PYTHON

convolutional layer of model architecture pass input_shape

classifier = tf.keras.Sequential([
        tf.keras.layers.Conv2D(16,(3,3),activation='relu',input_shape=(IMG_SHAPE, IMG_SHAPE, 3)),
        tf.keras.layers.MaxPooling2D(2,2),

        tf.keras.layers.Conv2D(32,(3,3),activation='relu'),
        tf.keras.layers.MaxPooling2D(2,2),

        tf.keras.layers.Conv2D(64,(3,3),activation='relu'),
        tf.keras.layers.MaxPooling2D(2,2),
        
        tf.keras.layers.Conv2D(128,(3,3),activation='relu'),
        tf.keras.layers.MaxPooling2D(2,2),

        tf.keras.layers.Dropout(0.32),
        tf.keras.layers.Flatten(),
        tf.keras.layers.Dense(1024,activation= 'relu'),
        tf.keras.layers.Dense(3, activation = "softmax")  
])