Advanced Deep Learning with Keras

logp = Lambda(self.logp,
output_shape=(1,),
name='logp')([mean, stddev, action])
self.logp_model = Model(inputs, logp, name='logp')
self.logp_model.summary()
plot_model(self.logp_model, to_file='logp_model.png', show_
shapes=True)
Chapter 10
entropy = Lambda(self.entropy,
output_shape=(1,),
name='entropy')([mean, stddev])
self.entropy_model = Model(inputs, entropy, name='entropy')
self.entropy_model.summary()
plot_model(self.entropy_model, to_file='entropy_model.png', show_
shapes=True)
value = Dense(1,
activation='linear',
kernel_initializer='zero',
name='value')(x)
self.value_model = Model(inputs, value, name='value')
self.value_model.summary()
Figure 10.6.6: Gaussian log probability model of the policy
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