365c861ccac7588596907b0cff8ddf69cc7a966c,hypergan/samplers/grid_sampler.py,GridSampler,_sample,#GridSampler#,13

Before Change

        g = np.concatenate(g, axis=1)
        g = np.concatenate(g, axis=1)
        g = np.expand_dims(g, axis=0)
        x_hat = gan.session.run(gan.autoencoded_x, feed_dict={gan.inputs.x: self.x})
        //e = gan.session.run(gan.encoder.sample, feed_dict={gan.inputs.x: g})

        return {
            "generator":g

After Change

        gs = []
        for i in range(int(needed)):
            zi = z[i*gan.batch_size():(i+1)*gan.batch_size()]
            zi = torch.from_numpy(zi).type(torch.FloatTensor).cuda()
            g = gan.generator(zi).detach().cpu().numpy()
            gs.append(g)
        g = np.reshape(gs, [4, 8, gan.channels(), gan.height(), gan.width()])
        g = np.concatenate(g, axis=0)

Instances