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import os |
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import subprocess |
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from pathlib import Path |
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import gradio as gr |
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import torch |
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from demo import SdmCompressionDemo |
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dest_path_config = Path('checkpoints/BK-SDM-Small_iter50000/unet/config.json') |
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dest_path_torch_ckpt = Path('checkpoints/BK-SDM-Small_iter50000/unet/diffusion_pytorch_model.bin') |
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BK_SDM_CONFIG_URL: str = os.getenv('BK_SDM_CONFIG_URL', None) |
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BK_SDM_TORCH_CKPT_URL: str = os.getenv('BK_SDM_TORCH_CKPT_URL', None) |
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assert BK_SDM_CONFIG_URL is not None |
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assert BK_SDM_TORCH_CKPT_URL is not None |
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subprocess.call( |
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f"wget --no-check-certificate -O {dest_path_config} {BK_SDM_CONFIG_URL}", |
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shell=True |
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) |
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subprocess.call( |
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f"wget --no-check-certificate -O {dest_path_torch_ckpt} {BK_SDM_TORCH_CKPT_URL}", |
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shell=True |
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) |
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if __name__ == "__main__": |
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device = 'cuda' if torch.cuda.is_available() else 'cpu' |
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servicer = SdmCompressionDemo(device) |
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example_list = servicer.get_example_list() |
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with gr.Blocks(theme='nota-ai/theme') as demo: |
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gr.Markdown(Path('docs/header.md').read_text()) |
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gr.Markdown(Path('docs/description.md').read_text()) |
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with gr.Row(): |
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with gr.Column(variant='panel', scale=30): |
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text = gr.Textbox(label="Input Prompt", max_lines=5, placeholder="Enter your prompt") |
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with gr.Row().style(equal_height=True): |
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generate_original_button = gr.Button(value="Generate with Original Model", variant="primary") |
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generate_compressed_button = gr.Button(value="Generate with Compressed Model", variant="primary") |
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with gr.Accordion("Advanced Settings", open=False): |
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negative = gr.Textbox(label=f'Negative Prompt', placeholder=f'Enter aspects to remove (e.g., {"low quality"})') |
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with gr.Row(): |
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guidance_scale = gr.Slider(label="Guidance Scale", value=7.5, minimum=4, maximum=11, step=0.5) |
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steps = gr.Slider(label="Denoising Steps", value=25, minimum=10, maximum=75, step=5) |
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seed = gr.Slider(0, 999999, label='Random Seed', value=1234, step=1) |
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with gr.Tab("Example Prompts"): |
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examples = gr.Examples(examples=example_list, inputs=[text]) |
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with gr.Column(variant='panel',scale=35): |
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gr.Markdown('<h2 align="center">Original Stable Diffusion 1.4</h2>') |
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original_model_output = gr.Image(label="Original Model") |
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with gr.Row().style(equal_height=True): |
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with gr.Column(): |
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original_model_test_time = gr.Textbox(value="", label="Inference Time (sec)") |
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original_model_params = gr.Textbox(value=servicer.get_sdm_params(servicer.pipe_original), label="# Parameters") |
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original_model_error = gr.Markdown() |
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with gr.Column(variant='panel',scale=35): |
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gr.Markdown('<h2 align="center">Compressed Stable Diffusion (Ours)</h2>') |
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compressed_model_output = gr.Image(label="Compressed Model") |
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with gr.Row().style(equal_height=True): |
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with gr.Column(): |
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compressed_model_test_time = gr.Textbox(value="", label="Inference Time (sec)") |
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compressed_model_params = gr.Textbox(value=servicer.get_sdm_params(servicer.pipe_compressed), label="# Parameters") |
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compressed_model_error = gr.Markdown() |
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inputs = [text, negative, guidance_scale, steps, seed] |
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original_model_outputs = [original_model_output, original_model_error, original_model_test_time] |
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text.submit(servicer.infer_original_model, inputs=inputs, outputs=original_model_outputs) |
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generate_original_button.click(servicer.infer_original_model, inputs=inputs, outputs=original_model_outputs) |
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compressed_model_outputs = [compressed_model_output, compressed_model_error, compressed_model_test_time] |
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text.submit(servicer.infer_compressed_model, inputs=inputs, outputs=compressed_model_outputs) |
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generate_compressed_button.click(servicer.infer_compressed_model, inputs=inputs, outputs=compressed_model_outputs) |
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gr.Markdown(Path('docs/footer.md').read_text()) |
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demo.queue(concurrency_count=1) |
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demo.launch() |
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