from tensorflow.keras.models import Sequential
from tensorflow.keras.layers import Conv2D, MaxPooling2D, Flatten, Dense, Dropout, BatchNormalization
import time
start = time.time()

model = Sequential([
    #Pierwszy blok konwoucyjny 
    Conv2D(32, (3, 3), activation='relu', padding='same', input_shape=(28,28,1)),
    BatchNormalization(),
    MaxPooling2D((2,2)),
    Dropout(0.25),

    #Drugi blok konwoucyjny 
    Conv2D(64, (3, 3), activation='relu', padding='same'),
    BatchNormalization(),
    MaxPooling2D((2,2)),
    Dropout(0.25),

    #blok gęsty
    Flatten(),
    Dense(128, activation='relu'),
    BatchNormalization(),
    Dropout(0.5),
    Dense(10, activation='softmax')
])

model.compile(optimizer="adam", loss="categorical_crossentropy", metrics=["accuracy"])

history = model.fit(x_train, y_train, epochs=10, batch_size=32, validation_data=(x_test, y_test))

loss, accuracy = model.evaluate(x_test, y_test, verbose=0)
print(f"Strata: {loss:.4f}, Dokładność: {accuracy:.4f}")

end = time.time()

print(f"Czas wykonania: {end - start:.2f} sekundy")