Merge branch 'master' of https://github.com/anapnoe/stable-diffusion-webui

modules/images.py

@@ -573,6 +573,11 @@ def save_image(image, path, basename, seed=None, prompt=None, extension='png', i
         os.replace(temp_file_path, filename_without_extension + extension)
 
     fullfn_without_extension, extension = os.path.splitext(params.filename)
+    if hasattr(os, 'statvfs'):
+        max_name_len = os.statvfs(path).f_namemax
+        fullfn_without_extension = fullfn_without_extension[:max_name_len - max(4, len(extension))]
+        params.filename = fullfn_without_extension + extension
+        fullfn = params.filename
     _atomically_save_image(image, fullfn_without_extension, extension)
 
     image.already_saved_as = fullfn

modules/models/diffusion/uni_pc/sampler.py

@@ -71,7 +71,7 @@ class UniPCSampler(object):
         # sampling
         C, H, W = shape
         size = (batch_size, C, H, W)
-        print(f'Data shape for UniPC sampling is {size}')
+        # print(f'Data shape for UniPC sampling is {size}')
 
         device = self.model.betas.device
         if x_T is None:

modules/models/diffusion/uni_pc/uni_pc.py

@@ -1,6 +1,7 @@
 import torch
 import torch.nn.functional as F
 import math
+from tqdm.auto import trange
 
 
 class NoiseScheduleVP:
@@ -750,7 +751,7 @@ class UniPC:
         if method == 'multistep':
             assert steps >= order, "UniPC order must be < sampling steps"
             timesteps = self.get_time_steps(skip_type=skip_type, t_T=t_T, t_0=t_0, N=steps, device=device)
-            print(f"Running UniPC Sampling with {timesteps.shape[0]} timesteps, order {order}")
+            #print(f"Running UniPC Sampling with {timesteps.shape[0]} timesteps, order {order}")
             assert timesteps.shape[0] - 1 == steps
             with torch.no_grad():
                 vec_t = timesteps[0].expand((x.shape[0]))
@@ -766,7 +767,7 @@ class UniPC:
                         self.after_update(x, model_x)
                     model_prev_list.append(model_x)
                     t_prev_list.append(vec_t)
-                for step in range(order, steps + 1):
+                for step in trange(order, steps + 1):
                     vec_t = timesteps[step].expand(x.shape[0])
                     if lower_order_final:
                         step_order = min(order, steps + 1 - step)

modules/processing.py

@@ -583,6 +583,7 @@ def process_images_inner(p: StableDiffusionProcessing) -> Processed:
         if state.job_count == -1:
             state.job_count = p.n_iter
 
+        extra_network_data = None
         for n in range(p.n_iter):
             p.iteration = n
 
@@ -712,7 +713,7 @@ def process_images_inner(p: StableDiffusionProcessing) -> Processed:
             if opts.grid_save:
                 images.save_image(grid, p.outpath_grids, "grid", p.all_seeds[0], p.all_prompts[0], opts.grid_format, info=infotext(), short_filename=not opts.grid_extended_filename, p=p, grid=True)
 
-    if not p.disable_extra_networks:
+    if not p.disable_extra_networks and extra_network_data:
         extra_networks.deactivate(p, extra_network_data)
 
     devices.torch_gc()

modules/sd_models.py

@@ -225,7 +225,7 @@ def read_metadata_from_safetensors(filename):
         res = {}
         for k, v in json_obj.get("__metadata__", {}).items():
             res[k] = v
-            if isinstance(v, str) and v[0] == '{':
+            if isinstance(v, str) and v[0:1] == '{':
                 try:
                     res[k] = json.loads(v)
                 except Exception as e:

modules/ui_extra_networks.py

@@ -30,8 +30,8 @@ def add_pages_to_demo(app):
             raise ValueError(f"File cannot be fetched: {filename}. Must be in one of directories registered by extra pages.")
 
         ext = os.path.splitext(filename)[1].lower()
-        if ext not in (".png", ".jpg"):
-            raise ValueError(f"File cannot be fetched: {filename}. Only png and jpg.")
+        if ext not in (".png", ".jpg", ".webp"):
+            raise ValueError(f"File cannot be fetched: {filename}. Only png and jpg and webp.")
 
         # would profit from returning 304
         return FileResponse(filename, headers={"Accept-Ranges": "bytes"})