From fd383140cf405100f3c619f106472273a7545beb Mon Sep 17 00:00:00 2001 From: v0xie <28695009+v0xie@users.noreply.github.com> Date: Mon, 22 Jan 2024 02:52:34 -0800 Subject: fix: wrong devices for eye and constraint --- extensions-builtin/Lora/network_oft.py | 4 ++-- 1 file changed, 2 insertions(+), 2 deletions(-) (limited to 'extensions-builtin') diff --git a/extensions-builtin/Lora/network_oft.py b/extensions-builtin/Lora/network_oft.py index 342fcd0d..d1c46a4b 100644 --- a/extensions-builtin/Lora/network_oft.py +++ b/extensions-builtin/Lora/network_oft.py @@ -57,12 +57,12 @@ class NetworkModuleOFT(network.NetworkModule): def calc_updown(self, orig_weight): oft_blocks = self.oft_blocks.to(orig_weight.device) - eye = torch.eye(self.block_size, device=self.oft_blocks.device) + eye = torch.eye(self.block_size, device=oft_blocks.device) if self.is_kohya: block_Q = oft_blocks - oft_blocks.transpose(1, 2) # ensure skew-symmetric orthogonal matrix norm_Q = torch.norm(block_Q.flatten()) - new_norm_Q = torch.clamp(norm_Q, max=self.constraint) + new_norm_Q = torch.clamp(norm_Q, max=self.constraint.to(oft_blocks.device)) block_Q = block_Q * ((new_norm_Q + 1e-8) / (norm_Q + 1e-8)) oft_blocks = torch.matmul(eye + block_Q, (eye - block_Q).float().inverse()) -- cgit v1.2.1