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fix: use merge_weight to cache value

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v0xie 2023-10-21 17:37:17 -07:00
parent 76f5abdbdb
commit de8ee92ed8
1 changed files with 40 additions and 17 deletions
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57
extensions-builtin/Lora/network_oft.py
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@ -29,23 +29,27 @@ class NetworkModuleOFT(network.NetworkModule):
self.block_size = self.out_dim // self.num_blocks
self.org_module: list[torch.Module] = [self.sd_module]
self.org_weight = self.org_module[0].weight.to(self.org_module[0].weight.device, copy=True)
#self.org_weight = self.org_module[0].weight.to(self.org_module[0].weight.device, copy=True)
init_multiplier = self.multiplier() * self.calc_scale()
self.last_multiplier = init_multiplier
self.R = self.get_weight(self.oft_blocks, init_multiplier)
self.hooks = []
self.merged_weight = self.merge_weight()
self.apply_to()
#self.apply_to()
self.applied = False
self.merged = False
def merge_weight(self):
R = self.R.to(self.org_weight.device, dtype=self.org_weight.dtype)
if self.org_weight.dim() == 4:
weight = torch.einsum("oihw, op -> pihw", self.org_weight, R)
org_weight = self.org_module[0].weight
R = self.R.to(org_weight.device, dtype=org_weight.dtype)
if org_weight.dim() == 4:
weight = torch.einsum("oihw, op -> pihw", org_weight, R)
else:
weight = torch.einsum("oi, op -> pi", self.org_weight, R)
weight = torch.einsum("oi, op -> pi", org_weight, R)
return weight
def replace_weight(self, new_weight):
@ -55,17 +59,29 @@ class NetworkModuleOFT(network.NetworkModule):
self.merged = True
def restore_weight(self):
org_sd = self.org_module[0].state_dict()
org_sd['weight'] = self.org_weight
self.org_module[0].load_state_dict(org_sd)
self.merged = False
pass
#org_sd = self.org_module[0].state_dict()
#org_sd['weight'] = self.org_weight
#self.org_module[0].load_state_dict(org_sd)
#self.merged = False
# FIXME: hook forward method of original linear, but how do we undo the hook when we are done?
def apply_to(self):
self.org_forward = self.org_module[0].forward
#self.org_module[0].forward = self.forward
self.org_module[0].register_forward_pre_hook(self.pre_forward_hook)
self.org_module[0].register_forward_hook(self.forward_hook)
if not self.applied:
self.org_forward = self.org_module[0].forward
#self.org_module[0].forward = self.forward
prehook = self.org_module[0].register_forward_pre_hook(self.pre_forward_hook)
hook = self.org_module[0].register_forward_hook(self.forward_hook)
self.hooks.append(prehook)
self.hooks.append(hook)
self.applied = True
def remove_from(self):
if self.applied:
for hook in self.hooks:
hook.remove()
self.hooks = []
self.applied = False
def get_weight(self, oft_blocks, multiplier=None):
multiplier = multiplier.to(oft_blocks.device, dtype=oft_blocks.dtype)
@ -82,14 +98,22 @@ class NetworkModuleOFT(network.NetworkModule):
return R
def calc_updown(self, orig_weight):
if not self.applied:
self.apply_to()
self.merged_weight = self.merged_weight.to(orig_weight.device, dtype=orig_weight.dtype)
updown = torch.zeros_like(orig_weight, device=orig_weight.device, dtype=orig_weight.dtype)
output_shape = orig_weight.shape
orig_weight = self.merged_weight.to(orig_weight.device, dtype=orig_weight.dtype)
orig_weight = self.merged_weight
#output_shape = self.oft_blocks.shape
return self.finalize_updown(updown, orig_weight, output_shape)
def pre_forward_hook(self, module, input):
#if not self.applied:
# self.apply_to()
multiplier = self.multiplier() * self.calc_scale()
if not multiplier==self.last_multiplier or not self.merged:
@ -98,6 +122,5 @@ class NetworkModuleOFT(network.NetworkModule):
self.merged_weight = self.merge_weight()
self.replace_weight(self.merged_weight)
def forward_hook(self, module, args, output):
pass
pass