Update app.py

app.py

@@ -59,7 +59,6 @@ def generate(
     guidance_scale_base: float = 5.0,
     num_inference_steps_base: int = 25,
     strength_img2img: float = 0.7,
-    is_sdxl: bool = False,
     use_lora: bool = False,
     use_lora2: bool = False,
     model = 'stabilityai/stable-diffusion-xl-base-1.0',
@@ -117,14 +116,6 @@ def generate(
     # É SDXL 1.0 (NÃO SD 1.5)
     if is_sdxl:
         pipe.enable_model_cpu_offload()
-        compel = Compel(
-        tokenizer=[pipe.tokenizer, pipe.tokenizer_2],
-        text_encoder=[pipe.text_encoder, pipe.text_encoder_2],
-        returned_embeddings_type=ReturnedEmbeddingsType.PENULTIMATE_HIDDEN_STATES_NON_NORMALIZED,
-        requires_pooled=[False, True],
-        truncate_long_prompts=False
-        )
-        conditioning, pooled = compel(prompt)
         generator = torch.Generator().manual_seed(seed)
         
         if not use_negative_prompt:
@@ -133,8 +124,8 @@ def generate(
         with pipeline_lock:
             if use_img2img:
                 result = pipe(
-                    prompt_embeds=conditioning,
-                    pooled_prompt_embeds=pooled,
+                    prompt=prompt,
+                    negative_prompt=negative_prompt,
                     image=init_image,
                     strength=strength_img2img,
                     negative_prompt=negative_prompt,
@@ -146,8 +137,7 @@ def generate(
                 ).images[0]
             else:
                 result = pipe(
-                    prompt_embeds=conditioning,
-                    pooled_prompt_embeds=pooled,
+                    prompt=prompt,
                     negative_prompt=negative_prompt,
                     width=width,
                     height=height,
@@ -157,49 +147,7 @@ def generate(
                 ).images[0]
     
         # Limpeza de memória
-        del pipe, conditioning, pooled
-        torch.cuda.empty_cache()
-        gc.collect()
-        return result
-
-    # NÃO É SDXL (E SIM SD 1.5)
-    if not is_sdxl:
-        pipe.enable_model_cpu_offload()
-        compel = Compel(tokenizer=pipe.tokenizer, text_encoder=pipe.text_encoder, truncate_long_prompts=False)
-        conditioning = compel.build_conditioning_tensor(prompt)
-        negative_conditioning = compel.build_conditioning_tensor(negative_prompt)
-        [conditioning, negative_conditioning] = compel.pad_conditioning_tensors_to_same_length([conditioning, negative_conditioning])
-        generator = torch.Generator().manual_seed(seed)
-        
-        if not use_negative_prompt:
-            negative_prompt = None  # type: ignore
-            
-        with pipeline_lock:
-            if use_img2img:
-                result = pipe(
-                    prompt_embeds=conditioning,
-                    image=init_image,
-                    strength=strength_img2img,
-                    negative_prompt_embeds=negative_conditioning,
-                    width=width,
-                    height=height,
-                    guidance_scale=guidance_scale_base,
-                    num_inference_steps=num_inference_steps_base,
-                    generator=generator,
-                ).images[0]
-            else:
-                result = pipe(
-                    prompt_embeds=conditioning,
-                    negative_prompt_embeds=negative_conditioning,
-                    width=width,
-                    height=height,
-                    guidance_scale=guidance_scale_base,
-                    num_inference_steps=num_inference_steps_base,
-                    generator=generator,
-                ).images[0]
-    
-        # Limpeza de memória
-        del pipe, conditioning, negative_conditioning
+        del pipe
         torch.cuda.empty_cache()
         gc.collect()
         return result
@@ -243,7 +191,6 @@ with gr.Blocks(theme=gr.themes.Soft(), css="style.css") as demo:
     with gr.Accordion("Advanced options", open=False):
         with gr.Row():
             use_img2img = gr.Checkbox(label='Use Img2Img', value=False, visible=ENABLE_USE_IMG2IMG)
-            is_sdxl = gr.Checkbox(label='Is SDXL?', value=False)
             use_lora = gr.Checkbox(label='Use Lora 1', value=False, visible=ENABLE_USE_LORA)
             use_lora2 = gr.Checkbox(label='Use Lora 2', value=False, visible=ENABLE_USE_LORA2)
             use_negative_prompt = gr.Checkbox(label="Use negative prompt", value=False)
@@ -326,13 +273,6 @@ with gr.Blocks(theme=gr.themes.Soft(), css="style.css") as demo:
         queue=False,
         api_name=False,
     )
-    is_sdxl.change(
-        fn=lambda x: gr.update(visible=x),
-        inputs=is_sdxl,
-        outputs=is_sdxl,
-        queue=False,
-        api_name=False,
-    )
     use_img2img.change(
         fn=lambda x: gr.update(visible=x),
         inputs=use_img2img,
@@ -364,7 +304,6 @@ with gr.Blocks(theme=gr.themes.Soft(), css="style.css") as demo:
             guidance_scale_base,
             num_inference_steps_base,
             strength_img2img,
-            is_sdxl,
             use_lora,
             use_lora2,
             model,