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@utkucanaytac
Created May 1, 2021 10:06
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Adaptive_Lr.ipynb
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{
"nbformat": 4,
"nbformat_minor": 0,
"metadata": {
"colab": {
"name": "Adaptive_Lr.ipynb",
"provenance": [],
"collapsed_sections": [],
"machine_shape": "hm",
"mount_file_id": "1g72srTRb-XkdXay4tpu1ewilVnOMRQPd",
"authorship_tag": "ABX9TyPv+eRKA7EEvNq/mAgMFEe1",
"include_colab_link": true
},
"kernelspec": {
"name": "python3",
"display_name": "Python 3"
},
"accelerator": "GPU"
},
"cells": [
{
"cell_type": "markdown",
"metadata": {
"id": "view-in-github",
"colab_type": "text"
},
"source": [
"<a href=\"https://colab.research.google.com/gist/utkucanaytac/11125e78cf420021ad6b06dbda1958b0/adaptive_lr.ipynb\" target=\"_parent\"><img src=\"https://colab.research.google.com/assets/colab-badge.svg\" alt=\"Open In Colab\"/></a>"
]
},
{
"cell_type": "code",
"metadata": {
"id": "e4dsZvx2MiRh",
"colab": {
"base_uri": "https://localhost:8080/",
"height": 302
},
"outputId": "d86aa82b-cedf-4bcf-ec07-fcf292407b0b"
},
"source": [
"%load_ext tensorboard\n",
"import datetime, os\n",
"from keras.datasets import cifar10\n",
"from keras.utils import to_categorical\n",
"from tensorflow.keras.models import Sequential\n",
"from tensorflow.keras.layers import Dense, Dropout, Flatten, MaxPool2D\n",
"from tensorflow.keras.layers import Conv2D, MaxPooling2D,BatchNormalization\n",
"from sklearn.metrics import classification_report\n",
"import numpy as np\n",
"from tensorflow.keras.callbacks import Callback\n",
"from tensorflow.keras.optimizers import SGD\n",
"import matplotlib.pyplot as plt\n",
"from keras import backend as K\n",
"import tensorflow as tf\n",
"from tensorflow import keras\n",
"from tensorflow.keras import layers\n",
"from tensorflow.keras import regularizers\n",
"import math\n",
"from tensorflow.keras.optimizers import SGD, Adagrad, Adadelta, RMSprop, Adam\n",
"\n",
"(x_train,y_train),(x_test,y_test)=cifar10.load_data()\n",
"y_test_cat = to_categorical(y_test,10)\n",
"y_train = to_categorical(y_train,10)\n",
"\n",
"x_train = x_train.astype('float32')\n",
"x_test = x_test.astype('float32')\n",
"\n",
"x_train = x_train/x_train.max()\n",
"x_test = x_test/x_test.max()\n",
"\n",
"\n",
"for i in range(9):\n",
" plt.subplot(330 + 1 + i)\n",
" plt.imshow(x_train[i])\n",
"plt.show()\n",
"\n",
"class CustomLearningRateScheduler(keras.callbacks.Callback):\n",
"\n",
" def __init__(self, schedule):\n",
" super(CustomLearningRateScheduler, self).__init__()\n",
" self.schedule = schedule\n",
"\n",
" def on_epoch_end(self, epoch, logs={}):\n",
" if not hasattr(self.model.optimizer, \"lr\"):\n",
" raise ValueError('Optimizer must have a \"lr\" attribute.')\n",
" \n",
" global temp\n",
" temp = logs[\"loss\"]\n",
" lr = float(tf.keras.backend.get_value(self.model.optimizer.learning_rate))\n",
" scheduled_lr= self.schedule(epoch,lr)\n",
" tf.keras.backend.set_value(self.model.optimizer.lr,scheduled_lr)\n",
