revertinng the use same settings change till i find a fix

app.py

@@ -84,70 +84,49 @@ def generate_single_image(
 @spaces.GPU(duration=80)
 def generate_arena_images(
     prompt,
-    negative_prompt_A,
-    negative_prompt_B,
-    num_inference_steps_A,
-    num_inference_steps_B,
-    height_A,
-    height_B,
-    width_A,
-    width_B,
-    guidance_scale_A,
-    guidance_scale_B,
-    seed_A,
-    seed_B,
-    num_images_per_prompt_A,
-    num_images_per_prompt_B,
-    model_choice_A,
-    model_choice_B,
-    use_same_settings,
+    negative_prompt,
+    num_inference_steps,
+    height,
+    width,
+    guidance_scale,
+    seed,
+    num_images_per_prompt,
+    model_choice_1,
+    model_choice_2,
     progress=gr.Progress(track_tqdm=True),
 ):
-    if seed_A == 0:
-        seed_A = random.randint(1, 2**32 - 1)
-    if seed_B == 0:
-        seed_B = random.randint(1, 2**32 - 1)
-
-    generator_A = torch.Generator().manual_seed(seed_A)
-    generator_B = torch.Generator().manual_seed(seed_B)
+    if seed == 0:
+        seed = random.randint(1, 2**32 - 1)
 
-    # Apply settings based on use_same_settings
-    if use_same_settings:
-        num_inference_steps_B = num_inference_steps_A
-        height_B = height_A
-        width_B = width_A
-        guidance_scale_B = guidance_scale_A
-        negative_prompt_B = negative_prompt_A
-        seed_B = seed_A
-        num_images_per_prompt_B = num_images_per_prompt_A
+    generator = torch.Generator().manual_seed(seed)
 
     # Generate images for both models
-    images_A = generate_single_image(
+    images_1 = generate_single_image(
         prompt,
-        negative_prompt_A,
-        num_inference_steps_A,
-        height_A,
-        width_A,
-        guidance_scale_A,
-        seed_A,
-        num_images_per_prompt_A,
-        model_choice_A,
-        generator_A,
+        negative_prompt,
+        num_inference_steps,
+        height,
+        width,
+        guidance_scale,
+        seed,
+        num_images_per_prompt,
+        model_choice_1,
+        generator,
     )
-    images_B = generate_single_image(
+    images_2 = generate_single_image(
         prompt,
-        negative_prompt_B,
-        num_inference_steps_B,
-        height_B,
-        width_B,
-        guidance_scale_B,
-        seed_B,
-        num_images_per_prompt_B,
-        model_choice_B,
-        generator_B,
+        negative_prompt,
+        num_inference_steps,
+        height,
+        width,
+        guidance_scale,
+        seed,
+        num_images_per_prompt,
+        model_choice_2,
+        generator,
     )
 
-    return images_A, images_B
+    return images_1, images_2
 
 # Define the image generation function for the Individual tab
 @spaces.GPU(duration=80)
@@ -220,31 +199,28 @@ with gr.Blocks(css=css) as demo:
                         info="Describe the image you want",
                         placeholder="A cat...",
                     )
-                    model_choice_A = gr.Dropdown(
-                        label="Stable Diffusion Model A",
+                    model_choice_1 = gr.Dropdown(
+                        label="Stable Diffusion Model 1",
                         choices=["sd3 medium", "sd2.1", "sdxl", "sdxl flash"],
                         value="sd3 medium",
                     )
-                    model_choice_B = gr.Dropdown(
-                        label="Stable Diffusion Model B",
+                    model_choice_2 = gr.Dropdown(
+                        label="Stable Diffusion Model 2",
                         choices=["sd3 medium", "sd2.1", "sdxl", "sdxl flash"],
                         value="sdxl",
                     )
                     run_button = gr.Button("Run")
-                result_A = gr.Gallery(label="Generated Images (Model A)", elem_id="gallery_A")
-                result_B = gr.Gallery(label="Generated Images (Model B)", elem_id="gallery_B")
+                result_1 = gr.Gallery(label="Generated Images (Model 1)", elem_id="gallery_1")
+                result_2 = gr.Gallery(label="Generated Images (Model 2)", elem_id="gallery_2")
             with gr.Accordion("Advanced options", open=False):
-                use_same_settings = gr.Checkbox(label='Use same settings for both models', value=True)
-
-                # UI elements for shared settings
-                with gr.Row(visible=True):
+                with gr.Row():
                     negative_prompt = gr.Textbox(
                         label="Negative Prompt",
                         info="Describe what you don't want in the image",
                         value="deformed, distorted, disfigured, poorly drawn, bad anatomy, incorrect anatomy, extra limb, missing limb, floating limbs, mutated hands and fingers, disconnected limbs, mutation, mutated, ugly, disgusting, blurry, amputation",
                         placeholder="Ugly, bad anatomy...",
                     )
-                with gr.Row(visible=True):
+                with gr.Row():
                     num_inference_steps = gr.Slider(
                         label="Number of Inference Steps",
                         info="The number of denoising steps of the image. More denoising steps usually lead to a higher quality image at the cost of slower inference",
@@ -261,7 +237,7 @@ with gr.Blocks(css=css) as demo:
                         value=7.5,
                         step=0.1,
                     )
-                with gr.Row(visible=True):
+                with gr.Row():
                     width = gr.Slider(
                         label="Width",
                         info="Width of the Image",
@@ -278,7 +254,7 @@ with gr.Blocks(css=css) as demo:
                         step=32,
                         value=1024,
                     )
-                with gr.Row(visible=True):
+                with gr.Row():
                     seed = gr.Slider(
                         value=42,
                         minimum=0,
@@ -296,123 +272,10 @@ with gr.Blocks(css=css) as demo:
                         value=2,
                     )
 
