text_html_output_1.png
from keras.models import Sequential

from tensorflow.keras.layers import Dense,Flatten,Dropout,Conv2D,MaxPooling2D,BatchNormalization

model = Sequential()
model.add(Conv2D(64, (4, 4), input_shape=(9, 9, 1), activation='relu'))
model.add(Conv2D(32, (2, 2), activation='relu'))
model.add(Dropout(0.2))
model.add(Flatten())
model.add(Dense(32, activation='relu'))
model.add(Dense(8, activation='relu'))
model.add(Dense(2, activation='softmax'))

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

model.summary()