37m\u001b[0m \u001b[1m0s\u001b[0m 67ms/step\n",
      "\u001b[1m1/1\u001b[0m \u001b[32m━━━━━━━━━━━━━━━━━━━━\u001b[0m\u001b[37m\u001b[0m \u001b[1m0s\u001b[0m 40ms/step\n",
      "\u001b[1m1/1\u001b[0m \u001b[32m━━━━━━━━━━━━━━━━━━━━\u001b[0m\u001b[37m\u001b[0m \u001b[1m0s\u001b[0m 54ms/step\n",
      "\u001b[1m1/1\u001b[0m \u001b[32m━━━━━━━━━━━━━━━━━━━━\u001b[0m\u001b[37m\u001b[0m \u001b[1m0s\u001b[0m 64ms/step\n",
      "\u001b[1m1/1\u001b[0m \u001b[32m━━━━━━━━━━━━━━━━━━━━\u001b[0m\u001b[37m\u001b[0m \u001b[1m0s\u001b[0m 54ms/step\n",
      "\u001b[1m1/1\u001b[0m \u001b[32m━━━━━━━━━━━━━━━━━━━━\u001b[0m\u001b[37m\u001b[0m \u001b[1m0s\u001b[0m 54ms/step\n",
      "\u001b[1m1/1\u001b[0m \u001b[32m━━━━━━━━━━━━━━━━━━━━\u001b[0m\u001b[37m\u001b[0m \u001b[1m0s\u001b[0m 55ms/step\n",
      "\u001b[1m1/1\u001b[0m \u001b[32m━━━━━━━━━━━━━━━━━━━━\u001b[0m\u001b[37m\u001b[0m \u001b[1m0s\u001b[0m 63ms/step\n",
      "\u001b[1m1/1\u001b[0m \u001b[32m━━━━━━━━━━━━━━━━━━━━\u001b[0m\u001b[37m\u001b[0m \u001b[1m0s\u001b[0m 51ms/step\n",
      "\u001b[1m1/1\u001b[0m \u001b[32m━━━━━━━━━━━━━━━━━━━━\u001b[0m\u001b[37m\u001b[0m \u001b[1m0s\u001b[0m 54ms/step\n",
      "\u001b[1m1/1\u001b[0m \u001b[32m━━━━━━━━━━━━━━━━━━━━\u001b[0m\u001b[37m\u001b[0m \u001b[1m0s\u001b[0m 42ms/step\n",
      "\u001b[1m1/1\u001b[0m \u001b[32m━━━━━━━━━━━━━━━━━━━━\u001b[0m\u001b[37m\u001b[0m \u001b[1m0s\u001b[0m 53ms/step\n",
      "\u001b[1m1/1\u001b[0m \u001b[32m━━━━━━━━━━━━━━━━━━━━\u001b[0m\u001b[37m\u001b[0m \u001b[1m0s\u001b[0m 40ms/step\n",
      "\u001b[1m1/1\u001b[0m \u001b[32m━━━━━━━━━━━━━━━━━━━━\u001b[0m\u001b[37m\u001b[0m \u001b[1m0s\u001b[0m 54ms/step\n",
      "\u001b[1m1/1\u001b[0m \u001b[32m━━━━━━━━━━━━━━━━━━━━\u001b[0m\u001b[37m\u001b[0m \u001b[1m0s\u001b[0m 54ms/step\n",
      "\u001b[1m1/1\u001b[0m \u001b[32m━━━━━━━━━━━━━━━━━━━━\u001b[0m\u001b[37m\u001b[0m \u001b[1m0s\u001b[0m 41ms/step\n",
      "\u001b[1m1/1\u001b[0m \u001b[32m━━━━━━━━━━━━━━━━━━━━\u001b[0m\u001b[37m\u001b[0m \u001b[1m0s\u001b[0m 54ms/step\n",
      "\u001b[1m1/1\u001b[0m \u001b[32m━━━━━━━━━━━━━━━━━━━━\u001b[0m\u001b[37m\u001b[0m \u001b[1m0s\u001b[0m 60ms/step\n",
      "\u001b[1m1/1\u001b[0m \u001b[32m━━━━━━━━━━━━━━━━━━━━\u001b[0m\u001b[37m\u001b[0m \u001b[1m0s\u001b[0m 54ms/step\n",
      "\u001b[1m1/1\u001b[0m \u001b[32m━━━━━━━━━━━━━━━━━━━━\u001b[0m\u001b[37m\u001b[0m \u001b[1m0s\u001b[0m 62ms/step\n",
      "\u001b[1m1/1\u001b[0m \u001b[32m━━━━━━━━━━━━━━━━━━━━\u001b[0m\u001b[37m\u001b[0m \u001b[1m0s\u001b[0m 52ms/step\n",
      "\u001b[1m1/1\u001b[0m \u001b[32m━━━━━━━━━━━━━━━━━━━━\u001b[0m\u001b[37m\u001b[0m \u001b[1m0s\u001b[0m 54ms/step\n",
      "\u001b[1m1/1\u001b[0m \u001b[32m━━━━━━━━━━━━━━━━━━━━\u001b[0m\u001b[37m\u001b[0m \u001b[1m0s\u001b[0m 54ms/step\n",
      "\u001b[1m1/1\u001b[0m \u001b[32m━━━━━━━━━━━━━━━━━━━━\u001b[0m\u001b[37m\u001b[0m \u001b[1m0s\u001b[0m 64ms/step\n",
      "\u001b[1m1/1\u001b[0m \u001b[32m━━━━━━━━━━━━━━━━━━━━\u001b[0m\u001b[37m\u001b[0m \u001b[1m0s\u001b[0m 51ms/step\n",
      "\u001b[1m1/1\u001b[0m \u001b[32m━━━━━━━━━━━━━━━━━━━━\u001b[0m\u001b[37m\u001b[0m \u001b[1m0s\u001b[0m 54ms/step\n",
      "\u001b[1m1/1\u001b[0m \u001b[32m━━━━━━━━━━━━━━━━━━━━\u001b[0m\u001b[37m\u001b[0m \u001b[1m0s\u001b[0m 53ms/step\n",
      "\u001b[1m1/1\u001b[0m \u001b[32m━━━━━━━━━━━━━━━━━━━━\u001b[0m\u001b[37m\u001b[0m \u001b[1m0s\u001b[0m 54ms/step\n",
      "\u001b[1m1/1\u001b[0m \u001b[32m━━━━━━━━━━━━━━━━━━━━\u001b[0m\u001b[37m\u001b[0m \u001b[1m0s\u001b[0m 56ms/step\n",
      "\u001b[1m1/1\u001b[0m \u001b[32m━━━━━━━━━━━━━━━━━━━━\u001b[0m\u001b[37m\u001b[0m \u001b[1m0s\u001b[0m 54ms/step\n",
      "\u001b[1m1/1\u001b[0m \u001b[32m━━━━━━━━━━━━━━━━━━━━\u001b[0m\u001b[37m\u001b[0m \u001b[1m0s\u001b[0m 54ms/step\n",
      "\u001b[1m1/1\u001b[0m \u001b[32m━━━━━━━━━━━━━━━━━━━━\u001b[0m\u001b[37m\u001b[0m \u001b[1m0s\u001b[0m 67ms/step\n",
      "\u001b[1m1/1\u001b[0m \u001b[32m━━━━━━━━━━━━━━━━━━━━\u001b[0m\u001b[37m\u001b[0m \u001b[1m0s\u001b[0m 67ms/step\n",
      "\u001b[1m1/1\u001b[0m \u001b[32m━━━━━━━━━━━━━━━━━━━━\u001b[0m\u001b[37m\u001b[0m \u001b[1m0s\u001b[0m 43ms/step\n",
      "\u001b[1m1/1\u001b[0m \u001b[32m━━━━━━━━━━━━━━━━━━━━\u001b[0m\u001b[37m\u001b[0m \u001b[1m0s\u001b[0m 53ms/step\n",
      "\u001b[1m1/1\u001b[0m \u001b[32m━━━━━━━━━━━━━━━━━━━━\u001b[0m\u001b[37m\u001b[0m \u001b[1m0s\u001b[0m 53ms/step\n",
      "\u001b[1m1/1\u001b[0m \u001b[32m━━━━━━━━━━━━━━━━━━━━\u001b[0m\u001b[37m\u001b[0m \u001b[1m0s\u001b[0m 54ms/step\n",
      "\u001b[1m1/1\u001b[0m \u001b[32m━━━━━━━━━━━━━━━━━━━━\u001b[0m\u001b[37m\u001b[0m \u001b[1m0s\u001b[0m 47ms/step\n",
      "\u001b[1m1/1\u001b[0m \u001b[32m━━━━━━━━━━━━━━━━━━━━\u001b[0m\u001b[37m\u001b[0m \u001b[1m0s\u001b[0m 67ms/step\n",
      "\u001b[1m1/1\u001b[0m \u001b[32m━━━━━━━━━━━━━━━━━━━━\u001b[0m\u001b[37m\u001b[0m \u001b[1m0s\u001b[0m 54ms/step\n",
      "\u001b[1m1/1\u001b[0m \u001b[32m━━━━━━━━━━━━━━━━━━━━\u001b[0m\u001b[37m\u001b[0m \u001b[1m0s\u001b[0m 54ms/step\n",
      "\u001b[1m1/1\u001b[0m \u001b[32m━━━━━━━━━━━━━━━━━━━━\u001b[0m\u001b[37m\u001b[0m \u001b[1m0s\u001b[0m 54ms/step\n",
      "\u001b[1m1/1\u001b[0m \u001b[32m━━━━━━━━━━━━━━━━━━━━\u001b[0m\u001b[37m\u001b[0m \u001b[1m0s\u001b[0m 46ms/step\n",
      "\u001b[1m1/1\u001b[0m \u001b[32m━━━━━━━━━━━━━━━━━━━━\u001b[0m\u001b[37m\u001b[0m \u001b[1m0s\u001b[0m 40ms/step\n",
      "\u001b[1m1/1\u001b[0m \u001b[32m━━━━━━━━━━━━━━━━━━━━\u001b[0m\u001b[37m\u001b[0m \u001b[1m0s\u001b[0m 53ms/step\n",
      "\u001b[1m1/1\u001b[0m \u001b[32m━━━━━━━━━━━━━━━━━━━━\u001b[0m\u001b[37m\u001b[0m \u001b[1m0s\u001b[0m 54ms/step\n",
      "\u001b[1m1/1\u001b[0m \u001b[32m━━━━━━━━━━━━━━━━━━━━\u001b[0m\u001b[37m\u001b[0m \u001b[1m0s\u001b[0m 57ms/step\n",
      "\u001b[1m1/1\u001b[0m \u001b[32m━━━━━━━━━━━━━━━━━━━━\u001b[0m\u001b[37m\u001b[0m \u001b[1m0s\u001b[0m 54ms/step\n",
      "\u001b[1m1/1\u001b[0m \u001b[32m━━━━━━━━━━━━━━━━━━━━\u001b[0m\u001b[37m\u001b[0m \u001b[1m0s\u001b[0m 54ms/step\n",
      "\u001b[1m1/1\u001b[0m \u001b[32m━━━━━━━━━━━━━━━━━━━━\u001b[0m\u001b[37m\u001b[0m \u001b[1m0s\u001b[0m 54ms/step\n",
      "\u001b[1m1/1\u001b[0m \u001b[32m━━━━━━━━━━━━━━━━━━━━\u001b[0m\u001b[37m\u001b[0m \u001b[1m0s\u001b[0m 54ms/step\n",
      "\u001b[1m1/1\u001b[0m \u001b[32m━━━━━━━━━━━━━━━━━━━━\u001b[0m\u001b[37m\u001b[0m \u001b[1m0s\u001b[0m 52ms/step\n",
      "\u001b[1m1/1\u001b[0m \u001b[32m━━━━━━━━━━━━━━━━━━━━\u001b[0m\u001b[37m\u001b[0m \u001b[1m0s\u001b[0m 54ms/step\n",
      "\u001b[1m1/1\u001b[0m \u001b[32m━━━━━━━━━━━━━━━━━━━━\u001b[0m\u001b[37m\u001b[0m \u001b[1m0s\u001b[0m 54ms/step\n",
      "\u001b[1m1/1\u001b[0m \u001b[32m━━━━━━━━━━━━━━━━━━━━\u001b[0m\u001b[37m\u001b[0m \u001b[1m0s\u001b[0m 54ms/step\n",
      "\u001b[1m1/1\u001b[0m \u001b[32m━━━━━━━━━━━━━━━━━━━━\u001b[0m\u001b[37m\u001b[0m \u001b[1m0s\u001b[0m 64ms/step\n",
      "\u001b[1m1/1\u001b[0m \u001b[32m━━━━━━━━━━━━━━━━━━━━\u001b[0m\u001b[37m\u001b[0m \u001b[1m0s\u001b[0m 62ms/step\n",
      "\u001b[1m1/1\u001b[0m \u001b[32m━━━━━━━━━━━━━━━━━━━━\u001b[0m\u001b[37m\u001b[0m \u001b[1m0s\u001b[0m 54ms/step\n",
      "\u001b[1m1/1\u001b[0m \u001b[32m━━━━━━━━━━━━━━━━━━━━\u001b[0m\u001b[37m\u001b[0m \u001b[1m0s\u001b[0m 54ms/step\n",
      "\u001b[1m1/1\u001b[0m \u001b[32m━━━━━━━━━━━━━━━━━━━━\u001b[0m\u001b[37m\u001b[0m \u001b[1m0s\u001b[0m 54ms/step\n",
      "\u001b[1m1/1\u001b[0m \u001b[32m━━━━━━━━━━━━━━━━━━━━\u001b[0m\u001b[37m\u001b[0m \u001b[1m0s\u001b[0m 51ms/step\n",
      "\u001b[1m1/1\u001b[0m \u001b[32m━━━━━━━━━━━━━━━━━━━━\u001b[0m\u001b[37m\u001b[0m \u001b[1m0s\u001b[0m 53ms/step\n",
      "\u001b[1m1/1\u001b[0m \u001b[32m━━━━━━━━━━━━━━━━━━━━\u001b[0m\u001b[37m\u001b[0m \u001b[1m0s\u001b[0m 54ms/step\n",
      "\u001b[1m1/1\u001b[0m \u001b[32m━━━━━━━━━━━━━━━━━━━━\u001b[0m\u001b[37m\u001b[0m \u001b[1m0s\u001b[0m 54ms/step\n",
      "\u001b[1m1/1\u001b[0m \u001b[32m━━━━━━━━━━━━━━━━━━━━\u001b[0m\u001b[37m\u001b[0m \u001b[1m0s\u001b[0m 59ms/step\n",
      "\u001b[1m1/1\u001b[0m \u001b[32m━━━━━━━━━━━━━━━━━━━━\u001b[0m\u001b[37m\u001b[0m \u001b[1m0s\u001b[0m 67ms/step\n",
      "\u001b[1m1/1\u001b[0m \u001b[32m━━━━━━━━━━━━━━━━━━━━\u001b[0m\u001b[37m\u001b[0m \u001b[1m0s\u001b[0m 54ms/step\n",
      "\u001b[1m1/1\u001b[0m \u001b[32m━━━━━━━━━━━━━━━━━━━━\u001b[0m\u001b[37m\u001b[0m \u001b[1m0s\u001b[0m 53ms/step\n",
      "\u001b[1m1/1\u001b[0m \u001b[32m━━━━━━━━━━━━━━━━━━━━\u001b[0m\u001b[37m\u001b[0m \u001b[1m0s\u001b[0m 50ms/step\n",
      "\u001b[1m1/1\u001b[0m \u001b[32m━━━━━━━━━━━━━━━━━━━━\u001b[0m\u001b[37m\u001b[0m \u001b[1m0s\u001b[0m 52ms/step\n",
      "\u001b[1m1/1\u001b[0m \u001b[32m━━━━━━━━━━━━━━━━━━━━\u001b[0m\u001b[37m\u001b[0m \u001b[1m0s\u001b[0m 56ms/step\n",
      "\u001b[1m1/1\u001b[0m \u001b[32m━━━━━━━━━━━━━━━━━━━━\u001b[0m\u001b[37m\u001b[0m \u001b[1m0s\u001b[0m 54ms/step\n",
      "\u001b[1m1/1\u001b[0m \u001b[32m━━━━━━━━━━━━━━━━━━━━\u001b[0m\u001b[37m\u001b[0m \u001b[1m0s\u001b[0m 54ms/step\n",
      "\u001b[1m1/1\u001b[0m \u001b[32m━━━━━━━━━━━━━━━━━━━━\u001b[0m\u001b[37m\u001b[0m \u001b[1m0s\u001b[0m 58ms/step\n",
      "\u001b[1m1/1\u001b[0m \u001b[32m━━━━━━━━━━━━━━━━━━━━\u001b[0m\u001b[37m\u001b[0m \u001b[1m0s\u001b[0m 51ms/step\n",
      "\u001b[1m1/1\u001b[0m \u001b[32m━━━━━━━━━━━━━━━━━━━━\u001b[0m\u001b[37m\u001b[0m \u001b[1m0s\u001b[0m 54ms/step\n",
      "\u001b[1m1/1\u001b[0m \u001b[32m━━━━━━━━━━━━━━━━━━━━\u001b[0m\u001b[37m\u001b[0m \u001b[1m0s\u001b[0m 54ms/step\n",
      "\u001b[1m1/1\u001b[0m \u001b[32m━━━━━━━━━━━━━━━━━━━━\u001b[0m\u001b[37m\u001b[0m \u001b[1m0s\u001b[0m 53ms/step\n",
      "\u001b[1m1/1\u001b[0m \u001b[32m━━━━━━━━━━━━━━━━━━━━\u001b[0m\u001b[37m\u001b[0m \u001b[1m0s\u001b[0m 57ms/step\n",
      "\u001b[1m1/1\u001b[0m \u001b[32m━━━━━━━━━━━━━━━━━━━━\u001b[0m\u001b[37m\u001b[0m \u001b[1m0s\u001b[0m 54ms/step\n",
      "\u001b[1m1/1\u001b[0m \u001b[32m━━━━━━━━━━━━━━━━━━━━\u001b[0m\u001b[37m\u001b[0m \u001b[1m0s\u001b[0m 52ms/step\n",
      "\u001b[1m1/1\u001b[0m \u001b[32m━━━━━━━━━━━━━━━━━━━━\u001b[0m\u001b[37m\u001b[0m \u001b[1m0s\u001b[0m 54ms/step\n",
      "\u001b[1m1/1\u001b[0m \u001b[32m━━━━━━━━━━━━━━━━━━━━\u001b[0m\u001b[37m\u001b[0m \u001b[1m0s\u001b[0m 54ms/step\n",
      "\u001b[1m1/1\u001b[0m \u001b[32m━━━━━━━━━━━━━━━━━━━━\u001b[0m\u001b[37m\u001b[0m \u001b[1m0s\u001b[0m 54ms/step\n",
      "\u001b[1m1/1\u001b[0m \u001b[32m━━━━━━━━━━━━━━━━━━━━\u001b[0m\u001b[37m\u001b[0m \u001b[1m0s\u001b[0m 62ms/step\n",
      "\u001b[1m1/1\u001b[0m \u001b[32m━━━━━━━━━━━━━━━━━━━━\u001b[0m\u001b[37m\u001b[0m \u001b[1m0s\u001b[0m 51ms/step\n",
      "\u001b[1m1/1\u001b[0m \u001b[32m━━━━━━━━━━━━━━━━━━━━\u001b[0m\u001b[37m\u001b[0m \u001b[1m0s\u001b[0m 67ms/step\n",
      "\u001b[1m1/1\u001b[0m \u001b[32m━━━━━━━━━━━━━━━━━━━━\u001b[0m\u001b[37m\u001b[0m \u001b[1m0s\u001b[0m 40ms/step\n",
      "\u001b[1m1/1\u001b[0m \u001b[32m━━━━━━━━━━━━━━━━━━━━\u001b[0m\u001b[37m\u001b[0m \u001b[1m0s\u001b[0m 53ms/step\n",
      "\u001b[1m1/1\u001b[0m \u001b[32m━━━━━━━━━━━━━━━━━━━━\u001b[0m\u001b[37m\u001b[0m \u001b[1m0s\u001b[0m 61ms/step\n",
      "\u001b[1m1/1\u001b[0m \u001b[32m━━━━━━━━━━━━━━━━━━━━\u001b[0m\u001b[37m\u001b[0m \u001b[1m0s\u001b[0m 54ms/step\n",
      "\u001b[1m1/1\u001b[0m \u001b[32m━━━━━━━━━━━━━━━━━━━━\u001b[0m\u001b[37m\u001b[0m \u001b[1m0s\u001b[0m 54ms/step\n",
      "\u001b[1m1/1\u001b[0m \u001b[32m━━━━━━━━━━━━━━━━━━━━\u001b[0m\u001b[37m\u001b[0m \u001b[1m0s\u001b[0m 44ms/step\n",
      "\u001b[1m1/1\u001b[0m \u001b[32m━━━━━━━━━━━━━━━━━━━━\u001b[0m\u001b[37m\u001b[0m \u001b[1m0s\u001b[0m 54ms/step\n",
      "\u001b[1m1/1\u001b[0m \u001b[32m━━━━━━━━━━━━━━━━━━━━\u001b[0m\u001b[37m\u001b[0m \u001b[1m0s\u001b[0m 53ms/step\n",
      "\u001b[1m1/1\u001b[0m \u001b[32m━━━━━━━━━━━━━━━━━━━━\u001b[0m\u001b[37m\u001b[0m \u001b[1m0s\u001b[0m 54ms/step\n",
      "\u001b[1m1/1\u001b[0m \u001b[32m━━━━━━━━━━━━━━━━━━━━\u001b[0m\u001b[37m\u001b[0m \u001b[1m0s\u001b[0m 52ms/step\n",
      "\u001b[1m1/1\u001b[0m \u001b[32m━━━━━━━━━━━━━━━━━━━━\u001b[0m\u001b[37m\u001b[0m \u001b[1m0s\u001b[0m 54ms/step\n",
      "\u001b[1m1/1\u001b[0m \u001b[32m━━━━━━━━━━━━━━━━━━━━\u001b[0m\u001b[37m\u001b[0m \u001b[1m0s\u001b[0m 53ms/step\n",
      "\u001b[1m1/1\u001b[0m \u001b[32m━━━━━━━━━━━━━━━━━━━━\u001b[0m\u001b[37m\u001b[0m \u001b[1m0s\u001b[0m 53ms/step\n",
      "\u001b[1m1/1\u001b[0m \u001b[32m━━━━━━━━━━━━━━━━━━━━\u001b[0m\u001b[37m\u001b[0m \u001b[1m0s\u001b[0m 53ms/step\n",
      "\u001b[1m1/1\u001b[0m \u001b[32m━━━━━━━━━━━━━━━━━━━━\u001b[0m\u001b[37m\u001b[0m \u001b[1m0s\u001b[0m 54ms/step\n",
      "\u001b[1m1/1\u001b[0m \u001b[32m━━━━━━━━━━━━━━━━━━━━\u001b[0m\u001b[37m\u001b[0m \u001b[1m0s\u001b[0m 54ms/step\n",
      "\u001b[1m1/1\u001b[0m \u001b[32m━━━━━━━━━━━━━━━━━━━━\u001b[0m\u001b[37m\u001b[0m \u001b[1m0s\u001b[0m 49ms/step\n",
      "\u001b[1m1/1\u001b[0m \u001b[32m━━━━━━━━━━━━━━━━━━━━\u001b[0m\u001b[37m\u001b[0m \u001b[1m0s\u001b[0m 54ms/step\n",
      "\u001b[1m1/1\u001b[0m \u001b[32m━━━━━━━━━━━━━━━━━━━━\u001b[0m\u001b[37m\u001b[0m \u001b[1m0s\u001b[0m 54ms/step\n",
      "\u001b[1m1/1\u001b[0m \u001b[32m━━━━━━━━━━━━━━━━━━━━\u001b[0m\u001b[37m\u001b[0m \u001b[1m0s\u001b[0m 67ms/step\n",
      "\u001b[1m1/1\u001b[0m \u001b[32m━━━━━━━━━━━━━━━━━━━━\u001b[0m\u001b[37m\u001b[0m \u001b[1m0s\u001b[0m 54ms/step\n",
      "\u001b[1m1/1\u001b[0m \u001b[32m━━━━━━━━━━━━━━━━━━━━\u001b[0m\u001b[37m\u001b[0m \u001b[1m0s\u001b[0m 53ms/step\n",
      "\u001b[1m1/1\u001b[0m \u001b[32m━━━━━━━━━━━━━━━━━━━━\u001b[0m\u001b[37m\u001b[0m \u001b[1m0s\u001b[0m 54ms/step\n",
      "\u001b[1m1/1\u001b[0m \u001b[32m━━━━━━━━━━━━━━━━━━━━\u001b[0m\u001b[37m\u001b[0m \u001b[1m0s\u001b[0m 54ms/step\n",
      "\u001b[1m1/1\u001b[0m \u001b[32m━━━━━━━━━━━━━━━━━━━━\u001b[0m\u001b[37m\u001b[0m \u001b[1m0s\u001b[0m 66ms/step\n",
      "\u001b[1m1/1\u001b[0m \u001b[32m━━━━━━━━━━━━━━━━━━━━\u001b[0m\u001b[37m\u001b[0m \u001b[1m0s\u001b[0m 48ms/step\n",
      "\u001b[1m1/1\u001b[0m \u001b[32m━━━━━━━━━━━━━━━━━━━━\u001b[0m\u001b[37m\u001b[0m \u001b[1m0s\u001b[0m 53ms/step\n",
      "\u001b[1m1/1\u001b[0m \u001b[32m━━━━━━━━━━━━━━━━━━━━\u001b[0m\u001b[37m\u001b[0m \u001b[1m0s\u001b[0m 54ms/step\n",
      "\u001b[1m1/1\u001b[0m \u001b[32m━━━━━━━━━━━━━━━━━━━━\u001b[0m\u001b[37m\u001b[0m \u001b[1m0s\u001b[0m 54ms/step\n",
      "\u001b[1m1/1\u001b[0m \u001b[32m━━━━━━━━━━━━━━━━━━━━\u001b[0m\u001b[37m\u001b[0m \u001b[1m0s\u001b[0m 63ms/step\n",
      "\u001b[1m1/1\u001b[0m \u001b[32m━━━━━━━━━━━━━━━━━━━━\u001b[0m\u001b[37m\u001b[0m \u001b[1m0s\u001b[0m 52ms/step\n",
      "\u001b[1m1/1\u001b[0m \u001b[32m━━━━━━━━━━━━━━━━━━━━\u001b[0m\u001b[37m\u001b[0m \u001b[1m0s\u001b[0m 54ms/step\n",
      "\u001b[1m1/1\u001b[0m \u001b[32m━━━━━━━━━━━━━━━━━━━━\u001b[0m\u001b[37m\u001b[0m \u001b[1m0s\u001b[0m 40ms/step\n",
      "\u001b[1m1/1\u001b[0m \u001b[32m━━━━━━━━━━━━━━━━━━━━\u001b[0m\u001b[37m\u001b[0m \u001b[1m0s\u001b[0m 54ms/step\n",
      "\u001b[1m1/1\u001b[0m \u001b[32m━━━━━━━━━━━━━━━━━━━━\u001b[0m\u001b[37m\u001b[0m \u001b[1m0s\u001b[0m 60ms/step\n",
      "\u001b[1m1/1\u001b[0m \u001b[32m━━━━━━━━━━━━━━━━━━━━\u001b[0m\u001b[37m\u001b[0m \u001b[1m0s\u001b[0m 54ms/step\n",
      "\u001b[1m1/1\u001b[0m \u001b[32m━━━━━━━━━━━━━━━━━━━━\u001b[0m\u001b[37m\u001b[0m \u001b[1m0s\u001b[0m 54ms/step\n",
      "\u001b[1m1/1\u001b[0m \u001b[32m━━━━━━━━━━━━━━━━━━━━\u001b[0m\u001b[37m\u001b[0m \u001b[1m0s\u001b[0m 55ms/step\n",
      "\u001b[1m1/1\u001b[0m \u001b[32m━━━━━━━━━━━━━━━━━━━━\u001b[0m\u001b[37m\u001b[0m \u001b[1m0s\u001b[0m 54ms/step\n",
      "\u001b[1m1/1\u001b[0m \u001b[32m━━━━━━━━━━━━━━━━━━━━\u001b[0m\u001b[37m\u001b[0m \u001b[1m0s\u001b[0m 57ms/step\n",
      "\u001b[1m1/1\u001b[0m \u001b[32m━━━━━━━━━━━━━━━━━━━━\u001b[0m\u001b[37m\u001b[0m \u001b[1m0s\u001b[0m 54ms/step\n",
      "\u001b[1m1/1\u001b[0m \u001b[32m━━━━━━━━━━━━━━━━━━━━\u001b[0m\u001b[37m\u001b[0m \u001b[1m0s\u001b[0m 45ms/step\n",
      "\u001b[1m1/1\u001b[0m \u001b[32m━━━━━━━━━━━━━━━━━━━━\u001b[0m\u001b[37m\u001b[0m \u001b[1m0s\u001b[0m 53ms/step\n",
      "\u001b[1m1/1\u001b[0m \u001b[32m━━━━━━━━━━━━━━━━━━━━\u001b[0m\u001b[37m\u001b[0m \u001b[1m0s\u001b[0m 68ms/step\n",
      "\u001b[1m1/1\u001b[0m \u001b[32m━━━━━━━━━━━━━━━━━━━━\u001b[0m\u001b[37m\u001b[0m \u001b[1m0s\u001b[0m 67ms/step\n",
      "\u001b[1m1/1\u001b[0m \u001b[32m━━━━━━━━━━━━━━━━━━━━\u001b[0m\u001b[37m\u001b[0m \u001b[1m0s\u001b[0m 54ms/step\n",
      "\u001b[1m1/1\u001b[0m \u001b[32m━━━━━━━━━━━━━━━━━━━━\u001b[0m\u001b[37m\u001b[0m \u001b[1m0s\u001b[0m 52ms/step\n",
      "\u001b[1m1/1\u001b[0m \u001b[32m━━━━━━━━━━━━━━━━━━━━\u001b[0m\u001b[37m\u001b[0m \u001b[1m0s\u001b[0m 53ms/step\n",
      "\u001b[1m1/1\u001b[0m \u001b[32m━━━━━━━━━━━━━━━━━━━━\u001b[0m\u001b[37m\u001b[0m \u001b[1m0s\u001b[0m 61ms/step\n",
      "\u001b[1m1/1\u001b[0m \u001b[32m━━━━━━━━━━━━━━━━━━━━\u001b[0m\u001b[37m\u001b[0m \u001b[1m0s\u001b[0m 54ms/step\n",
      "\u001b[1m1/1\u001b[0m \u001b[32m━━━━━━━━━━━━━━━━━━━━\u001b[0m\u001b[37m\u001b[0m \u001b[1m0s\u001b[0m 48ms/step\n",
      "\u001b[1m1/1\u001b[0m \u001b[32m━━━━━━━━━━━━━━━━━━━━\u001b[0m\u001b[37m\u001b[0m \u001b[1m0s\u001b[0m 41ms/step\n",
      "\u001b[1m1/1\u001b[0m \u001b[32m━━━━━━━━━━━━━━━━━━━━\u001b[0m\u001b[37m\u001b[0m \u001b[1m0s\u001b[0m 54ms/step\n",
      "\u001b[1m1/1\u001b[0m \u001b[32m━━━━━━━━━━━━━━━━━━━━\u001b[0m\u001b[37m\u001b[0m \u001b[1m0s\u001b[0m 41ms/step\n",
      "\u001b[1m1/1\u001b[0m \u001b[32m━━━━━━━━━━━━━━━━━━━━\u001b[0m\u001b[37m\u001b[0m \u001b[1m0s\u001b[0m 54ms/step\n",
      "\u001b[1m1/1\u001b[0m \u001b[32m━━━━━━━━━━━━━━━━━━━━\u001b[0m\u001b[37m\u001b[0m \u001b[1m0s\u001b[0m 64ms/step\n",
      "\u001b[1m1/1\u001b[0m \u001b[32m━━━━━━━━━━━━━━━━━━━━\u001b[0m\u001b[37m\u001b[0m \u001b[1m0s\u001b[0m 53ms/step\n",
      "\u001b[1m1/1\u001b[0m \u001b[32m━━━━━━━━━━━━━━━━━━━━\u001b[0m\u001b[37m\u001b[0m \u001b[1m0s\u001b[0m 54ms/step\n",
      "\u001b[1m1/1\u001b[0m \u001b[32m━━━━━━━━━━━━━━━━━━━━\u001b[0m\u001b[37m\u001b[0m \u001b[1m0s\u001b[0m 54ms/step\n",
      "\u001b[1m1/1\u001b[0m \u001b[32m━━━━━━━━━━━━━━━━━━━━\u001b[0m\u001b[37m\u001b[0m \u001b[1m0s\u001b[0m 67ms/step\n",
      "\u001b[1m1/1\u001b[0m \u001b[32m━━━━━━━━━━━━━━━━━━━━\u001b[0m\u001b[37m\u001b[0m \u001b[1m0s\u001b[0m 54ms/step\n",
      "\u001b[1m1/1\u001b[0m \u001b[32m━━━━━━━━━━━━━━━━━━━━\u001b[0m\u001b[37m\u001b[0m \u001b[1m0s\u001b[0m 40ms/step\n",
      "\u001b[1m1/1\u001b[0m \u001b[32m━━━━━━━━━━━━━━━━━━━━\u001b[0m\u001b[37m\u001b[0m \u001b[1m0s\u001b[0m 50ms/step\n",
      "\u001b[1m1/1\u001b[0m \u001b[32m━━━━━━━━━━━━━━━━━━━━\u001b[0m\u001b[37m\u001b[0m \u001b[1m0s\u001b[0m 54ms/step\n",
      "\u001b[1m1/1\u001b[0m \u001b[32m━━━━━━━━━━━━━━━━━━━━\u001b[0m\u001b[37m\u001b[0m \u001b[1m0s\u001b[0m 54ms/step\n",
      "\u001b[1m1/1\u001b[0m \u001b[32m━━━━━━━━━━━━━━━━━━━━\u001b[0m\u001b[37m\u001b[0m \u001b[1m0s\u001b[0m 54ms/step\n",
      "\u001b[1m1/1\u001b[0m \u001b[32m━━━━━━━━━━━━━━━━━━━━\u001b[0m\u001b[37m\u001b[0m \u001b[1m0s\u001b[0m 58ms/step\n",
      "\u001b[1m1/1\u001b[0m \u001b[32m━━━━━━━━━━━━━━━━━━━━\u001b[0m\u001b[37m\u001b[0m \u001b[1m0s\u001b[0m 54ms/step\n",
      "\u001b[1m1/1\u001b[0m \u001b[32m━━━━━━━━━━━━━━━━━━━━\u001b[0m\u001b[37m\u001b[0m \u001b[1m0s\u001b[0m 67ms/step\n",
      "\u001b[1m1/1\u001b[0m \u001b[32m━━━━━━━━━━━━━━━━━━━━\u001b[0m\u001b[37m\u001b[0m \u001b[1m0s\u001b[0m 67ms/step\n",
      "\u001b[1m1/1\u001b[0m \u001b[32m━━━━━━━━━━━━━━━━━━━━\u001b[0m\u001b[37m\u001b[0m \u001b[1m0s\u001b[0m 54ms/step\n",
      "\u001b[1m1/1\u001b[0m \u001b[32m━━━━━━━━━━━━━━━━━━━━\u001b[0m\u001b[37m\u001b[0m \u001b[1m0s\u001b[0m 51ms/step\n",
      "\u001b[1m1/1\u001b[0m \u001b[32m━━━━━━━━━━━━━━━━━━━━\u001b[0m\u001b[37m\u001b[0m \u001b[1m0s\u001b[0m 53ms/step\n",
      "\u001b[1m1/1\u001b[0m \u001b[32m━━━━━━━━━━━━━━━━━━━━\u001b[0m\u001b[37m\u001b[0m \u001b[1m0s\u001b[0m 54ms/step\n",
      "\u001b[1m1/1\u001b[0m \u001b[32m━━━━━━━━━━━━━━━━━━━━\u001b[0m\u001b[37m\u001b[0m \u001b[1m0s\u001b[0m 54ms/step\n",
      "\u001b[1m1/1\u001b[0m \u001b[32m━━━━━━━━━━━━━━━━━━━━\u001b[0m\u001b[37m\u001b[0m \u001b[1m0s\u001b[0m 53ms/step\n",
      "\u001b[1m1/1\u001b[0m \u001b[32m━━━━━━━━━━━━━━━━━━━━\u001b[0m\u001b[37m\u001b[0m \u001b[1m0s\u001b[0m 44ms/step\n",
      "\u001b[1m1/1\u001b[0m \u001b[32m━━━━━━━━━━━━━━━━━━━━\u001b[0m\u001b[37m\u001b[0m \u001b[1m0s\u001b[0m 54ms/step\n",
      "\u001b[1m1/1\u001b[0m \u001b[32m━━━━━━━━━━━━━━━━━━━━\u001b[0m\u001b[37m\u001b[0m \u001b[1m0s\u001b[0m 53ms/step\n",
      "\u001b[1m1/1\u001b[0m \u001b[32m━━━━━━━━━━━━━━━━━━━━\u001b[0m\u001b[37m\u001b[0m \u001b[1m0s\u001b[0m 54ms/step\n",
      "\u001b[1m1/1\u001b[0m \u001b[32m━━━━━━━━━━━━━━━━━━━━\u001b[0m\u001b[37m\u001b[0m \u001b[1m0s\u001b[0m 47ms/step\n",
      "\u001b[1m1/1\u001b[0m \u001b[32m━━━━━━━━━━━━━━━━━━━━\u001b[0m\u001b[37m\u001b[0m \u001b[1m0s\u001b[0m 54ms/step\n",
      "\u001b[1m1/1\u001b[0m \u001b[32m━━━━━━━━━━━━━━━━━━━━\u001b[0m\u001b[37m\u001b[0m \u001b[1m0s\u001b[0m 54ms/step\n",
      "\u001b[1m1/1\u001b[0m \u001b[32m━━━━━━━━━━━━━━━━━━━━\u001b[0m\u001b[37m\u001b[0m \u001b[1m0s\u001b[0m 53ms/step\n",
      "\u001b[1m1/1\u001b[0m \u001b[32m━━━━━━━━━━━━━━━━━━━━\u001b[0m\u001b[37m\u001b[0m \u001b[1m0s\u001b[0m 59ms/step\n",
      "\u001b[1m1/1\u001b[0m \u001b[32m━━━━━━━━━━━━━━━━━━━━\u001b[0m\u001b[37m\u001b[0m \u001b[1m0s\u001b[0m 54ms/step\n",
      "\u001b[1m1/1\u001b[0m \u001b[32m━━━━━━━━━━━━━━━━━━━━\u001b[0m\u001b[37m\u001b[0m \u001b[1m0s\u001b[0m 53ms/step\n",
      "\u001b[1m1/1\u001b[0m \u001b[32m━━━━━━━━━━━━━━━━━━━━\u001b[0m\u001b[37m\u001b[0m \u001b[1m0s\u001b[0m 53ms/step\n",
      "\u001b[1m1/1\u001b[0m \u001b[32m━━━━━━━━━━━━━━━━━━━━\u001b[0m\u001b[37m\u001b[0m \u001b[1m0s\u001b[0m 54ms/step\n",
      "\u001b[1m1/1\u001b[0m \u001b[32m━━━━━━━━━━━━━━━━━━━━\u001b[0m\u001b[37m\u001b[0m \u001b[1m0s\u001b[0m 54ms/step\n",
      "\u001b[1m1/1\u001b[0m \u001b[32m━━━━━━━━━━━━━━━━━━━━\u001b[0m\u001b[37m\u001b[0m \u001b[1m0s\u001b[0m 54ms/step\n",
      "\u001b[1m1/1\u001b[0m \u001b[32m━━━━━━━━━━━━━━━━━━━━\u001b[0m\u001b[37m\u001b[0m \u001b[1m0s\u001b[0m 62ms/step\n",
      "\u001b[1m1/1\u001b[0m \u001b[32m━━━━━━━━━━━━━━━━━━━━\u001b[0m\u001b[37m\u001b[0m \u001b[1m0s\u001b[0m 52ms/step\n",
      "\u001b[1m1/1\u001b[0m \u001b[32m━━━━━━━━━━━━━━━━━━━━\u001b[0m\u001b[37m\u001b[0m \u001b[1m0s\u001b[0m 66ms/step\n",
      "\u001b[1m1/1\u001b[0m \u001b[32m━━━━━━━━━━━━━━━━━━━━\u001b[0m\u001b[37m\u001b[0m \u001b[1m0s\u001b[0m 54ms/step\n",
      "\u001b[1m1/1\u001b[0m \u001b[32m━━━━━━━━━━━━━━━━━━━━\u001b[0m\u001b[37m\u001b[0m \u001b[1m0s\u001b[0m 54ms/step\n",
      "\u001b[1m1/1\u001b[0m \u001b[32m━━━━━━━━━━━━━━━━━━━━\u001b[0m\u001b[37m\u001b[0m \u001b[1m0s\u001b[0m 53ms/step\n",
      "\u001b[1m1/1\u001b[0m \u001b[32m━━━━━━━━━━━━━━━━━━━━\u001b[0m\u001b[37m\u001b[0m \u001b[1m0s\u001b[0m 54ms/step\n",
      "\u001b[1m1/1\u001b[0m \u001b[32m━━━━━━━━━━━━━━━━━━━━\u001b[0m\u001b[37m\u001b[0m \u001b[1m0s\u001b[0m 54ms/step\n",
      "\u001b[1m1/1\u001b[0m \u001b[32m━━━━━━━━━━━━━━━━━━━━\u001b[0m\u001b[37m\u001b[0m \u001b[1m0s\u001b[0m 54ms/step\n",
      "\u001b[1m1/1\u001b[0m \u001b[32m━━━━━━━━━━━━━━━━━━━━\u001b[0m\u001b[37m\u001b[0m \u001b[1m0s\u001b[0m 54ms/step\n",
      "\u001b[1m1/1\u001b[0m \u001b[32m━━━━━━━━━━━━━━━━━━━━\u001b[0m\u001b[37m\u001b[0m \u001b[1m0s\u001b[0m 53ms/step\n",
      "\u001b[1m1/1\u001b[0m \u001b[32m━━━━━━━━━━━━━━━━━━━━\u001b[0m\u001b[37m\u001b[0m \u001b[1m0s\u001b[0m 54ms/step\n",
      "\u001b[1m1/1\u001b[0m \u001b[32m━━━━━━━━━━━━━━━━━━━━\u001b[0m\u001b[37m\u001b[0m \u001b[1m0s\u001b[0m 67ms/step\n",
      "\u001b[1m1/1\u001b[0m \u001b[32m━━━━━━━━━━━━━━━━━━━━\u001b[0m\u001b[37m\u001b[0m \u001b[1m0s\u001b[0m 54ms/step\n",
      "\u001b[1m1/1\u001b[0m \u001b[32m━━━━━━━━━━━━━━━━━━━━\u001b[0m\u001b[37m\u001b[0m \u001b[1m0s\u001b[0m 53ms/step\n",
      "\u001b[1m1/1\u001b[0m \u001b[32m━━━━━━━━━━━━━━━━━━━━\u001b[0m\u001b[37m\u001b[0m \u001b[1m0s\u001b[0m 54ms/step\n",
      "\u001b[1m1/1\u001b[0m \u001b[32m━━━━━━━━━━━━━━━━━━━━\u001b[0m\u001b[37m\u001b[0m \u001b[1m0s\u001b[0m 64ms/step\n",
      "\u001b[1m1/1\u001b[0m \u001b[32m━━━━━━━━━━━━━━━━━━━━\u001b[0m\u001b[37m\u001b[0m \u001b[1m0s\u001b[0m 54ms/step\n",
      "\u001b[1m1/1\u001b[0m \u001b[32m━━━━━━━━━━━━━━━━━━━━\u001b[0m\u001b[37m\u001b[0m \u001b[1m0s\u001b[0m 53ms/step\n",
      "\u001b[1m1/1\u001b[0m \u001b[32m━━━━━━━━━━━━━━━━━━━━\u001b[0m\u001b[37m\u001b[0m \u001b[1m0s\u001b[0m 54ms/step\n",
      "\u001b[1m1/1\u001b[0m \u001b[32m━━━━━━━━━━━━━━━━━━━━\u001b[0m\u001b[37m\u001b[0m \u001b[1m0s\u001b[0m 74ms/step\n",
      "\u001b[1m1/1\u001b[0m \u001b[32m━━━━━━━━━━━━━━━━━━━━\u001b[0m\u001b[37m\u001b[0m \u001b[1m0s\u001b[0m 67ms/step\n",
      "\u001b[1m1/1\u001b[0m \u001b[32m━━━━━━━━━━━━━━━━━━━━\u001b[0m\u001b[37m\u001b[0m \u001b[1m0s\u001b[0m 54ms/step\n",
      "\u001b[1m1/1\u001b[0m \u001b[32m━━━━━━━━━━━━━━━━━━━━\u001b[0m\u001b[37m\u001b[0m \u001b[1m0s\u001b[0m 40ms/step\n",
      "\u001b[1m1/1\u001b[0m \u001b[32m━━━━━━━━━━━━━━━━━━━━\u001b[0m\u001b[37m\u001b[0m \u001b[1m0s\u001b[0m 54ms/step\n",
      "\u001b[1m1/1\u001b[0m \u001b[32m━━━━━━━━━━━━━━━━━━━━\u001b[0m\u001b[37m\u001b[0m \u001b[1m0s\u001b[0m 54ms/step\n",
      "\u001b[1m1/1\u001b[0m \u001b[32m━━━━━━━━━━━━━━━━━━━━\u001b[0m\u001b[37m\u001b[0m \u001b[1m0s\u001b[0m 67ms/step\n",
      "\u001b[1m1/1\u001b[0m \u001b[32m━━━━━━━━━━━━━━━━━━━━\u001b[0m\u001b[37m\u001b[0m \u001b[1m0s\u001b[0m 66ms/step\n",
      "\u001b[1m1/1\u001b[0m \u001b[32m━━━━━━━━━━━━━━━━━━━━\u001b[0m\u001b[37m\u001b[0m \u001b[1m0s\u001b[0m 54ms/step\n",
      "\u001b[1m1/1\u001b[0m \u001b[32m━━━━━━━━━━━━━━━━━━━━\u001b[0m\u001b[37m\u001b[0m \u001b[1m0s\u001b[0m 57ms/step\n",
      "\u001b[1m1/1\u001b[0m \u001b[32m━━━━━━━━━━━━━━━━━━━━\u001b[0m\u001b[37m\u001b[0m \u001b[1m0s\u001b[0m 54ms/step\n",
      "\u001b[1m1/1\u001b[0m \u001b[32m━━━━━━━━━━━━━━━━━━━━\u001b[0m\u001b[37m\u001b[0m \u001b[1m0s\u001b[0m 53ms/step\n",
      "\u001b[1m1/1\u001b[0m \u001b[32m━━━━━━━━━━━━━━━━━━━━\u001b[0m\u001b[37m\u001b[0m \u001b[1m0s\u001b[0m 53ms/step\n",
      "\u001b[1m1/1\u001b[0m \u001b[32m━━━━━━━━━━━━━━━━━━━━\u001b[0m\u001b[37m\u001b[0m \u001b[1m0s\u001b[0m 41ms/step\n",
      "\u001b[1m1/1\u001b[0m \u001b[32m━━━━━━━━━━━━━━━━━━━━\u001b[0m\u001b[37m\u001b[0m \u001b[1m0s\u001b[0m 59ms/step\n",
      "\u001b[1m1/1\u001b[0m \u001b[32m━━━━━━━━━━━━━━━━━━━━\u001b[0m\u001b[37m\u001b[0m \u001b[1m0s\u001b[0m 54ms/step\n",
      "\u001b[1m1/1\u001b[0m \u001b[32m━━━━━━━━━━━━━━━━━━━━\u001b[0m\u001b[37m\u001b[0m \u001b[1m0s\u001b[0m 54ms/step\n",
      "\u001b[1m1/1\u001b[0m \u001b[32m━━━━━━━━━━━━━━━━━━━━\u001b[0m\u001b[37m\u001b[0m \u001b[1m0s\u001b[0m 46ms/step\n",
      "\u001b[1m1/1\u001b[0m \u001b[32m━━━━━━━━━━━━━━━━━━━━\u001b[0m\u001b[37m\u001b[0m \u001b[1m0s\u001b[0m 54ms/step\n",
      "\u001b[1m1/1\u001b[0m \u001b[32m━━━━━━━━━━━━━━━━━━━━\u001b[0m\u001b[37m\u001b[0m \u001b[1m0s\u001b[0m 54ms/step\n",
      "\u001b[1m1/1\u001b[0m \u001b[32m━━━━━━━━━━━━━━━━━━━━\u001b[0m\u001b[37m\u001b[0m \u001b[1m0s\u001b[0m 54ms/step\n",
      "\u001b[1m1/1\u001b[0m \u001b[32m━━━━━━━━━━━━━━━━━━━━\u001b[0m\u001b[37m\u001b[0m \u001b[1m0s\u001b[0m 52ms/step\n",
      "\u001b[1m1/1\u001b[0m \u001b[32m━━━━━━━━━━━━━━━━━━━━\u001b[0m\u001b[37m\u001b[0m \u001b[1m0s\u001b[0m 54ms/step\n",
      "\u001b[1m1/1\u001b[0m \u001b[32m━━━━━━━━━━━━━━━━━━━━\u001b[0m\u001b[37m\u001b[0m \u001b[1m0s\u001b[0m 67ms/step\n",
      "\u001b[1m1/1\u001b[0m \u001b[32m━━━━━━━━━━━━━━━━━━━━\u001b[0m\u001b[37m\u001b[0m \u001b[1m0s\u001b[0m 54ms/step\n",
      "\u001b[1m1/1\u001b[0m \u001b[32m━━━━━━━━━━━━━━━━━━━━\u001b[0m\u001b[37m\u001b[0m \u001b[1m0s\u001b[0m 53ms/step\n",
      "\u001b[1m1/1\u001b[0m \u001b[32m━━━━━━━━━━━━━━━━━━━━\u001b[0m\u001b[37m\u001b[0m \u001b[1m0s\u001b[0m 54ms/step\n",
      "\u001b[1m1/1\u001b[0m \u001b[32m━━━━━━━━━━━━━━━━━━━━\u001b[0m\u001b[37m\u001b[0m \u001b[1m0s\u001b[0m 53ms/step\n",
      "\u001b[1m1/1\u001b[0m \u001b[32m━━━━━━━━━━━━━━━━━━━━\u001b[0m\u001b[37m\u001b[0m \u001b[1m0s\u001b[0m 50ms/step\n",
      "\u001b[1m1/1\u001b[0m \u001b[32m━━━━━━━━━━━━━━━━━━━━\u001b[0m\u001b[37m\u001b[0m \u001b[1m0s\u001b[0m 54ms/step\n",
      "\u001b[1m1/1\u001b[0m \u001b[32m━━━━━━━━━━━━━━━━━━━━\u001b[0m\u001b[37m\u001b[0m \u001b[1m0s\u001b[0m 54ms/step\n",
      "\u001b[1m1/1\u001b[0m \u001b[32m━━━━━━━━━━━━━━━━━━━━\u001b[0m\u001b[37m\u001b[0m \u001b[1m0s\u001b[0m 54ms/step\n",
      "\u001b[1m1/1\u001b[0m \u001b[32m━━━━━━━━━━━━━━━━━━━━\u001b[0m\u001b[37m\u001b[0m \u001b[1m0s\u001b[0m 54ms/step\n",
      "\u001b[1m1/1\u001b[0m \u001b[32m━━━━━━━━━━━━━━━━━━━━\u001b[0m\u001b[37m\u001b[0m \u001b[1m0s\u001b[0m 54ms/step\n",
      "\u001b[1m1/1\u001b[0m \u001b[32m━━━━━━━━━━━━━━━━━━━━\u001b[0m\u001b[37m\u001b[0m \u001b[1m0s\u001b[0m 54ms/step\n",
      "\u001b[1m1/1\u001b[0m \u001b[32m━━━━━━━━━━━━━━━━━━━━\u001b[0m\u001b[37m\u001b[0m \u001b[1m0s\u001b[0m 54ms/step\n",
      "\u001b[1m1/1\u001b[0m \u001b[32m━━━━━━━━━━━━━━━━━━━━\u001b[0m\u001b[37m\u001b[0m \u001b[1m0s\u001b[0m 54ms/step\n",
      "\u001b[1m1/1\u001b[0m \u001b[32m━━━━━━━━━━━━━━━━━━━━\u001b[0m\u001b[37m\u001b[0m \u001b[1m0s\u001b[0m 52ms/step\n",
      "\u001b[1m1/1\u001b[0m \u001b[32m━━━━━━━━━━━━━━━━━━━━\u001b[0m\u001b[37m\u001b[0m \u001b[1m0s\u001b[0m 50ms/step\n",
      "\u001b[1m1/1\u001b[0m \u001b[32m━━━━━━━━━━━━━━━━━━━━\u001b[0m\u001b[37m\u001b[0m \u001b[1m0s\u001b[0m 54ms/step\n",
      "\u001b[1m1/1\u001b[0m \u001b[32m━━━━━━━━━━━━━━━━━━━━\u001b[0m\u001b[37m\u001b[0m \u001b[1m0s\u001b[0m 54ms/step\n",
      "\u001b[1m1/1\u001b[0m \u001b[32m━━━━━━━━━━━━━━━━━━━━\u001b[0m\u001b[37m\u001b[0m \u001b[1m0s\u001b[0m 80ms/step\n",
      "\u001b[1m1/1\u001b[0m \u001b[32m━━━━━━━━━━━━━━━━━━━━\u001b[0m\u001b[37m\u001b[0m \u001b[1m0s\u001b[0m 45ms/step\n",
      "\u001b[1m1/1\u001b[0m \u001b[32m━━━━━━━━━━━━━━━━━━━━\u001b[0m\u001b[37m\u001b[0m \u001b[1m0s\u001b[0m 54ms/step\n",
      "\u001b[1m1/1\u001b[0m \u001b[32m━━━━━━━━━━━━━━━━━━━━\u001b[0m\u001b[37m\u001b[0m \u001b[1m0s\u001b[0m 54ms/step\n",
      "\u001b[1m1/1\u001b[0m \u001b[32m━━━━━━━━━━━━━━━━━━━━\u001b[0m\u001b[37m\u001b[0m \u001b[1m0s\u001b[0m 54ms/step\n",
      "\u001b[1m1/1\u001b[0m \u001b[32m━━━━━━━━━━━━━━━━━━━━\u001b[0m\u001b[37m\u001b[0m \u001b[1m0s\u001b[0m 62ms/step\n",
      "\u001b[1m1/1\u001b[0m \u001b[32m━━━━━━━━━━━━━━━━━━━━\u001b[0m\u001b[37m\u001b[0m \u001b[1m0s\u001b[0m 48ms/step\n",
      "\u001b[1m1/1\u001b[0m \u001b[32m━━━━━━━━━━━━━━━━━━━━\u001b[0m\u001b[37m\u001b[0m \u001b[1m0s\u001b[0m 40ms/step\n",
      "\u001b[1m1/1\u001b[0m \u001b[32m━━━━━━━━━━━━━━━━━━━━\u001b[0m\u001b[37m\u001b[0m \u001b[1m0s\u001b[0m 54ms/step\n",
