models/s2s_big_hier_128.py [161:191]:
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                layers.DcConv(n_hid*8*self.n_ctx, n_hid*8*self.n_ctx, 1),
                layers.TemporalConv2d(n_hid*8*self.n_ctx, n_hid*8*2, 1),
                layers.TemporalNorm2d(1, 2*n_hid*8),
            ),
            'layer_10': nn.Sequential(
                layers.DcConv(n_hid*8*self.n_ctx, n_hid*8*self.n_ctx, 1),
                layers.TemporalConv2d(n_hid*8*self.n_ctx, n_hid*8*2, 1),
                layers.TemporalNorm2d(16, 2*n_hid*8),
            ),
            'layer_4': nn.Sequential(
                layers.DcConv(n_hid*2*self.n_ctx, n_hid*2*self.n_ctx, 1),
                layers.TemporalConv2d(n_hid*2*self.n_ctx, n_hid*2*2, 1),
                layers.TemporalNorm2d(16, 2*n_hid*2),
            ),
        })

        self.posterior_branches = nn.ModuleDict({
            'layer_4': nn.ModuleList([
                layers.TemporalConv2d(n_hid*2, n_hid*2, 1),
                layers.TemporalNorm2d(16, n_hid*2),
                layers.ConvLSTM(n_hid*2, n_hid*2, norm=True),
                layers.TemporalConv2d(n_hid*2 + n_hid*8 + n_hid*8, n_hid*2*2, 1),
                layers.TemporalNorm2d(16, n_hid*2*2),
            ]),
            'layer_10': nn.ModuleList([
                layers.TemporalConv2d(n_hid*8, n_hid*8, 1),
                layers.TemporalNorm2d(16, n_hid*8),
                layers.ConvLSTM(n_hid*8, n_hid*8, norm=True),
                layers.TemporalConv2d(n_hid*8 + n_hid*8, n_hid*8*2, 1),
                layers.TemporalNorm2d(16, n_hid*8*2),
            ]),
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models/s2s_big_hier_v4.py [155:185]:
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                layers.DcConv(n_hid*8*self.n_ctx, n_hid*8*self.n_ctx, 1),
                layers.TemporalConv2d(n_hid*8*self.n_ctx, n_hid*8*2, 1),
                layers.TemporalNorm2d(1, 2*n_hid*8),
            ),
            'layer_10': nn.Sequential(
                layers.DcConv(n_hid*8*self.n_ctx, n_hid*8*self.n_ctx, 1),
                layers.TemporalConv2d(n_hid*8*self.n_ctx, n_hid*8*2, 1),
                layers.TemporalNorm2d(16, 2*n_hid*8),
            ),
            'layer_4': nn.Sequential(
                layers.DcConv(n_hid*2*self.n_ctx, n_hid*2*self.n_ctx, 1),
                layers.TemporalConv2d(n_hid*2*self.n_ctx, n_hid*2*2, 1),
                layers.TemporalNorm2d(16, 2*n_hid*2),
            ),
        })

        self.posterior_branches = nn.ModuleDict({
            'layer_4': nn.ModuleList([
                layers.TemporalConv2d(n_hid*2, n_hid*2, 1),
                layers.TemporalNorm2d(16, n_hid*2),
                layers.ConvLSTM(n_hid*2, n_hid*2, norm=True),
                layers.TemporalConv2d(n_hid*2 + n_hid*8 + n_hid*8, n_hid*2*2, 1),
                layers.TemporalNorm2d(16, n_hid*2*2),
            ]),
            'layer_10': nn.ModuleList([
                layers.TemporalConv2d(n_hid*8, n_hid*8, 1),
                layers.TemporalNorm2d(16, n_hid*8),
                layers.ConvLSTM(n_hid*8, n_hid*8, norm=True),
                layers.TemporalConv2d(n_hid*8 + n_hid*8, n_hid*8*2, 1),
                layers.TemporalNorm2d(16, n_hid*8*2),
            ]),
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