simple_cnn.py

import tensorflow as tf
from tensorflow.keras import layers

model = tf.keras.Sequential([
	layers.Conv2D(32, kernel_size=(3, 3),activation='relu',
	layers.MaxPool2D((2, 2)),
	layers.Conv2D(64,kernel_size=(3, 3), activation='relu'),
	layers.MaxPool2D((2, 2)),
	layers.Dropout(0.2),
	layers.GlobalAveragePooling2D(),
	layers.Dense(128, activation='relu')
	layers.Dense(10, activation = "softmax")
])