revert diffusers

modules/sd_models.py

@@ -557,6 +557,7 @@ class ModelData:
                     shared.log.error("Failed to load stable diffusion model")
                     errors.display(e, "loading stable diffusion model")
                     self.sd_model = None
+            self.sd_model.model_type = shared.sd_model_type
         return self.sd_model
 
     def set_sd_model(self, v):
@@ -577,6 +578,7 @@ class ModelData:
                     shared.log.error("Failed to load stable diffusion model")
                     errors.display(e, "loading stable diffusion model")
                     self.sd_refiner = None
+            self.sd_refiner.model_type = shared.sd_refiner_type
         return self.sd_refiner
 
     def set_sd_refiner(self, v):
@@ -701,7 +703,6 @@ def load_diffuser(checkpoint_info=None, already_loaded_state_dict=None, timer=No
                 try:
                     shared.log.debug(f'Model load {op} config: {diffusers_load_config}')
                     sd_model = diffusers.DiffusionPipeline.from_pretrained(model_file, **diffusers_load_config)
-                    sd_model.model_type = sd_model.__class__.__name__
                 except Exception as e:
                     shared.log.error(f'Failed loading model: {model_file} {e}')
                 list_models() # rescan for downloaded model
@@ -830,6 +831,9 @@ def load_diffuser(checkpoint_info=None, already_loaded_state_dict=None, timer=No
                 else:
                     sd_model.vae.config["force_upcast"] = False
                     sd_model.vae.config.force_upcast = False
+                if shared.opts.no_half_vae:
+                    devices.dtype_vae = torch.float32
+                    sd_model.vae.to(devices.dtype_vae)
             shared.log.debug(f'Model {op} VAE: name={sd_vae.loaded_vae_file} upcast={sd_model.vae.config.get("force_upcast", None)}')
         if shared.opts.cross_attention_optimization == "xFormers" and hasattr(sd_model, 'enable_xformers_memory_efficient_attention'):
             sd_model.enable_xformers_memory_efficient_attention()

requirements.txt

@@ -47,7 +47,7 @@ requests==2.31.0
 tqdm==4.66.1
 accelerate==0.20.3
 opencv-python-headless==4.7.0.72
-diffusers==0.21.1
+diffusers==0.20.2
 einops==0.4.1
 gradio==3.43.2
 huggingface_hub==0.17.1

webui.bat

@@ -7,7 +7,7 @@ mkdir tmp 2>NUL
 
 %PYTHON% -c "" >tmp/stdout.txt 2>tmp/stderr.txt
 if %ERRORLEVEL% == 0 goto :check_pip
-echo Couldn't launch python
+echo Cannot launch python
 goto :show_stdout_stderr
 
 :check_pip
@@ -16,7 +16,7 @@ if %ERRORLEVEL% == 0 goto :start_venv
 if "%PIP_INSTALLER_LOCATION%" == "" goto :show_stdout_stderr
 %PYTHON% "%PIP_INSTALLER_LOCATION%" >tmp/stdout.txt 2>tmp/stderr.txt
 if %ERRORLEVEL% == 0 goto :start_venv
-echo Couldn't install pip
+echo Cannot install pip
 goto :show_stdout_stderr
 
 :start_venv
@@ -27,10 +27,11 @@ dir "%VENV_DIR%\Scripts\Python.exe" >tmp/stdout.txt 2>tmp/stderr.txt
 if %ERRORLEVEL% == 0 goto :activate_venv
 
 for /f "delims=" %%i in ('CALL %PYTHON% -c "import sys; print(sys.executable)"') do set PYTHON_FULLNAME="%%i"
-echo Creating venv in directory %VENV_DIR% using python %PYTHON_FULLNAME%
+echo Using python: %PYTHON_FULLNAME%
+echo Creating VENV: %VENV_DIR% 
 %PYTHON_FULLNAME% -m venv "%VENV_DIR%" >tmp/stdout.txt 2>tmp/stderr.txt
 if %ERRORLEVEL% == 0 goto :activate_venv
-echo Unable to create venv in directory "%VENV_DIR%"
+echo Failed creating VENV: "%VENV_DIR%"
 goto :show_stdout_stderr
 
 :activate_venv
@@ -42,7 +43,6 @@ if [%ACCELERATE%] == ["True"] goto :accelerate
 goto :launch
 
 :accelerate
-echo Checking for accelerate: %ACCELERATE%
 set ACCELERATE="%VENV_DIR%\Scripts\accelerate.exe"
 if EXIST %ACCELERATE% goto :accelerate_launch
 
@@ -52,7 +52,7 @@ pause
 exit /b
 
 :accelerate_launch
-echo Accelerating
+echo Using accelerate
 %ACCELERATE% launch --num_cpu_threads_per_process=6 launch.py %*
 pause
 exit /b
@@ -78,5 +78,5 @@ type tmp\stderr.txt
 :endofscript
 
 echo.
-echo Launch unsuccessful. Exiting.
+echo Launch Failed
 pause