In [1]:

    

from keras.models import Sequential
from keras.layers import Dense
model = Sequential()
model.add(Dense(2, input_dim=1, activation='relu'))
model.add(Dense(1, activation='sigmoid'))
print(model.summary())


    

    




Using TensorFlow backend.






    




_________________________________________________________________
Layer (type)                 Output Shape              Param #   
=================================================================
dense_1 (Dense)              (None, 2)                 4         
_________________________________________________________________
dense_2 (Dense)              (None, 1)                 3         
=================================================================
Total params: 7
Trainable params: 7
Non-trainable params: 0
_________________________________________________________________
None

In [2]:

    

from keras.utils.vis_utils import plot_model
plot_model(model, to_file='model_plot.png', show_shapes=True, show_layer_names=True)


    

In [7]:

    

from IPython.display import Image
Image('model_plot.png')


    

    
Out[7]:

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