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import spaces |
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import datetime |
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import os |
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import subprocess |
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import torch |
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import gradio as gr |
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CUSTOM_CSS = """ |
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#output_box textarea { |
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font-family: IBM Plex Mono, ui-monospace, SFMono-Regular, Menlo, Monaco, Consolas, "Liberation Mono", "Courier New", monospace; |
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} |
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""" |
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zero = torch.Tensor([0]).cuda() |
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print(zero.device) |
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@spaces.GPU |
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def run_gpu() -> str: |
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print(zero.device) |
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output: str = "" |
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try: |
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output = subprocess.check_output(["nvidia-smi"], text=True) |
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except FileNotFoundError: |
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output = "nvidia-smi failed" |
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comment = ( |
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datetime.datetime.now().replace(microsecond=0).isoformat().replace("T", " ") |
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) |
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return f"# {comment}\n\n{output}" |
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def run(check: bool) -> str: |
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if check: |
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return run_gpu() |
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else: |
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comment = ( |
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datetime.datetime.now().replace(microsecond=0).isoformat().replace("T", " ") |
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) |
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return f"# {comment}\n\nThis is running on CPU\n\nClick on 'Run on GPU' below to move to GPU instantly and run nvidia-smi" |
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output = gr.Textbox( |
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label="Command Output", max_lines=32, elem_id="output_box", value=run(False) |
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) |
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with gr.Blocks(css=CUSTOM_CSS) as demo: |
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gr.Markdown("#### `zero-gpu`: how to run on serverless GPU for free on Spaces 🔥") |
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output.render() |
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check = gr.Checkbox(label="Run on GPU") |
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check.change(run, inputs=[check], outputs=output, every=1) |
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demo.queue().launch(show_api=False) |
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