Merge branch 'main_upstream' into develop_upstream

Dockerfile

@@ -23,7 +23,7 @@ RUN chown -R user:user /content
 WORKDIR /content
 USER user
 
-COPY . /content/app
+COPY --chown=user:user . /content/app
 RUN mv /content/app/models /content/app/models.org
 
 CMD [ "sh", "-c", "/content/entrypoint.sh ${CMDARGS}" ]

css/style.css

@@ -74,31 +74,35 @@ progress::after {
     text-align: right;
     width: 215px;
 }
-
+div:has(> #positive_prompt) {
-.type_row{
+    border: none;
-  height: 80px !important;
 }
 
-.type_row_half{
+#positive_prompt {
-  height: 32px !important;
+    padding: 1px;
+    background: var(--background-fill-primary);
 }
 
-.scroll-hide{
+.type_row {
-  resize: none !important;
+  height: 84px !important;
 }
 
-.refresh_button{
+.type_row_half {
+  height: 34px !important;
+}
+
+.refresh_button {
   border: none !important;
   background: none !important;
   font-size: none !important;
   box-shadow: none !important;
 }
 
-.advanced_check_row{
+.advanced_check_row {
   width: 250px !important;
 }
 
-.min_check{
+.min_check {
   min-width: min(1px, 100%) !important;
 }
 

ldm_patched/contrib/external_custom_sampler.py

@@ -107,8 +107,7 @@ class SDTurboScheduler:
     def get_sigmas(self, model, steps, denoise):
         start_step = 10 - int(10 * denoise)
         timesteps = torch.flip(torch.arange(1, 11) * 100 - 1, (0,))[start_step:start_step + steps]
-        ldm_patched.modules.model_management.load_models_gpu([model])
+        sigmas = model.model_sampling.sigma(timesteps)
-        sigmas = model.model.model_sampling.sigma(timesteps)
         sigmas = torch.cat([sigmas, sigmas.new_zeros([1])])
         return (sigmas, )
 

modules/sample_hijack.py

@@ -175,7 +175,7 @@ def calculate_sigmas_scheduler_hacked(model, scheduler_name, steps):
     elif scheduler_name == "sgm_uniform":
         sigmas = normal_scheduler(model, steps, sgm=True)
     elif scheduler_name == "turbo":
-        sigmas = SDTurboScheduler().get_sigmas(namedtuple('Patcher', ['model'])(model=model), steps=steps, denoise=1.0)[0]
+        sigmas = SDTurboScheduler().get_sigmas(model=model, steps=steps, denoise=1.0)[0]
     elif scheduler_name == "align_your_steps":
         model_type = 'SDXL' if isinstance(model.latent_format, ldm_patched.modules.latent_formats.SDXL) else 'SD1'
         sigmas = AlignYourStepsScheduler().get_sigmas(model_type=model_type, steps=steps, denoise=1.0)[0]

readme.md

@@ -370,25 +370,36 @@ entry_with_update.py  [-h] [--listen [IP]] [--port PORT]
                       [--web-upload-size WEB_UPLOAD_SIZE]
                       [--hf-mirror HF_MIRROR]
                       [--external-working-path PATH [PATH ...]]
-                      [--output-path OUTPUT_PATH] [--temp-path TEMP_PATH]
+                      [--output-path OUTPUT_PATH]
+                      [--temp-path TEMP_PATH]
                       [--cache-path CACHE_PATH] [--in-browser]
-                      [--disable-in-browser] [--gpu-device-id DEVICE_ID]
+                      [--disable-in-browser]
+                      [--gpu-device-id DEVICE_ID]
                       [--async-cuda-allocation | --disable-async-cuda-allocation]
-                      [--disable-attention-upcast] [--all-in-fp32 | --all-in-fp16]
+                      [--disable-attention-upcast]
+                      [--all-in-fp32 | --all-in-fp16]
                       [--unet-in-bf16 | --unet-in-fp16 | --unet-in-fp8-e4m3fn | --unet-in-fp8-e5m2]
                       [--vae-in-fp16 | --vae-in-fp32 | --vae-in-bf16]   
+                      [--vae-in-cpu]
                       [--clip-in-fp8-e4m3fn | --clip-in-fp8-e5m2 | --clip-in-fp16 | --clip-in-fp32]
-                      [--directml [DIRECTML_DEVICE]] [--disable-ipex-hijack]
+                      [--directml [DIRECTML_DEVICE]]
+                      [--disable-ipex-hijack]
                       [--preview-option [none,auto,fast,taesd]]
                       [--attention-split | --attention-quad | --attention-pytorch]
                       [--disable-xformers]
                       [--always-gpu | --always-high-vram | --always-normal-vram |
                       --always-low-vram | --always-no-vram | --always-cpu [CPU_NUM_THREADS]]
-                      [--always-offload-from-vram] [--disable-server-log]
+                      [--always-offload-from-vram]
+                      [--pytorch-deterministic] [--disable-server-log]  
                       [--debug-mode] [--is-windows-embedded-python]     
-                      [--disable-server-info] [--share] [--preset PRESET]
+                      [--disable-server-info] [--multi-user] [--share]  
-                      [--language LANGUAGE] [--disable-offload-from-vram]
+                      [--preset PRESET] [--disable-preset-selection]    
-                      [--theme THEME] [--disable-image-log]
+                      [--language LANGUAGE]
+                      [--disable-offload-from-vram] [--theme THEME]     
+                      [--disable-image-log] [--disable-analytics]       
+                      [--disable-metadata] [--disable-preset-download]  
+                      [--enable-describe-uov-image]
+                      [--always-download-new-model]
 ```
 
 ## Advanced Features

webui.py

@@ -112,10 +112,10 @@ with shared.gradio_root:
             gallery = gr.Gallery(label='Gallery', show_label=False, object_fit='contain', visible=True, height=768,
                                  elem_classes=['resizable_area', 'main_view', 'final_gallery', 'image_gallery'],
                                  elem_id='final_gallery')
-            with gr.Row(elem_classes='type_row'):
+            with gr.Row():
                 with gr.Column(scale=17):
                     prompt = gr.Textbox(show_label=False, placeholder="Type prompt here or paste parameters.", elem_id='positive_prompt',
-                                        container=False, autofocus=True, elem_classes='type_row', lines=1024)
+                                        autofocus=True, lines=3)
 
                     default_prompt = modules.config.default_prompt
                     if isinstance(default_prompt, str) and default_prompt != '':