Fix control lora on fp8.
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be3468ddd5
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26b1c0a771
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@ -208,7 +208,7 @@ class ControlLoraOps:
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def forward(self, input):
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def forward(self, input):
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if self.up is not None:
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if self.up is not None:
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return torch.nn.functional.linear(input, self.weight.to(input.device) + (torch.mm(self.up.flatten(start_dim=1), self.down.flatten(start_dim=1))).reshape(self.weight.shape).type(input.dtype), self.bias)
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return torch.nn.functional.linear(input, self.weight.to(input.dtype).to(input.device) + (torch.mm(self.up.flatten(start_dim=1), self.down.flatten(start_dim=1))).reshape(self.weight.shape).type(input.dtype), self.bias)
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else:
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else:
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return torch.nn.functional.linear(input, self.weight.to(input.device), self.bias)
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return torch.nn.functional.linear(input, self.weight.to(input.device), self.bias)
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@ -247,7 +247,7 @@ class ControlLoraOps:
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def forward(self, input):
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def forward(self, input):
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if self.up is not None:
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if self.up is not None:
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return torch.nn.functional.conv2d(input, self.weight.to(input.device) + (torch.mm(self.up.flatten(start_dim=1), self.down.flatten(start_dim=1))).reshape(self.weight.shape).type(input.dtype), self.bias, self.stride, self.padding, self.dilation, self.groups)
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return torch.nn.functional.conv2d(input, self.weight.to(input.dtype).to(input.device) + (torch.mm(self.up.flatten(start_dim=1), self.down.flatten(start_dim=1))).reshape(self.weight.shape).type(input.dtype), self.bias, self.stride, self.padding, self.dilation, self.groups)
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else:
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else:
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return torch.nn.functional.conv2d(input, self.weight.to(input.device), self.bias, self.stride, self.padding, self.dilation, self.groups)
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return torch.nn.functional.conv2d(input, self.weight.to(input.device), self.bias, self.stride, self.padding, self.dilation, self.groups)
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