Pillow 9.5.0 ->10.0.1 blendmodes 2022 -> 2023

extensions-builtin/Lora/lora_logger.py

@@ -1,33 +0,0 @@
-import sys
-import copy
-import logging
-
-
-class ColoredFormatter(logging.Formatter):
-    COLORS = {
-        "DEBUG": "\033[0;36m",  # CYAN
-        "INFO": "\033[0;32m",  # GREEN
-        "WARNING": "\033[0;33m",  # YELLOW
-        "ERROR": "\033[0;31m",  # RED
-        "CRITICAL": "\033[0;37;41m",  # WHITE ON RED
-        "RESET": "\033[0m",  # RESET COLOR
-    }
-
-    def format(self, record):
-        colored_record = copy.copy(record)
-        levelname = colored_record.levelname
-        seq = self.COLORS.get(levelname, self.COLORS["RESET"])
-        colored_record.levelname = f"{seq}{levelname}{self.COLORS['RESET']}"
-        return super().format(colored_record)
-
-
-logger = logging.getLogger("lora")
-logger.propagate = False
-
-
-if not logger.handlers:
-    handler = logging.StreamHandler(sys.stdout)
-    handler.setFormatter(
-        ColoredFormatter("[%(name)s]-%(levelname)s: %(message)s")
-    )
-    logger.addHandler(handler)

extensions-builtin/Lora/network.py

@@ -93,7 +93,6 @@ class Network:  # LoraModule
         self.unet_multiplier = 1.0
         self.dyn_dim = None
         self.modules = {}
-        self.bundle_embeddings = {}
         self.mtime = None
 
         self.mentioned_name = None

extensions-builtin/Lora/networks.py

@@ -15,9 +15,6 @@ import torch
 from typing import Union
 
 from modules import shared, devices, sd_models, errors, scripts, sd_hijack
-from modules.textual_inversion.textual_inversion import Embedding
-
-from lora_logger import logger
 
 module_types = [
     network_lora.ModuleTypeLora(),
@@ -152,19 +149,9 @@ def load_network(name, network_on_disk):
     is_sd2 = 'model_transformer_resblocks' in shared.sd_model.network_layer_mapping
 
     matched_networks = {}
-    bundle_embeddings = {}
 
     for key_network, weight in sd.items():
         key_network_without_network_parts, network_part = key_network.split(".", 1)
-        if key_network_without_network_parts == "bundle_emb":
-            emb_name, vec_name = network_part.split(".", 1)
-            emb_dict = bundle_embeddings.get(emb_name, {})
-            if vec_name.split('.')[0] == 'string_to_param':
-                _, k2 = vec_name.split('.', 1)
-                emb_dict['string_to_param'] = {k2: weight}
-            else:
-                emb_dict[vec_name] = weight
-            bundle_embeddings[emb_name] = emb_dict
 
         key = convert_diffusers_name_to_compvis(key_network_without_network_parts, is_sd2)
         sd_module = shared.sd_model.network_layer_mapping.get(key, None)
@@ -208,41 +195,6 @@ def load_network(name, network_on_disk):
 
         net.modules[key] = net_module
 
-    embeddings = {}
-    for emb_name, data in bundle_embeddings.items():
-        # textual inversion embeddings
-        if 'string_to_param' in data:
-            param_dict = data['string_to_param']
-            param_dict = getattr(param_dict, '_parameters', param_dict)  # fix for torch 1.12.1 loading saved file from torch 1.11
-            assert len(param_dict) == 1, 'embedding file has multiple terms in it'
-            emb = next(iter(param_dict.items()))[1]
-            vec = emb.detach().to(devices.device, dtype=torch.float32)
-            shape = vec.shape[-1]
-            vectors = vec.shape[0]
-        elif type(data) == dict and 'clip_g' in data and 'clip_l' in data:  # SDXL embedding
-            vec = {k: v.detach().to(devices.device, dtype=torch.float32) for k, v in data.items()}
-            shape = data['clip_g'].shape[-1] + data['clip_l'].shape[-1]
-            vectors = data['clip_g'].shape[0]
-        elif type(data) == dict and type(next(iter(data.values()))) == torch.Tensor: # diffuser concepts
-            assert len(data.keys()) == 1, 'embedding file has multiple terms in it'
-
-            emb = next(iter(data.values()))
-            if len(emb.shape) == 1:
-                emb = emb.unsqueeze(0)
-            vec = emb.detach().to(devices.device, dtype=torch.float32)
-            shape = vec.shape[-1]
-            vectors = vec.shape[0]
-        else:
-            raise Exception(f"Couldn't identify {emb_name} in lora: {name} as neither textual inversion embedding nor diffuser concept.")
-
-        embedding = Embedding(vec, emb_name)
-        embedding.vectors = vectors
-        embedding.shape = shape
-        embedding.loaded = None
-        embeddings[emb_name] = embedding
-
-    net.bundle_embeddings = embeddings
-
     if keys_failed_to_match:
         logging.debug(f"Network {network_on_disk.filename} didn't match keys: {keys_failed_to_match}")
 
@@ -258,16 +210,11 @@ def purge_networks_from_memory():
 
 
 def load_networks(names, te_multipliers=None, unet_multipliers=None, dyn_dims=None):
-    emb_db = sd_hijack.model_hijack.embedding_db
     already_loaded = {}
 
     for net in loaded_networks:
         if net.name in names:
             already_loaded[net.name] = net
-        for emb_name, embedding in net.bundle_embeddings.items():
-            if embedding.loaded:
-                embedding.loaded = None
-                emb_db.register_embedding_by_name(None, shared.sd_model, emb_name)
 
     loaded_networks.clear()
 
@@ -310,21 +257,6 @@ def load_networks(names, te_multipliers=None, unet_multipliers=None, dyn_dims=No
         net.dyn_dim = dyn_dims[i] if dyn_dims else 1.0
         loaded_networks.append(net)
 
-        for emb_name, embedding in net.bundle_embeddings.items():
-            if embedding.loaded is None and emb_name in emb_db.word_embeddings:
-                logger.warning(
-                    f'Skip bundle embedding: "{emb_name}"'
-                    ' as it was already loaded from embeddings folder'
-                )
-                continue
-
-            embedding.loaded = False
-            if emb_db.expected_shape == -1 or emb_db.expected_shape == embedding.shape:
-                embedding.loaded = True
-                emb_db.register_embedding(embedding, shared.sd_model)
-            else:
-                emb_db.skipped_embeddings[name] = embedding
-
     if failed_to_load_networks:
         sd_hijack.model_hijack.comments.append("Networks not found: " + ", ".join(failed_to_load_networks))
 
@@ -633,7 +565,6 @@ extra_network_lora = None
 available_networks = {}
 available_network_aliases = {}
 loaded_networks = []
-loaded_bundle_embeddings = {}
 networks_in_memory = {}
 available_network_hash_lookup = {}
 forbidden_network_aliases = {}

requirements_versions.txt

@@ -1,8 +1,8 @@
 GitPython==3.1.32
-Pillow==9.5.0
+Pillow==10.0.1
 accelerate==0.21.0
 basicsr==1.4.2
-blendmodes==2022
+blendmodes==2023
 clean-fid==0.1.35
 einops==0.4.1
 fastapi==0.94.0