Upload 2 files

app.py

@@ -381,12 +381,12 @@ with gr.Blocks(fill_width=True, elem_id="container", css=css) as demo:
         )
 
     model_name.change(update_task_options, [model_name, task], [task], queue=False, show_api=False)\
-    .success(update_task_options, [model_name, task_sel], [task_sel], queue=False, show_api=False)
+    .success(update_task_options, [model_name, task_sel], [task_sel], queue=False, show_api=False)\
+    .success(update_textual_inversion, [active_textual_inversion, model_name], [use_textual_inversion], queue=False, show_api=False)
     task_sel.select(lambda x: x, [task_sel], [task], queue=False, show_api=False)
     task.change(change_preprocessor_choices, [task], [preprocessor_name], queue=False, show_api=False)\
     .success(lambda x: x, [task], [task_sel], queue=False, show_api=False)
     active_textual_inversion.change(update_textual_inversion, [active_textual_inversion, model_name], [use_textual_inversion], queue=False, show_api=False)
-    model_name.change(update_textual_inversion, [active_textual_inversion, model_name], [use_textual_inversion], queue=False, show_api=False)
     use_textual_inversion.change(set_textual_inversion_prompt, [use_textual_inversion, prompt, negative_prompt, prompt_syntax], [prompt, negative_prompt])
     result_to_cm_button.click(lambda x: x, [result], [image_base], queue=False, show_api=False)
     result_to_ic_button.click(lambda x: x, [result], [image_control], queue=False, show_api=False)

dc.py

@@ -672,7 +672,7 @@ def dummy_gpu():
     return None
 
 
-def sd_gen_generate_pipeline(*args):
+def sd_gen_generate_pipeline(sd_gen, *args):
     gpu_duration_arg = int(args[-1]) if args[-1] else 59
     verbose_arg = int(args[-2])
     load_lora_cpu = args[-3]
@@ -783,7 +783,7 @@ def process_upscale(image, upscaler_name, upscaler_size):
 # https://huggingface.co/spaces/BestWishYsh/ConsisID-preview-Space/discussions/1#674969a022b99c122af5d407
 # dynamic_gpu_duration.zerogpu = True
 # sd_gen_generate_pipeline.zerogpu = True
-sd_gen = GuiSD()
+#sd_gen = GuiSD()
 
 
 from pathlib import Path
@@ -794,6 +794,8 @@ import random
 import json
 import shutil
 import gc
+import threading
+from collections import defaultdict
 from tagger.tagger import insert_model_recom_prompt
 from modutils import (safe_float, escape_lora_basename, to_lora_key, to_lora_path, valid_model_name, set_textual_inversion_prompt,
     get_local_model_list, get_model_pipeline, get_private_lora_model_lists, get_valid_lora_name, get_state, set_state,
@@ -803,6 +805,21 @@ from modutils import (safe_float, escape_lora_basename, to_lora_key, to_lora_pat
     apply_lora_prompt, update_loras, search_civitai_lora, search_civitai_lora_json, update_civitai_selection, select_civitai_lora)
 
 
+_PIPELINES = {}
+_LOCKS = defaultdict(threading.Lock)
+
+
+def get_gsd(repo_id, vae, task, controlnet_model):
+    with _LOCKS[repo_id]:
+        gsd = _PIPELINES.get(repo_id)
+        if gsd is None:
+            gsd = GuiSD()
+            for _ in gsd.load_new_model(repo_id, vae, task, controlnet_model):
+                pass
+            _PIPELINES[repo_id] = gsd
+        return gsd
+
+
 #@spaces.GPU
 def infer(prompt, negative_prompt, seed, randomize_seed, width, height, guidance_scale, num_inference_steps,
           model_name=load_diffusers_format_model[0], lora1=None, lora1_wt=1.0, lora2=None, lora2_wt=1.0,
@@ -877,13 +894,11 @@ def infer(prompt, negative_prompt, seed, randomize_seed, width, height, guidance
     lora6 = get_valid_lora_path(lora6)
     lora7 = get_valid_lora_path(lora7)
     progress(1, desc="Preparation completed. Starting inference...")
-
     progress(0, desc="Loading model...")
-    for _ in sd_gen.load_new_model(valid_model_name(model_name), vae, task, controlnet_model):
-        pass
+    gsd = get_gsd(valid_model_name(model_name), vae, task, controlnet_model)
     progress(1, desc="Model loaded.")
     progress(0, desc="Starting Inference...")
-    for info_state, stream_images, info_images in sd_gen_generate_pipeline(prompt, negative_prompt, 1, num_inference_steps,
+    for info_state, stream_images, info_images in sd_gen_generate_pipeline(gsd, prompt, negative_prompt, 1, num_inference_steps,
         guidance_scale, clip_skip, generator, lora1, lora1_wt, lora2, lora2_wt, lora3, lora3_wt,
         lora4, lora4_wt, lora5, lora5_wt, lora6, lora6_wt, lora7, lora7_wt, sampler, schedule_type, schedule_prediction_type,
         height, width, model_name, vae, task, image_control, preprocessor_name, preprocess_resolution, image_resolution,