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Update app.py
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app.py
CHANGED
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@@ -57,19 +57,13 @@ pipe_hyper.to("cuda")
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del unet
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@spaces.GPU
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def
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image_turbo=pipe_turbo(prompt=prompt, num_inference_steps=1, guidance_scale=0).images[0]
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@spaces.GPU
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def run_comparison_lightning(prompt, progress=gr.Progress(track_tqdm=True)):
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image_lightning=pipe_lightning(prompt=prompt, num_inference_steps=1, guidance_scale=0).images[0]
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@spaces.GPU
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def run_comparison_hyper(prompt, progress=gr.Progress(track_tqdm=True)):
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image_hyper=pipe_hyper(prompt=prompt, num_inference_steps=1, guidance_scale=0, timesteps=[800]).images[0]
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return image_hyper
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examples = ["A dignified beaver wearing glasses, a vest, and colorful neck tie.",
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"The spirit of a tamagotchi wandering in the city of Barcelona",
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@@ -98,22 +92,16 @@ with gr.Blocks() as demo:
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image_outputs = [image_turbo, image_lightning, image_hyper]
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gr.on(
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triggers=[prompt.submit, run.click],
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fn=
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inputs=prompt,
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outputs=image_turbo
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).then(
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fn=run_comparison_lightning,
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inputs=prompt,
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outputs=image_lightning
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).then(
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fn=run_comparison_hyper,
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inputs=prompt,
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outputs=
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)
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gr.Examples(
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examples=examples,
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inputs=prompt,
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outputs=image_outputs,
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cache_examples=False
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)
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demo.launch()
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del unet
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@spaces.GPU
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def run_comparison(prompt, progress=gr.Progress(track_tqdm=True)):
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image_turbo=pipe_turbo(prompt=prompt, num_inference_steps=1, guidance_scale=0).images[0]
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yield image_turbo, None, None
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image_lightning=pipe_lightning(prompt=prompt, num_inference_steps=1, guidance_scale=0).images[0]
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yield image_turbo, image_lightning, None
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image_hyper=pipe_hyper(prompt=prompt, num_inference_steps=1, guidance_scale=0, timesteps=[800]).images[0]
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return image_turbo, image_lightning, image_hyper
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examples = ["A dignified beaver wearing glasses, a vest, and colorful neck tie.",
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"The spirit of a tamagotchi wandering in the city of Barcelona",
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image_outputs = [image_turbo, image_lightning, image_hyper]
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gr.on(
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triggers=[prompt.submit, run.click],
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fn=run_comparison,
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inputs=prompt,
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outputs=image_outputs
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)
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gr.Examples(
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examples=examples,
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fn=run_comparison,
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inputs=prompt,
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outputs=image_outputs,
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cache_examples=False,
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run_on_click=True
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)
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demo.launch()
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