# Bigram

import tensorflow as tf
keras = tf.keras
from keras.layers import Conv2D, Input
from keras.models import Sequential

model = Sequential([
    Input(shape=(6, 6, 1)),
    Conv2D(1, (3, 3), (1, 2), "same")
])
model.summary()

Model: "sequential_2"
_________________________________________________________________
 Layer (type)                Output Shape              Param #   
=================================================================
 conv2d_2 (Conv2D)           (None, 6, 3, 1)           10        
                                                                 
=================================================================
Total params: 10 (40.00 Byte)
Trainable params: 10 (40.00 Byte)
Non-trainable params: 0 (0.00 Byte)
_________________________________________________________________
_________________________________________________________________
 Layer (type)                Output Shape              Param #   
=================================================================
 conv2d_2 (Conv2D)           (None, 6, 3, 1)           10        
                                                                 
=================================================================
Total params: 10 (40.00 Byte)
Trainable params: 10 (40.00 Byte)
Non-trainable params: 0 (0.00 Byte)
_________________________________________________________________