      "\u001b[1m1/1\u001b[0m \u001b[32m━━━━━━━━━━━━━━━━━━━━\u001b[0m\u001b[37m\u001b[0m \u001b[1m0s\u001b[0m 54ms/step\n",
      "\u001b[1m1/1\u001b[0m \u001b[32m━━━━━━━━━━━━━━━━━━━━\u001b[0m\u001b[37m\u001b[0m \u001b[1m0s\u001b[0m 54ms/step\n",
      "\u001b[1m1/1\u001b[0m \u001b[32m━━━━━━━━━━━━━━━━━━━━\u001b[0m\u001b[37m\u001b[0m \u001b[1m0s\u001b[0m 54ms/step\n",
      "\u001b[1m1/1\u001b[0m \u001b[32m━━━━━━━━━━━━━━━━━━━━\u001b[0m\u001b[37m\u001b[0m \u001b[1m0s\u001b[0m 53ms/step\n",
      "\u001b[1m1/1\u001b[0m \u001b[32m━━━━━━━━━━━━━━━━━━━━\u001b[0m\u001b[37m\u001b[0m \u001b[1m0s\u001b[0m 54ms/step\n",
      "\u001b[1m1/1\u001b[0m \u001b[32m━━━━━━━━━━━━━━━━━━━━\u001b[0m\u001b[37m\u001b[0m \u001b[1m0s\u001b[0m 54ms/step\n",
      "\u001b[1m1/1\u001b[0m \u001b[32m━━━━━━━━━━━━━━━━━━━━\u001b[0m\u001b[37m\u001b[0m \u001b[1m0s\u001b[0m 49ms/step\n",
      "\u001b[1m1/1\u001b[0m \u001b[32m━━━━━━━━━━━━━━━━━━━━\u001b[0m\u001b[37m\u001b[0m \u001b[1m0s\u001b[0m 52ms/step\n",
      "\u001b[1m1/1\u001b[0m \u001b[32m━━━━━━━━━━━━━━━━━━━━\u001b[0m\u001b[37m\u001b[0m \u001b[1m0s\u001b[0m 54ms/step\n",
      "\u001b[1m1/1\u001b[0m \u001b[32m━━━━━━━━━━━━━━━━━━━━\u001b[0m\u001b[37m\u001b[0m \u001b[1m0s\u001b[0m 40ms/step\n",
      "\u001b[1m1/1\u001b[0m \u001b[32m━━━━━━━━━━━━━━━━━━━━\u001b[0m\u001b[37m\u001b[0m \u001b[1m0s\u001b[0m 48ms/step\n",
      "\u001b[1m1/1\u001b[0m \u001b[32m━━━━━━━━━━━━━━━━━━━━\u001b[0m\u001b[37m\u001b[0m \u001b[1m0s\u001b[0m 53ms/step\n",
      "\u001b[1m1/1\u001b[0m \u001b[32m━━━━━━━━━━━━━━━━━━━━\u001b[0m\u001b[37m\u001b[0m \u001b[1m0s\u001b[0m 54ms/step\n",
      "\u001b[1m1/1\u001b[0m \u001b[32m━━━━━━━━━━━━━━━━━━━━\u001b[0m\u001b[37m\u001b[0m \u001b[1m0s\u001b[0m 54ms/step\n",
      "\u001b[1m1/1\u001b[0m \u001b[32m━━━━━━━━━━━━━━━━━━━━\u001b[0m\u001b[37m\u001b[0m \u001b[1m0s\u001b[0m 56ms/step\n",
      "\u001b[1m1/1\u001b[0m \u001b[32m━━━━━━━━━━━━━━━━━━━━\u001b[0m\u001b[37m\u001b[0m \u001b[1m0s\u001b[0m 67ms/step\n",
      "\u001b[1m1/1\u001b[0m \u001b[32m━━━━━━━━━━━━━━━━━━━━\u001b[0m\u001b[37m\u001b[0m \u001b[1m0s\u001b[0m 53ms/step\n",
      "\u001b[1m1/1\u001b[0m \u001b[32m━━━━━━━━━━━━━━━━━━━━\u001b[0m\u001b[37m\u001b[0m \u001b[1m0s\u001b[0m 53ms/step\n",
      "\u001b[1m1/1\u001b[0m \u001b[32m━━━━━━━━━━━━━━━━━━━━\u001b[0m\u001b[37m\u001b[0m \u001b[1m0s\u001b[0m 54ms/step\n",
      "\u001b[1m1/1\u001b[0m \u001b[32m━━━━━━━━━━━━━━━━━━━━\u001b[0m\u001b[37m\u001b[0m \u001b[1m0s\u001b[0m 53ms/step\n",
      "\u001b[1m1/1\u001b[0m \u001b[32m━━━━━━━━━━━━━━━━━━━━\u001b[0m\u001b[37m\u001b[0m \u001b[1m0s\u001b[0m 54ms/step\n",
      "\u001b[1m1/1\u001b[0m \u001b[32m━━━━━━━━━━━━━━━━━━━━\u001b[0m\u001b[37m\u001b[0m \u001b[1m0s\u001b[0m 53ms/step\n",
      "\u001b[1m1/1\u001b[0m \u001b[32m━━━━━━━━━━━━━━━━━━━━\u001b[0m\u001b[37m\u001b[0m \u001b[1m0s\u001b[0m 54ms/step\n",
      "\u001b[1m1/1\u001b[0m \u001b[32m━━━━━━━━━━━━━━━━━━━━\u001b[0m\u001b[37m\u001b[0m \u001b[1m0s\u001b[0m 54ms/step\n",
      "\u001b[1m1/1\u001b[0m \u001b[32m━━━━━━━━━━━━━━━━━━━━\u001b[0m\u001b[37m\u001b[0m \u001b[1m0s\u001b[0m 47ms/step\n",
      "\u001b[1m1/1\u001b[0m \u001b[32m━━━━━━━━━━━━━━━━━━━━\u001b[0m\u001b[37m\u001b[0m \u001b[1m0s\u001b[0m 54ms/step\n",
      "\u001b[1m1/1\u001b[0m \u001b[32m━━━━━━━━━━━━━━━━━━━━\u001b[0m\u001b[37m\u001b[0m \u001b[1m0s\u001b[0m 67ms/step\n",
      "\u001b[1m1/1\u001b[0m \u001b[32m━━━━━━━━━━━━━━━━━━━━\u001b[0m\u001b[37m\u001b[0m \u001b[1m0s\u001b[0m 56ms/step\n",
      "\u001b[1m1/1\u001b[0m \u001b[32m━━━━━━━━━━━━━━━━━━━━\u001b[0m\u001b[37m\u001b[0m \u001b[1m0s\u001b[0m 52ms/step\n",
      "\u001b[1m1/1\u001b[0m \u001b[32m━━━━━━━━━━━━━━━━━━━━\u001b[0m\u001b[37m\u001b[0m \u001b[1m0s\u001b[0m 54ms/step\n",
      "\u001b[1m1/1\u001b[0m \u001b[32m━━━━━━━━━━━━━━━━━━━━\u001b[0m\u001b[37m\u001b[0m \u001b[1m0s\u001b[0m 54ms/step\n",
      "\u001b[1m1/1\u001b[0m \u001b[32m━━━━━━━━━━━━━━━━━━━━\u001b[0m\u001b[37m\u001b[0m \u001b[1m0s\u001b[0m 54ms/step\n",
      "\u001b[1m1/1\u001b[0m \u001b[32m━━━━━━━━━━━━━━━━━━━━\u001b[0m\u001b[37m\u001b[0m \u001b[1m0s\u001b[0m 54ms/step\n",
      "\u001b[1m1/1\u001b[0m \u001b[32m━━━━━━━━━━━━━━━━━━━━\u001b[0m\u001b[37m\u001b[0m \u001b[1m0s\u001b[0m 40ms/step\n",
      "\u001b[1m1/1\u001b[0m \u001b[32m━━━━━━━━━━━━━━━━━━━━\u001b[0m\u001b[37m\u001b[0m \u001b[1m0s\u001b[0m 54ms/step\n",
      "\u001b[1m1/1\u001b[0m \u001b[32m━━━━━━━━━━━━━━━━━━━━\u001b[0m\u001b[37m\u001b[0m \u001b[1m0s\u001b[0m 53ms/step\n",
      "\u001b[1m1/1\u001b[0m \u001b[32m━━━━━━━━━━━━━━━━━━━━\u001b[0m\u001b[37m\u001b[0m \u001b[1m0s\u001b[0m 54ms/step\n",
      "\u001b[1m1/1\u001b[0m \u001b[32m━━━━━━━━━━━━━━━━━━━━\u001b[0m\u001b[37m\u001b[0m \u001b[1m0s\u001b[0m 62ms/step\n",
      "\u001b[1m1/1\u001b[0m \u001b[32m━━━━━━━━━━━━━━━━━━━━\u001b[0m\u001b[37m\u001b[0m \u001b[1m0s\u001b[0m 53ms/step\n",
      "\u001b[1m1/1\u001b[0m \u001b[32m━━━━━━━━━━━━━━━━━━━━\u001b[0m\u001b[37m\u001b[0m \u001b[1m0s\u001b[0m 54ms/step\n",
      "\u001b[1m1/1\u001b[0m \u001b[32m━━━━━━━━━━━━━━━━━━━━\u001b[0m\u001b[37m\u001b[0m \u001b[1m0s\u001b[0m 54ms/step\n",
      "\u001b[1m1/1\u001b[0m \u001b[32m━━━━━━━━━━━━━━━━━━━━\u001b[0m\u001b[37m\u001b[0m \u001b[1m0s\u001b[0m 54ms/step\n",
      "\u001b[1m1/1\u001b[0m \u001b[32m━━━━━━━━━━━━━━━━━━━━\u001b[0m\u001b[37m\u001b[0m \u001b[1m0s\u001b[0m 54ms/step\n",
      "\u001b[1m1/1\u001b[0m \u001b[32m━━━━━━━━━━━━━━━━━━━━\u001b[0m\u001b[37m\u001b[0m \u001b[1m0s\u001b[0m 53ms/step\n",
      "\u001b[1m1/1\u001b[0m \u001b[32m━━━━━━━━━━━━━━━━━━━━\u001b[0m\u001b[37m\u001b[0m \u001b[1m0s\u001b[0m 42ms/step\n",
      "\u001b[1m1/1\u001b[0m \u001b[32m━━━━━━━━━━━━━━━━━━━━\u001b[0m\u001b[37m\u001b[0m \u001b[1m0s\u001b[0m 54ms/step\n",
      "\u001b[1m1/1\u001b[0m \u001b[32m━━━━━━━━━━━━━━━━━━━━\u001b[0m\u001b[37m\u001b[0m \u001b[1m0s\u001b[0m 54ms/step\n",
      "\u001b[1m1/1\u001b[0m \u001b[32m━━━━━━━━━━━━━━━━━━━━\u001b[0m\u001b[37m\u001b[0m \u001b[1m0s\u001b[0m 54ms/step\n",
      "\u001b[1m1/1\u001b[0m \u001b[32m━━━━━━━━━━━━━━━━━━━━\u001b[0m\u001b[37m\u001b[0m \u001b[1m0s\u001b[0m 63ms/step\n",
      "\u001b[1m1/1\u001b[0m \u001b[32m━━━━━━━━━━━━━━━━━━━━\u001b[0m\u001b[37m\u001b[0m \u001b[1m0s\u001b[0m 50ms/step\n",
      "\u001b[1m1/1\u001b[0m \u001b[32m━━━━━━━━━━━━━━━━━━━━\u001b[0m\u001b[37m\u001b[0m \u001b[1m0s\u001b[0m 52ms/step\n",
      "\u001b[1m1/1\u001b[0m \u001b[32m━━━━━━━━━━━━━━━━━━━━\u001b[0m\u001b[37m\u001b[0m \u001b[1m0s\u001b[0m 53ms/step\n",
      "\u001b[1m1/1\u001b[0m \u001b[32m━━━━━━━━━━━━━━━━━━━━\u001b[0m\u001b[37m\u001b[0m \u001b[1m0s\u001b[0m 41ms/step\n",
      "\u001b[1m1/1\u001b[0m \u001b[32m━━━━━━━━━━━━━━━━━━━━\u001b[0m\u001b[37m\u001b[0m \u001b[1m0s\u001b[0m 62ms/step\n",
      "\u001b[1m1/1\u001b[0m \u001b[32m━━━━━━━━━━━━━━━━━━━━\u001b[0m\u001b[37m\u001b[0m \u001b[1m0s\u001b[0m 40ms/step\n",
      "\u001b[1m1/1\u001b[0m \u001b[32m━━━━━━━━━━━━━━━━━━━━\u001b[0m\u001b[37m\u001b[0m \u001b[1m0s\u001b[0m 67ms/step\n",
      "\u001b[1m1/1\u001b[0m \u001b[32m━━━━━━━━━━━━━━━━━━━━\u001b[0m\u001b[37m\u001b[0m \u001b[1m0s\u001b[0m 67ms/step\n",
      "\u001b[1m1/1\u001b[0m \u001b[32m━━━━━━━━━━━━━━━━━━━━\u001b[0m\u001b[37m\u001b[0m \u001b[1m0s\u001b[0m 64ms/step\n",
      "\u001b[1m1/1\u001b[0m \u001b[32m━━━━━━━━━━━━━━━━━━━━\u001b[0m\u001b[37m\u001b[0m \u001b[1m0s\u001b[0m 48ms/step\n",
      "\u001b[1m1/1\u001b[0m \u001b[32m━━━━━━━━━━━━━━━━━━━━\u001b[0m\u001b[37m\u001b[0m \u001b[1m0s\u001b[0m 54ms/step\n",
      "\u001b[1m1/1\u001b[0m \u001b[32m━━━━━━━━━━━━━━━━━━━━\u001b[0m\u001b[37m\u001b[0m \u001b[1m0s\u001b[0m 53ms/step\n",
      "\u001b[1m1/1\u001b[0m \u001b[32m━━━━━━━━━━━━━━━━━━━━\u001b[0m\u001b[37m\u001b[0m \u001b[1m0s\u001b[0m 53ms/step\n",
      "\u001b[1m1/1\u001b[0m \u001b[32m━━━━━━━━━━━━━━━━━━━━\u001b[0m\u001b[37m\u001b[0m \u001b[1m0s\u001b[0m 64ms/step\n",
      "\u001b[1m1/1\u001b[0m \u001b[32m━━━━━━━━━━━━━━━━━━━━\u001b[0m\u001b[37m\u001b[0m \u001b[1m0s\u001b[0m 54ms/step\n",
      "\u001b[1m1/1\u001b[0m \u001b[32m━━━━━━━━━━━━━━━━━━━━\u001b[0m\u001b[37m\u001b[0m \u001b[1m0s\u001b[0m 54ms/step\n",
      "\u001b[1m1/1\u001b[0m \u001b[32m━━━━━━━━━━━━━━━━━━━━\u001b[0m\u001b[37m\u001b[0m \u001b[1m0s\u001b[0m 54ms/step\n",
      "\u001b[1m1/1\u001b[0m \u001b[32m━━━━━━━━━━━━━━━━━━━━\u001b[0m\u001b[37m\u001b[0m \u001b[1m0s\u001b[0m 70ms/step\n",
      "\u001b[1m1/1\u001b[0m \u001b[32m━━━━━━━━━━━━━━━━━━━━\u001b[0m\u001b[37m\u001b[0m \u001b[1m0s\u001b[0m 54ms/step\n",
      "\u001b[1m1/1\u001b[0m \u001b[32m━━━━━━━━━━━━━━━━━━━━\u001b[0m\u001b[37m\u001b[0m \u001b[1m0s\u001b[0m 54ms/step\n",
      "\u001b[1m1/1\u001b[0m \u001b[32m━━━━━━━━━━━━━━━━━━━━\u001b[0m\u001b[37m\u001b[0m \u001b[1m0s\u001b[0m 49ms/step\n",
      "\u001b[1m1/1\u001b[0m \u001b[32m━━━━━━━━━━━━━━━━━━━━\u001b[0m\u001b[37m\u001b[0m \u001b[1m0s\u001b[0m 44ms/step\n",
      "\u001b[1m1/1\u001b[0m \u001b[32m━━━━━━━━━━━━━━━━━━━━\u001b[0m\u001b[37m\u001b[0m \u001b[1m0s\u001b[0m 54ms/step\n",
      "\u001b[1m1/1\u001b[0m \u001b[32m━━━━━━━━━━━━━━━━━━━━\u001b[0m\u001b[37m\u001b[0m \u001b[1m0s\u001b[0m 54ms/step\n",
      "\u001b[1m1/1\u001b[0m \u001b[32m━━━━━━━━━━━━━━━━━━━━\u001b[0m\u001b[37m\u001b[0m \u001b[1m0s\u001b[0m 64ms/step\n",
      "\u001b[1m1/1\u001b[0m \u001b[32m━━━━━━━━━━━━━━━━━━━━\u001b[0m\u001b[37m\u001b[0m \u001b[1m0s\u001b[0m 50ms/step\n",
      "\u001b[1m1/1\u001b[0m \u001b[32m━━━━━━━━━━━━━━━━━━━━\u001b[0m\u001b[37m\u001b[0m \u001b[1m0s\u001b[0m 53ms/step\n",
      "\u001b[1m1/1\u001b[0m \u001b[32m━━━━━━━━━━━━━━━━━━━━\u001b[0m\u001b[37m\u001b[0m \u001b[1m0s\u001b[0m 53ms/step\n",
      "\u001b[1m1/1\u001b[0m \u001b[32m━━━━━━━━━━━━━━━━━━━━\u001b[0m\u001b[37m\u001b[0m \u001b[1m0s\u001b[0m 53ms/step\n",
      "\u001b[1m1/1\u001b[0m \u001b[32m━━━━━━━━━━━━━━━━━━━━\u001b[0m\u001b[37m\u001b[0m \u001b[1m0s\u001b[0m 51ms/step\n",
      "\u001b[1m1/1\u001b[0m \u001b[32m━━━━━━━━━━━━━━━━━━━━\u001b[0m\u001b[37m\u001b[0m \u001b[1m0s\u001b[0m 46ms/step\n",
      "\u001b[1m1/1\u001b[0m \u001b[32m━━━━━━━━━━━━━━━━━━━━\u001b[0m\u001b[37m\u001b[0m \u001b[1m0s\u001b[0m 69ms/step\n",
      "\u001b[1m1/1\u001b[0m \u001b[32m━━━━━━━━━━━━━━━━━━━━\u001b[0m\u001b[37m\u001b[0m \u001b[1m0s\u001b[0m 54ms/step\n",
      "\u001b[1m1/1\u001b[0m \u001b[32m━━━━━━━━━━━━━━━━━━━━\u001b[0m\u001b[37m\u001b[0m \u001b[1m0s\u001b[0m 54ms/step\n",
      "\u001b[1m1/1\u001b[0m \u001b[32m━━━━━━━━━━━━━━━━━━━━\u001b[0m\u001b[37m\u001b[0m \u001b[1m0s\u001b[0m 42ms/step\n",
      "\u001b[1m1/1\u001b[0m \u001b[32m━━━━━━━━━━━━━━━━━━━━\u001b[0m\u001b[37m\u001b[0m \u001b[1m0s\u001b[0m 54ms/step\n",
      "\u001b[1m1/1\u001b[0m \u001b[32m━━━━━━━━━━━━━━━━━━━━\u001b[0m\u001b[37m\u001b[0m \u001b[1m0s\u001b[0m 53ms/step\n",
      "\u001b[1m1/1\u001b[0m \u001b[32m━━━━━━━━━━━━━━━━━━━━\u001b[0m\u001b[37m\u001b[0m \u001b[1m0s\u001b[0m 53ms/step\n",
      "\u001b[1m1/1\u001b[0m \u001b[32m━━━━━━━━━━━━━━━━━━━━\u001b[0m\u001b[37m\u001b[0m \u001b[1m0s\u001b[0m 62ms/step\n",
      "\u001b[1m1/1\u001b[0m \u001b[32m━━━━━━━━━━━━━━━━━━━━\u001b[0m\u001b[37m\u001b[0m \u001b[1m0s\u001b[0m 53ms/step\n",
      "\u001b[1m1/1\u001b[0m \u001b[32m━━━━━━━━━━━━━━━━━━━━\u001b[0m\u001b[37m\u001b[0m \u001b[1m0s\u001b[0m 54ms/step\n",
      "\u001b[1m1/1\u001b[0m \u001b[32m━━━━━━━━━━━━━━━━━━━━\u001b[0m\u001b[37m\u001b[0m \u001b[1m0s\u001b[0m 54ms/step\n",
      "\u001b[1m1/1\u001b[0m \u001b[32m━━━━━━━━━━━━━━━━━━━━\u001b[0m\u001b[37m\u001b[0m \u001b[1m0s\u001b[0m 54ms/step\n",
      "\u001b[1m1/1\u001b[0m \u001b[32m━━━━━━━━━━━━━━━━━━━━\u001b[0m\u001b[37m\u001b[0m \u001b[1m0s\u001b[0m 60ms/step\n",
      "\u001b[1m1/1\u001b[0m \u001b[32m━━━━━━━━━━━━━━━━━━━━\u001b[0m\u001b[37m\u001b[0m \u001b[1m0s\u001b[0m 54ms/step\n",
      "\u001b[1m1/1\u001b[0m \u001b[32m━━━━━━━━━━━━━━━━━━━━\u001b[0m\u001b[37m\u001b[0m \u001b[1m0s\u001b[0m 53ms/step\n",
      "\u001b[1m1/1\u001b[0m \u001b[32m━━━━━━━━━━━━━━━━━━━━\u001b[0m\u001b[37m\u001b[0m \u001b[1m0s\u001b[0m 53ms/step\n",
      "\u001b[1m1/1\u001b[0m \u001b[32m━━━━━━━━━━━━━━━━━━━━\u001b[0m\u001b[37m\u001b[0m \u001b[1m0s\u001b[0m 67ms/step\n",
      "\u001b[1m1/1\u001b[0m \u001b[32m━━━━━━━━━━━━━━━━━━━━\u001b[0m\u001b[37m\u001b[0m \u001b[1m0s\u001b[0m 47ms/step\n",
      "\u001b[1m1/1\u001b[0m \u001b[32m━━━━━━━━━━━━━━━━━━━━\u001b[0m\u001b[37m\u001b[0m \u001b[1m0s\u001b[0m 67ms/step\n",
      "\u001b[1m1/1\u001b[0m \u001b[32m━━━━━━━━━━━━━━━━━━━━\u001b[0m\u001b[37m\u001b[0m \u001b[1m0s\u001b[0m 53ms/step\n",
      "\u001b[1m1/1\u001b[0m \u001b[32m━━━━━━━━━━━━━━━━━━━━\u001b[0m\u001b[37m\u001b[0m \u001b[1m0s\u001b[0m 40ms/step\n",
      "\u001b[1m1/1\u001b[0m \u001b[32m━━━━━━━━━━━━━━━━━━━━\u001b[0m\u001b[37m\u001b[0m \u001b[1m0s\u001b[0m 65ms/step\n",
      "\u001b[1m1/1\u001b[0m \u001b[32m━━━━━━━━━━━━━━━━━━━━\u001b[0m\u001b[37m\u001b[0m \u001b[1m0s\u001b[0m 54ms/step\n",
      "\u001b[1m1/1\u001b[0m \u001b[32m━━━━━━━━━━━━━━━━━━━━\u001b[0m\u001b[37m\u001b[0m \u001b[1m0s\u001b[0m 53ms/step\n",
      "\u001b[1m1/1\u001b[0m \u001b[32m━━━━━━━━━━━━━━━━━━━━\u001b[0m\u001b[37m\u001b[0m \u001b[1m0s\u001b[0m 54ms/step\n",
      "\u001b[1m1/1\u001b[0m \u001b[32m━━━━━━━━━━━━━━━━━━━━\u001b[0m\u001b[37m\u001b[0m \u001b[1m0s\u001b[0m 62ms/step\n",
      "\u001b[1m1/1\u001b[0m \u001b[32m━━━━━━━━━━━━━━━━━━━━\u001b[0m\u001b[37m\u001b[0m \u001b[1m0s\u001b[0m 53ms/step\n",
      "\u001b[1m1/1\u001b[0m \u001b[32m━━━━━━━━━━━━━━━━━━━━\u001b[0m\u001b[37m\u001b[0m \u001b[1m0s\u001b[0m 40ms/step\n",
      "\u001b[1m1/1\u001b[0m \u001b[32m━━━━━━━━━━━━━━━━━━━━\u001b[0m\u001b[37m\u001b[0m \u001b[1m0s\u001b[0m 54ms/step\n",
      "\u001b[1m1/1\u001b[0m \u001b[32m━━━━━━━━━━━━━━━━━━━━\u001b[0m\u001b[37m\u001b[0m \u001b[1m0s\u001b[0m 54ms/step\n",
      "\u001b[1m1/1\u001b[0m \u001b[32m━━━━━━━━━━━━━━━━━━━━\u001b[0m\u001b[37m\u001b[0m \u001b[1m0s\u001b[0m 57ms/step\n",
      "\u001b[1m1/1\u001b[0m \u001b[32m━━━━━━━━━━━━━━━━━━━━\u001b[0m\u001b[37m\u001b[0m \u001b[1m0s\u001b[0m 54ms/step\n",
      "\u001b[1m1/1\u001b[0m \u001b[32m━━━━━━━━━━━━━━━━━━━━\u001b[0m\u001b[37m\u001b[0m \u001b[1m0s\u001b[0m 54ms/step\n",
      "\u001b[1m1/1\u001b[0m \u001b[32m━━━━━━━━━━━━━━━━━━━━\u001b[0m\u001b[37m\u001b[0m \u001b[1m0s\u001b[0m 55ms/step\n",
      "\u001b[1m1/1\u001b[0m \u001b[32m━━━━━━━━━━━━━━━━━━━━\u001b[0m\u001b[37m\u001b[0m \u001b[1m0s\u001b[0m 53ms/step\n",
      "\u001b[1m1/1\u001b[0m \u001b[32m━━━━━━━━━━━━━━━━━━━━\u001b[0m\u001b[37m\u001b[0m \u001b[1m0s\u001b[0m 54ms/step\n",
      "\u001b[1m1/1\u001b[0m \u001b[32m━━━━━━━━━━━━━━━━━━━━\u001b[0m\u001b[37m\u001b[0m \u001b[1m0s\u001b[0m 54ms/step\n",
      "\u001b[1m1/1\u001b[0m \u001b[32m━━━━━━━━━━━━━━━━━━━━\u001b[0m\u001b[37m\u001b[0m \u001b[1m0s\u001b[0m 50ms/step\n",
      "\u001b[1m1/1\u001b[0m \u001b[32m━━━━━━━━━━━━━━━━━━━━\u001b[0m\u001b[37m\u001b[0m \u001b[1m0s\u001b[0m 54ms/step\n",
      "\u001b[1m1/1\u001b[0m \u001b[32m━━━━━━━━━━━━━━━━━━━━\u001b[0m\u001b[37m\u001b[0m \u001b[1m0s\u001b[0m 53ms/step\n",
      "\u001b[1m1/1\u001b[0m \u001b[32m━━━━━━━━━━━━━━━━━━━━\u001b[0m\u001b[37m\u001b[0m \u001b[1m0s\u001b[0m 54ms/step\n",
      "\u001b[1m1/1\u001b[0m \u001b[32m━━━━━━━━━━━━━━━━━━━━\u001b[0m\u001b[37m\u001b[0m \u001b[1m0s\u001b[0m 64ms/step\n",
      "\u001b[1m1/1\u001b[0m \u001b[32m━━━━━━━━━━━━━━━━━━━━\u001b[0m\u001b[37m\u001b[0m \u001b[1m0s\u001b[0m 49ms/step\n",
      "\u001b[1m1/1\u001b[0m \u001b[32m━━━━━━━━━━━━━━━━━━━━\u001b[0m\u001b[37m\u001b[0m \u001b[1m0s\u001b[0m 54ms/step\n",
      "\u001b[1m1/1\u001b[0m \u001b[32m━━━━━━━━━━━━━━━━━━━━\u001b[0m\u001b[37m\u001b[0m \u001b[1m0s\u001b[0m 54ms/step\n",
      "\u001b[1m1/1\u001b[0m \u001b[32m━━━━━━━━━━━━━━━━━━━━\u001b[0m\u001b[37m\u001b[0m \u001b[1m0s\u001b[0m 53ms/step\n",
      "\u001b[1m1/1\u001b[0m \u001b[32m━━━━━━━━━━━━━━━━━━━━\u001b[0m\u001b[37m\u001b[0m \u001b[1m0s\u001b[0m 51ms/step\n",
      "\u001b[1m1/1\u001b[0m \u001b[32m━━━━━━━━━━━━━━━━━━━━\u001b[0m\u001b[37m\u001b[0m \u001b[1m0s\u001b[0m 54ms/step\n",
      "\u001b[1m1/1\u001b[0m \u001b[32m━━━━━━━━━━━━━━━━━━━━\u001b[0m\u001b[37m\u001b[0m \u001b[1m0s\u001b[0m 54ms/step\n",
      "\u001b[1m1/1\u001b[0m \u001b[32m━━━━━━━━━━━━━━━━━━━━\u001b[0m\u001b[37m\u001b[0m \u001b[1m0s\u001b[0m 67ms/step\n",
      "\u001b[1m1/1\u001b[0m \u001b[32m━━━━━━━━━━━━━━━━━━━━\u001b[0m\u001b[37m\u001b[0m \u001b[1m0s\u001b[0m 67ms/step\n",
      "\u001b[1m1/1\u001b[0m \u001b[32m━━━━━━━━━━━━━━━━━━━━\u001b[0m\u001b[37m\u001b[0m \u001b[1m0s\u001b[0m 53ms/step\n",
      "\u001b[1m1/1\u001b[0m \u001b[32m━━━━━━━━━━━━━━━━━━━━\u001b[0m\u001b[37m\u001b[0m \u001b[1m0s\u001b[0m 52ms/step\n",
      "\u001b[1m1/1\u001b[0m \u001b[32m━━━━━━━━━━━━━━━━━━━━\u001b[0m\u001b[37m\u001b[0m \u001b[1m0s\u001b[0m 54ms/step\n",
      "\u001b[1m1/1\u001b[0m \u001b[32m━━━━━━━━━━━━━━━━━━━━\u001b[0m\u001b[37m\u001b[0m \u001b[1m0s\u001b[0m 54ms/step\n",
      "\u001b[1m1/1\u001b[0m \u001b[32m━━━━━━━━━━━━━━━━━━━━\u001b[0m\u001b[37m\u001b[0m \u001b[1m0s\u001b[0m 50ms/step\n",
      "\u001b[1m1/1\u001b[0m \u001b[32m━━━━━━━━━━━━━━━━━━━━\u001b[0m\u001b[37m\u001b[0m \u001b[1m0s\u001b[0m 54ms/step\n",
      "\u001b[1m1/1\u001b[0m \u001b[32m━━━━━━━━━━━━━━━━━━━━\u001b[0m\u001b[37m\u001b[0m \u001b[1m0s\u001b[0m 53ms/step\n",
      "\u001b[1m1/1\u001b[0m \u001b[32m━━━━━━━━━━━━━━━━━━━━\u001b[0m\u001b[37m\u001b[0m \u001b[1m0s\u001b[0m 53ms/step\n",
      "\u001b[1m1/1\u001b[0m \u001b[32m━━━━━━━━━━━━━━━━━━━━\u001b[0m\u001b[37m\u001b[0m \u001b[1m0s\u001b[0m 57ms/step\n",
      "\u001b[1m1/1\u001b[0m \u001b[32m━━━━━━━━━━━━━━━━━━━━\u001b[0m\u001b[37m\u001b[0m \u001b[1m0s\u001b[0m 54ms/step\n",
      "\u001b[1m1/1\u001b[0m \u001b[32m━━━━━━━━━━━━━━━━━━━━\u001b[0m\u001b[37m\u001b[0m \u001b[1m0s\u001b[0m 54ms/step\n",
      "\u001b[1m1/1\u001b[0m \u001b[32m━━━━━━━━━━━━━━━━━━━━\u001b[0m\u001b[37m\u001b[0m \u001b[1m0s\u001b[0m 47ms/step\n",
      "\u001b[1m1/1\u001b[0m \u001b[32m━━━━━━━━━━━━━━━━━━━━\u001b[0m\u001b[37m\u001b[0m \u001b[1m0s\u001b[0m 53ms/step\n",
      "\u001b[1m1/1\u001b[0m \u001b[32m━━━━━━━━━━━━━━━━━━━━\u001b[0m\u001b[37m\u001b[0m \u001b[1m0s\u001b[0m 54ms/step\n",
      "\u001b[1m1/1\u001b[0m \u001b[32m━━━━━━━━━━━━━━━━━━━━\u001b[0m\u001b[37m\u001b[0m \u001b[1m0s\u001b[0m 54ms/step\n",
      "\u001b[1m1/1\u001b[0m \u001b[32m━━━━━━━━━━━━━━━━━━━━\u001b[0m\u001b[37m\u001b[0m \u001b[1m0s\u001b[0m 67ms/step\n",
      "\u001b[1m1/1\u001b[0m \u001b[32m━━━━━━━━━━━━━━━━━━━━\u001b[0m\u001b[37m\u001b[0m \u001b[1m0s\u001b[0m 48ms/step\n",
      "\u001b[1m1/1\u001b[0m \u001b[32m━━━━━━━━━━━━━━━━━━━━\u001b[0m\u001b[37m\u001b[0m \u001b[1m0s\u001b[0m 66ms/step\n",
      "\u001b[1m1/1\u001b[0m \u001b[32m━━━━━━━━━━━━━━━━━━━━\u001b[0m\u001b[37m\u001b[0m \u001b[1m0s\u001b[0m 54ms/step\n",
      "\u001b[1m1/1\u001b[0m \u001b[32m━━━━━━━━━━━━━━━━━━━━\u001b[0m\u001b[37m\u001b[0m \u001b[1m0s\u001b[0m 54ms/step\n",
      "\u001b[1m1/1\u001b[0m \u001b[32m━━━━━━━━━━━━━━━━━━━━\u001b[0m\u001b[37m\u001b[0m \u001b[1m0s\u001b[0m 54ms/step\n",
      "\u001b[1m1/1\u001b[0m \u001b[32m━━━━━━━━━━━━━━━━━━━━\u001b[0m\u001b[37m\u001b[0m \u001b[1m0s\u001b[0m 54ms/step\n",
      "\u001b[1m1/1\u001b[0m \u001b[32m━━━━━━━━━━━━━━━━━━━━\u001b[0m\u001b[37m\u001b[0m \u001b[1m0s\u001b[0m 55ms/step\n",
      "\u001b[1m1/1\u001b[0m \u001b[32m━━━━━━━━━━━━━━━━━━━━\u001b[0m\u001b[37m\u001b[0m \u001b[1m0s\u001b[0m 67ms/step\n",
      "\u001b[1m1/1\u001b[0m \u001b[32m━━━━━━━━━━━━━━━━━━━━\u001b[0m\u001b[37m\u001b[0m \u001b[1m0s\u001b[0m 69ms/step\n",
      "\u001b[1m1/1\u001b[0m \u001b[32m━━━━━━━━━━━━━━━━━━━━\u001b[0m\u001b[37m\u001b[0m \u001b[1m0s\u001b[0m 53ms/step\n",
      "\u001b[1m1/1\u001b[0m \u001b[32m━━━━━━━━━━━━━━━━━━━━\u001b[0m\u001b[37m\u001b[0m \u001b[1m0s\u001b[0m 54ms/step\n",
      "\u001b[1m1/1\u001b[0m \u001b[32m━━━━━━━━━━━━━━━━━━━━\u001b[0m\u001b[37m\u001b[0m \u001b[1m0s\u001b[0m 47ms/step\n",
      "\u001b[1m1/1\u001b[0m \u001b[32m━━━━━━━━━━━━━━━━━━━━\u001b[0m\u001b[37m\u001b[0m \u001b[1m0s\u001b[0m 67ms/step\n",
      "\u001b[1m1/1\u001b[0m \u001b[32m━━━━━━━━━━━━━━━━━━━━\u001b[0m\u001b[37m\u001b[0m \u001b[1m0s\u001b[0m 40ms/step\n",
      "\u001b[1m1/1\u001b[0m \u001b[32m━━━━━━━━━━━━━━━━━━━━\u001b[0m\u001b[37m\u001b[0m \u001b[1m0s\u001b[0m 53ms/step\n",
      "\u001b[1m1/1\u001b[0m \u001b[32m━━━━━━━━━━━━━━━━━━━━\u001b[0m\u001b[37m\u001b[0m \u001b[1m0s\u001b[0m 50ms/step\n",
      "\u001b[1m1/1\u001b[0m \u001b[32m━━━━━━━━━━━━━━━━━━━━\u001b[0m\u001b[37m\u001b[0m \u001b[1m0s\u001b[0m 53ms/step\n",
      "\u001b[1m1/1\u001b[0m \u001b[32m━━━━━━━━━━━━━━━━━━━━\u001b[0m\u001b[37m\u001b[0m \u001b[1m0s\u001b[0m 54ms/step\n",
      "\u001b[1m1/1\u001b[0m \u001b[32m━━━━━━━━━━━━━━━━━━━━\u001b[0m\u001b[37m\u001b[0m \u001b[1m0s\u001b[0m 53ms/step\n",
      "\u001b[1m1/1\u001b[0m \u001b[32m━━━━━━━━━━━━━━━━━━━━\u001b[0m\u001b[37m\u001b[0m \u001b[1m0s\u001b[0m 63ms/step\n",
      "\u001b[1m1/1\u001b[0m \u001b[32m━━━━━━━━━━━━━━━━━━━━\u001b[0m\u001b[37m\u001b[0m \u001b[1m0s\u001b[0m 51ms/step\n",
      "\u001b[1m1/1\u001b[0m \u001b[32m━━━━━━━━━━━━━━━━━━━━\u001b[0m\u001b[37m\u001b[0m \u001b[1m0s\u001b[0m 53ms/step\n",
      "\u001b[1m1/1\u001b[0m \u001b[32m━━━━━━━━━━━━━━━━━━━━\u001b[0m\u001b[37m\u001b[0m \u001b[1m0s\u001b[0m 53ms/step\n",
      "\u001b[1m1/1\u001b[0m \u001b[32m━━━━━━━━━━━━━━━━━━━━\u001b[0m\u001b[37m\u001b[0m \u001b[1m0s\u001b[0m 54ms/step\n",
      "\u001b[1m1/1\u001b[0m \u001b[32m━━━━━━━━━━━━━━━━━━━━\u001b[0m\u001b[37m\u001b[0m \u001b[1m0s\u001b[0m 54ms/step\n",
      "\u001b[1m1/1\u001b[0m \u001b[32m━━━━━━━━━━━━━━━━━━━━\u001b[0m\u001b[37m\u001b[0m \u001b[1m0s\u001b[0m 53ms/step\n",
      "\u001b[1m1/1\u001b[0m \u001b[32m━━━━━━━━━━━━━━━━━━━━\u001b[0m\u001b[37m\u001b[0m \u001b[1m0s\u001b[0m 52ms/step\n",
      "\u001b[1m1/1\u001b[0m \u001b[32m━━━━━━━━━━━━━━━━━━━━\u001b[0m\u001b[37m\u001b[0m \u001b[1m0s\u001b[0m 44ms/step\n",
      "\u001b[1m1/1\u001b[0m \u001b[32m━━━━━━━━━━━━━━━━━━━━\u001b[0m\u001b[37m\u001b[0m \u001b[1m0s\u001b[0m 53ms/step\n",
      "\u001b[1m1/1\u001b[0m \u001b[32m━━━━━━━━━━━━━━━━━━━━\u001b[0m\u001b[37m\u001b[0m \u001b[1m0s\u001b[0m 54ms/step\n",
      "\u001b[1m1/1\u001b[0m \u001b[32m━━━━━━━━━━━━━━━━━━━━\u001b[0m\u001b[37m\u001b[0m \u001b[1m0s\u001b[0m 54ms/step\n",
      "\u001b[1m1/1\u001b[0m \u001b[32m━━━━━━━━━━━━━━━━━━━━\u001b[0m\u001b[37m\u001b[0m \u001b[1m0s\u001b[0m 53ms/step\n",
      "\u001b[1m1/1\u001b[0m \u001b[32m━━━━━━━━━━━━━━━━━━━━\u001b[0m\u001b[37m\u001b[0m \u001b[1m0s\u001b[0m 67ms/step\n",
      "\u001b[1m1/1\u001b[0m \u001b[32m━━━━━━━━━━━━━━━━━━━━\u001b[0m\u001b[37m\u001b[0m \u001b[1m0s\u001b[0m 67ms/step\n",
      "\u001b[1m1/1\u001b[0m \u001b[32m━━━━━━━━━━━━━━━━━━━━\u001b[0m\u001b[37m\u001b[0m \u001b[1m0s\u001b[0m 65ms/step\n",
      "\u001b[1m1/1\u001b[0m \u001b[32m━━━━━━━━━━━━━━━━━━━━\u001b[0m\u001b[37m\u001b[0m \u001b[1m0s\u001b[0m 52ms/step\n",
      "\u001b[1m1/1\u001b[0m \u001b[32m━━━━━━━━━━━━━━━━━━━━\u001b[0m\u001b[37m\u001b[0m \u001b[1m0s\u001b[0m 65ms/step\n",
      "\u001b[1m1/1\u001b[0m \u001b[32m━━━━━━━━━━━━━━━━━━━━\u001b[0m\u001b[37m\u001b[0m \u001b[1m0s\u001b[0m 53ms/step\n",
      "\u001b[1m1/1\u001b[0m \u001b[32m━━━━━━━━━━━━━━━━━━━━\u001b[0m\u001b[37m\u001b[0m \u001b[1m0s\u001b[0m 53ms/step\n",
      "\u001b[1m1/1\u001b[0m \u001b[32m━━━━━━━━━━━━━━━━━━━━\u001b[0m\u001b[37m\u001b[0m \u001b[1m0s\u001b[0m 54ms/step\n",
      "\u001b[1m1/1\u001b[0m \u001b[32m━━━━━━━━━━━━━━━━━━━━\u001b[0m\u001b[37m\u001b[0m \u001b[1m0s\u001b[0m 55ms/step\n",
      "\u001b[1m1/1\u001b[0m \u001b[32m━━━━━━━━━━━━━━━━━━━━\u001b[0m\u001b[37m\u001b[0m \u001b[1m0s\u001b[0m 54ms/step\n",
      "\u001b[1m1/1\u001b[0m \u001b[32m━━━━━━━━━━━━━━━━━━━━\u001b[0m\u001b[37m\u001b[0m \u001b[1m0s\u001b[0m 54ms/step\n",
      "\u001b[1m1/1\u001b[0m \u001b[32m━━━━━━━━━━━━━━━━━━━━\u001b[0m\u001b[37m\u001b[0m \u001b[1m0s\u001b[0m 54ms/step\n",
      "\u001b[1m1/1\u001b[0m \u001b[32m━━━━━━━━━━━━━━━━━━━━\u001b[0m\u001b[37m\u001b[0m \u001b[1m0s\u001b[0m 54ms/step\n",
      "\u001b[1m1/1\u001b[0m \u001b[32m━━━━━━━━━━━━━━━━━━━━\u001b[0m\u001b[37m\u001b[0m \u001b[1m0s\u001b[0m 53ms/step\n",
      "\u001b[1m1/1\u001b[0m \u001b[32m━━━━━━━━━━━━━━━━━━━━\u001b[0m\u001b[37m\u001b[0m \u001b[1m0s\u001b[0m 54ms/step\n",
      "\u001b[1m1/1\u001b[0m \u001b[32m━━━━━━━━━━━━━━━━━━━━\u001b[0m\u001b[37m\u001b[0m \u001b[1m0s\u001b[0m 54ms/step\n",
      "\u001b[1m1/1\u001b[0m \u001b[32m━━━━━━━━━━━━━━━━━━━━\u001b[0m\u001b[37m\u001b[0m \u001b[1m0s\u001b[0m 53ms/step\n",
      "\u001b[1m1/1\u001b[0m \u001b[32m━━━━━━━━━━━━━━━━━━━━\u001b[0m\u001b[37m\u001b[0m \u001b[1m0s\u001b[0m 60ms/step\n",
      "\u001b[1m1/1\u001b[0m \u001b[32m━━━━━━━━━━━━━━━━━━━━\u001b[0m\u001b[37m\u001b[0m \u001b[1m0s\u001b[0m 53ms/step\n",
      "\u001b[1m1/1\u001b[0m \u001b[32m━━━━━━━━━━━━━━━━━━━━\u001b[0m\u001b[37m\u001b[0m \u001b[1m0s\u001b[0m 54ms/step\n",
      "\u001b[1m1/1\u001b[0m \u001b[32m━━━━━━━━━━━━━━━━━━━━\u001b[0m\u001b[37m\u001b[0m \u001b[1m0s\u001b[0m 54ms/step\n",
      "\u001b[1m1/1\u001b[0m \u001b[32m━━━━━━━━━━━━━━━━━━━━\u001b[0m\u001b[37m\u001b[0m \u001b[1m0s\u001b[0m 73ms/step\n",
      "\u001b[1m1/1\u001b[0m \u001b[32m━━━━━━━━━━━━━━━━━━━━\u001b[0m\u001b[37m\u001b[0m \u001b[1m0s\u001b[0m 54ms/step\n",
      "\u001b[1m1/1\u001b[0m \u001b[32m━━━━━━━━━━━━━━━━━━━━\u001b[0m\u001b[37m\u001b[0m \u001b[1m0s\u001b[0m 73ms/step\n",
      "\u001b[1m1/1\u001b[0m \u001b[32m━━━━━━━━━━━━━━━━━━━━\u001b[0m\u001b[37m\u001b[0m \u001b[1m0s\u001b[0m 66ms/step\n",
      "\u001b[1m1/1\u001b[0m \u001b[32m━━━━━━━━━━━━━━━━━━━━\u001b[0m\u001b[37m\u001b[0m \u001b[1m0s\u001b[0m 60ms/step\n",
      "\u001b[1m1/1\u001b[0m \u001b[32m━━━━━━━━━━━━━━━━━━━━\u001b[0m\u001b[37m\u001b[0m \u001b[1m0s\u001b[0m 50ms/step\n",
      "\u001b[1m1/1\u001b[0m \u001b[32m━━━━━━━━━━━━━━━━━━━━\u001b[0m\u001b[37m\u001b[0m \u001b[1m0s\u001b[0m 54ms/step\n",
      "\u001b[1m1/1\u001b[0m \u001b[32m━━━━━━━━━━━━━━━━━━━━\u001b[0m\u001b[37m\u001b[0m \u001b[1m0s\u001b[0m 54ms/step\n",
      "\u001b[1m1/1\u001b[0m \u001b[32m━━━━━━━━━━━━━━━━━━━━\u001b[0m\u001b[37m\u001b[0m \u001b[1m0s\u001b[0m 58ms/step\n",
      "\u001b[1m1/1\u001b[0m \u001b[32m━━━━━━━━━━━━━━━━━━━━\u001b[0m\u001b[37m\u001b[0m \u001b[1m0s\u001b[0m 52ms/step\n",
      "\u001b[1m1/1\u001b[0m \u001b[32m━━━━━━━━━━━━━━━━━━━━\u001b[0m\u001b[37m\u001b[0m \u001b[1m0s\u001b[0m 54ms/step\n",
      "\u001b[1m1/1\u001b[0m \u001b[32m━━━━━━━━━━━━━━━━━━━━\u001b[0m\u001b[37m\u001b[0m \u001b[1m0s\u001b[0m 53ms/step\n",
      "\u001b[1m1/1\u001b[0m \u001b[32m━━━━━━━━━━━━━━━━━━━━\u001b[0m\u001b[37m\u001b[0m \u001b[1m0s\u001b[0m 54ms/step\n",
      "\u001b[1m1/1\u001b[0m \u001b[32m━━━━━━━━━━━━━━━━━━━━\u001b[0m\u001b[37m\u001b[0m \u001b[1m0s\u001b[0m 61ms/step\n",
      "\u001b[1m1/1\u001b[0m \u001b[32m━━━━━━━━━━━━━━━━━━━━\u001b[0m\u001b[37m\u001b[0m \u001b[1m0s\u001b[0m 53ms/step\n",
      "\u001b[1m1/1\u001b[0m \u001b[32m━━━━━━━━━━━━━━━━━━━━\u001b[0m\u001b[37m\u001b[0m \u001b[1m0s\u001b[0m 53ms/step\n",
      "\u001b[1m1/1\u001b[0m \u001b[32m━━━━━━━━━━━━━━━━━━━━\u001b[0m\u001b[37m\u001b[0m \u001b[1m0s\u001b[0m 53ms/step\n",
      "\u001b[1m1/1\u001b[0m \u001b[32m━━━━━━━━━━━━━━━━━━━━\u001b[0m\u001b[37m\u001b[0m \u001b[1m0s\u001b[0m 54ms/step\n",
      "\u001b[1m1/1\u001b[0m \u001b[32m━━━━━━━━━━━━━━━━━━━━\u001b[0m\u001b[37m\u001b[0m \u001b[1m0s\u001b[0m 54ms/step\n",
      "\u001b[1m1/1\u001b[0m \u001b[32m━━━━━━━━━━━━━━━━━━━━\u001b[0m\u001b[37m\u001b[0m \u001b[1m0s\u001b[0m 54ms/step\n",
      "\u001b[1m1/1\u001b[0m \u001b[32m━━━━━━━━━━━━━━━━━━━━\u001b[0m\u001b[37m\u001b[0m \u001b[1m0s\u001b[0m 50ms/step\n",
      "\u001b[1m1/1\u001b[0m \u001b[32m━━━━━━━━━━━━━━━━━━━━\u001b[0m\u001b[37m\u001b[0m \u001b[1m0s\u001b[0m 54ms/step\n",
      "\u001b[1m1/1\u001b[0m \u001b[32m━━━━━━━━━━━━━━━━━━━━\u001b[0m\u001b[37m\u001b[0m \u001b[1m0s\u001b[0m 54ms/step\n",
      "\u001b[1m1/1\u001b[0m \u001b[32m━━━━━━━━━━━━━━━━━━━━\u001b[0m\u001b[37m\u001b[0m \u001b[1m0s\u001b[0m 54ms/step\n",
      "\u001b[1m1/1\u001b[0m \u001b[32m━━━━━━━━━━━━━━━━━━━━\u001b[0m\u001b[37m\u001b[0m \u001b[1m0s\u001b[0m 61ms/step\n",
      "\u001b[1m1/1\u001b[0m \u001b[32m━━━━━━━━━━━━━━━━━━━━\u001b[0m\u001b[37m\u001b[0m \u001b[1m0s\u001b[0m 54ms/step\n",
      "\u001b[1m1/1\u001b[0m \u001b[32m━━━━━━━━━━━━━━━━━━━━\u001b[0m\u001b[37m\u001b[0m \u001b[1m0s\u001b[0m 66ms/step\n",
      "\u001b[1m1/1\u001b[0m \u001b[32m━━━━━━━━━━━━━━━━━━━━\u001b[0m\u001b[37m\u001b[0m \u001b[1m0s\u001b[0m 54ms/step\n",
      "\u001b[1m1/1\u001b[0m \u001b[32m━━━━━━━━━━━━━━━━━━━━\u001b[0m\u001b[37m\u001b[0m \u001b[1m0s\u001b[0m 53ms/step\n",
      "\u001b[1m1/1\u001b[0m \u001b[32m━━━━━━━━━━━━━━━━━━━━\u001b[0m\u001b[37m\u001b[0m \u001b[1m0s\u001b[0m 50ms/step\n",
      "\u001b[1m1/1\u001b[0m \u001b[32m━━━━━━━━━━━━━━━━━━━━\u001b[0m\u001b[37m\u001b[0m \u001b[1m0s\u001b[0m 56ms/step\n",
      "\u001b[1m1/1\u001b[0m \u001b[32m━━━━━━━━━━━━━━━━━━━━\u001b[0m\u001b[37m\u001b[0m \u001b[1m0s\u001b[0m 54ms/step\n",
      "\u001b[1m1/1\u001b[0m \u001b[32m━━━━━━━━━━━━━━━━━━━━\u001b[0m\u001b[37m\u001b[0m \u001b[1m0s\u001b[0m 53ms/step\n",
      "\u001b[1m1/1\u001b[0m \u001b[32m━━━━━━━━━━━━━━━━━━━━\u001b[0m\u001b[37m\u001b[0m \u001b[1m0s\u001b[0m 60ms/step\n",
      "\u001b[1m1/1\u001b[0m \u001b[32m━━━━━━━━━━━━━━━━━━━━\u001b[0m\u001b[37m\u001b[0m \u001b[1m0s\u001b[0m 67ms/step\n",
      "\u001b[1m1/1\u001b[0m \u001b[32m━━━━━━━━━━━━━━━━━━━━\u001b[0m\u001b[37m\u001b[0m \u001b[1m0s\u001b[0m 55ms/step\n",
      "\u001b[1m1/1\u001b[0m \u001b[32m━━━━━━━━━━━━━━━━━━━━\u001b[0m\u001b[37m\u001b[0m \u001b[1m0s\u001b[0m 42ms/step\n",
      "\u001b[1m1/1\u001b[0m \u001b[32m━━━━━━━━━━━━━━━━━━━━\u001b[0m\u001b[37m\u001b[0m \u001b[1m0s\u001b[0m 54ms/step\n",
      "\u001b[1m1/1\u001b[0m \u001b[32m━━━━━━━━━━━━━━━━━━━━\u001b[0m\u001b[37m\u001b[0m \u001b[1m0s\u001b[0m 72ms/step\n",
      "\u001b[1m1/1\u001b[0m \u001b[32m━━━━━━━━━━━━━━━━━━━━\u001b[0m\u001b[37m\u001b[0m \u001b[1m0s\u001b[0m 54ms/step\n",
      "\u001b[1m1/1\u001b[0m \u001b[32m━━━━━━━━━━━━━━━━━━━━\u001b[0m\u001b[37m\u001b[0m \u001b[1m0s\u001b[0m 54ms/step\n",
      "\u001b[1m1/1\u001b[0m \u001b[32m━━━━━━━━━━━━━━━━━━━━\u001b[0m\u001b[37m\u001b[0m \u001b[1m0s\u001b[0m 46ms/step\n",
      "\u001b[1m1/1\u001b[0m \u001b[32m━━━━━━━━━━━━━━━━━━━━\u001b[0m\u001b[37m\u001b[0m \u001b[1m0s\u001b[0m 54ms/step\n",
      "\u001b[1m1/1\u001b[0m \u001b[32m━━━━━━━━━━━━━━━━━━━━\u001b[0m\u001b[37m\u001b[0m \u001b[1m0s\u001b[0m 54ms/step\n",
      "\u001b[1m1/1\u001b[0m \u001b[32m━━━━━━━━━━━━━━━━━━━━\u001b[0m\u001b[37m\u001b[0m \u001b[1m0s\u001b[0m 54ms/step\n",
      "\u001b[1m1/1\u001b[0m \u001b[32m━━━━━━━━━━━━━━━━━━━━\u001b[0m\u001b[37m\u001b[0m \u001b[1m0s\u001b[0m 51ms/step\n",
      "\u001b[1m1/1\u001b[0m \u001b[32m━━━━━━━━━━━━━━━━━━━━\u001b[0m\u001b[37m\u001b[0m \u001b[1m0s\u001b[0m 54ms/step\n",
      "\u001b[1m1/1\u001b[0m \u001b[32m━━━━━━━━━━━━━━━━━━━━\u001b[0m\u001b[37m\u001b[0m \u001b[1m0s\u001b[0m 40ms/step\n",
