ec43bfe71f25287c3987d88255f4adaf22030651,hypergan/train_hooks/imle_train_hook.py,IMLETrainHook,before_step,#IMLETrainHook#Any#Any#,71

Before Change

            self.gan.session.run([self.assign_x[_j], self.assign_encoded_latent[_j]])
    else:
        for j in range(new_entries):
            scores = []
            _j = (j+self.offset) % self.memory_size
            self.gan.session.run(self.assign_x[_j])
            for i in range(self.search_size):
                s,_ = self.gan.session.run([self.l2_loss_on_g[_j], self.assign_latent[i]])
                scores.append(s)
            sort = zip(scores, self.assign_latent_to_max[_j])
            sort2 = sorted(sort, key=itemgetter(0))
            print("  Max ", sort2[-1][0])
            print("  Min ", sort2[0][0])
            self.gan.session.run(sort2[0][-1])
    self.offset += new_entries

After Change

            min_score = None
            for i in range(self.search_size):
                s,_ = self.gan.session.run([self.l2_loss_on_g[_j], self.assign_latent])
                if( min_score == None or min_score > s):
                    self.gan.session.run(self.assign_latent_to_min[_j])
                    min_score = s
                else:
                    pass
                    //print("Ignoring score", s)
            print("  Min ", min_score)
    self.offset += new_entries

Instances