mirror of https://github.com/vladmandic/automatic
85 lines
4.0 KiB
Python
85 lines
4.0 KiB
Python
import time
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import networks
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import lora_patches
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from modules import extra_networks, shared
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class ExtraNetworkLora(extra_networks.ExtraNetwork):
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def __init__(self):
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super().__init__('lora')
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self.active = False
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self.errors = {}
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networks.originals = lora_patches.LoraPatches()
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"""mapping of network names to the number of errors the network had during operation"""
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def activate(self, p, params_list):
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t0 = time.time()
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self.errors.clear()
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if len(params_list) > 0:
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self.active = True
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networks.originals.apply() # apply patches
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if networks.debug:
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shared.log.debug("LoRA activate")
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names = []
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te_multipliers = []
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unet_multipliers = []
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dyn_dims = []
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for params in params_list:
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assert params.items
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names.append(params.positional[0])
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te_multiplier = float(params.positional[1]) if len(params.positional) > 1 else 1.0
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te_multiplier = float(params.named.get("te", te_multiplier))
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unet_multiplier = [float(params.positional[2]) if len(params.positional) > 2 else te_multiplier] * 3
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unet_multiplier = [float(params.named.get("unet", unet_multiplier[0]))] * 3
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unet_multiplier[0] = float(params.named.get("in", unet_multiplier[0]))
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unet_multiplier[1] = float(params.named.get("mid", unet_multiplier[1]))
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unet_multiplier[2] = float(params.named.get("out", unet_multiplier[2]))
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dyn_dim = int(params.positional[3]) if len(params.positional) > 3 else None
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dyn_dim = int(params.named["dyn"]) if "dyn" in params.named else dyn_dim
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te_multipliers.append(te_multiplier)
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unet_multipliers.append(unet_multiplier)
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dyn_dims.append(dyn_dim)
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t1 = time.time()
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networks.load_networks(names, te_multipliers, unet_multipliers, dyn_dims)
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t2 = time.time()
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if shared.opts.lora_add_hashes_to_infotext:
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network_hashes = []
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for item in networks.loaded_networks:
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shorthash = item.network_on_disk.shorthash
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if not shorthash:
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continue
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alias = item.mentioned_name
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if not alias:
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continue
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alias = alias.replace(":", "").replace(",", "")
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network_hashes.append(f"{alias}: {shorthash}")
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if network_hashes:
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p.extra_generation_params["Lora hashes"] = ", ".join(network_hashes)
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if len(names) > 0:
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shared.log.info(f'LoRA apply: {names} patch={t1-t0:.2f} load={t2-t1:.2f}')
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elif self.active:
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self.active = False
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def deactivate(self, p):
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if shared.backend == shared.Backend.DIFFUSERS and hasattr(shared.sd_model, "unload_lora_weights") and hasattr(shared.sd_model, "text_encoder"):
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if 'CLIP' in shared.sd_model.text_encoder.__class__.__name__ and not (shared.compiled_model_state is not None and shared.compiled_model_state.is_compiled is True):
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if shared.opts.lora_fuse_diffusers:
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shared.sd_model.unfuse_lora()
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try:
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shared.sd_model.unload_lora_weights() # fails for non-CLIP models
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except Exception:
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pass
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if not self.active and getattr(networks, "originals", None ) is not None:
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networks.originals.undo() # remove patches
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if networks.debug:
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shared.log.debug("LoRA deactivate")
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if self.active and networks.debug:
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shared.log.debug(f"LoRA end: load={networks.timer['load']:.2f} apply={networks.timer['apply']:.2f} restore={networks.timer['restore']:.2f}")
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if self.errors:
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p.comment("Networks with errors: " + ", ".join(f"{k} ({v})" for k, v in self.errors.items()))
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for k, v in self.errors.items():
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shared.log.error(f'LoRA errors: file="{k}" errors={v}')
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self.errors.clear()
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