      "\u001b[1m1/1\u001b[0m \u001b[32m━━━━━━━━━━━━━━━━━━━━\u001b[0m\u001b[37m\u001b[0m \u001b[1m0s\u001b[0m 54ms/step\n",
      "\u001b[1m1/1\u001b[0m \u001b[32m━━━━━━━━━━━━━━━━━━━━\u001b[0m\u001b[37m\u001b[0m \u001b[1m0s\u001b[0m 54ms/step\n",
      "\u001b[1m1/1\u001b[0m \u001b[32m━━━━━━━━━━━━━━━━━━━━\u001b[0m\u001b[37m\u001b[0m \u001b[1m0s\u001b[0m 53ms/step\n",
      "\u001b[1m1/1\u001b[0m \u001b[32m━━━━━━━━━━━━━━━━━━━━\u001b[0m\u001b[37m\u001b[0m \u001b[1m0s\u001b[0m 54ms/step\n",
      "\u001b[1m1/1\u001b[0m \u001b[32m━━━━━━━━━━━━━━━━━━━━\u001b[0m\u001b[37m\u001b[0m \u001b[1m0s\u001b[0m 54ms/step\n",
      "\u001b[1m1/1\u001b[0m \u001b[32m━━━━━━━━━━━━━━━━━━━━\u001b[0m\u001b[37m\u001b[0m \u001b[1m0s\u001b[0m 54ms/step\n",
      "\u001b[1m1/1\u001b[0m \u001b[32m━━━━━━━━━━━━━━━━━━━━\u001b[0m\u001b[37m\u001b[0m \u001b[1m0s\u001b[0m 65ms/step\n",
      "\u001b[1m1/1\u001b[0m \u001b[32m━━━━━━━━━━━━━━━━━━━━\u001b[0m\u001b[37m\u001b[0m \u001b[1m0s\u001b[0m 53ms/step\n",
      "\u001b[1m1/1\u001b[0m \u001b[32m━━━━━━━━━━━━━━━━━━━━\u001b[0m\u001b[37m\u001b[0m \u001b[1m0s\u001b[0m 54ms/step\n",
      "\u001b[1m1/1\u001b[0m \u001b[32m━━━━━━━━━━━━━━━━━━━━\u001b[0m\u001b[37m\u001b[0m \u001b[1m0s\u001b[0m 53ms/step\n",
      "\u001b[1m1/1\u001b[0m \u001b[32m━━━━━━━━━━━━━━━━━━━━\u001b[0m\u001b[37m\u001b[0m \u001b[1m0s\u001b[0m 57ms/step\n",
      "\u001b[1m1/1\u001b[0m \u001b[32m━━━━━━━━━━━━━━━━━━━━\u001b[0m\u001b[37m\u001b[0m \u001b[1m0s\u001b[0m 60ms/step\n",
      "\u001b[1m1/1\u001b[0m \u001b[32m━━━━━━━━━━━━━━━━━━━━\u001b[0m\u001b[37m\u001b[0m \u001b[1m0s\u001b[0m 54ms/step\n",
      "\u001b[1m1/1\u001b[0m \u001b[32m━━━━━━━━━━━━━━━━━━━━\u001b[0m\u001b[37m\u001b[0m \u001b[1m0s\u001b[0m 50ms/step\n",
      "\u001b[1m1/1\u001b[0m \u001b[32m━━━━━━━━━━━━━━━━━━━━\u001b[0m\u001b[37m\u001b[0m \u001b[1m0s\u001b[0m 43ms/step\n",
      "\u001b[1m1/1\u001b[0m \u001b[32m━━━━━━━━━━━━━━━━━━━━\u001b[0m\u001b[37m\u001b[0m \u001b[1m0s\u001b[0m 54ms/step\n",
      "\u001b[1m1/1\u001b[0m \u001b[32m━━━━━━━━━━━━━━━━━━━━\u001b[0m\u001b[37m\u001b[0m \u001b[1m0s\u001b[0m 54ms/step\n",
      "\u001b[1m1/1\u001b[0m \u001b[32m━━━━━━━━━━━━━━━━━━━━\u001b[0m\u001b[37m\u001b[0m \u001b[1m0s\u001b[0m 54ms/step\n",
      "\u001b[1m1/1\u001b[0m \u001b[32m━━━━━━━━━━━━━━━━━━━━\u001b[0m\u001b[37m\u001b[0m \u001b[1m0s\u001b[0m 57ms/step\n",
      "\u001b[1m1/1\u001b[0m \u001b[32m━━━━━━━━━━━━━━━━━━━━\u001b[0m\u001b[37m\u001b[0m \u001b[1m0s\u001b[0m 54ms/step\n",
      "\u001b[1m1/1\u001b[0m \u001b[32m━━━━━━━━━━━━━━━━━━━━\u001b[0m\u001b[37m\u001b[0m \u001b[1m0s\u001b[0m 45ms/step\n",
      "\u001b[1m1/1\u001b[0m \u001b[32m━━━━━━━━━━━━━━━━━━━━\u001b[0m\u001b[37m\u001b[0m \u001b[1m0s\u001b[0m 40ms/step\n",
      "\u001b[1m1/1\u001b[0m \u001b[32m━━━━━━━━━━━━━━━━━━━━\u001b[0m\u001b[37m\u001b[0m \u001b[1m0s\u001b[0m 54ms/step\n",
      "\u001b[1m1/1\u001b[0m \u001b[32m━━━━━━━━━━━━━━━━━━━━\u001b[0m\u001b[37m\u001b[0m \u001b[1m0s\u001b[0m 54ms/step\n",
      "\u001b[1m1/1\u001b[0m \u001b[32m━━━━━━━━━━━━━━━━━━━━\u001b[0m\u001b[37m\u001b[0m \u001b[1m0s\u001b[0m 54ms/step\n",
      "\u001b[1m1/1\u001b[0m \u001b[32m━━━━━━━━━━━━━━━━━━━━\u001b[0m\u001b[37m\u001b[0m \u001b[1m0s\u001b[0m 62ms/step\n",
      "\u001b[1m1/1\u001b[0m \u001b[32m━━━━━━━━━━━━━━━━━━━━\u001b[0m\u001b[37m\u001b[0m \u001b[1m0s\u001b[0m 67ms/step\n",
      "\u001b[1m1/1\u001b[0m \u001b[32m━━━━━━━━━━━━━━━━━━━━\u001b[0m\u001b[37m\u001b[0m \u001b[1m0s\u001b[0m 52ms/step\n",
      "\u001b[1m1/1\u001b[0m \u001b[32m━━━━━━━━━━━━━━━━━━━━\u001b[0m\u001b[37m\u001b[0m \u001b[1m0s\u001b[0m 67ms/step\n",
      "\u001b[1m1/1\u001b[0m \u001b[32m━━━━━━━━━━━━━━━━━━━━\u001b[0m\u001b[37m\u001b[0m \u001b[1m0s\u001b[0m 67ms/step\n",
      "\u001b[1m1/1\u001b[0m \u001b[32m━━━━━━━━━━━━━━━━━━━━\u001b[0m\u001b[37m\u001b[0m \u001b[1m0s\u001b[0m 59ms/step\n",
      "\u001b[1m1/1\u001b[0m \u001b[32m━━━━━━━━━━━━━━━━━━━━\u001b[0m\u001b[37m\u001b[0m \u001b[1m0s\u001b[0m 54ms/step\n",
      "\u001b[1m1/1\u001b[0m \u001b[32m━━━━━━━━━━━━━━━━━━━━\u001b[0m\u001b[37m\u001b[0m \u001b[1m0s\u001b[0m 54ms/step\n",
      "\u001b[1m1/1\u001b[0m \u001b[32m━━━━━━━━━━━━━━━━━━━━\u001b[0m\u001b[37m\u001b[0m \u001b[1m0s\u001b[0m 54ms/step\n",
      "\u001b[1m1/1\u001b[0m \u001b[32m━━━━━━━━━━━━━━━━━━━━\u001b[0m\u001b[37m\u001b[0m \u001b[1m0s\u001b[0m 50ms/step\n",
      "\u001b[1m1/1\u001b[0m \u001b[32m━━━━━━━━━━━━━━━━━━━━\u001b[0m\u001b[37m\u001b[0m \u001b[1m0s\u001b[0m 54ms/step\n",
      "\u001b[1m1/1\u001b[0m \u001b[32m━━━━━━━━━━━━━━━━━━━━\u001b[0m\u001b[37m\u001b[0m \u001b[1m0s\u001b[0m 54ms/step\n",
      "\u001b[1m1/1\u001b[0m \u001b[32m━━━━━━━━━━━━━━━━━━━━\u001b[0m\u001b[37m\u001b[0m \u001b[1m0s\u001b[0m 54ms/step\n",
      "\u001b[1m1/1\u001b[0m \u001b[32m━━━━━━━━━━━━━━━━━━━━\u001b[0m\u001b[37m\u001b[0m \u001b[1m0s\u001b[0m 61ms/step\n",
      "\u001b[1m1/1\u001b[0m \u001b[32m━━━━━━━━━━━━━━━━━━━━\u001b[0m\u001b[37m\u001b[0m \u001b[1m0s\u001b[0m 40ms/step\n",
      "\u001b[1m1/1\u001b[0m \u001b[32m━━━━━━━━━━━━━━━━━━━━\u001b[0m\u001b[37m\u001b[0m \u001b[1m0s\u001b[0m 55ms/step\n",
      "\u001b[1m1/1\u001b[0m \u001b[32m━━━━━━━━━━━━━━━━━━━━\u001b[0m\u001b[37m\u001b[0m \u001b[1m0s\u001b[0m 43ms/step\n",
      "\u001b[1m1/1\u001b[0m \u001b[32m━━━━━━━━━━━━━━━━━━━━\u001b[0m\u001b[37m\u001b[0m \u001b[1m0s\u001b[0m 53ms/step\n",
      "\u001b[1m1/1\u001b[0m \u001b[32m━━━━━━━━━━━━━━━━━━━━\u001b[0m\u001b[37m\u001b[0m \u001b[1m0s\u001b[0m 54ms/step\n",
      "\u001b[1m1/1\u001b[0m \u001b[32m━━━━━━━━━━━━━━━━━━━━\u001b[0m\u001b[37m\u001b[0m \u001b[1m0s\u001b[0m 54ms/step\n",
      "\u001b[1m1/1\u001b[0m \u001b[32m━━━━━━━━━━━━━━━━━━━━\u001b[0m\u001b[37m\u001b[0m \u001b[1m0s\u001b[0m 63ms/step\n",
      "\u001b[1m1/1\u001b[0m \u001b[32m━━━━━━━━━━━━━━━━━━━━\u001b[0m\u001b[37m\u001b[0m \u001b[1m0s\u001b[0m 52ms/step\n",
      "\u001b[1m1/1\u001b[0m \u001b[32m━━━━━━━━━━━━━━━━━━━━\u001b[0m\u001b[37m\u001b[0m \u001b[1m0s\u001b[0m 54ms/step\n",
      "\u001b[1m1/1\u001b[0m \u001b[32m━━━━━━━━━━━━━━━━━━━━\u001b[0m\u001b[37m\u001b[0m \u001b[1m0s\u001b[0m 42ms/step\n",
      "\u001b[1m1/1\u001b[0m \u001b[32m━━━━━━━━━━━━━━━━━━━━\u001b[0m\u001b[37m\u001b[0m \u001b[1m0s\u001b[0m 54ms/step\n",
      "\u001b[1m1/1\u001b[0m \u001b[32m━━━━━━━━━━━━━━━━━━━━\u001b[0m\u001b[37m\u001b[0m \u001b[1m0s\u001b[0m 59ms/step\n",
      "\u001b[1m1/1\u001b[0m \u001b[32m━━━━━━━━━━━━━━━━━━━━\u001b[0m\u001b[37m\u001b[0m \u001b[1m0s\u001b[0m 53ms/step\n",
      "\u001b[1m1/1\u001b[0m \u001b[32m━━━━━━━━━━━━━━━━━━━━\u001b[0m\u001b[37m\u001b[0m \u001b[1m0s\u001b[0m 54ms/step\n",
      "\u001b[1m1/1\u001b[0m \u001b[32m━━━━━━━━━━━━━━━━━━━━\u001b[0m\u001b[37m\u001b[0m \u001b[1m0s\u001b[0m 55ms/step\n",
      "\u001b[1m1/1\u001b[0m \u001b[32m━━━━━━━━━━━━━━━━━━━━\u001b[0m\u001b[37m\u001b[0m \u001b[1m0s\u001b[0m 59ms/step\n",
      "\u001b[1m1/1\u001b[0m \u001b[32m━━━━━━━━━━━━━━━━━━━━\u001b[0m\u001b[37m\u001b[0m \u001b[1m0s\u001b[0m 54ms/step\n",
      "\u001b[1m1/1\u001b[0m \u001b[32m━━━━━━━━━━━━━━━━━━━━\u001b[0m\u001b[37m\u001b[0m \u001b[1m0s\u001b[0m 53ms/step\n",
      "\u001b[1m1/1\u001b[0m \u001b[32m━━━━━━━━━━━━━━━━━━━━\u001b[0m\u001b[37m\u001b[0m \u001b[1m0s\u001b[0m 54ms/step\n",
      "\u001b[1m1/1\u001b[0m \u001b[32m━━━━━━━━━━━━━━━━━━━━\u001b[0m\u001b[37m\u001b[0m \u001b[1m0s\u001b[0m 54ms/step\n",
      "\u001b[1m1/1\u001b[0m \u001b[32m━━━━━━━━━━━━━━━━━━━━\u001b[0m\u001b[37m\u001b[0m \u001b[1m0s\u001b[0m 63ms/step\n",
      "\u001b[1m1/1\u001b[0m \u001b[32m━━━━━━━━━━━━━━━━━━━━\u001b[0m\u001b[37m\u001b[0m \u001b[1m0s\u001b[0m 54ms/step\n",
      "\u001b[1m1/1\u001b[0m \u001b[32m━━━━━━━━━━━━━━━━━━━━\u001b[0m\u001b[37m\u001b[0m \u001b[1m0s\u001b[0m 53ms/step\n",
      "\u001b[1m1/1\u001b[0m \u001b[32m━━━━━━━━━━━━━━━━━━━━\u001b[0m\u001b[37m\u001b[0m \u001b[1m0s\u001b[0m 54ms/step\n",
      "\u001b[1m1/1\u001b[0m \u001b[32m━━━━━━━━━━━━━━━━━━━━\u001b[0m\u001b[37m\u001b[0m \u001b[1m0s\u001b[0m 54ms/step\n",
      "\u001b[1m1/1\u001b[0m \u001b[32m━━━━━━━━━━━━━━━━━━━━\u001b[0m\u001b[37m\u001b[0m \u001b[1m0s\u001b[0m 54ms/step\n",
      "\u001b[1m1/1\u001b[0m \u001b[32m━━━━━━━━━━━━━━━━━━━━\u001b[0m\u001b[37m\u001b[0m \u001b[1m0s\u001b[0m 53ms/step\n",
      "\u001b[1m1/1\u001b[0m \u001b[32m━━━━━━━━━━━━━━━━━━━━\u001b[0m\u001b[37m\u001b[0m \u001b[1m0s\u001b[0m 54ms/step\n",
      "\u001b[1m1/1\u001b[0m \u001b[32m━━━━━━━━━━━━━━━━━━━━\u001b[0m\u001b[37m\u001b[0m \u001b[1m0s\u001b[0m 54ms/step\n",
      "\u001b[1m1/1\u001b[0m \u001b[32m━━━━━━━━━━━━━━━━━━━━\u001b[0m\u001b[37m\u001b[0m \u001b[1m0s\u001b[0m 54ms/step\n",
      "\u001b[1m1/1\u001b[0m \u001b[32m━━━━━━━━━━━━━━━━━━━━\u001b[0m\u001b[37m\u001b[0m \u001b[1m0s\u001b[0m 47ms/step\n",
      "\u001b[1m1/1\u001b[0m \u001b[32m━━━━━━━━━━━━━━━━━━━━\u001b[0m\u001b[37m\u001b[0m \u001b[1m0s\u001b[0m 54ms/step\n",
      "\u001b[1m1/1\u001b[0m \u001b[32m━━━━━━━━━━━━━━━━━━━━\u001b[0m\u001b[37m\u001b[0m \u001b[1m0s\u001b[0m 53ms/step\n",
      "\u001b[1m1/1\u001b[0m \u001b[32m━━━━━━━━━━━━━━━━━━━━\u001b[0m\u001b[37m\u001b[0m \u001b[1m0s\u001b[0m 54ms/step\n",
      "\u001b[1m1/1\u001b[0m \u001b[32m━━━━━━━━━━━━━━━━━━━━\u001b[0m\u001b[37m\u001b[0m \u001b[1m0s\u001b[0m 63ms/step\n",
      "\u001b[1m1/1\u001b[0m \u001b[32m━━━━━━━━━━━━━━━━━━━━\u001b[0m\u001b[37m\u001b[0m \u001b[1m0s\u001b[0m 52ms/step\n",
      "\u001b[1m1/1\u001b[0m \u001b[32m━━━━━━━━━━━━━━━━━━━━\u001b[0m\u001b[37m\u001b[0m \u001b[1m0s\u001b[0m 54ms/step\n",
      "\u001b[1m1/1\u001b[0m \u001b[32m━━━━━━━━━━━━━━━━━━━━\u001b[0m\u001b[37m\u001b[0m \u001b[1m0s\u001b[0m 43ms/step\n",
      "\u001b[1m1/1\u001b[0m \u001b[32m━━━━━━━━━━━━━━━━━━━━\u001b[0m\u001b[37m\u001b[0m \u001b[1m0s\u001b[0m 54ms/step\n",
      "\u001b[1m1/1\u001b[0m \u001b[32m━━━━━━━━━━━━━━━━━━━━\u001b[0m\u001b[37m\u001b[0m \u001b[1m0s\u001b[0m 67ms/step\n",
      "\u001b[1m1/1\u001b[0m \u001b[32m━━━━━━━━━━━━━━━━━━━━\u001b[0m\u001b[37m\u001b[0m \u001b[1m0s\u001b[0m 40ms/step\n",
      "\u001b[1m1/1\u001b[0m \u001b[32m━━━━━━━━━━━━━━━━━━━━\u001b[0m\u001b[37m\u001b[0m \u001b[1m0s\u001b[0m 53ms/step\n",
      "\u001b[1m1/1\u001b[0m \u001b[32m━━━━━━━━━━━━━━━━━━━━\u001b[0m\u001b[37m\u001b[0m \u001b[1m0s\u001b[0m 53ms/step\n",
      "\u001b[1m1/1\u001b[0m \u001b[32m━━━━━━━━━━━━━━━━━━━━\u001b[0m\u001b[37m\u001b[0m \u001b[1m0s\u001b[0m 59ms/step\n",
      "\u001b[1m1/1\u001b[0m \u001b[32m━━━━━━━━━━━━━━━━━━━━\u001b[0m\u001b[37m\u001b[0m \u001b[1m0s\u001b[0m 54ms/step\n",
      "\u001b[1m1/1\u001b[0m \u001b[32m━━━━━━━━━━━━━━━━━━━━\u001b[0m\u001b[37m\u001b[0m \u001b[1m0s\u001b[0m 67ms/step\n",
      "\u001b[1m1/1\u001b[0m \u001b[32m━━━━━━━━━━━━━━━━━━━━\u001b[0m\u001b[37m\u001b[0m \u001b[1m0s\u001b[0m 54ms/step\n",
      "\u001b[1m1/1\u001b[0m \u001b[32m━━━━━━━━━━━━━━━━━━━━\u001b[0m\u001b[37m\u001b[0m \u001b[1m0s\u001b[0m 54ms/step\n",
      "\u001b[1m1/1\u001b[0m \u001b[32m━━━━━━━━━━━━━━━━━━━━\u001b[0m\u001b[37m\u001b[0m \u001b[1m0s\u001b[0m 53ms/step\n",
      "\u001b[1m1/1\u001b[0m \u001b[32m━━━━━━━━━━━━━━━━━━━━\u001b[0m\u001b[37m\u001b[0m \u001b[1m0s\u001b[0m 53ms/step\n",
      "\u001b[1m1/1\u001b[0m \u001b[32m━━━━━━━━━━━━━━━━━━━━\u001b[0m\u001b[37m\u001b[0m \u001b[1m0s\u001b[0m 65ms/step\n",
      "\u001b[1m1/1\u001b[0m \u001b[32m━━━━━━━━━━━━━━━━━━━━\u001b[0m\u001b[37m\u001b[0m \u001b[1m0s\u001b[0m 53ms/step\n",
      "\u001b[1m1/1\u001b[0m \u001b[32m━━━━━━━━━━━━━━━━━━━━\u001b[0m\u001b[37m\u001b[0m \u001b[1m0s\u001b[0m 53ms/step\n",
      "\u001b[1m1/1\u001b[0m \u001b[32m━━━━━━━━━━━━━━━━━━━━\u001b[0m\u001b[37m\u001b[0m \u001b[1m0s\u001b[0m 67ms/step\n",
      "\u001b[1m1/1\u001b[0m \u001b[32m━━━━━━━━━━━━━━━━━━━━\u001b[0m\u001b[37m\u001b[0m \u001b[1m0s\u001b[0m 67ms/step\n",
      "\u001b[1m1/1\u001b[0m \u001b[32m━━━━━━━━━━━━━━━━━━━━\u001b[0m\u001b[37m\u001b[0m \u001b[1m0s\u001b[0m 61ms/step\n",
      "\u001b[1m1/1\u001b[0m \u001b[32m━━━━━━━━━━━━━━━━━━━━\u001b[0m\u001b[37m\u001b[0m \u001b[1m0s\u001b[0m 62ms/step\n",
      "\u001b[1m1/1\u001b[0m \u001b[32m━━━━━━━━━━━━━━━━━━━━\u001b[0m\u001b[37m\u001b[0m \u001b[1m0s\u001b[0m 58ms/step\n",
      "\u001b[1m1/1\u001b[0m \u001b[32m━━━━━━━━━━━━━━━━━━━━\u001b[0m\u001b[37m\u001b[0m \u001b[1m0s\u001b[0m 66ms/step\n",
      "\u001b[1m1/1\u001b[0m \u001b[32m━━━━━━━━━━━━━━━━━━━━\u001b[0m\u001b[37m\u001b[0m \u001b[1m0s\u001b[0m 62ms/step\n",
      "\u001b[1m1/1\u001b[0m \u001b[32m━━━━━━━━━━━━━━━━━━━━\u001b[0m\u001b[37m\u001b[0m \u001b[1m0s\u001b[0m 59ms/step\n",
      "\u001b[1m1/1\u001b[0m \u001b[32m━━━━━━━━━━━━━━━━━━━━\u001b[0m\u001b[37m\u001b[0m \u001b[1m0s\u001b[0m 67ms/step\n",
      "\u001b[1m1/1\u001b[0m \u001b[32m━━━━━━━━━━━━━━━━━━━━\u001b[0m\u001b[37m\u001b[0m \u001b[1m0s\u001b[0m 53ms/step\n",
      "\u001b[1m1/1\u001b[0m \u001b[32m━━━━━━━━━━━━━━━━━━━━\u001b[0m\u001b[37m\u001b[0m \u001b[1m0s\u001b[0m 79ms/step\n",
      "\u001b[1m1/1\u001b[0m \u001b[32m━━━━━━━━━━━━━━━━━━━━\u001b[0m\u001b[37m\u001b[0m \u001b[1m0s\u001b[0m 54ms/step\n",
      "\u001b[1m1/1\u001b[0m \u001b[32m━━━━━━━━━━━━━━━━━━━━\u001b[0m\u001b[37m\u001b[0m \u001b[1m0s\u001b[0m 62ms/step\n",
      "\u001b[1m1/1\u001b[0m \u001b[32m━━━━━━━━━━━━━━━━━━━━\u001b[0m\u001b[37m\u001b[0m \u001b[1m0s\u001b[0m 53ms/step\n",
      "\u001b[1m1/1\u001b[0m \u001b[32m━━━━━━━━━━━━━━━━━━━━\u001b[0m\u001b[37m\u001b[0m \u001b[1m0s\u001b[0m 52ms/step\n",
      "\u001b[1m1/1\u001b[0m \u001b[32m━━━━━━━━━━━━━━━━━━━━\u001b[0m\u001b[37m\u001b[0m \u001b[1m0s\u001b[0m 70ms/step\n",
      "\u001b[1m1/1\u001b[0m \u001b[32m━━━━━━━━━━━━━━━━━━━━\u001b[0m\u001b[37m\u001b[0m \u001b[1m0s\u001b[0m 81ms/step\n",
      "\u001b[1m1/1\u001b[0m \u001b[32m━━━━━━━━━━━━━━━━━━━━\u001b[0m\u001b[37m\u001b[0m \u001b[1m0s\u001b[0m 62ms/step\n",
      "\u001b[1m1/1\u001b[0m \u001b[32m━━━━━━━━━━━━━━━━━━━━\u001b[0m\u001b[37m\u001b[0m \u001b[1m0s\u001b[0m 67ms/step\n",
      "\u001b[1m1/1\u001b[0m \u001b[32m━━━━━━━━━━━━━━━━━━━━\u001b[0m\u001b[37m\u001b[0m \u001b[1m0s\u001b[0m 51ms/step\n",
      "\u001b[1m1/1\u001b[0m \u001b[32m━━━━━━━━━━━━━━━━━━━━\u001b[0m\u001b[37m\u001b[0m \u001b[1m0s\u001b[0m 51ms/step\n",
      "\u001b[1m1/1\u001b[0m \u001b[32m━━━━━━━━━━━━━━━━━━━━\u001b[0m\u001b[37m\u001b[0m \u001b[1m0s\u001b[0m 62ms/step\n",
      "\u001b[1m1/1\u001b[0m \u001b[32m━━━━━━━━━━━━━━━━━━━━\u001b[0m\u001b[37m\u001b[0m \u001b[1m0s\u001b[0m 46ms/step\n",
      "\u001b[1m1/1\u001b[0m \u001b[32m━━━━━━━━━━━━━━━━━━━━\u001b[0m\u001b[37m\u001b[0m \u001b[1m0s\u001b[0m 62ms/step\n",
      "\u001b[1m1/1\u001b[0m \u001b[32m━━━━━━━━━━━━━━━━━━━━\u001b[0m\u001b[37m\u001b[0m \u001b[1m0s\u001b[0m 47ms/step\n",
      "\u001b[1m1/1\u001b[0m \u001b[32m━━━━━━━━━━━━━━━━━━━━\u001b[0m\u001b[37m\u001b[0m \u001b[1m0s\u001b[0m 47ms/step\n",
      "\u001b[1m1/1\u001b[0m \u001b[32m━━━━━━━━━━━━━━━━━━━━\u001b[0m\u001b[37m\u001b[0m \u001b[1m0s\u001b[0m 47ms/step\n",
      "\u001b[1m1/1\u001b[0m \u001b[32m━━━━━━━━━━━━━━━━━━━━\u001b[0m\u001b[37m\u001b[0m \u001b[1m0s\u001b[0m 47ms/step\n",
      "\u001b[1m1/1\u001b[0m \u001b[32m━━━━━━━━━━━━━━━━━━━━\u001b[0m\u001b[37m\u001b[0m \u001b[1m0s\u001b[0m 47ms/step\n",
      "\u001b[1m1/1\u001b[0m \u001b[32m━━━━━━━━━━━━━━━━━━━━\u001b[0m\u001b[37m\u001b[0m \u001b[1m0s\u001b[0m 79ms/step\n",
      "\u001b[1m1/1\u001b[0m \u001b[32m━━━━━━━━━━━━━━━━━━━━\u001b[0m\u001b[37m\u001b[0m \u001b[1m0s\u001b[0m 58ms/step\n",
      "\u001b[1m1/1\u001b[0m \u001b[32m━━━━━━━━━━━━━━━━━━━━\u001b[0m\u001b[37m\u001b[0m \u001b[1m0s\u001b[0m 78ms/step\n",
      "\u001b[1m1/1\u001b[0m \u001b[32m━━━━━━━━━━━━━━━━━━━━\u001b[0m\u001b[37m\u001b[0m \u001b[1m0s\u001b[0m 47ms/step\n",
      "\u001b[1m1/1\u001b[0m \u001b[32m━━━━━━━━━━━━━━━━━━━━\u001b[0m\u001b[37m\u001b[0m \u001b[1m0s\u001b[0m 62ms/step\n",
      "\u001b[1m1/1\u001b[0m \u001b[32m━━━━━━━━━━━━━━━━━━━━\u001b[0m\u001b[37m\u001b[0m \u001b[1m0s\u001b[0m 48ms/step\n",
      "\u001b[1m1/1\u001b[0m \u001b[32m━━━━━━━━━━━━━━━━━━━━\u001b[0m\u001b[37m\u001b[0m \u001b[1m0s\u001b[0m 41ms/step\n",
      "\u001b[1m1/1\u001b[0m \u001b[32m━━━━━━━━━━━━━━━━━━━━\u001b[0m\u001b[37m\u001b[0m \u001b[1m0s\u001b[0m 47ms/step\n",
      "\u001b[1m1/1\u001b[0m \u001b[32m━━━━━━━━━━━━━━━━━━━━\u001b[0m\u001b[37m\u001b[0m \u001b[1m0s\u001b[0m 47ms/step\n",
      "\u001b[1m1/1\u001b[0m \u001b[32m━━━━━━━━━━━━━━━━━━━━\u001b[0m\u001b[37m\u001b[0m \u001b[1m0s\u001b[0m 66ms/step\n",
      "\u001b[1m1/1\u001b[0m \u001b[32m━━━━━━━━━━━━━━━━━━━━\u001b[0m\u001b[37m\u001b[0m \u001b[1m0s\u001b[0m 47ms/step\n",
      "\u001b[1m1/1\u001b[0m \u001b[32m━━━━━━━━━━━━━━━━━━━━\u001b[0m\u001b[37m\u001b[0m \u001b[1m0s\u001b[0m 63ms/step\n",
      "\u001b[1m1/1\u001b[0m \u001b[32m━━━━━━━━━━━━━━━━━━━━\u001b[0m\u001b[37m\u001b[0m \u001b[1m0s\u001b[0m 47ms/step\n",
      "\u001b[1m1/1\u001b[0m \u001b[32m━━━━━━━━━━━━━━━━━━━━\u001b[0m\u001b[37m\u001b[0m \u001b[1m0s\u001b[0m 47ms/step\n",
      "\u001b[1m1/1\u001b[0m \u001b[32m━━━━━━━━━━━━━━━━━━━━\u001b[0m\u001b[37m\u001b[0m \u001b[1m0s\u001b[0m 47ms/step\n",
      "\u001b[1m1/1\u001b[0m \u001b[32m━━━━━━━━━━━━━━━━━━━━\u001b[0m\u001b[37m\u001b[0m \u001b[1m0s\u001b[0m 47ms/step\n",
      "\u001b[1m1/1\u001b[0m \u001b[32m━━━━━━━━━━━━━━━━━━━━\u001b[0m\u001b[37m\u001b[0m \u001b[1m0s\u001b[0m 47ms/step\n",
      "\u001b[1m1/1\u001b[0m \u001b[32m━━━━━━━━━━━━━━━━━━━━\u001b[0m\u001b[37m\u001b[0m \u001b[1m0s\u001b[0m 63ms/step\n",
      "\u001b[1m1/1\u001b[0m \u001b[32m━━━━━━━━━━━━━━━━━━━━\u001b[0m\u001b[37m\u001b[0m \u001b[1m0s\u001b[0m 47ms/step\n",
      "\u001b[1m1/1\u001b[0m \u001b[32m━━━━━━━━━━━━━━━━━━━━\u001b[0m\u001b[37m\u001b[0m \u001b[1m0s\u001b[0m 62ms/step\n",
      "\u001b[1m1/1\u001b[0m \u001b[32m━━━━━━━━━━━━━━━━━━━━\u001b[0m\u001b[37m\u001b[0m \u001b[1m0s\u001b[0m 47ms/step\n",
      "\u001b[1m1/1\u001b[0m \u001b[32m━━━━━━━━━━━━━━━━━━━━\u001b[0m\u001b[37m\u001b[0m \u001b[1m0s\u001b[0m 47ms/step\n",
      "\u001b[1m1/1\u001b[0m \u001b[32m━━━━━━━━━━━━━━━━━━━━\u001b[0m\u001b[37m\u001b[0m \u001b[1m0s\u001b[0m 47ms/step\n",
      "\u001b[1m1/1\u001b[0m \u001b[32m━━━━━━━━━━━━━━━━━━━━\u001b[0m\u001b[37m\u001b[0m \u001b[1m0s\u001b[0m 47ms/step\n",
      "\u001b[1m1/1\u001b[0m \u001b[32m━━━━━━━━━━━━━━━━━━━━\u001b[0m\u001b[37m\u001b[0m \u001b[1m0s\u001b[0m 47ms/step\n",
      "\u001b[1m1/1\u001b[0m \u001b[32m━━━━━━━━━━━━━━━━━━━━\u001b[0m\u001b[37m\u001b[0m \u001b[1m0s\u001b[0m 47ms/step\n",
      "\u001b[1m1/1\u001b[0m \u001b[32m━━━━━━━━━━━━━━━━━━━━\u001b[0m\u001b[37m\u001b[0m \u001b[1m0s\u001b[0m 62ms/step\n",
      "\u001b[1m1/1\u001b[0m \u001b[32m━━━━━━━━━━━━━━━━━━━━\u001b[0m\u001b[37m\u001b[0m \u001b[1m0s\u001b[0m 63ms/step\n",
      "\u001b[1m1/1\u001b[0m \u001b[32m━━━━━━━━━━━━━━━━━━━━\u001b[0m\u001b[37m\u001b[0m \u001b[1m0s\u001b[0m 47ms/step\n",
      "\u001b[1m1/1\u001b[0m \u001b[32m━━━━━━━━━━━━━━━━━━━━\u001b[0m\u001b[37m\u001b[0m \u001b[1m0s\u001b[0m 44ms/step\n",
      "\u001b[1m1/1\u001b[0m \u001b[32m━━━━━━━━━━━━━━━━━━━━\u001b[0m\u001b[37m\u001b[0m \u001b[1m0s\u001b[0m 62ms/step\n",
      "\u001b[1m1/1\u001b[0m \u001b[32m━━━━━━━━━━━━━━━━━━━━\u001b[0m\u001b[37m\u001b[0m \u001b[1m0s\u001b[0m 47ms/step\n",
      "\u001b[1m1/1\u001b[0m \u001b[32m━━━━━━━━━━━━━━━━━━━━\u001b[0m\u001b[37m\u001b[0m \u001b[1m0s\u001b[0m 62ms/step\n",
      "\u001b[1m1/1\u001b[0m \u001b[32m━━━━━━━━━━━━━━━━━━━━\u001b[0m\u001b[37m\u001b[0m \u001b[1m0s\u001b[0m 62ms/step\n",
      "\u001b[1m1/1\u001b[0m \u001b[32m━━━━━━━━━━━━━━━━━━━━\u001b[0m\u001b[37m\u001b[0m \u001b[1m0s\u001b[0m 47ms/step\n",
      "\u001b[1m1/1\u001b[0m \u001b[32m━━━━━━━━━━━━━━━━━━━━\u001b[0m\u001b[37m\u001b[0m \u001b[1m0s\u001b[0m 57ms/step\n",
      "\u001b[1m1/1\u001b[0m \u001b[32m━━━━━━━━━━━━━━━━━━━━\u001b[0m\u001b[37m\u001b[0m \u001b[1m0s\u001b[0m 44ms/step\n",
      "\u001b[1m1/1\u001b[0m \u001b[32m━━━━━━━━━━━━━━━━━━━━\u001b[0m\u001b[37m\u001b[0m \u001b[1m0s\u001b[0m 64ms/step\n",
      "\u001b[1m1/1\u001b[0m \u001b[32m━━━━━━━━━━━━━━━━━━━━\u001b[0m\u001b[37m\u001b[0m \u001b[1m0s\u001b[0m 47ms/step\n",
      "\u001b[1m1/1\u001b[0m \u001b[32m━━━━━━━━━━━━━━━━━━━━\u001b[0m\u001b[37m\u001b[0m \u001b[1m0s\u001b[0m 62ms/step\n",
      "\u001b[1m1/1\u001b[0m \u001b[32m━━━━━━━━━━━━━━━━━━━━\u001b[0m\u001b[37m\u001b[0m \u001b[1m0s\u001b[0m 47ms/step\n",
      "\u001b[1m1/1\u001b[0m \u001b[32m━━━━━━━━━━━━━━━━━━━━\u001b[0m\u001b[37m\u001b[0m \u001b[1m0s\u001b[0m 64ms/step\n",
      "\u001b[1m1/1\u001b[0m \u001b[32m━━━━━━━━━━━━━━━━━━━━\u001b[0m\u001b[37m\u001b[0m \u001b[1m0s\u001b[0m 54ms/step\n",
      "\u001b[1m1/1\u001b[0m \u001b[32m━━━━━━━━━━━━━━━━━━━━\u001b[0m\u001b[37m\u001b[0m \u001b[1m0s\u001b[0m 47ms/step\n",
      "\u001b[1m1/1\u001b[0m \u001b[32m━━━━━━━━━━━━━━━━━━━━\u001b[0m\u001b[37m\u001b[0m \u001b[1m0s\u001b[0m 47ms/step\n",
      "\u001b[1m1/1\u001b[0m \u001b[32m━━━━━━━━━━━━━━━━━━━━\u001b[0m\u001b[37m\u001b[0m \u001b[1m0s\u001b[0m 64ms/step\n",
      "\u001b[1m1/1\u001b[0m \u001b[32m━━━━━━━━━━━━━━━━━━━━\u001b[0m\u001b[37m\u001b[0m \u001b[1m0s\u001b[0m 62ms/step\n",
      "\u001b[1m1/1\u001b[0m \u001b[32m━━━━━━━━━━━━━━━━━━━━\u001b[0m\u001b[37m\u001b[0m \u001b[1m0s\u001b[0m 47ms/step\n",
      "\u001b[1m1/1\u001b[0m \u001b[32m━━━━━━━━━━━━━━━━━━━━\u001b[0m\u001b[37m\u001b[0m \u001b[1m0s\u001b[0m 62ms/step\n",
      "\u001b[1m1/1\u001b[0m \u001b[32m━━━━━━━━━━━━━━━━━━━━\u001b[0m\u001b[37m\u001b[0m \u001b[1m0s\u001b[0m 62ms/step\n",
      "\u001b[1m1/1\u001b[0m \u001b[32m━━━━━━━━━━━━━━━━━━━━\u001b[0m\u001b[37m\u001b[0m \u001b[1m0s\u001b[0m 62ms/step\n",
      "\u001b[1m1/1\u001b[0m \u001b[32m━━━━━━━━━━━━━━━━━━━━\u001b[0m\u001b[37m\u001b[0m \u001b[1m0s\u001b[0m 62ms/step\n",
      "\u001b[1m1/1\u001b[0m \u001b[32m━━━━━━━━━━━━━━━━━━━━\u001b[0m\u001b[37m\u001b[0m \u001b[1m0s\u001b[0m 62ms/step\n",
      "\u001b[1m1/1\u001b[0m \u001b[32m━━━━━━━━━━━━━━━━━━━━\u001b[0m\u001b[37m\u001b[0m \u001b[1m0s\u001b[0m 62ms/step\n",
      "\u001b[1m1/1\u001b[0m \u001b[32m━━━━━━━━━━━━━━━━━━━━\u001b[0m\u001b[37m\u001b[0m \u001b[1m0s\u001b[0m 62ms/step\n",
      "\u001b[1m1/1\u001b[0m \u001b[32m━━━━━━━━━━━━━━━━━━━━\u001b[0m\u001b[37m\u001b[0m \u001b[1m0s\u001b[0m 62ms/step\n",
      "\u001b[1m1/1\u001b[0m \u001b[32m━━━━━━━━━━━━━━━━━━━━\u001b[0m\u001b[37m\u001b[0m \u001b[1m0s\u001b[0m 47ms/step\n",
      "\u001b[1m1/1\u001b[0m \u001b[32m━━━━━━━━━━━━━━━━━━━━\u001b[0m\u001b[37m\u001b[0m \u001b[1m0s\u001b[0m 47ms/step\n",
      "\u001b[1m1/1\u001b[0m \u001b[32m━━━━━━━━━━━━━━━━━━━━\u001b[0m\u001b[37m\u001b[0m \u001b[1m0s\u001b[0m 62ms/step\n",
      "\u001b[1m1/1\u001b[0m \u001b[32m━━━━━━━━━━━━━━━━━━━━\u001b[0m\u001b[37m\u001b[0m \u001b[1m0s\u001b[0m 48ms/step\n",
      "\u001b[1m1/1\u001b[0m \u001b[32m━━━━━━━━━━━━━━━━━━━━\u001b[0m\u001b[37m\u001b[0m \u001b[1m0s\u001b[0m 62ms/step\n",
      "\u001b[1m1/1\u001b[0m \u001b[32m━━━━━━━━━━━━━━━━━━━━\u001b[0m\u001b[37m\u001b[0m \u001b[1m0s\u001b[0m 47ms/step\n",
      "\u001b[1m1/1\u001b[0m \u001b[32m━━━━━━━━━━━━━━━━━━━━\u001b[0m\u001b[37m\u001b[0m \u001b[1m0s\u001b[0m 47ms/step\n",
      "\u001b[1m1/1\u001b[0m \u001b[32m━━━━━━━━━━━━━━━━━━━━\u001b[0m\u001b[37m\u001b[0m \u001b[1m0s\u001b[0m 47ms/step\n",
      "\u001b[1m1/1\u001b[0m \u001b[32m━━━━━━━━━━━━━━━━━━━━\u001b[0m\u001b[37m\u001b[0m \u001b[1m0s\u001b[0m 62ms/step\n",
      "\u001b[1m1/1\u001b[0m \u001b[32m━━━━━━━━━━━━━━━━━━━━\u001b[0m\u001b[37m\u001b[0m \u001b[1m0s\u001b[0m 53ms/step\n",
      "\u001b[1m1/1\u001b[0m \u001b[32m━━━━━━━━━━━━━━━━━━━━\u001b[0m\u001b[37m\u001b[0m \u001b[1m0s\u001b[0m 62ms/step\n",
      "\u001b[1m1/1\u001b[0m \u001b[32m━━━━━━━━━━━━━━━━━━━━\u001b[0m\u001b[37m\u001b[0m \u001b[1m0s\u001b[0m 47ms/step\n",
      "\u001b[1m1/1\u001b[0m \u001b[32m━━━━━━━━━━━━━━━━━━━━\u001b[0m\u001b[37m\u001b[0m \u001b[1m0s\u001b[0m 62ms/step\n",
      "\u001b[1m1/1\u001b[0m \u001b[32m━━━━━━━━━━━━━━━━━━━━\u001b[0m\u001b[37m\u001b[0m \u001b[1m0s\u001b[0m 47ms/step\n",
      "\u001b[1m1/1\u001b[0m \u001b[32m━━━━━━━━━━━━━━━━━━━━\u001b[0m\u001b[37m\u001b[0m \u001b[1m0s\u001b[0m 47ms/step\n",
      "\u001b[1m1/1\u001b[0m \u001b[32m━━━━━━━━━━━━━━━━━━━━\u001b[0m\u001b[37m\u001b[0m \u001b[1m0s\u001b[0m 62ms/step\n",
      "\u001b[1m1/1\u001b[0m \u001b[32m━━━━━━━━━━━━━━━━━━━━\u001b[0m\u001b[37m\u001b[0m \u001b[1m0s\u001b[0m 50ms/step\n",
      "\u001b[1m1/1\u001b[0m \u001b[32m━━━━━━━━━━━━━━━━━━━━\u001b[0m\u001b[37m\u001b[0m \u001b[1m0s\u001b[0m 62ms/step\n",
      "\u001b[1m1/1\u001b[0m \u001b[32m━━━━━━━━━━━━━━━━━━━━\u001b[0m\u001b[37m\u001b[0m \u001b[1m0s\u001b[0m 64ms/step\n",
      "\u001b[1m1/1\u001b[0m \u001b[32m━━━━━━━━━━━━━━━━━━━━\u001b[0m\u001b[37m\u001b[0m \u001b[1m0s\u001b[0m 62ms/step\n",
      "\u001b[1m1/1\u001b[0m \u001b[32m━━━━━━━━━━━━━━━━━━━━\u001b[0m\u001b[37m\u001b[0m \u001b[1m0s\u001b[0m 47ms/step\n",
      "\u001b[1m1/1\u001b[0m \u001b[32m━━━━━━━━━━━━━━━━━━━━\u001b[0m\u001b[37m\u001b[0m \u001b[1m0s\u001b[0m 47ms/step\n",
      "\u001b[1m1/1\u001b[0m \u001b[32m━━━━━━━━━━━━━━━━━━━━\u001b[0m\u001b[37m\u001b[0m \u001b[1m0s\u001b[0m 47ms/step\n",
      "\u001b[1m1/1\u001b[0m \u001b[32m━━━━━━━━━━━━━━━━━━━━\u001b[0m\u001b[37m\u001b[0m \u001b[1m0s\u001b[0m 48ms/step\n",
      "\u001b[1m1/1\u001b[0m \u001b[32m━━━━━━━━━━━━━━━━━━━━\u001b[0m\u001b[37m\u001b[0m \u001b[1m0s\u001b[0m 47ms/step\n",
      "\u001b[1m1/1\u001b[0m \u001b[32m━━━━━━━━━━━━━━━━━━━━\u001b[0m\u001b[37m\u001b[0m \u001b[1m0s\u001b[0m 47ms/step\n",
      "\u001b[1m1/1\u001b[0m \u001b[32m━━━━━━━━━━━━━━━━━━━━\u001b[0m\u001b[37m\u001b[0m \u001b[1m0s\u001b[0m 62ms/step\n",
      "\u001b[1m1/1\u001b[0m \u001b[32m━━━━━━━━━━━━━━━━━━━━\u001b[0m\u001b[37m\u001b[0m \u001b[1m0s\u001b[0m 62ms/step\n",
      "\u001b[1m1/1\u001b[0m \u001b[32m━━━━━━━━━━━━━━━━━━━━\u001b[0m\u001b[37m\u001b[0m \u001b[1m0s\u001b[0m 47ms/step\n",
      "\u001b[1m1/1\u001b[0m \u001b[32m━━━━━━━━━━━━━━━━━━━━\u001b[0m\u001b[37m\u001b[0m \u001b[1m0s\u001b[0m 62ms/step\n",
      "\u001b[1m1/1\u001b[0m \u001b[32m━━━━━━━━━━━━━━━━━━━━\u001b[0m\u001b[37m\u001b[0m \u001b[1m0s\u001b[0m 62ms/step\n",
      "\u001b[1m1/1\u001b[0m \u001b[32m━━━━━━━━━━━━━━━━━━━━\u001b[0m\u001b[37m\u001b[0m \u001b[1m0s\u001b[0m 47ms/step\n",
      "\u001b[1m1/1\u001b[0m \u001b[32m━━━━━━━━━━━━━━━━━━━━\u001b[0m\u001b[37m\u001b[0m \u001b[1m0s\u001b[0m 62ms/step\n",
      "\u001b[1m1/1\u001b[0m \u001b[32m━━━━━━━━━━━━━━━━━━━━\u001b[0m\u001b[37m\u001b[0m \u001b[1m0s\u001b[0m 47ms/step\n",
      "\u001b[1m1/1\u001b[0m \u001b[32m━━━━━━━━━━━━━━━━━━━━\u001b[0m\u001b[37m\u001b[0m \u001b[1m0s\u001b[0m 62ms/step\n",
      "\u001b[1m1/1\u001b[0m \u001b[32m━━━━━━━━━━━━━━━━━━━━\u001b[0m\u001b[37m\u001b[0m \u001b[1m0s\u001b[0m 47ms/step\n",
      "\u001b[1m1/1\u001b[0m \u001b[32m━━━━━━━━━━━━━━━━━━━━\u001b[0m\u001b[37m\u001b[0m \u001b[1m0s\u001b[0m 62ms/step\n",
      "\u001b[1m1/1\u001b[0m \u001b[32m━━━━━━━━━━━━━━━━━━━━\u001b[0m\u001b[37m\u001b[0m \u001b[1m0s\u001b[0m 62ms/step\n",
      "\u001b[1m1/1\u001b[0m \u001b[32m━━━━━━━━━━━━━━━━━━━━\u001b[0m\u001b[37m\u001b[0m \u001b[1m0s\u001b[0m 60ms/step\n",
      "\u001b[1m1/1\u001b[0m \u001b[32m━━━━━━━━━━━━━━━━━━━━\u001b[0m\u001b[37m\u001b[0m \u001b[1m0s\u001b[0m 59ms/step\n",
      "\u001b[1m1/1\u001b[0m \u001b[32m━━━━━━━━━━━━━━━━━━━━\u001b[0m\u001b[37m\u001b[0m \u001b[1m0s\u001b[0m 47ms/step\n",
      "\u001b[1m1/1\u001b[0m \u001b[32m━━━━━━━━━━━━━━━━━━━━\u001b[0m\u001b[37m\u001b[0m \u001b[1m0s\u001b[0m 63ms/step\n",
      "\u001b[1m1/1\u001b[0m \u001b[32m━━━━━━━━━━━━━━━━━━━━\u001b[0m\u001b[37m\u001b[0m \u001b[1m0s\u001b[0m 47ms/step\n",
      "\u001b[1m1/1\u001b[0m \u001b[32m━━━━━━━━━━━━━━━━━━━━\u001b[0m\u001b[37m\u001b[0m \u001b[1m0s\u001b[0m 47ms/step\n",
      "\u001b[1m1/1\u001b[0m \u001b[32m━━━━━━━━━━━━━━━━━━━━\u001b[0m\u001b[37m\u001b[0m \u001b[1m0s\u001b[0m 47ms/step\n",
      "\u001b[1m1/1\u001b[0m \u001b[32m━━━━━━━━━━━━━━━━━━━━\u001b[0m\u001b[37m\u001b[0m \u001b[1m0s\u001b[0m 47ms/step\n",
      "\u001b[1m1/1\u001b[0m \u001b[32m━━━━━━━━━━━━━━━━━━━━\u001b[0m\u001b[37m\u001b[0m \u001b[1m0s\u001b[0m 62ms/step\n",
      "\u001b[1m1/1\u001b[0m \u001b[32m━━━━━━━━━━━━━━━━━━━━\u001b[0m\u001b[37m\u001b[0m \u001b[1m0s\u001b[0m 48ms/step\n",
      "\u001b[1m1/1\u001b[0m \u001b[32m━━━━━━━━━━━━━━━━━━━━\u001b[0m\u001b[37m\u001b[0m \u001b[1m0s\u001b[0m 67ms/step\n",
      "\u001b[1m1/1\u001b[0m \u001b[32m━━━━━━━━━━━━━━━━━━━━\u001b[0m\u001b[37m\u001b[0m \u001b[1m0s\u001b[0m 62ms/step\n",
      "\u001b[1m1/1\u001b[0m \u001b[32m━━━━━━━━━━━━━━━━━━━━\u001b[0m\u001b[37m\u001b[0m \u001b[1m0s\u001b[0m 47ms/step\n",
      "\u001b[1m1/1\u001b[0m \u001b[32m━━━━━━━━━━━━━━━━━━━━\u001b[0m\u001b[37m\u001b[0m \u001b[1m0s\u001b[0m 62ms/step\n",
      "\u001b[1m1/1\u001b[0m \u001b[32m━━━━━━━━━━━━━━━━━━━━\u001b[0m\u001b[37m\u001b[0m \u001b[1m0s\u001b[0m 62ms/step\n",
      "\u001b[1m1/1\u001b[0m \u001b[32m━━━━━━━━━━━━━━━━━━━━\u001b[0m\u001b[37m\u001b[0m \u001b[1m0s\u001b[0m 62ms/step\n",
      "\u001b[1m1/1\u001b[0m \u001b[32m━━━━━━━━━━━━━━━━━━━━\u001b[0m\u001b[37m\u001b[0m \u001b[1m0s\u001b[0m 62ms/step\n",
      "\u001b[1m1/1\u001b[0m \u001b[32m━━━━━━━━━━━━━━━━━━━━\u001b[0m\u001b[37m\u001b[0m \u001b[1m0s\u001b[0m 48ms/step\n",
      "\u001b[1m1/1\u001b[0m \u001b[32m━━━━━━━━━━━━━━━━━━━━\u001b[0m\u001b[37m\u001b[0m \u001b[1m0s\u001b[0m 45ms/step\n",
      "\u001b[1m1/1\u001b[0m \u001b[32m━━━━━━━━━━━━━━━━━━━━\u001b[0m\u001b[37m\u001b[0m \u001b[1m0s\u001b[0m 53ms/step\n",
      "\u001b[1m1/1\u001b[0m \u001b[32m━━━━━━━━━━━━━━━━━━━━\u001b[0m\u001b[37m\u001b[0m \u001b[1m0s\u001b[0m 61ms/step\n",
      "\u001b[1m1/1\u001b[0m \u001b[32m━━━━━━━━━━━━━━━━━━━━\u001b[0m\u001b[37m\u001b[0m \u001b[1m0s\u001b[0m 52ms/step\n",
      "\u001b[1m1/1\u001b[0m \u001b[32m━━━━━━━━━━━━━━━━━━━━\u001b[0m\u001b[37m\u001b[0m \u001b[1m0s\u001b[0m 54ms/step\n",
      "\u001b[1m1/1\u001b[0m \u001b[32m━━━━━━━━━━━━━━━━━━━━\u001b[0m\u001b[37m\u001b[0m \u001b[1m0s\u001b[0m 53ms/step\n",
      "\u001b[1m1/1\u001b[0m \u001b[32m━━━━━━━━━━━━━━━━━━━━\u001b[0m\u001b[37m\u001b[0m \u001b[1m0s\u001b[0m 54ms/step\n",
      "\u001b[1m1/1\u001b[0m \u001b[32m━━━━━━━━━━━━━━━━━━━━\u001b[0m\u001b[37m\u001b[0m \u001b[1m0s\u001b[0m 42ms/step\n",
      "\u001b[1m1/1\u001b[0m \u001b[32m━━━━━━━━━━━━━━━━━━━━\u001b[0m\u001b[37m\u001b[0m \u001b[1m0s\u001b[0m 54ms/step\n",
      "\u001b[1m1/1\u001b[0m \u001b[32m━━━━━━━━━━━━━━━━━━━━\u001b[0m\u001b[37m\u001b[0m \u001b[1m0s\u001b[0m 54ms/step\n",
      "\u001b[1m1/1\u001b[0m \u001b[32m━━━━━━━━━━━━━━━━━━━━\u001b[0m\u001b[37m\u001b[0m \u001b[1m0s\u001b[0m 54ms/step\n",
      "\u001b[1m1/1\u001b[0m \u001b[32m━━━━━━━━━━━━━━━━━━━━\u001b[0m\u001b[37m\u001b[0m \u001b[1m0s\u001b[0m 67ms/step\n",
      "\u001b[1m1/1\u001b[0m \u001b[32m━━━━━━━━━━━━━━━━━━━━\u001b[0m\u001b[37m\u001b[0m \u001b[1m0s\u001b[0m 56ms/step\n",
      "\u001b[1m1/1\u001b[0m \u001b[32m━━━━━━━━━━━━━━━━━━━━\u001b[0m\u001b[37m\u001b[0m \u001b[1m0s\u001b[0m 54ms/step\n",
