NASNetMobile-fold0.ipynb

{
 "cells": [
  {
   "cell_type": "code",
   "execution_count": 1,
   "metadata": {},
   "outputs": [],
   "source": [
    "import tensorflow.compat.v2 as tf\n",
    "from tensorflow import keras\n",
    "import matplotlib.pyplot as plt\n",
    "%matplotlib inline\n",
    "import numpy as np\n",
    "import pathlib\n",
    "import random\n",
    "import glob\n",
    "import os\n",
    "from tensorflow.compat.v1 import ConfigProto\n",
    "from tensorflow.compat.v1 import InteractiveSession\n",
    "import time\n",
    "keras = tf.keras\n",
    "config = ConfigProto()\n",
    "config.gpu_options.allow_growth = True\n",
    "session = InteractiveSession(config=config)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 2,
   "metadata": {},
   "outputs": [],
   "source": [
    "def load_and_preprocess_image(path):\n",
    "    image = tf.io.read_file(path)\n",
    "    image = tf.image.decode_jpeg(image, channels=3)\n",
    "    image = tf.image.resize(image, [224, 224])\n",
    "    image = tf.cast(image, tf.float32)\n",
    "    image = image/255.0\n",
    "    image = 2*image-1\n",
    "    return image"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 3,
   "metadata": {},
   "outputs": [],
   "source": [
    "train_dir = r'C:\\Users\\24306\\Desktop\\datasets\\kfold\\0\\train'\n",
    "test_dir  = r'C:\\Users\\24306\\Desktop\\datasets\\kfold\\0\\test'\n",
    "checkpoint_path = r'C:\\Users\\24306\\Desktop\\NASNetMobile\\0\\NASNetMobile.ckpt'"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "# 处理训练数据"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 4,
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
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      "<PrefetchDataset element_spec=(TensorSpec(shape=(None, 224, 224, 3), dtype=tf.float32, name=None), TensorSpec(shape=(None,), dtype=tf.float32, name=None))>\n"
     ]
    }
   ],
   "source": [
    "#打乱顺序\n",
    "train_root = pathlib.Path(train_dir)\n",
    "train_image_paths = list(train_root.glob('*/*'))\n",
    "train_image_paths = [str(path) for path in train_image_paths]\n",
    "random.shuffle(train_image_paths)\n",
    "#处理训练标签\n",
    "train_image_labels = [pathlib.Path(path).parent.name for path in train_image_paths]\n",
    "train_labels = [[label.split('_')[0]] for label in train_image_labels]\n",
    "new_train_labels=[]\n",
    "for n in train_labels:\n",
    "    new_train_labels.append(float(n[0]));  \n",
    "train_labels=new_train_labels\n",
    "print(train_labels)\n",
    "#处理训练图像\n",
    "train_path_ds = tf.data.Dataset.from_tensor_slices(train_image_paths)\n",
    "AUTOTUNE = tf.data.experimental.AUTOTUNE\n",
    "train_image_ds = train_path_ds.map(load_and_preprocess_image, num_parallel_calls=AUTOTUNE)\n",
    "train_label_ds = tf.data.Dataset.from_tensor_slices(train_labels)\n",
    "train_image_label_ds = tf.data.Dataset.zip((train_image_ds, train_label_ds))\n",
    "# image_count = len(all_image_paths)\n",
    "\n",
    "# test_count = int(image_count*0.2)\n",
    "train_count = len(train_image_paths)\n",
    "# train_data = image_label_ds.skip(test_count)\n",
    "# test_data = image_label_ds.take(test_count)\n",
    "\n",
    "BATCH_SIZE = 32\n",
    "train_data = train_image_label_ds.shuffle(buffer_size=train_count).repeat(-1)\n",
    "train_data = train_data.batch(BATCH_SIZE)\n",
    "train_data = train_data.prefetch(buffer_size=AUTOTUNE)\n",
    "\n",
    "#test_data = test_data.batch(BATCH_SIZE)\n",
    "print(train_data)\n",
    "\n"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "# 处理验证数据"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 5,
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
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      "<PrefetchDataset element_spec=(TensorSpec(shape=(None, 224, 224, 3), dtype=tf.float32, name=None), TensorSpec(shape=(None,), dtype=tf.float32, name=None))>\n"
     ]
    }
   ],
   "source": [
    "#打乱顺序\n",
    "test_root = pathlib.Path(test_dir)\n",
    "test_image_paths = list(test_root.glob('*/*'))\n",
    "test_image_paths = [str(path) for path in test_image_paths]\n",
    "#random.shuffle(train_image_paths)\n",
    "#处理训练标签\n",
    "test_image_labels = [pathlib.Path(path).parent.name for path in test_image_paths]\n",
    "test_labels = [[label.split('_')[0]] for label in test_image_labels]\n",
    "new_test_labels=[]\n",
    "for n in test_labels:\n",
    "    new_test_labels.append(float(n[0]));  \n",
    "test_labels=new_test_labels\n",
    "print(test_labels)\n",
    "#处理训练图像\n",
    "test_path_ds = tf.data.Dataset.from_tensor_slices(test_image_paths)\n",
    "AUTOTUNE = tf.data.experimental.AUTOTUNE\n",
    "test_image_ds = test_path_ds.map(load_and_preprocess_image, num_parallel_calls=AUTOTUNE)\n",
    "test_label_ds = tf.data.Dataset.from_tensor_slices(test_labels)\n",
    "test_image_label_ds = tf.data.Dataset.zip((test_image_ds, test_label_ds))\n",
    "# image_count = len(all_image_paths)\n",
    "\n",
    "# test_count = int(image_count*0.2)\n",
    "test_count = len(test_image_paths)\n",
    "# train_data = image_label_ds.skip(test_count)\n",
    "# test_data = image_label_ds.take(test_count)\n",
    "\n",
    "BATCH_SIZE = 32\n",
    "test_data = test_image_label_ds.shuffle(buffer_size=test_count).repeat(-1)\n",
    "test_data = test_data.batch(BATCH_SIZE)\n",
    "test_data = test_data.prefetch(buffer_size=AUTOTUNE)\n",
    "\n",
    "#test_data = test_data.batch(BATCH_SIZE)\n",
    "print(test_data)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 6,
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "Downloading data from https://storage.googleapis.com/tensorflow/keras-applications/nasnet/NASNet-mobile-no-top.h5\n",
      "19993432/19993432 [==============================] - 2s 0us/step\n",
      "Model: \"model\"\n",
      "_________________________________________________________________\n",
      " Layer (type)                Output Shape              Param #   \n",
      "=================================================================\n",
      " input_2 (InputLayer)        [(None, 224, 224, 3)]     0         \n",
      "                                                                 \n",
      " NASNet (Functional)         (None, 7, 7, 1056)        4269716   \n",
      "                                                                 \n",
      " global_average_pooling2d (G  (None, 1056)             0         \n",
      " lobalAveragePooling2D)                                          \n",
      "                                                                 \n",
      " out_weight (Dense)          (None, 1)                 1057      \n",
      "                                                                 \n",
      "=================================================================\n",
      "Total params: 4,270,773\n",
      "Trainable params: 4,234,035\n",
      "Non-trainable params: 36,738\n",
      "_________________________________________________________________\n"
     ]
    }
   ],
   "source": [
    "#要改\n",
    "NASNetMobile = tf.keras.applications.NASNetMobile(weights='imagenet',include_top=False,input_shape=(224, 224, 3))\n",
    "#要改\n",
    "NASNetMobile.trainable = True\n",
    "inputs = tf.keras.Input(shape=(224, 224, 3))\n",
    "#要改\n",
    "x = NASNetMobile(inputs)\n",
    "x = tf.keras.layers.GlobalAveragePooling2D()(x)\n",
    "out_weight = tf.keras.layers.Dense(1,name='out_weight')(x)\n",
    "\n",
    "model = tf.keras.Model(inputs=inputs,\n",
    "                       outputs=[out_weight])\n",
    "model.summary()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 7,
   "metadata": {
    "scrolled": true
   },
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "start time: Thu Apr  6 17:33:07 2023\n",
      "Epoch 1/300\n",
      "591/591 [==============================] - ETA: 0s - loss: 66.2527"
     ]
    },
    {
     "name": "stderr",
     "output_type": "stream",
     "text": [
      "WARNING:absl:Found untraced functions such as _jit_compiled_convolution_op, _jit_compiled_convolution_op, _jit_compiled_convolution_op, _jit_compiled_convolution_op, _jit_compiled_convolution_op while saving (showing 5 of 196). These functions will not be directly callable after loading.\n"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "INFO:tensorflow:Assets written to: C:\\Users\\24306\\Desktop\\NASNetMobile\\0\\NASNetMobile.ckpt\\assets\n"
     ]
    },
    {
     "name": "stderr",
     "output_type": "stream",
     "text": [
      "INFO:tensorflow:Assets written to: C:\\Users\\24306\\Desktop\\NASNetMobile\\0\\NASNetMobile.ckpt\\assets\n"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "591/591 [==============================] - 193s 274ms/step - loss: 66.2527 - val_loss: 763.3864\n",
      "Epoch 2/300\n",
      "591/591 [==============================] - ETA: 0s - loss: 2.5564"
     ]
    },
    {
     "name": "stderr",
     "output_type": "stream",
     "text": [
      "WARNING:absl:Found untraced functions such as _jit_compiled_convolution_op, _jit_compiled_convolution_op, _jit_compiled_convolution_op, _jit_compiled_convolution_op, _jit_compiled_convolution_op while saving (showing 5 of 196). These functions will not be directly callable after loading.\n"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "INFO:tensorflow:Assets written to: C:\\Users\\24306\\Desktop\\NASNetMobile\\0\\NASNetMobile.ckpt\\assets\n"
     ]
    },
    {
     "name": "stderr",
     "output_type": "stream",
     "text": [
