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reduce_mean(disc_real) gen_train_op = tf.train.RMSPropOptimizer( learning_rate=5e-5 ).minimize(gen_cost, var_list=gen_params) disc_train_op = tf.train.RMSPropOptimizer( learning_rate=5e-5 ).minimize(disc_cost, var_list=disc_params) clip_ops = [] for var in lib.params_with_name('...
/usr/bin/env python # -*- coding: UTF-8 -*- # coding=utf-8 """ @author: Li Tian ...
(l) # This creates a model that includes # the Input layer, a TFILM layer, and a dense layer model = Model(inputs=inputs, outputs=outputs) model.compile(optimizer='rmsprop', loss='binary_crossentropy', metrics=['accuracy']) print(model.summary()) model.fit(x, y, epochs=10) # ...