      "\u001b[1m1/1\u001b[0m \u001b[32m━━━━━━━━━━━━━━━━━━━━\u001b[0m\u001b[37m\u001b[0m \u001b[1m0s\u001b[0m 54ms/step\n",
      "\u001b[1m1/1\u001b[0m \u001b[32m━━━━━━━━━━━━━━━━━━━━\u001b[0m\u001b[37m\u001b[0m \u001b[1m0s\u001b[0m 54ms/step\n",
      "\u001b[1m1/1\u001b[0m \u001b[32m━━━━━━━━━━━━━━━━━━━━\u001b[0m\u001b[37m\u001b[0m \u001b[1m0s\u001b[0m 50ms/step\n",
      "\u001b[1m1/1\u001b[0m \u001b[32m━━━━━━━━━━━━━━━━━━━━\u001b[0m\u001b[37m\u001b[0m \u001b[1m0s\u001b[0m 67ms/step\n",
      "\u001b[1m1/1\u001b[0m \u001b[32m━━━━━━━━━━━━━━━━━━━━\u001b[0m\u001b[37m\u001b[0m \u001b[1m0s\u001b[0m 40ms/step\n",
      "\u001b[1m1/1\u001b[0m \u001b[32m━━━━━━━━━━━━━━━━━━━━\u001b[0m\u001b[37m\u001b[0m \u001b[1m0s\u001b[0m 54ms/step\n",
      "\u001b[1m1/1\u001b[0m \u001b[32m━━━━━━━━━━━━━━━━━━━━\u001b[0m\u001b[37m\u001b[0m \u001b[1m0s\u001b[0m 64ms/step\n",
      "\u001b[1m1/1\u001b[0m \u001b[32m━━━━━━━━━━━━━━━━━━━━\u001b[0m\u001b[37m\u001b[0m \u001b[1m0s\u001b[0m 51ms/step\n",
      "\u001b[1m1/1\u001b[0m \u001b[32m━━━━━━━━━━━━━━━━━━━━\u001b[0m\u001b[37m\u001b[0m \u001b[1m0s\u001b[0m 67ms/step\n",
      "\u001b[1m1/1\u001b[0m \u001b[32m━━━━━━━━━━━━━━━━━━━━\u001b[0m\u001b[37m\u001b[0m \u001b[1m0s\u001b[0m 54ms/step\n",
      "\u001b[1m1/1\u001b[0m \u001b[32m━━━━━━━━━━━━━━━━━━━━\u001b[0m\u001b[37m\u001b[0m \u001b[1m0s\u001b[0m 54ms/step\n",
      "\u001b[1m1/1\u001b[0m \u001b[32m━━━━━━━━━━━━━━━━━━━━\u001b[0m\u001b[37m\u001b[0m \u001b[1m0s\u001b[0m 65ms/step\n",
      "\u001b[1m1/1\u001b[0m \u001b[32m━━━━━━━━━━━━━━━━━━━━\u001b[0m\u001b[37m\u001b[0m \u001b[1m0s\u001b[0m 53ms/step\n",
      "\u001b[1m1/1\u001b[0m \u001b[32m━━━━━━━━━━━━━━━━━━━━\u001b[0m\u001b[37m\u001b[0m \u001b[1m0s\u001b[0m 53ms/step\n",
      "\u001b[1m1/1\u001b[0m \u001b[32m━━━━━━━━━━━━━━━━━━━━\u001b[0m\u001b[37m\u001b[0m \u001b[1m0s\u001b[0m 54ms/step\n",
      "\u001b[1m1/1\u001b[0m \u001b[32m━━━━━━━━━━━━━━━━━━━━\u001b[0m\u001b[37m\u001b[0m \u001b[1m0s\u001b[0m 61ms/step\n",
      "\u001b[1m1/1\u001b[0m \u001b[32m━━━━━━━━━━━━━━━━━━━━\u001b[0m\u001b[37m\u001b[0m \u001b[1m0s\u001b[0m 53ms/step\n",
      "\u001b[1m1/1\u001b[0m \u001b[32m━━━━━━━━━━━━━━━━━━━━\u001b[0m\u001b[37m\u001b[0m \u001b[1m0s\u001b[0m 54ms/step\n",
      "\u001b[1m1/1\u001b[0m \u001b[32m━━━━━━━━━━━━━━━━━━━━\u001b[0m\u001b[37m\u001b[0m \u001b[1m0s\u001b[0m 53ms/step\n",
      "\u001b[1m1/1\u001b[0m \u001b[32m━━━━━━━━━━━━━━━━━━━━\u001b[0m\u001b[37m\u001b[0m \u001b[1m0s\u001b[0m 55ms/step\n",
      "\u001b[1m1/1\u001b[0m \u001b[32m━━━━━━━━━━━━━━━━━━━━\u001b[0m\u001b[37m\u001b[0m \u001b[1m0s\u001b[0m 54ms/step\n",
      "\u001b[1m1/1\u001b[0m \u001b[32m━━━━━━━━━━━━━━━━━━━━\u001b[0m\u001b[37m\u001b[0m \u001b[1m0s\u001b[0m 67ms/step\n",
      "\u001b[1m1/1\u001b[0m \u001b[32m━━━━━━━━━━━━━━━━━━━━\u001b[0m\u001b[37m\u001b[0m \u001b[1m0s\u001b[0m 67ms/step\n",
      "\u001b[1m1/1\u001b[0m \u001b[32m━━━━━━━━━━━━━━━━━━━━\u001b[0m\u001b[37m\u001b[0m \u001b[1m0s\u001b[0m 54ms/step\n",
      "\u001b[1m1/1\u001b[0m \u001b[32m━━━━━━━━━━━━━━━━━━━━\u001b[0m\u001b[37m\u001b[0m \u001b[1m0s\u001b[0m 40ms/step\n",
      "\u001b[1m1/1\u001b[0m \u001b[32m━━━━━━━━━━━━━━━━━━━━\u001b[0m\u001b[37m\u001b[0m \u001b[1m0s\u001b[0m 54ms/step\n",
      "\u001b[1m1/1\u001b[0m \u001b[32m━━━━━━━━━━━━━━━━━━━━\u001b[0m\u001b[37m\u001b[0m \u001b[1m0s\u001b[0m 55ms/step\n",
      "\u001b[1m1/1\u001b[0m \u001b[32m━━━━━━━━━━━━━━━━━━━━\u001b[0m\u001b[37m\u001b[0m \u001b[1m0s\u001b[0m 54ms/step\n",
      "\u001b[1m1/1\u001b[0m \u001b[32m━━━━━━━━━━━━━━━━━━━━\u001b[0m\u001b[37m\u001b[0m \u001b[1m0s\u001b[0m 54ms/step\n",
      "\u001b[1m1/1\u001b[0m \u001b[32m━━━━━━━━━━━━━━━━━━━━\u001b[0m\u001b[37m\u001b[0m \u001b[1m0s\u001b[0m 47ms/step\n",
      "\u001b[1m1/1\u001b[0m \u001b[32m━━━━━━━━━━━━━━━━━━━━\u001b[0m\u001b[37m\u001b[0m \u001b[1m0s\u001b[0m 54ms/step\n",
      "\u001b[1m1/1\u001b[0m \u001b[32m━━━━━━━━━━━━━━━━━━━━\u001b[0m\u001b[37m\u001b[0m \u001b[1m0s\u001b[0m 53ms/step\n",
      "\u001b[1m1/1\u001b[0m \u001b[32m━━━━━━━━━━━━━━━━━━━━\u001b[0m\u001b[37m\u001b[0m \u001b[1m0s\u001b[0m 54ms/step\n",
      "\u001b[1m1/1\u001b[0m \u001b[32m━━━━━━━━━━━━━━━━━━━━\u001b[0m\u001b[37m\u001b[0m \u001b[1m0s\u001b[0m 67ms/step\n",
      "\u001b[1m1/1\u001b[0m \u001b[32m━━━━━━━━━━━━━━━━━━━━\u001b[0m\u001b[37m\u001b[0m \u001b[1m0s\u001b[0m 54ms/step\n",
      "\u001b[1m1/1\u001b[0m \u001b[32m━━━━━━━━━━━━━━━━━━━━\u001b[0m\u001b[37m\u001b[0m \u001b[1m0s\u001b[0m 54ms/step\n",
      "\u001b[1m1/1\u001b[0m \u001b[32m━━━━━━━━━━━━━━━━━━━━\u001b[0m\u001b[37m\u001b[0m \u001b[1m0s\u001b[0m 54ms/step\n",
      "\u001b[1m1/1\u001b[0m \u001b[32m━━━━━━━━━━━━━━━━━━━━\u001b[0m\u001b[37m\u001b[0m \u001b[1m0s\u001b[0m 54ms/step\n",
      "\u001b[1m1/1\u001b[0m \u001b[32m━━━━━━━━━━━━━━━━━━━━\u001b[0m\u001b[37m\u001b[0m \u001b[1m0s\u001b[0m 55ms/step\n",
      "\u001b[1m1/1\u001b[0m \u001b[32m━━━━━━━━━━━━━━━━━━━━\u001b[0m\u001b[37m\u001b[0m \u001b[1m0s\u001b[0m 76ms/step\n",
      "\u001b[1m1/1\u001b[0m \u001b[32m━━━━━━━━━━━━━━━━━━━━\u001b[0m\u001b[37m\u001b[0m \u001b[1m0s\u001b[0m 53ms/step\n",
      "\u001b[1m1/1\u001b[0m \u001b[32m━━━━━━━━━━━━━━━━━━━━\u001b[0m\u001b[37m\u001b[0m \u001b[1m0s\u001b[0m 53ms/step\n",
      "\u001b[1m1/1\u001b[0m \u001b[32m━━━━━━━━━━━━━━━━━━━━\u001b[0m\u001b[37m\u001b[0m \u001b[1m0s\u001b[0m 43ms/step\n",
      "\u001b[1m1/1\u001b[0m \u001b[32m━━━━━━━━━━━━━━━━━━━━\u001b[0m\u001b[37m\u001b[0m \u001b[1m0s\u001b[0m 53ms/step\n",
      "\u001b[1m1/1\u001b[0m \u001b[32m━━━━━━━━━━━━━━━━━━━━\u001b[0m\u001b[37m\u001b[0m \u001b[1m0s\u001b[0m 54ms/step\n",
      "\u001b[1m1/1\u001b[0m \u001b[32m━━━━━━━━━━━━━━━━━━━━\u001b[0m\u001b[37m\u001b[0m \u001b[1m0s\u001b[0m 54ms/step\n",
      "\u001b[1m1/1\u001b[0m \u001b[32m━━━━━━━━━━━━━━━━━━━━\u001b[0m\u001b[37m\u001b[0m \u001b[1m0s\u001b[0m 67ms/step\n",
      "\u001b[1m1/1\u001b[0m \u001b[32m━━━━━━━━━━━━━━━━━━━━\u001b[0m\u001b[37m\u001b[0m \u001b[1m0s\u001b[0m 66ms/step\n",
      "\u001b[1m1/1\u001b[0m \u001b[32m━━━━━━━━━━━━━━━━━━━━\u001b[0m\u001b[37m\u001b[0m \u001b[1m0s\u001b[0m 54ms/step\n",
      "\u001b[1m1/1\u001b[0m \u001b[32m━━━━━━━━━━━━━━━━━━━━\u001b[0m\u001b[37m\u001b[0m \u001b[1m0s\u001b[0m 49ms/step\n",
      "\u001b[1m1/1\u001b[0m \u001b[32m━━━━━━━━━━━━━━━━━━━━\u001b[0m\u001b[37m\u001b[0m \u001b[1m0s\u001b[0m 67ms/step\n",
      "\u001b[1m1/1\u001b[0m \u001b[32m━━━━━━━━━━━━━━━━━━━━\u001b[0m\u001b[37m\u001b[0m \u001b[1m0s\u001b[0m 54ms/step\n",
      "\u001b[1m1/1\u001b[0m \u001b[32m━━━━━━━━━━━━━━━━━━━━\u001b[0m\u001b[37m\u001b[0m \u001b[1m0s\u001b[0m 53ms/step\n",
      "\u001b[1m1/1\u001b[0m \u001b[32m━━━━━━━━━━━━━━━━━━━━\u001b[0m\u001b[37m\u001b[0m \u001b[1m0s\u001b[0m 51ms/step\n",
      "\u001b[1m1/1\u001b[0m \u001b[32m━━━━━━━━━━━━━━━━━━━━\u001b[0m\u001b[37m\u001b[0m \u001b[1m0s\u001b[0m 54ms/step\n",
      "\u001b[1m1/1\u001b[0m \u001b[32m━━━━━━━━━━━━━━━━━━━━\u001b[0m\u001b[37m\u001b[0m \u001b[1m0s\u001b[0m 54ms/step\n",
      "\u001b[1m1/1\u001b[0m \u001b[32m━━━━━━━━━━━━━━━━━━━━\u001b[0m\u001b[37m\u001b[0m \u001b[1m0s\u001b[0m 67ms/step\n",
      "\u001b[1m1/1\u001b[0m \u001b[32m━━━━━━━━━━━━━━━━━━━━\u001b[0m\u001b[37m\u001b[0m \u001b[1m0s\u001b[0m 62ms/step\n",
      "\u001b[1m1/1\u001b[0m \u001b[32m━━━━━━━━━━━━━━━━━━━━\u001b[0m\u001b[37m\u001b[0m \u001b[1m0s\u001b[0m 50ms/step\n",
      "\u001b[1m1/1\u001b[0m \u001b[32m━━━━━━━━━━━━━━━━━━━━\u001b[0m\u001b[37m\u001b[0m \u001b[1m0s\u001b[0m 67ms/step\n",
      "\u001b[1m1/1\u001b[0m \u001b[32m━━━━━━━━━━━━━━━━━━━━\u001b[0m\u001b[37m\u001b[0m \u001b[1m0s\u001b[0m 53ms/step\n",
      "\u001b[1m1/1\u001b[0m \u001b[32m━━━━━━━━━━━━━━━━━━━━\u001b[0m\u001b[37m\u001b[0m \u001b[1m0s\u001b[0m 54ms/step\n",
      "\u001b[1m1/1\u001b[0m \u001b[32m━━━━━━━━━━━━━━━━━━━━\u001b[0m\u001b[37m\u001b[0m \u001b[1m0s\u001b[0m 54ms/step\n",
      "\u001b[1m1/1\u001b[0m \u001b[32m━━━━━━━━━━━━━━━━━━━━\u001b[0m\u001b[37m\u001b[0m \u001b[1m0s\u001b[0m 54ms/step\n",
      "\u001b[1m1/1\u001b[0m \u001b[32m━━━━━━━━━━━━━━━━━━━━\u001b[0m\u001b[37m\u001b[0m \u001b[1m0s\u001b[0m 54ms/step\n",
      "\u001b[1m1/1\u001b[0m \u001b[32m━━━━━━━━━━━━━━━━━━━━\u001b[0m\u001b[37m\u001b[0m \u001b[1m0s\u001b[0m 44ms/step\n",
      "\u001b[1m1/1\u001b[0m \u001b[32m━━━━━━━━━━━━━━━━━━━━\u001b[0m\u001b[37m\u001b[0m \u001b[1m0s\u001b[0m 54ms/step\n",
      "\u001b[1m1/1\u001b[0m \u001b[32m━━━━━━━━━━━━━━━━━━━━\u001b[0m\u001b[37m\u001b[0m \u001b[1m0s\u001b[0m 54ms/step\n",
      "\u001b[1m1/1\u001b[0m \u001b[32m━━━━━━━━━━━━━━━━━━━━\u001b[0m\u001b[37m\u001b[0m \u001b[1m0s\u001b[0m 54ms/step\n",
      "\u001b[1m1/1\u001b[0m \u001b[32m━━━━━━━━━━━━━━━━━━━━\u001b[0m\u001b[37m\u001b[0m \u001b[1m0s\u001b[0m 54ms/step\n",
      "\u001b[1m1/1\u001b[0m \u001b[32m━━━━━━━━━━━━━━━━━━━━\u001b[0m\u001b[37m\u001b[0m \u001b[1m0s\u001b[0m 54ms/step\n",
      "\u001b[1m1/1\u001b[0m \u001b[32m━━━━━━━━━━━━━━━━━━━━\u001b[0m\u001b[37m\u001b[0m \u001b[1m0s\u001b[0m 59ms/step\n",
      "\u001b[1m1/1\u001b[0m \u001b[32m━━━━━━━━━━━━━━━━━━━━\u001b[0m\u001b[37m\u001b[0m \u001b[1m0s\u001b[0m 54ms/step\n",
      "\u001b[1m1/1\u001b[0m \u001b[32m━━━━━━━━━━━━━━━━━━━━\u001b[0m\u001b[37m\u001b[0m \u001b[1m0s\u001b[0m 53ms/step\n",
      "\u001b[1m1/1\u001b[0m \u001b[32m━━━━━━━━━━━━━━━━━━━━\u001b[0m\u001b[37m\u001b[0m \u001b[1m0s\u001b[0m 54ms/step\n",
      "\u001b[1m1/1\u001b[0m \u001b[32m━━━━━━━━━━━━━━━━━━━━\u001b[0m\u001b[37m\u001b[0m \u001b[1m0s\u001b[0m 67ms/step\n",
      "\u001b[1m1/1\u001b[0m \u001b[32m━━━━━━━━━━━━━━━━━━━━\u001b[0m\u001b[37m\u001b[0m \u001b[1m0s\u001b[0m 60ms/step\n",
      "\u001b[1m1/1\u001b[0m \u001b[32m━━━━━━━━━━━━━━━━━━━━\u001b[0m\u001b[37m\u001b[0m \u001b[1m0s\u001b[0m 67ms/step\n",
      "\u001b[1m1/1\u001b[0m \u001b[32m━━━━━━━━━━━━━━━━━━━━\u001b[0m\u001b[37m\u001b[0m \u001b[1m0s\u001b[0m 53ms/step\n",
      "\u001b[1m1/1\u001b[0m \u001b[32m━━━━━━━━━━━━━━━━━━━━\u001b[0m\u001b[37m\u001b[0m \u001b[1m0s\u001b[0m 54ms/step\n",
      "\u001b[1m1/1\u001b[0m \u001b[32m━━━━━━━━━━━━━━━━━━━━\u001b[0m\u001b[37m\u001b[0m \u001b[1m0s\u001b[0m 58ms/step\n",
      "\u001b[1m1/1\u001b[0m \u001b[32m━━━━━━━━━━━━━━━━━━━━\u001b[0m\u001b[37m\u001b[0m \u001b[1m0s\u001b[0m 53ms/step\n",
      "\u001b[1m1/1\u001b[0m \u001b[32m━━━━━━━━━━━━━━━━━━━━\u001b[0m\u001b[37m\u001b[0m \u001b[1m0s\u001b[0m 54ms/step\n",
      "\u001b[1m1/1\u001b[0m \u001b[32m━━━━━━━━━━━━━━━━━━━━\u001b[0m\u001b[37m\u001b[0m \u001b[1m0s\u001b[0m 53ms/step\n",
      "\u001b[1m1/1\u001b[0m \u001b[32m━━━━━━━━━━━━━━━━━━━━\u001b[0m\u001b[37m\u001b[0m \u001b[1m0s\u001b[0m 54ms/step\n",
      "\u001b[1m1/1\u001b[0m \u001b[32m━━━━━━━━━━━━━━━━━━━━\u001b[0m\u001b[37m\u001b[0m \u001b[1m0s\u001b[0m 55ms/step\n",
      "\u001b[1m1/1\u001b[0m \u001b[32m━━━━━━━━━━━━━━━━━━━━\u001b[0m\u001b[37m\u001b[0m \u001b[1m0s\u001b[0m 54ms/step\n",
      "\u001b[1m1/1\u001b[0m \u001b[32m━━━━━━━━━━━━━━━━━━━━\u001b[0m\u001b[37m\u001b[0m \u001b[1m0s\u001b[0m 54ms/step\n",
      "\u001b[1m1/1\u001b[0m \u001b[32m━━━━━━━━━━━━━━━━━━━━\u001b[0m\u001b[37m\u001b[0m \u001b[1m0s\u001b[0m 53ms/step\n",
      "\u001b[1m1/1\u001b[0m \u001b[32m━━━━━━━━━━━━━━━━━━━━\u001b[0m\u001b[37m\u001b[0m \u001b[1m0s\u001b[0m 52ms/step\n",
      "\u001b[1m1/1\u001b[0m \u001b[32m━━━━━━━━━━━━━━━━━━━━\u001b[0m\u001b[37m\u001b[0m \u001b[1m0s\u001b[0m 53ms/step\n",
      "\u001b[1m1/1\u001b[0m \u001b[32m━━━━━━━━━━━━━━━━━━━━\u001b[0m\u001b[37m\u001b[0m \u001b[1m0s\u001b[0m 54ms/step\n",
      "\u001b[1m1/1\u001b[0m \u001b[32m━━━━━━━━━━━━━━━━━━━━\u001b[0m\u001b[37m\u001b[0m \u001b[1m0s\u001b[0m 65ms/step\n",
      "\u001b[1m1/1\u001b[0m \u001b[32m━━━━━━━━━━━━━━━━━━━━\u001b[0m\u001b[37m\u001b[0m \u001b[1m0s\u001b[0m 53ms/step\n",
      "\u001b[1m1/1\u001b[0m \u001b[32m━━━━━━━━━━━━━━━━━━━━\u001b[0m\u001b[37m\u001b[0m \u001b[1m0s\u001b[0m 64ms/step\n",
      "\u001b[1m1/1\u001b[0m \u001b[32m━━━━━━━━━━━━━━━━━━━━\u001b[0m\u001b[37m\u001b[0m \u001b[1m0s\u001b[0m 67ms/step\n",
      "\u001b[1m1/1\u001b[0m \u001b[32m━━━━━━━━━━━━━━━━━━━━\u001b[0m\u001b[37m\u001b[0m \u001b[1m0s\u001b[0m 54ms/step\n",
      "\u001b[1m1/1\u001b[0m \u001b[32m━━━━━━━━━━━━━━━━━━━━\u001b[0m\u001b[37m\u001b[0m \u001b[1m0s\u001b[0m 54ms/step\n",
      "\u001b[1m1/1\u001b[0m \u001b[32m━━━━━━━━━━━━━━━━━━━━\u001b[0m\u001b[37m\u001b[0m \u001b[1m0s\u001b[0m 54ms/step\n",
      "\u001b[1m1/1\u001b[0m \u001b[32m━━━━━━━━━━━━━━━━━━━━\u001b[0m\u001b[37m\u001b[0m \u001b[1m0s\u001b[0m 45ms/step\n",
      "\u001b[1m1/1\u001b[0m \u001b[32m━━━━━━━━━━━━━━━━━━━━\u001b[0m\u001b[37m\u001b[0m \u001b[1m0s\u001b[0m 54ms/step\n",
      "\u001b[1m1/1\u001b[0m \u001b[32m━━━━━━━━━━━━━━━━━━━━\u001b[0m\u001b[37m\u001b[0m \u001b[1m0s\u001b[0m 54ms/step\n",
      "\u001b[1m1/1\u001b[0m \u001b[32m━━━━━━━━━━━━━━━━━━━━\u001b[0m\u001b[37m\u001b[0m \u001b[1m0s\u001b[0m 53ms/step\n",
      "\u001b[1m1/1\u001b[0m \u001b[32m━━━━━━━━━━━━━━━━━━━━\u001b[0m\u001b[37m\u001b[0m \u001b[1m0s\u001b[0m 64ms/step\n",
      "\u001b[1m1/1\u001b[0m \u001b[32m━━━━━━━━━━━━━━━━━━━━\u001b[0m\u001b[37m\u001b[0m \u001b[1m0s\u001b[0m 54ms/step\n",
      "\u001b[1m1/1\u001b[0m \u001b[32m━━━━━━━━━━━━━━━━━━━━\u001b[0m\u001b[37m\u001b[0m \u001b[1m0s\u001b[0m 54ms/step\n",
      "\u001b[1m1/1\u001b[0m \u001b[32m━━━━━━━━━━━━━━━━━━━━\u001b[0m\u001b[37m\u001b[0m \u001b[1m0s\u001b[0m 54ms/step\n",
      "\u001b[1m1/1\u001b[0m \u001b[32m━━━━━━━━━━━━━━━━━━━━\u001b[0m\u001b[37m\u001b[0m \u001b[1m0s\u001b[0m 57ms/step\n",
      "\u001b[1m1/1\u001b[0m \u001b[32m━━━━━━━━━━━━━━━━━━━━\u001b[0m\u001b[37m\u001b[0m \u001b[1m0s\u001b[0m 54ms/step\n",
      "\u001b[1m1/1\u001b[0m \u001b[32m━━━━━━━━━━━━━━━━━━━━\u001b[0m\u001b[37m\u001b[0m \u001b[1m0s\u001b[0m 54ms/step\n",
      "\u001b[1m1/1\u001b[0m \u001b[32m━━━━━━━━━━━━━━━━━━━━\u001b[0m\u001b[37m\u001b[0m \u001b[1m0s\u001b[0m 44ms/step\n",
      "\u001b[1m1/1\u001b[0m \u001b[32m━━━━━━━━━━━━━━━━━━━━\u001b[0m\u001b[37m\u001b[0m \u001b[1m0s\u001b[0m 54ms/step\n",
      "\u001b[1m1/1\u001b[0m \u001b[32m━━━━━━━━━━━━━━━━━━━━\u001b[0m\u001b[37m\u001b[0m \u001b[1m0s\u001b[0m 67ms/step\n",
      "\u001b[1m1/1\u001b[0m \u001b[32m━━━━━━━━━━━━━━━━━━━━\u001b[0m\u001b[37m\u001b[0m \u001b[1m0s\u001b[0m 54ms/step\n",
      "\u001b[1m1/1\u001b[0m \u001b[32m━━━━━━━━━━━━━━━━━━━━\u001b[0m\u001b[37m\u001b[0m \u001b[1m0s\u001b[0m 54ms/step\n",
      "\u001b[1m1/1\u001b[0m \u001b[32m━━━━━━━━━━━━━━━━━━━━\u001b[0m\u001b[37m\u001b[0m \u001b[1m0s\u001b[0m 54ms/step\n",
      "\u001b[1m1/1\u001b[0m \u001b[32m━━━━━━━━━━━━━━━━━━━━\u001b[0m\u001b[37m\u001b[0m \u001b[1m0s\u001b[0m 66ms/step\n",
      "\u001b[1m1/1\u001b[0m \u001b[32m━━━━━━━━━━━━━━━━━━━━\u001b[0m\u001b[37m\u001b[0m \u001b[1m0s\u001b[0m 48ms/step\n",
      "\u001b[1m1/1\u001b[0m \u001b[32m━━━━━━━━━━━━━━━━━━━━\u001b[0m\u001b[37m\u001b[0m \u001b[1m0s\u001b[0m 67ms/step\n",
      "\u001b[1m1/1\u001b[0m \u001b[32m━━━━━━━━━━━━━━━━━━━━\u001b[0m\u001b[37m\u001b[0m \u001b[1m0s\u001b[0m 54ms/step\n",
      "\u001b[1m1/1\u001b[0m \u001b[32m━━━━━━━━━━━━━━━━━━━━\u001b[0m\u001b[37m\u001b[0m \u001b[1m0s\u001b[0m 54ms/step\n",
      "\u001b[1m1/1\u001b[0m \u001b[32m━━━━━━━━━━━━━━━━━━━━\u001b[0m\u001b[37m\u001b[0m \u001b[1m0s\u001b[0m 53ms/step\n",
      "\u001b[1m1/1\u001b[0m \u001b[32m━━━━━━━━━━━━━━━━━━━━\u001b[0m\u001b[37m\u001b[0m \u001b[1m0s\u001b[0m 54ms/step\n",
      "\u001b[1m1/1\u001b[0m \u001b[32m━━━━━━━━━━━━━━━━━━━━\u001b[0m\u001b[37m\u001b[0m \u001b[1m0s\u001b[0m 60ms/step\n",
      "\u001b[1m1/1\u001b[0m \u001b[32m━━━━━━━━━━━━━━━━━━━━\u001b[0m\u001b[37m\u001b[0m \u001b[1m0s\u001b[0m 54ms/step\n",
      "\u001b[1m1/1\u001b[0m \u001b[32m━━━━━━━━━━━━━━━━━━━━\u001b[0m\u001b[37m\u001b[0m \u001b[1m0s\u001b[0m 54ms/step\n",
      "\u001b[1m1/1\u001b[0m \u001b[32m━━━━━━━━━━━━━━━━━━━━\u001b[0m\u001b[37m\u001b[0m \u001b[1m0s\u001b[0m 53ms/step\n",
      "\u001b[1m1/1\u001b[0m \u001b[32m━━━━━━━━━━━━━━━━━━━━\u001b[0m\u001b[37m\u001b[0m \u001b[1m0s\u001b[0m 54ms/step\n",
      "\u001b[1m1/1\u001b[0m \u001b[32m━━━━━━━━━━━━━━━━━━━━\u001b[0m\u001b[37m\u001b[0m \u001b[1m0s\u001b[0m 54ms/step\n",
      "\u001b[1m1/1\u001b[0m \u001b[32m━━━━━━━━━━━━━━━━━━━━\u001b[0m\u001b[37m\u001b[0m \u001b[1m0s\u001b[0m 54ms/step\n",
      "\u001b[1m1/1\u001b[0m \u001b[32m━━━━━━━━━━━━━━━━━━━━\u001b[0m\u001b[37m\u001b[0m \u001b[1m0s\u001b[0m 47ms/step\n",
      "\u001b[1m1/1\u001b[0m \u001b[32m━━━━━━━━━━━━━━━━━━━━\u001b[0m\u001b[37m\u001b[0m \u001b[1m0s\u001b[0m 54ms/step\n",
      "\u001b[1m1/1\u001b[0m \u001b[32m━━━━━━━━━━━━━━━━━━━━\u001b[0m\u001b[37m\u001b[0m \u001b[1m0s\u001b[0m 54ms/step\n",
      "\u001b[1m1/1\u001b[0m \u001b[32m━━━━━━━━━━━━━━━━━━━━\u001b[0m\u001b[37m\u001b[0m \u001b[1m0s\u001b[0m 54ms/step\n",
      "\u001b[1m1/1\u001b[0m \u001b[32m━━━━━━━━━━━━━━━━━━━━\u001b[0m\u001b[37m\u001b[0m \u001b[1m0s\u001b[0m 54ms/step\n",
      "\u001b[1m1/1\u001b[0m \u001b[32m━━━━━━━━━━━━━━━━━━━━\u001b[0m\u001b[37m\u001b[0m \u001b[1m0s\u001b[0m 54ms/step\n",
      "\u001b[1m1/1\u001b[0m \u001b[32m━━━━━━━━━━━━━━━━━━━━\u001b[0m\u001b[37m\u001b[0m \u001b[1m0s\u001b[0m 61ms/step\n",
      "\u001b[1m1/1\u001b[0m \u001b[32m━━━━━━━━━━━━━━━━━━━━\u001b[0m\u001b[37m\u001b[0m \u001b[1m0s\u001b[0m 53ms/step\n",
      "\u001b[1m1/1\u001b[0m \u001b[32m━━━━━━━━━━━━━━━━━━━━\u001b[0m\u001b[37m\u001b[0m \u001b[1m0s\u001b[0m 54ms/step\n",
      "\u001b[1m1/1\u001b[0m \u001b[32m━━━━━━━━━━━━━━━━━━━━\u001b[0m\u001b[37m\u001b[0m \u001b[1m0s\u001b[0m 42ms/step\n",
      "\u001b[1m1/1\u001b[0m \u001b[32m━━━━━━━━━━━━━━━━━━━━\u001b[0m\u001b[37m\u001b[0m \u001b[1m0s\u001b[0m 54ms/step\n",
      "\u001b[1m1/1\u001b[0m \u001b[32m━━━━━━━━━━━━━━━━━━━━\u001b[0m\u001b[37m\u001b[0m \u001b[1m0s\u001b[0m 54ms/step\n",
      "\u001b[1m1/1\u001b[0m \u001b[32m━━━━━━━━━━━━━━━━━━━━\u001b[0m\u001b[37m\u001b[0m \u001b[1m0s\u001b[0m 54ms/step\n",
      "\u001b[1m1/1\u001b[0m \u001b[32m━━━━━━━━━━━━━━━━━━━━\u001b[0m\u001b[37m\u001b[0m \u001b[1m0s\u001b[0m 54ms/step\n",
      "\u001b[1m1/1\u001b[0m \u001b[32m━━━━━━━━━━━━━━━━━━━━\u001b[0m\u001b[37m\u001b[0m \u001b[1m0s\u001b[0m 66ms/step\n",
      "\u001b[1m1/1\u001b[0m \u001b[32m━━━━━━━━━━━━━━━━━━━━\u001b[0m\u001b[37m\u001b[0m \u001b[1m0s\u001b[0m 64ms/step\n",
      "\u001b[1m1/1\u001b[0m \u001b[32m━━━━━━━━━━━━━━━━━━━━\u001b[0m\u001b[37m\u001b[0m \u001b[1m0s\u001b[0m 50ms/step\n",
      "\u001b[1m1/1\u001b[0m \u001b[32m━━━━━━━━━━━━━━━━━━━━\u001b[0m\u001b[37m\u001b[0m \u001b[1m0s\u001b[0m 54ms/step\n",
      "\u001b[1m1/1\u001b[0m \u001b[32m━━━━━━━━━━━━━━━━━━━━\u001b[0m\u001b[37m\u001b[0m \u001b[1m0s\u001b[0m 53ms/step\n",
      "\u001b[1m1/1\u001b[0m \u001b[32m━━━━━━━━━━━━━━━━━━━━\u001b[0m\u001b[37m\u001b[0m \u001b[1m0s\u001b[0m 54ms/step\n",
      "\u001b[1m1/1\u001b[0m \u001b[32m━━━━━━━━━━━━━━━━━━━━\u001b[0m\u001b[37m\u001b[0m \u001b[1m0s\u001b[0m 67ms/step\n",
      "\u001b[1m1/1\u001b[0m \u001b[32m━━━━━━━━━━━━━━━━━━━━\u001b[0m\u001b[37m\u001b[0m \u001b[1m0s\u001b[0m 43ms/step\n",
      "\u001b[1m1/1\u001b[0m \u001b[32m━━━━━━━━━━━━━━━━━━━━\u001b[0m\u001b[37m\u001b[0m \u001b[1m0s\u001b[0m 54ms/step\n",
      "\u001b[1m1/1\u001b[0m \u001b[32m━━━━━━━━━━━━━━━━━━━━\u001b[0m\u001b[37m\u001b[0m \u001b[1m0s\u001b[0m 54ms/step\n",
      "\u001b[1m1/1\u001b[0m \u001b[32m━━━━━━━━━━━━━━━━━━━━\u001b[0m\u001b[37m\u001b[0m \u001b[1m0s\u001b[0m 67ms/step\n",
      "\u001b[1m1/1\u001b[0m \u001b[32m━━━━━━━━━━━━━━━━━━━━\u001b[0m\u001b[37m\u001b[0m \u001b[1m0s\u001b[0m 65ms/step\n",
      "\u001b[1m1/1\u001b[0m \u001b[32m━━━━━━━━━━━━━━━━━━━━\u001b[0m\u001b[37m\u001b[0m \u001b[1m0s\u001b[0m 54ms/step\n",
      "\u001b[1m1/1\u001b[0m \u001b[32m━━━━━━━━━━━━━━━━━━━━\u001b[0m\u001b[37m\u001b[0m \u001b[1m0s\u001b[0m 53ms/step\n",
      "\u001b[1m1/1\u001b[0m \u001b[32m━━━━━━━━━━━━━━━━━━━━\u001b[0m\u001b[37m\u001b[0m \u001b[1m0s\u001b[0m 54ms/step\n",
      "\u001b[1m1/1\u001b[0m \u001b[32m━━━━━━━━━━━━━━━━━━━━\u001b[0m\u001b[37m\u001b[0m \u001b[1m0s\u001b[0m 52ms/step\n",
      "\u001b[1m1/1\u001b[0m \u001b[32m━━━━━━━━━━━━━━━━━━━━\u001b[0m\u001b[37m\u001b[0m \u001b[1m0s\u001b[0m 42ms/step\n",
      "\u001b[1m1/1\u001b[0m \u001b[32m━━━━━━━━━━━━━━━━━━━━\u001b[0m\u001b[37m\u001b[0m \u001b[1m0s\u001b[0m 54ms/step\n",
      "\u001b[1m1/1\u001b[0m \u001b[32m━━━━━━━━━━━━━━━━━━━━\u001b[0m\u001b[37m\u001b[0m \u001b[1m0s\u001b[0m 54ms/step\n",
      "\u001b[1m1/1\u001b[0m \u001b[32m━━━━━━━━━━━━━━━━━━━━\u001b[0m\u001b[37m\u001b[0m \u001b[1m0s\u001b[0m 54ms/step\n",
      "\u001b[1m1/1\u001b[0m \u001b[32m━━━━━━━━━━━━━━━━━━━━\u001b[0m\u001b[37m\u001b[0m \u001b[1m0s\u001b[0m 61ms/step\n",
      "\u001b[1m1/1\u001b[0m \u001b[32m━━━━━━━━━━━━━━━━━━━━\u001b[0m\u001b[37m\u001b[0m \u001b[1m0s\u001b[0m 53ms/step\n",
      "\u001b[1m1/1\u001b[0m \u001b[32m━━━━━━━━━━━━━━━━━━━━\u001b[0m\u001b[37m\u001b[0m \u001b[1m0s\u001b[0m 54ms/step\n",
      "\u001b[1m1/1\u001b[0m \u001b[32m━━━━━━━━━━━━━━━━━━━━\u001b[0m\u001b[37m\u001b[0m \u001b[1m0s\u001b[0m 66ms/step\n",
      "\u001b[1m1/1\u001b[0m \u001b[32m━━━━━━━━━━━━━━━━━━━━\u001b[0m\u001b[37m\u001b[0m \u001b[1m0s\u001b[0m 67ms/step\n",
      "\u001b[1m1/1\u001b[0m \u001b[32m━━━━━━━━━━━━━━━━━━━━\u001b[0m\u001b[37m\u001b[0m \u001b[1m0s\u001b[0m 66ms/step\n",
      "\u001b[1m1/1\u001b[0m \u001b[32m━━━━━━━━━━━━━━━━━━━━\u001b[0m\u001b[37m\u001b[0m \u001b[1m0s\u001b[0m 59ms/step\n",
      "\u001b[1m1/1\u001b[0m \u001b[32m━━━━━━━━━━━━━━━━━━━━\u001b[0m\u001b[37m\u001b[0m \u001b[1m0s\u001b[0m 53ms/step\n",
      "\u001b[1m1/1\u001b[0m \u001b[32m━━━━━━━━━━━━━━━━━━━━\u001b[0m\u001b[37m\u001b[0m \u001b[1m0s\u001b[0m 53ms/step\n",
      "\u001b[1m1/1\u001b[0m \u001b[32m━━━━━━━━━━━━━━━━━━━━\u001b[0m\u001b[37m\u001b[0m \u001b[1m0s\u001b[0m 54ms/step\n",
      "\u001b[1m1/1\u001b[0m \u001b[32m━━━━━━━━━━━━━━━━━━━━\u001b[0m\u001b[37m\u001b[0m \u001b[1m0s\u001b[0m 67ms/step\n",
      "\u001b[1m1/1\u001b[0m \u001b[32m━━━━━━━━━━━━━━━━━━━━\u001b[0m\u001b[37m\u001b[0m \u001b[1m0s\u001b[0m 58ms/step\n",
      "\u001b[1m1/1\u001b[0m \u001b[32m━━━━━━━━━━━━━━━━━━━━\u001b[0m\u001b[37m\u001b[0m \u001b[1m0s\u001b[0m 54ms/step\n",
      "\u001b[1m1/1\u001b[0m \u001b[32m━━━━━━━━━━━━━━━━━━━━\u001b[0m\u001b[37m\u001b[0m \u001b[1m0s\u001b[0m 54ms/step\n",
      "\u001b[1m1/1\u001b[0m \u001b[32m━━━━━━━━━━━━━━━━━━━━\u001b[0m\u001b[37m\u001b[0m \u001b[1m0s\u001b[0m 47ms/step\n",
      "\u001b[1m1/1\u001b[0m \u001b[32m━━━━━━━━━━━━━━━━━━━━\u001b[0m\u001b[37m\u001b[0m \u001b[1m0s\u001b[0m 53ms/step\n",
      "\u001b[1m1/1\u001b[0m \u001b[32m━━━━━━━━━━━━━━━━━━━━\u001b[0m\u001b[37m\u001b[0m \u001b[1m0s\u001b[0m 54ms/step\n",
      "\u001b[1m1/1\u001b[0m \u001b[32m━━━━━━━━━━━━━━━━━━━━\u001b[0m\u001b[37m\u001b[0m \u001b[1m0s\u001b[0m 54ms/step\n",
      "\u001b[1m1/1\u001b[0m \u001b[32m━━━━━━━━━━━━━━━━━━━━\u001b[0m\u001b[37m\u001b[0m \u001b[1m0s\u001b[0m 56ms/step\n",
      "\u001b[1m1/1\u001b[0m \u001b[32m━━━━━━━━━━━━━━━━━━━━\u001b[0m\u001b[37m\u001b[0m \u001b[1m0s\u001b[0m 67ms/step\n",
      "\u001b[1m1/1\u001b[0m \u001b[32m━━━━━━━━━━━━━━━━━━━━\u001b[0m\u001b[37m\u001b[0m \u001b[1m0s\u001b[0m 40ms/step\n",
      "\u001b[1m1/1\u001b[0m \u001b[32m━━━━━━━━━━━━━━━━━━━━\u001b[0m\u001b[37m\u001b[0m \u001b[1m0s\u001b[0m 53ms/step\n",
      "\u001b[1m1/1\u001b[0m \u001b[32m━━━━━━━━━━━━━━━━━━━━\u001b[0m\u001b[37m\u001b[0m \u001b[1m0s\u001b[0m 68ms/step\n",
      "\u001b[1m1/1\u001b[0m \u001b[32m━━━━━━━━━━━━━━━━━━━━\u001b[0m\u001b[37m\u001b[0m \u001b[1m0s\u001b[0m 54ms/step\n",
      "\u001b[1m1/1\u001b[0m \u001b[32m━━━━━━━━━━━━━━━━━━━━\u001b[0m\u001b[37m\u001b[0m \u001b[1m0s\u001b[0m 67ms/step\n",
      "\u001b[1m1/1\u001b[0m \u001b[32m━━━━━━━━━━━━━━━━━━━━\u001b[0m\u001b[37m\u001b[0m \u001b[1m0s\u001b[0m 53ms/step\n",
      "\u001b[1m1/1\u001b[0m \u001b[32m━━━━━━━━━━━━━━━━━━━━\u001b[0m\u001b[37m\u001b[0m \u001b[1m0s\u001b[0m 54ms/step\n",
      "\u001b[1m1/1\u001b[0m \u001b[32m━━━━━━━━━━━━━━━━━━━━\u001b[0m\u001b[37m\u001b[0m \u001b[1m0s\u001b[0m 53ms/step\n",
      "\u001b[1m1/1\u001b[0m \u001b[32m━━━━━━━━━━━━━━━━━━━━\u001b[0m\u001b[37m\u001b[0m \u001b[1m0s\u001b[0m 54ms/step\n",
      "\u001b[1m1/1\u001b[0m \u001b[32m━━━━━━━━━━━━━━━━━━━━\u001b[0m\u001b[37m\u001b[0m \u001b[1m0s\u001b[0m 54ms/step\n",
      "\u001b[1m1/1\u001b[0m \u001b[32m━━━━━━━━━━━━━━━━━━━━\u001b[0m\u001b[37m\u001b[0m \u001b[1m0s\u001b[0m 54ms/step\n",
      "\u001b[1m1/1\u001b[0m \u001b[32m━━━━━━━━━━━━━━━━━━━━\u001b[0m\u001b[37m\u001b[0m \u001b[1m0s\u001b[0m 53ms/step\n",
      "\u001b[1m1/1\u001b[0m \u001b[32m━━━━━━━━━━━━━━━━━━━━\u001b[0m\u001b[37m\u001b[0m \u001b[1m0s\u001b[0m 52ms/step\n",
      "\u001b[1m1/1\u001b[0m \u001b[32m━━━━━━━━━━━━━━━━━━━━\u001b[0m\u001b[37m\u001b[0m \u001b[1m0s\u001b[0m 54ms/step\n",
      "\u001b[1m1/1\u001b[0m \u001b[32m━━━━━━━━━━━━━━━━━━━━\u001b[0m\u001b[37m\u001b[0m \u001b[1m0s\u001b[0m 54ms/step\n",
      "\u001b[1m1/1\u001b[0m \u001b[32m━━━━━━━━━━━━━━━━━━━━\u001b[0m\u001b[37m\u001b[0m \u001b[1m0s\u001b[0m 53ms/step\n",
      "\u001b[1m1/1\u001b[0m \u001b[32m━━━━━━━━━━━━━━━━━━━━\u001b[0m\u001b[37m\u001b[0m \u001b[1m0s\u001b[0m 54ms/step\n",
      "\u001b[1m1/1\u001b[0m \u001b[32m━━━━━━━━━━━━━━━━━━━━\u001b[0m\u001b[37m\u001b[0m \u001b[1m0s\u001b[0m 54ms/step\n",
      "\u001b[1m1/1\u001b[0m \u001b[32m━━━━━━━━━━━━━━━━━━━━\u001b[0m\u001b[37m\u001b[0m \u001b[1m0s\u001b[0m 41ms/step\n",
      "\u001b[1m1/1\u001b[0m \u001b[32m━━━━━━━━━━━━━━━━━━━━\u001b[0m\u001b[37m\u001b[0m \u001b[1m0s\u001b[0m 67ms/step\n",
      "\u001b[1m1/1\u001b[0m \u001b[32m━━━━━━━━━━━━━━━━━━━━\u001b[0m\u001b[37m\u001b[0m \u001b[1m0s\u001b[0m 54ms/step\n",
      "\u001b[1m1/1\u001b[0m \u001b[32m━━━━━━━━━━━━━━━━━━━━\u001b[0m\u001b[37m\u001b[0m \u001b[1m0s\u001b[0m 54ms/step\n",
      "\u001b[1m1/1\u001b[0m \u001b[32m━━━━━━━━━━━━━━━━━━━━\u001b[0m\u001b[37m\u001b[0m \u001b[1m0s\u001b[0m 54ms/step\n",
      "\u001b[1m1/1\u001b[0m \u001b[32m━━━━━━━━━━━━━━━━━━━━\u001b[0m\u001b[37m\u001b[0m \u001b[1m0s\u001b[0m 54ms/step\n",
      "\u001b[1m1/1\u001b[0m \u001b[32m━━━━━━━━━━━━━━━━━━━━\u001b[0m\u001b[37m\u001b[0m \u001b[1m0s\u001b[0m 54ms/step\n",
      "\u001b[1m1/1\u001b[0m \u001b[32m━━━━━━━━━━━━━━━━━━━━\u001b[0m\u001b[37m\u001b[0m \u001b[1m0s\u001b[0m 47ms/step\n",
      "\u001b[1m1/1\u001b[0m \u001b[32m━━━━━━━━━━━━━━━━━━━━\u001b[0m\u001b[37m\u001b[0m \u001b[1m0s\u001b[0m 54ms/step\n",
      "\u001b[1m1/1\u001b[0m \u001b[32m━━━━━━━━━━━━━━━━━━━━\u001b[0m\u001b[37m\u001b[0m \u001b[1m0s\u001b[0m 54ms/step\n",
      "\u001b[1m1/1\u001b[0m \u001b[32m━━━━━━━━━━━━━━━━━━━━\u001b[0m\u001b[37m\u001b[0m \u001b[1m0s\u001b[0m 67ms/step\n",
      "\u001b[1m1/1\u001b[0m \u001b[32m━━━━━━━━━━━━━━━━━━━━\u001b[0m\u001b[37m\u001b[0m \u001b[1m0s\u001b[0m 66ms/step\n",
      "\u001b[1m1/1\u001b[0m \u001b[32m━━━━━━━━━━━━━━━━━━━━\u001b[0m\u001b[37m\u001b[0m \u001b[1m0s\u001b[0m 48ms/step\n",
      "\u001b[1m1/1\u001b[0m \u001b[32m━━━━━━━━━━━━━━━━━━━━\u001b[0m\u001b[37m\u001b[0m \u001b[1m0s\u001b[0m 54ms/step\n",
      "\u001b[1m1/1\u001b[0m \u001b[32m━━━━━━━━━━━━━━━━━━━━\u001b[0m\u001b[37m\u001b[0m \u001b[1m0s\u001b[0m 54ms/step\n",
      "\u001b[1m1/1\u001b[0m \u001b[32m━━━━━━━━━━━━━━━━━━━━\u001b[0m\u001b[37m\u001b[0m \u001b[1m0s\u001b[0m 54ms/step\n",
      "\u001b[1m1/1\u001b[0m \u001b[32m━━━━━━━━━━━━━━━━━━━━\u001b[0m\u001b[37m\u001b[0m \u001b[1m0s\u001b[0m 50ms/step\n",
      "\u001b[1m1/1\u001b[0m \u001b[32m━━━━━━━━━━━━━━━━━━━━\u001b[0m\u001b[37m\u001b[0m \u001b[1m0s\u001b[0m 54ms/step\n",
      "\u001b[1m1/1\u001b[0m \u001b[32m━━━━━━━━━━━━━━━━━━━━\u001b[0m\u001b[37m\u001b[0m \u001b[1m0s\u001b[0m 53ms/step\n",
      "\u001b[1m1/1\u001b[0m \u001b[32m━━━━━━━━━━━━━━━━━━━━\u001b[0m\u001b[37m\u001b[0m \u001b[1m0s\u001b[0m 54ms/step\n",
      "\u001b[1m1/1\u001b[0m \u001b[32m━━━━━━━━━━━━━━━━━━━━\u001b[0m\u001b[37m\u001b[0m \u001b[1m0s\u001b[0m 54ms/step\n",
      "\u001b[1m1/1\u001b[0m \u001b[32m━━━━━━━━━━━━━━━━━━━━\u001b[0m\u001b[37m\u001b[0m \u001b[1m0s\u001b[0m 46ms/step\n",
      "\u001b[1m1/1\u001b[0m \u001b[32m━━━━━━━━━━━━━━━━━━━━\u001b[0m\u001b[37m\u001b[0m \u001b[1m0s\u001b[0m 54ms/step\n",
      "\u001b[1m1/1\u001b[0m \u001b[32m━━━━━━━━━━━━━━━━━━━━\u001b[0m\u001b[37m\u001b[0m \u001b[1m0s\u001b[0m 54ms/step\n",
      "\u001b[1m1/1\u001b[0m \u001b[32m━━━━━━━━━━━━━━━━━━━━\u001b[0m\u001b[37m\u001b[0m \u001b[1m0s\u001b[0m 54ms/step\n",
      "\u001b[1m1/1\u001b[0m \u001b[32m━━━━━━━━━━━━━━━━━━━━\u001b[0m\u001b[37m\u001b[0m \u001b[1m0s\u001b[0m 52ms/step\n",
      "\u001b[1m1/1\u001b[0m \u001b[32m━━━━━━━━━━━━━━━━━━━━\u001b[0m\u001b[37m\u001b[0m \u001b[1m0s\u001b[0m 54ms/step\n",
      "\u001b[1m1/1\u001b[0m \u001b[32m━━━━━━━━━━━━━━━━━━━━\u001b[0m\u001b[37m\u001b[0m \u001b[1m0s\u001b[0m 54ms/step\n",
      "\u001b[1m1/1\u001b[0m \u001b[32m━━━━━━━━━━━━━━━━━━━━\u001b[0m\u001b[37m\u001b[0m \u001b[1m0s\u001b[0m 54ms/step\n",
      "\u001b[1m1/1\u001b[0m \u001b[32m━━━━━━━━━━━━━━━━━━━━\u001b[0m\u001b[37m\u001b[0m \u001b[1m0s\u001b[0m 63ms/step\n",
      "\u001b[1m1/1\u001b[0m \u001b[32m━━━━━━━━━━━━━━━━━━━━\u001b[0m\u001b[37m\u001b[0m \u001b[1m0s\u001b[0m 52ms/step\n",
      "\u001b[1m1/1\u001b[0m \u001b[32m━━━━━━━━━━━━━━━━━━━━\u001b[0m\u001b[37m\u001b[0m \u001b[1m0s\u001b[0m 54ms/step\n",
      "\u001b[1m1/1\u001b[0m \u001b[32m━━━━━━━━━━━━━━━━━━━━\u001b[0m\u001b[37m\u001b[0m \u001b[1m0s\u001b[0m 53ms/step\n",
      "\u001b[1m1/1\u001b[0m \u001b[32m━━━━━━━━━━━━━━━━━━━━\u001b[0m\u001b[37m\u001b[0m \u001b[1m0s\u001b[0m 53ms/step\n",
      "\u001b[1m1/1\u001b[0m \u001b[32m━━━━━━━━━━━━━━━━━━━━\u001b[0m\u001b[37m\u001b[0m \u001b[1m0s\u001b[0m 43ms/step\n",
      "\u001b[1m1/1\u001b[0m \u001b[32m━━━━━━━━━━━━━━━━━━━━\u001b[0m\u001b[37m\u001b[0m \u001b[1m0s\u001b[0m 53ms/step\n",
      "\u001b[1m1/1\u001b[0m \u001b[32m━━━━━━━━━━━━━━━━━━━━\u001b[0m\u001b[37m\u001b[0m \u001b[1m0s\u001b[0m 54ms/step\n",
      "\u001b[1m1/1\u001b[0m \u001b[32m━━━━━━━━━━━━━━━━━━━━\u001b[0m\u001b[37m\u001b[0m \u001b[1m0s\u001b[0m 54ms/step\n",
      "\u001b[1m1/1\u001b[0m \u001b[32m━━━━━━━━━━━━━━━━━━━━\u001b[0m\u001b[37m\u001b[0m \u001b[1m0s\u001b[0m 63ms/step\n",
      "\u001b[1m1/1\u001b[0m \u001b[32m━━━━━━━━━━━━━━━━━━━━\u001b[0m\u001b[37m\u001b[0m \u001b[1m0s\u001b[0m 57ms/step\n",
      "\u001b[1m1/1\u001b[0m \u001b[32m━━━━━━━━━━━━━━━━━━━━\u001b[0m\u001b[37m\u001b[0m \u001b[1m0s\u001b[0m 63ms/step\n",
      "\u001b[1m1/1\u001b[0m \u001b[32m━━━━━━━━━━━━━━━━━━━━\u001b[0m\u001b[37m\u001b[0m \u001b[1m0s\u001b[0m 49ms/step\n",
      "\u001b[1m1/1\u001b[0m \u001b[32m━━━━━━━━━━━━━━━━━━━━\u001b[0m\u001b[37m\u001b[0m \u001b[1m0s\u001b[0m 66ms/step\n",
      "\u001b[1m1/1\u001b[0m \u001b[32m━━━━━━━━━━━━━━━━━━━━\u001b[0m\u001b[37m\u001b[0m \u001b[1m0s\u001b[0m 53ms/step\n",
      "\u001b[1m1/1\u001b[0m \u001b[32m━━━━━━━━━━━━━━━━━━━━\u001b[0m\u001b[37m\u001b[0m \u001b[1m0s\u001b[0m 53ms/step\n",
      "\u001b[1m1/1\u001b[0m \u001b[32m━━━━━━━━━━━━━━━━━━━━\u001b[0m\u001b[37m\u001b[0m \u001b[1m0s\u001b[0m 48ms/step\n",