" print(\"\\nEpoch %05d: Learning rate is %6.4f.\" % (epoch, scheduled_lr))\n",
" \n",
"\n",
"LR_SCHEDULE = [\n",
" # (epoch to start, learning rate) tuples\n",
" (3, 0.05),\n",
" (6, 0.01),\n",
" (9, 0.005),\n",
" (12, 0.001),\n",
"]\n",
"\n",
"\n",
"def lr_schedule(epoch, lr):\n",
" \"\"\"Helper function to retrieve the scheduled learning rate based on epoch.\"\"\"\n",
" if epoch < 1:\n",
" return lr\n",
" print(temp)\n",
" initial_lr = 0.05\n",
" return np.exp(-1/np.sqrt(initial_lr*temp))\n",
" \n",
"\n",
"\n",
"#def scheduler(epoch,lr):\n",
"\n",
" #b = -(temp*lr)\n",
"\n",
" #lr_new = 1-tf.math.exp(b)\n",
"\n",
" #return lr_new\n",
"\n",
"\n",
"def get_lr_metric(optimizer):\n",
" def lr(y_true, y_pred):\n",
" return optimizer.lr\n",
" return lr\n",
"\n",
"\n",
"optimizer = keras.optimizers.SGD(learning_rate=0.05)\n",
"lr_metric = get_lr_metric(optimizer)\n",
"\n",
"\n",
"logdir = os.path.join(\"logs\", datetime.datetime.now().strftime(\"%Y%m%d-%H%M%S\"))\n",
"tensorboard_callback = tf.keras.callbacks.TensorBoard(logdir, histogram_freq=1)\n",
"\n",
"#predictions = model.predict(x_test)\n",
"#predict_class = np.argmax(predictions,axis=1)\n",
"#print(classification_report(y_test,predict_class))\n",
"\n"
],
"execution_count": null,
"outputs": [
{
"output_type": "stream",
"text": [
"Downloading data from https://www.cs.toronto.edu/~kriz/cifar-10-python.tar.gz\n",
"170500096/170498071 [==============================] - 6s 0us/step\n"
],
"name": "stdout"
},
{
"output_type": "display_data",
"data": {
"image/png": 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\n",
"text/plain": [
"<Figure size 432x288 with 9 Axes>"
]
},
"metadata": {
"tags": [],
"needs_background": "light"
}
}
]
},
{
"cell_type": "code",
"metadata": {
"id": "zug2cvj1-E2S"
},
"source": [
"def cnn_model():\n",
" model = Sequential()\n",
" weight_decay = 0.0005 \n",
" x_shape = [32,32,3]\n",
"\n",
" model.add(Conv2D(64, (3, 3), padding='same', input_shape=x_shape, kernel_regularizer=regularizers.l2(weight_decay),activation='relu'))\n",
" model.add(BatchNormalization())\n",
" model.add(Dropout(0.3))\n",
" model.add(Conv2D(64, (3, 3), padding='same',kernel_regularizer=regularizers.l2(weight_decay),activation='relu'))\n",
" model.add(BatchNormalization())\n",
" model.add(MaxPooling2D(pool_size=(2, 2)))\n",
" model.add(Conv2D(128, (3, 3), padding='same',kernel_regularizer=regularizers.l2(weight_decay),activation='relu'))\n",
" model.add(BatchNormalization())\n",
" model.add(Dropout(0.4))\n",
" model.add(Conv2D(128, (3, 3), padding='same',kernel_regularizer=regularizers.l2(weight_decay),activation='relu'))\n",
" model.add(BatchNormalization())\n",
" model.add(MaxPooling2D(pool_size=(2, 2)))\n",
" model.add(Conv2D(256, (3, 3), padding='same',kernel_regularizer=regularizers.l2(weight_decay),activation='relu'))\n",
" model.add(BatchNormalization())\n",
" model.add(Dropout(0.4))\n",
" model.add(Conv2D(256, (3, 3), padding='same',kernel_regularizer=regularizers.l2(weight_decay),activation='relu'))\n",
