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modeltf = keras.Sequential([
keras.layers.Conv2D(input_shape=(28,28,1), filters=16, kernel_size=5, strides=1, padding="same", activation=tf.nn.relu),
keras.layers.BatchNormalization(),
keras.layers.MaxPooling2D(pool_size=2, strides=2),
keras.layers.Conv2D(32, kernel_size=5, strides=1, padding="same", activation=tf.nn.relu),
keras.layers.BatchNormalization(),
keras.layers.MaxPooling2D(pool_size=2, strides=2),
keras.layers.Flatten(),
keras.layers.Dense(10, activation=tf.nn.softmax)
])
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