keras_model.py

import tensorflow as tf

# Create the model
model = tf.keras.models.Sequential([
    tf.keras.layers.Conv2D(16, kernel_size = (3, 3), activation = 'relu', padding = 'same', input_shape = (244, 244, 3)),
    tf.keras.layers.MaxPool2D(pool_size = (2, 2), strides = 2),
    tf.keras.layers.Conv2D(32, kernel_size = (3, 3), activation = 'relu', padding = 'same'),
    tf.keras.layers.MaxPool2D(pool_size = (2, 2), strides = 2),
    tf.keras.layers.Flatten(),
    tf.keras.layers.Dense(2, activation = 'softmax')
])

# Save the model                                                                                                                                                                             
model.save("keras_model.h5")