diff options
Diffstat (limited to 'extensions-builtin')
| -rw-r--r-- | extensions-builtin/Lora/extra_networks_lora.py | 10 | ||||
| -rw-r--r-- | extensions-builtin/Lora/networks.py | 69 | ||||
| -rw-r--r-- | extensions-builtin/Lora/scripts/lora_script.py | 6 | ||||
| -rw-r--r-- | extensions-builtin/Lora/ui_extra_networks_lora.py | 3 |
4 files changed, 55 insertions, 33 deletions
diff --git a/extensions-builtin/Lora/extra_networks_lora.py b/extensions-builtin/Lora/extra_networks_lora.py index ba2945c6..005ff32c 100644 --- a/extensions-builtin/Lora/extra_networks_lora.py +++ b/extensions-builtin/Lora/extra_networks_lora.py @@ -6,9 +6,14 @@ class ExtraNetworkLora(extra_networks.ExtraNetwork): def __init__(self):
super().__init__('lora')
+ self.errors = {}
+ """mapping of network names to the number of errors the network had during operation"""
+
def activate(self, p, params_list):
additional = shared.opts.sd_lora
+ self.errors.clear()
+
if additional != "None" and additional in networks.available_networks and not any(x for x in params_list if x.items[0] == additional):
p.all_prompts = [x + f"<lora:{additional}:{shared.opts.extra_networks_default_multiplier}>" for x in p.all_prompts]
params_list.append(extra_networks.ExtraNetworkParams(items=[additional, shared.opts.extra_networks_default_multiplier]))
@@ -56,4 +61,7 @@ class ExtraNetworkLora(extra_networks.ExtraNetwork): p.extra_generation_params["Lora hashes"] = ", ".join(network_hashes)
def deactivate(self, p):
- pass
+ if self.errors:
+ p.comment("Networks with errors: " + ", ".join(f"{k} ({v})" for k, v in self.errors.items()))
+
+ self.errors.clear()
diff --git a/extensions-builtin/Lora/networks.py b/extensions-builtin/Lora/networks.py index 1645b822..96d14344 100644 --- a/extensions-builtin/Lora/networks.py +++ b/extensions-builtin/Lora/networks.py @@ -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()
@@ -327,20 +327,25 @@ 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)
-
- 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))
+ 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))
+
+ self.weight += updown
+ if ex_bias is not None and hasattr(self, 'bias'):
+ if self.bias is None:
+ self.bias = torch.nn.Parameter(ex_bias)
+ else:
+ 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
- self.weight += updown
- if ex_bias is not None and hasattr(self, 'bias'):
- if self.bias is None:
- self.bias = torch.nn.Parameter(ex_bias)
- else:
- self.bias += ex_bias
- continue
+ continue
module_q = net.modules.get(network_layer_name + "_q_proj", None)
module_k = net.modules.get(network_layer_name + "_k_proj", None)
@@ -348,26 +353,33 @@ 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, ex_bias = module_out.calc_updown(self.out_proj.weight)
-
- self.in_proj_weight += updown_qkv
- self.out_proj.weight += updown_out
+ 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, ex_bias = module_out.calc_updown(self.out_proj.weight)
+
+ self.in_proj_weight += updown_qkv
+ self.out_proj.weight += updown_out
if ex_bias is not None:
if self.out_proj.bias is None:
self.out_proj.bias = torch.nn.Parameter(ex_bias)
else:
self.out_proj.bias += ex_bias
- continue
+
+ 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
@@ -540,6 +552,7 @@ def infotext_pasted(infotext, params): if added:
params["Prompt"] += "\n" + "".join(added)
+extra_network_lora = None
available_networks = {}
available_network_aliases = {}
diff --git a/extensions-builtin/Lora/scripts/lora_script.py b/extensions-builtin/Lora/scripts/lora_script.py index dc307f8c..4c6e774a 100644 --- a/extensions-builtin/Lora/scripts/lora_script.py +++ b/extensions-builtin/Lora/scripts/lora_script.py @@ -23,9 +23,9 @@ def unload(): def before_ui():
ui_extra_networks.register_page(ui_extra_networks_lora.ExtraNetworksPageLora())
- extra_network = extra_networks_lora.ExtraNetworkLora()
- extra_networks.register_extra_network(extra_network)
- extra_networks.register_extra_network_alias(extra_network, "lyco")
+ networks.extra_network_lora = extra_networks_lora.ExtraNetworkLora()
+ extra_networks.register_extra_network(networks.extra_network_lora)
+ extra_networks.register_extra_network_alias(networks.extra_network_lora, "lyco")
if not hasattr(torch.nn, 'Linear_forward_before_network'):
diff --git a/extensions-builtin/Lora/ui_extra_networks_lora.py b/extensions-builtin/Lora/ui_extra_networks_lora.py index 3629e5c0..55409a78 100644 --- a/extensions-builtin/Lora/ui_extra_networks_lora.py +++ b/extensions-builtin/Lora/ui_extra_networks_lora.py @@ -25,9 +25,10 @@ class ExtraNetworksPageLora(ui_extra_networks.ExtraNetworksPage): item = {
"name": name,
"filename": lora_on_disk.filename,
+ "shorthash": lora_on_disk.shorthash,
"preview": self.find_preview(path),
"description": self.find_description(path),
- "search_term": self.search_terms_from_path(lora_on_disk.filename),
+ "search_term": self.search_terms_from_path(lora_on_disk.filename) + " " + (lora_on_disk.hash or ""),
"local_preview": f"{path}.{shared.opts.samples_format}",
"metadata": lora_on_disk.metadata,
"sort_keys": {'default': index, **self.get_sort_keys(lora_on_disk.filename)},
|