68729f8b6458c3ae3cc26b895d00d1326e5d1c2d,hypergan/trainers/simultaneous_trainer.py,SimultaneousTrainer,_create,#SimultaneousTrainer#,12

Before Change

        for grad, v in apply_vec:
            if grad is None:
                print("Gradient is None:", v)
        self.gan.gradient_mean = sum([tf.reduce_mean(tf.abs(grad)) for grad in d_grads+g_grads])/len(d_grads+g_grads)
        self.g_loss = g_loss
        self.d_loss = d_loss
        self.gan.trainer = self

After Change

        for grad, v in apply_vec:
            if grad is None:
                print("Gradient is None:", v)
        for t in self.train_hooks:
            d_grads, g_grads = t.gradients(d_grads, g_grads)
        self.g_loss = g_loss
        self.d_loss = d_loss
        self.gan.trainer = self

Instances