      "\u001b[1m1/1\u001b[0m \u001b[32m━━━━━━━━━━━━━━━━━━━━\u001b[0m\u001b[37m\u001b[0m \u001b[1m0s\u001b[0m 54ms/step\n",
      "\u001b[1m1/1\u001b[0m \u001b[32m━━━━━━━━━━━━━━━━━━━━\u001b[0m\u001b[37m\u001b[0m \u001b[1m0s\u001b[0m 52ms/step\n",
      "\u001b[1m1/1\u001b[0m \u001b[32m━━━━━━━━━━━━━━━━━━━━\u001b[0m\u001b[37m\u001b[0m \u001b[1m0s\u001b[0m 67ms/step\n",
      "\u001b[1m1/1\u001b[0m \u001b[32m━━━━━━━━━━━━━━━━━━━━\u001b[0m\u001b[37m\u001b[0m \u001b[1m0s\u001b[0m 52ms/step\n",
      "\u001b[1m1/1\u001b[0m \u001b[32m━━━━━━━━━━━━━━━━━━━━\u001b[0m\u001b[37m\u001b[0m \u001b[1m0s\u001b[0m 49ms/step\n",
      "\u001b[1m1/1\u001b[0m \u001b[32m━━━━━━━━━━━━━━━━━━━━\u001b[0m\u001b[37m\u001b[0m \u001b[1m0s\u001b[0m 67ms/step\n",
      "\u001b[1m1/1\u001b[0m \u001b[32m━━━━━━━━━━━━━━━━━━━━\u001b[0m\u001b[37m\u001b[0m \u001b[1m0s\u001b[0m 54ms/step\n",
      "\u001b[1m1/1\u001b[0m \u001b[32m━━━━━━━━━━━━━━━━━━━━\u001b[0m\u001b[37m\u001b[0m \u001b[1m0s\u001b[0m 54ms/step\n",
      "\u001b[1m1/1\u001b[0m \u001b[32m━━━━━━━━━━━━━━━━━━━━\u001b[0m\u001b[37m\u001b[0m \u001b[1m0s\u001b[0m 54ms/step\n",
      "\u001b[1m1/1\u001b[0m \u001b[32m━━━━━━━━━━━━━━━━━━━━\u001b[0m\u001b[37m\u001b[0m \u001b[1m0s\u001b[0m 52ms/step\n",
      "\u001b[1m1/1\u001b[0m \u001b[32m━━━━━━━━━━━━━━━━━━━━\u001b[0m\u001b[37m\u001b[0m \u001b[1m0s\u001b[0m 54ms/step\n",
      "\u001b[1m1/1\u001b[0m \u001b[32m━━━━━━━━━━━━━━━━━━━━\u001b[0m\u001b[37m\u001b[0m \u001b[1m0s\u001b[0m 41ms/step\n",
      "\u001b[1m1/1\u001b[0m \u001b[32m━━━━━━━━━━━━━━━━━━━━\u001b[0m\u001b[37m\u001b[0m \u001b[1m0s\u001b[0m 54ms/step\n",
      "\u001b[1m1/1\u001b[0m \u001b[32m━━━━━━━━━━━━━━━━━━━━\u001b[0m\u001b[37m\u001b[0m \u001b[1m0s\u001b[0m 60ms/step\n",
      "\u001b[1m1/1\u001b[0m \u001b[32m━━━━━━━━━━━━━━━━━━━━\u001b[0m\u001b[37m\u001b[0m \u001b[1m0s\u001b[0m 54ms/step\n",
      "\u001b[1m1/1\u001b[0m \u001b[32m━━━━━━━━━━━━━━━━━━━━\u001b[0m\u001b[37m\u001b[0m \u001b[1m0s\u001b[0m 54ms/step\n",
      "\u001b[1m1/1\u001b[0m \u001b[32m━━━━━━━━━━━━━━━━━━━━\u001b[0m\u001b[37m\u001b[0m \u001b[1m0s\u001b[0m 53ms/step\n",
      "\u001b[1m1/1\u001b[0m \u001b[32m━━━━━━━━━━━━━━━━━━━━\u001b[0m\u001b[37m\u001b[0m \u001b[1m0s\u001b[0m 67ms/step\n",
      "\u001b[1m1/1\u001b[0m \u001b[32m━━━━━━━━━━━━━━━━━━━━\u001b[0m\u001b[37m\u001b[0m \u001b[1m0s\u001b[0m 67ms/step\n",
      "\u001b[1m1/1\u001b[0m \u001b[32m━━━━━━━━━━━━━━━━━━━━\u001b[0m\u001b[37m\u001b[0m \u001b[1m0s\u001b[0m 68ms/step\n",
      "\u001b[1m1/1\u001b[0m \u001b[32m━━━━━━━━━━━━━━━━━━━━\u001b[0m\u001b[37m\u001b[0m \u001b[1m0s\u001b[0m 54ms/step\n",
      "\u001b[1m1/1\u001b[0m \u001b[32m━━━━━━━━━━━━━━━━━━━━\u001b[0m\u001b[37m\u001b[0m \u001b[1m0s\u001b[0m 54ms/step\n",
      "\u001b[1m1/1\u001b[0m \u001b[32m━━━━━━━━━━━━━━━━━━━━\u001b[0m\u001b[37m\u001b[0m \u001b[1m0s\u001b[0m 46ms/step\n",
      "\u001b[1m1/1\u001b[0m \u001b[32m━━━━━━━━━━━━━━━━━━━━\u001b[0m\u001b[37m\u001b[0m \u001b[1m0s\u001b[0m 53ms/step\n",
      "\u001b[1m1/1\u001b[0m \u001b[32m━━━━━━━━━━━━━━━━━━━━\u001b[0m\u001b[37m\u001b[0m \u001b[1m0s\u001b[0m 54ms/step\n",
      "\u001b[1m1/1\u001b[0m \u001b[32m━━━━━━━━━━━━━━━━━━━━\u001b[0m\u001b[37m\u001b[0m \u001b[1m0s\u001b[0m 54ms/step\n",
      "\u001b[1m1/1\u001b[0m \u001b[32m━━━━━━━━━━━━━━━━━━━━\u001b[0m\u001b[37m\u001b[0m \u001b[1m0s\u001b[0m 65ms/step\n",
      "\u001b[1m1/1\u001b[0m \u001b[32m━━━━━━━━━━━━━━━━━━━━\u001b[0m\u001b[37m\u001b[0m \u001b[1m0s\u001b[0m 47ms/step\n",
      "\u001b[1m1/1\u001b[0m \u001b[32m━━━━━━━━━━━━━━━━━━━━\u001b[0m\u001b[37m\u001b[0m \u001b[1m0s\u001b[0m 54ms/step\n",
      "\u001b[1m1/1\u001b[0m \u001b[32m━━━━━━━━━━━━━━━━━━━━\u001b[0m\u001b[37m\u001b[0m \u001b[1m0s\u001b[0m 66ms/step\n",
      "\u001b[1m1/1\u001b[0m \u001b[32m━━━━━━━━━━━━━━━━━━━━\u001b[0m\u001b[37m\u001b[0m \u001b[1m0s\u001b[0m 52ms/step\n",
      "\u001b[1m1/1\u001b[0m \u001b[32m━━━━━━━━━━━━━━━━━━━━\u001b[0m\u001b[37m\u001b[0m \u001b[1m0s\u001b[0m 53ms/step\n",
      "\u001b[1m1/1\u001b[0m \u001b[32m━━━━━━━━━━━━━━━━━━━━\u001b[0m\u001b[37m\u001b[0m \u001b[1m0s\u001b[0m 55ms/step\n",
      "\u001b[1m1/1\u001b[0m \u001b[32m━━━━━━━━━━━━━━━━━━━━\u001b[0m\u001b[37m\u001b[0m \u001b[1m0s\u001b[0m 54ms/step\n",
      "\u001b[1m1/1\u001b[0m \u001b[32m━━━━━━━━━━━━━━━━━━━━\u001b[0m\u001b[37m\u001b[0m \u001b[1m0s\u001b[0m 67ms/step\n",
      "\u001b[1m1/1\u001b[0m \u001b[32m━━━━━━━━━━━━━━━━━━━━\u001b[0m\u001b[37m\u001b[0m \u001b[1m0s\u001b[0m 54ms/step\n",
      "\u001b[1m1/1\u001b[0m \u001b[32m━━━━━━━━━━━━━━━━━━━━\u001b[0m\u001b[37m\u001b[0m \u001b[1m0s\u001b[0m 47ms/step\n",
      "\u001b[1m1/1\u001b[0m \u001b[32m━━━━━━━━━━━━━━━━━━━━\u001b[0m\u001b[37m\u001b[0m \u001b[1m0s\u001b[0m 54ms/step\n",
      "\u001b[1m1/1\u001b[0m \u001b[32m━━━━━━━━━━━━━━━━━━━━\u001b[0m\u001b[37m\u001b[0m \u001b[1m0s\u001b[0m 67ms/step\n",
      "\u001b[1m1/1\u001b[0m \u001b[32m━━━━━━━━━━━━━━━━━━━━\u001b[0m\u001b[37m\u001b[0m \u001b[1m0s\u001b[0m 53ms/step\n",
      "\u001b[1m1/1\u001b[0m \u001b[32m━━━━━━━━━━━━━━━━━━━━\u001b[0m\u001b[37m\u001b[0m \u001b[1m0s\u001b[0m 50ms/step\n",
      "\u001b[1m1/1\u001b[0m \u001b[32m━━━━━━━━━━━━━━━━━━━━\u001b[0m\u001b[37m\u001b[0m \u001b[1m0s\u001b[0m 54ms/step\n",
      "\u001b[1m1/1\u001b[0m \u001b[32m━━━━━━━━━━━━━━━━━━━━\u001b[0m\u001b[37m\u001b[0m \u001b[1m0s\u001b[0m 53ms/step\n",
      "\u001b[1m1/1\u001b[0m \u001b[32m━━━━━━━━━━━━━━━━━━━━\u001b[0m\u001b[37m\u001b[0m \u001b[1m0s\u001b[0m 67ms/step\n",
      "\u001b[1m1/1\u001b[0m \u001b[32m━━━━━━━━━━━━━━━━━━━━\u001b[0m\u001b[37m\u001b[0m \u001b[1m0s\u001b[0m 54ms/step\n",
      "\u001b[1m1/1\u001b[0m \u001b[32m━━━━━━━━━━━━━━━━━━━━\u001b[0m\u001b[37m\u001b[0m \u001b[1m0s\u001b[0m 54ms/step\n",
      "\u001b[1m1/1\u001b[0m \u001b[32m━━━━━━━━━━━━━━━━━━━━\u001b[0m\u001b[37m\u001b[0m \u001b[1m0s\u001b[0m 54ms/step\n",
      "\u001b[1m1/1\u001b[0m \u001b[32m━━━━━━━━━━━━━━━━━━━━\u001b[0m\u001b[37m\u001b[0m \u001b[1m0s\u001b[0m 53ms/step\n",
      "\u001b[1m1/1\u001b[0m \u001b[32m━━━━━━━━━━━━━━━━━━━━\u001b[0m\u001b[37m\u001b[0m \u001b[1m0s\u001b[0m 53ms/step\n",
      "\u001b[1m1/1\u001b[0m \u001b[32m━━━━━━━━━━━━━━━━━━━━\u001b[0m\u001b[37m\u001b[0m \u001b[1m0s\u001b[0m 54ms/step\n",
      "\u001b[1m1/1\u001b[0m \u001b[32m━━━━━━━━━━━━━━━━━━━━\u001b[0m\u001b[37m\u001b[0m \u001b[1m0s\u001b[0m 54ms/step\n",
      "\u001b[1m1/1\u001b[0m \u001b[32m━━━━━━━━━━━━━━━━━━━━\u001b[0m\u001b[37m\u001b[0m \u001b[1m0s\u001b[0m 53ms/step\n",
      "\u001b[1m1/1\u001b[0m \u001b[32m━━━━━━━━━━━━━━━━━━━━\u001b[0m\u001b[37m\u001b[0m \u001b[1m0s\u001b[0m 67ms/step\n",
      "\u001b[1m1/1\u001b[0m \u001b[32m━━━━━━━━━━━━━━━━━━━━\u001b[0m\u001b[37m\u001b[0m \u001b[1m0s\u001b[0m 54ms/step\n",
      "\u001b[1m1/1\u001b[0m \u001b[32m━━━━━━━━━━━━━━━━━━━━\u001b[0m\u001b[37m\u001b[0m \u001b[1m0s\u001b[0m 54ms/step\n",
      "\u001b[1m1/1\u001b[0m \u001b[32m━━━━━━━━━━━━━━━━━━━━\u001b[0m\u001b[37m\u001b[0m \u001b[1m0s\u001b[0m 54ms/step\n",
      "\u001b[1m1/1\u001b[0m \u001b[32m━━━━━━━━━━━━━━━━━━━━\u001b[0m\u001b[37m\u001b[0m \u001b[1m0s\u001b[0m 46ms/step\n",
      "\u001b[1m1/1\u001b[0m \u001b[32m━━━━━━━━━━━━━━━━━━━━\u001b[0m\u001b[37m\u001b[0m \u001b[1m0s\u001b[0m 52ms/step\n",
      "\u001b[1m1/1\u001b[0m \u001b[32m━━━━━━━━━━━━━━━━━━━━\u001b[0m\u001b[37m\u001b[0m \u001b[1m0s\u001b[0m 40ms/step\n",
      "\u001b[1m1/1\u001b[0m \u001b[32m━━━━━━━━━━━━━━━━━━━━\u001b[0m\u001b[37m\u001b[0m \u001b[1m0s\u001b[0m 54ms/step\n",
      "\u001b[1m1/1\u001b[0m \u001b[32m━━━━━━━━━━━━━━━━━━━━\u001b[0m\u001b[37m\u001b[0m \u001b[1m0s\u001b[0m 51ms/step\n",
      "\u001b[1m1/1\u001b[0m \u001b[32m━━━━━━━━━━━━━━━━━━━━\u001b[0m\u001b[37m\u001b[0m \u001b[1m0s\u001b[0m 54ms/step\n",
      "\u001b[1m1/1\u001b[0m \u001b[32m━━━━━━━━━━━━━━━━━━━━\u001b[0m\u001b[37m\u001b[0m \u001b[1m0s\u001b[0m 54ms/step\n",
      "\u001b[1m1/1\u001b[0m \u001b[32m━━━━━━━━━━━━━━━━━━━━\u001b[0m\u001b[37m\u001b[0m \u001b[1m0s\u001b[0m 54ms/step\n",
      "\u001b[1m1/1\u001b[0m \u001b[32m━━━━━━━━━━━━━━━━━━━━\u001b[0m\u001b[37m\u001b[0m \u001b[1m0s\u001b[0m 53ms/step\n",
      "\u001b[1m1/1\u001b[0m \u001b[32m━━━━━━━━━━━━━━━━━━━━\u001b[0m\u001b[37m\u001b[0m \u001b[1m0s\u001b[0m 54ms/step\n",
      "\u001b[1m1/1\u001b[0m \u001b[32m━━━━━━━━━━━━━━━━━━━━\u001b[0m\u001b[37m\u001b[0m \u001b[1m0s\u001b[0m 67ms/step\n",
      "\u001b[1m1/1\u001b[0m \u001b[32m━━━━━━━━━━━━━━━━━━━━\u001b[0m\u001b[37m\u001b[0m \u001b[1m0s\u001b[0m 66ms/step\n",
      "\u001b[1m1/1\u001b[0m \u001b[32m━━━━━━━━━━━━━━━━━━━━\u001b[0m\u001b[37m\u001b[0m \u001b[1m0s\u001b[0m 52ms/step\n",
      "\u001b[1m1/1\u001b[0m \u001b[32m━━━━━━━━━━━━━━━━━━━━\u001b[0m\u001b[37m\u001b[0m \u001b[1m0s\u001b[0m 48ms/step\n",
      "\u001b[1m1/1\u001b[0m \u001b[32m━━━━━━━━━━━━━━━━━━━━\u001b[0m\u001b[37m\u001b[0m \u001b[1m0s\u001b[0m 54ms/step\n",
      "\u001b[1m1/1\u001b[0m \u001b[32m━━━━━━━━━━━━━━━━━━━━\u001b[0m\u001b[37m\u001b[0m \u001b[1m0s\u001b[0m 54ms/step\n",
      "\u001b[1m1/1\u001b[0m \u001b[32m━━━━━━━━━━━━━━━━━━━━\u001b[0m\u001b[37m\u001b[0m \u001b[1m0s\u001b[0m 53ms/step\n",
      "\u001b[1m1/1\u001b[0m \u001b[32m━━━━━━━━━━━━━━━━━━━━\u001b[0m\u001b[37m\u001b[0m \u001b[1m0s\u001b[0m 51ms/step\n",
      "\u001b[1m1/1\u001b[0m \u001b[32m━━━━━━━━━━━━━━━━━━━━\u001b[0m\u001b[37m\u001b[0m \u001b[1m0s\u001b[0m 54ms/step\n",
      "\u001b[1m1/1\u001b[0m \u001b[32m━━━━━━━━━━━━━━━━━━━━\u001b[0m\u001b[37m\u001b[0m \u001b[1m0s\u001b[0m 60ms/step\n",
      "\u001b[1m1/1\u001b[0m \u001b[32m━━━━━━━━━━━━━━━━━━━━\u001b[0m\u001b[37m\u001b[0m \u001b[1m0s\u001b[0m 67ms/step\n",
      "\u001b[1m1/1\u001b[0m \u001b[32m━━━━━━━━━━━━━━━━━━━━\u001b[0m\u001b[37m\u001b[0m \u001b[1m0s\u001b[0m 53ms/step\n",
      "\u001b[1m1/1\u001b[0m \u001b[32m━━━━━━━━━━━━━━━━━━━━\u001b[0m\u001b[37m\u001b[0m \u001b[1m0s\u001b[0m 54ms/step\n",
      "\u001b[1m1/1\u001b[0m \u001b[32m━━━━━━━━━━━━━━━━━━━━\u001b[0m\u001b[37m\u001b[0m \u001b[1m0s\u001b[0m 54ms/step\n",
      "\u001b[1m1/1\u001b[0m \u001b[32m━━━━━━━━━━━━━━━━━━━━\u001b[0m\u001b[37m\u001b[0m \u001b[1m0s\u001b[0m 54ms/step\n",
      "\u001b[1m1/1\u001b[0m \u001b[32m━━━━━━━━━━━━━━━━━━━━\u001b[0m\u001b[37m\u001b[0m \u001b[1m0s\u001b[0m 54ms/step\n",
      "\u001b[1m1/1\u001b[0m \u001b[32m━━━━━━━━━━━━━━━━━━━━\u001b[0m\u001b[37m\u001b[0m \u001b[1m0s\u001b[0m 58ms/step\n",
      "\u001b[1m1/1\u001b[0m \u001b[32m━━━━━━━━━━━━━━━━━━━━\u001b[0m\u001b[37m\u001b[0m \u001b[1m0s\u001b[0m 54ms/step\n",
      "\u001b[1m1/1\u001b[0m \u001b[32m━━━━━━━━━━━━━━━━━━━━\u001b[0m\u001b[37m\u001b[0m \u001b[1m0s\u001b[0m 54ms/step\n",
      "\u001b[1m1/1\u001b[0m \u001b[32m━━━━━━━━━━━━━━━━━━━━\u001b[0m\u001b[37m\u001b[0m \u001b[1m0s\u001b[0m 53ms/step\n",
      "\u001b[1m1/1\u001b[0m \u001b[32m━━━━━━━━━━━━━━━━━━━━\u001b[0m\u001b[37m\u001b[0m \u001b[1m0s\u001b[0m 54ms/step\n",
      "\u001b[1m1/1\u001b[0m \u001b[32m━━━━━━━━━━━━━━━━━━━━\u001b[0m\u001b[37m\u001b[0m \u001b[1m0s\u001b[0m 53ms/step\n",
      "\u001b[1m1/1\u001b[0m \u001b[32m━━━━━━━━━━━━━━━━━━━━\u001b[0m\u001b[37m\u001b[0m \u001b[1m0s\u001b[0m 54ms/step\n",
      "\u001b[1m1/1\u001b[0m \u001b[32m━━━━━━━━━━━━━━━━━━━━\u001b[0m\u001b[37m\u001b[0m \u001b[1m0s\u001b[0m 53ms/step\n",
      "\u001b[1m1/1\u001b[0m \u001b[32m━━━━━━━━━━━━━━━━━━━━\u001b[0m\u001b[37m\u001b[0m \u001b[1m0s\u001b[0m 54ms/step\n",
      "\u001b[1m1/1\u001b[0m \u001b[32m━━━━━━━━━━━━━━━━━━━━\u001b[0m\u001b[37m\u001b[0m \u001b[1m0s\u001b[0m 64ms/step\n",
      "\u001b[1m1/1\u001b[0m \u001b[32m━━━━━━━━━━━━━━━━━━━━\u001b[0m\u001b[37m\u001b[0m \u001b[1m0s\u001b[0m 54ms/step\n",
      "\u001b[1m1/1\u001b[0m \u001b[32m━━━━━━━━━━━━━━━━━━━━\u001b[0m\u001b[37m\u001b[0m \u001b[1m0s\u001b[0m 51ms/step\n",
      "\u001b[1m1/1\u001b[0m \u001b[32m━━━━━━━━━━━━━━━━━━━━\u001b[0m\u001b[37m\u001b[0m \u001b[1m0s\u001b[0m 54ms/step\n",
      "\u001b[1m1/1\u001b[0m \u001b[32m━━━━━━━━━━━━━━━━━━━━\u001b[0m\u001b[37m\u001b[0m \u001b[1m0s\u001b[0m 40ms/step\n",
      "\u001b[1m1/1\u001b[0m \u001b[32m━━━━━━━━━━━━━━━━━━━━\u001b[0m\u001b[37m\u001b[0m \u001b[1m0s\u001b[0m 54ms/step\n",
      "\u001b[1m1/1\u001b[0m \u001b[32m━━━━━━━━━━━━━━━━━━━━\u001b[0m\u001b[37m\u001b[0m \u001b[1m0s\u001b[0m 54ms/step\n",
      "\u001b[1m1/1\u001b[0m \u001b[32m━━━━━━━━━━━━━━━━━━━━\u001b[0m\u001b[37m\u001b[0m \u001b[1m0s\u001b[0m 48ms/step\n",
      "\u001b[1m1/1\u001b[0m \u001b[32m━━━━━━━━━━━━━━━━━━━━\u001b[0m\u001b[37m\u001b[0m \u001b[1m0s\u001b[0m 54ms/step\n",
      "\u001b[1m1/1\u001b[0m \u001b[32m━━━━━━━━━━━━━━━━━━━━\u001b[0m\u001b[37m\u001b[0m \u001b[1m0s\u001b[0m 54ms/step\n",
      "\u001b[1m1/1\u001b[0m \u001b[32m━━━━━━━━━━━━━━━━━━━━\u001b[0m\u001b[37m\u001b[0m \u001b[1m0s\u001b[0m 65ms/step\n",
      "\u001b[1m1/1\u001b[0m \u001b[32m━━━━━━━━━━━━━━━━━━━━\u001b[0m\u001b[37m\u001b[0m \u001b[1m0s\u001b[0m 54ms/step\n",
      "\u001b[1m1/1\u001b[0m \u001b[32m━━━━━━━━━━━━━━━━━━━━\u001b[0m\u001b[37m\u001b[0m \u001b[1m0s\u001b[0m 55ms/step\n",
      "\u001b[1m1/1\u001b[0m \u001b[32m━━━━━━━━━━━━━━━━━━━━\u001b[0m\u001b[37m\u001b[0m \u001b[1m0s\u001b[0m 67ms/step\n",
      "\u001b[1m1/1\u001b[0m \u001b[32m━━━━━━━━━━━━━━━━━━━━\u001b[0m\u001b[37m\u001b[0m \u001b[1m0s\u001b[0m 54ms/step\n",
      "\u001b[1m1/1\u001b[0m \u001b[32m━━━━━━━━━━━━━━━━━━━━\u001b[0m\u001b[37m\u001b[0m \u001b[1m0s\u001b[0m 63ms/step\n",
      "\u001b[1m1/1\u001b[0m \u001b[32m━━━━━━━━━━━━━━━━━━━━\u001b[0m\u001b[37m\u001b[0m \u001b[1m0s\u001b[0m 54ms/step\n",
      "\u001b[1m1/1\u001b[0m \u001b[32m━━━━━━━━━━━━━━━━━━━━\u001b[0m\u001b[37m\u001b[0m \u001b[1m0s\u001b[0m 54ms/step\n",
      "\u001b[1m1/1\u001b[0m \u001b[32m━━━━━━━━━━━━━━━━━━━━\u001b[0m\u001b[37m\u001b[0m \u001b[1m0s\u001b[0m 70ms/step\n",
      "\u001b[1m1/1\u001b[0m \u001b[32m━━━━━━━━━━━━━━━━━━━━\u001b[0m\u001b[37m\u001b[0m \u001b[1m0s\u001b[0m 54ms/step\n",
      "\u001b[1m1/1\u001b[0m \u001b[32m━━━━━━━━━━━━━━━━━━━━\u001b[0m\u001b[37m\u001b[0m \u001b[1m0s\u001b[0m 54ms/step\n",
      "\u001b[1m1/1\u001b[0m \u001b[32m━━━━━━━━━━━━━━━━━━━━\u001b[0m\u001b[37m\u001b[0m \u001b[1m0s\u001b[0m 54ms/step\n",
      "\u001b[1m1/1\u001b[0m \u001b[32m━━━━━━━━━━━━━━━━━━━━\u001b[0m\u001b[37m\u001b[0m \u001b[1m0s\u001b[0m 65ms/step\n",
      "\u001b[1m1/1\u001b[0m \u001b[32m━━━━━━━━━━━━━━━━━━━━\u001b[0m\u001b[37m\u001b[0m \u001b[1m0s\u001b[0m 54ms/step\n",
      "\u001b[1m1/1\u001b[0m \u001b[32m━━━━━━━━━━━━━━━━━━━━\u001b[0m\u001b[37m\u001b[0m \u001b[1m0s\u001b[0m 54ms/step\n",
      "\u001b[1m1/1\u001b[0m \u001b[32m━━━━━━━━━━━━━━━━━━━━\u001b[0m\u001b[37m\u001b[0m \u001b[1m0s\u001b[0m 55ms/step\n",
      "\u001b[1m1/1\u001b[0m \u001b[32m━━━━━━━━━━━━━━━━━━━━\u001b[0m\u001b[37m\u001b[0m \u001b[1m0s\u001b[0m 57ms/step\n",
      "\u001b[1m1/1\u001b[0m \u001b[32m━━━━━━━━━━━━━━━━━━━━\u001b[0m\u001b[37m\u001b[0m \u001b[1m0s\u001b[0m 54ms/step\n",
      "\u001b[1m1/1\u001b[0m \u001b[32m━━━━━━━━━━━━━━━━━━━━\u001b[0m\u001b[37m\u001b[0m \u001b[1m0s\u001b[0m 54ms/step\n",
      "\u001b[1m1/1\u001b[0m \u001b[32m━━━━━━━━━━━━━━━━━━━━\u001b[0m\u001b[37m\u001b[0m \u001b[1m0s\u001b[0m 54ms/step\n",
      "\u001b[1m1/1\u001b[0m \u001b[32m━━━━━━━━━━━━━━━━━━━━\u001b[0m\u001b[37m\u001b[0m \u001b[1m0s\u001b[0m 53ms/step\n",
      "\u001b[1m1/1\u001b[0m \u001b[32m━━━━━━━━━━━━━━━━━━━━\u001b[0m\u001b[37m\u001b[0m \u001b[1m0s\u001b[0m 54ms/step\n",
      "\u001b[1m1/1\u001b[0m \u001b[32m━━━━━━━━━━━━━━━━━━━━\u001b[0m\u001b[37m\u001b[0m \u001b[1m0s\u001b[0m 54ms/step\n",
      "\u001b[1m1/1\u001b[0m \u001b[32m━━━━━━━━━━━━━━━━━━━━\u001b[0m\u001b[37m\u001b[0m \u001b[1m0s\u001b[0m 46ms/step\n",
      "\u001b[1m1/1\u001b[0m \u001b[32m━━━━━━━━━━━━━━━━━━━━\u001b[0m\u001b[37m\u001b[0m \u001b[1m0s\u001b[0m 67ms/step\n",
      "\u001b[1m1/1\u001b[0m \u001b[32m━━━━━━━━━━━━━━━━━━━━\u001b[0m\u001b[37m\u001b[0m \u001b[1m0s\u001b[0m 55ms/step\n",
      "\u001b[1m1/1\u001b[0m \u001b[32m━━━━━━━━━━━━━━━━━━━━\u001b[0m\u001b[37m\u001b[0m \u001b[1m0s\u001b[0m 60ms/step\n",
      "\u001b[1m1/1\u001b[0m \u001b[32m━━━━━━━━━━━━━━━━━━━━\u001b[0m\u001b[37m\u001b[0m \u001b[1m0s\u001b[0m 67ms/step\n",
      "\u001b[1m1/1\u001b[0m \u001b[32m━━━━━━━━━━━━━━━━━━━━\u001b[0m\u001b[37m\u001b[0m \u001b[1m0s\u001b[0m 54ms/step\n",
      "\u001b[1m1/1\u001b[0m \u001b[32m━━━━━━━━━━━━━━━━━━━━\u001b[0m\u001b[37m\u001b[0m \u001b[1m0s\u001b[0m 53ms/step\n",
      "\u001b[1m1/1\u001b[0m \u001b[32m━━━━━━━━━━━━━━━━━━━━\u001b[0m\u001b[37m\u001b[0m \u001b[1m0s\u001b[0m 49ms/step\n",
      "\u001b[1m1/1\u001b[0m \u001b[32m━━━━━━━━━━━━━━━━━━━━\u001b[0m\u001b[37m\u001b[0m \u001b[1m0s\u001b[0m 65ms/step\n",
      "\u001b[1m1/1\u001b[0m \u001b[32m━━━━━━━━━━━━━━━━━━━━\u001b[0m\u001b[37m\u001b[0m \u001b[1m0s\u001b[0m 54ms/step\n",
      "\u001b[1m1/1\u001b[0m \u001b[32m━━━━━━━━━━━━━━━━━━━━\u001b[0m\u001b[37m\u001b[0m \u001b[1m0s\u001b[0m 53ms/step\n",
      "\u001b[1m1/1\u001b[0m \u001b[32m━━━━━━━━━━━━━━━━━━━━\u001b[0m\u001b[37m\u001b[0m \u001b[1m0s\u001b[0m 54ms/step\n",
      "\u001b[1m1/1\u001b[0m \u001b[32m━━━━━━━━━━━━━━━━━━━━\u001b[0m\u001b[37m\u001b[0m \u001b[1m0s\u001b[0m 48ms/step\n",
      "\u001b[1m1/1\u001b[0m \u001b[32m━━━━━━━━━━━━━━━━━━━━\u001b[0m\u001b[37m\u001b[0m \u001b[1m0s\u001b[0m 54ms/step\n",
      "\u001b[1m1/1\u001b[0m \u001b[32m━━━━━━━━━━━━━━━━━━━━\u001b[0m\u001b[37m\u001b[0m \u001b[1m0s\u001b[0m 54ms/step\n",
      "\u001b[1m1/1\u001b[0m \u001b[32m━━━━━━━━━━━━━━━━━━━━\u001b[0m\u001b[37m\u001b[0m \u001b[1m0s\u001b[0m 54ms/step\n",
      "\u001b[1m1/1\u001b[0m \u001b[32m━━━━━━━━━━━━━━━━━━━━\u001b[0m\u001b[37m\u001b[0m \u001b[1m0s\u001b[0m 54ms/step\n",
      "\u001b[1m1/1\u001b[0m \u001b[32m━━━━━━━━━━━━━━━━━━━━\u001b[0m\u001b[37m\u001b[0m \u001b[1m0s\u001b[0m 54ms/step\n",
      "\u001b[1m1/1\u001b[0m \u001b[32m━━━━━━━━━━━━━━━━━━━━\u001b[0m\u001b[37m\u001b[0m \u001b[1m0s\u001b[0m 54ms/step\n",
      "\u001b[1m1/1\u001b[0m \u001b[32m━━━━━━━━━━━━━━━━━━━━\u001b[0m\u001b[37m\u001b[0m \u001b[1m0s\u001b[0m 70ms/step\n",
      "\u001b[1m1/1\u001b[0m \u001b[32m━━━━━━━━━━━━━━━━━━━━\u001b[0m\u001b[37m\u001b[0m \u001b[1m0s\u001b[0m 54ms/step\n",
      "\u001b[1m1/1\u001b[0m \u001b[32m━━━━━━━━━━━━━━━━━━━━\u001b[0m\u001b[37m\u001b[0m \u001b[1m0s\u001b[0m 54ms/step\n",
      "\u001b[1m1/1\u001b[0m \u001b[32m━━━━━━━━━━━━━━━━━━━━\u001b[0m\u001b[37m\u001b[0m \u001b[1m0s\u001b[0m 54ms/step\n",
      "\u001b[1m1/1\u001b[0m \u001b[32m━━━━━━━━━━━━━━━━━━━━\u001b[0m\u001b[37m\u001b[0m \u001b[1m0s\u001b[0m 68ms/step\n",
      "\u001b[1m1/1\u001b[0m \u001b[32m━━━━━━━━━━━━━━━━━━━━\u001b[0m\u001b[37m\u001b[0m \u001b[1m0s\u001b[0m 66ms/step\n",
      "\u001b[1m1/1\u001b[0m \u001b[32m━━━━━━━━━━━━━━━━━━━━\u001b[0m\u001b[37m\u001b[0m \u001b[1m0s\u001b[0m 52ms/step\n",
      "\u001b[1m1/1\u001b[0m \u001b[32m━━━━━━━━━━━━━━━━━━━━\u001b[0m\u001b[37m\u001b[0m \u001b[1m0s\u001b[0m 53ms/step\n",
      "\u001b[1m1/1\u001b[0m \u001b[32m━━━━━━━━━━━━━━━━━━━━\u001b[0m\u001b[37m\u001b[0m \u001b[1m0s\u001b[0m 53ms/step\n",
      "\u001b[1m1/1\u001b[0m \u001b[32m━━━━━━━━━━━━━━━━━━━━\u001b[0m\u001b[37m\u001b[0m \u001b[1m0s\u001b[0m 51ms/step\n",
      "\u001b[1m1/1\u001b[0m \u001b[32m━━━━━━━━━━━━━━━━━━━━\u001b[0m\u001b[37m\u001b[0m \u001b[1m0s\u001b[0m 54ms/step\n",
      "\u001b[1m1/1\u001b[0m \u001b[32m━━━━━━━━━━━━━━━━━━━━\u001b[0m\u001b[37m\u001b[0m \u001b[1m0s\u001b[0m 54ms/step\n",
      "\u001b[1m1/1\u001b[0m \u001b[32m━━━━━━━━━━━━━━━━━━━━\u001b[0m\u001b[37m\u001b[0m \u001b[1m0s\u001b[0m 54ms/step\n",
      "\u001b[1m1/1\u001b[0m \u001b[32m━━━━━━━━━━━━━━━━━━━━\u001b[0m\u001b[37m\u001b[0m \u001b[1m0s\u001b[0m 43ms/step\n",
      "\u001b[1m1/1\u001b[0m \u001b[32m━━━━━━━━━━━━━━━━━━━━\u001b[0m\u001b[37m\u001b[0m \u001b[1m0s\u001b[0m 54ms/step\n",
      "\u001b[1m1/1\u001b[0m \u001b[32m━━━━━━━━━━━━━━━━━━━━\u001b[0m\u001b[37m\u001b[0m \u001b[1m0s\u001b[0m 54ms/step\n",
      "\u001b[1m1/1\u001b[0m \u001b[32m━━━━━━━━━━━━━━━━━━━━\u001b[0m\u001b[37m\u001b[0m \u001b[1m0s\u001b[0m 58ms/step\n",
      "\u001b[1m1/1\u001b[0m \u001b[32m━━━━━━━━━━━━━━━━━━━━\u001b[0m\u001b[37m\u001b[0m \u001b[1m0s\u001b[0m 54ms/step\n",
      "\u001b[1m1/1\u001b[0m \u001b[32m━━━━━━━━━━━━━━━━━━━━\u001b[0m\u001b[37m\u001b[0m \u001b[1m0s\u001b[0m 54ms/step\n",
      "\u001b[1m1/1\u001b[0m \u001b[32m━━━━━━━━━━━━━━━━━━━━\u001b[0m\u001b[37m\u001b[0m \u001b[1m0s\u001b[0m 54ms/step\n",
      "\u001b[1m1/1\u001b[0m \u001b[32m━━━━━━━━━━━━━━━━━━━━\u001b[0m\u001b[37m\u001b[0m \u001b[1m0s\u001b[0m 55ms/step\n",
      "\u001b[1m1/1\u001b[0m \u001b[32m━━━━━━━━━━━━━━━━━━━━\u001b[0m\u001b[37m\u001b[0m \u001b[1m0s\u001b[0m 54ms/step\n",
      "\u001b[1m1/1\u001b[0m \u001b[32m━━━━━━━━━━━━━━━━━━━━\u001b[0m\u001b[37m\u001b[0m \u001b[1m0s\u001b[0m 54ms/step\n",
      "\u001b[1m1/1\u001b[0m \u001b[32m━━━━━━━━━━━━━━━━━━━━\u001b[0m\u001b[37m\u001b[0m \u001b[1m0s\u001b[0m 61ms/step\n",
      "\u001b[1m1/1\u001b[0m \u001b[32m━━━━━━━━━━━━━━━━━━━━\u001b[0m\u001b[37m\u001b[0m \u001b[1m0s\u001b[0m 67ms/step\n",
      "\u001b[1m1/1\u001b[0m \u001b[32m━━━━━━━━━━━━━━━━━━━━\u001b[0m\u001b[37m\u001b[0m \u001b[1m0s\u001b[0m 53ms/step\n",
      "\u001b[1m1/1\u001b[0m \u001b[32m━━━━━━━━━━━━━━━━━━━━\u001b[0m\u001b[37m\u001b[0m \u001b[1m0s\u001b[0m 54ms/step\n",
      "\u001b[1m1/1\u001b[0m \u001b[32m━━━━━━━━━━━━━━━━━━━━\u001b[0m\u001b[37m\u001b[0m \u001b[1m0s\u001b[0m 48ms/step\n",
      "\u001b[1m1/1\u001b[0m \u001b[32m━━━━━━━━━━━━━━━━━━━━\u001b[0m\u001b[37m\u001b[0m \u001b[1m0s\u001b[0m 54ms/step\n",
      "\u001b[1m1/1\u001b[0m \u001b[32m━━━━━━━━━━━━━━━━━━━━\u001b[0m\u001b[37m\u001b[0m \u001b[1m0s\u001b[0m 54ms/step\n",
      "\u001b[1m1/1\u001b[0m \u001b[32m━━━━━━━━━━━━━━━━━━━━\u001b[0m\u001b[37m\u001b[0m \u001b[1m0s\u001b[0m 54ms/step\n",
      "\u001b[1m1/1\u001b[0m \u001b[32m━━━━━━━━━━━━━━━━━━━━\u001b[0m\u001b[37m\u001b[0m \u001b[1m0s\u001b[0m 54ms/step\n",
      "\u001b[1m1/1\u001b[0m \u001b[32m━━━━━━━━━━━━━━━━━━━━\u001b[0m\u001b[37m\u001b[0m \u001b[1m0s\u001b[0m 56ms/step\n",
      "\u001b[1m1/1\u001b[0m \u001b[32m━━━━━━━━━━━━━━━━━━━━\u001b[0m\u001b[37m\u001b[0m \u001b[1m0s\u001b[0m 54ms/step\n",
      "\u001b[1m1/1\u001b[0m \u001b[32m━━━━━━━━━━━━━━━━━━━━\u001b[0m\u001b[37m\u001b[0m \u001b[1m0s\u001b[0m 54ms/step\n",
      "\u001b[1m1/1\u001b[0m \u001b[32m━━━━━━━━━━━━━━━━━━━━\u001b[0m\u001b[37m\u001b[0m \u001b[1m0s\u001b[0m 67ms/step\n",
      "\u001b[1m1/1\u001b[0m \u001b[32m━━━━━━━━━━━━━━━━━━━━\u001b[0m\u001b[37m\u001b[0m \u001b[1m0s\u001b[0m 51ms/step\n",
      "\u001b[1m1/1\u001b[0m \u001b[32m━━━━━━━━━━━━━━━━━━━━\u001b[0m\u001b[37m\u001b[0m \u001b[1m0s\u001b[0m 66ms/step\n",
      "\u001b[1m1/1\u001b[0m \u001b[32m━━━━━━━━━━━━━━━━━━━━\u001b[0m\u001b[37m\u001b[0m \u001b[1m0s\u001b[0m 54ms/step\n",
      "\u001b[1m1/1\u001b[0m \u001b[32m━━━━━━━━━━━━━━━━━━━━\u001b[0m\u001b[37m\u001b[0m \u001b[1m0s\u001b[0m 54ms/step\n",
      "\u001b[1m1/1\u001b[0m \u001b[32m━━━━━━━━━━━━━━━━━━━━\u001b[0m\u001b[37m\u001b[0m \u001b[1m0s\u001b[0m 47ms/step\n",
      "\u001b[1m1/1\u001b[0m \u001b[32m━━━━━━━━━━━━━━━━━━━━\u001b[0m\u001b[37m\u001b[0m \u001b[1m0s\u001b[0m 54ms/step\n",
      "\u001b[1m1/1\u001b[0m \u001b[32m━━━━━━━━━━━━━━━━━━━━\u001b[0m\u001b[37m\u001b[0m \u001b[1m0s\u001b[0m 54ms/step\n",
      "\u001b[1m1/1\u001b[0m \u001b[32m━━━━━━━━━━━━━━━━━━━━\u001b[0m\u001b[37m\u001b[0m \u001b[1m0s\u001b[0m 55ms/step\n",
      "\u001b[1m1/1\u001b[0m \u001b[32m━━━━━━━━━━━━━━━━━━━━\u001b[0m\u001b[37m\u001b[0m \u001b[1m0s\u001b[0m 54ms/step\n",
      "\u001b[1m1/1\u001b[0m \u001b[32m━━━━━━━━━━━━━━━━━━━━\u001b[0m\u001b[37m\u001b[0m \u001b[1m0s\u001b[0m 54ms/step\n",
      "\u001b[1m1/1\u001b[0m \u001b[32m━━━━━━━━━━━━━━━━━━━━\u001b[0m\u001b[37m\u001b[0m \u001b[1m0s\u001b[0m 67ms/step\n",
      "\u001b[1m1/1\u001b[0m \u001b[32m━━━━━━━━━━━━━━━━━━━━\u001b[0m\u001b[37m\u001b[0m \u001b[1m0s\u001b[0m 54ms/step\n",
      "\u001b[1m1/1\u001b[0m \u001b[32m━━━━━━━━━━━━━━━━━━━━\u001b[0m\u001b[37m\u001b[0m \u001b[1m0s\u001b[0m 54ms/step\n",
      "\u001b[1m1/1\u001b[0m \u001b[32m━━━━━━━━━━━━━━━━━━━━\u001b[0m\u001b[37m\u001b[0m \u001b[1m0s\u001b[0m 54ms/step\n",
      "\u001b[1m1/1\u001b[0m \u001b[32m━━━━━━━━━━━━━━━━━━━━\u001b[0m\u001b[37m\u001b[0m \u001b[1m0s\u001b[0m 67ms/step\n",
      "\u001b[1m1/1\u001b[0m \u001b[32m━━━━━━━━━━━━━━━━━━━━\u001b[0m\u001b[37m\u001b[0m \u001b[1m0s\u001b[0m 54ms/step\n",
      "\u001b[1m1/1\u001b[0m \u001b[32m━━━━━━━━━━━━━━━━━━━━\u001b[0m\u001b[37m\u001b[0m \u001b[1m0s\u001b[0m 54ms/step\n",
      "\u001b[1m1/1\u001b[0m \u001b[32m━━━━━━━━━━━━━━━━━━━━\u001b[0m\u001b[37m\u001b[0m \u001b[1m0s\u001b[0m 52ms/step\n",
      "\u001b[1m1/1\u001b[0m \u001b[32m━━━━━━━━━━━━━━━━━━━━\u001b[0m\u001b[37m\u001b[0m \u001b[1m0s\u001b[0m 54ms/step\n",
      "\u001b[1m1/1\u001b[0m \u001b[32m━━━━━━━━━━━━━━━━━━━━\u001b[0m\u001b[37m\u001b[0m \u001b[1m0s\u001b[0m 52ms/step\n",
      "\u001b[1m1/1\u001b[0m \u001b[32m━━━━━━━━━━━━━━━━━━━━\u001b[0m\u001b[37m\u001b[0m \u001b[1m0s\u001b[0m 67ms/step\n",
      "\u001b[1m1/1\u001b[0m \u001b[32m━━━━━━━━━━━━━━━━━━━━\u001b[0m\u001b[37m\u001b[0m \u001b[1m0s\u001b[0m 46ms/step\n",
      "\u001b[1m1/1\u001b[0m \u001b[32m━━━━━━━━━━━━━━━━━━━━\u001b[0m\u001b[37m\u001b[0m \u001b[1m0s\u001b[0m 58ms/step\n",
      "\u001b[1m1/1\u001b[0m \u001b[32m━━━━━━━━━━━━━━━━━━━━\u001b[0m\u001b[37m\u001b[0m \u001b[1m0s\u001b[0m 54ms/step\n",
      "\u001b[1m1/1\u001b[0m \u001b[32m━━━━━━━━━━━━━━━━━━━━\u001b[0m\u001b[37m\u001b[0m \u001b[1m0s\u001b[0m 53ms/step\n",
      "\u001b[1m1/1\u001b[0m \u001b[32m━━━━━━━━━━━━━━━━━━━━\u001b[0m\u001b[37m\u001b[0m \u001b[1m0s\u001b[0m 55ms/step\n",
      "\u001b[1m1/1\u001b[0m \u001b[32m━━━━━━━━━━━━━━━━━━━━\u001b[0m\u001b[37m\u001b[0m \u001b[1m0s\u001b[0m 67ms/step\n",
      "\u001b[1m1/1\u001b[0m \u001b[32m━━━━━━━━━━━━━━━━━━━━\u001b[0m\u001b[37m\u001b[0m \u001b[1m0s\u001b[0m 67ms/step\n",
      "\u001b[1m1/1\u001b[0m \u001b[32m━━━━━━━━━━━━━━━━━━━━\u001b[0m\u001b[37m\u001b[0m \u001b[1m0s\u001b[0m 58ms/step\n",
      "\u001b[1m1/1\u001b[0m \u001b[32m━━━━━━━━━━━━━━━━━━━━\u001b[0m\u001b[37m\u001b[0m \u001b[1m0s\u001b[0m 67ms/step\n",
      "\u001b[1m1/1\u001b[0m \u001b[32m━━━━━━━━━━━━━━━━━━━━\u001b[0m\u001b[37m\u001b[0m \u001b[1m0s\u001b[0m 63ms/step\n",
      "\u001b[1m1/1\u001b[0m \u001b[32m━━━━━━━━━━━━━━━━━━━━\u001b[0m\u001b[37m\u001b[0m \u001b[1m0s\u001b[0m 53ms/step\n",
      "\u001b[1m1/1\u001b[0m \u001b[32m━━━━━━━━━━━━━━━━━━━━\u001b[0m\u001b[37m\u001b[0m \u001b[1m0s\u001b[0m 48ms/step\n",
      "\u001b[1m1/1\u001b[0m \u001b[32m━━━━━━━━━━━━━━━━━━━━\u001b[0m\u001b[37m\u001b[0m \u001b[1m0s\u001b[0m 54ms/step\n",
      "\u001b[1m1/1\u001b[0m \u001b[32m━━━━━━━━━━━━━━━━━━━━\u001b[0m\u001b[37m\u001b[0m \u001b[1m0s\u001b[0m 54ms/step\n",
      "\u001b[1m1/1\u001b[0m \u001b[32m━━━━━━━━━━━━━━━━━━━━\u001b[0m\u001b[37m\u001b[0m \u001b[1m0s\u001b[0m 54ms/step\n",
      "\u001b[1m1/1\u001b[0m \u001b[32m━━━━━━━━━━━━━━━━━━━━\u001b[0m\u001b[37m\u001b[0m \u001b[1m0s\u001b[0m 54ms/step\n",
      "\u001b[1m1/1\u001b[0m \u001b[32m━━━━━━━━━━━━━━━━━━━━\u001b[0m\u001b[37m\u001b[0m \u001b[1m0s\u001b[0m 54ms/step\n",
      "\u001b[1m1/1\u001b[0m \u001b[32m━━━━━━━━━━━━━━━━━━━━\u001b[0m\u001b[37m\u001b[0m \u001b[1m0s\u001b[0m 54ms/step\n",
      "\u001b[1m1/1\u001b[0m \u001b[32m━━━━━━━━━━━━━━━━━━━━\u001b[0m\u001b[37m\u001b[0m \u001b[1m0s\u001b[0m 66ms/step\n",
      "\u001b[1m1/1\u001b[0m \u001b[32m━━━━━━━━━━━━━━━━━━━━\u001b[0m\u001b[37m\u001b[0m \u001b[1m0s\u001b[0m 54ms/step\n",
      "\u001b[1m1/1\u001b[0m \u001b[32m━━━━━━━━━━━━━━━━━━━━\u001b[0m\u001b[37m\u001b[0m \u001b[1m0s\u001b[0m 67ms/step\n",
      "\u001b[1m1/1\u001b[0m \u001b[32m━━━━━━━━━━━━━━━━━━━━\u001b[0m\u001b[37m\u001b[0m \u001b[1m0s\u001b[0m 54ms/step\n",
      "\u001b[1m1/1\u001b[0m \u001b[32m━━━━━━━━━━━━━━━━━━━━\u001b[0m\u001b[37m\u001b[0m \u001b[1m0s\u001b[0m 54ms/step\n",
      "\u001b[1m1/1\u001b[0m \u001b[32m━━━━━━━━━━━━━━━━━━━━\u001b[0m\u001b[37m\u001b[0m \u001b[1m0s\u001b[0m 53ms/step\n",
      "\u001b[1m1/1\u001b[0m \u001b[32m━━━━━━━━━━━━━━━━━━━━\u001b[0m\u001b[37m\u001b[0m \u001b[1m0s\u001b[0m 54ms/step\n",
      "\u001b[1m1/1\u001b[0m \u001b[32m━━━━━━━━━━━━━━━━━━━━\u001b[0m\u001b[37m\u001b[0m \u001b[1m0s\u001b[0m 51ms/step\n",
      "\u001b[1m1/1\u001b[0m \u001b[32m━━━━━━━━━━━━━━━━━━━━\u001b[0m\u001b[37m\u001b[0m \u001b[1m0s\u001b[0m 64ms/step\n",
      "\u001b[1m1/1\u001b[0m \u001b[32m━━━━━━━━━━━━━━━━━━━━\u001b[0m\u001b[37m\u001b[0m \u001b[1m0s\u001b[0m 67ms/step\n",
      "\u001b[1m1/1\u001b[0m \u001b[32m━━━━━━━━━━━━━━━━━━━━\u001b[0m\u001b[37m\u001b[0m \u001b[1m0s\u001b[0m 54ms/step\n",
      "\u001b[1m1/1\u001b[0m \u001b[32m━━━━━━━━━━━━━━━━━━━━\u001b[0m\u001b[37m\u001b[0m \u001b[1m0s\u001b[0m 54ms/step\n",
      "\u001b[1m1/1\u001b[0m \u001b[32m━━━━━━━━━━━━━━━━━━━━\u001b[0m\u001b[37m\u001b[0m \u001b[1m0s\u001b[0m 54ms/step\n",
      "\u001b[1m1/1\u001b[0m \u001b[32m━━━━━━━━━━━━━━━━━━━━\u001b[0m\u001b[37m\u001b[0m \u001b[1m0s\u001b[0m 54ms/step\n",
      "\u001b[1m1/1\u001b[0m \u001b[32m━━━━━━━━━━━━━━━━━━━━\u001b[0m\u001b[37m\u001b[0m \u001b[1m0s\u001b[0m 54ms/step\n",
      "\u001b[1m1/1\u001b[0m \u001b[32m━━━━━━━━━━━━━━━━━━━━\u001b[0m\u001b[37m\u001b[0m \u001b[1m0s\u001b[0m 54ms/step\n",
      "\u001b[1m1/1\u001b[0m \u001b[32m━━━━━━━━━━━━━━━━━━━━\u001b[0m\u001b[37m\u001b[0m \u001b[1m0s\u001b[0m 54ms/step\n",
      "\u001b[1m1/1\u001b[0m \u001b[32m━━━━━━━━━━━━━━━━━━━━\u001b[0m\u001b[37m\u001b[0m \u001b[1m0s\u001b[0m 54ms/step\n",
      "\u001b[1m1/1\u001b[0m \u001b[32m━━━━━━━━━━━━━━━━━━━━\u001b[0m\u001b[37m\u001b[0m \u001b[1m0s\u001b[0m 57ms/step\n",
      "\u001b[1m1/1\u001b[0m \u001b[32m━━━━━━━━━━━━━━━━━━━━\u001b[0m\u001b[37m\u001b[0m \u001b[1m0s\u001b[0m 67ms/step\n",
      "\u001b[1m1/1\u001b[0m \u001b[32m━━━━━━━━━━━━━━━━━━━━\u001b[0m\u001b[37m\u001b[0m \u001b[1m0s\u001b[0m 64ms/step\n",
      "\u001b[1m1/1\u001b[0m \u001b[32m━━━━━━━━━━━━━━━━━━━━\u001b[0m\u001b[37m\u001b[0m \u001b[1m0s\u001b[0m 54ms/step\n",
      "\u001b[1m1/1\u001b[0m \u001b[32m━━━━━━━━━━━━━━━━━━━━\u001b[0m\u001b[37m\u001b[0m \u001b[1m0s\u001b[0m 66ms/step\n",
      "\u001b[1m1/1\u001b[0m \u001b[32m━━━━━━━━━━━━━━━━━━━━\u001b[0m\u001b[37m\u001b[0m \u001b[1m0s\u001b[0m 41ms/step\n",
      "\u001b[1m1/1\u001b[0m \u001b[32m━━━━━━━━━━━━━━━━━━━━\u001b[0m\u001b[37m\u001b[0m \u001b[1m0s\u001b[0m 48ms/step\n",
      "\u001b[1m1/1\u001b[0m \u001b[32m━━━━━━━━━━━━━━━━━━━━\u001b[0m\u001b[37m\u001b[0m \u001b[1m0s\u001b[0m 54ms/step\n",
      "\u001b[1m1/1\u001b[0m \u001b[32m━━━━━━━━━━━━━━━━━━━━\u001b[0m\u001b[37m\u001b[0m \u001b[1m0s\u001b[0m 64ms/step\n",
      "\u001b[1m1/1\u001b[0m \u001b[32m━━━━━━━━━━━━━━━━━━━━\u001b[0m\u001b[37m\u001b[0m \u001b[1m0s\u001b[0m 54ms/step\n",
      "\u001b[1m1/1\u001b[0m \u001b[32m━━━━━━━━━━━━━━━━━━━━\u001b[0m\u001b[37m\u001b[0m \u001b[1m0s\u001b[0m 49ms/step\n",
