您可以使用plot_model来显示模型。您不能仅直接显示第一个图层

from tensorflow.keras.models import Sequential
from tensorflow.keras.layers import Conv2D, MaxPooling2D, Dense, Flatten, Dropout
model = Sequential()
model.add(Conv2D(16, (3,3), 1, activation='relu', input_shape=(256,256,3)))
model.add(MaxPooling2D())
model.add(Conv2D(32, (3,3), 1, activation='relu'))
model.add(MaxPooling2D())
model.add(Conv2D(16, (3,3), 1, activation='relu'))
model.add(MaxPooling2D())
model.add(Flatten())
model.add(Dense(256, activation='relu'))
model.add(Dense(1, activation='sigmoid'))
model.compile('adam', loss=tf.losses.BinaryCrossentropy(), metrics=['accuracy'])
#model. Summary()
#Visualization code
from keras.utils import plot_model
plot_model(model, to_file='model.png', show_shapes=True)

https://www.tensorflow.org/tensorboard/get_started，Tensorboard也可以帮助您