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(requested) support AMD 8GB GPUs via Windows DirectML

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this update is requested by users
This commit is contained in:
lllyasviel
2023-12-30 06:30:59 -08:00
committed by GitHub
parent c0e11c3451
commit 8e62a72a63
31 changed files with 402 additions and 148 deletions
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ldm_patched/taesd/taesd.py
+3 -2
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@@ -7,9 +7,10 @@ import torch
import torch.nn as nn
import ldm_patched.modules.utils
import ldm_patched.modules.ops
def conv(n_in, n_out, **kwargs):
return nn.Conv2d(n_in, n_out, 3, padding=1, **kwargs)
return ldm_patched.modules.ops.disable_weight_init.Conv2d(n_in, n_out, 3, padding=1, **kwargs)
class Clamp(nn.Module):
def forward(self, x):
@@ -19,7 +20,7 @@ class Block(nn.Module):
def __init__(self, n_in, n_out):
super().__init__()
self.conv = nn.Sequential(conv(n_in, n_out), nn.ReLU(), conv(n_out, n_out), nn.ReLU(), conv(n_out, n_out))
self.skip = nn.Conv2d(n_in, n_out, 1, bias=False) if n_in != n_out else nn.Identity()
self.skip = ldm_patched.modules.ops.disable_weight_init.Conv2d(n_in, n_out, 1, bias=False) if n_in != n_out else nn.Identity()
self.fuse = nn.ReLU()
def forward(self, x):
return self.fuse(self.conv(x) + self.skip(x))