      "\u001b[1m1/1\u001b[0m \u001b[32m━━━━━━━━━━━━━━━━━━━━\u001b[0m\u001b[37m\u001b[0m \u001b[1m0s\u001b[0m 63ms/step\n",
      "\u001b[1m1/1\u001b[0m \u001b[32m━━━━━━━━━━━━━━━━━━━━\u001b[0m\u001b[37m\u001b[0m \u001b[1m0s\u001b[0m 54ms/step\n",
      "\u001b[1m1/1\u001b[0m \u001b[32m━━━━━━━━━━━━━━━━━━━━\u001b[0m\u001b[37m\u001b[0m \u001b[1m0s\u001b[0m 54ms/step\n",
      "\u001b[1m1/1\u001b[0m \u001b[32m━━━━━━━━━━━━━━━━━━━━\u001b[0m\u001b[37m\u001b[0m \u001b[1m0s\u001b[0m 66ms/step\n",
      "\u001b[1m1/1\u001b[0m \u001b[32m━━━━━━━━━━━━━━━━━━━━\u001b[0m\u001b[37m\u001b[0m \u001b[1m0s\u001b[0m 54ms/step\n",
      "\u001b[1m1/1\u001b[0m \u001b[32m━━━━━━━━━━━━━━━━━━━━\u001b[0m\u001b[37m\u001b[0m \u001b[1m0s\u001b[0m 51ms/step\n",
      "\u001b[1m1/1\u001b[0m \u001b[32m━━━━━━━━━━━━━━━━━━━━\u001b[0m\u001b[37m\u001b[0m \u001b[1m0s\u001b[0m 54ms/step\n",
      "\u001b[1m1/1\u001b[0m \u001b[32m━━━━━━━━━━━━━━━━━━━━\u001b[0m\u001b[37m\u001b[0m \u001b[1m0s\u001b[0m 47ms/step\n",
      "\u001b[1m1/1\u001b[0m \u001b[32m━━━━━━━━━━━━━━━━━━━━\u001b[0m\u001b[37m\u001b[0m \u001b[1m0s\u001b[0m 60ms/step\n",
      "\u001b[1m1/1\u001b[0m \u001b[32m━━━━━━━━━━━━━━━━━━━━\u001b[0m\u001b[37m\u001b[0m \u001b[1m0s\u001b[0m 54ms/step\n",
      "\u001b[1m1/1\u001b[0m \u001b[32m━━━━━━━━━━━━━━━━━━━━\u001b[0m\u001b[37m\u001b[0m \u001b[1m0s\u001b[0m 52ms/step\n",
      "\u001b[1m1/1\u001b[0m \u001b[32m━━━━━━━━━━━━━━━━━━━━\u001b[0m\u001b[37m\u001b[0m \u001b[1m0s\u001b[0m 54ms/step\n",
      "\u001b[1m1/1\u001b[0m \u001b[32m━━━━━━━━━━━━━━━━━━━━\u001b[0m\u001b[37m\u001b[0m \u001b[1m0s\u001b[0m 54ms/step\n",
      "\u001b[1m1/1\u001b[0m \u001b[32m━━━━━━━━━━━━━━━━━━━━\u001b[0m\u001b[37m\u001b[0m \u001b[1m0s\u001b[0m 67ms/step\n",
      "\u001b[1m1/1\u001b[0m \u001b[32m━━━━━━━━━━━━━━━━━━━━\u001b[0m\u001b[37m\u001b[0m \u001b[1m0s\u001b[0m 66ms/step\n",
      "\u001b[1m1/1\u001b[0m \u001b[32m━━━━━━━━━━━━━━━━━━━━\u001b[0m\u001b[37m\u001b[0m \u001b[1m0s\u001b[0m 54ms/step\n",
      "\u001b[1m1/1\u001b[0m \u001b[32m━━━━━━━━━━━━━━━━━━━━\u001b[0m\u001b[37m\u001b[0m \u001b[1m0s\u001b[0m 51ms/step\n",
      "\u001b[1m1/1\u001b[0m \u001b[32m━━━━━━━━━━━━━━━━━━━━\u001b[0m\u001b[37m\u001b[0m \u001b[1m0s\u001b[0m 67ms/step\n",
      "\u001b[1m1/1\u001b[0m \u001b[32m━━━━━━━━━━━━━━━━━━━━\u001b[0m\u001b[37m\u001b[0m \u001b[1m0s\u001b[0m 53ms/step\n",
      "\u001b[1m1/1\u001b[0m \u001b[32m━━━━━━━━━━━━━━━━━━━━\u001b[0m\u001b[37m\u001b[0m \u001b[1m0s\u001b[0m 54ms/step\n",
      "\u001b[1m1/1\u001b[0m \u001b[32m━━━━━━━━━━━━━━━━━━━━\u001b[0m\u001b[37m\u001b[0m \u001b[1m0s\u001b[0m 55ms/step\n",
      "\u001b[1m1/1\u001b[0m \u001b[32m━━━━━━━━━━━━━━━━━━━━\u001b[0m\u001b[37m\u001b[0m \u001b[1m0s\u001b[0m 54ms/step\n",
      "\u001b[1m1/1\u001b[0m \u001b[32m━━━━━━━━━━━━━━━━━━━━\u001b[0m\u001b[37m\u001b[0m \u001b[1m0s\u001b[0m 66ms/step\n",
      "\u001b[1m1/1\u001b[0m \u001b[32m━━━━━━━━━━━━━━━━━━━━\u001b[0m\u001b[37m\u001b[0m \u001b[1m0s\u001b[0m 47ms/step\n",
      "\u001b[1m1/1\u001b[0m \u001b[32m━━━━━━━━━━━━━━━━━━━━\u001b[0m\u001b[37m\u001b[0m \u001b[1m0s\u001b[0m 54ms/step\n",
      "\u001b[1m1/1\u001b[0m \u001b[32m━━━━━━━━━━━━━━━━━━━━\u001b[0m\u001b[37m\u001b[0m \u001b[1m0s\u001b[0m 43ms/step\n",
      "\u001b[1m1/1\u001b[0m \u001b[32m━━━━━━━━━━━━━━━━━━━━\u001b[0m\u001b[37m\u001b[0m \u001b[1m0s\u001b[0m 67ms/step\n",
      "\u001b[1m1/1\u001b[0m \u001b[32m━━━━━━━━━━━━━━━━━━━━\u001b[0m\u001b[37m\u001b[0m \u001b[1m0s\u001b[0m 54ms/step\n",
      "\u001b[1m1/1\u001b[0m \u001b[32m━━━━━━━━━━━━━━━━━━━━\u001b[0m\u001b[37m\u001b[0m \u001b[1m0s\u001b[0m 67ms/step\n",
      "\u001b[1m1/1\u001b[0m \u001b[32m━━━━━━━━━━━━━━━━━━━━\u001b[0m\u001b[37m\u001b[0m \u001b[1m0s\u001b[0m 54ms/step\n",
      "\u001b[1m1/1\u001b[0m \u001b[32m━━━━━━━━━━━━━━━━━━━━\u001b[0m\u001b[37m\u001b[0m \u001b[1m0s\u001b[0m 62ms/step\n",
      "\u001b[1m1/1\u001b[0m \u001b[32m━━━━━━━━━━━━━━━━━━━━\u001b[0m\u001b[37m\u001b[0m \u001b[1m0s\u001b[0m 53ms/step\n",
      "\u001b[1m1/1\u001b[0m \u001b[32m━━━━━━━━━━━━━━━━━━━━\u001b[0m\u001b[37m\u001b[0m \u001b[1m0s\u001b[0m 67ms/step\n",
      "\u001b[1m1/1\u001b[0m \u001b[32m━━━━━━━━━━━━━━━━━━━━\u001b[0m\u001b[37m\u001b[0m \u001b[1m0s\u001b[0m 54ms/step\n",
      "\u001b[1m1/1\u001b[0m \u001b[32m━━━━━━━━━━━━━━━━━━━━\u001b[0m\u001b[37m\u001b[0m \u001b[1m0s\u001b[0m 54ms/step\n",
      "\u001b[1m1/1\u001b[0m \u001b[32m━━━━━━━━━━━━━━━━━━━━\u001b[0m\u001b[37m\u001b[0m \u001b[1m0s\u001b[0m 54ms/step\n",
      "\u001b[1m1/1\u001b[0m \u001b[32m━━━━━━━━━━━━━━━━━━━━\u001b[0m\u001b[37m\u001b[0m \u001b[1m0s\u001b[0m 54ms/step\n",
      "\u001b[1m1/1\u001b[0m \u001b[32m━━━━━━━━━━━━━━━━━━━━\u001b[0m\u001b[37m\u001b[0m \u001b[1m0s\u001b[0m 54ms/step\n",
      "\u001b[1m1/1\u001b[0m \u001b[32m━━━━━━━━━━━━━━━━━━━━\u001b[0m\u001b[37m\u001b[0m \u001b[1m0s\u001b[0m 59ms/step\n",
      "\u001b[1m1/1\u001b[0m \u001b[32m━━━━━━━━━━━━━━━━━━━━\u001b[0m\u001b[37m\u001b[0m \u001b[1m0s\u001b[0m 67ms/step\n",
      "\u001b[1m1/1\u001b[0m \u001b[32m━━━━━━━━━━━━━━━━━━━━\u001b[0m\u001b[37m\u001b[0m \u001b[1m0s\u001b[0m 54ms/step\n",
      "\u001b[1m1/1\u001b[0m \u001b[32m━━━━━━━━━━━━━━━━━━━━\u001b[0m\u001b[37m\u001b[0m \u001b[1m0s\u001b[0m 67ms/step\n",
      "\u001b[1m1/1\u001b[0m \u001b[32m━━━━━━━━━━━━━━━━━━━━\u001b[0m\u001b[37m\u001b[0m \u001b[1m0s\u001b[0m 54ms/step\n",
      "\u001b[1m1/1\u001b[0m \u001b[32m━━━━━━━━━━━━━━━━━━━━\u001b[0m\u001b[37m\u001b[0m \u001b[1m0s\u001b[0m 54ms/step\n",
      "\u001b[1m1/1\u001b[0m \u001b[32m━━━━━━━━━━━━━━━━━━━━\u001b[0m\u001b[37m\u001b[0m \u001b[1m0s\u001b[0m 53ms/step\n",
      "\u001b[1m1/1\u001b[0m \u001b[32m━━━━━━━━━━━━━━━━━━━━\u001b[0m\u001b[37m\u001b[0m \u001b[1m0s\u001b[0m 54ms/step\n",
      "\u001b[1m1/1\u001b[0m \u001b[32m━━━━━━━━━━━━━━━━━━━━\u001b[0m\u001b[37m\u001b[0m \u001b[1m0s\u001b[0m 51ms/step\n",
      "\u001b[1m1/1\u001b[0m \u001b[32m━━━━━━━━━━━━━━━━━━━━\u001b[0m\u001b[37m\u001b[0m \u001b[1m0s\u001b[0m 60ms/step\n",
      "\u001b[1m1/1\u001b[0m \u001b[32m━━━━━━━━━━━━━━━━━━━━\u001b[0m\u001b[37m\u001b[0m \u001b[1m0s\u001b[0m 54ms/step\n",
      "\u001b[1m1/1\u001b[0m \u001b[32m━━━━━━━━━━━━━━━━━━━━\u001b[0m\u001b[37m\u001b[0m \u001b[1m0s\u001b[0m 55ms/step\n",
      "\u001b[1m1/1\u001b[0m \u001b[32m━━━━━━━━━━━━━━━━━━━━\u001b[0m\u001b[37m\u001b[0m \u001b[1m0s\u001b[0m 67ms/step\n",
      "\u001b[1m1/1\u001b[0m \u001b[32m━━━━━━━━━━━━━━━━━━━━\u001b[0m\u001b[37m\u001b[0m \u001b[1m0s\u001b[0m 62ms/step\n",
      "\u001b[1m1/1\u001b[0m \u001b[32m━━━━━━━━━━━━━━━━━━━━\u001b[0m\u001b[37m\u001b[0m \u001b[1m0s\u001b[0m 54ms/step\n",
      "\u001b[1m1/1\u001b[0m \u001b[32m━━━━━━━━━━━━━━━━━━━━\u001b[0m\u001b[37m\u001b[0m \u001b[1m0s\u001b[0m 53ms/step\n",
      "\u001b[1m1/1\u001b[0m \u001b[32m━━━━━━━━━━━━━━━━━━━━\u001b[0m\u001b[37m\u001b[0m \u001b[1m0s\u001b[0m 67ms/step\n",
      "\u001b[1m1/1\u001b[0m \u001b[32m━━━━━━━━━━━━━━━━━━━━\u001b[0m\u001b[37m\u001b[0m \u001b[1m0s\u001b[0m 53ms/step\n",
      "\u001b[1m1/1\u001b[0m \u001b[32m━━━━━━━━━━━━━━━━━━━━\u001b[0m\u001b[37m\u001b[0m \u001b[1m0s\u001b[0m 53ms/step\n",
      "\u001b[1m1/1\u001b[0m \u001b[32m━━━━━━━━━━━━━━━━━━━━\u001b[0m\u001b[37m\u001b[0m \u001b[1m0s\u001b[0m 53ms/step\n",
      "\u001b[1m1/1\u001b[0m \u001b[32m━━━━━━━━━━━━━━━━━━━━\u001b[0m\u001b[37m\u001b[0m \u001b[1m0s\u001b[0m 67ms/step\n",
      "\u001b[1m1/1\u001b[0m \u001b[32m━━━━━━━━━━━━━━━━━━━━\u001b[0m\u001b[37m\u001b[0m \u001b[1m0s\u001b[0m 47ms/step\n",
      "\u001b[1m1/1\u001b[0m \u001b[32m━━━━━━━━━━━━━━━━━━━━\u001b[0m\u001b[37m\u001b[0m \u001b[1m0s\u001b[0m 54ms/step\n",
      "\u001b[1m1/1\u001b[0m \u001b[32m━━━━━━━━━━━━━━━━━━━━\u001b[0m\u001b[37m\u001b[0m \u001b[1m0s\u001b[0m 67ms/step\n",
      "\u001b[1m1/1\u001b[0m \u001b[32m━━━━━━━━━━━━━━━━━━━━\u001b[0m\u001b[37m\u001b[0m \u001b[1m0s\u001b[0m 54ms/step\n",
      "\u001b[1m1/1\u001b[0m \u001b[32m━━━━━━━━━━━━━━━━━━━━\u001b[0m\u001b[37m\u001b[0m \u001b[1m0s\u001b[0m 54ms/step\n",
      "\u001b[1m1/1\u001b[0m \u001b[32m━━━━━━━━━━━━━━━━━━━━\u001b[0m\u001b[37m\u001b[0m \u001b[1m0s\u001b[0m 56ms/step\n",
      "\u001b[1m1/1\u001b[0m \u001b[32m━━━━━━━━━━━━━━━━━━━━\u001b[0m\u001b[37m\u001b[0m \u001b[1m0s\u001b[0m 54ms/step\n",
      "\u001b[1m1/1\u001b[0m \u001b[32m━━━━━━━━━━━━━━━━━━━━\u001b[0m\u001b[37m\u001b[0m \u001b[1m0s\u001b[0m 53ms/step\n",
      "\u001b[1m1/1\u001b[0m \u001b[32m━━━━━━━━━━━━━━━━━━━━\u001b[0m\u001b[37m\u001b[0m \u001b[1m0s\u001b[0m 54ms/step\n",
      "\u001b[1m1/1\u001b[0m \u001b[32m━━━━━━━━━━━━━━━━━━━━\u001b[0m\u001b[37m\u001b[0m \u001b[1m0s\u001b[0m 40ms/step\n",
      "\u001b[1m1/1\u001b[0m \u001b[32m━━━━━━━━━━━━━━━━━━━━\u001b[0m\u001b[37m\u001b[0m \u001b[1m0s\u001b[0m 54ms/step\n",
      "\u001b[1m1/1\u001b[0m \u001b[32m━━━━━━━━━━━━━━━━━━━━\u001b[0m\u001b[37m\u001b[0m \u001b[1m0s\u001b[0m 54ms/step\n",
      "\u001b[1m1/1\u001b[0m \u001b[32m━━━━━━━━━━━━━━━━━━━━\u001b[0m\u001b[37m\u001b[0m \u001b[1m0s\u001b[0m 54ms/step\n",
      "\u001b[1m1/1\u001b[0m \u001b[32m━━━━━━━━━━━━━━━━━━━━\u001b[0m\u001b[37m\u001b[0m \u001b[1m0s\u001b[0m 54ms/step\n",
      "\u001b[1m1/1\u001b[0m \u001b[32m━━━━━━━━━━━━━━━━━━━━\u001b[0m\u001b[37m\u001b[0m \u001b[1m0s\u001b[0m 53ms/step\n",
      "\u001b[1m1/1\u001b[0m \u001b[32m━━━━━━━━━━━━━━━━━━━━\u001b[0m\u001b[37m\u001b[0m \u001b[1m0s\u001b[0m 54ms/step\n",
      "\u001b[1m1/1\u001b[0m \u001b[32m━━━━━━━━━━━━━━━━━━━━\u001b[0m\u001b[37m\u001b[0m \u001b[1m0s\u001b[0m 66ms/step\n",
      "\u001b[1m1/1\u001b[0m \u001b[32m━━━━━━━━━━━━━━━━━━━━\u001b[0m\u001b[37m\u001b[0m \u001b[1m0s\u001b[0m 55ms/step\n",
      "\u001b[1m1/1\u001b[0m \u001b[32m━━━━━━━━━━━━━━━━━━━━\u001b[0m\u001b[37m\u001b[0m \u001b[1m0s\u001b[0m 67ms/step\n",
      "\u001b[1m1/1\u001b[0m \u001b[32m━━━━━━━━━━━━━━━━━━━━\u001b[0m\u001b[37m\u001b[0m \u001b[1m0s\u001b[0m 54ms/step\n",
      "\u001b[1m1/1\u001b[0m \u001b[32m━━━━━━━━━━━━━━━━━━━━\u001b[0m\u001b[37m\u001b[0m \u001b[1m0s\u001b[0m 54ms/step\n",
      "\u001b[1m1/1\u001b[0m \u001b[32m━━━━━━━━━━━━━━━━━━━━\u001b[0m\u001b[37m\u001b[0m \u001b[1m0s\u001b[0m 54ms/step\n",
      "\u001b[1m1/1\u001b[0m \u001b[32m━━━━━━━━━━━━━━━━━━━━\u001b[0m\u001b[37m\u001b[0m \u001b[1m0s\u001b[0m 67ms/step\n",
      "\u001b[1m1/1\u001b[0m \u001b[32m━━━━━━━━━━━━━━━━━━━━\u001b[0m\u001b[37m\u001b[0m \u001b[1m0s\u001b[0m 54ms/step\n",
      "\u001b[1m1/1\u001b[0m \u001b[32m━━━━━━━━━━━━━━━━━━━━\u001b[0m\u001b[37m\u001b[0m \u001b[1m0s\u001b[0m 59ms/step\n",
      "\u001b[1m1/1\u001b[0m \u001b[32m━━━━━━━━━━━━━━━━━━━━\u001b[0m\u001b[37m\u001b[0m \u001b[1m0s\u001b[0m 54ms/step\n",
      "\u001b[1m1/1\u001b[0m \u001b[32m━━━━━━━━━━━━━━━━━━━━\u001b[0m\u001b[37m\u001b[0m \u001b[1m0s\u001b[0m 67ms/step\n",
      "\u001b[1m1/1\u001b[0m \u001b[32m━━━━━━━━━━━━━━━━━━━━\u001b[0m\u001b[37m\u001b[0m \u001b[1m0s\u001b[0m 40ms/step\n",
      "\u001b[1m1/1\u001b[0m \u001b[32m━━━━━━━━━━━━━━━━━━━━\u001b[0m\u001b[37m\u001b[0m \u001b[1m0s\u001b[0m 48ms/step\n",
      "\u001b[1m1/1\u001b[0m \u001b[32m━━━━━━━━━━━━━━━━━━━━\u001b[0m\u001b[37m\u001b[0m \u001b[1m0s\u001b[0m 54ms/step\n",
      "\u001b[1m1/1\u001b[0m \u001b[32m━━━━━━━━━━━━━━━━━━━━\u001b[0m\u001b[37m\u001b[0m \u001b[1m0s\u001b[0m 56ms/step\n",
      "\u001b[1m1/1\u001b[0m \u001b[32m━━━━━━━━━━━━━━━━━━━━\u001b[0m\u001b[37m\u001b[0m \u001b[1m0s\u001b[0m 54ms/step\n",
      "\u001b[1m1/1\u001b[0m \u001b[32m━━━━━━━━━━━━━━━━━━━━\u001b[0m\u001b[37m\u001b[0m \u001b[1m0s\u001b[0m 55ms/step\n",
      "\u001b[1m1/1\u001b[0m \u001b[32m━━━━━━━━━━━━━━━━━━━━\u001b[0m\u001b[37m\u001b[0m \u001b[1m0s\u001b[0m 54ms/step\n",
      "\u001b[1m1/1\u001b[0m \u001b[32m━━━━━━━━━━━━━━━━━━━━\u001b[0m\u001b[37m\u001b[0m \u001b[1m0s\u001b[0m 54ms/step\n",
      "\u001b[1m1/1\u001b[0m \u001b[32m━━━━━━━━━━━━━━━━━━━━\u001b[0m\u001b[37m\u001b[0m \u001b[1m0s\u001b[0m 54ms/step\n",
      "\u001b[1m1/1\u001b[0m \u001b[32m━━━━━━━━━━━━━━━━━━━━\u001b[0m\u001b[37m\u001b[0m \u001b[1m0s\u001b[0m 54ms/step\n",
      "\u001b[1m1/1\u001b[0m \u001b[32m━━━━━━━━━━━━━━━━━━━━\u001b[0m\u001b[37m\u001b[0m \u001b[1m0s\u001b[0m 67ms/step\n",
      "\u001b[1m1/1\u001b[0m \u001b[32m━━━━━━━━━━━━━━━━━━━━\u001b[0m\u001b[37m\u001b[0m \u001b[1m0s\u001b[0m 54ms/step\n",
      "\u001b[1m1/1\u001b[0m \u001b[32m━━━━━━━━━━━━━━━━━━━━\u001b[0m\u001b[37m\u001b[0m \u001b[1m0s\u001b[0m 54ms/step\n",
      "\u001b[1m1/1\u001b[0m \u001b[32m━━━━━━━━━━━━━━━━━━━━\u001b[0m\u001b[37m\u001b[0m \u001b[1m0s\u001b[0m 61ms/step\n",
      "\u001b[1m1/1\u001b[0m \u001b[32m━━━━━━━━━━━━━━━━━━━━\u001b[0m\u001b[37m\u001b[0m \u001b[1m0s\u001b[0m 54ms/step\n",
      "\u001b[1m1/1\u001b[0m \u001b[32m━━━━━━━━━━━━━━━━━━━━\u001b[0m\u001b[37m\u001b[0m \u001b[1m0s\u001b[0m 50ms/step\n",
      "\u001b[1m1/1\u001b[0m \u001b[32m━━━━━━━━━━━━━━━━━━━━\u001b[0m\u001b[37m\u001b[0m \u001b[1m0s\u001b[0m 53ms/step\n",
      "\u001b[1m1/1\u001b[0m \u001b[32m━━━━━━━━━━━━━━━━━━━━\u001b[0m\u001b[37m\u001b[0m \u001b[1m0s\u001b[0m 67ms/step\n",
      "\u001b[1m1/1\u001b[0m \u001b[32m━━━━━━━━━━━━━━━━━━━━\u001b[0m\u001b[37m\u001b[0m \u001b[1m0s\u001b[0m 67ms/step\n",
      "\u001b[1m1/1\u001b[0m \u001b[32m━━━━━━━━━━━━━━━━━━━━\u001b[0m\u001b[37m\u001b[0m \u001b[1m0s\u001b[0m 54ms/step\n",
      "\u001b[1m1/1\u001b[0m \u001b[32m━━━━━━━━━━━━━━━━━━━━\u001b[0m\u001b[37m\u001b[0m \u001b[1m0s\u001b[0m 54ms/step\n",
      "\u001b[1m1/1\u001b[0m \u001b[32m━━━━━━━━━━━━━━━━━━━━\u001b[0m\u001b[37m\u001b[0m \u001b[1m0s\u001b[0m 50ms/step\n",
      "\u001b[1m1/1\u001b[0m \u001b[32m━━━━━━━━━━━━━━━━━━━━\u001b[0m\u001b[37m\u001b[0m \u001b[1m0s\u001b[0m 57ms/step\n",
      "\u001b[1m1/1\u001b[0m \u001b[32m━━━━━━━━━━━━━━━━━━━━\u001b[0m\u001b[37m\u001b[0m \u001b[1m0s\u001b[0m 55ms/step\n",
      "\u001b[1m1/1\u001b[0m \u001b[32m━━━━━━━━━━━━━━━━━━━━\u001b[0m\u001b[37m\u001b[0m \u001b[1m0s\u001b[0m 63ms/step\n",
      "\u001b[1m1/1\u001b[0m \u001b[32m━━━━━━━━━━━━━━━━━━━━\u001b[0m\u001b[37m\u001b[0m \u001b[1m0s\u001b[0m 54ms/step\n",
      "\u001b[1m1/1\u001b[0m \u001b[32m━━━━━━━━━━━━━━━━━━━━\u001b[0m\u001b[37m\u001b[0m \u001b[1m0s\u001b[0m 54ms/step\n",
      "\u001b[1m1/1\u001b[0m \u001b[32m━━━━━━━━━━━━━━━━━━━━\u001b[0m\u001b[37m\u001b[0m \u001b[1m0s\u001b[0m 54ms/step\n",
      "\u001b[1m1/1\u001b[0m \u001b[32m━━━━━━━━━━━━━━━━━━━━\u001b[0m\u001b[37m\u001b[0m \u001b[1m0s\u001b[0m 54ms/step\n",
      "\u001b[1m1/1\u001b[0m \u001b[32m━━━━━━━━━━━━━━━━━━━━\u001b[0m\u001b[37m\u001b[0m \u001b[1m0s\u001b[0m 53ms/step\n",
      "\u001b[1m1/1\u001b[0m \u001b[32m━━━━━━━━━━━━━━━━━━━━\u001b[0m\u001b[37m\u001b[0m \u001b[1m0s\u001b[0m 54ms/step\n",
      "\u001b[1m1/1\u001b[0m \u001b[32m━━━━━━━━━━━━━━━━━━━━\u001b[0m\u001b[37m\u001b[0m \u001b[1m0s\u001b[0m 54ms/step\n",
      "\u001b[1m1/1\u001b[0m \u001b[32m━━━━━━━━━━━━━━━━━━━━\u001b[0m\u001b[37m\u001b[0m \u001b[1m0s\u001b[0m 65ms/step\n",
      "\u001b[1m1/1\u001b[0m \u001b[32m━━━━━━━━━━━━━━━━━━━━\u001b[0m\u001b[37m\u001b[0m \u001b[1m0s\u001b[0m 53ms/step\n",
      "\u001b[1m1/1\u001b[0m \u001b[32m━━━━━━━━━━━━━━━━━━━━\u001b[0m\u001b[37m\u001b[0m \u001b[1m0s\u001b[0m 54ms/step\n",
      "\u001b[1m1/1\u001b[0m \u001b[32m━━━━━━━━━━━━━━━━━━━━\u001b[0m\u001b[37m\u001b[0m \u001b[1m0s\u001b[0m 53ms/step\n",
      "\u001b[1m1/1\u001b[0m \u001b[32m━━━━━━━━━━━━━━━━━━━━\u001b[0m\u001b[37m\u001b[0m \u001b[1m0s\u001b[0m 62ms/step\n",
      "\u001b[1m1/1\u001b[0m \u001b[32m━━━━━━━━━━━━━━━━━━━━\u001b[0m\u001b[37m\u001b[0m \u001b[1m0s\u001b[0m 56ms/step\n",
      "\u001b[1m1/1\u001b[0m \u001b[32m━━━━━━━━━━━━━━━━━━━━\u001b[0m\u001b[37m\u001b[0m \u001b[1m0s\u001b[0m 67ms/step\n",
      "\u001b[1m1/1\u001b[0m \u001b[32m━━━━━━━━━━━━━━━━━━━━\u001b[0m\u001b[37m\u001b[0m \u001b[1m0s\u001b[0m 53ms/step\n",
      "\u001b[1m1/1\u001b[0m \u001b[32m━━━━━━━━━━━━━━━━━━━━\u001b[0m\u001b[37m\u001b[0m \u001b[1m0s\u001b[0m 54ms/step\n",
      "\u001b[1m1/1\u001b[0m \u001b[32m━━━━━━━━━━━━━━━━━━━━\u001b[0m\u001b[37m\u001b[0m \u001b[1m0s\u001b[0m 67ms/step\n",
      "\u001b[1m1/1\u001b[0m \u001b[32m━━━━━━━━━━━━━━━━━━━━\u001b[0m\u001b[37m\u001b[0m \u001b[1m0s\u001b[0m 53ms/step\n",
      "\u001b[1m1/1\u001b[0m \u001b[32m━━━━━━━━━━━━━━━━━━━━\u001b[0m\u001b[37m\u001b[0m \u001b[1m0s\u001b[0m 54ms/step\n",
      "\u001b[1m1/1\u001b[0m \u001b[32m━━━━━━━━━━━━━━━━━━━━\u001b[0m\u001b[37m\u001b[0m \u001b[1m0s\u001b[0m 67ms/step\n",
      "\u001b[1m1/1\u001b[0m \u001b[32m━━━━━━━━━━━━━━━━━━━━\u001b[0m\u001b[37m\u001b[0m \u001b[1m0s\u001b[0m 53ms/step\n",
      "\u001b[1m1/1\u001b[0m \u001b[32m━━━━━━━━━━━━━━━━━━━━\u001b[0m\u001b[37m\u001b[0m \u001b[1m0s\u001b[0m 62ms/step\n",
      "\u001b[1m1/1\u001b[0m \u001b[32m━━━━━━━━━━━━━━━━━━━━\u001b[0m\u001b[37m\u001b[0m \u001b[1m0s\u001b[0m 56ms/step\n",
      "\u001b[1m1/1\u001b[0m \u001b[32m━━━━━━━━━━━━━━━━━━━━\u001b[0m\u001b[37m\u001b[0m \u001b[1m0s\u001b[0m 64ms/step\n",
      "\u001b[1m1/1\u001b[0m \u001b[32m━━━━━━━━━━━━━━━━━━━━\u001b[0m\u001b[37m\u001b[0m \u001b[1m0s\u001b[0m 54ms/step\n",
      "\u001b[1m1/1\u001b[0m \u001b[32m━━━━━━━━━━━━━━━━━━━━\u001b[0m\u001b[37m\u001b[0m \u001b[1m0s\u001b[0m 59ms/step\n",
      "\u001b[1m1/1\u001b[0m \u001b[32m━━━━━━━━━━━━━━━━━━━━\u001b[0m\u001b[37m\u001b[0m \u001b[1m0s\u001b[0m 47ms/step\n",
      "\u001b[1m1/1\u001b[0m \u001b[32m━━━━━━━━━━━━━━━━━━━━\u001b[0m\u001b[37m\u001b[0m \u001b[1m0s\u001b[0m 70ms/step\n",
      "\u001b[1m1/1\u001b[0m \u001b[32m━━━━━━━━━━━━━━━━━━━━\u001b[0m\u001b[37m\u001b[0m \u001b[1m0s\u001b[0m 48ms/step\n",
      "\u001b[1m1/1\u001b[0m \u001b[32m━━━━━━━━━━━━━━━━━━━━\u001b[0m\u001b[37m\u001b[0m \u001b[1m0s\u001b[0m 54ms/step\n",
      "\u001b[1m1/1\u001b[0m \u001b[32m━━━━━━━━━━━━━━━━━━━━\u001b[0m\u001b[37m\u001b[0m \u001b[1m0s\u001b[0m 67ms/step\n",
      "\u001b[1m1/1\u001b[0m \u001b[32m━━━━━━━━━━━━━━━━━━━━\u001b[0m\u001b[37m\u001b[0m \u001b[1m0s\u001b[0m 53ms/step\n",
      "\u001b[1m1/1\u001b[0m \u001b[32m━━━━━━━━━━━━━━━━━━━━\u001b[0m\u001b[37m\u001b[0m \u001b[1m0s\u001b[0m 53ms/step\n",
      "\u001b[1m1/1\u001b[0m \u001b[32m━━━━━━━━━━━━━━━━━━━━\u001b[0m\u001b[37m\u001b[0m \u001b[1m0s\u001b[0m 54ms/step\n",
      "\u001b[1m1/1\u001b[0m \u001b[32m━━━━━━━━━━━━━━━━━━━━\u001b[0m\u001b[37m\u001b[0m \u001b[1m0s\u001b[0m 66ms/step\n",
      "\u001b[1m1/1\u001b[0m \u001b[32m━━━━━━━━━━━━━━━━━━━━\u001b[0m\u001b[37m\u001b[0m \u001b[1m0s\u001b[0m 69ms/step\n",
      "\u001b[1m1/1\u001b[0m \u001b[32m━━━━━━━━━━━━━━━━━━━━\u001b[0m\u001b[37m\u001b[0m \u001b[1m0s\u001b[0m 48ms/step\n",
      "\u001b[1m1/1\u001b[0m \u001b[32m━━━━━━━━━━━━━━━━━━━━\u001b[0m\u001b[37m\u001b[0m \u001b[1m0s\u001b[0m 54ms/step\n",
      "\u001b[1m1/1\u001b[0m \u001b[32m━━━━━━━━━━━━━━━━━━━━\u001b[0m\u001b[37m\u001b[0m \u001b[1m0s\u001b[0m 67ms/step\n",
      "\u001b[1m1/1\u001b[0m \u001b[32m━━━━━━━━━━━━━━━━━━━━\u001b[0m\u001b[37m\u001b[0m \u001b[1m0s\u001b[0m 40ms/step\n",
      "\u001b[1m1/1\u001b[0m \u001b[32m━━━━━━━━━━━━━━━━━━━━\u001b[0m\u001b[37m\u001b[0m \u001b[1m0s\u001b[0m 52ms/step\n",
      "\u001b[1m1/1\u001b[0m \u001b[32m━━━━━━━━━━━━━━━━━━━━\u001b[0m\u001b[37m\u001b[0m \u001b[1m0s\u001b[0m 54ms/step\n",
      "\u001b[1m1/1\u001b[0m \u001b[32m━━━━━━━━━━━━━━━━━━━━\u001b[0m\u001b[37m\u001b[0m \u001b[1m0s\u001b[0m 54ms/step\n",
      "\u001b[1m1/1\u001b[0m \u001b[32m━━━━━━━━━━━━━━━━━━━━\u001b[0m\u001b[37m\u001b[0m \u001b[1m0s\u001b[0m 67ms/step\n",
      "\u001b[1m1/1\u001b[0m \u001b[32m━━━━━━━━━━━━━━━━━━━━\u001b[0m\u001b[37m\u001b[0m \u001b[1m0s\u001b[0m 54ms/step\n",
      "\u001b[1m1/1\u001b[0m \u001b[32m━━━━━━━━━━━━━━━━━━━━\u001b[0m\u001b[37m\u001b[0m \u001b[1m0s\u001b[0m 54ms/step\n",
      "\u001b[1m1/1\u001b[0m \u001b[32m━━━━━━━━━━━━━━━━━━━━\u001b[0m\u001b[37m\u001b[0m \u001b[1m0s\u001b[0m 53ms/step\n",
      "\u001b[1m1/1\u001b[0m \u001b[32m━━━━━━━━━━━━━━━━━━━━\u001b[0m\u001b[37m\u001b[0m \u001b[1m0s\u001b[0m 54ms/step\n",
      "\u001b[1m1/1\u001b[0m \u001b[32m━━━━━━━━━━━━━━━━━━━━\u001b[0m\u001b[37m\u001b[0m \u001b[1m0s\u001b[0m 53ms/step\n",
      "\u001b[1m1/1\u001b[0m \u001b[32m━━━━━━━━━━━━━━━━━━━━\u001b[0m\u001b[37m\u001b[0m \u001b[1m0s\u001b[0m 54ms/step\n",
      "\u001b[1m1/1\u001b[0m \u001b[32m━━━━━━━━━━━━━━━━━━━━\u001b[0m\u001b[37m\u001b[0m \u001b[1m0s\u001b[0m 53ms/step\n",
      "\u001b[1m1/1\u001b[0m \u001b[32m━━━━━━━━━━━━━━━━━━━━\u001b[0m\u001b[37m\u001b[0m \u001b[1m0s\u001b[0m 53ms/step\n",
      "\u001b[1m1/1\u001b[0m \u001b[32m━━━━━━━━━━━━━━━━━━━━\u001b[0m\u001b[37m\u001b[0m \u001b[1m0s\u001b[0m 44ms/step\n",
      "\u001b[1m1/1\u001b[0m \u001b[32m━━━━━━━━━━━━━━━━━━━━\u001b[0m\u001b[37m\u001b[0m \u001b[1m0s\u001b[0m 54ms/step\n",
      "\u001b[1m1/1\u001b[0m \u001b[32m━━━━━━━━━━━━━━━━━━━━\u001b[0m\u001b[37m\u001b[0m \u001b[1m0s\u001b[0m 55ms/step\n",
      "\u001b[1m1/1\u001b[0m \u001b[32m━━━━━━━━━━━━━━━━━━━━\u001b[0m\u001b[37m\u001b[0m \u001b[1m0s\u001b[0m 54ms/step\n",
      "\u001b[1m1/1\u001b[0m \u001b[32m━━━━━━━━━━━━━━━━━━━━\u001b[0m\u001b[37m\u001b[0m \u001b[1m0s\u001b[0m 48ms/step\n",
      "\u001b[1m1/1\u001b[0m \u001b[32m━━━━━━━━━━━━━━━━━━━━\u001b[0m\u001b[37m\u001b[0m \u001b[1m0s\u001b[0m 54ms/step\n",
      "\u001b[1m1/1\u001b[0m \u001b[32m━━━━━━━━━━━━━━━━━━━━\u001b[0m\u001b[37m\u001b[0m \u001b[1m0s\u001b[0m 53ms/step\n",
      "\u001b[1m1/1\u001b[0m \u001b[32m━━━━━━━━━━━━━━━━━━━━\u001b[0m\u001b[37m\u001b[0m \u001b[1m0s\u001b[0m 54ms/step\n",
      "\u001b[1m1/1\u001b[0m \u001b[32m━━━━━━━━━━━━━━━━━━━━\u001b[0m\u001b[37m\u001b[0m \u001b[1m0s\u001b[0m 66ms/step\n",
      "\u001b[1m1/1\u001b[0m \u001b[32m━━━━━━━━━━━━━━━━━━━━\u001b[0m\u001b[37m\u001b[0m \u001b[1m0s\u001b[0m 54ms/step\n",
      "\u001b[1m1/1\u001b[0m \u001b[32m━━━━━━━━━━━━━━━━━━━━\u001b[0m\u001b[37m\u001b[0m \u001b[1m0s\u001b[0m 60ms/step\n",
      "\u001b[1m1/1\u001b[0m \u001b[32m━━━━━━━━━━━━━━━━━━━━\u001b[0m\u001b[37m\u001b[0m \u001b[1m0s\u001b[0m 54ms/step\n",
      "\u001b[1m1/1\u001b[0m \u001b[32m━━━━━━━━━━━━━━━━━━━━\u001b[0m\u001b[37m\u001b[0m \u001b[1m0s\u001b[0m 54ms/step\n",
      "\u001b[1m1/1\u001b[0m \u001b[32m━━━━━━━━━━━━━━━━━━━━\u001b[0m\u001b[37m\u001b[0m \u001b[1m0s\u001b[0m 54ms/step\n",
      "\u001b[1m1/1\u001b[0m \u001b[32m━━━━━━━━━━━━━━━━━━━━\u001b[0m\u001b[37m\u001b[0m \u001b[1m0s\u001b[0m 54ms/step\n",
      "\u001b[1m1/1\u001b[0m \u001b[32m━━━━━━━━━━━━━━━━━━━━\u001b[0m\u001b[37m\u001b[0m \u001b[1m0s\u001b[0m 60ms/step\n",
      "\u001b[1m1/1\u001b[0m \u001b[32m━━━━━━━━━━━━━━━━━━━━\u001b[0m\u001b[37m\u001b[0m \u001b[1m0s\u001b[0m 67ms/step\n",
      "\u001b[1m1/1\u001b[0m \u001b[32m━━━━━━━━━━━━━━━━━━━━\u001b[0m\u001b[37m\u001b[0m \u001b[1m0s\u001b[0m 54ms/step\n",
      "\u001b[1m1/1\u001b[0m \u001b[32m━━━━━━━━━━━━━━━━━━━━\u001b[0m\u001b[37m\u001b[0m \u001b[1m0s\u001b[0m 54ms/step\n",
      "\u001b[1m1/1\u001b[0m \u001b[32m━━━━━━━━━━━━━━━━━━━━\u001b[0m\u001b[37m\u001b[0m \u001b[1m0s\u001b[0m 54ms/step\n",
      "\u001b[1m1/1\u001b[0m \u001b[32m━━━━━━━━━━━━━━━━━━━━\u001b[0m\u001b[37m\u001b[0m \u001b[1m0s\u001b[0m 52ms/step\n",
      "\u001b[1m1/1\u001b[0m \u001b[32m━━━━━━━━━━━━━━━━━━━━\u001b[0m\u001b[37m\u001b[0m \u001b[1m0s\u001b[0m 46ms/step\n",
      "\u001b[1m1/1\u001b[0m \u001b[32m━━━━━━━━━━━━━━━━━━━━\u001b[0m\u001b[37m\u001b[0m \u001b[1m0s\u001b[0m 44ms/step\n",
      "\u001b[1m1/1\u001b[0m \u001b[32m━━━━━━━━━━━━━━━━━━━━\u001b[0m\u001b[37m\u001b[0m \u001b[1m0s\u001b[0m 54ms/step\n",
      "\u001b[1m1/1\u001b[0m \u001b[32m━━━━━━━━━━━━━━━━━━━━\u001b[0m\u001b[37m\u001b[0m \u001b[1m0s\u001b[0m 67ms/step\n",
      "\u001b[1m1/1\u001b[0m \u001b[32m━━━━━━━━━━━━━━━━━━━━\u001b[0m\u001b[37m\u001b[0m \u001b[1m0s\u001b[0m 54ms/step\n",
      "\u001b[1m1/1\u001b[0m \u001b[32m━━━━━━━━━━━━━━━━━━━━\u001b[0m\u001b[37m\u001b[0m \u001b[1m0s\u001b[0m 64ms/step\n",
      "\u001b[1m1/1\u001b[0m \u001b[32m━━━━━━━━━━━━━━━━━━━━\u001b[0m\u001b[37m\u001b[0m \u001b[1m0s\u001b[0m 68ms/step\n",
      "\u001b[1m1/1\u001b[0m \u001b[32m━━━━━━━━━━━━━━━━━━━━\u001b[0m\u001b[37m\u001b[0m \u001b[1m0s\u001b[0m 67ms/step\n",
      "\u001b[1m1/1\u001b[0m \u001b[32m━━━━━━━━━━━━━━━━━━━━\u001b[0m\u001b[37m\u001b[0m \u001b[1m0s\u001b[0m 54ms/step\n",
      "\u001b[1m1/1\u001b[0m \u001b[32m━━━━━━━━━━━━━━━━━━━━\u001b[0m\u001b[37m\u001b[0m \u001b[1m0s\u001b[0m 54ms/step\n",
      "\u001b[1m1/1\u001b[0m \u001b[32m━━━━━━━━━━━━━━━━━━━━\u001b[0m\u001b[37m\u001b[0m \u001b[1m0s\u001b[0m 46ms/step\n",
      "\u001b[1m1/1\u001b[0m \u001b[32m━━━━━━━━━━━━━━━━━━━━\u001b[0m\u001b[37m\u001b[0m \u001b[1m0s\u001b[0m 67ms/step\n",
      "\u001b[1m1/1\u001b[0m \u001b[32m━━━━━━━━━━━━━━━━━━━━\u001b[0m\u001b[37m\u001b[0m \u001b[1m0s\u001b[0m 54ms/step\n",
      "\u001b[1m1/1\u001b[0m \u001b[32m━━━━━━━━━━━━━━━━━━━━\u001b[0m\u001b[37m\u001b[0m \u001b[1m0s\u001b[0m 53ms/step\n",
      "\u001b[1m1/1\u001b[0m \u001b[32m━━━━━━━━━━━━━━━━━━━━\u001b[0m\u001b[37m\u001b[0m \u001b[1m0s\u001b[0m 53ms/step\n",
      "\u001b[1m1/1\u001b[0m \u001b[32m━━━━━━━━━━━━━━━━━━━━\u001b[0m\u001b[37m\u001b[0m \u001b[1m0s\u001b[0m 54ms/step\n",
      "\u001b[1m1/1\u001b[0m \u001b[32m━━━━━━━━━━━━━━━━━━━━\u001b[0m\u001b[37m\u001b[0m \u001b[1m0s\u001b[0m 54ms/step\n",
      "\u001b[1m1/1\u001b[0m \u001b[32m━━━━━━━━━━━━━━━━━━━━\u001b[0m\u001b[37m\u001b[0m \u001b[1m0s\u001b[0m 54ms/step\n",
      "\u001b[1m1/1\u001b[0m \u001b[32m━━━━━━━━━━━━━━━━━━━━\u001b[0m\u001b[37m\u001b[0m \u001b[1m0s\u001b[0m 51ms/step\n",
      "\u001b[1m1/1\u001b[0m \u001b[32m━━━━━━━━━━━━━━━━━━━━\u001b[0m\u001b[37m\u001b[0m \u001b[1m0s\u001b[0m 54ms/step\n",
      "\u001b[1m1/1\u001b[0m \u001b[32m━━━━━━━━━━━━━━━━━━━━\u001b[0m\u001b[37m\u001b[0m \u001b[1m0s\u001b[0m 67ms/step\n",
      "\u001b[1m1/1\u001b[0m \u001b[32m━━━━━━━━━━━━━━━━━━━━\u001b[0m\u001b[37m\u001b[0m \u001b[1m0s\u001b[0m 54ms/step\n",
      "\u001b[1m1/1\u001b[0m \u001b[32m━━━━━━━━━━━━━━━━━━━━\u001b[0m\u001b[37m\u001b[0m \u001b[1m0s\u001b[0m 67ms/step\n",
      "\u001b[1m1/1\u001b[0m \u001b[32m━━━━━━━━━━━━━━━━━━━━\u001b[0m\u001b[37m\u001b[0m \u001b[1m0s\u001b[0m 66ms/step\n",
      "\u001b[1m1/1\u001b[0m \u001b[32m━━━━━━━━━━━━━━━━━━━━\u001b[0m\u001b[37m\u001b[0m \u001b[1m0s\u001b[0m 54ms/step\n",
      "\u001b[1m1/1\u001b[0m \u001b[32m━━━━━━━━━━━━━━━━━━━━\u001b[0m\u001b[37m\u001b[0m \u001b[1m0s\u001b[0m 54ms/step\n",
      "\u001b[1m1/1\u001b[0m \u001b[32m━━━━━━━━━━━━━━━━━━━━\u001b[0m\u001b[37m\u001b[0m \u001b[1m0s\u001b[0m 54ms/step\n",
      "\u001b[1m1/1\u001b[0m \u001b[32m━━━━━━━━━━━━━━━━━━━━\u001b[0m\u001b[37m\u001b[0m \u001b[1m0s\u001b[0m 54ms/step\n",
      "\u001b[1m1/1\u001b[0m \u001b[32m━━━━━━━━━━━━━━━━━━━━\u001b[0m\u001b[37m\u001b[0m \u001b[1m0s\u001b[0m 47ms/step\n",
      "\u001b[1m1/1\u001b[0m \u001b[32m━━━━━━━━━━━━━━━━━━━━\u001b[0m\u001b[37m\u001b[0m \u001b[1m0s\u001b[0m 54ms/step\n",
      "\u001b[1m1/1\u001b[0m \u001b[32m━━━━━━━━━━━━━━━━━━━━\u001b[0m\u001b[37m\u001b[0m \u001b[1m0s\u001b[0m 53ms/step\n",
      "\u001b[1m1/1\u001b[0m \u001b[32m━━━━━━━━━━━━━━━━━━━━\u001b[0m\u001b[37m\u001b[0m \u001b[1m0s\u001b[0m 56ms/step\n",
      "\u001b[1m1/1\u001b[0m \u001b[32m━━━━━━━━━━━━━━━━━━━━\u001b[0m\u001b[37m\u001b[0m \u001b[1m0s\u001b[0m 54ms/step\n",
      "\u001b[1m1/1\u001b[0m \u001b[32m━━━━━━━━━━━━━━━━━━━━\u001b[0m\u001b[37m\u001b[0m \u001b[1m0s\u001b[0m 54ms/step\n",
      "\u001b[1m1/1\u001b[0m \u001b[32m━━━━━━━━━━━━━━━━━━━━\u001b[0m\u001b[37m\u001b[0m \u001b[1m0s\u001b[0m 54ms/step\n",
      "\u001b[1m1/1\u001b[0m \u001b[32m━━━━━━━━━━━━━━━━━━━━\u001b[0m\u001b[37m\u001b[0m \u001b[1m0s\u001b[0m 68ms/step\n",
      "\u001b[1m1/1\u001b[0m \u001b[32m━━━━━━━━━━━━━━━━━━━━\u001b[0m\u001b[37m\u001b[0m \u001b[1m0s\u001b[0m 60ms/step\n",
      "\u001b[1m1/1\u001b[0m \u001b[32m━━━━━━━━━━━━━━━━━━━━\u001b[0m\u001b[37m\u001b[0m \u001b[1m0s\u001b[0m 54ms/step\n",
      "\u001b[1m1/1\u001b[0m \u001b[32m━━━━━━━━━━━━━━━━━━━━\u001b[0m\u001b[37m\u001b[0m \u001b[1m0s\u001b[0m 53ms/step\n",
      "\u001b[1m1/1\u001b[0m \u001b[32m━━━━━━━━━━━━━━━━━━━━\u001b[0m\u001b[37m\u001b[0m \u001b[1m0s\u001b[0m 70ms/step\n",
      "\u001b[1m1/1\u001b[0m \u001b[32m━━━━━━━━━━━━━━━━━━━━\u001b[0m\u001b[37m\u001b[0m \u001b[1m0s\u001b[0m 54ms/step\n",
      "\u001b[1m1/1\u001b[0m \u001b[32m━━━━━━━━━━━━━━━━━━━━\u001b[0m\u001b[37m\u001b[0m \u001b[1m0s\u001b[0m 67ms/step\n",
      "\u001b[1m1/1\u001b[0m \u001b[32m━━━━━━━━━━━━━━━━━━━━\u001b[0m\u001b[37m\u001b[0m \u001b[1m0s\u001b[0m 55ms/step\n",
      "\u001b[1m1/1\u001b[0m \u001b[32m━━━━━━━━━━━━━━━━━━━━\u001b[0m\u001b[37m\u001b[0m \u001b[1m0s\u001b[0m 53ms/step\n",
      "\u001b[1m1/1\u001b[0m \u001b[32m━━━━━━━━━━━━━━━━━━━━\u001b[0m\u001b[37m\u001b[0m \u001b[1m0s\u001b[0m 53ms/step\n",
      "\u001b[1m1/1\u001b[0m \u001b[32m━━━━━━━━━━━━━━━━━━━━\u001b[0m\u001b[37m\u001b[0m \u001b[1m0s\u001b[0m 54ms/step\n",
      "\u001b[1m1/1\u001b[0m \u001b[32m━━━━━━━━━━━━━━━━━━━━\u001b[0m\u001b[37m\u001b[0m \u001b[1m0s\u001b[0m 54ms/step\n",
      "\u001b[1m1/1\u001b[0m \u001b[32m━━━━━━━━━━━━━━━━━━━━\u001b[0m\u001b[37m\u001b[0m \u001b[1m0s\u001b[0m 54ms/step\n",
      "\u001b[1m1/1\u001b[0m \u001b[32m━━━━━━━━━━━━━━━━━━━━\u001b[0m\u001b[37m\u001b[0m \u001b[1m0s\u001b[0m 45ms/step\n",
      "\u001b[1m1/1\u001b[0m \u001b[32m━━━━━━━━━━━━━━━━━━━━\u001b[0m\u001b[37m\u001b[0m \u001b[1m0s\u001b[0m 67ms/step\n",
      "\u001b[1m1/1\u001b[0m \u001b[32m━━━━━━━━━━━━━━━━━━━━\u001b[0m\u001b[37m\u001b[0m \u001b[1m0s\u001b[0m 66ms/step\n",
      "\u001b[1m1/1\u001b[0m \u001b[32m━━━━━━━━━━━━━━━━━━━━\u001b[0m\u001b[37m\u001b[0m \u001b[1m0s\u001b[0m 54ms/step\n",
      "\u001b[1m1/1\u001b[0m \u001b[32m━━━━━━━━━━━━━━━━━━━━\u001b[0m\u001b[37m\u001b[0m \u001b[1m0s\u001b[0m 43ms/step\n",
      "\u001b[1m1/1\u001b[0m \u001b[32m━━━━━━━━━━━━━━━━━━━━\u001b[0m\u001b[37m\u001b[0m \u001b[1m0s\u001b[0m 54ms/step\n",
      "\u001b[1m1/1\u001b[0m \u001b[32m━━━━━━━━━━━━━━━━━━━━\u001b[0m\u001b[37m\u001b[0m \u001b[1m0s\u001b[0m 60ms/step\n",
      "\u001b[1m1/1\u001b[0m \u001b[32m━━━━━━━━━━━━━━━━━━━━\u001b[0m\u001b[37m\u001b[0m \u001b[1m0s\u001b[0m 54ms/step\n",
      "\u001b[1m1/1\u001b[0m \u001b[32m━━━━━━━━━━━━━━━━━━━━\u001b[0m\u001b[37m\u001b[0m \u001b[1m0s\u001b[0m 55ms/step\n",
      "\u001b[1m1/1\u001b[0m \u001b[32m━━━━━━━━━━━━━━━━━━━━\u001b[0m\u001b[37m\u001b[0m \u001b[1m0s\u001b[0m 54ms/step\n",
      "\u001b[1m1/1\u001b[0m \u001b[32m━━━━━━━━━━━━━━━━━━━━\u001b[0m\u001b[37m\u001b[0m \u001b[1m0s\u001b[0m 54ms/step\n",
      "\u001b[1m1/1\u001b[0m \u001b[32m━━━━━━━━━━━━━━━━━━━━\u001b[0m\u001b[37m\u001b[0m \u001b[1m0s\u001b[0m 54ms/step\n",
      "\u001b[1m1/1\u001b[0m \u001b[32m━━━━━━━━━━━━━━━━━━━━\u001b[0m\u001b[37m\u001b[0m \u001b[1m0s\u001b[0m 61ms/step\n",
      "\u001b[1m1/1\u001b[0m \u001b[32m━━━━━━━━━━━━━━━━━━━━\u001b[0m\u001b[37m\u001b[0m \u001b[1m0s\u001b[0m 54ms/step\n",
      "\u001b[1m1/1\u001b[0m \u001b[32m━━━━━━━━━━━━━━━━━━━━\u001b[0m\u001b[37m\u001b[0m \u001b[1m0s\u001b[0m 49ms/step\n",
      "\u001b[1m1/1\u001b[0m \u001b[32m━━━━━━━━━━━━━━━━━━━━\u001b[0m\u001b[37m\u001b[0m \u001b[1m0s\u001b[0m 53ms/step\n",