" model.add(BatchNormalization())\n",
" model.add(Dropout(0.4))\n",
" model.add(Conv2D(256, (3, 3), padding='same',kernel_regularizer=regularizers.l2(weight_decay),activation='relu'))\n",
" model.add(BatchNormalization())\n",
" model.add(MaxPooling2D(pool_size=(2, 2)))\n",
" model.add(Conv2D(512, (3, 3), padding='same',kernel_regularizer=regularizers.l2(weight_decay),activation='relu'))\n",
" model.add(BatchNormalization())\n",
" model.add(Dropout(0.4))\n",
" model.add(Conv2D(512, (3, 3), padding='same',kernel_regularizer=regularizers.l2(weight_decay),activation='relu'))\n",
" model.add(BatchNormalization())\n",
" model.add(Dropout(0.4))\n",
" model.add(Conv2D(512, (3, 3), padding='same',kernel_regularizer=regularizers.l2(weight_decay),activation='relu'))\n",
" model.add(BatchNormalization())\n",
" model.add(MaxPooling2D(pool_size=(2, 2)))\n",
" model.add(Conv2D(512, (3, 3), padding='same',kernel_regularizer=regularizers.l2(weight_decay),activation='relu'))\n",
" model.add(BatchNormalization())\n",
" model.add(Dropout(0.4))\n",
" model.add(Conv2D(512, (3, 3), padding='same',kernel_regularizer=regularizers.l2(weight_decay),activation='relu'))\n",
" model.add(BatchNormalization())\n",
" model.add(Dropout(0.4))\n",
" model.add(Conv2D(512, (3, 3), padding='same',kernel_regularizer=regularizers.l2(weight_decay),activation='relu'))\n",
" model.add(BatchNormalization())\n",
" model.add(MaxPooling2D(pool_size=(2, 2)))\n",
" model.add(Dropout(0.5))\n",
" model.add(Flatten())\n",
" model.add(Dense(512,kernel_regularizer=regularizers.l2(weight_decay),activation='relu'))\n",
" model.add(BatchNormalization())\n",
" model.add(Dropout(0.5))\n",
" model.add(Dense(10,activation = 'softmax'))\n",
" return (model)\n",
"\n",
"epochs = 20\n",
"\n",
"\n"
],
"execution_count": null,
"outputs": []
},
{
"cell_type": "code",
"metadata": {
"id": "FsDgfvUFq2ym"
},
"source": [
"model = cnn_model()\n",
"model.compile(optimizer= optimizer, loss='categorical_crossentropy',metrics=['accuracy',lr_metric])\n",
"history = model.fit(x_train,y_train,epochs=epochs,verbose=1,validation_data=(x_test,y_test_cat),callbacks=[tensorboard_callback, CustomLearningRateScheduler(lr_schedule)])"
],
"execution_count": null,
"outputs": []
},
{
"cell_type": "code",
"metadata": {
"id": "oLwcY-m9_oTS"
},
"source": [
"# fit CNN model using Adadelta optimizer\n",
"\n",
"K.clear_session()\n",
"model2 = cnn_model()\n",
"model2.compile(loss=keras.losses.categorical_crossentropy,\n",
" optimizer=Adadelta(lr=1.0, rho=0.95, epsilon=1e-08, decay=0.0),\n",
" metrics=['accuracy'])\n",
"history2 = model2.fit(x_train, y_train, \n",
" validation_data=(x_test, y_test_cat), \n",
" epochs=epochs, \n",
" verbose=1)\n",
"\n",
"# fit CNN model using RMSprop optimizer\n",
"K.clear_session()\n",
"model3 = cnn_model()\n",
"model3.compile(loss=keras.losses.categorical_crossentropy,\n",
" optimizer=RMSprop(lr=0.001, rho=0.9, epsilon=1e-08, decay=0.0),\n",
" metrics=['accuracy'])\n",