      "INFO:tensorflow:Assets written to: C:\\Users\\24306\\Desktop\\NASNetMobile\\0\\NASNetMobile.ckpt\\assets\n"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "591/591 [==============================] - 168s 284ms/step - loss: 2.5564 - val_loss: 691.2800\n",
      "Epoch 3/300\n",
      "591/591 [==============================] - ETA: 0s - loss: 1.0653"
     ]
    },
    {
     "name": "stderr",
     "output_type": "stream",
     "text": [
      "WARNING:absl:Found untraced functions such as _jit_compiled_convolution_op, _jit_compiled_convolution_op, _jit_compiled_convolution_op, _jit_compiled_convolution_op, _jit_compiled_convolution_op while saving (showing 5 of 196). These functions will not be directly callable after loading.\n"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "INFO:tensorflow:Assets written to: C:\\Users\\24306\\Desktop\\NASNetMobile\\0\\NASNetMobile.ckpt\\assets\n"
     ]
    },
    {
     "name": "stderr",
     "output_type": "stream",
     "text": [
      "INFO:tensorflow:Assets written to: C:\\Users\\24306\\Desktop\\NASNetMobile\\0\\NASNetMobile.ckpt\\assets\n"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "591/591 [==============================] - 176s 298ms/step - loss: 1.0653 - val_loss: 471.3808\n",
      "Epoch 4/300\n",
      "591/591 [==============================] - ETA: 0s - loss: 0.6095"
     ]
    },
    {
     "name": "stderr",
     "output_type": "stream",
     "text": [
      "WARNING:absl:Found untraced functions such as _jit_compiled_convolution_op, _jit_compiled_convolution_op, _jit_compiled_convolution_op, _jit_compiled_convolution_op, _jit_compiled_convolution_op while saving (showing 5 of 196). These functions will not be directly callable after loading.\n"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "INFO:tensorflow:Assets written to: C:\\Users\\24306\\Desktop\\NASNetMobile\\0\\NASNetMobile.ckpt\\assets\n"
     ]
    },
    {
     "name": "stderr",
     "output_type": "stream",
     "text": [
      "INFO:tensorflow:Assets written to: C:\\Users\\24306\\Desktop\\NASNetMobile\\0\\NASNetMobile.ckpt\\assets\n"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "591/591 [==============================] - 183s 310ms/step - loss: 0.6095 - val_loss: 283.4311\n",
      "Epoch 5/300\n",
      "591/591 [==============================] - ETA: 0s - loss: 0.4462"
     ]
    },
    {
     "name": "stderr",
     "output_type": "stream",
     "text": [
      "WARNING:absl:Found untraced functions such as _jit_compiled_convolution_op, _jit_compiled_convolution_op, _jit_compiled_convolution_op, _jit_compiled_convolution_op, _jit_compiled_convolution_op while saving (showing 5 of 196). These functions will not be directly callable after loading.\n"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "INFO:tensorflow:Assets written to: C:\\Users\\24306\\Desktop\\NASNetMobile\\0\\NASNetMobile.ckpt\\assets\n"
     ]
    },
    {
     "name": "stderr",
     "output_type": "stream",
     "text": [
      "INFO:tensorflow:Assets written to: C:\\Users\\24306\\Desktop\\NASNetMobile\\0\\NASNetMobile.ckpt\\assets\n"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "591/591 [==============================] - 181s 306ms/step - loss: 0.4462 - val_loss: 173.1541\n",
      "Epoch 6/300\n",
      "591/591 [==============================] - ETA: 0s - loss: 0.3934"
     ]
    },
    {
     "name": "stderr",
     "output_type": "stream",
     "text": [
      "WARNING:absl:Found untraced functions such as _jit_compiled_convolution_op, _jit_compiled_convolution_op, _jit_compiled_convolution_op, _jit_compiled_convolution_op, _jit_compiled_convolution_op while saving (showing 5 of 196). These functions will not be directly callable after loading.\n"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "INFO:tensorflow:Assets written to: C:\\Users\\24306\\Desktop\\NASNetMobile\\0\\NASNetMobile.ckpt\\assets\n"
     ]
    },
    {
     "name": "stderr",
     "output_type": "stream",
     "text": [
      "INFO:tensorflow:Assets written to: C:\\Users\\24306\\Desktop\\NASNetMobile\\0\\NASNetMobile.ckpt\\assets\n"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "591/591 [==============================] - 184s 311ms/step - loss: 0.3934 - val_loss: 91.8208\n",
      "Epoch 7/300\n",
      "591/591 [==============================] - ETA: 0s - loss: 0.2579"
     ]
    },
    {
     "name": "stderr",
     "output_type": "stream",
     "text": [
      "WARNING:absl:Found untraced functions such as _jit_compiled_convolution_op, _jit_compiled_convolution_op, _jit_compiled_convolution_op, _jit_compiled_convolution_op, _jit_compiled_convolution_op while saving (showing 5 of 196). These functions will not be directly callable after loading.\n"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "INFO:tensorflow:Assets written to: C:\\Users\\24306\\Desktop\\NASNetMobile\\0\\NASNetMobile.ckpt\\assets\n"
     ]
    },
    {
     "name": "stderr",
     "output_type": "stream",
     "text": [
      "INFO:tensorflow:Assets written to: C:\\Users\\24306\\Desktop\\NASNetMobile\\0\\NASNetMobile.ckpt\\assets\n"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "591/591 [==============================] - 184s 311ms/step - loss: 0.2579 - val_loss: 43.8410\n",
      "Epoch 8/300\n",
      "591/591 [==============================] - ETA: 0s - loss: 0.2866"
     ]
    },
    {
     "name": "stderr",
     "output_type": "stream",
     "text": [
      "WARNING:absl:Found untraced functions such as _jit_compiled_convolution_op, _jit_compiled_convolution_op, _jit_compiled_convolution_op, _jit_compiled_convolution_op, _jit_compiled_convolution_op while saving (showing 5 of 196). These functions will not be directly callable after loading.\n"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "INFO:tensorflow:Assets written to: C:\\Users\\24306\\Desktop\\NASNetMobile\\0\\NASNetMobile.ckpt\\assets\n"
     ]
    },
    {
     "name": "stderr",
     "output_type": "stream",
     "text": [
      "INFO:tensorflow:Assets written to: C:\\Users\\24306\\Desktop\\NASNetMobile\\0\\NASNetMobile.ckpt\\assets\n"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "591/591 [==============================] - 185s 313ms/step - loss: 0.2866 - val_loss: 23.0025\n",
      "Epoch 9/300\n",
      "591/591 [==============================] - ETA: 0s - loss: 0.2652"
     ]
    },
    {
     "name": "stderr",
     "output_type": "stream",
     "text": [
      "WARNING:absl:Found untraced functions such as _jit_compiled_convolution_op, _jit_compiled_convolution_op, _jit_compiled_convolution_op, _jit_compiled_convolution_op, _jit_compiled_convolution_op while saving (showing 5 of 196). These functions will not be directly callable after loading.\n"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "INFO:tensorflow:Assets written to: C:\\Users\\24306\\Desktop\\NASNetMobile\\0\\NASNetMobile.ckpt\\assets\n"
     ]
    },
    {
     "name": "stderr",
     "output_type": "stream",
     "text": [
      "INFO:tensorflow:Assets written to: C:\\Users\\24306\\Desktop\\NASNetMobile\\0\\NASNetMobile.ckpt\\assets\n"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "591/591 [==============================] - 187s 316ms/step - loss: 0.2652 - val_loss: 17.4643\n",
      "Epoch 10/300\n",
      "591/591 [==============================] - ETA: 0s - loss: 0.2017"
     ]
    },
    {
     "name": "stderr",
     "output_type": "stream",
     "text": [
      "WARNING:absl:Found untraced functions such as _jit_compiled_convolution_op, _jit_compiled_convolution_op, _jit_compiled_convolution_op, _jit_compiled_convolution_op, _jit_compiled_convolution_op while saving (showing 5 of 196). These functions will not be directly callable after loading.\n"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "INFO:tensorflow:Assets written to: C:\\Users\\24306\\Desktop\\NASNetMobile\\0\\NASNetMobile.ckpt\\assets\n"
     ]
    },
    {
     "name": "stderr",
     "output_type": "stream",
     "text": [
      "INFO:tensorflow:Assets written to: C:\\Users\\24306\\Desktop\\NASNetMobile\\0\\NASNetMobile.ckpt\\assets\n"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "591/591 [==============================] - 191s 323ms/step - loss: 0.2017 - val_loss: 10.9370\n",
      "Epoch 11/300\n",
      "591/591 [==============================] - ETA: 0s - loss: 0.1734"
     ]
    },
    {
     "name": "stderr",
     "output_type": "stream",
     "text": [
      "WARNING:absl:Found untraced functions such as _jit_compiled_convolution_op, _jit_compiled_convolution_op, _jit_compiled_convolution_op, _jit_compiled_convolution_op, _jit_compiled_convolution_op while saving (showing 5 of 196). These functions will not be directly callable after loading.\n"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "INFO:tensorflow:Assets written to: C:\\Users\\24306\\Desktop\\NASNetMobile\\0\\NASNetMobile.ckpt\\assets\n"
     ]
    },
    {
     "name": "stderr",
     "output_type": "stream",
     "text": [
      "INFO:tensorflow:Assets written to: C:\\Users\\24306\\Desktop\\NASNetMobile\\0\\NASNetMobile.ckpt\\assets\n"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "591/591 [==============================] - 191s 322ms/step - loss: 0.1734 - val_loss: 9.2481\n",
      "Epoch 12/300\n",
      "591/591 [==============================] - ETA: 0s - loss: 0.1873"
     ]
    },
    {
     "name": "stderr",
     "output_type": "stream",
     "text": [