      "\u001b[1m1/1\u001b[0m \u001b[32m━━━━━━━━━━━━━━━━━━━━\u001b[0m\u001b[37m\u001b[0m \u001b[1m0s\u001b[0m 54ms/step\n",
      "\u001b[1m1/1\u001b[0m \u001b[32m━━━━━━━━━━━━━━━━━━━━\u001b[0m\u001b[37m\u001b[0m \u001b[1m0s\u001b[0m 53ms/step\n",
      "\u001b[1m1/1\u001b[0m \u001b[32m━━━━━━━━━━━━━━━━━━━━\u001b[0m\u001b[37m\u001b[0m \u001b[1m0s\u001b[0m 54ms/step\n",
      "\u001b[1m1/1\u001b[0m \u001b[32m━━━━━━━━━━━━━━━━━━━━\u001b[0m\u001b[37m\u001b[0m \u001b[1m0s\u001b[0m 54ms/step\n",
      "\u001b[1m1/1\u001b[0m \u001b[32m━━━━━━━━━━━━━━━━━━━━\u001b[0m\u001b[37m\u001b[0m \u001b[1m0s\u001b[0m 54ms/step\n",
      "\u001b[1m1/1\u001b[0m \u001b[32m━━━━━━━━━━━━━━━━━━━━\u001b[0m\u001b[37m\u001b[0m \u001b[1m0s\u001b[0m 54ms/step\n",
      "\u001b[1m1/1\u001b[0m \u001b[32m━━━━━━━━━━━━━━━━━━━━\u001b[0m\u001b[37m\u001b[0m \u001b[1m0s\u001b[0m 54ms/step\n",
      "\u001b[1m1/1\u001b[0m \u001b[32m━━━━━━━━━━━━━━━━━━━━\u001b[0m\u001b[37m\u001b[0m \u001b[1m0s\u001b[0m 54ms/step\n",
      "\u001b[1m1/1\u001b[0m \u001b[32m━━━━━━━━━━━━━━━━━━━━\u001b[0m\u001b[37m\u001b[0m \u001b[1m0s\u001b[0m 49ms/step\n",
      "\u001b[1m1/1\u001b[0m \u001b[32m━━━━━━━━━━━━━━━━━━━━\u001b[0m\u001b[37m\u001b[0m \u001b[1m0s\u001b[0m 53ms/step\n",
      "\u001b[1m1/1\u001b[0m \u001b[32m━━━━━━━━━━━━━━━━━━━━\u001b[0m\u001b[37m\u001b[0m \u001b[1m0s\u001b[0m 54ms/step\n",
      "\u001b[1m1/1\u001b[0m \u001b[32m━━━━━━━━━━━━━━━━━━━━\u001b[0m\u001b[37m\u001b[0m \u001b[1m0s\u001b[0m 54ms/step\n",
      "\u001b[1m1/1\u001b[0m \u001b[32m━━━━━━━━━━━━━━━━━━━━\u001b[0m\u001b[37m\u001b[0m \u001b[1m0s\u001b[0m 67ms/step\n",
      "\u001b[1m1/1\u001b[0m \u001b[32m━━━━━━━━━━━━━━━━━━━━\u001b[0m\u001b[37m\u001b[0m \u001b[1m0s\u001b[0m 54ms/step\n",
      "\u001b[1m1/1\u001b[0m \u001b[32m━━━━━━━━━━━━━━━━━━━━\u001b[0m\u001b[37m\u001b[0m \u001b[1m0s\u001b[0m 61ms/step\n",
      "\u001b[1m1/1\u001b[0m \u001b[32m━━━━━━━━━━━━━━━━━━━━\u001b[0m\u001b[37m\u001b[0m \u001b[1m0s\u001b[0m 53ms/step\n",
      "\u001b[1m1/1\u001b[0m \u001b[32m━━━━━━━━━━━━━━━━━━━━\u001b[0m\u001b[37m\u001b[0m \u001b[1m0s\u001b[0m 54ms/step\n",
      "\u001b[1m1/1\u001b[0m \u001b[32m━━━━━━━━━━━━━━━━━━━━\u001b[0m\u001b[37m\u001b[0m \u001b[1m0s\u001b[0m 54ms/step\n",
      "\u001b[1m1/1\u001b[0m \u001b[32m━━━━━━━━━━━━━━━━━━━━\u001b[0m\u001b[37m\u001b[0m \u001b[1m0s\u001b[0m 53ms/step\n",
      "\u001b[1m1/1\u001b[0m \u001b[32m━━━━━━━━━━━━━━━━━━━━\u001b[0m\u001b[37m\u001b[0m \u001b[1m0s\u001b[0m 67ms/step\n",
      "\u001b[1m1/1\u001b[0m \u001b[32m━━━━━━━━━━━━━━━━━━━━\u001b[0m\u001b[37m\u001b[0m \u001b[1m0s\u001b[0m 54ms/step\n",
      "\u001b[1m1/1\u001b[0m \u001b[32m━━━━━━━━━━━━━━━━━━━━\u001b[0m\u001b[37m\u001b[0m \u001b[1m0s\u001b[0m 54ms/step\n",
      "\u001b[1m1/1\u001b[0m \u001b[32m━━━━━━━━━━━━━━━━━━━━\u001b[0m\u001b[37m\u001b[0m \u001b[1m0s\u001b[0m 54ms/step\n",
      "\u001b[1m1/1\u001b[0m \u001b[32m━━━━━━━━━━━━━━━━━━━━\u001b[0m\u001b[37m\u001b[0m \u001b[1m0s\u001b[0m 66ms/step\n",
      "\u001b[1m1/1\u001b[0m \u001b[32m━━━━━━━━━━━━━━━━━━━━\u001b[0m\u001b[37m\u001b[0m \u001b[1m0s\u001b[0m 50ms/step\n",
      "\u001b[1m1/1\u001b[0m \u001b[32m━━━━━━━━━━━━━━━━━━━━\u001b[0m\u001b[37m\u001b[0m \u001b[1m0s\u001b[0m 54ms/step\n",
      "\u001b[1m1/1\u001b[0m \u001b[32m━━━━━━━━━━━━━━━━━━━━\u001b[0m\u001b[37m\u001b[0m \u001b[1m0s\u001b[0m 53ms/step\n",
      "\u001b[1m1/1\u001b[0m \u001b[32m━━━━━━━━━━━━━━━━━━━━\u001b[0m\u001b[37m\u001b[0m \u001b[1m0s\u001b[0m 54ms/step\n",
      "\u001b[1m1/1\u001b[0m \u001b[32m━━━━━━━━━━━━━━━━━━━━\u001b[0m\u001b[37m\u001b[0m \u001b[1m0s\u001b[0m 54ms/step\n",
      "\u001b[1m1/1\u001b[0m \u001b[32m━━━━━━━━━━━━━━━━━━━━\u001b[0m\u001b[37m\u001b[0m \u001b[1m0s\u001b[0m 54ms/step\n",
      "\u001b[1m1/1\u001b[0m \u001b[32m━━━━━━━━━━━━━━━━━━━━\u001b[0m\u001b[37m\u001b[0m \u001b[1m0s\u001b[0m 67ms/step\n",
      "\u001b[1m1/1\u001b[0m \u001b[32m━━━━━━━━━━━━━━━━━━━━\u001b[0m\u001b[37m\u001b[0m \u001b[1m0s\u001b[0m 53ms/step\n",
      "\u001b[1m1/1\u001b[0m \u001b[32m━━━━━━━━━━━━━━━━━━━━\u001b[0m\u001b[37m\u001b[0m \u001b[1m0s\u001b[0m 53ms/step\n",
      "\u001b[1m1/1\u001b[0m \u001b[32m━━━━━━━━━━━━━━━━━━━━\u001b[0m\u001b[37m\u001b[0m \u001b[1m0s\u001b[0m 67ms/step\n",
      "\u001b[1m1/1\u001b[0m \u001b[32m━━━━━━━━━━━━━━━━━━━━\u001b[0m\u001b[37m\u001b[0m \u001b[1m0s\u001b[0m 54ms/step\n",
      "\u001b[1m1/1\u001b[0m \u001b[32m━━━━━━━━━━━━━━━━━━━━\u001b[0m\u001b[37m\u001b[0m \u001b[1m0s\u001b[0m 55ms/step\n",
      "\u001b[1m1/1\u001b[0m \u001b[32m━━━━━━━━━━━━━━━━━━━━\u001b[0m\u001b[37m\u001b[0m \u001b[1m0s\u001b[0m 60ms/step\n",
      "\u001b[1m1/1\u001b[0m \u001b[32m━━━━━━━━━━━━━━━━━━━━\u001b[0m\u001b[37m\u001b[0m \u001b[1m0s\u001b[0m 54ms/step\n",
      "\u001b[1m1/1\u001b[0m \u001b[32m━━━━━━━━━━━━━━━━━━━━\u001b[0m\u001b[37m\u001b[0m \u001b[1m0s\u001b[0m 54ms/step\n",
      "\u001b[1m1/1\u001b[0m \u001b[32m━━━━━━━━━━━━━━━━━━━━\u001b[0m\u001b[37m\u001b[0m \u001b[1m0s\u001b[0m 54ms/step\n",
      "\u001b[1m1/1\u001b[0m \u001b[32m━━━━━━━━━━━━━━━━━━━━\u001b[0m\u001b[37m\u001b[0m \u001b[1m0s\u001b[0m 67ms/step\n",
      "\u001b[1m1/1\u001b[0m \u001b[32m━━━━━━━━━━━━━━━━━━━━\u001b[0m\u001b[37m\u001b[0m \u001b[1m0s\u001b[0m 54ms/step\n",
      "\u001b[1m1/1\u001b[0m \u001b[32m━━━━━━━━━━━━━━━━━━━━\u001b[0m\u001b[37m\u001b[0m \u001b[1m0s\u001b[0m 54ms/step\n",
      "\u001b[1m1/1\u001b[0m \u001b[32m━━━━━━━━━━━━━━━━━━━━\u001b[0m\u001b[37m\u001b[0m \u001b[1m0s\u001b[0m 54ms/step\n",
      "\u001b[1m1/1\u001b[0m \u001b[32m━━━━━━━━━━━━━━━━━━━━\u001b[0m\u001b[37m\u001b[0m \u001b[1m0s\u001b[0m 54ms/step\n",
      "\u001b[1m1/1\u001b[0m \u001b[32m━━━━━━━━━━━━━━━━━━━━\u001b[0m\u001b[37m\u001b[0m \u001b[1m0s\u001b[0m 47ms/step\n",
      "\u001b[1m1/1\u001b[0m \u001b[32m━━━━━━━━━━━━━━━━━━━━\u001b[0m\u001b[37m\u001b[0m \u001b[1m0s\u001b[0m 46ms/step\n",
      "\u001b[1m1/1\u001b[0m \u001b[32m━━━━━━━━━━━━━━━━━━━━\u001b[0m\u001b[37m\u001b[0m \u001b[1m0s\u001b[0m 46ms/step\n",
      "\u001b[1m1/1\u001b[0m \u001b[32m━━━━━━━━━━━━━━━━━━━━\u001b[0m\u001b[37m\u001b[0m \u001b[1m0s\u001b[0m 54ms/step\n",
      "\u001b[1m1/1\u001b[0m \u001b[32m━━━━━━━━━━━━━━━━━━━━\u001b[0m\u001b[37m\u001b[0m \u001b[1m0s\u001b[0m 54ms/step\n",
      "\u001b[1m1/1\u001b[0m \u001b[32m━━━━━━━━━━━━━━━━━━━━\u001b[0m\u001b[37m\u001b[0m \u001b[1m0s\u001b[0m 46ms/step\n",
      "\u001b[1m1/1\u001b[0m \u001b[32m━━━━━━━━━━━━━━━━━━━━\u001b[0m\u001b[37m\u001b[0m \u001b[1m0s\u001b[0m 54ms/step\n",
      "\u001b[1m1/1\u001b[0m \u001b[32m━━━━━━━━━━━━━━━━━━━━\u001b[0m\u001b[37m\u001b[0m \u001b[1m0s\u001b[0m 54ms/step\n",
      "\u001b[1m1/1\u001b[0m \u001b[32m━━━━━━━━━━━━━━━━━━━━\u001b[0m\u001b[37m\u001b[0m \u001b[1m0s\u001b[0m 67ms/step\n",
      "\u001b[1m1/1\u001b[0m \u001b[32m━━━━━━━━━━━━━━━━━━━━\u001b[0m\u001b[37m\u001b[0m \u001b[1m0s\u001b[0m 57ms/step\n",
      "\u001b[1m1/1\u001b[0m \u001b[32m━━━━━━━━━━━━━━━━━━━━\u001b[0m\u001b[37m\u001b[0m \u001b[1m0s\u001b[0m 67ms/step\n",
      "\u001b[1m1/1\u001b[0m \u001b[32m━━━━━━━━━━━━━━━━━━━━\u001b[0m\u001b[37m\u001b[0m \u001b[1m0s\u001b[0m 54ms/step\n",
      "\u001b[1m1/1\u001b[0m \u001b[32m━━━━━━━━━━━━━━━━━━━━\u001b[0m\u001b[37m\u001b[0m \u001b[1m0s\u001b[0m 68ms/step\n",
      "\u001b[1m1/1\u001b[0m \u001b[32m━━━━━━━━━━━━━━━━━━━━\u001b[0m\u001b[37m\u001b[0m \u001b[1m0s\u001b[0m 66ms/step\n",
      "\u001b[1m1/1\u001b[0m \u001b[32m━━━━━━━━━━━━━━━━━━━━\u001b[0m\u001b[37m\u001b[0m \u001b[1m0s\u001b[0m 49ms/step\n",
      "\u001b[1m1/1\u001b[0m \u001b[32m━━━━━━━━━━━━━━━━━━━━\u001b[0m\u001b[37m\u001b[0m \u001b[1m0s\u001b[0m 54ms/step\n",
      "\u001b[1m1/1\u001b[0m \u001b[32m━━━━━━━━━━━━━━━━━━━━\u001b[0m\u001b[37m\u001b[0m \u001b[1m0s\u001b[0m 67ms/step\n",
      "\u001b[1m1/1\u001b[0m \u001b[32m━━━━━━━━━━━━━━━━━━━━\u001b[0m\u001b[37m\u001b[0m \u001b[1m0s\u001b[0m 67ms/step\n",
      "\u001b[1m1/1\u001b[0m \u001b[32m━━━━━━━━━━━━━━━━━━━━\u001b[0m\u001b[37m\u001b[0m \u001b[1m0s\u001b[0m 54ms/step\n",
      "\u001b[1m1/1\u001b[0m \u001b[32m━━━━━━━━━━━━━━━━━━━━\u001b[0m\u001b[37m\u001b[0m \u001b[1m0s\u001b[0m 54ms/step\n",
      "\u001b[1m1/1\u001b[0m \u001b[32m━━━━━━━━━━━━━━━━━━━━\u001b[0m\u001b[37m\u001b[0m \u001b[1m0s\u001b[0m 54ms/step\n",
      "\u001b[1m1/1\u001b[0m \u001b[32m━━━━━━━━━━━━━━━━━━━━\u001b[0m\u001b[37m\u001b[0m \u001b[1m0s\u001b[0m 67ms/step\n",
      "\u001b[1m1/1\u001b[0m \u001b[32m━━━━━━━━━━━━━━━━━━━━\u001b[0m\u001b[37m\u001b[0m \u001b[1m0s\u001b[0m 54ms/step\n",
      "\u001b[1m1/1\u001b[0m \u001b[32m━━━━━━━━━━━━━━━━━━━━\u001b[0m\u001b[37m\u001b[0m \u001b[1m0s\u001b[0m 52ms/step\n",
      "\u001b[1m1/1\u001b[0m \u001b[32m━━━━━━━━━━━━━━━━━━━━\u001b[0m\u001b[37m\u001b[0m \u001b[1m0s\u001b[0m 67ms/step\n",
      "\u001b[1m1/1\u001b[0m \u001b[32m━━━━━━━━━━━━━━━━━━━━\u001b[0m\u001b[37m\u001b[0m \u001b[1m0s\u001b[0m 54ms/step\n",
      "\u001b[1m1/1\u001b[0m \u001b[32m━━━━━━━━━━━━━━━━━━━━\u001b[0m\u001b[37m\u001b[0m \u001b[1m0s\u001b[0m 54ms/step\n",
      "\u001b[1m1/1\u001b[0m \u001b[32m━━━━━━━━━━━━━━━━━━━━\u001b[0m\u001b[37m\u001b[0m \u001b[1m0s\u001b[0m 54ms/step\n",
      "\u001b[1m1/1\u001b[0m \u001b[32m━━━━━━━━━━━━━━━━━━━━\u001b[0m\u001b[37m\u001b[0m \u001b[1m0s\u001b[0m 54ms/step\n",
      "\u001b[1m1/1\u001b[0m \u001b[32m━━━━━━━━━━━━━━━━━━━━\u001b[0m\u001b[37m\u001b[0m \u001b[1m0s\u001b[0m 54ms/step\n",
      "\u001b[1m1/1\u001b[0m \u001b[32m━━━━━━━━━━━━━━━━━━━━\u001b[0m\u001b[37m\u001b[0m \u001b[1m0s\u001b[0m 54ms/step\n",
      "\u001b[1m1/1\u001b[0m \u001b[32m━━━━━━━━━━━━━━━━━━━━\u001b[0m\u001b[37m\u001b[0m \u001b[1m0s\u001b[0m 48ms/step\n",
      "\u001b[1m1/1\u001b[0m \u001b[32m━━━━━━━━━━━━━━━━━━━━\u001b[0m\u001b[37m\u001b[0m \u001b[1m0s\u001b[0m 53ms/step\n",
      "\u001b[1m1/1\u001b[0m \u001b[32m━━━━━━━━━━━━━━━━━━━━\u001b[0m\u001b[37m\u001b[0m \u001b[1m0s\u001b[0m 54ms/step\n",
      "\u001b[1m1/1\u001b[0m \u001b[32m━━━━━━━━━━━━━━━━━━━━\u001b[0m\u001b[37m\u001b[0m \u001b[1m0s\u001b[0m 46ms/step\n",
      "\u001b[1m1/1\u001b[0m \u001b[32m━━━━━━━━━━━━━━━━━━━━\u001b[0m\u001b[37m\u001b[0m \u001b[1m0s\u001b[0m 54ms/step\n",
      "\u001b[1m1/1\u001b[0m \u001b[32m━━━━━━━━━━━━━━━━━━━━\u001b[0m\u001b[37m\u001b[0m \u001b[1m0s\u001b[0m 54ms/step\n",
      "\u001b[1m1/1\u001b[0m \u001b[32m━━━━━━━━━━━━━━━━━━━━\u001b[0m\u001b[37m\u001b[0m \u001b[1m0s\u001b[0m 54ms/step\n",
      "\u001b[1m1/1\u001b[0m \u001b[32m━━━━━━━━━━━━━━━━━━━━\u001b[0m\u001b[37m\u001b[0m \u001b[1m0s\u001b[0m 65ms/step\n",
      "\u001b[1m1/1\u001b[0m \u001b[32m━━━━━━━━━━━━━━━━━━━━\u001b[0m\u001b[37m\u001b[0m \u001b[1m0s\u001b[0m 60ms/step\n",
      "\u001b[1m1/1\u001b[0m \u001b[32m━━━━━━━━━━━━━━━━━━━━\u001b[0m\u001b[37m\u001b[0m \u001b[1m0s\u001b[0m 60ms/step\n",
      "\u001b[1m1/1\u001b[0m \u001b[32m━━━━━━━━━━━━━━━━━━━━\u001b[0m\u001b[37m\u001b[0m \u001b[1m0s\u001b[0m 66ms/step\n",
      "\u001b[1m1/1\u001b[0m \u001b[32m━━━━━━━━━━━━━━━━━━━━\u001b[0m\u001b[37m\u001b[0m \u001b[1m0s\u001b[0m 63ms/step\n",
      "\u001b[1m1/1\u001b[0m \u001b[32m━━━━━━━━━━━━━━━━━━━━\u001b[0m\u001b[37m\u001b[0m \u001b[1m0s\u001b[0m 55ms/step\n",
      "\u001b[1m1/1\u001b[0m \u001b[32m━━━━━━━━━━━━━━━━━━━━\u001b[0m\u001b[37m\u001b[0m \u001b[1m0s\u001b[0m 54ms/step\n",
      "\u001b[1m1/1\u001b[0m \u001b[32m━━━━━━━━━━━━━━━━━━━━\u001b[0m\u001b[37m\u001b[0m \u001b[1m0s\u001b[0m 62ms/step\n",
      "\u001b[1m1/1\u001b[0m \u001b[32m━━━━━━━━━━━━━━━━━━━━\u001b[0m\u001b[37m\u001b[0m \u001b[1m0s\u001b[0m 54ms/step\n",
      "\u001b[1m1/1\u001b[0m \u001b[32m━━━━━━━━━━━━━━━━━━━━\u001b[0m\u001b[37m\u001b[0m \u001b[1m0s\u001b[0m 54ms/step\n",
      "\u001b[1m1/1\u001b[0m \u001b[32m━━━━━━━━━━━━━━━━━━━━\u001b[0m\u001b[37m\u001b[0m \u001b[1m0s\u001b[0m 67ms/step\n",
      "\u001b[1m1/1\u001b[0m \u001b[32m━━━━━━━━━━━━━━━━━━━━\u001b[0m\u001b[37m\u001b[0m \u001b[1m0s\u001b[0m 67ms/step\n",
      "\u001b[1m1/1\u001b[0m \u001b[32m━━━━━━━━━━━━━━━━━━━━\u001b[0m\u001b[37m\u001b[0m \u001b[1m0s\u001b[0m 54ms/step\n",
      "\u001b[1m1/1\u001b[0m \u001b[32m━━━━━━━━━━━━━━━━━━━━\u001b[0m\u001b[37m\u001b[0m \u001b[1m0s\u001b[0m 67ms/step\n",
      "\u001b[1m1/1\u001b[0m \u001b[32m━━━━━━━━━━━━━━━━━━━━\u001b[0m\u001b[37m\u001b[0m \u001b[1m0s\u001b[0m 54ms/step\n",
      "\u001b[1m1/1\u001b[0m \u001b[32m━━━━━━━━━━━━━━━━━━━━\u001b[0m\u001b[37m\u001b[0m \u001b[1m0s\u001b[0m 54ms/step\n",
      "\u001b[1m1/1\u001b[0m \u001b[32m━━━━━━━━━━━━━━━━━━━━\u001b[0m\u001b[37m\u001b[0m \u001b[1m0s\u001b[0m 54ms/step\n",
      "\u001b[1m1/1\u001b[0m \u001b[32m━━━━━━━━━━━━━━━━━━━━\u001b[0m\u001b[37m\u001b[0m \u001b[1m0s\u001b[0m 54ms/step\n",
      "\u001b[1m1/1\u001b[0m \u001b[32m━━━━━━━━━━━━━━━━━━━━\u001b[0m\u001b[37m\u001b[0m \u001b[1m0s\u001b[0m 54ms/step\n",
      "\u001b[1m1/1\u001b[0m \u001b[32m━━━━━━━━━━━━━━━━━━━━\u001b[0m\u001b[37m\u001b[0m \u001b[1m0s\u001b[0m 54ms/step\n",
      "\u001b[1m1/1\u001b[0m \u001b[32m━━━━━━━━━━━━━━━━━━━━\u001b[0m\u001b[37m\u001b[0m \u001b[1m0s\u001b[0m 54ms/step\n",
      "\u001b[1m1/1\u001b[0m \u001b[32m━━━━━━━━━━━━━━━━━━━━\u001b[0m\u001b[37m\u001b[0m \u001b[1m0s\u001b[0m 54ms/step\n",
      "\u001b[1m1/1\u001b[0m \u001b[32m━━━━━━━━━━━━━━━━━━━━\u001b[0m\u001b[37m\u001b[0m \u001b[1m0s\u001b[0m 54ms/step\n",
      "\u001b[1m1/1\u001b[0m \u001b[32m━━━━━━━━━━━━━━━━━━━━\u001b[0m\u001b[37m\u001b[0m \u001b[1m0s\u001b[0m 67ms/step\n",
      "\u001b[1m1/1\u001b[0m \u001b[32m━━━━━━━━━━━━━━━━━━━━\u001b[0m\u001b[37m\u001b[0m \u001b[1m0s\u001b[0m 54ms/step\n",
      "\u001b[1m1/1\u001b[0m \u001b[32m━━━━━━━━━━━━━━━━━━━━\u001b[0m\u001b[37m\u001b[0m \u001b[1m0s\u001b[0m 54ms/step\n",
      "\u001b[1m1/1\u001b[0m \u001b[32m━━━━━━━━━━━━━━━━━━━━\u001b[0m\u001b[37m\u001b[0m \u001b[1m0s\u001b[0m 54ms/step\n",
      "\u001b[1m1/1\u001b[0m \u001b[32m━━━━━━━━━━━━━━━━━━━━\u001b[0m\u001b[37m\u001b[0m \u001b[1m0s\u001b[0m 54ms/step\n",
      "\u001b[1m1/1\u001b[0m \u001b[32m━━━━━━━━━━━━━━━━━━━━\u001b[0m\u001b[37m\u001b[0m \u001b[1m0s\u001b[0m 54ms/step\n",
      "\u001b[1m1/1\u001b[0m \u001b[32m━━━━━━━━━━━━━━━━━━━━\u001b[0m\u001b[37m\u001b[0m \u001b[1m0s\u001b[0m 53ms/step\n",
      "\u001b[1m1/1\u001b[0m \u001b[32m━━━━━━━━━━━━━━━━━━━━\u001b[0m\u001b[37m\u001b[0m \u001b[1m0s\u001b[0m 54ms/step\n",
      "\u001b[1m1/1\u001b[0m \u001b[32m━━━━━━━━━━━━━━━━━━━━\u001b[0m\u001b[37m\u001b[0m \u001b[1m0s\u001b[0m 53ms/step\n",
      "\u001b[1m1/1\u001b[0m \u001b[32m━━━━━━━━━━━━━━━━━━━━\u001b[0m\u001b[37m\u001b[0m \u001b[1m0s\u001b[0m 66ms/step\n",
      "\u001b[1m1/1\u001b[0m \u001b[32m━━━━━━━━━━━━━━━━━━━━\u001b[0m\u001b[37m\u001b[0m \u001b[1m0s\u001b[0m 67ms/step\n",
      "\u001b[1m1/1\u001b[0m \u001b[32m━━━━━━━━━━━━━━━━━━━━\u001b[0m\u001b[37m\u001b[0m \u001b[1m0s\u001b[0m 54ms/step\n",
      "\u001b[1m1/1\u001b[0m \u001b[32m━━━━━━━━━━━━━━━━━━━━\u001b[0m\u001b[37m\u001b[0m \u001b[1m0s\u001b[0m 66ms/step\n",
      "\u001b[1m1/1\u001b[0m \u001b[32m━━━━━━━━━━━━━━━━━━━━\u001b[0m\u001b[37m\u001b[0m \u001b[1m0s\u001b[0m 53ms/step\n",
      "\u001b[1m1/1\u001b[0m \u001b[32m━━━━━━━━━━━━━━━━━━━━\u001b[0m\u001b[37m\u001b[0m \u001b[1m0s\u001b[0m 53ms/step\n",
      "\u001b[1m1/1\u001b[0m \u001b[32m━━━━━━━━━━━━━━━━━━━━\u001b[0m\u001b[37m\u001b[0m \u001b[1m0s\u001b[0m 54ms/step\n",
      "\u001b[1m1/1\u001b[0m \u001b[32m━━━━━━━━━━━━━━━━━━━━\u001b[0m\u001b[37m\u001b[0m \u001b[1m0s\u001b[0m 54ms/step\n",
      "\u001b[1m1/1\u001b[0m \u001b[32m━━━━━━━━━━━━━━━━━━━━\u001b[0m\u001b[37m\u001b[0m \u001b[1m0s\u001b[0m 53ms/step\n",
      "\u001b[1m1/1\u001b[0m \u001b[32m━━━━━━━━━━━━━━━━━━━━\u001b[0m\u001b[37m\u001b[0m \u001b[1m0s\u001b[0m 54ms/step\n",
      "\u001b[1m1/1\u001b[0m \u001b[32m━━━━━━━━━━━━━━━━━━━━\u001b[0m\u001b[37m\u001b[0m \u001b[1m0s\u001b[0m 54ms/step\n",
      "\u001b[1m1/1\u001b[0m \u001b[32m━━━━━━━━━━━━━━━━━━━━\u001b[0m\u001b[37m\u001b[0m \u001b[1m0s\u001b[0m 54ms/step\n",
      "\u001b[1m1/1\u001b[0m \u001b[32m━━━━━━━━━━━━━━━━━━━━\u001b[0m\u001b[37m\u001b[0m \u001b[1m0s\u001b[0m 67ms/step\n",
      "\u001b[1m1/1\u001b[0m \u001b[32m━━━━━━━━━━━━━━━━━━━━\u001b[0m\u001b[37m\u001b[0m \u001b[1m0s\u001b[0m 54ms/step\n",
      "\u001b[1m1/1\u001b[0m \u001b[32m━━━━━━━━━━━━━━━━━━━━\u001b[0m\u001b[37m\u001b[0m \u001b[1m0s\u001b[0m 54ms/step\n",
      "\u001b[1m1/1\u001b[0m \u001b[32m━━━━━━━━━━━━━━━━━━━━\u001b[0m\u001b[37m\u001b[0m \u001b[1m0s\u001b[0m 54ms/step\n",
      "\u001b[1m1/1\u001b[0m \u001b[32m━━━━━━━━━━━━━━━━━━━━\u001b[0m\u001b[37m\u001b[0m \u001b[1m0s\u001b[0m 66ms/step\n",
      "\u001b[1m1/1\u001b[0m \u001b[32m━━━━━━━━━━━━━━━━━━━━\u001b[0m\u001b[37m\u001b[0m \u001b[1m0s\u001b[0m 67ms/step\n",
      "\u001b[1m1/1\u001b[0m \u001b[32m━━━━━━━━━━━━━━━━━━━━\u001b[0m\u001b[37m\u001b[0m \u001b[1m0s\u001b[0m 54ms/step\n",
      "\u001b[1m1/1\u001b[0m \u001b[32m━━━━━━━━━━━━━━━━━━━━\u001b[0m\u001b[37m\u001b[0m \u001b[1m0s\u001b[0m 53ms/step\n",
      "\u001b[1m1/1\u001b[0m \u001b[32m━━━━━━━━━━━━━━━━━━━━\u001b[0m\u001b[37m\u001b[0m \u001b[1m0s\u001b[0m 54ms/step\n",
      "\u001b[1m1/1\u001b[0m \u001b[32m━━━━━━━━━━━━━━━━━━━━\u001b[0m\u001b[37m\u001b[0m \u001b[1m0s\u001b[0m 54ms/step\n",
      "\u001b[1m1/1\u001b[0m \u001b[32m━━━━━━━━━━━━━━━━━━━━\u001b[0m\u001b[37m\u001b[0m \u001b[1m0s\u001b[0m 54ms/step\n",
      "\u001b[1m1/1\u001b[0m \u001b[32m━━━━━━━━━━━━━━━━━━━━\u001b[0m\u001b[37m\u001b[0m \u001b[1m0s\u001b[0m 67ms/step\n",
      "\u001b[1m1/1\u001b[0m \u001b[32m━━━━━━━━━━━━━━━━━━━━\u001b[0m\u001b[37m\u001b[0m \u001b[1m0s\u001b[0m 40ms/step\n",
      "\u001b[1m1/1\u001b[0m \u001b[32m━━━━━━━━━━━━━━━━━━━━\u001b[0m\u001b[37m\u001b[0m \u001b[1m0s\u001b[0m 67ms/step\n",
      "\u001b[1m1/1\u001b[0m \u001b[32m━━━━━━━━━━━━━━━━━━━━\u001b[0m\u001b[37m\u001b[0m \u001b[1m0s\u001b[0m 66ms/step\n",
      "\u001b[1m1/1\u001b[0m \u001b[32m━━━━━━━━━━━━━━━━━━━━\u001b[0m\u001b[37m\u001b[0m \u001b[1m0s\u001b[0m 54ms/step\n",
      "\u001b[1m1/1\u001b[0m \u001b[32m━━━━━━━━━━━━━━━━━━━━\u001b[0m\u001b[37m\u001b[0m \u001b[1m0s\u001b[0m 54ms/step\n",
      "\u001b[1m1/1\u001b[0m \u001b[32m━━━━━━━━━━━━━━━━━━━━\u001b[0m\u001b[37m\u001b[0m \u001b[1m0s\u001b[0m 53ms/step\n",
      "\u001b[1m1/1\u001b[0m \u001b[32m━━━━━━━━━━━━━━━━━━━━\u001b[0m\u001b[37m\u001b[0m \u001b[1m0s\u001b[0m 54ms/step\n",
      "\u001b[1m1/1\u001b[0m \u001b[32m━━━━━━━━━━━━━━━━━━━━\u001b[0m\u001b[37m\u001b[0m \u001b[1m0s\u001b[0m 54ms/step\n",
      "\u001b[1m1/1\u001b[0m \u001b[32m━━━━━━━━━━━━━━━━━━━━\u001b[0m\u001b[37m\u001b[0m \u001b[1m0s\u001b[0m 54ms/step\n",
      "\u001b[1m1/1\u001b[0m \u001b[32m━━━━━━━━━━━━━━━━━━━━\u001b[0m\u001b[37m\u001b[0m \u001b[1m0s\u001b[0m 53ms/step\n",
      "\u001b[1m1/1\u001b[0m \u001b[32m━━━━━━━━━━━━━━━━━━━━\u001b[0m\u001b[37m\u001b[0m \u001b[1m0s\u001b[0m 67ms/step\n",
      "\u001b[1m1/1\u001b[0m \u001b[32m━━━━━━━━━━━━━━━━━━━━\u001b[0m\u001b[37m\u001b[0m \u001b[1m0s\u001b[0m 54ms/step\n",
      "\u001b[1m1/1\u001b[0m \u001b[32m━━━━━━━━━━━━━━━━━━━━\u001b[0m\u001b[37m\u001b[0m \u001b[1m0s\u001b[0m 53ms/step\n",
      "\u001b[1m1/1\u001b[0m \u001b[32m━━━━━━━━━━━━━━━━━━━━\u001b[0m\u001b[37m\u001b[0m \u001b[1m0s\u001b[0m 54ms/step\n",
      "\u001b[1m1/1\u001b[0m \u001b[32m━━━━━━━━━━━━━━━━━━━━\u001b[0m\u001b[37m\u001b[0m \u001b[1m0s\u001b[0m 54ms/step\n",
      "\u001b[1m1/1\u001b[0m \u001b[32m━━━━━━━━━━━━━━━━━━━━\u001b[0m\u001b[37m\u001b[0m \u001b[1m0s\u001b[0m 52ms/step\n",
      "\u001b[1m1/1\u001b[0m \u001b[32m━━━━━━━━━━━━━━━━━━━━\u001b[0m\u001b[37m\u001b[0m \u001b[1m0s\u001b[0m 53ms/step\n",
      "\u001b[1m1/1\u001b[0m \u001b[32m━━━━━━━━━━━━━━━━━━━━\u001b[0m\u001b[37m\u001b[0m \u001b[1m0s\u001b[0m 54ms/step\n",
      "\u001b[1m1/1\u001b[0m \u001b[32m━━━━━━━━━━━━━━━━━━━━\u001b[0m\u001b[37m\u001b[0m \u001b[1m0s\u001b[0m 54ms/step\n",
      "\u001b[1m1/1\u001b[0m \u001b[32m━━━━━━━━━━━━━━━━━━━━\u001b[0m\u001b[37m\u001b[0m \u001b[1m0s\u001b[0m 54ms/step\n",
      "\u001b[1m1/1\u001b[0m \u001b[32m━━━━━━━━━━━━━━━━━━━━\u001b[0m\u001b[37m\u001b[0m \u001b[1m0s\u001b[0m 53ms/step\n",
      "\u001b[1m1/1\u001b[0m \u001b[32m━━━━━━━━━━━━━━━━━━━━\u001b[0m\u001b[37m\u001b[0m \u001b[1m0s\u001b[0m 54ms/step\n",
      "\u001b[1m1/1\u001b[0m \u001b[32m━━━━━━━━━━━━━━━━━━━━\u001b[0m\u001b[37m\u001b[0m \u001b[1m0s\u001b[0m 67ms/step\n",
      "\u001b[1m1/1\u001b[0m \u001b[32m━━━━━━━━━━━━━━━━━━━━\u001b[0m\u001b[37m\u001b[0m \u001b[1m0s\u001b[0m 54ms/step\n",
      "\u001b[1m1/1\u001b[0m \u001b[32m━━━━━━━━━━━━━━━━━━━━\u001b[0m\u001b[37m\u001b[0m \u001b[1m0s\u001b[0m 54ms/step\n",
      "\u001b[1m1/1\u001b[0m \u001b[32m━━━━━━━━━━━━━━━━━━━━\u001b[0m\u001b[37m\u001b[0m \u001b[1m0s\u001b[0m 54ms/step\n",
      "\u001b[1m1/1\u001b[0m \u001b[32m━━━━━━━━━━━━━━━━━━━━\u001b[0m\u001b[37m\u001b[0m \u001b[1m0s\u001b[0m 66ms/step\n",
      "\u001b[1m1/1\u001b[0m \u001b[32m━━━━━━━━━━━━━━━━━━━━\u001b[0m\u001b[37m\u001b[0m \u001b[1m0s\u001b[0m 40ms/step\n",
      "\u001b[1m1/1\u001b[0m \u001b[32m━━━━━━━━━━━━━━━━━━━━\u001b[0m\u001b[37m\u001b[0m \u001b[1m0s\u001b[0m 53ms/step\n",
      "\u001b[1m1/1\u001b[0m \u001b[32m━━━━━━━━━━━━━━━━━━━━\u001b[0m\u001b[37m\u001b[0m \u001b[1m0s\u001b[0m 54ms/step\n",
      "\u001b[1m1/1\u001b[0m \u001b[32m━━━━━━━━━━━━━━━━━━━━\u001b[0m\u001b[37m\u001b[0m \u001b[1m0s\u001b[0m 54ms/step\n",
      "\u001b[1m1/1\u001b[0m \u001b[32m━━━━━━━━━━━━━━━━━━━━\u001b[0m\u001b[37m\u001b[0m \u001b[1m0s\u001b[0m 54ms/step\n",
      "\u001b[1m1/1\u001b[0m \u001b[32m━━━━━━━━━━━━━━━━━━━━\u001b[0m\u001b[37m\u001b[0m \u001b[1m0s\u001b[0m 67ms/step\n",
      "\u001b[1m1/1\u001b[0m \u001b[32m━━━━━━━━━━━━━━━━━━━━\u001b[0m\u001b[37m\u001b[0m \u001b[1m0s\u001b[0m 54ms/step\n",
      "\u001b[1m1/1\u001b[0m \u001b[32m━━━━━━━━━━━━━━━━━━━━\u001b[0m\u001b[37m\u001b[0m \u001b[1m0s\u001b[0m 54ms/step\n",
      "\u001b[1m1/1\u001b[0m \u001b[32m━━━━━━━━━━━━━━━━━━━━\u001b[0m\u001b[37m\u001b[0m \u001b[1m0s\u001b[0m 53ms/step\n",
      "\u001b[1m1/1\u001b[0m \u001b[32m━━━━━━━━━━━━━━━━━━━━\u001b[0m\u001b[37m\u001b[0m \u001b[1m0s\u001b[0m 53ms/step\n",
      "\u001b[1m1/1\u001b[0m \u001b[32m━━━━━━━━━━━━━━━━━━━━\u001b[0m\u001b[37m\u001b[0m \u001b[1m0s\u001b[0m 54ms/step\n",
      "\u001b[1m1/1\u001b[0m \u001b[32m━━━━━━━━━━━━━━━━━━━━\u001b[0m\u001b[37m\u001b[0m \u001b[1m0s\u001b[0m 54ms/step\n",
      "\u001b[1m1/1\u001b[0m \u001b[32m━━━━━━━━━━━━━━━━━━━━\u001b[0m\u001b[37m\u001b[0m \u001b[1m0s\u001b[0m 54ms/step\n",
      "\u001b[1m1/1\u001b[0m \u001b[32m━━━━━━━━━━━━━━━━━━━━\u001b[0m\u001b[37m\u001b[0m \u001b[1m0s\u001b[0m 67ms/step\n",
      "\u001b[1m1/1\u001b[0m \u001b[32m━━━━━━━━━━━━━━━━━━━━\u001b[0m\u001b[37m\u001b[0m \u001b[1m0s\u001b[0m 55ms/step\n",
      "\u001b[1m1/1\u001b[0m \u001b[32m━━━━━━━━━━━━━━━━━━━━\u001b[0m\u001b[37m\u001b[0m \u001b[1m0s\u001b[0m 53ms/step\n",
      "\u001b[1m1/1\u001b[0m \u001b[32m━━━━━━━━━━━━━━━━━━━━\u001b[0m\u001b[37m\u001b[0m \u001b[1m0s\u001b[0m 67ms/step\n",
      "\u001b[1m1/1\u001b[0m \u001b[32m━━━━━━━━━━━━━━━━━━━━\u001b[0m\u001b[37m\u001b[0m \u001b[1m0s\u001b[0m 54ms/step\n",
      "\u001b[1m1/1\u001b[0m \u001b[32m━━━━━━━━━━━━━━━━━━━━\u001b[0m\u001b[37m\u001b[0m \u001b[1m0s\u001b[0m 54ms/step\n",
      "\u001b[1m1/1\u001b[0m \u001b[32m━━━━━━━━━━━━━━━━━━━━\u001b[0m\u001b[37m\u001b[0m \u001b[1m0s\u001b[0m 53ms/step\n",
      "\u001b[1m1/1\u001b[0m \u001b[32m━━━━━━━━━━━━━━━━━━━━\u001b[0m\u001b[37m\u001b[0m \u001b[1m0s\u001b[0m 54ms/step\n",
      "\u001b[1m1/1\u001b[0m \u001b[32m━━━━━━━━━━━━━━━━━━━━\u001b[0m\u001b[37m\u001b[0m \u001b[1m0s\u001b[0m 54ms/step\n",
      "\u001b[1m1/1\u001b[0m \u001b[32m━━━━━━━━━━━━━━━━━━━━\u001b[0m\u001b[37m\u001b[0m \u001b[1m0s\u001b[0m 63ms/step\n",
      "\u001b[1m1/1\u001b[0m \u001b[32m━━━━━━━━━━━━━━━━━━━━\u001b[0m\u001b[37m\u001b[0m \u001b[1m0s\u001b[0m 46ms/step\n",
      "\u001b[1m1/1\u001b[0m \u001b[32m━━━━━━━━━━━━━━━━━━━━\u001b[0m\u001b[37m\u001b[0m \u001b[1m0s\u001b[0m 66ms/step\n",
      "\u001b[1m1/1\u001b[0m \u001b[32m━━━━━━━━━━━━━━━━━━━━\u001b[0m\u001b[37m\u001b[0m \u001b[1m0s\u001b[0m 54ms/step\n",
      "\u001b[1m1/1\u001b[0m \u001b[32m━━━━━━━━━━━━━━━━━━━━\u001b[0m\u001b[37m\u001b[0m \u001b[1m0s\u001b[0m 67ms/step\n",
      "\u001b[1m1/1\u001b[0m \u001b[32m━━━━━━━━━━━━━━━━━━━━\u001b[0m\u001b[37m\u001b[0m \u001b[1m0s\u001b[0m 64ms/step\n",
      "\u001b[1m1/1\u001b[0m \u001b[32m━━━━━━━━━━━━━━━━━━━━\u001b[0m\u001b[37m\u001b[0m \u001b[1m0s\u001b[0m 54ms/step\n",
      "\u001b[1m1/1\u001b[0m \u001b[32m━━━━━━━━━━━━━━━━━━━━\u001b[0m\u001b[37m\u001b[0m \u001b[1m0s\u001b[0m 54ms/step\n",
      "\u001b[1m1/1\u001b[0m \u001b[32m━━━━━━━━━━━━━━━━━━━━\u001b[0m\u001b[37m\u001b[0m \u001b[1m0s\u001b[0m 54ms/step\n",
      "\u001b[1m1/1\u001b[0m \u001b[32m━━━━━━━━━━━━━━━━━━━━\u001b[0m\u001b[37m\u001b[0m \u001b[1m0s\u001b[0m 66ms/step\n",
      "\u001b[1m1/1\u001b[0m \u001b[32m━━━━━━━━━━━━━━━━━━━━\u001b[0m\u001b[37m\u001b[0m \u001b[1m0s\u001b[0m 49ms/step\n",
      "\u001b[1m1/1\u001b[0m \u001b[32m━━━━━━━━━━━━━━━━━━━━\u001b[0m\u001b[37m\u001b[0m \u001b[1m0s\u001b[0m 67ms/step\n",
      "\u001b[1m1/1\u001b[0m \u001b[32m━━━━━━━━━━━━━━━━━━━━\u001b[0m\u001b[37m\u001b[0m \u001b[1m0s\u001b[0m 54ms/step\n",
      "\u001b[1m1/1\u001b[0m \u001b[32m━━━━━━━━━━━━━━━━━━━━\u001b[0m\u001b[37m\u001b[0m \u001b[1m0s\u001b[0m 66ms/step\n",
      "\u001b[1m1/1\u001b[0m \u001b[32m━━━━━━━━━━━━━━━━━━━━\u001b[0m\u001b[37m\u001b[0m \u001b[1m0s\u001b[0m 67ms/step\n",
      "\u001b[1m1/1\u001b[0m \u001b[32m━━━━━━━━━━━━━━━━━━━━\u001b[0m\u001b[37m\u001b[0m \u001b[1m0s\u001b[0m 67ms/step\n",
      "\u001b[1m1/1\u001b[0m \u001b[32m━━━━━━━━━━━━━━━━━━━━\u001b[0m\u001b[37m\u001b[0m \u001b[1m0s\u001b[0m 72ms/step\n",
      "\u001b[1m1/1\u001b[0m \u001b[32m━━━━━━━━━━━━━━━━━━━━\u001b[0m\u001b[37m\u001b[0m \u001b[1m0s\u001b[0m 52ms/step\n"
     ]
    }
   ],
   "source": [
    "# Memuat dan mengekstraksi fitur dari dataset\n",
    "features = []\n",
    "labels = []\n",
    "\n",
    "for label in os.listdir(base_dir):\n",
    "    label_folder = os.path.join(base_dir, label)\n",
    "    if os.path.isdir(label_folder):\n",
    "        for filename in os.listdir(label_folder):\n",
    "            image_path = os.path.join(label_folder, filename)\n",
    "            feature = extract_features(feature_extractor, image_path, img_size)\n",
    "            features.append(feature)\n",
    "            labels.append(label)\n",
    "\n",
    "features = np.array(features)\n",
    "labels = np.array(labels)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 7,
   "metadata": {},
   "outputs": [],
   "source": [
    "# Encode labels\n",
    "label_encoder = LabelEncoder()\n",
    "labels_encoded = label_encoder.fit_transform(labels)\n",
    "\n",
    "\n",
    "# Reduksi dimensi menggunakan PCA untuk mengurangi kompleksitas\n",
    "# fitur.\n",
    "\n",
    "pca = PCA(n_components= 50)  # pengurangan \n",
    "features_pca = pca.fit_transform(features)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 8,
   "metadata": {},
   "outputs": [],
   "source": [
    "# Membagi dataset menjadi data latih dan validasi\n",
    "train_split = 0.8\n",
    "X_train, X_valid, y_train, y_valid = train_test_split(features_pca, labels_encoded, \n",
    "                                                      train_size=train_split, shuffle=True, \n",
    "                                                      random_state=123)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 9,
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "Best parameters found:  {'metric': 'euclidean', 'n_neighbors': 3}\n"
     ]
    }
   ],
   "source": [
    "# menentukan parameter grid untuk knn\n",
    "param_grid = {\n",
    "    'n_neighbors': [3, 5, 7, 9, 11, 13],\n",
    "    'metric': ['euclidean', 'manhattan', 'minkowski']\n",
    "}\n",
    "\n",
    "# Melakukan Grid Search untuk mencari parameter terbaik\n",
    "knn = KNeighborsClassifier()\n",
    "grid_search = GridSearchCV(knn, param_grid, cv=5, scoring='accuracy', error_score='raise')\n",
    "grid_search.fit(X_train, y_train)\n",
    "\n",
    "print(\"Best parameters found: \", grid_search.best_params_)\n",
    "# print(\"Best cross-validation accuracy: {:.2f}\".format(grid_search.best_score_))"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 10,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/html": [
       "<style>#sk-container-id-1 {\n",
       "  /* Definition of color scheme common for light and dark mode */\n",
       "  --sklearn-color-text: black;\n",
       "  --sklearn-color-line: gray;\n",
       "  /* Definition of color scheme for unfitted estimators */\n",
       "  --sklearn-color-unfitted-level-0: #fff5e6;\n",
       "  --sklearn-color-unfitted-level-1: #f6e4d2;\n",
       "  --sklearn-color-unfitted-level-2: #ffe0b3;\n",
       "  --sklearn-color-unfitted-level-3: chocolate;\n",
       "  /* Definition of color scheme for fitted estimators */\n",
       "  --sklearn-color-fitted-level-0: #f0f8ff;\n",
       "  --sklearn-color-fitted-level-1: #d4ebff;\n",
       "  --sklearn-color-fitted-level-2: #b3dbfd;\n",
       "  --sklearn-color-fitted-level-3: cornflowerblue;\n",
       "\n",
       "  /* Specific color for light theme */\n",
       "  --sklearn-color-text-on-default-background: var(--sg-text-color, var(--theme-code-foreground, var(--jp-content-font-color1, black)));\n",
       "  --sklearn-color-background: var(--sg-background-color, var(--theme-background, var(--jp-layout-color0, white)));\n",
       "  --sklearn-color-border-box: var(--sg-text-color, var(--theme-code-foreground, var(--jp-content-font-color1, black)));\n",
       "  --sklearn-color-icon: #696969;\n",
       "\n",
       "  @media (prefers-color-scheme: dark) {\n",
       "    /* Redefinition of color scheme for dark theme */\n",
       "    --sklearn-color-text-on-default-background: var(--sg-text-color, var(--theme-code-foreground, var(--jp-content-font-color1, white)));\n",
       "    --sklearn-color-background: var(--sg-background-color, var(--theme-background, var(--jp-layout-color0, #111)));\n",
       "    --sklearn-color-border-box: var(--sg-text-color, var(--theme-code-foreground, var(--jp-content-font-color1, white)));\n",
       "    --sklearn-color-icon: #878787;\n",
       "  }\n",
       "}\n",
       "\n",
       "#sk-container-id-1 {\n",
       "  color: var(--sklearn-color-text);\n",
       "}\n",
       "\n",
       "#sk-container-id-1 pre {\n",
       "  padding: 0;\n",
       "}\n",
       "\n",
       "#sk-container-id-1 input.sk-hidden--visually {\n",
       "  border: 0;\n",
       "  clip: rect(1px 1px 1px 1px);\n",
       "  clip: rect(1px, 1px, 1px, 1px);\n",
       "  height: 1px;\n",
       "  margin: -1px;\n",
       "  overflow: hidden;\n",
       "  padding: 0;\n",
       "  position: absolute;\n",
       "  width: 1px;\n",
       "}\n",
       "\n",
