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Fix taesd VAE in lowvram mode.
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@ -7,9 +7,10 @@ import torch
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import torch.nn as nn
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import torch.nn as nn
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import comfy.utils
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import comfy.utils
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import comfy.ops
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def conv(n_in, n_out, **kwargs):
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def conv(n_in, n_out, **kwargs):
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return nn.Conv2d(n_in, n_out, 3, padding=1, **kwargs)
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return comfy.ops.disable_weight_init.Conv2d(n_in, n_out, 3, padding=1, **kwargs)
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class Clamp(nn.Module):
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class Clamp(nn.Module):
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def forward(self, x):
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def forward(self, x):
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@ -19,7 +20,7 @@ class Block(nn.Module):
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def __init__(self, n_in, n_out):
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def __init__(self, n_in, n_out):
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super().__init__()
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super().__init__()
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self.conv = nn.Sequential(conv(n_in, n_out), nn.ReLU(), conv(n_out, n_out), nn.ReLU(), conv(n_out, n_out))
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self.conv = nn.Sequential(conv(n_in, n_out), nn.ReLU(), conv(n_out, n_out), nn.ReLU(), conv(n_out, n_out))
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self.skip = nn.Conv2d(n_in, n_out, 1, bias=False) if n_in != n_out else nn.Identity()
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self.skip = comfy.ops.disable_weight_init.Conv2d(n_in, n_out, 1, bias=False) if n_in != n_out else nn.Identity()
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self.fuse = nn.ReLU()
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self.fuse = nn.ReLU()
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def forward(self, x):
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def forward(self, x):
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return self.fuse(self.conv(x) + self.skip(x))
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return self.fuse(self.conv(x) + self.skip(x))
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