      "WARNING:absl:Found untraced functions such as _jit_compiled_convolution_op, _jit_compiled_convolution_op, _jit_compiled_convolution_op, _jit_compiled_convolution_op, _jit_compiled_convolution_op while saving (showing 5 of 196). These functions will not be directly callable after loading.\n"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "INFO:tensorflow:Assets written to: C:\\Users\\24306\\Desktop\\NASNetMobile\\0\\NASNetMobile.ckpt\\assets\n"
     ]
    },
    {
     "name": "stderr",
     "output_type": "stream",
     "text": [
      "INFO:tensorflow:Assets written to: C:\\Users\\24306\\Desktop\\NASNetMobile\\0\\NASNetMobile.ckpt\\assets\n"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "591/591 [==============================] - 190s 322ms/step - loss: 0.1873 - val_loss: 9.1462\n",
      "Epoch 13/300\n",
      "591/591 [==============================] - ETA: 0s - loss: 0.1680"
     ]
    },
    {
     "name": "stderr",
     "output_type": "stream",
     "text": [
      "WARNING:absl:Found untraced functions such as _jit_compiled_convolution_op, _jit_compiled_convolution_op, _jit_compiled_convolution_op, _jit_compiled_convolution_op, _jit_compiled_convolution_op while saving (showing 5 of 196). These functions will not be directly callable after loading.\n"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "INFO:tensorflow:Assets written to: C:\\Users\\24306\\Desktop\\NASNetMobile\\0\\NASNetMobile.ckpt\\assets\n"
     ]
    },
    {
     "name": "stderr",
     "output_type": "stream",
     "text": [
      "INFO:tensorflow:Assets written to: C:\\Users\\24306\\Desktop\\NASNetMobile\\0\\NASNetMobile.ckpt\\assets\n"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "591/591 [==============================] - 190s 322ms/step - loss: 0.1680 - val_loss: 5.5787\n",
      "Epoch 14/300\n",
      "591/591 [==============================] - 106s 179ms/step - loss: 0.1408 - val_loss: 6.5950\n",
      "Epoch 15/300\n",
      "591/591 [==============================] - ETA: 0s - loss: 0.1339"
     ]
    },
    {
     "name": "stderr",
     "output_type": "stream",
     "text": [
      "WARNING:absl:Found untraced functions such as _jit_compiled_convolution_op, _jit_compiled_convolution_op, _jit_compiled_convolution_op, _jit_compiled_convolution_op, _jit_compiled_convolution_op while saving (showing 5 of 196). These functions will not be directly callable after loading.\n"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "INFO:tensorflow:Assets written to: C:\\Users\\24306\\Desktop\\NASNetMobile\\0\\NASNetMobile.ckpt\\assets\n"
     ]
    },
    {
     "name": "stderr",
     "output_type": "stream",
     "text": [
      "INFO:tensorflow:Assets written to: C:\\Users\\24306\\Desktop\\NASNetMobile\\0\\NASNetMobile.ckpt\\assets\n"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "591/591 [==============================] - 189s 320ms/step - loss: 0.1339 - val_loss: 4.1784\n",
      "Epoch 16/300\n",
      "591/591 [==============================] - ETA: 0s - loss: 0.1317"
     ]
    },
    {
     "name": "stderr",
     "output_type": "stream",
     "text": [
      "WARNING:absl:Found untraced functions such as _jit_compiled_convolution_op, _jit_compiled_convolution_op, _jit_compiled_convolution_op, _jit_compiled_convolution_op, _jit_compiled_convolution_op while saving (showing 5 of 196). These functions will not be directly callable after loading.\n"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "INFO:tensorflow:Assets written to: C:\\Users\\24306\\Desktop\\NASNetMobile\\0\\NASNetMobile.ckpt\\assets\n"
     ]
    },
    {
     "name": "stderr",
     "output_type": "stream",
     "text": [
      "INFO:tensorflow:Assets written to: C:\\Users\\24306\\Desktop\\NASNetMobile\\0\\NASNetMobile.ckpt\\assets\n"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "591/591 [==============================] - 195s 330ms/step - loss: 0.1317 - val_loss: 3.8577\n",
      "Epoch 17/300\n",
      "591/591 [==============================] - 110s 186ms/step - loss: 0.1355 - val_loss: 4.2823\n",
      "Epoch 18/300\n",
      "591/591 [==============================] - ETA: 0s - loss: 0.1080"
     ]
    },
    {
     "name": "stderr",
     "output_type": "stream",
     "text": [
      "WARNING:absl:Found untraced functions such as _jit_compiled_convolution_op, _jit_compiled_convolution_op, _jit_compiled_convolution_op, _jit_compiled_convolution_op, _jit_compiled_convolution_op while saving (showing 5 of 196). These functions will not be directly callable after loading.\n"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "INFO:tensorflow:Assets written to: C:\\Users\\24306\\Desktop\\NASNetMobile\\0\\NASNetMobile.ckpt\\assets\n"
     ]
    },
    {
     "name": "stderr",
     "output_type": "stream",
     "text": [
      "INFO:tensorflow:Assets written to: C:\\Users\\24306\\Desktop\\NASNetMobile\\0\\NASNetMobile.ckpt\\assets\n"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "591/591 [==============================] - 193s 327ms/step - loss: 0.1080 - val_loss: 3.0958\n",
      "Epoch 19/300\n",
      "591/591 [==============================] - ETA: 0s - loss: 0.0954"
     ]
    },
    {
     "name": "stderr",
     "output_type": "stream",
     "text": [
      "WARNING:absl:Found untraced functions such as _jit_compiled_convolution_op, _jit_compiled_convolution_op, _jit_compiled_convolution_op, _jit_compiled_convolution_op, _jit_compiled_convolution_op while saving (showing 5 of 196). These functions will not be directly callable after loading.\n"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "INFO:tensorflow:Assets written to: C:\\Users\\24306\\Desktop\\NASNetMobile\\0\\NASNetMobile.ckpt\\assets\n"
     ]
    },
    {
     "name": "stderr",
     "output_type": "stream",
     "text": [
      "INFO:tensorflow:Assets written to: C:\\Users\\24306\\Desktop\\NASNetMobile\\0\\NASNetMobile.ckpt\\assets\n"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "591/591 [==============================] - 195s 330ms/step - loss: 0.0954 - val_loss: 2.5696\n",
      "Epoch 20/300\n",
      "591/591 [==============================] - 112s 189ms/step - loss: 0.1028 - val_loss: 2.8393\n",
      "Epoch 21/300\n",
      "591/591 [==============================] - ETA: 0s - loss: 0.0951"
     ]
    },
    {
     "name": "stderr",
     "output_type": "stream",
     "text": [
      "WARNING:absl:Found untraced functions such as _jit_compiled_convolution_op, _jit_compiled_convolution_op, _jit_compiled_convolution_op, _jit_compiled_convolution_op, _jit_compiled_convolution_op while saving (showing 5 of 196). These functions will not be directly callable after loading.\n"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "INFO:tensorflow:Assets written to: C:\\Users\\24306\\Desktop\\NASNetMobile\\0\\NASNetMobile.ckpt\\assets\n"
     ]
    },
    {
     "name": "stderr",
     "output_type": "stream",
     "text": [
      "INFO:tensorflow:Assets written to: C:\\Users\\24306\\Desktop\\NASNetMobile\\0\\NASNetMobile.ckpt\\assets\n"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "591/591 [==============================] - 198s 335ms/step - loss: 0.0951 - val_loss: 1.7680\n",
      "Epoch 22/300\n",
      "591/591 [==============================] - ETA: 0s - loss: 0.1007"
     ]
    },
    {
     "name": "stderr",
     "output_type": "stream",
     "text": [
      "WARNING:absl:Found untraced functions such as _jit_compiled_convolution_op, _jit_compiled_convolution_op, _jit_compiled_convolution_op, _jit_compiled_convolution_op, _jit_compiled_convolution_op while saving (showing 5 of 196). These functions will not be directly callable after loading.\n"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "INFO:tensorflow:Assets written to: C:\\Users\\24306\\Desktop\\NASNetMobile\\0\\NASNetMobile.ckpt\\assets\n"
     ]
    },
    {
     "name": "stderr",
     "output_type": "stream",
     "text": [
      "INFO:tensorflow:Assets written to: C:\\Users\\24306\\Desktop\\NASNetMobile\\0\\NASNetMobile.ckpt\\assets\n"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "591/591 [==============================] - 202s 343ms/step - loss: 0.1007 - val_loss: 1.1661\n",
      "Epoch 23/300\n",
      "591/591 [==============================] - 116s 196ms/step - loss: 0.0883 - val_loss: 1.4393\n",
      "Epoch 24/300\n",
      "591/591 [==============================] - ETA: 0s - loss: 0.0879"
     ]
    },
    {
     "name": "stderr",
     "output_type": "stream",
     "text": [
      "WARNING:absl:Found untraced functions such as _jit_compiled_convolution_op, _jit_compiled_convolution_op, _jit_compiled_convolution_op, _jit_compiled_convolution_op, _jit_compiled_convolution_op while saving (showing 5 of 196). These functions will not be directly callable after loading.\n"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "INFO:tensorflow:Assets written to: C:\\Users\\24306\\Desktop\\NASNetMobile\\0\\NASNetMobile.ckpt\\assets\n"
     ]
    },
    {
     "name": "stderr",
     "output_type": "stream",
     "text": [
      "INFO:tensorflow:Assets written to: C:\\Users\\24306\\Desktop\\NASNetMobile\\0\\NASNetMobile.ckpt\\assets\n"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "591/591 [==============================] - 202s 341ms/step - loss: 0.0879 - val_loss: 1.0965\n",
      "Epoch 25/300\n",
      "591/591 [==============================] - ETA: 0s - loss: 0.0914"
     ]
    },
    {
     "name": "stderr",
     "output_type": "stream",
     "text": [
      "WARNING:absl:Found untraced functions such as _jit_compiled_convolution_op, _jit_compiled_convolution_op, _jit_compiled_convolution_op, _jit_compiled_convolution_op, _jit_compiled_convolution_op while saving (showing 5 of 196). These functions will not be directly callable after loading.\n"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "INFO:tensorflow:Assets written to: C:\\Users\\24306\\Desktop\\NASNetMobile\\0\\NASNetMobile.ckpt\\assets\n"
