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import gradio as gr | |
from pathlib import Path | |
from demo import SdmCompressionDemo | |
if __name__ == "__main__": | |
servicer = SdmCompressionDemo() | |
example_list = servicer.get_example_list() | |
with gr.Blocks(theme='nota-ai/theme') as demo: | |
gr.Markdown(Path('docs/header.md').read_text()) | |
gr.Markdown(Path('docs/description.md').read_text()) | |
with gr.Row(): | |
with gr.Column(variant='panel',scale=30): | |
text = gr.Textbox(label="Input Prompt", max_lines=5, placeholder="Enter your prompt") | |
with gr.Row().style(equal_height=True): | |
generate_original_button = gr.Button(value="Generate with Original Model", variant="primary") | |
generate_compressed_button = gr.Button(value="Generate with Compressed Model", variant="primary") | |
with gr.Accordion("Advanced Settings", open=False): | |
negative = gr.Textbox(label=f'Negative Prompt', placeholder=f'Enter aspects to remove (e.g., {"low quality"})') | |
with gr.Row(): | |
guidance_scale = gr.Slider(label="Guidance Scale", value=7.5, minimum=4, maximum=11, step=0.5) | |
steps = gr.Slider(label="Denoising Steps", value=25, minimum=10, maximum=75, step=5) | |
seed = gr.Slider(0, 999999, label='Random Seed', value=1234, step=1) | |
with gr.Tab("Example Prompts"): | |
examples = gr.Examples(examples=example_list, inputs=[text]) | |
with gr.Column(variant='panel',scale=35): | |
# Define original model output components | |
gr.Markdown('<h2 align="center">Original Stable Diffusion 1.4</h2>') | |
original_model_output = gr.Image(label="Original Model") | |
with gr.Row().style(equal_height=True): | |
original_model_test_time = gr.Textbox(value="", label="Inference Time (sec)") | |
original_model_error = gr.Markdown() | |
with gr.Column(variant='panel',scale=35): | |
# Define compressed model output components | |
gr.Markdown('<h2 align="center">Compressed Stable Diffusion (Ours)</h2>') | |
compressed_model_output = gr.Image(label="Compressed Model") | |
with gr.Row().style(equal_height=True): | |
compressed_model_test_time = gr.Textbox(value="", label="Inference Time (sec)") | |
compressed_model_error = gr.Markdown() | |
inputs = [text, negative, guidance_scale, steps, seed] | |
# Click the generate button for original model | |
original_model_outputs = [original_model_output, original_model_error, original_model_test_time] | |
text.submit(servicer.infer_original_model, inputs=inputs, outputs=original_model_outputs) | |
generate_original_button.click(servicer.infer_original_model, inputs=inputs, outputs=original_model_outputs) | |
# Click the generate button for compressed model | |
compressed_model_outputs = [compressed_model_output, compressed_model_error, compressed_model_test_time] | |
text.submit(servicer.infer_compressed_model, inputs=inputs, outputs=compressed_model_outputs) | |
generate_compressed_button.click(servicer.infer_compressed_model, inputs=inputs, outputs=compressed_model_outputs) | |
gr.Markdown(Path('docs/footer.md').read_text()) | |
demo.queue(concurrency_count=1) | |
# demo.launch() | |
demo.launch(share=True, auth=("test", "testasdf@@19")) | |