       "#sk-container-id-1 div.sk-dashed-wrapped {\n",
       "  border: 1px dashed var(--sklearn-color-line);\n",
       "  margin: 0 0.4em 0.5em 0.4em;\n",
       "  box-sizing: border-box;\n",
       "  padding-bottom: 0.4em;\n",
       "  background-color: var(--sklearn-color-background);\n",
       "}\n",
       "\n",
       "#sk-container-id-1 div.sk-container {\n",
       "  /* jupyter's `normalize.less` sets `[hidden] { display: none; }`\n",
       "     but bootstrap.min.css set `[hidden] { display: none !important; }`\n",
       "     so we also need the `!important` here to be able to override the\n",
       "     default hidden behavior on the sphinx rendered scikit-learn.org.\n",
       "     See: https://github.com/scikit-learn/scikit-learn/issues/21755 */\n",
       "  display: inline-block !important;\n",
       "  position: relative;\n",
       "}\n",
       "\n",
       "#sk-container-id-1 div.sk-text-repr-fallback {\n",
       "  display: none;\n",
       "}\n",
       "\n",
       "div.sk-parallel-item,\n",
       "div.sk-serial,\n",
       "div.sk-item {\n",
       "  /* draw centered vertical line to link estimators */\n",
       "  background-image: linear-gradient(var(--sklearn-color-text-on-default-background), var(--sklearn-color-text-on-default-background));\n",
       "  background-size: 2px 100%;\n",
       "  background-repeat: no-repeat;\n",
       "  background-position: center center;\n",
       "}\n",
       "\n",
       "/* Parallel-specific style estimator block */\n",
       "\n",
       "#sk-container-id-1 div.sk-parallel-item::after {\n",
       "  content: \"\";\n",
       "  width: 100%;\n",
       "  border-bottom: 2px solid var(--sklearn-color-text-on-default-background);\n",
       "  flex-grow: 1;\n",
       "}\n",
       "\n",
       "#sk-container-id-1 div.sk-parallel {\n",
       "  display: flex;\n",
       "  align-items: stretch;\n",
       "  justify-content: center;\n",
       "  background-color: var(--sklearn-color-background);\n",
       "  position: relative;\n",
       "}\n",
       "\n",
       "#sk-container-id-1 div.sk-parallel-item {\n",
       "  display: flex;\n",
       "  flex-direction: column;\n",
       "}\n",
       "\n",
       "#sk-container-id-1 div.sk-parallel-item:first-child::after {\n",
       "  align-self: flex-end;\n",
       "  width: 50%;\n",
       "}\n",
       "\n",
       "#sk-container-id-1 div.sk-parallel-item:last-child::after {\n",
       "  align-self: flex-start;\n",
       "  width: 50%;\n",
       "}\n",
       "\n",
       "#sk-container-id-1 div.sk-parallel-item:only-child::after {\n",
       "  width: 0;\n",
       "}\n",
       "\n",
       "/* Serial-specific style estimator block */\n",
       "\n",
       "#sk-container-id-1 div.sk-serial {\n",
       "  display: flex;\n",
       "  flex-direction: column;\n",
       "  align-items: center;\n",
       "  background-color: var(--sklearn-color-background);\n",
       "  padding-right: 1em;\n",
       "  padding-left: 1em;\n",
       "}\n",
       "\n",
       "\n",
       "/* Toggleable style: style used for estimator/Pipeline/ColumnTransformer box that is\n",
       "clickable and can be expanded/collapsed.\n",
       "- Pipeline and ColumnTransformer use this feature and define the default style\n",
       "- Estimators will overwrite some part of the style using the `sk-estimator` class\n",
       "*/\n",
       "\n",
       "/* Pipeline and ColumnTransformer style (default) */\n",
       "\n",
       "#sk-container-id-1 div.sk-toggleable {\n",
       "  /* Default theme specific background. It is overwritten whether we have a\n",
       "  specific estimator or a Pipeline/ColumnTransformer */\n",
       "  background-color: var(--sklearn-color-background);\n",
       "}\n",
       "\n",
       "/* Toggleable label */\n",
       "#sk-container-id-1 label.sk-toggleable__label {\n",
       "  cursor: pointer;\n",
       "  display: block;\n",
       "  width: 100%;\n",
       "  margin-bottom: 0;\n",
       "  padding: 0.5em;\n",
       "  box-sizing: border-box;\n",
       "  text-align: center;\n",
       "}\n",
       "\n",
       "#sk-container-id-1 label.sk-toggleable__label-arrow:before {\n",
       "  /* Arrow on the left of the label */\n",
       "  content: \"▸\";\n",
       "  float: left;\n",
       "  margin-right: 0.25em;\n",
       "  color: var(--sklearn-color-icon);\n",
       "}\n",
       "\n",
       "#sk-container-id-1 label.sk-toggleable__label-arrow:hover:before {\n",
       "  color: var(--sklearn-color-text);\n",
       "}\n",
       "\n",
       "/* Toggleable content - dropdown */\n",
       "\n",
       "#sk-container-id-1 div.sk-toggleable__content {\n",
       "  max-height: 0;\n",
       "  max-width: 0;\n",
       "  overflow: hidden;\n",
       "  text-align: left;\n",
       "  /* unfitted */\n",
       "  background-color: var(--sklearn-color-unfitted-level-0);\n",
       "}\n",
       "\n",
       "#sk-container-id-1 div.sk-toggleable__content.fitted {\n",
       "  /* fitted */\n",
       "  background-color: var(--sklearn-color-fitted-level-0);\n",
       "}\n",
       "\n",
       "#sk-container-id-1 div.sk-toggleable__content pre {\n",
       "  margin: 0.2em;\n",
       "  border-radius: 0.25em;\n",
       "  color: var(--sklearn-color-text);\n",
       "  /* unfitted */\n",
       "  background-color: var(--sklearn-color-unfitted-level-0);\n",
       "}\n",
       "\n",
       "#sk-container-id-1 div.sk-toggleable__content.fitted pre {\n",
       "  /* unfitted */\n",
       "  background-color: var(--sklearn-color-fitted-level-0);\n",
       "}\n",
       "\n",
       "#sk-container-id-1 input.sk-toggleable__control:checked~div.sk-toggleable__content {\n",
       "  /* Expand drop-down */\n",
       "  max-height: 200px;\n",
       "  max-width: 100%;\n",
       "  overflow: auto;\n",
       "}\n",
       "\n",
       "#sk-container-id-1 input.sk-toggleable__control:checked~label.sk-toggleable__label-arrow:before {\n",
       "  content: \"▾\";\n",
       "}\n",
       "\n",
       "/* Pipeline/ColumnTransformer-specific style */\n",
       "\n",
       "#sk-container-id-1 div.sk-label input.sk-toggleable__control:checked~label.sk-toggleable__label {\n",
       "  color: var(--sklearn-color-text);\n",
       "  background-color: var(--sklearn-color-unfitted-level-2);\n",
       "}\n",
       "\n",
       "#sk-container-id-1 div.sk-label.fitted input.sk-toggleable__control:checked~label.sk-toggleable__label {\n",
       "  background-color: var(--sklearn-color-fitted-level-2);\n",
       "}\n",
       "\n",
       "/* Estimator-specific style */\n",
       "\n",
       "/* Colorize estimator box */\n",
       "#sk-container-id-1 div.sk-estimator input.sk-toggleable__control:checked~label.sk-toggleable__label {\n",
       "  /* unfitted */\n",
       "  background-color: var(--sklearn-color-unfitted-level-2);\n",
       "}\n",
       "\n",
       "#sk-container-id-1 div.sk-estimator.fitted input.sk-toggleable__control:checked~label.sk-toggleable__label {\n",
       "  /* fitted */\n",
       "  background-color: var(--sklearn-color-fitted-level-2);\n",
       "}\n",
       "\n",
       "#sk-container-id-1 div.sk-label label.sk-toggleable__label,\n",
       "#sk-container-id-1 div.sk-label label {\n",
       "  /* The background is the default theme color */\n",
       "  color: var(--sklearn-color-text-on-default-background);\n",
       "}\n",
       "\n",
       "/* On hover, darken the color of the background */\n",
       "#sk-container-id-1 div.sk-label:hover label.sk-toggleable__label {\n",
       "  color: var(--sklearn-color-text);\n",
       "  background-color: var(--sklearn-color-unfitted-level-2);\n",
       "}\n",
       "\n",
       "/* Label box, darken color on hover, fitted */\n",
       "#sk-container-id-1 div.sk-label.fitted:hover label.sk-toggleable__label.fitted {\n",
       "  color: var(--sklearn-color-text);\n",
       "  background-color: var(--sklearn-color-fitted-level-2);\n",
       "}\n",
       "\n",
       "/* Estimator label */\n",
       "\n",
       "#sk-container-id-1 div.sk-label label {\n",
       "  font-family: monospace;\n",
       "  font-weight: bold;\n",
       "  display: inline-block;\n",
       "  line-height: 1.2em;\n",
       "}\n",
       "\n",
       "#sk-container-id-1 div.sk-label-container {\n",
       "  text-align: center;\n",
       "}\n",
       "\n",
       "/* Estimator-specific */\n",
       "#sk-container-id-1 div.sk-estimator {\n",
       "  font-family: monospace;\n",
       "  border: 1px dotted var(--sklearn-color-border-box);\n",
       "  border-radius: 0.25em;\n",
       "  box-sizing: border-box;\n",
       "  margin-bottom: 0.5em;\n",
       "  /* unfitted */\n",
       "  background-color: var(--sklearn-color-unfitted-level-0);\n",
       "}\n",
       "\n",
       "#sk-container-id-1 div.sk-estimator.fitted {\n",
       "  /* fitted */\n",
       "  background-color: var(--sklearn-color-fitted-level-0);\n",
       "}\n",
       "\n",
       "/* on hover */\n",
       "#sk-container-id-1 div.sk-estimator:hover {\n",
       "  /* unfitted */\n",
       "  background-color: var(--sklearn-color-unfitted-level-2);\n",
       "}\n",
       "\n",
       "#sk-container-id-1 div.sk-estimator.fitted:hover {\n",
       "  /* fitted */\n",
       "  background-color: var(--sklearn-color-fitted-level-2);\n",
       "}\n",
       "\n",
       "/* Specification for estimator info (e.g. \"i\" and \"?\") */\n",
       "\n",
       "/* Common style for \"i\" and \"?\" */\n",
       "\n",
       ".sk-estimator-doc-link,\n",
       "a:link.sk-estimator-doc-link,\n",
       "a:visited.sk-estimator-doc-link {\n",
       "  float: right;\n",
       "  font-size: smaller;\n",
       "  line-height: 1em;\n",
       "  font-family: monospace;\n",
       "  background-color: var(--sklearn-color-background);\n",
       "  border-radius: 1em;\n",
       "  height: 1em;\n",
       "  width: 1em;\n",
       "  text-decoration: none !important;\n",
       "  margin-left: 1ex;\n",
       "  /* unfitted */\n",
       "  border: var(--sklearn-color-unfitted-level-1) 1pt solid;\n",
       "  color: var(--sklearn-color-unfitted-level-1);\n",
       "}\n",
       "\n",
       ".sk-estimator-doc-link.fitted,\n",
       "a:link.sk-estimator-doc-link.fitted,\n",
       "a:visited.sk-estimator-doc-link.fitted {\n",
       "  /* fitted */\n",
       "  border: var(--sklearn-color-fitted-level-1) 1pt solid;\n",
       "  color: var(--sklearn-color-fitted-level-1);\n",
       "}\n",
       "\n",
       "/* On hover */\n",
       "div.sk-estimator:hover .sk-estimator-doc-link:hover,\n",
       ".sk-estimator-doc-link:hover,\n",
       "div.sk-label-container:hover .sk-estimator-doc-link:hover,\n",
       ".sk-estimator-doc-link:hover {\n",
       "  /* unfitted */\n",
       "  background-color: var(--sklearn-color-unfitted-level-3);\n",
       "  color: var(--sklearn-color-background);\n",
       "  text-decoration: none;\n",
       "}\n",
       "\n",
       "div.sk-estimator.fitted:hover .sk-estimator-doc-link.fitted:hover,\n",
       ".sk-estimator-doc-link.fitted:hover,\n",
       "div.sk-label-container:hover .sk-estimator-doc-link.fitted:hover,\n",
       ".sk-estimator-doc-link.fitted:hover {\n",
       "  /* fitted */\n",
       "  background-color: var(--sklearn-color-fitted-level-3);\n",
       "  color: var(--sklearn-color-background);\n",
       "  text-decoration: none;\n",
       "}\n",
       "\n",
       "/* Span, style for the box shown on hovering the info icon */\n",
       ".sk-estimator-doc-link span {\n",
       "  display: none;\n",
       "  z-index: 9999;\n",
       "  position: relative;\n",
       "  font-weight: normal;\n",
       "  right: .2ex;\n",
       "  padding: .5ex;\n",
       "  margin: .5ex;\n",
       "  width: min-content;\n",
       "  min-width: 20ex;\n",
       "  max-width: 50ex;\n",
       "  color: var(--sklearn-color-text);\n",
       "  box-shadow: 2pt 2pt 4pt #999;\n",
       "  /* unfitted */\n",
       "  background: var(--sklearn-color-unfitted-level-0);\n",
       "  border: .5pt solid var(--sklearn-color-unfitted-level-3);\n",
       "}\n",
       "\n",
       ".sk-estimator-doc-link.fitted span {\n",
       "  /* fitted */\n",
       "  background: var(--sklearn-color-fitted-level-0);\n",
       "  border: var(--sklearn-color-fitted-level-3);\n",
       "}\n",
       "\n",
       ".sk-estimator-doc-link:hover span {\n",
       "  display: block;\n",
       "}\n",
       "\n",
       "/* \"?\"-specific style due to the `<a>` HTML tag */\n",
       "\n",
       "#sk-container-id-1 a.estimator_doc_link {\n",
       "  float: right;\n",
       "  font-size: 1rem;\n",
       "  line-height: 1em;\n",
       "  font-family: monospace;\n",
       "  background-color: var(--sklearn-color-background);\n",
       "  border-radius: 1rem;\n",
       "  height: 1rem;\n",
       "  width: 1rem;\n",
       "  text-decoration: none;\n",
       "  /* unfitted */\n",
       "  color: var(--sklearn-color-unfitted-level-1);\n",
       "  border: var(--sklearn-color-unfitted-level-1) 1pt solid;\n",
       "}\n",
       "\n",
       "#sk-container-id-1 a.estimator_doc_link.fitted {\n",
       "  /* fitted */\n",
       "  border: var(--sklearn-color-fitted-level-1) 1pt solid;\n",
       "  color: var(--sklearn-color-fitted-level-1);\n",
       "}\n",
       "\n",
       "/* On hover */\n",
       "#sk-container-id-1 a.estimator_doc_link:hover {\n",
       "  /* unfitted */\n",
       "  background-color: var(--sklearn-color-unfitted-level-3);\n",
       "  color: var(--sklearn-color-background);\n",
       "  text-decoration: none;\n",
       "}\n",
       "\n",
       "#sk-container-id-1 a.estimator_doc_link.fitted:hover {\n",
       "  /* fitted */\n",
       "  background-color: var(--sklearn-color-fitted-level-3);\n",
       "}\n",
       "</style><div id=\"sk-container-id-1\" class=\"sk-top-container\"><div class=\"sk-text-repr-fallback\"><pre>KNeighborsClassifier(metric=&#x27;euclidean&#x27;, n_neighbors=3)</pre><b>In a Jupyter environment, please rerun this cell to show the HTML representation or trust the notebook. <br />On GitHub, the HTML representation is unable to render, please try loading this page with nbviewer.org.</b></div><div class=\"sk-container\" hidden><div class=\"sk-item\"><div class=\"sk-estimator fitted sk-toggleable\"><input class=\"sk-toggleable__control sk-hidden--visually\" id=\"sk-estimator-id-1\" type=\"checkbox\" checked><label for=\"sk-estimator-id-1\" class=\"sk-toggleable__label fitted sk-toggleable__label-arrow fitted\">&nbsp;&nbsp;KNeighborsClassifier<a class=\"sk-estimator-doc-link fitted\" rel=\"noreferrer\" target=\"_blank\" href=\"https://scikit-learn.org/1.5/modules/generated/sklearn.neighbors.KNeighborsClassifier.html\">?<span>Documentation for KNeighborsClassifier</span></a><span class=\"sk-estimator-doc-link fitted\">i<span>Fitted</span></span></label><div class=\"sk-toggleable__content fitted\"><pre>KNeighborsClassifier(metric=&#x27;euclidean&#x27;, n_neighbors=3)</pre></div> </div></div></div></div>"
      ],
      "text/plain": [
       "KNeighborsClassifier(metric='euclidean', n_neighbors=3)"
      ]
     },
     "execution_count": 10,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "# Melatih model KNN\n",
    "best_knn = grid_search.best_estimator_\n",
    "best_knn.fit(X_train, y_train)\n"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 11,
   "metadata": {},
   "outputs": [],
   "source": [
    "# Menyimpan model yang sudah dilatih, PCA, dan label encoder yang \n",
    "# sudah dilatih kedalam file\n",
    "\n",
    "model_path = \"knn_model_vgg16&PCA.pkl\"\n",
    "with open(model_path, 'wb') as file:\n",
    "    pickle.dump(best_knn, file)\n",
    "    pickle.dump(pca, file)\n",
    "    pickle.dump(label_encoder, file)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 12,
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "Akurasi: 81.19%\n"
     ]
    }
   ],
   "source": [
    "# Menguji model dan mengevaluasi kinerja\n",
    "y_pred = best_knn.predict(X_valid)\n",
    "accuracy = accuracy_score(y_valid, y_pred)\n",
    "print(f'Akurasi: {accuracy * 100:.2f}%')"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 13,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "image/png": 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",
      "text/plain": [
       "<Figure size 600x300 with 1 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "# Fungsi untuk menampilkan grafik akurasi KNN selama cross-validation\n",
    "def plot_knn_cross_validation(cv_results):\n",
    "    mean_test_scores = cv_results['mean_test_score']\n",
    "    std_test_scores = cv_results['std_test_score']\n",
    "    params = [str(params) for params in cv_results['params']]\n",
    "    \n",
    "    plt.figure(figsize=(6, 3))\n",
    "    plt.errorbar(range(len(params)), mean_test_scores, yerr=std_test_scores, fmt='o', ecolor='g', capthick=2)\n",
    "    plt.xticks(range(len(params)), params, rotation=90)\n",
    "    plt.xlabel('Parameter settings')\n",
    "    plt.ylabel('Mean Accuracy')\n",
    "    plt.title('Cross-Validation Mean Accuracy for KNN')\n",
    "    plt.show()\n",
    "\n",
    "# Memanggil fungsi untuk menampilkan grafik\n",
    "plot_knn_cross_validation(grid_search.cv_results_)\n"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 22,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "image/png": 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",
      "text/plain": [
       "<Figure size 500x500 with 2 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "Confusion Matrix\n",
      "[[104   4   3   0   0   2   0]\n",
      " [  3  97   4   9   0  11   1]\n",
      " [  0   4   8   6   0   2   0]\n",
      " [  4   2   5  56   1  17   0]\n",
      " [  0   0   1   6  84  15   5]\n",
      " [  2   6   3   4   3 197   0]\n",
      " [  1   0   1   3   0   2  15]]\n",
      "Classification Report\n",
      "               precision    recall  f1-score   support\n",
      "\n",
      "   Buah Sakit       0.91      0.92      0.92       113\n",
      "   Buah Sehat       0.86      0.78      0.82       125\n",
      "  Daun Gemini       0.32      0.40      0.36        20\n",
      "Daun Keriting       0.67      0.66      0.66        85\n",
      "  Daun Mosaic       0.95      0.76      0.84       111\n",
      "   Daun Sehat       0.80      0.92      0.85       215\n",
      "   Kutu Kebul       0.71      0.68      0.70        22\n",
      "\n",
      "     accuracy                           0.81       691\n",
      "    macro avg       0.75      0.73      0.74       691\n",
      " weighted avg       0.82      0.81      0.81       691\n",
      "\n",
      "Precision: 0.8210\n",
      "Recall: 0.8119\n",
      "F1-Score: 0.8129\n"
     ]
    }
   ],
   "source": [
    "cm = confusion_matrix(y_valid, y_pred)\n",
    "disp = ConfusionMatrixDisplay(confusion_matrix=cm, display_labels=label_encoder.classes_)\n",
    "fig, ax = plt.subplots(figsize=(5, 5))\n",
    "disp.plot(cmap=plt.cm.Blues, ax=ax, xticks_rotation='vertical')\n",
    "plt.xlabel('Predicted Label')\n",
    "plt.ylabel('True Label')\n",
    "plt.show()\n",
    "\n",
    "# Confusion Matrix\n",
    "print('Confusion Matrix')\n",
    "print(cm)\n",
    "\n",
    "# Classification Report\n",
    "report = classification_report(y_valid, y_pred, target_names=label_encoder.classes_)\n",
    "print('Classification Report')\n",
    "print(report)\n",
    "\n",
    "# Precision, Recall, F1-Score\n",
    "precision = precision_score(y_valid, y_pred, average='weighted')\n",
    "recall = recall_score(y_valid, y_pred, average='weighted')\n",
    "f1 = f1_score(y_valid, y_pred, average='weighted')\n",
    "\n",
    "print(f'Precision: {precision:.4f}')\n",
    "print(f'Recall: {recall:.4f}')\n",
    "print(f'F1-Score: {f1:.4f}')"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 14,
   "metadata": {},
   "outputs": [],
   "source": [
    "# # Menampilkan Confusion Matrix \n",
    "# cm = confusion_matrix(y_valid, y_pred, labels=best_knn.classes_)\n",
    "# disp = ConfusionMatrixDisplay(confusion_matrix=cm, display_labels=best_knn.classes_)\n",
    "# disp.plot(cmap=plt.cm.Blues, xticks_rotation='vertical') # coba ganti vertikal menjadi horizontal, lihat perbedaan pada grafik\n",
    "# plt.xlabel('Predicted Label')\n",
    "# plt.ylabel('True Label')\n",
    "# plt.show()\n",
    "\n",
    "# # Confusion Matrix\n",
    "# print('Confusion Matrix')\n",
    "# cm = confusion_matrix(y_valid, y_pred)\n",
    "# print(cm)\n",
    "\n",
    "# # classification report\n",
    "# report = classification_report(y_valid, y_pred, target_names=label_encoder.classes_)\n",
    "# print('Classification Report')\n",
    "# print(report)\n",
    "\n",
    "# # Precision, Recall, F1-Score\n",
    "# precision = precision_score(y_valid, y_pred, average='weighted')\n",
    "# recall = recall_score(y_valid, y_pred, average='weighted')\n",
    "# f1 = f1_score(y_valid, y_pred, average='weighted')\n",
    "\n",
    "# print(f'Precision: {precision:.4f}')\n",
    "# print(f'Recall: {recall:.4f}')\n",
    "# print(f'F1-Score: {f1:.4f}')\n",
    "\n"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 15,
   "metadata": {},
   "outputs": [],
   "source": [
    "# Fungsi untuk mendapatkan probabilitas prediksi dari gambar yang dikenal\n",
    "# def get_probabilities(folder_path, knn_model, feature_extractor, pca_model, img_size=(128, 128)):\n",
    "#     probabilities = []\n",
    "#     for filename in os.listdir(folder_path):\n",
    "#         if filename.endswith(('.jpeg', '.png', '.jpg')):\n",
    "#             image_path = os.path.join(folder_path, filename)\n",
    "#             features = extract_features(feature_extractor, image_path, img_size)\n",
    "#             features_pca = pca_model.transform(features.reshape(1, -1))\n",
    "#             prob = np.max(knn_model.predict_proba(features_pca))\n",
    "#             probabilities.append(prob)\n",
    "#     return probabilities\n",
    "\n",
    "# # Path ke folder gambar tes yang dikenal\n",
    "# known_test_folder_path = r'D:\\penelitian arya\\Tes\\tes yang dikenal'\n",
    "\n",
    "# # Mengumpulkan probabilitas untuk gambar yang dikenal\n",
    "# known_probabilities = get_probabilities(known_test_folder_path, best_knn, feature_extractor, pca, img_size=(128, 128))\n",
    "\n",
    "# # Path ke folder gambar tes yang tidak dikenal\n",
    "# unknown_test_folder_path = r'D:\\penelitian arya\\Tes\\tes yang tidak dikenal'\n",
    "\n",
    "# # Mengumpulkan probabilitas untuk gambar yang tidak dikenal\n",
    "# unknown_probabilities = get_probabilities(unknown_test_folder_path, best_knn, feature_extractor, pca, img_size=(128, 128))\n",
    "\n",
    "# # Menyeimbangkan jumlah gambar dengan undersampling\n",
    "# # min_samples = min(len(known_probabilities), len(unknown_probabilities))\n",
    "# # known_probabilities_resampled = resample(known_probabilities, replace=False, n_samples=min_samples, random_state=123)\n",
    "# # unknown_probabilities_resampled = resample(unknown_probabilities, replace=False, n_samples=min_samples, random_state=123)\n",
    "\n",
    "# # Plot distribusi probabilitas\n",
    "# plt.figure(figsize=(6, 6))\n",
    "# plt.hist(known_probabilities, bins=50, alpha=0.5, label='dikenal')\n",
    "# plt.hist(unknown_probabilities, bins=50, alpha=0.5, label='tidak dikenal')\n",
    "# plt.xlabel('Probability')\n",
    "# plt.ylabel('Frequency')\n",
    "# plt.legend(loc='upper right')\n",
    "# plt.title('Distribution of Prediction Probabilities')\n",
    "# plt.show()\n",
    "\n",
    "# # Menentukan ambang batas optimal berdasarkan analisis distribusi\n",
    "# optimal_threshold = 0.7  # Contoh ambang batas yang didapat dari analisis distribusi\n"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 16,
   "metadata": {},
   "outputs": [],
   "source": [
    "# Menggabungkan probabilitas dan label untuk known dan unknown\n",
    "# all_probabilities = np.concatenate((known_probabilities_resampled, unknown_probabilities_resampled))\n",
    "# all_labels = np.concatenate((np.ones(len(known_probabilities_resampled)), np.zeros(len(unknown_probabilities_resampled))))\n",
    "\n",
    "# # Menghitung ROC Curve\n",
    "# fpr, tpr, thresholds = roc_curve(all_labels, all_probabilities)\n",
    "\n",
    "# # Menghitung AUC\n",
    "# roc_auc = auc(fpr, tpr)\n",
    "\n",
    "# # Plot ROC Curve\n",
    "# plt.figure(figsize=(5, 5))\n",
    "# plt.plot(fpr, tpr, color='darkorange', lw=2, label='ROC curve (area = %0.2f)' % roc_auc)\n",
    "# plt.plot([0, 1], [0, 1], color='navy', lw=2, linestyle='--')\n",
    "# plt.xlim([0.0, 1.0])\n",
    "# plt.ylim([0.0, 1.05])\n",
    "# plt.xlabel('False Positive Rate')\n",
    "# plt.ylabel('True Positive Rate')\n",
    "# plt.title('Receiver Operating Characteristic (ROC) Curve')\n",
    "# plt.legend(loc=\"lower right\")\n",
    "# plt.show()\n",
    "\n",
    "# # Menemukan threshold optimal\n",
    "# optimal_idx = np.argmax(tpr - fpr)\n",
    "# optimal_threshold = thresholds[optimal_idx]\n",
    "# print(f\"Optimal Threshold: {optimal_threshold}\")"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 17,
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "\u001b[1m1/1\u001b[0m \u001b[32m━━━━━━━━━━━━━━━━━━━━\u001b[0m\u001b[37m\u001b[0m \u001b[1m0s\u001b[0m 133ms/step\n"
     ]
    },
    {
     "data": {
      "image/png": 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",
      "text/plain": [
       "<Figure size 900x400 with 1 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "# Fungsi untuk memprediksi gambar dan menampilkannya\n",
    "def predict_and_show_images_in_folder(folder_path, knn_model, feature_extractor, pca_model, label_encoder, img_size=(128, 128)):\n",
    "    try:\n",
    "        # Mendapatkan daftar file gambar\n",
    "        image_files = [f for f in os.listdir(folder_path) if f.endswith(('.jpeg', '.png', '.jpg'))]\n",
    "        num_images = len(image_files)\n",
    "        num_columns = 4\n",
    "        num_rows = num_images // num_columns + (num_images % num_columns != 0)\n",
    "        \n",
    "        plt.figure(figsize=(9, num_rows * 4))\n",
    "        \n",
    "        for i, filename in enumerate(image_files):\n",
    "            image_path = os.path.join(folder_path, filename)\n",
    "            features = extract_features(feature_extractor, image_path, img_size)\n",
    "            # features = features.reshape(1, -1)\n",
    "            features_pca = pca_model.transform(features.reshape(1, -1))\n",
    "            \n",
    "            # # Melakukan prediksi probabilitas\n",
    "            # probabilities = knn_model.predict_proba(features_pca)\n",
    "            # max_prob = np.max(probabilities)\n",
    "            # predicted_class = np.argmax(probabilities)\n",
    "            \n",
    "            # # Tentukan hasil berdasarkan ambang batas kepercayaan\n",
    "            # if max_prob < threshold:\n",
    "            #     result = \"Tidak Dikenal\"\n",
    "            # else:\n",
    "            #     result = label_encoder.inverse_transform([predicted_class])[0]\n",
    "\n",
    "\n",
    "            # # Melakukan prediksi\n",
    "            prediction = knn_model.predict(features_pca)\n",
    "            # predicted_class_index = int(prediction[0])\n",
    "            result = label_encoder.inverse_transform(prediction)[0]\n",
    "\n",
    "            # Menampilkan gambar dengan prediksi\n",
    "            img = cv2.cvtColor(cv2.resize(cv2.imread(image_path), img_size), cv2.COLOR_BGR2RGB)\n",
    "            \n",
    "            plt.subplot(num_rows, num_columns, i + 1)\n",
    "            plt.imshow(img)\n",
    "            plt.title(f'File: {filename}\\nPrediction: {result}')\n",
    "            plt.axis('off')\n",
    "\n",
    "        plt.tight_layout()\n",
    "        plt.show()\n",
    "    except Exception as e:\n",
    "        print(f\"Error: {e}\")\n",
    "\n",
    "# Path ke folder gambar tes \n",
    "test_folder_path = r'D:\\penelitian arya\\Tes\\tes7'\n",
    "img_width, img_height = 128, 128# Ukuran gambar yang sesuai dengan pelatihan\n",
    "img_size = (img_width, img_height)\n",
    "\n",
    "# # Memuat model KNN \n",
    "model_path = r'D:\\penelitian arya\\knn_model_vgg16&PCA.pkl'\n",
    "with open(model_path, 'rb') as file:\n",
    "    loaded_knn = pickle.load(file)\n",
    "    loaded_pca = pickle.load(file)\n",
    "    loaded_label_encoder = pickle.load(file)\n",
    "\n",
    "\n",
    "# Memuat model VGG16 pra-terlatih\n",
    "base_model = VGG16(weights='imagenet', include_top=False, input_shape=(128, 128, 3))\n",
    "feature_extractor = Model(inputs=base_model.input, outputs=base_model.output)\n",
    "\n",
    "# Daftar label kelas\n",
    "class_labels = ['Buah Sakit', 'Buah Sehat', 'Sakit Virus Gemini', 'Sakit Daun Keriting',\n",
    "                'Sakit Daun Mosaic', 'Daun Sehat', 'Hama Kutu Kebul']\n",
    "\n",
    "# Memanggil fungsi predict_and_show_images_in_folder\n",
    "# optimal_threshold = 0.7\n",
    "predict_and_show_images_in_folder(test_folder_path, loaded_knn, feature_extractor, loaded_pca, loaded_label_encoder, img_size=(128, 128))"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 18,
   "metadata": {},
   "outputs": [],
   "source": [
    "# Fungsi predict_and_show_images_in_folder digunakan untuk memprediksi kelas \n",
    "# dari gambar-gambar dalam folder tertentu dan menampilkan hasilnya dalam grid.\n",
    "# Memuat model KNN, PCA, dan label encoder yang telah disimpan.\n",
    "# Menggunakan model VGG16 untuk mengekstraksi fitur dari gambar dalam folder tes.\n",
    "# Menampilkan hasil prediksi untuk setiap gambar dalam folder tes."
   ]
  }
 ],
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   "language": "python",
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  "language_info": {
   "codemirror_mode": {
    "name": "ipython",
    "version": 3
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   "file_extension": ".py",
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   "nbconvert_exporter": "python",
   "pygments_lexer": "ipython3",
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