     ]
    },
    {
     "name": "stderr",
     "output_type": "stream",
     "text": [
      "INFO:tensorflow:Assets written to: C:\\Users\\24306\\Desktop\\NASNetMobile\\0\\NASNetMobile.ckpt\\assets\n"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "591/591 [==============================] - 203s 343ms/step - loss: 0.0914 - val_loss: 0.9074\n",
      "Epoch 26/300\n",
      "591/591 [==============================] - ETA: 0s - loss: 0.0734"
     ]
    },
    {
     "name": "stderr",
     "output_type": "stream",
     "text": [
      "WARNING:absl:Found untraced functions such as _jit_compiled_convolution_op, _jit_compiled_convolution_op, _jit_compiled_convolution_op, _jit_compiled_convolution_op, _jit_compiled_convolution_op while saving (showing 5 of 196). These functions will not be directly callable after loading.\n"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "INFO:tensorflow:Assets written to: C:\\Users\\24306\\Desktop\\NASNetMobile\\0\\NASNetMobile.ckpt\\assets\n"
     ]
    },
    {
     "name": "stderr",
     "output_type": "stream",
     "text": [
      "INFO:tensorflow:Assets written to: C:\\Users\\24306\\Desktop\\NASNetMobile\\0\\NASNetMobile.ckpt\\assets\n"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "591/591 [==============================] - 206s 348ms/step - loss: 0.0734 - val_loss: 0.6575\n",
      "Epoch 27/300\n",
      "591/591 [==============================] - ETA: 0s - loss: 0.0842"
     ]
    },
    {
     "name": "stderr",
     "output_type": "stream",
     "text": [
      "WARNING:absl:Found untraced functions such as _jit_compiled_convolution_op, _jit_compiled_convolution_op, _jit_compiled_convolution_op, _jit_compiled_convolution_op, _jit_compiled_convolution_op while saving (showing 5 of 196). These functions will not be directly callable after loading.\n"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "INFO:tensorflow:Assets written to: C:\\Users\\24306\\Desktop\\NASNetMobile\\0\\NASNetMobile.ckpt\\assets\n"
     ]
    },
    {
     "name": "stderr",
     "output_type": "stream",
     "text": [
      "INFO:tensorflow:Assets written to: C:\\Users\\24306\\Desktop\\NASNetMobile\\0\\NASNetMobile.ckpt\\assets\n"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "591/591 [==============================] - 209s 354ms/step - loss: 0.0842 - val_loss: 0.4431\n",
      "Epoch 28/300\n",
      "591/591 [==============================] - ETA: 0s - loss: 0.0707"
     ]
    },
    {
     "name": "stderr",
     "output_type": "stream",
     "text": [
      "WARNING:absl:Found untraced functions such as _jit_compiled_convolution_op, _jit_compiled_convolution_op, _jit_compiled_convolution_op, _jit_compiled_convolution_op, _jit_compiled_convolution_op while saving (showing 5 of 196). These functions will not be directly callable after loading.\n"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "INFO:tensorflow:Assets written to: C:\\Users\\24306\\Desktop\\NASNetMobile\\0\\NASNetMobile.ckpt\\assets\n"
     ]
    },
    {
     "name": "stderr",
     "output_type": "stream",
     "text": [
      "INFO:tensorflow:Assets written to: C:\\Users\\24306\\Desktop\\NASNetMobile\\0\\NASNetMobile.ckpt\\assets\n"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "591/591 [==============================] - 212s 359ms/step - loss: 0.0707 - val_loss: 0.3467\n",
      "Epoch 29/300\n",
      "591/591 [==============================] - ETA: 0s - loss: 0.0792"
     ]
    },
    {
     "name": "stderr",
     "output_type": "stream",
     "text": [
      "WARNING:absl:Found untraced functions such as _jit_compiled_convolution_op, _jit_compiled_convolution_op, _jit_compiled_convolution_op, _jit_compiled_convolution_op, _jit_compiled_convolution_op while saving (showing 5 of 196). These functions will not be directly callable after loading.\n"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "INFO:tensorflow:Assets written to: C:\\Users\\24306\\Desktop\\NASNetMobile\\0\\NASNetMobile.ckpt\\assets\n"
     ]
    },
    {
     "name": "stderr",
     "output_type": "stream",
     "text": [
      "INFO:tensorflow:Assets written to: C:\\Users\\24306\\Desktop\\NASNetMobile\\0\\NASNetMobile.ckpt\\assets\n"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "591/591 [==============================] - 211s 357ms/step - loss: 0.0792 - val_loss: 0.3000\n",
      "Epoch 30/300\n",
      "591/591 [==============================] - 122s 206ms/step - loss: 0.0856 - val_loss: 0.3729\n",
      "Epoch 31/300\n",
      "591/591 [==============================] - 119s 202ms/step - loss: 0.0716 - val_loss: 0.3735\n",
      "Epoch 32/300\n",
      "591/591 [==============================] - 119s 202ms/step - loss: 0.0684 - val_loss: 0.3443\n",
      "Epoch 33/300\n",
      "591/591 [==============================] - ETA: 0s - loss: 0.0646"
     ]
    },
    {
     "name": "stderr",
     "output_type": "stream",
     "text": [
      "WARNING:absl:Found untraced functions such as _jit_compiled_convolution_op, _jit_compiled_convolution_op, _jit_compiled_convolution_op, _jit_compiled_convolution_op, _jit_compiled_convolution_op while saving (showing 5 of 196). These functions will not be directly callable after loading.\n"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "INFO:tensorflow:Assets written to: C:\\Users\\24306\\Desktop\\NASNetMobile\\0\\NASNetMobile.ckpt\\assets\n"
     ]
    },
    {
     "name": "stderr",
     "output_type": "stream",
     "text": [
      "INFO:tensorflow:Assets written to: C:\\Users\\24306\\Desktop\\NASNetMobile\\0\\NASNetMobile.ckpt\\assets\n"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "591/591 [==============================] - 211s 356ms/step - loss: 0.0646 - val_loss: 0.1484\n",
      "Epoch 34/300\n",
      "591/591 [==============================] - 124s 209ms/step - loss: 0.0645 - val_loss: 0.3397\n",
      "Epoch 35/300\n",
      "591/591 [==============================] - 136s 231ms/step - loss: 0.0615 - val_loss: 0.2322\n",
      "Epoch 36/300\n",
      "591/591 [==============================] - 157s 266ms/step - loss: 0.0689 - val_loss: 0.3685\n",
      "Epoch 37/300\n",
      "591/591 [==============================] - 157s 265ms/step - loss: 0.0756 - val_loss: 0.1964\n",
      "Epoch 38/300\n",
      "591/591 [==============================] - 157s 265ms/step - loss: 0.0752 - val_loss: 0.2686\n",
      "Epoch 39/300\n",
      "591/591 [==============================] - 157s 265ms/step - loss: 0.0770 - val_loss: 0.5982\n",
      "Epoch 40/300\n",
      "591/591 [==============================] - 156s 264ms/step - loss: 0.0779 - val_loss: 0.2914\n",
      "Epoch 41/300\n",
      "591/591 [==============================] - 158s 267ms/step - loss: 0.0549 - val_loss: 0.2808\n",
      "Epoch 42/300\n",
      "591/591 [==============================] - 157s 266ms/step - loss: 0.0604 - val_loss: 0.1700\n",
      "Epoch 43/300\n",
      "591/591 [==============================] - 157s 266ms/step - loss: 0.0534 - val_loss: 0.3130\n",
      "Epoch 44/300\n",
      "591/591 [==============================] - 157s 266ms/step - loss: 0.0620 - val_loss: 0.1821\n",
      "Epoch 45/300\n",
      "591/591 [==============================] - ETA: 0s - loss: 0.0741"
     ]
    },
    {
     "name": "stderr",
     "output_type": "stream",
     "text": [
      "WARNING:absl:Found untraced functions such as _jit_compiled_convolution_op, _jit_compiled_convolution_op, _jit_compiled_convolution_op, _jit_compiled_convolution_op, _jit_compiled_convolution_op while saving (showing 5 of 196). These functions will not be directly callable after loading.\n"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "INFO:tensorflow:Assets written to: C:\\Users\\24306\\Desktop\\NASNetMobile\\0\\NASNetMobile.ckpt\\assets\n"
     ]
    },
    {
     "name": "stderr",
     "output_type": "stream",
     "text": [
      "INFO:tensorflow:Assets written to: C:\\Users\\24306\\Desktop\\NASNetMobile\\0\\NASNetMobile.ckpt\\assets\n"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "591/591 [==============================] - 250s 423ms/step - loss: 0.0741 - val_loss: 0.1348\n",
      "Epoch 46/300\n",
      "591/591 [==============================] - ETA: 0s - loss: 0.0577"
     ]
    },
    {
     "name": "stderr",
     "output_type": "stream",
     "text": [
      "WARNING:absl:Found untraced functions such as _jit_compiled_convolution_op, _jit_compiled_convolution_op, _jit_compiled_convolution_op, _jit_compiled_convolution_op, _jit_compiled_convolution_op while saving (showing 5 of 196). These functions will not be directly callable after loading.\n"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "INFO:tensorflow:Assets written to: C:\\Users\\24306\\Desktop\\NASNetMobile\\0\\NASNetMobile.ckpt\\assets\n"
     ]
    },
    {
     "name": "stderr",
     "output_type": "stream",
     "text": [
      "INFO:tensorflow:Assets written to: C:\\Users\\24306\\Desktop\\NASNetMobile\\0\\NASNetMobile.ckpt\\assets\n"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "591/591 [==============================] - 257s 435ms/step - loss: 0.0577 - val_loss: 0.0784\n",
      "Epoch 47/300\n",
      "591/591 [==============================] - 163s 276ms/step - loss: 0.0633 - val_loss: 0.1605\n",
      "Epoch 48/300\n",
      "591/591 [==============================] - 151s 256ms/step - loss: 0.0529 - val_loss: 0.1661\n",
      "Epoch 49/300\n",
      "591/591 [==============================] - 124s 209ms/step - loss: 0.0478 - val_loss: 0.1156\n",
