forge classic

install.py

@@ -36,6 +36,7 @@ def is_installed(pip_package):
 requirements = [
 "diffusers==0.31.0",
 "scikit-learn",
+"accelerate"
 ]
 
 for module in requirements:

scripts/A1111/networks.py

@@ -18,7 +18,7 @@ import scripts.A1111.network_oft as network_oft
 import torch
 from typing import Union
 
-from modules import shared, devices, sd_models, errors, scripts, sd_hijack
+from modules import shared, devices, sd_models, errors, scripts, sd_hijack, launch_utils
 import modules.textual_inversion.textual_inversion as textual_inversion
 
 class QkvLinear(torch.nn.Linear):
@@ -34,8 +34,8 @@ module_types = [
     network_glora.ModuleTypeGLora(),
     network_oft.ModuleTypeOFT(),
 ]
-from modules.ui import versions_html
-forge = "forge" in versions_html()
+
+forge = launch_utils.git_tag()[0:2] == "f2"
 
 re_digits = re.compile(r"\d+")
 re_x_proj = re.compile(r"(.*)_([qkv]_proj)$")
@@ -676,7 +676,10 @@ def network_MultiheadAttention_load_state_dict(self, *args, **kwargs):
 
 def process_network_files(names: list[str] | None = None):
     candidates = list(shared.walk_files(shared.cmd_opts.lora_dir, allowed_extensions=[".pt", ".ckpt", ".safetensors"]))
-    candidates += list(shared.walk_files(shared.cmd_opts.lyco_dir_backcompat, allowed_extensions=[".pt", ".ckpt", ".safetensors"]))
+    try:
+        candidates += list(shared.walk_files(shared.cmd_opts.lyco_dir_backcompat, allowed_extensions=[".pt", ".ckpt", ".safetensors"]))
+    except:
+        pass
     for filename in candidates:
         if os.path.isdir(filename):
             continue

scripts/GenParamGetter.py

@@ -71,7 +71,6 @@ class GenParamGetter(scripts.Script):
         return components
     
     def compare_components_with_ids(components: list[gr.Blocks], ids: list[int]):
-        
         try:
             return len(components) == len(ids) and all(component._id == _id for component, _id in zip(components, ids))
         except:
@@ -80,8 +79,10 @@ class GenParamGetter(scripts.Script):
     def get_params_components(demo: gr.Blocks, app):
         for _id, _is_txt2img in zip([GenParamGetter.txt2img_gen_button._id, GenParamGetter.img2img_gen_button._id], [True, False]):
             if hasattr(demo,"dependencies"):
-                dependencies: list[dict] = [x for x in demo.dependencies if x["trigger"] == "click" and _id in x["targets"]]
+                #dependencies: list[dict] = [x for x in demo.dependencies if x["trigger"] == "click" and _id in x["targets"]]
+                dependencies: list[dict] = [x for x in demo.dependencies if _id in x["targets"]]
                 g4 = False
+                
             else:
                 dependencies: list[dict] = [x for x in demo.config["dependencies"] if x["targets"][0][1] == "click" and _id in x["targets"][0]]
                 g4 = True
@@ -91,6 +92,7 @@ class GenParamGetter(scripts.Script):
             for d in dependencies:
                 if len(d["outputs"]) == 4:
                     dependency = d
+                    print("GenParamsGetter detected!")
             
             if g4:
                 params = [demo.blocks[x] for x in dependency['inputs']]
@@ -102,6 +104,8 @@ class GenParamGetter(scripts.Script):
                 else:
                     components.img2img_params = params
             else:
+                if dependency is None:continue
+
                 params = [params for params in demo.fns if GenParamGetter.compare_components_with_ids(params.inputs, dependency["inputs"])]
 
                 if _is_txt2img:
@@ -111,7 +115,6 @@ class GenParamGetter(scripts.Script):
                     components.txt2img_params = params[0].inputs 
                 else:
                     components.img2img_params = params[0].inputs
-
         
         if not GenParamGetter.events_assigned:
             with demo:

scripts/mergers/mergers.py

@@ -1187,7 +1187,7 @@ def simggen(s_prompt,s_nprompt,s_steps,s_sampler,s_cfg,s_seed,s_w,s_h,s_batch_si
         elif wantedv and wantedv in paramsnames:return txt2imgparams[paramsnames.index(wantedv)]
         else:return None
 
