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import time | |
import gradio as gr | |
import atexit | |
import pathlib | |
log_file = pathlib.Path(__file__).parent / "cancel_events_output_log.txt" | |
def fake_diffusion(steps): | |
log_file.write_text("") | |
for i in range(steps): | |
print(f"Current step: {i}") | |
with log_file.open("a") as f: | |
f.write(f"Current step: {i}\n") | |
time.sleep(0.2) | |
yield str(i) | |
def long_prediction(*args, **kwargs): | |
time.sleep(10) | |
return 42 | |
with gr.Blocks() as demo: | |
with gr.Row(): | |
with gr.Column(): | |
n = gr.Slider(1, 10, value=9, step=1, label="Number Steps") | |
run = gr.Button(value="Start Iterating") | |
output = gr.Textbox(label="Iterative Output") | |
stop = gr.Button(value="Stop Iterating") | |
with gr.Column(): | |
textbox = gr.Textbox(label="Prompt") | |
prediction = gr.Number(label="Expensive Calculation") | |
run_pred = gr.Button(value="Run Expensive Calculation") | |
with gr.Column(): | |
cancel_on_change = gr.Textbox( | |
label="Cancel Iteration and Expensive Calculation on Change" | |
) | |
cancel_on_submit = gr.Textbox( | |
label="Cancel Iteration and Expensive Calculation on Submit" | |
) | |
echo = gr.Textbox(label="Echo") | |
with gr.Row(): | |
with gr.Column(): | |
image = gr.Image( | |
sources=["webcam"], label="Cancel on clear", interactive=True | |
) | |
with gr.Column(): | |
video = gr.Video( | |
sources=["webcam"], label="Cancel on start recording", interactive=True | |
) | |
click_event = run.click(fake_diffusion, n, output) | |
stop.click(fn=None, inputs=None, outputs=None, cancels=[click_event]) | |
pred_event = run_pred.click( | |
fn=long_prediction, inputs=[textbox], outputs=prediction | |
) | |
cancel_on_change.change(None, None, None, cancels=[click_event, pred_event]) | |
cancel_on_submit.submit( | |
lambda s: s, cancel_on_submit, echo, cancels=[click_event, pred_event] | |
) | |
image.clear(None, None, None, cancels=[click_event, pred_event]) | |
video.start_recording(None, None, None, cancels=[click_event, pred_event]) | |
demo.queue(max_size=20) | |
atexit.register(lambda: log_file.unlink()) | |
if __name__ == "__main__": | |
demo.launch() | |