-                # UI elements for separate settings (hidden by default)
-                with gr.Row(visible=False):
-                    with gr.Column(scale=1):
-                        negative_prompt_A = gr.Textbox(
-                            label="Negative Prompt (Model A)",
-                            info="Describe what you don't want in the image",
-                            value="deformed, distorted, disfigured, poorly drawn, bad anatomy, incorrect anatomy, extra limb, missing limb, floating limbs, mutated hands and fingers, disconnected limbs, mutation, mutated, ugly, disgusting, blurry, amputation",
-                            placeholder="Ugly, bad anatomy...",
-                        )
-                        num_inference_steps_A = gr.Slider(
-                            label="Number of Inference Steps (Model A)",
-                            info="The number of denoising steps of the image. More denoising steps usually lead to a higher quality image at the cost of slower inference",
-                            minimum=1,
-                            maximum=50,
-                            value=25,
-                            step=1,
-                        )
-                        width_A = gr.Slider(
-                            label="Width (Model A)",
-                            info="Width of the Image",
-                            minimum=256,
-                            maximum=1344,
-                            step=32,
-                            value=1024,
-                        )
-                        height_A = gr.Slider(
-                            label="Height (Model A)",
-                            info="Height of the Image",
-                            minimum=256,
-                            maximum=1344,
-                            step=32,
-                            value=1024,
-                        )
-                        guidance_scale_A = gr.Slider(
-                            label="Guidance Scale (Model A)",
-                            info="Controls how much the image generation process follows the text prompt. Higher values make the image stick more closely to the input text.",
-                            minimum=0.0,
-                            maximum=10.0,
-                            value=7.5,
-                            step=0.1,
-                        )
-                        seed_A = gr.Slider(
-                            value=42,
-                            minimum=0,
-                            maximum=MAX_SEED,
-                            step=1,
-                            label="Seed (Model A)",
-                            info="A starting point to initiate the generation process, put 0 for a random one",
-                        )
-                        num_images_per_prompt_A = gr.Slider(
-                            label="Images Per Prompt (Model A)",
-                            info="Number of Images to generate with the settings",
-                            minimum=1,
-                            maximum=4,
-                            step=1,
-                            value=2,
-                        )
-                    with gr.Column(scale=1):
-                        negative_prompt_B = gr.Textbox(
-                            label="Negative Prompt (Model B)",
-                            info="Describe what you don't want in the image",
-                            value="deformed, distorted, disfigured, poorly drawn, bad anatomy, incorrect anatomy, extra limb, missing limb, floating limbs, mutated hands and fingers, disconnected limbs, mutation, mutated, ugly, disgusting, blurry, amputation",
-                            placeholder="Ugly, bad anatomy...",
-                        )
-                        num_inference_steps_B = gr.Slider(
-                            label="Number of Inference Steps (Model B)",
-                            info="The number of denoising steps of the image. More denoising steps usually lead to a higher quality image at the cost of slower inference",
-                            minimum=1,
-                            maximum=50,
-                            value=25,
-                            step=1,
-                        )
-                        width_B = gr.Slider(
-                            label="Width (Model B)",
-                            info="Width of the Image",
-                            minimum=256,
-                            maximum=1344,
-                            step=32,
-                            value=1024,
-                        )
-                        height_B = gr.Slider(
-                            label="Height (Model B)",
-                            info="Height of the Image",
-                            minimum=256,
-                            maximum=1344,
-                            step=32,
-                            value=1024,
-                        )
-                        guidance_scale_B = gr.Slider(
-                            label="Guidance Scale (Model B)",
-                            info="Controls how much the image generation process follows the text prompt. Higher values make the image stick more closely to the input text.",
-                            minimum=0.0,
-                            maximum=10.0,
-                            value=7.5,
-                            step=0.1,
-                        )
-                        seed_B = gr.Slider(
-                            value=42,
-                            minimum=0,
-                            maximum=MAX_SEED,
-                            step=1,
-                            label="Seed (Model B)",
-                            info="A starting point to initiate the generation process, put 0 for a random one",
-                        )
-                        num_images_per_prompt_B = gr.Slider(
-                            label="Images Per Prompt (Model B)",
-                            info="Number of Images to generate with the settings",
-                            minimum=1,
-                            maximum=4,
-                            step=1,
-                            value=2,
-                        )
-
             gr.Examples(
                 examples=examples,
                 inputs=[prompt],
-                outputs=[result_A, result_B],
+                outputs=[result_1, result_2],
                 fn=generate_arena_images,
             )
 
@@ -424,25 +287,17 @@ with gr.Blocks(css=css) as demo:
                 fn=generate_arena_images,
                 inputs=[
                     prompt,
-                    negative_prompt_A,
-                    negative_prompt_B,
-                    num_inference_steps_A,
-                    num_inference_steps_B,
-                    height_A,
-                    height_B,
-                    width_A,
-                    width_B,
-                    guidance_scale_A,
-                    guidance_scale_B,
-                    seed_A,
-                    seed_B,
-                    num_images_per_prompt_A,
-                    num_images_per_prompt_B,
-                    model_choice_A,
-                    model_choice_B,
-                    use_same_settings,
+                    negative_prompt,
+                    num_inference_steps,
+                    width,
+                    height,
+                    guidance_scale,
+                    seed,
+                    num_images_per_prompt,
+                    model_choice_1,
+                    model_choice_2,
                 ],
-                outputs=[result_A, result_B],
+                outputs=[result_1, result_2],
             )
 
         with gr.TabItem("Individual"):