Spaces:
Running
on
Zero
Running
on
Zero
fixed arena tab compare < 4 not working, fixed height width models not changing always
Browse files
app.py
CHANGED
@@ -121,7 +121,7 @@ def generate_single_image(
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guidance_scale=decoder_guidance_scale,
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).images
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-
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else:
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output = pipe(
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prompt=prompt,
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@@ -138,7 +138,7 @@ def generate_single_image(
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# Define the image generation function for the Arena tab
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-
@spaces.GPU(duration=
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def generate_arena_images(
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prompt,
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negative_prompt,
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@@ -189,7 +189,6 @@ def generate_arena_images(
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generator = torch.Generator().manual_seed(seed)
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# Generate images for selected models
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-
images = []
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if num_models_to_compare >= 2:
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images_a = generate_single_image(
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prompt,
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@@ -207,7 +206,6 @@ def generate_arena_images(
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decoder_num_inference_steps_a,
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decoder_guidance_scale_a,
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)
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-
images.append(images_a)
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images_b = generate_single_image(
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prompt,
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negative_prompt,
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@@ -224,7 +222,9 @@ def generate_arena_images(
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decoder_num_inference_steps_b,
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decoder_guidance_scale_b,
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)
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-
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if num_models_to_compare >= 3:
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images_c = generate_single_image(
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prompt,
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@@ -242,7 +242,9 @@ def generate_arena_images(
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decoder_num_inference_steps_c,
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decoder_guidance_scale_c,
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)
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-
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if num_models_to_compare >= 4:
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images_d = generate_single_image(
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prompt,
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@@ -260,9 +262,10 @@ def generate_arena_images(
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decoder_num_inference_steps_d,
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decoder_guidance_scale_d,
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)
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-
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-
return
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# Define the image generation function for the Individual tab
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@@ -998,6 +1001,8 @@ with gr.Blocks(theme=theme, css=css) as demo:
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prior_guidance_scale_c: gr.update(visible=True),
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decoder_num_inference_steps_c: gr.update(visible=True),
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decoder_guidance_scale_c: gr.update(visible=True),
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}
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elif model_choice_c == "sdxl flash":
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return {
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@@ -1007,6 +1012,8 @@ with gr.Blocks(theme=theme, css=css) as demo:
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prior_guidance_scale_c: gr.update(visible=False),
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decoder_num_inference_steps_c: gr.update(visible=False),
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decoder_guidance_scale_c: gr.update(visible=False),
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}
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elif model_choice_c == "sd1.5":
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return {
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@@ -1038,8 +1045,8 @@ with gr.Blocks(theme=theme, css=css) as demo:
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prior_guidance_scale_c: gr.update(visible=False),
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decoder_num_inference_steps_c: gr.update(visible=False),
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decoder_guidance_scale_c: gr.update(visible=False),
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-
width_c: gr.update(maximum=1344),
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-
height_c: gr.update(maximum=1344),
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}
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def toggle_visibility_arena_d(model_choice_d):
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@@ -1051,6 +1058,8 @@ with gr.Blocks(theme=theme, css=css) as demo:
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prior_guidance_scale_d: gr.update(visible=True),
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decoder_num_inference_steps_d: gr.update(visible=True),
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decoder_guidance_scale_d: gr.update(visible=True),
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}
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elif model_choice_d == "sdxl flash":
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return {
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@@ -1060,6 +1069,8 @@ with gr.Blocks(theme=theme, css=css) as demo:
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prior_guidance_scale_d: gr.update(visible=False),
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decoder_num_inference_steps_d: gr.update(visible=False),
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decoder_guidance_scale_d: gr.update(visible=False),
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}
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elif model_choice_d == "sd1.5":
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return {
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@@ -1091,8 +1102,8 @@ with gr.Blocks(theme=theme, css=css) as demo:
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prior_guidance_scale_d: gr.update(visible=False),
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decoder_num_inference_steps_d: gr.update(visible=False),
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decoder_guidance_scale_d: gr.update(visible=False),
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-
width_d: gr.update(maximum=1344),
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-
height_d: gr.update(maximum=1344),
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}
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model_choice_a.change(
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@@ -1426,6 +1437,8 @@ with gr.Blocks(theme=theme, css=css) as demo:
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prior_guidance_scale: gr.update(visible=True),
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decoder_num_inference_steps: gr.update(visible=True),
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decoder_guidance_scale: gr.update(visible=True),
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}
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elif model_choice == "sdxl flash":
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return {
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@@ -1435,6 +1448,8 @@ with gr.Blocks(theme=theme, css=css) as demo:
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prior_guidance_scale: gr.update(visible=False),
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decoder_num_inference_steps: gr.update(visible=False),
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decoder_guidance_scale: gr.update(visible=False),
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}
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elif model_choice == "sd1.5":
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return {
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@@ -1466,8 +1481,8 @@ with gr.Blocks(theme=theme, css=css) as demo:
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prior_guidance_scale: gr.update(visible=False),
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decoder_num_inference_steps: gr.update(visible=False),
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decoder_guidance_scale: gr.update(visible=False),
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-
width: gr.update(maximum=1344),
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-
height: gr.update(maximum=1344),