"history3 = model3.fit(x_train, y_train, \n",
" validation_data=(x_test, y_test_cat), \n",
" epochs=epochs, \n",
" verbose=1)\n",
"\n",
"# fit CNN model using Adam optimizer\n",
"K.clear_session()\n",
"model4 = cnn_model()\n",
"model4.compile(loss=keras.losses.categorical_crossentropy,\n",
" optimizer=Adam(lr=0.001, beta_1=0.9, beta_2=0.999, epsilon=1e-08, decay=0.0),\n",
" metrics=['accuracy'])\n",
"history4 = model4.fit(x_train, y_train, \n",
" validation_data=(x_test, y_test_cat), \n",
" epochs=epochs, \n",
" verbose=1)\n",
"\n",
"# fit CNN model using Adagrad optimizer\n",
"K.clear_session()\n",
"model5 = cnn_model()\n",
"model5.compile(loss=keras.losses.categorical_crossentropy,\n",
" optimizer=Adagrad(lr=0.01, epsilon=1e-08, decay=0.0),\n",
" metrics=['accuracy'])\n",
"history5 = model5.fit(x_train, y_train, \n",
" validation_data=(x_test, y_test_cat), \n",
" epochs=epochs, \n",
" verbose=2)"
],
"execution_count": null,
"outputs": []
},
{
"cell_type": "code",
"metadata": {
"id": "_PIJiJgZ_R2P",
"colab": {
"base_uri": "https://localhost:8080/",
"height": 513
},
"outputId": "8dd3f558-a546-4f95-804f-185a89996709"
},
"source": [
"\n",
"\n",
"fig = plt.figure(figsize=(12,8))\n",
"plt.plot(range(epochs),history.history['val_accuracy'],label='Proposed_Lr')\n",
"plt.plot(range(epochs),history2.history['val_accuracy'],label='Adadelta')\n",
"plt.plot(range(epochs),history3.history['val_accuracy'],label='RMSprop')\n",
"plt.plot(range(epochs),history4.history['val_accuracy'],label='Adam')\n",
"plt.plot(range(epochs),history5.history['val_accuracy'],label='Adagrad')\n",
"\n",
"plt.legend(loc=0)\n",
"plt.xlabel('epochs')\n",
"plt.xlim([0,epochs])\n",
"plt.ylabel('accuracy on validation set')\n",
"plt.grid(True)\n",
"plt.title(\"Comparing Model Accuracy\")\n",
"plt.show()\n",
"fig.savefig(r'C:\\Users\\ucan.aytac\\Desktop\\compare-accuracy.jpg')\n",
"plt.close(fig)\n",
"\n",
"\n",
"#plt.plot(history['val_accuracy'])\n",
"#plt.title('val. accuracy')\n",
"#plt.ylabel('accuracy')\n",
"#plt.xlabel('epoch')\n",
"#plt.legend(['Adaptive Lr'], loc='lower right')\n",
"#plt.show()\n"
],
"execution_count": null,
"outputs": [
{
"output_type": "display_data",
"data": {
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\n",
"text/plain": [
"<Figure size 864x576 with 1 Axes>"
]
},
"metadata": {
"tags": [],
"needs_background": "light"
}
}
]
},
{
"cell_type": "code",
"metadata": {
"id": "5ZisUE6CGzh2"
},
"source": [
"%load_ext tensorboard\n",
"import datetime, os\n",
"from keras.datasets import cifar10\n",
"from keras.utils import to_categorical\n",
"from tensorflow.keras.models import Sequential\n",
"from tensorflow.keras.layers import Dense, Dropout, Flatten, MaxPool2D\n",
"from tensorflow.keras.layers import Conv2D, MaxPooling2D,BatchNormalization\n",
"from sklearn.metrics import classification_report\n",
"import numpy as np\n",
"from tensorflow.keras.callbacks import Callback\n",
"from tensorflow.keras.optimizers import SGD\n",
"import matplotlib.pyplot as plt\n",
"from keras import backend as K\n",
