Why keras does not allow to add a convolutional layer in this way?

Question

The following code

from tensorflow import keras
from keras.layers import Conv2D

model = keras.Sequential()
model.add(Conv2D(1, (3, 3), padding=\'same\', input_s         


        

Answer 1

Try this:

from tensorflow import keras
from tensorflow.keras.layers import Conv2D

model = keras.Sequential()
model.add(Conv2D(1, (3, 3), padding='same', input_shape=(28, 28, 1)))

You are mixing a tf.keras Sequential model with a keras Conv2D layer (instead of a tf.keras Conv2D layer.)

Or, as remarked below, use actual Keras:

import keras
from keras.models import Sequential
from keras.layers import Conv2D

model = Sequential()
model.add(Conv2D(1, (3, 3), padding='same', input_shape=(28, 28, 1)))

Answer 2

You should import Sequential from keras models

from keras.models import Sequential
from keras.layers import Conv2D

model = Sequential()
model.add(Conv2D(1, (3, 3), padding='same', input_shape=(28, 28, 1)))