How to create model checkpoints in keras?
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How to create model checkpoints in keras?

How to create model checkpoints in keras?

This recipe helps you create model checkpoints in keras

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Recipe Objective

Create model checkpoints in keras. Sometimes deep learning models are very big and tedious to train, it requires a lot of hours, on a very big and research level sometimes days. If the running stops in between then we can loose a lot of time and work then you have to start from starting again. The checkpoints can be used directly, or used as the starting point for a new run, picking up where it left off. When we train the deep learning model, the checkpoints is the weights of the model.These weights are then used in making predictions, or it can be used as the basis for ongoing training.

Step 1- Importing Libraries

#importing Libraries import pandas as pd import numpy as np from keras.datasets import mnist from sklearn.model_selection import train_test_split from keras.models import Sequential from keras.layers import Dense from keras.layers import Dropout from tensorflow.keras import layers #We will import the modelcheckpoint here from keras.callbacks import ModelCheckpoint

Step 2- Load the dataset

#Loading Dataset (X_train, y_train), (X_test, y_test) = mnist.load_data()

Step 3- Define the model.

We will define the model with the defining parameters.

#Model model = Sequential() model.add(layers.Dense(64, kernel_initializer='uniform', input_shape=(10,)))

Step 4- Defining the activation function.

We will Defining the activation function as ReLU.

model.add(layers.Activation('relu'))

Step 5- Adding layers

We will add layers to our model.

#Adding Layers model.add(Dense(512)) model.add(Dropout(0.2)) model.add(Dense(256, activation='relu')) model.add(Dropout(0.1))

Step 6- Creating Checkpoints

we will create our required checkpoint here after making layers.

#We will create the checkpoint. filepath="mnist_data_checkpoint" checkpoint = ModelCheckpoint(filepath, monitor='val_accuracy', verbose=1, save_best_only=True, mode='max') callbacks_list = [checkpoint] print(model) print(callbacks_list)

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