"import tensorflow as tf\n",
"from tensorflow import keras\n",
"from tensorflow.keras import layers\n",
"from tensorflow.keras import regularizers\n",
"from tensorflow.keras.applications.vgg16 import VGG16\n",
"from tensorflow.keras.applications.resnet50 import ResNet50\n",
"from tensorflow.keras.applications.inception_v3 import InceptionV3\n",
"from tensorflow.keras.applications.xception import Xception\n",
"import tensorflow.keras as tk\n",
"\n",
"(x_train,y_train),(x_test,y_test)=cifar10.load_data()\n",
"y_test_cat = to_categorical(y_test,10)\n",
"y_train = to_categorical(y_train,10)\n",
"\n",
"x_train = x_train.astype('float32')\n",
"x_test = x_test.astype('float32')\n",
"\n",
"x_train = x_train/x_train.max()\n",
"x_test = x_test/x_test.max()\n",
"\n",
"\n",
"\n",
"for i in range(9):\n",
" plt.subplot(330 + 1 + i)\n",
" plt.imshow(x_train[i])\n",
"plt.show()\n",
"\n",
"def get_lr_metric(optimizer):\n",
" def lr(y_true, y_pred):\n",
" return optimizer.lr\n",
" return lr\n",
"\n",
"def scheduler(epoch, lr):\n",
" if epoch < 10:\n",
" return lr\n",
" else:\n",
" return lr * tf.math.exp(-0.1) #some f function\n",
"\n",
"lr_callback = keras.callbacks.LearningRateScheduler(scheduler, verbose=True)\n",
"\n",
"optimizer = keras.optimizers.SGD(learning_rate=0.01)\n",
"lr_metric = get_lr_metric(optimizer)\n",
"\n",
"\n",
"input_tensor = tk.Input(shape=(32, 32, 3))\n",
"resized_images = tk.layers.Lambda(lambda image: tf.image.resize(image, (150, 150)))(input_tensor)\n",
"\n",
"\n",
"frozen = Xception (weights=\"imagenet\", input_tensor=resized_images, input_shape=(150, 150, 3), include_top=False)\n",
"\n",
"model = Sequential(frozen)\n",
"model.add(Flatten())\n",
"model.add(Dense(10,activation = 'softmax'))\n",
"model.compile(optimizer= optimizer, loss='categorical_crossentropy',metrics=['accuracy',lr_metric])\n",
"\n",
"model.summary()\n",
"\n",
"logdir = os.path.join(\"logs\", datetime.datetime.now().strftime(\"%Y%m%d-%H%M%S\"))\n",
"tensorboard_callback = tf.keras.callbacks.TensorBoard(logdir, histogram_freq=1)\n",
"\n",
"model.fit(x_train,y_train,epochs=1,verbose=1,validation_data=(x_test,y_test_cat),callbacks=[lr_callback,tensorboard_callback])\n",
"model.save_weights('/Users/utkucanaytac/Desktop/my_model_weights')\n",
"history = model.history.history\n",
"\n",
"plt.plot(history['val_accuracy'])\n",
"plt.title('val. accuracy')\n",
"plt.ylabel('accuracy')\n",
"plt.xlabel('epoch')\n",
"plt.legend(['New_Optimizer'], loc='lower right')\n",
"plt.show()\n",
"\n",
"predictions = model.predict(x_test)\n",
"predict_class = np.argmax(predictions,axis=1)\n",
"print(classification_report(y_test,predict_class))\n",
"\n"
],
"execution_count": null,
"outputs": []
},
{
"cell_type": "code",
"metadata": {
"id": "2lMjpHKzEuYO"
},
"source": [
"%tensorboard --logdir logs"
],
"execution_count": null,
"outputs": []
},
{
"cell_type": "markdown",
"metadata": {
"id": "xPs05x0SW_Mv"
},
"source": [
"# Yeni Bölüm"
]
}
]
}
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