      "Epoch 50/300\n",
      "591/591 [==============================] - 124s 210ms/step - loss: 0.0536 - val_loss: 0.1068\n",
      "Epoch 51/300\n",
      "591/591 [==============================] - 124s 209ms/step - loss: 0.0520 - val_loss: 0.1642\n",
      "Epoch 52/300\n",
      "591/591 [==============================] - 124s 209ms/step - loss: 0.0577 - val_loss: 0.1115\n",
      "Epoch 53/300\n",
      "591/591 [==============================] - 124s 209ms/step - loss: 0.0504 - val_loss: 0.1523\n",
      "Epoch 54/300\n",
      "591/591 [==============================] - 124s 210ms/step - loss: 0.0527 - val_loss: 0.1507\n",
      "Epoch 55/300\n",
      "591/591 [==============================] - 124s 210ms/step - loss: 0.0499 - val_loss: 0.0791\n",
      "Epoch 56/300\n",
      "591/591 [==============================] - ETA: 0s - loss: 0.1146"
     ]
    },
    {
     "name": "stderr",
     "output_type": "stream",
     "text": [
      "WARNING:absl:Found untraced functions such as _jit_compiled_convolution_op, _jit_compiled_convolution_op, _jit_compiled_convolution_op, _jit_compiled_convolution_op, _jit_compiled_convolution_op while saving (showing 5 of 196). These functions will not be directly callable after loading.\n"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "INFO:tensorflow:Assets written to: C:\\Users\\24306\\Desktop\\NASNetMobile\\0\\NASNetMobile.ckpt\\assets\n"
     ]
    },
    {
     "name": "stderr",
     "output_type": "stream",
     "text": [
      "INFO:tensorflow:Assets written to: C:\\Users\\24306\\Desktop\\NASNetMobile\\0\\NASNetMobile.ckpt\\assets\n"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "591/591 [==============================] - 213s 360ms/step - loss: 0.1146 - val_loss: 0.0782\n",
      "Epoch 57/300\n",
      "591/591 [==============================] - ETA: 0s - loss: 0.0466"
     ]
    },
    {
     "name": "stderr",
     "output_type": "stream",
     "text": [
      "WARNING:absl:Found untraced functions such as _jit_compiled_convolution_op, _jit_compiled_convolution_op, _jit_compiled_convolution_op, _jit_compiled_convolution_op, _jit_compiled_convolution_op while saving (showing 5 of 196). These functions will not be directly callable after loading.\n"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "INFO:tensorflow:Assets written to: C:\\Users\\24306\\Desktop\\NASNetMobile\\0\\NASNetMobile.ckpt\\assets\n"
     ]
    },
    {
     "name": "stderr",
     "output_type": "stream",
     "text": [
      "INFO:tensorflow:Assets written to: C:\\Users\\24306\\Desktop\\NASNetMobile\\0\\NASNetMobile.ckpt\\assets\n"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "591/591 [==============================] - 217s 368ms/step - loss: 0.0466 - val_loss: 0.0701\n",
      "Epoch 58/300\n",
      "591/591 [==============================] - 131s 220ms/step - loss: 0.0635 - val_loss: 0.0834\n",
      "Epoch 59/300\n",
      "591/591 [==============================] - ETA: 0s - loss: 0.0580"
     ]
    },
    {
     "name": "stderr",
     "output_type": "stream",
     "text": [
      "WARNING:absl:Found untraced functions such as _jit_compiled_convolution_op, _jit_compiled_convolution_op, _jit_compiled_convolution_op, _jit_compiled_convolution_op, _jit_compiled_convolution_op while saving (showing 5 of 196). These functions will not be directly callable after loading.\n"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "INFO:tensorflow:Assets written to: C:\\Users\\24306\\Desktop\\NASNetMobile\\0\\NASNetMobile.ckpt\\assets\n"
     ]
    },
    {
     "name": "stderr",
     "output_type": "stream",
     "text": [
      "INFO:tensorflow:Assets written to: C:\\Users\\24306\\Desktop\\NASNetMobile\\0\\NASNetMobile.ckpt\\assets\n"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "591/591 [==============================] - 218s 369ms/step - loss: 0.0580 - val_loss: 0.0591\n",
      "Epoch 60/300\n",
      "591/591 [==============================] - 131s 221ms/step - loss: 0.0501 - val_loss: 0.0678\n",
      "Epoch 61/300\n",
      "591/591 [==============================] - 129s 218ms/step - loss: 0.0458 - val_loss: 0.0969\n",
      "Epoch 62/300\n",
      "591/591 [==============================] - 129s 218ms/step - loss: 0.0441 - val_loss: 0.1114\n",
      "Epoch 63/300\n",
      "591/591 [==============================] - 128s 217ms/step - loss: 0.0553 - val_loss: 0.0813\n",
      "Epoch 64/300\n",
      "591/591 [==============================] - 128s 217ms/step - loss: 0.0407 - val_loss: 0.1131\n",
      "Epoch 65/300\n",
      "591/591 [==============================] - 129s 218ms/step - loss: 0.0410 - val_loss: 0.0796\n",
      "Epoch 66/300\n",
      "591/591 [==============================] - 128s 217ms/step - loss: 0.0397 - val_loss: 0.1377\n",
      "Epoch 67/300\n",
      "591/591 [==============================] - 129s 218ms/step - loss: 0.0402 - val_loss: 0.0907\n",
      "Epoch 68/300\n",
      "591/591 [==============================] - 129s 219ms/step - loss: 0.0413 - val_loss: 0.1163\n",
      "Epoch 69/300\n",
      "591/591 [==============================] - 130s 219ms/step - loss: 0.0425 - val_loss: 0.0842\n",
      "Epoch 70/300\n",
      "591/591 [==============================] - 129s 218ms/step - loss: 0.0397 - val_loss: 0.1207\n",
      "Epoch 71/300\n",
      "591/591 [==============================] - 129s 219ms/step - loss: 0.0450 - val_loss: 0.0893\n",
      "Epoch 72/300\n",
      "591/591 [==============================] - 129s 218ms/step - loss: 0.0391 - val_loss: 0.0928\n",
      "Epoch 73/300\n",
      "591/591 [==============================] - 130s 219ms/step - loss: 0.0390 - val_loss: 0.0945\n",
      "Epoch 74/300\n",
      "591/591 [==============================] - 130s 220ms/step - loss: 0.0387 - val_loss: 0.0593\n",
      "Epoch 75/300\n",
      "591/591 [==============================] - 130s 220ms/step - loss: 0.0687 - val_loss: 0.0667\n",
      "Epoch 76/300\n",
      "591/591 [==============================] - 130s 219ms/step - loss: 0.0395 - val_loss: 0.0757\n",
      "Epoch 77/300\n",
      "591/591 [==============================] - 130s 219ms/step - loss: 0.0510 - val_loss: 0.0594\n",
      "Epoch 78/300\n",
      "591/591 [==============================] - 130s 220ms/step - loss: 0.0410 - val_loss: 0.0929\n",
      "Epoch 79/300\n",
      "591/591 [==============================] - 130s 220ms/step - loss: 0.0421 - val_loss: 0.0630\n",
      "Epoch 80/300\n",
      "591/591 [==============================] - 131s 221ms/step - loss: 0.0436 - val_loss: 0.0711\n",
      "Epoch 81/300\n",
      "591/591 [==============================] - ETA: 0s - loss: 0.0386"
     ]
    },
    {
     "name": "stderr",
     "output_type": "stream",
     "text": [
      "WARNING:absl:Found untraced functions such as _jit_compiled_convolution_op, _jit_compiled_convolution_op, _jit_compiled_convolution_op, _jit_compiled_convolution_op, _jit_compiled_convolution_op while saving (showing 5 of 196). These functions will not be directly callable after loading.\n"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "INFO:tensorflow:Assets written to: C:\\Users\\24306\\Desktop\\NASNetMobile\\0\\NASNetMobile.ckpt\\assets\n"
     ]
    },
    {
     "name": "stderr",
     "output_type": "stream",
     "text": [
      "INFO:tensorflow:Assets written to: C:\\Users\\24306\\Desktop\\NASNetMobile\\0\\NASNetMobile.ckpt\\assets\n"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "591/591 [==============================] - 220s 373ms/step - loss: 0.0386 - val_loss: 0.0552\n",
      "Epoch 82/300\n",
      "591/591 [==============================] - 133s 225ms/step - loss: 0.0391 - val_loss: 0.1100\n",
      "Epoch 83/300\n",
      "591/591 [==============================] - 133s 224ms/step - loss: 0.0528 - val_loss: 0.0621\n",
      "Epoch 84/300\n",
      "591/591 [==============================] - 133s 224ms/step - loss: 0.0498 - val_loss: 0.1174\n",
      "Epoch 85/300\n",
      "591/591 [==============================] - 132s 223ms/step - loss: 0.1743 - val_loss: 0.0747\n",
      "Epoch 86/300\n",
      "591/591 [==============================] - 132s 223ms/step - loss: 0.0372 - val_loss: 0.1219\n",
      "Epoch 87/300\n",
      "591/591 [==============================] - 132s 224ms/step - loss: 0.0530 - val_loss: 0.0798\n",
      "Epoch 88/300\n",
      "591/591 [==============================] - 132s 224ms/step - loss: 0.0345 - val_loss: 0.1120\n",
      "Epoch 89/300\n",
      "591/591 [==============================] - 133s 225ms/step - loss: 0.0411 - val_loss: 0.1093\n",
      "Epoch 90/300\n",
      "591/591 [==============================] - 132s 223ms/step - loss: 0.0372 - val_loss: 0.1139\n",
      "Epoch 91/300\n",
      "591/591 [==============================] - 132s 223ms/step - loss: 0.0649 - val_loss: 0.1470\n",
      "Epoch 92/300\n",
      "591/591 [==============================] - 132s 224ms/step - loss: 0.0382 - val_loss: 0.1057\n",
      "Epoch 93/300\n",
      "591/591 [==============================] - 132s 224ms/step - loss: 0.0363 - val_loss: 0.1346\n",
      "Epoch 94/300\n",
      "591/591 [==============================] - 132s 223ms/step - loss: 0.0361 - val_loss: 0.1005\n",
      "Epoch 95/300\n",
      "591/591 [==============================] - 132s 224ms/step - loss: 0.0331 - val_loss: 0.1139\n",
      "Epoch 96/300\n",
      "591/591 [==============================] - 132s 223ms/step - loss: 0.0347 - val_loss: 0.0714\n",
      "Epoch 97/300\n",
