from __future__ import annotations import os from collections import namedtuple import enum from modules import sd_models, cache, errors, hashes, shared NetworkWeights = namedtuple('NetworkWeights', ['network_key', 'sd_key', 'w', 'sd_module']) metadata_tags_order = {"ss_sd_model_name": 1, "ss_resolution": 2, "ss_clip_skip": 3, "ss_num_train_images": 10, "ss_tag_frequency": 20} class SdVersion(enum.Enum): Unknown = 1 SD1 = 2 SD2 = 3 SDXL = 4 class NetworkOnDisk: def __init__(self, name, filename): self.name = name self.filename = filename self.metadata = {} self.is_safetensors = os.path.splitext(filename)[1].lower() == ".safetensors" def read_metadata(): metadata = sd_models.read_metadata_from_safetensors(filename) metadata.pop('ssmd_cover_images', None) # those are cover images, and they are too big to display in UI as text return metadata if self.is_safetensors: try: self.metadata = cache.cached_data_for_file('safetensors-metadata', "lora/" + self.name, filename, read_metadata) except Exception as e: errors.display(e, f"reading lora {filename}") if self.metadata: m = {} for k, v in sorted(self.metadata.items(), key=lambda x: metadata_tags_order.get(x[0], 999)): m[k] = v self.metadata = m self.alias = self.metadata.get('ss_output_name', self.name) self.hash = None self.shorthash = None self.set_hash( self.metadata.get('sshs_model_hash') or hashes.sha256_from_cache(self.filename, "lora/" + self.name, use_addnet_hash=self.is_safetensors) or '' ) self.sd_version = self.detect_version() def detect_version(self): if str(self.metadata.get('ss_base_model_version', "")).startswith("sdxl_"): return SdVersion.SDXL elif str(self.metadata.get('ss_v2', "")) == "True": return SdVersion.SD2 elif len(self.metadata): return SdVersion.SD1 return SdVersion.Unknown def set_hash(self, v): self.hash = v self.shorthash = self.hash[0:12] if self.shorthash: import networks networks.available_network_hash_lookup[self.shorthash] = self def read_hash(self): if not self.hash: self.set_hash(hashes.sha256(self.filename, "lora/" + self.name, use_addnet_hash=self.is_safetensors) or '') def get_alias(self): import networks if shared.opts.lora_preferred_name == "Filename" or self.alias.lower() in networks.forbidden_network_aliases: return self.name else: return self.alias class Network: # LoraModule def __init__(self, name, network_on_disk: NetworkOnDisk): self.name = name self.network_on_disk = network_on_disk self.te_multiplier = 1.0 self.unet_multiplier = 1.0 self.dyn_dim = None self.modules = {} self.mtime = None self.mentioned_name = None """the text that was used to add the network to prompt - can be either name or an alias""" class ModuleType: def create_module(self, net: Network, weights: NetworkWeights) -> Network | None: return None class NetworkModule: def __init__(self, net: Network, weights: NetworkWeights): self.network = net self.network_key = weights.network_key self.sd_key = weights.sd_key self.sd_module = weights.sd_module if hasattr(self.sd_module, 'weight'): self.shape = self.sd_module.weight.shape self.dim = None self.bias = weights.w.get("bias") self.alpha = weights.w["alpha"].item() if "alpha" in weights.w else None self.scale = weights.w["scale"].item() if "scale" in weights.w else None def multiplier(self): if 'transformer' in self.sd_key[:20]: return self.network.te_multiplier else: return self.network.unet_multiplier def calc_scale(self): if self.scale is not None: return self.scale if self.dim is not None and self.alpha is not None: return self.alpha / self.dim return 1.0 def finalize_updown(self, updown, orig_weight, output_shape, ex_bias=None): if self.bias is not None: updown = updown.reshape(self.bias.shape) updown += self.bias.to(orig_weight.device, dtype=orig_weight.dtype) updown = updown.reshape(output_shape) if len(output_shape) == 4: updown = updown.reshape(output_shape) if orig_weight.size().numel() == updown.size().numel(): updown = updown.reshape(orig_weight.shape) if ex_bias is None: ex_bias = 0 return updown * self.calc_scale() * self.multiplier(), ex_bias * self.multiplier() def calc_updown(self, target): raise NotImplementedError() def forward(self, x, y): raise NotImplementedError()