7d8f3f66495979f1bbd27205d422d673991709f2,GANs/stylegan2/generate.py,,synthesis,#,28

Before Change

        if i > 4:
            inmaps = inmaps // 2
        noise = nn.Variable.from_numpy_array(rnd.randn(*curr_shape))
        h = conv_block(h, w[(2+i)*2-4], noise, res=2 ** (i + 2), outmaps=outmaps, inmaps=inmaps,
                       kernel_size=3, pad_size=1, namescope="Conv1")

        // toRGB blocks
        prev_torgb = upsample_2d(torgb, k=[1, 3, 3, 1])
        curr_torgb = conv_block(h, w[(2+i)*2-3], noise=None, res=2 ** (i + 2), outmaps=3, inmaps=inmaps,
                                kernel_size=1, pad_size=0, demodulate=False, namescope="ToRGB", act=F.identity)

        torgb = curr_torgb + prev_torgb

    return torgb

After Change

            outmaps = outmaps // 2
        curr_shape = (1, 1, 2 ** (i + 2), 2 ** (i + 2))
        noise = nn.Variable.from_numpy_array(rnd.randn(*curr_shape))
        h = conv_block(h, w_1, noise, res=2 ** (i + 2), outmaps=outmaps, inmaps=inmaps,
                       kernel_size=3, up=True, namescope="Conv0_up")

        if i > 4:
            inmaps = inmaps // 2
        noise = nn.Variable.from_numpy_array(rnd.randn(*curr_shape))
        h = conv_block(h, w_2, noise, res=2 ** (i + 2), outmaps=outmaps, inmaps=inmaps,
                       kernel_size=3, pad_size=1, namescope="Conv1")

        // toRGB blocks
        prev_torgb = upsample_2d(torgb, k=[1, 3, 3, 1])
        curr_torgb = conv_block(h, w_3, noise=None, res=2 ** (i + 2), outmaps=3, inmaps=inmaps,
                                kernel_size=1, pad_size=0, demodulate=False, namescope="ToRGB", act=F.identity)

        torgb = curr_torgb + prev_torgb

    return torgb

Instances