      "591/591 [==============================] - 133s 225ms/step - loss: 0.0355 - val_loss: 0.0586\n",
      "Epoch 98/300\n",
      "591/591 [==============================] - 133s 225ms/step - loss: 0.0388 - val_loss: 0.0837\n",
      "Epoch 99/300\n",
      "591/591 [==============================] - 133s 225ms/step - loss: 0.0380 - val_loss: 0.1308\n",
      "Epoch 100/300\n",
      "591/591 [==============================] - 134s 226ms/step - loss: 0.0369 - val_loss: 0.1358\n",
      "Epoch 101/300\n",
      "591/591 [==============================] - 133s 225ms/step - loss: 0.0353 - val_loss: 0.0908\n",
      "Epoch 102/300\n",
      "591/591 [==============================] - 133s 225ms/step - loss: 0.0335 - val_loss: 0.0650\n",
      "Epoch 103/300\n",
      "591/591 [==============================] - 133s 225ms/step - loss: 0.0330 - val_loss: 0.1111\n",
      "Epoch 104/300\n",
      "591/591 [==============================] - 133s 224ms/step - loss: 0.0355 - val_loss: 0.1135\n",
      "Epoch 105/300\n",
      "591/591 [==============================] - 133s 225ms/step - loss: 0.0354 - val_loss: 0.0944\n",
      "Epoch 106/300\n",
      "591/591 [==============================] - 133s 225ms/step - loss: 0.0374 - val_loss: 0.0840\n",
      "Epoch 107/300\n",
      "591/591 [==============================] - 133s 225ms/step - loss: 0.0399 - val_loss: 0.1048\n",
      "Epoch 108/300\n",
      "591/591 [==============================] - 133s 226ms/step - loss: 0.0338 - val_loss: 0.0716\n",
      "Epoch 109/300\n",
      "591/591 [==============================] - 133s 225ms/step - loss: 0.0433 - val_loss: 0.0914\n",
      "Epoch 110/300\n",
      "591/591 [==============================] - 133s 225ms/step - loss: 0.0369 - val_loss: 0.0905\n",
      "Epoch 111/300\n",
      "591/591 [==============================] - 134s 226ms/step - loss: 0.0365 - val_loss: 0.1020\n",
      "Epoch 112/300\n",
      "591/591 [==============================] - 134s 226ms/step - loss: 0.0383 - val_loss: 0.0716\n",
      "Epoch 113/300\n",
      "591/591 [==============================] - 133s 226ms/step - loss: 0.0322 - val_loss: 0.0958\n",
      "Epoch 114/300\n",
      "591/591 [==============================] - 134s 226ms/step - loss: 0.0460 - val_loss: 0.0653\n",
      "Epoch 115/300\n",
      "591/591 [==============================] - 134s 226ms/step - loss: 0.0334 - val_loss: 0.0631\n",
      "Epoch 116/300\n",
      "591/591 [==============================] - 134s 226ms/step - loss: 0.0321 - val_loss: 0.0679\n",
      "Epoch 117/300\n",
      "591/591 [==============================] - 133s 225ms/step - loss: 0.0557 - val_loss: 0.0579\n",
      "Epoch 118/300\n",
      "591/591 [==============================] - 133s 225ms/step - loss: 0.0364 - val_loss: 0.0787\n",
      "Epoch 119/300\n",
      "591/591 [==============================] - 134s 227ms/step - loss: 0.0342 - val_loss: 0.0891\n",
      "Epoch 120/300\n",
      "591/591 [==============================] - 133s 226ms/step - loss: 0.0529 - val_loss: 0.0780\n",
      "Epoch 121/300\n",
      "591/591 [==============================] - 134s 226ms/step - loss: 0.0354 - val_loss: 0.0924\n",
      "Epoch 122/300\n",
      "591/591 [==============================] - 133s 225ms/step - loss: 0.0316 - val_loss: 0.0771\n",
      "Epoch 123/300\n",
      "591/591 [==============================] - 133s 225ms/step - loss: 0.0311 - val_loss: 0.0821\n",
      "Epoch 124/300\n",
      "591/591 [==============================] - 134s 226ms/step - loss: 0.0302 - val_loss: 0.0951\n",
      "Epoch 125/300\n",
      "591/591 [==============================] - 134s 226ms/step - loss: 0.0315 - val_loss: 0.0642\n",
      "Epoch 126/300\n",
      "591/591 [==============================] - 134s 226ms/step - loss: 0.0318 - val_loss: 0.1044\n",
      "Epoch 127/300\n",
      "591/591 [==============================] - 134s 227ms/step - loss: 0.0345 - val_loss: 0.0738\n",
      "Epoch 128/300\n",
      "591/591 [==============================] - 134s 226ms/step - loss: 0.0339 - val_loss: 0.0791\n",
      "Epoch 129/300\n",
      "591/591 [==============================] - 134s 227ms/step - loss: 0.0340 - val_loss: 0.0602\n",
      "Epoch 130/300\n",
      "591/591 [==============================] - 134s 226ms/step - loss: 0.0340 - val_loss: 0.0599\n",
      "Epoch 131/300\n",
      "591/591 [==============================] - 134s 226ms/step - loss: 0.0401 - val_loss: 0.1603\n",
      "Epoch 132/300\n",
      "591/591 [==============================] - 134s 226ms/step - loss: 0.0286 - val_loss: 0.1123\n",
      "Epoch 133/300\n",
      "591/591 [==============================] - 134s 226ms/step - loss: 0.0386 - val_loss: 0.1259\n",
      "Epoch 134/300\n",
      "591/591 [==============================] - 134s 227ms/step - loss: 0.0319 - val_loss: 0.0939\n",
      "Epoch 135/300\n",
      "591/591 [==============================] - 134s 226ms/step - loss: 0.0295 - val_loss: 0.1071\n",
      "Epoch 136/300\n",
      "591/591 [==============================] - 134s 226ms/step - loss: 0.0311 - val_loss: 0.1099\n",
      "Epoch 137/300\n",
      "591/591 [==============================] - 134s 227ms/step - loss: 0.0313 - val_loss: 0.1094\n",
      "Epoch 138/300\n",
      "591/591 [==============================] - 134s 227ms/step - loss: 0.0305 - val_loss: 0.1002\n",
      "Epoch 139/300\n",
      "591/591 [==============================] - 133s 225ms/step - loss: 0.0289 - val_loss: 0.1050\n",
      "Epoch 140/300\n",
      "591/591 [==============================] - 134s 226ms/step - loss: 0.0335 - val_loss: 0.0851\n",
      "Epoch 141/300\n",
      "591/591 [==============================] - 134s 226ms/step - loss: 0.0390 - val_loss: 0.0838\n",
      "Epoch 142/300\n",
      "591/591 [==============================] - 133s 226ms/step - loss: 0.0331 - val_loss: 0.0820\n",
      "Epoch 143/300\n",
      "591/591 [==============================] - 133s 225ms/step - loss: 0.0297 - val_loss: 0.0893\n",
      "Epoch 144/300\n",
      "591/591 [==============================] - 133s 225ms/step - loss: 0.0290 - val_loss: 0.0687\n",
      "Epoch 145/300\n",
      "591/591 [==============================] - 134s 226ms/step - loss: 0.0368 - val_loss: 0.0556\n",
      "Epoch 146/300\n",
      "591/591 [==============================] - 134s 226ms/step - loss: 0.0328 - val_loss: 0.0758\n",
      "Epoch 147/300\n",
      "591/591 [==============================] - 135s 228ms/step - loss: 0.0318 - val_loss: 0.0941\n",
      "Epoch 148/300\n",
      "591/591 [==============================] - 133s 226ms/step - loss: 0.0375 - val_loss: 0.0676\n",
      "Epoch 149/300\n",
      "591/591 [==============================] - 134s 226ms/step - loss: 0.0300 - val_loss: 0.0782\n",
      "Epoch 150/300\n",
      "591/591 [==============================] - 134s 226ms/step - loss: 0.0633 - val_loss: 0.0642\n",
      "Epoch 151/300\n",
      "591/591 [==============================] - 134s 226ms/step - loss: 0.0311 - val_loss: 0.0573\n",
      "Epoch 152/300\n",
      "591/591 [==============================] - ETA: 0s - loss: 0.0371"
     ]
    },
    {
     "name": "stderr",
     "output_type": "stream",
     "text": [
      "WARNING:absl:Found untraced functions such as _jit_compiled_convolution_op, _jit_compiled_convolution_op, _jit_compiled_convolution_op, _jit_compiled_convolution_op, _jit_compiled_convolution_op while saving (showing 5 of 196). These functions will not be directly callable after loading.\n"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "INFO:tensorflow:Assets written to: C:\\Users\\24306\\Desktop\\NASNetMobile\\0\\NASNetMobile.ckpt\\assets\n"
     ]
    },
    {
     "name": "stderr",
     "output_type": "stream",
     "text": [
      "INFO:tensorflow:Assets written to: C:\\Users\\24306\\Desktop\\NASNetMobile\\0\\NASNetMobile.ckpt\\assets\n"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "591/591 [==============================] - 226s 382ms/step - loss: 0.0371 - val_loss: 0.0515\n",
      "Epoch 153/300\n",
      "591/591 [==============================] - 141s 238ms/step - loss: 0.0307 - val_loss: 0.0823\n",
      "Epoch 154/300\n",
      "591/591 [==============================] - 138s 233ms/step - loss: 0.0331 - val_loss: 0.0664\n",
      "Epoch 155/300\n",
      "591/591 [==============================] - 138s 233ms/step - loss: 0.0279 - val_loss: 0.0900\n",
      "Epoch 156/300\n",
      "591/591 [==============================] - 139s 235ms/step - loss: 0.0345 - val_loss: 0.0896\n",
      "Epoch 157/300\n",
      "591/591 [==============================] - 137s 232ms/step - loss: 0.0285 - val_loss: 0.0682\n",
      "Epoch 158/300\n",
      "591/591 [==============================] - 139s 234ms/step - loss: 0.0316 - val_loss: 0.1041\n",
      "Epoch 159/300\n",
      "591/591 [==============================] - 139s 235ms/step - loss: 0.0264 - val_loss: 0.0682\n",
      "Epoch 160/300\n",
      "591/591 [==============================] - 138s 233ms/step - loss: 0.0502 - val_loss: 0.1221\n",
      "Epoch 161/300\n",
      "591/591 [==============================] - 139s 234ms/step - loss: 0.0303 - val_loss: 0.0821\n",
      "Epoch 162/300\n",
      "591/591 [==============================] - 139s 235ms/step - loss: 0.0283 - val_loss: 0.0942\n",
      "Epoch 163/300\n",
      "591/591 [==============================] - 139s 234ms/step - loss: 0.0401 - val_loss: 0.0979\n",
      "Epoch 164/300\n",
      "591/591 [==============================] - 139s 235ms/step - loss: 0.0312 - val_loss: 0.0949\n",
      "Epoch 165/300\n",
