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Runtime error
Update stable_cascade.py
Browse files- stable_cascade.py +17 -7
stable_cascade.py
CHANGED
@@ -7,14 +7,14 @@ import gradio as gr
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prior = StableCascadePriorPipeline.from_pretrained("stabilityai/stable-cascade-prior", torch_dtype=torch.bfloat16)
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decoder = StableCascadeDecoderPipeline.from_pretrained("stabilityai/stable-cascade", torch_dtype=torch.bfloat16)
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def generate_images(
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prompt="a photo of a girl",
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@@ -22,6 +22,7 @@ def generate_images(
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height=1024,
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width=1024,
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guidance_scale=4.0,
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prior_inference_steps=20,
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decoder_inference_steps=10
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):
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@@ -46,7 +47,7 @@ def generate_images(
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width=width,
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negative_prompt=negative_prompt,
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guidance_scale=guidance_scale,
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num_images_per_prompt=
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num_inference_steps=prior_inference_steps
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)
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@@ -80,6 +81,14 @@ def web_demo():
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)
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with gr.Row():
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with gr.Column():
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text2image_height = gr.Slider(
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minimum=128,
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maximum=1280,
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@@ -136,6 +145,7 @@ def web_demo():
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text2image_height,
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text2image_width,
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text2image_guidance_scale,
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text2image_prior_inference_step,
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text2image_decoder_inference_step
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],
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prior = StableCascadePriorPipeline.from_pretrained("stabilityai/stable-cascade-prior", torch_dtype=torch.bfloat16)
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decoder = StableCascadeDecoderPipeline.from_pretrained("stabilityai/stable-cascade", torch_dtype=torch.bfloat16)
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prior.enable_model_cpu_offload()
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decoder.enable_model_cpu_offload()
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prior.prior = torch.compile(prior_pipeline.prior, mode="reduce-overhead", fullgraph=True)
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decoder.decoder = torch.compile(decoder_pipeline.decoder, mode="max-autotune", fullgraph=True)
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prior.to("cuda")
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decoder.to("cuda")
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def generate_images(
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prompt="a photo of a girl",
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height=1024,
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width=1024,
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guidance_scale=4.0,
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num_images_per_prompt=1,
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prior_inference_steps=20,
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decoder_inference_steps=10
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):
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width=width,
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negative_prompt=negative_prompt,
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guidance_scale=guidance_scale,
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num_images_per_prompt=num_images_per_prompt,
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num_inference_steps=prior_inference_steps
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)
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)
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with gr.Row():
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with gr.Column():
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text2image_num_images_per_prompt = gr.Slider(
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minimum=1,
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maximum=4,
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step=1,
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value=1,
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label="Number Image",
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)
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text2image_height = gr.Slider(
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minimum=128,
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maximum=1280,
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text2image_height,
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text2image_width,
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text2image_guidance_scale,
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text2image_num_images_per_prompt,
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text2image_prior_inference_step,
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text2image_decoder_inference_step
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],
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