gistfile1.txt

lr=0.001

#Do this when multiple networks interact with each other
tvars=tf.trainable_variables()  #returns all variables created(the two variable scopes) and makes trainable true
d_vars=[var for var in tvars if 'dis' in var.name]
g_vars=[var for var in tvars if 'gen' in var.name]

D_trainer=tf.train.AdamOptimizer(lr).minimize(D_loss,var_list=d_vars)
G_trainer=tf.train.AdamOptimizer(lr).minimize(G_loss,var_list=g_vars)

batch_size=100
epochs=100
init=tf.global_variables_initializer()