      "591/591 [==============================] - 138s 234ms/step - loss: 0.0273 - val_loss: 0.0903\n",
      "Epoch 166/300\n",
      "591/591 [==============================] - 139s 235ms/step - loss: 0.0260 - val_loss: 0.0760\n",
      "Epoch 167/300\n",
      "591/591 [==============================] - 139s 235ms/step - loss: 0.0313 - val_loss: 0.0855\n",
      "Epoch 168/300\n",
      "591/591 [==============================] - 138s 234ms/step - loss: 0.0373 - val_loss: 0.0804\n",
      "Epoch 169/300\n",
      "591/591 [==============================] - 139s 234ms/step - loss: 0.0287 - val_loss: 0.0913\n",
      "Epoch 170/300\n",
      "591/591 [==============================] - 138s 234ms/step - loss: 0.0282 - val_loss: 0.0751\n",
      "Epoch 171/300\n",
      "591/591 [==============================] - 139s 234ms/step - loss: 0.0392 - val_loss: 0.0565\n",
      "Epoch 172/300\n",
      "591/591 [==============================] - 140s 236ms/step - loss: 0.0267 - val_loss: 0.0754\n",
      "Epoch 173/300\n",
      "591/591 [==============================] - 139s 235ms/step - loss: 0.0279 - val_loss: 0.0764\n",
      "Epoch 174/300\n",
      "591/591 [==============================] - 139s 235ms/step - loss: 0.0301 - val_loss: 0.0726\n",
      "Epoch 175/300\n",
      "591/591 [==============================] - 139s 235ms/step - loss: 0.0253 - val_loss: 0.0704\n",
      "Epoch 176/300\n",
      "591/591 [==============================] - 139s 236ms/step - loss: 0.0257 - val_loss: 0.0979\n",
      "Epoch 177/300\n",
      "591/591 [==============================] - 139s 235ms/step - loss: 0.0255 - val_loss: 0.0878\n",
      "Epoch 178/300\n",
      "591/591 [==============================] - 139s 235ms/step - loss: 0.0308 - val_loss: 0.0997\n",
      "Epoch 179/300\n",
      "591/591 [==============================] - 140s 236ms/step - loss: 0.0316 - val_loss: 0.0755\n",
      "Epoch 180/300\n",
      "591/591 [==============================] - 139s 236ms/step - loss: 0.0303 - val_loss: 0.0821\n",
      "Epoch 181/300\n",
      "591/591 [==============================] - 139s 235ms/step - loss: 0.0294 - val_loss: 0.0786\n",
      "Epoch 182/300\n",
      "591/591 [==============================] - 140s 236ms/step - loss: 0.0287 - val_loss: 0.0772\n",
      "Epoch 183/300\n",
      "591/591 [==============================] - 139s 235ms/step - loss: 0.0261 - val_loss: 0.0575\n",
      "Epoch 184/300\n",
      "591/591 [==============================] - 140s 237ms/step - loss: 0.0341 - val_loss: 0.0845\n",
      "Epoch 185/300\n",
      "591/591 [==============================] - 140s 236ms/step - loss: 0.0269 - val_loss: 0.0713\n",
      "Epoch 186/300\n",
      "591/591 [==============================] - 139s 235ms/step - loss: 0.0263 - val_loss: 0.1053\n",
      "Epoch 187/300\n",
      "591/591 [==============================] - 140s 237ms/step - loss: 0.0249 - val_loss: 0.0924\n",
      "Epoch 188/300\n",
      "591/591 [==============================] - 140s 237ms/step - loss: 0.0328 - val_loss: 0.0727\n",
      "Epoch 189/300\n",
      "591/591 [==============================] - 140s 237ms/step - loss: 0.0280 - val_loss: 0.0574\n",
      "Epoch 190/300\n",
      "591/591 [==============================] - 140s 237ms/step - loss: 0.0257 - val_loss: 0.0607\n",
      "Epoch 191/300\n",
      "591/591 [==============================] - 140s 237ms/step - loss: 0.0262 - val_loss: 0.0671\n",
      "Epoch 192/300\n",
      "591/591 [==============================] - 140s 237ms/step - loss: 0.0630 - val_loss: 0.0948\n",
      "Epoch 193/300\n",
      "591/591 [==============================] - 140s 237ms/step - loss: 0.0315 - val_loss: 0.0565\n",
      "Epoch 194/300\n",
      "591/591 [==============================] - 140s 237ms/step - loss: 0.0255 - val_loss: 0.0712\n",
      "Epoch 195/300\n",
      "591/591 [==============================] - 140s 236ms/step - loss: 0.0278 - val_loss: 0.0866\n",
      "Epoch 196/300\n",
      "591/591 [==============================] - 141s 238ms/step - loss: 0.0248 - val_loss: 0.0777\n",
      "Epoch 197/300\n",
      "591/591 [==============================] - 141s 238ms/step - loss: 0.0268 - val_loss: 0.0721\n",
      "Epoch 198/300\n",
      "591/591 [==============================] - 141s 238ms/step - loss: 0.0267 - val_loss: 0.1068\n",
      "Epoch 199/300\n",
      "591/591 [==============================] - 140s 237ms/step - loss: 0.0310 - val_loss: 0.0915\n",
      "Epoch 200/300\n",
      "591/591 [==============================] - 141s 238ms/step - loss: 0.0281 - val_loss: 0.0557\n",
      "Epoch 201/300\n",
      "591/591 [==============================] - 140s 237ms/step - loss: 0.0265 - val_loss: 0.0799\n",
      "Epoch 202/300\n",
      "591/591 [==============================] - 141s 238ms/step - loss: 0.0384 - val_loss: 0.0643\n",
      "Epoch 203/300\n",
      "591/591 [==============================] - 140s 236ms/step - loss: 0.0250 - val_loss: 0.0697\n",
      "Epoch 204/300\n",
      "591/591 [==============================] - 140s 237ms/step - loss: 0.0324 - val_loss: 0.0641\n",
      "Epoch 205/300\n",
      "591/591 [==============================] - 141s 238ms/step - loss: 0.0261 - val_loss: 0.0717\n",
      "Epoch 206/300\n",
      "591/591 [==============================] - 140s 237ms/step - loss: 0.0267 - val_loss: 0.0705\n",
      "Epoch 207/300\n",
      "591/591 [==============================] - 140s 237ms/step - loss: 0.0257 - val_loss: 0.0689\n",
      "Epoch 208/300\n",
      "591/591 [==============================] - 141s 238ms/step - loss: 0.0259 - val_loss: 0.0763\n",
      "Epoch 209/300\n",
      "591/591 [==============================] - 140s 237ms/step - loss: 0.0318 - val_loss: 0.0884\n",
      "Epoch 210/300\n",
      "591/591 [==============================] - 141s 238ms/step - loss: 0.0238 - val_loss: 0.1002\n",
      "Epoch 211/300\n",
      "591/591 [==============================] - 141s 238ms/step - loss: 0.0262 - val_loss: 0.0770\n",
      "Epoch 212/300\n",
      "591/591 [==============================] - 140s 237ms/step - loss: 0.0451 - val_loss: 0.0864\n",
      "Epoch 213/300\n",
      "591/591 [==============================] - 141s 237ms/step - loss: 0.0261 - val_loss: 0.0892\n",
      "Epoch 214/300\n",
      "591/591 [==============================] - 141s 238ms/step - loss: 0.0285 - val_loss: 0.0901\n",
      "Epoch 215/300\n",
      "591/591 [==============================] - 141s 238ms/step - loss: 0.0278 - val_loss: 0.0813\n",
      "Epoch 216/300\n",
      "591/591 [==============================] - 141s 238ms/step - loss: 0.0281 - val_loss: 0.0819\n",
      "Epoch 217/300\n",
      "591/591 [==============================] - 141s 239ms/step - loss: 0.0245 - val_loss: 0.0952\n",
      "Epoch 218/300\n",
      "591/591 [==============================] - 141s 239ms/step - loss: 0.0304 - val_loss: 0.0690\n",
      "Epoch 219/300\n",
      "591/591 [==============================] - 141s 238ms/step - loss: 0.0446 - val_loss: 0.1076\n",
      "Epoch 220/300\n",
      "591/591 [==============================] - 141s 238ms/step - loss: 0.0326 - val_loss: 0.0846\n",
      "Epoch 221/300\n",
      "591/591 [==============================] - 141s 238ms/step - loss: 0.0243 - val_loss: 0.1019\n",
      "Epoch 222/300\n",
      "591/591 [==============================] - 141s 238ms/step - loss: 0.0253 - val_loss: 0.0742\n",
      "Epoch 223/300\n",
      "591/591 [==============================] - 141s 239ms/step - loss: 0.0253 - val_loss: 0.0880\n",
      "Epoch 224/300\n",
      "591/591 [==============================] - 141s 238ms/step - loss: 0.0274 - val_loss: 0.0948\n",
      "Epoch 225/300\n",
      "591/591 [==============================] - 142s 240ms/step - loss: 0.0237 - val_loss: 0.0744\n",
      "Epoch 226/300\n",
      "591/591 [==============================] - 142s 240ms/step - loss: 0.0266 - val_loss: 0.0829\n",
      "Epoch 227/300\n",
      "591/591 [==============================] - 141s 238ms/step - loss: 0.0257 - val_loss: 0.0739\n",
      "Epoch 228/300\n",
      "591/591 [==============================] - 142s 240ms/step - loss: 0.0243 - val_loss: 0.0798\n",
      "Epoch 229/300\n",
      "591/591 [==============================] - 141s 239ms/step - loss: 0.0267 - val_loss: 0.0628\n",
      "Epoch 230/300\n",
      "591/591 [==============================] - 141s 238ms/step - loss: 0.0324 - val_loss: 0.0731\n",
      "Epoch 231/300\n",
      "591/591 [==============================] - 141s 238ms/step - loss: 0.0286 - val_loss: 0.0665\n",
      "Epoch 232/300\n",
      "591/591 [==============================] - 141s 238ms/step - loss: 0.0252 - val_loss: 0.0828\n",
      "Epoch 233/300\n",
      "591/591 [==============================] - 142s 239ms/step - loss: 0.0249 - val_loss: 0.0670\n",
      "Epoch 234/300\n",
      "591/591 [==============================] - 141s 238ms/step - loss: 0.0246 - val_loss: 0.0867\n",
      "Epoch 235/300\n",
      "591/591 [==============================] - 141s 239ms/step - loss: 0.0254 - val_loss: 0.0682\n",
      "Epoch 236/300\n",
      "591/591 [==============================] - 141s 239ms/step - loss: 0.0396 - val_loss: 0.0805\n",
      "Epoch 237/300\n",
      "591/591 [==============================] - 142s 240ms/step - loss: 0.0234 - val_loss: 0.0719\n",
      "Epoch 238/300\n",
      "591/591 [==============================] - 141s 238ms/step - loss: 0.0241 - val_loss: 0.0928\n",
      "Epoch 239/300\n",
      "591/591 [==============================] - 141s 238ms/step - loss: 0.0260 - val_loss: 0.0727\n",
