Loading extensions-builtin/Lora/network_ia3.py +0 −1 Original line number Diff line number Diff line import lyco_helpers import network import network_lyco Loading extensions-builtin/Lora/network_lokr.py 0 → 100644 +65 −0 Original line number Diff line number Diff line import torch import lyco_helpers import network import network_lyco class ModuleTypeLokr(network.ModuleType): def create_module(self, net: network.Network, weights: network.NetworkWeights): has_1 = "lokr_w1" in weights.w or ("lokr_w1a" in weights.w and "lokr_w1b" in weights.w) has_2 = "lokr_w2" in weights.w or ("lokr_w2a" in weights.w and "lokr_w2b" in weights.w) if has_1 and has_2: return NetworkModuleLokr(net, weights) return None def make_kron(orig_shape, w1, w2): if len(w2.shape) == 4: w1 = w1.unsqueeze(2).unsqueeze(2) w2 = w2.contiguous() return torch.kron(w1, w2).reshape(orig_shape) class NetworkModuleLokr(network_lyco.NetworkModuleLyco): def __init__(self, net: network.Network, weights: network.NetworkWeights): super().__init__(net, weights) self.w1 = weights.w.get("lokr_w1") self.w1a = weights.w.get("lokr_w1_a") self.w1b = weights.w.get("lokr_w1_b") self.dim = self.w1b.shape[0] if self.w1b else self.dim self.w2 = weights.w.get("lokr_w2") self.w2a = weights.w.get("lokr_w2_a") self.w2b = weights.w.get("lokr_w2_b") self.dim = self.w2b.shape[0] if self.w2b else self.dim self.t2 = weights.w.get("lokr_t2") def calc_updown(self, orig_weight): if self.w1 is not None: w1 = self.w1.to(orig_weight.device, dtype=orig_weight.dtype) else: w1a = self.w1a.to(orig_weight.device, dtype=orig_weight.dtype) w1b = self.w1b.to(orig_weight.device, dtype=orig_weight.dtype) w1 = w1a @ w1b if self.w2 is not None: w2 = self.w2.to(orig_weight.device, dtype=orig_weight.dtype) elif self.t2 is None: w2a = self.w2a.to(orig_weight.device, dtype=orig_weight.dtype) w2b = self.w2b.to(orig_weight.device, dtype=orig_weight.dtype) w2 = w2a @ w2b else: t2 = self.t2.to(orig_weight.device, dtype=orig_weight.dtype) w2a = self.w2a.to(orig_weight.device, dtype=orig_weight.dtype) w2b = self.w2b.to(orig_weight.device, dtype=orig_weight.dtype) w2 = lyco_helpers.make_weight_cp(t2, w2a, w2b) output_shape = [w1.size(0) * w2.size(0), w1.size(1) * w2.size(1)] if len(orig_weight.shape) == 4: output_shape = orig_weight.shape updown = make_kron(output_shape, w1, w2) return self.finalize_updown(updown, orig_weight, output_shape) extensions-builtin/Lora/networks.py +2 −0 Original line number Diff line number Diff line Loading @@ -5,6 +5,7 @@ import network import network_lora import network_hada import network_ia3 import network_lokr import torch from typing import Union Loading @@ -15,6 +16,7 @@ module_types = [ network_lora.ModuleTypeLora(), network_hada.ModuleTypeHada(), network_ia3.ModuleTypeIa3(), network_lokr.ModuleTypeLokr(), ] Loading Loading
extensions-builtin/Lora/network_ia3.py +0 −1 Original line number Diff line number Diff line import lyco_helpers import network import network_lyco Loading
extensions-builtin/Lora/network_lokr.py 0 → 100644 +65 −0 Original line number Diff line number Diff line import torch import lyco_helpers import network import network_lyco class ModuleTypeLokr(network.ModuleType): def create_module(self, net: network.Network, weights: network.NetworkWeights): has_1 = "lokr_w1" in weights.w or ("lokr_w1a" in weights.w and "lokr_w1b" in weights.w) has_2 = "lokr_w2" in weights.w or ("lokr_w2a" in weights.w and "lokr_w2b" in weights.w) if has_1 and has_2: return NetworkModuleLokr(net, weights) return None def make_kron(orig_shape, w1, w2): if len(w2.shape) == 4: w1 = w1.unsqueeze(2).unsqueeze(2) w2 = w2.contiguous() return torch.kron(w1, w2).reshape(orig_shape) class NetworkModuleLokr(network_lyco.NetworkModuleLyco): def __init__(self, net: network.Network, weights: network.NetworkWeights): super().__init__(net, weights) self.w1 = weights.w.get("lokr_w1") self.w1a = weights.w.get("lokr_w1_a") self.w1b = weights.w.get("lokr_w1_b") self.dim = self.w1b.shape[0] if self.w1b else self.dim self.w2 = weights.w.get("lokr_w2") self.w2a = weights.w.get("lokr_w2_a") self.w2b = weights.w.get("lokr_w2_b") self.dim = self.w2b.shape[0] if self.w2b else self.dim self.t2 = weights.w.get("lokr_t2") def calc_updown(self, orig_weight): if self.w1 is not None: w1 = self.w1.to(orig_weight.device, dtype=orig_weight.dtype) else: w1a = self.w1a.to(orig_weight.device, dtype=orig_weight.dtype) w1b = self.w1b.to(orig_weight.device, dtype=orig_weight.dtype) w1 = w1a @ w1b if self.w2 is not None: w2 = self.w2.to(orig_weight.device, dtype=orig_weight.dtype) elif self.t2 is None: w2a = self.w2a.to(orig_weight.device, dtype=orig_weight.dtype) w2b = self.w2b.to(orig_weight.device, dtype=orig_weight.dtype) w2 = w2a @ w2b else: t2 = self.t2.to(orig_weight.device, dtype=orig_weight.dtype) w2a = self.w2a.to(orig_weight.device, dtype=orig_weight.dtype) w2b = self.w2b.to(orig_weight.device, dtype=orig_weight.dtype) w2 = lyco_helpers.make_weight_cp(t2, w2a, w2b) output_shape = [w1.size(0) * w2.size(0), w1.size(1) * w2.size(1)] if len(orig_weight.shape) == 4: output_shape = orig_weight.shape updown = make_kron(output_shape, w1, w2) return self.finalize_updown(updown, orig_weight, output_shape)
extensions-builtin/Lora/networks.py +2 −0 Original line number Diff line number Diff line Loading @@ -5,6 +5,7 @@ import network import network_lora import network_hada import network_ia3 import network_lokr import torch from typing import Union Loading @@ -15,6 +16,7 @@ module_types = [ network_lora.ModuleTypeLora(), network_hada.ModuleTypeHada(), network_ia3.ModuleTypeIa3(), network_lokr.ModuleTypeLokr(), ] Loading
