hoelee/stable-diffusion-webui
1
0
Fork 0
mirror of https://github.com/AUTOMATIC1111/stable-diffusion-webui.git synced 2025-08-08 05:12:35 +00:00
Code Issues Actions Packages Projects Releases Wiki Activity

Lora: output warnings in UI rather than fail for unfitting loras; switch to logging for error output in console

Browse Source
This commit is contained in:
AUTOMATIC1111
2023-08-13 15:07:37 +03:00
parent da80d649fd
commit d8419762c1
4 changed files with 57 additions and 33 deletions
Download Patch File Download Diff File Expand all files Collapse all files

59
extensions-builtin/Lora/networks.py
View File

@@ -1,3 +1,4 @@
import logging
import os
import re
@@ -194,7 +195,7 @@ def load_network(name, network_on_disk):
net.modules[key] = net_module
if keys_failed_to_match:
print(f"Failed to match keys when loading network {network_on_disk.filename}: {keys_failed_to_match}")
logging.debug(f"Network {network_on_disk.filename} didn't match keys: {keys_failed_to_match}")
return net
@@ -207,7 +208,6 @@ def purge_networks_from_memory():
devices.torch_gc()
def load_networks(names, te_multipliers=None, unet_multipliers=None, dyn_dims=None):
already_loaded = {}
@@ -248,7 +248,7 @@ def load_networks(names, te_multipliers=None, unet_multipliers=None, dyn_dims=No
if net is None:
failed_to_load_networks.append(name)
print(f"Couldn't find network with name {name}")
logging.info(f"Couldn't find network with name {name}")
continue
net.te_multiplier = te_multipliers[i] if te_multipliers else 1.0
@@ -257,7 +257,7 @@ def load_networks(names, te_multipliers=None, unet_multipliers=None, dyn_dims=No
loaded_networks.append(net)
if failed_to_load_networks:
sd_hijack.model_hijack.comments.append("Failed to find networks: " + ", ".join(failed_to_load_networks))
sd_hijack.model_hijack.comments.append("Networks not found: " + ", ".join(failed_to_load_networks))
purge_networks_from_memory()
@@ -314,17 +314,22 @@ def network_apply_weights(self: Union[torch.nn.Conv2d, torch.nn.Linear, torch.nn
for net in loaded_networks:
module = net.modules.get(network_layer_name, None)
if module is not None and hasattr(self, 'weight'):
with torch.no_grad():
updown, ex_bias = module.calc_updown(self.weight)
try:
with torch.no_grad():
updown, ex_bias = module.calc_updown(self.weight)
if len(self.weight.shape) == 4 and self.weight.shape[1] == 9:
# inpainting model. zero pad updown to make channel[1] 4 to 9
updown = torch.nn.functional.pad(updown, (0, 0, 0, 0, 0, 5))
if len(self.weight.shape) == 4 and self.weight.shape[1] == 9:
# inpainting model. zero pad updown to make channel[1] 4 to 9
updown = torch.nn.functional.pad(updown, (0, 0, 0, 0, 0, 5))
self.weight += updown
if ex_bias is not None and getattr(self, 'bias', None) is not None:
self.bias += ex_bias
continue
self.weight += updown
if ex_bias is not None and getattr(self, 'bias', None) is not None:
self.bias += ex_bias
except RuntimeError as e:
logging.debug(f"Network {net.name} layer {network_layer_name}: {e}")
extra_network_lora.errors[net.name] = extra_network_lora.errors.get(net.name, 0) + 1
continue
module_q = net.modules.get(network_layer_name + "_q_proj", None)
module_k = net.modules.get(network_layer_name + "_k_proj", None)
@@ -332,21 +337,28 @@ def network_apply_weights(self: Union[torch.nn.Conv2d, torch.nn.Linear, torch.nn
module_out = net.modules.get(network_layer_name + "_out_proj", None)
if isinstance(self, torch.nn.MultiheadAttention) and module_q and module_k and module_v and module_out:
with torch.no_grad():
updown_q = module_q.calc_updown(self.in_proj_weight)
updown_k = module_k.calc_updown(self.in_proj_weight)
updown_v = module_v.calc_updown(self.in_proj_weight)
updown_qkv = torch.vstack([updown_q, updown_k, updown_v])
updown_out = module_out.calc_updown(self.out_proj.weight)
try:
with torch.no_grad():
updown_q = module_q.calc_updown(self.in_proj_weight)
updown_k = module_k.calc_updown(self.in_proj_weight)
updown_v = module_v.calc_updown(self.in_proj_weight)
updown_qkv = torch.vstack([updown_q, updown_k, updown_v])
updown_out = module_out.calc_updown(self.out_proj.weight)
self.in_proj_weight += updown_qkv
self.out_proj.weight += updown_out
continue
self.in_proj_weight += updown_qkv
self.out_proj.weight += updown_out
except RuntimeError as e:
logging.debug(f"Network {net.name} layer {network_layer_name}: {e}")
extra_network_lora.errors[net.name] = extra_network_lora.errors.get(net.name, 0) + 1
continue
if module is None:
continue
print(f'failed to calculate network weights for layer {network_layer_name}')
logging.debug(f"Network {net.name} layer {network_layer_name}: couldn't find supported operation")
extra_network_lora.errors[net.name] = extra_network_lora.errors.get(net.name, 0) + 1
self.network_current_names = wanted_names
@@ -519,6 +531,7 @@ def infotext_pasted(infotext, params):
if added:
params["Prompt"] += "\n" + "".join(added)
extra_network_lora = None
available_networks = {}
available_network_aliases = {}