      "Epoch 240/300\n",
      "591/591 [==============================] - 141s 238ms/step - loss: 0.0222 - val_loss: 0.0717\n",
      "Epoch 241/300\n",
      "591/591 [==============================] - 141s 238ms/step - loss: 0.0567 - val_loss: 0.0773\n",
      "Epoch 242/300\n",
      "591/591 [==============================] - 141s 238ms/step - loss: 0.0273 - val_loss: 0.0974\n",
      "Epoch 243/300\n",
      "591/591 [==============================] - 141s 238ms/step - loss: 0.0235 - val_loss: 0.0957\n",
      "Epoch 244/300\n",
      "591/591 [==============================] - 141s 238ms/step - loss: 0.0243 - val_loss: 0.0990\n",
      "Epoch 245/300\n",
      "591/591 [==============================] - 141s 238ms/step - loss: 0.0288 - val_loss: 0.0710\n",
      "Epoch 246/300\n",
      "591/591 [==============================] - 141s 239ms/step - loss: 0.0248 - val_loss: 0.0614\n",
      "Epoch 247/300\n",
      "591/591 [==============================] - 141s 238ms/step - loss: 0.0243 - val_loss: 0.0749\n",
      "Epoch 248/300\n",
      "591/591 [==============================] - 141s 239ms/step - loss: 0.0227 - val_loss: 0.0738\n",
      "Epoch 249/300\n",
      "591/591 [==============================] - 141s 239ms/step - loss: 0.0256 - val_loss: 0.0778\n",
      "Epoch 250/300\n",
      "591/591 [==============================] - 141s 238ms/step - loss: 0.0246 - val_loss: 0.0710\n",
      "Epoch 251/300\n",
      "591/591 [==============================] - 142s 239ms/step - loss: 0.0216 - val_loss: 0.0827\n",
      "Epoch 252/300\n",
      "591/591 [==============================] - 141s 239ms/step - loss: 0.0234 - val_loss: 0.0887\n",
      "Epoch 253/300\n",
      "591/591 [==============================] - 143s 241ms/step - loss: 0.0243 - val_loss: 0.0777\n",
      "Epoch 254/300\n",
      "591/591 [==============================] - 142s 240ms/step - loss: 0.0267 - val_loss: 0.0944\n",
      "Epoch 255/300\n",
      "591/591 [==============================] - 141s 239ms/step - loss: 0.0229 - val_loss: 0.0742\n",
      "Epoch 256/300\n",
      "591/591 [==============================] - 142s 240ms/step - loss: 0.0264 - val_loss: 0.0786\n",
      "Epoch 257/300\n",
      "591/591 [==============================] - 142s 240ms/step - loss: 0.0252 - val_loss: 0.0877\n",
      "Epoch 258/300\n",
      "591/591 [==============================] - 142s 239ms/step - loss: 0.0239 - val_loss: 0.0735\n",
      "Epoch 259/300\n",
      "591/591 [==============================] - 142s 240ms/step - loss: 0.0243 - val_loss: 0.0690\n",
      "Epoch 260/300\n",
      "591/591 [==============================] - 142s 240ms/step - loss: 0.0260 - val_loss: 0.0917\n",
      "Epoch 261/300\n",
      "591/591 [==============================] - 142s 239ms/step - loss: 0.0266 - val_loss: 0.0859\n",
      "Epoch 262/300\n",
      "591/591 [==============================] - 142s 240ms/step - loss: 0.0234 - val_loss: 0.0862\n",
      "Epoch 263/300\n",
      "591/591 [==============================] - 142s 239ms/step - loss: 0.0230 - val_loss: 0.0860\n",
      "Epoch 264/300\n",
      "591/591 [==============================] - 142s 240ms/step - loss: 0.0243 - val_loss: 0.1011\n",
      "Epoch 265/300\n",
      "591/591 [==============================] - 142s 240ms/step - loss: 0.0269 - val_loss: 0.0954\n",
      "Epoch 266/300\n",
      "591/591 [==============================] - 142s 240ms/step - loss: 0.0225 - val_loss: 0.0964\n",
      "Epoch 267/300\n",
      "591/591 [==============================] - 142s 241ms/step - loss: 0.0262 - val_loss: 0.0776\n",
      "Epoch 268/300\n",
      "591/591 [==============================] - 142s 240ms/step - loss: 0.0234 - val_loss: 0.0712\n",
      "Epoch 269/300\n",
      "591/591 [==============================] - 141s 239ms/step - loss: 0.0233 - val_loss: 0.0873\n",
      "Epoch 270/300\n",
      "591/591 [==============================] - 142s 240ms/step - loss: 0.0298 - val_loss: 0.0829\n",
      "Epoch 271/300\n",
      "591/591 [==============================] - 142s 240ms/step - loss: 0.0255 - val_loss: 0.0660\n",
      "Epoch 272/300\n",
      "591/591 [==============================] - 142s 241ms/step - loss: 0.0250 - val_loss: 0.0877\n",
      "Epoch 273/300\n",
      "591/591 [==============================] - 142s 239ms/step - loss: 0.0221 - val_loss: 0.0798\n",
      "Epoch 274/300\n",
      "591/591 [==============================] - 142s 240ms/step - loss: 0.0238 - val_loss: 0.0831\n",
      "Epoch 275/300\n",
      "591/591 [==============================] - 141s 239ms/step - loss: 0.0268 - val_loss: 0.0880\n",
      "Epoch 276/300\n",
      "591/591 [==============================] - 142s 240ms/step - loss: 0.0220 - val_loss: 0.0955\n",
      "Epoch 277/300\n",
      "591/591 [==============================] - 142s 240ms/step - loss: 0.0231 - val_loss: 0.0898\n",
      "Epoch 278/300\n",
      "591/591 [==============================] - 142s 241ms/step - loss: 0.0240 - val_loss: 0.0913\n",
      "Epoch 279/300\n",
      "591/591 [==============================] - 141s 239ms/step - loss: 0.0298 - val_loss: 0.0810\n",
      "Epoch 280/300\n",
      "591/591 [==============================] - 142s 240ms/step - loss: 0.0257 - val_loss: 0.0926\n",
      "Epoch 281/300\n",
      "591/591 [==============================] - 142s 241ms/step - loss: 0.0256 - val_loss: 0.0780\n",
      "Epoch 282/300\n",
      "591/591 [==============================] - 142s 240ms/step - loss: 0.0237 - val_loss: 0.0795\n",
      "Epoch 283/300\n",
      "591/591 [==============================] - 142s 240ms/step - loss: 0.0413 - val_loss: 0.0646\n",
      "Epoch 284/300\n",
      "591/591 [==============================] - 143s 241ms/step - loss: 0.0225 - val_loss: 0.0842\n",
      "Epoch 285/300\n",
      "591/591 [==============================] - 142s 241ms/step - loss: 0.0215 - val_loss: 0.0656\n",
      "Epoch 286/300\n",
      "591/591 [==============================] - 143s 241ms/step - loss: 0.0232 - val_loss: 0.0639\n",
      "Epoch 287/300\n",
      "591/591 [==============================] - 141s 239ms/step - loss: 0.0234 - val_loss: 0.0673\n",
      "Epoch 288/300\n",
      "591/591 [==============================] - 142s 240ms/step - loss: 0.0568 - val_loss: 0.0643\n",
      "Epoch 289/300\n",
      "591/591 [==============================] - 143s 242ms/step - loss: 0.0238 - val_loss: 0.0768\n",
      "Epoch 290/300\n",
      "591/591 [==============================] - 142s 241ms/step - loss: 0.0210 - val_loss: 0.0582\n",
      "Epoch 291/300\n",
      "591/591 [==============================] - 142s 240ms/step - loss: 0.0211 - val_loss: 0.0663\n",
      "Epoch 292/300\n",
      "591/591 [==============================] - 143s 241ms/step - loss: 0.0240 - val_loss: 0.0753\n",
      "Epoch 293/300\n",
      "591/591 [==============================] - 142s 240ms/step - loss: 0.0234 - val_loss: 0.0640\n",
      "Epoch 294/300\n",
      "591/591 [==============================] - 143s 241ms/step - loss: 0.0271 - val_loss: 0.0825\n",
      "Epoch 295/300\n",
      "591/591 [==============================] - 142s 241ms/step - loss: 0.0236 - val_loss: 0.0645\n",
      "Epoch 296/300\n",
      "591/591 [==============================] - 142s 241ms/step - loss: 0.0236 - val_loss: 0.0667\n",
      "Epoch 297/300\n",
      "591/591 [==============================] - 142s 241ms/step - loss: 0.0216 - val_loss: 0.0693\n",
      "Epoch 298/300\n",
      "591/591 [==============================] - 142s 240ms/step - loss: 0.0540 - val_loss: 0.0713\n",
      "Epoch 299/300\n",
      "591/591 [==============================] - 143s 241ms/step - loss: 0.0248 - val_loss: 0.0611\n",
      "Epoch 300/300\n",
      "591/591 [==============================] - 143s 241ms/step - loss: 0.0233 - val_loss: 0.0699\n",
      "end time: Fri Apr  7 05:35:08 2023\n"
     ]
    }
   ],
   "source": [
    "print ('start time:',time.asctime( time.localtime(time.time()) ))\n",
    "model.compile(optimizer=keras.optimizers.Adam(learning_rate=0.001, beta_1=0.9, beta_2=0.999, epsilon=1e-07, decay=0.01),loss='mse')\n",
    "\n",
    "cp_callback = tf.keras.callbacks.ModelCheckpoint(checkpoint_path,save_best_only=True,monitor='val_loss')\n",
    "history = model.fit(train_data,\n",
    "                    steps_per_epoch=train_count//BATCH_SIZE,\n",
    "                    epochs=300,\n",
    "                    validation_data=test_data,\n",
    "                    validation_steps=test_count//BATCH_SIZE,\n",
    "                   callbacks=[cp_callback])\n",
    "#要改\n",
    "np.savetxt('NASNetMobile_loss_0.txt',history.history['loss'])\n",
    "#要改\n",
    "np.savetxt('NASNetMobile_valloss_0.txt',history.history['val_loss'])\n",
    "print ('end time:',time.asctime( time.localtime(time.time()) ))"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "metadata": {},
   "outputs": [],
   "source": []
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "metadata": {},
   "outputs": [],
   "source": []
  }
 ],
 "metadata": {
  "kernelspec": {
   "display_name": "Python 3",
   "language": "python",
   "name": "python3"
  },
  "language_info": {
   "codemirror_mode": {
    "name": "ipython",
    "version": 3
   },
   "file_extension": ".py",
   "mimetype": "text/x-python",
   "name": "python",
   "nbconvert_exporter": "python",
   "pygments_lexer": "ipython3",
   "version": "3.6.5"
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 },
 "nbformat": 4,
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