Extracted text: For the following source code section:e # build model model = Sequential() model.add(Conv2D(filters=16, input_shape=(32, 32, 3), kernel_size=(3, 3), strides=(1, 1), padding='same', activation='relu')) model.add(MaxPooling2D(pool_size=(2, 2), strides=(2, 2), padding='valid')) model.add(Conv2D(filters=32, kernel_size=(3, 3), strides=(1, 1), padding='same', activation='relu')) model.add(MaxPooling2D(pool_size=(2, 2), strides=(2, 2), padding='valid')) model.add(Flatten()) model.add(Dense(units=1024, activation='relu')) model.add(Dense(units=512, activation='relu')) model.add(Dense(units=10, activation='softmax')) What is the dimension of the output of each layer?e If the output has 3 dimensions, you should use height x width x depth to indicate the dimension.e If the output has 2 dimensions, you should use height x width to indicate the dimension.e If the output is a vector, you should use height x 1 to indicate the dimension.e