-    sampler_index = g("Sampling method")
+    sampler_index = g("Sampling method","Sampling Method")
     if type(sampler_index) is str:
         sampler_name = sampler_index
     else:       
@@ -1206,7 +1206,7 @@ def simggen(s_prompt,s_nprompt,s_steps,s_sampler,s_cfg,s_seed,s_w,s_h,s_batch_si
         outpath_grids=opts.outdir_grids or opts.outdir_txt2img_grids,
         prompt=g("Prompt"),
         styles=g("Styles"),
-        negative_prompt=g('Negative prompt'),
+        negative_prompt=g('Negative prompt','Negative Prompt'),
         seed=g("Seed","Initial seed"),
         subseed=g("Variation seed"),
         subseed_strength=g("Variation strength"),
@@ -1214,9 +1214,9 @@ def simggen(s_prompt,s_nprompt,s_steps,s_sampler,s_cfg,s_seed,s_w,s_h,s_batch_si
         seed_resize_from_w=g("Resize seed from width"),
         seed_enable_extras=g("Extra"),
         sampler_name=sampler_name,
-        batch_size=g("Batch size"),
-        n_iter=g("Batch count"),
-        steps=g("Sampling steps"),
+        batch_size=g("Batch size","Batch Size"),
+        n_iter=g("Batch count","Batch Count"),
+        steps=g("Sampling steps","Sampling Steps"),
         cfg_scale=g("CFG Scale"),
         width=g("Width"),
         height=g("Height"),

scripts/mergers/pluslora.py

@@ -15,7 +15,7 @@ import numpy as np
 import safetensors.torch
 import scripts.mergers.components as components
 import torch
-from modules import extra_networks, scripts, sd_models, lowvram
+from modules import extra_networks, scripts, sd_models, launch_utils
 from modules.ui import create_refresh_button
 from safetensors.torch import load_file, save_file
 from scripts.kohyas import extract_lora_from_models as ext
@@ -23,9 +23,8 @@ from scripts.A1111 import networks as nets
 from scripts.mergers.model_util import filenamecutter, savemodel
 from scripts.mergers.mergers import extract_super, unload_forge, q_dequantize, q_quantize, qdtyper, prefixer, BLOCKIDFLUX
 from tqdm import tqdm
-from modules.ui import versions_html
 
-forge = "forge" in versions_html()
+forge = launch_utils.git_tag()[0:2] == "f2"
 
 selectable = []
 pchanged = False
@@ -314,7 +313,7 @@ def makelora(model_a,model_b,dim,saveto,settings,alpha,beta,save_precision,calc_
     except:
         currentinfo = None
 
-    lowvram.module_in_gpu = None #web-uiのバグ対策
+    lowvramdealer() #web-uiのバグ対策
 
     checkpoint_info = sd_models.get_closet_checkpoint_match(model_a)
     load_model(checkpoint_info)
@@ -809,7 +808,7 @@ def pluslora(lnames,loraratios,settings,output,model,save_precision,calc_precisi
             elif "model_" in skey:
                 keychanger[skey.split("model_",1)[1]] = key
 
-    lowvram.module_in_gpu = None #web-uiのバグ対策
+    lowvramdealer() #web-uiのバグ対策
 
     if is15:
         if shared.sd_model is not None:
@@ -1668,6 +1667,13 @@ def convert_diffusers_name_to_compvis(key, is_sd2):
 
     return key
 
+def lowvramdealer():
+    try:
+        from modules import lowvram
+        lowvram.module_in_gpu = None #web-uiのバグ対策
+    except:
+        pass
+
 def get_flux_blocks(key):
     if "vae" in key:
         return "VAE"