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* changes * changes * revert changes * changes * add changeset * notebooks script * changes * changes --------- Co-authored-by: Ali Abid <aliabid94@gmail.com> Co-authored-by: gradio-pr-bot <gradio-pr-bot@users.noreply.github.com> Co-authored-by: Ali Abdalla <ali.si3luwa@gmail.com>
68 lines
2.3 KiB
Python
68 lines
2.3 KiB
Python
import time
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import gradio as gr
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import atexit
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import pathlib
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log_file = pathlib.Path(__file__).parent / "cancel_events_output_log.txt"
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def fake_diffusion(steps):
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log_file.write_text("")
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for i in range(steps):
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print(f"Current step: {i}")
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with log_file.open("a") as f:
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f.write(f"Current step: {i}\n")
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time.sleep(0.2)
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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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run = gr.Button(value="Start Iterating")
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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(
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label="Cancel Iteration and Expensive Calculation on Change"
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)
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cancel_on_submit = gr.Textbox(
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label="Cancel Iteration and Expensive Calculation on Submit"
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)
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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(
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sources=["webcam"], label="Cancel on clear", interactive=True
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)
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with gr.Column():
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video = gr.Video(
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sources=["webcam"], label="Cancel on start recording", interactive=True
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)
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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(
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fn=long_prediction, inputs=[textbox], outputs=prediction
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)
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cancel_on_change.change(None, None, None, cancels=[click_event, pred_event])
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cancel_on_submit.submit(
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lambda s: s, cancel_on_submit, echo, cancels=[click_event, pred_event]
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)
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image.clear(None, None, None, cancels=[click_event, pred_event])
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video.start_recording(None, None, None, cancels=[click_event, pred_event])
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demo.queue(max_size=20)
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atexit.register(lambda: log_file.unlink())
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if __name__ == "__main__":
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demo.launch()
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