fixes...

modules/devices.py

@@ -181,7 +181,7 @@ else:
 
 if backend == 'ipex':
     import os
-    def ipex_no_cuda(orig_func, *args, **kwargs):
+    def ipex_no_cuda(orig_func, *args, **kwargs): # pylint: disable=redefined-outer-name
         torch.cuda.is_available = lambda: False
         orig_func(*args, **kwargs)
         torch.cuda.is_available = torch.xpu.is_available
@@ -193,7 +193,7 @@ if backend == 'ipex':
     torch.cuda.current_device = torch.xpu.current_device
     torch.cuda.get_device_name = torch.xpu.get_device_name
     torch.cuda.get_device_properties = torch.xpu.get_device_properties
-    torch._utils._get_available_device_type = lambda: "xpu"
+    torch._utils._get_available_device_type = lambda: "xpu" # pylint: disable=protected-access
     torch.cuda.set_device = torch.xpu.set_device
     torch.Tensor.cuda = torch.Tensor.xpu
 
@@ -321,7 +321,7 @@ def without_autocast(disable=False):
     if disable:
         return contextlib.nullcontext()
     if shared.cmd_opts.use_directml:
-        return torch.dml.amp.autocast(enabled=False) if torch.is_autocast_enabled() else contextlib.nullcontext()
+        return torch.dml.amp.autocast(enabled=False) if torch.is_autocast_enabled() else contextlib.nullcontext() # pylint: disable=unexpected-keyword-arg
     if backend == 'ipex':
         return torch.xpu.amp.autocast(enabled=False) if torch.is_autocast_enabled() else contextlib.nullcontext()
     if cuda_ok:

modules/img2img.py

@@ -11,7 +11,7 @@ from modules.memstats import memory_stats
 def process_batch(p, input_files, input_dir, output_dir, inpaint_mask_dir, args):
     shared.log.debug(f'batch: {input_dir}|{output_dir}|{inpaint_mask_dir}')
     processing.fix_seed(p)
-    if len(input_files) > 0:
+    if input_files is not None and len(input_files) > 0:
         image_files = [f.name for f in input_files]
     else:
         if not os.path.isdir(input_dir):

modules/sd_models.py

@@ -395,8 +395,10 @@ def load_model_weights(model: torch.nn.Module, checkpoint_info: CheckpointInfo,
         model.first_stage_model = vae
         if depth_model:
             model.depth_model = depth_model
-    # devices.dtype_unet = model.model.diffusion_model.dtype
-    model.model.diffusion_model.to(devices.dtype_unet)
+    if shared.opts.cuda_cast_unet:
+        devices.dtype_unet = model.model.diffusion_model.dtype
+    else:
+        model.model.diffusion_model.to(devices.dtype_unet)
     model.first_stage_model.to(devices.dtype_vae)
     # clean up cache if limit is reached
     while len(checkpoints_loaded) > shared.opts.sd_checkpoint_cache:
@@ -727,7 +729,7 @@ def load_diffuser(checkpoint_info=None, already_loaded_state_dict=None, timer=No
                 sd_model.enable_attention_slicing()
             else:
                 sd_model.disable_attention_slicing()
-        if shared.opts.cross_attention_optimization == "xFormers":
+        if shared.opts.cross_attention_optimization == "xFormers" and hasattr(sd_model, 'enable_xformers_memory_efficient_attention'):
             sd_model.enable_xformers_memory_efficient_attention()
         if shared.opts.opt_channelslast:
             shared.log.debug('Diffusers: enable channels last')

modules/shared.py

@@ -381,6 +381,7 @@ options_templates.update(options_section(('cuda', "Compute Settings"), {
     "no_half_vae": OptionInfo(False, "Use full precision for VAE (--no-half-vae)"),
     "upcast_sampling": OptionInfo(True if sys.platform == "darwin" else False, "Enable upcast sampling"),
     "upcast_attn": OptionInfo(False, "Enable upcast cross attention layer"),
+    "cuda_cast_unet": OptionInfo(False, "Use fixed UNet precision"),
     "disable_nan_check": OptionInfo(True, "Disable NaN check in produced images/latent spaces"),
     "rollback_vae": OptionInfo(False, "Attempt VAE roll back when produced NaN values (experimental)"),
     "opt_channelslast": OptionInfo(False, "Use channels last as torch memory format "),

modules/ui_extra_networks.py

@@ -1,3 +1,4 @@
+import re
 import json
 import html
 import os.path
@@ -249,7 +250,9 @@ class ExtraNetworksPage:
         for file in [f"{path}.txt", f"{path}.description.txt"]:
             try:
                 with open(file, "r", encoding="utf-8", errors="replace") as f:
-                    return f.read()
+                    txt = f.read()
+                    txt = re.sub('[<>]', '', txt)
+                    return txt
             except OSError:
                 pass
         return None
@@ -259,7 +262,9 @@ class ExtraNetworksPage:
         for file in [f"{path}.info", f"{path}.civitai.info", f"{basename}.info", f"{basename}.civitai.info"]:
             try:
                 with open(file, "r", encoding="utf-8", errors="replace") as f:
-                    return f.read()
+                    txt = f.read()
+                    txt = re.sub('[<>]', '', txt)
+                    return txt
             except OSError:
                 pass
         return None