2022-10-15 06:43:24 +08:00
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import time
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import gradio as gr
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def fake_diffusion(steps):
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for i in range(steps):
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print(f"Current step: {i}")
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2023-06-30 23:59:50 +08:00
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time.sleep(0.2)
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2022-10-15 06:43:24 +08:00
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yield str(i)
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def long_prediction(*args, **kwargs):
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time.sleep(10)
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return 42
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with gr.Blocks() as demo:
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with gr.Row():
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with gr.Column():
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n = gr.Slider(1, 10, value=9, step=1, label="Number Steps")
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2023-06-30 23:59:50 +08:00
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run = gr.Button(value="Start Iterating")
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2022-10-15 06:43:24 +08:00
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output = gr.Textbox(label="Iterative Output")
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stop = gr.Button(value="Stop Iterating")
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with gr.Column():
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textbox = gr.Textbox(label="Prompt")
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prediction = gr.Number(label="Expensive Calculation")
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run_pred = gr.Button(value="Run Expensive Calculation")
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with gr.Column():
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cancel_on_change = gr.Textbox(label="Cancel Iteration and Expensive Calculation on Change")
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cancel_on_submit = gr.Textbox(label="Cancel Iteration and Expensive Calculation on Submit")
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echo = gr.Textbox(label="Echo")
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with gr.Row():
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with gr.Column():
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image = gr.Image(source="webcam", tool="editor", label="Cancel on edit", interactive=True)
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with gr.Column():
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video = gr.Video(source="webcam", label="Cancel on play", interactive=True)
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click_event = run.click(fake_diffusion, n, output)
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stop.click(fn=None, inputs=None, outputs=None, cancels=[click_event])
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pred_event = run_pred.click(fn=long_prediction, inputs=[textbox], outputs=prediction)
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cancel_on_change.change(None, None, None, cancels=[click_event, pred_event])
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cancel_on_submit.submit(lambda s: s, cancel_on_submit, echo, cancels=[click_event, pred_event])
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image.edit(None, None, None, cancels=[click_event, pred_event])
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video.play(None, None, None, cancels=[click_event, pred_event])
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2023-06-30 23:59:50 +08:00
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demo.queue(concurrency_count=2, max_size=20)
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2022-10-15 06:43:24 +08:00
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if __name__ == "__main__":
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2023-06-30 23:59:50 +08:00
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demo.launch()
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