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}
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model_choice.change(
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guidance_scale=decoder_guidance_scale,
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).images
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+
# the rest of the models have similar pipeline
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else:
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output = pipe(
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prompt=prompt,
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# Define the image generation function for the Arena tab
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+
@spaces.GPU(duration=200)
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def generate_arena_images(
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prompt,
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negative_prompt,
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generator = torch.Generator().manual_seed(seed)
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# Generate images for selected models
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if num_models_to_compare >= 2:
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images_a = generate_single_image(
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prompt,
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decoder_num_inference_steps_a,
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decoder_guidance_scale_a,
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)
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images_b = generate_single_image(
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prompt,
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negative_prompt,
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decoder_num_inference_steps_b,
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decoder_guidance_scale_b,
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)
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+
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+
output_arena_images = images_a, images_b, None, None
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+
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if num_models_to_compare >= 3:
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images_c = generate_single_image(
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prompt,
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decoder_num_inference_steps_c,
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decoder_guidance_scale_c,
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)
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+
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+
output_arena_images = images_a, images_b, images_c, None
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+
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if num_models_to_compare >= 4:
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images_d = generate_single_image(
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prompt,
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decoder_num_inference_steps_d,
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decoder_guidance_scale_d,
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)
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+
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+
output_arena_images = images_a, images_b, images_c, images_d
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+
return output_arena_images
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# Define the image generation function for the Individual tab
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prior_guidance_scale_c: gr.update(visible=True),
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decoder_num_inference_steps_c: gr.update(visible=True),
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decoder_guidance_scale_c: gr.update(visible=True),
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width_c: gr.update(value=1024, maximum=1344),
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height_c: gr.update(value=1024, maximum=1344),
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}
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elif model_choice_c == "sdxl flash":
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return {
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prior_guidance_scale_c: gr.update(visible=False),
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decoder_num_inference_steps_c: gr.update(visible=False),
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decoder_guidance_scale_c: gr.update(visible=False),
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width_c: gr.update(value=1024, maximum=1344),
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height_c: gr.update(value=1024, maximum=1344),
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}
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elif model_choice_c == "sd1.5":
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return {
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prior_guidance_scale_c: gr.update(visible=False),
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decoder_num_inference_steps_c: gr.update(visible=False),
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decoder_guidance_scale_c: gr.update(visible=False),
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width_c: gr.update(value=1024, maximum=1344),
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height_c: gr.update(value=1024, maximum=1344),
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}
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def toggle_visibility_arena_d(model_choice_d):
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prior_guidance_scale_d: gr.update(visible=True),
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decoder_num_inference_steps_d: gr.update(visible=True),
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decoder_guidance_scale_d: gr.update(visible=True),
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width_d: gr.update(value=1024, maximum=1344),
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height_d: gr.update(value=1024, maximum=1344),
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}
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elif model_choice_d == "sdxl flash":
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return {
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prior_guidance_scale_d: gr.update(visible=False),
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decoder_num_inference_steps_d: gr.update(visible=False),
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decoder_guidance_scale_d: gr.update(visible=False),
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width_d: gr.update(value=1024, maximum=1344),
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height_d: gr.update(value=1024, maximum=1344),
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}
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elif model_choice_d == "sd1.5":
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return {
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prior_guidance_scale_d: gr.update(visible=False),
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decoder_num_inference_steps_d: gr.update(visible=False),
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decoder_guidance_scale_d: gr.update(visible=False),
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width_d: gr.update(value=1024, maximum=1344),
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height_d: gr.update(value=1024, maximum=1344),
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}
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model_choice_a.change(
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prior_guidance_scale: gr.update(visible=True),
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decoder_num_inference_steps: gr.update(visible=True),
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decoder_guidance_scale: gr.update(visible=True),
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+
width: gr.update(value=1024, maximum=1344),
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height: gr.update(value=1024, maximum=1344),
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}
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elif model_choice == "sdxl flash":
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return {
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prior_guidance_scale: gr.update(visible=False),
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decoder_num_inference_steps: gr.update(visible=False),
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decoder_guidance_scale: gr.update(visible=False),
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+
width: gr.update(value=1024, maximum=1344),
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+
height: gr.update(value=1024, maximum=1344),
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}
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elif model_choice == "sd1.5":
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return {
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prior_guidance_scale: gr.update(visible=False),
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decoder_num_inference_steps: gr.update(visible=False),
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decoder_guidance_scale: gr.update(visible=False),
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+
width: gr.update(value=1024, maximum=1344),
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+
height: gr.update(value=1024, maximum=1344),
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}
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model_choice.change(
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