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Merge pull request #370 from sfinktah/sfink-debug
Fix for AMD error when not using tiled VAE decoding
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commit
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@ -33,9 +33,27 @@ class CausalConv3d(nn.Conv3d):
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padding[4] -= cache_x.shape[2]
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padding[4] -= cache_x.shape[2]
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cache_x = None
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cache_x = None
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x = F.pad(x, padding)
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x = F.pad(x, padding)
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x = super().forward(x)
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try:
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out = super().forward(x)
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return x
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return out
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except RuntimeError as e:
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if "miopenStatus" in str(e):
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print("⚠️ MIOpen fallback: AMD gets upset when trying to work with large areas, and so CPU will be "
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"used for this decoding (which is very slow). Consider using tiled VAE Decoding.")
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x_cpu = x.float().cpu()
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weight_cpu = self.weight.float().cpu()
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bias_cpu = self.bias.float().cpu() if self.bias is not None else None
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print(f"[Fallback] x shape: {x_cpu.shape}, weight shape: {weight_cpu.shape}")
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out = F.conv3d(x_cpu, weight_cpu, bias_cpu,
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self.stride, (0, 0, 0), # avoid double padding here
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self.dilation, self.groups)
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out = out.to(x.device)
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if x.dtype in (torch.float16, torch.bfloat16):
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out = out.half()
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if x.dtype != out.dtype:
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out = out.to(x.dtype)
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return out
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raise
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class RMS_norm(nn.Module):
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class RMS_norm(nn.Module):
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