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import spaces
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import gradio as gr
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import platform
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import os;
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import socket;
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import torch
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import torch.nn as nn
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device = torch.device("cuda" if torch.cuda.is_available() else "cpu")
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class SimpleModel(nn.Module):
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def __init__(self):
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super(SimpleModel, self).__init__()
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def forward(self, x):
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pass
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def device():
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return next(model.parameters()).device
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model = SimpleModel().to(device);
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@torch.inference_mode()
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def sysinfo():
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RandomTensor = torch.randn(1, 2)
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tensorExample = RandomTensor.to(device)
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return f"""
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hostname: {platform.node()} {socket.gethostname()}
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device: {device}
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model device: {model.device}
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tensor: {tensorExample}
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""";
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@spaces.GPU
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def gpu():
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return sysinfo();
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def nogpu():
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return sysinfo();
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with gr.Blocks() as demo:
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outgpu = gr.Textbox(lines=5);
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outnpu = gr.Textbox(lines=5);
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btngpu = gr.Button(value="gpu");
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btngpun = gr.Button(value="ngpu");
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btngpu.click(gpu, None, [outgpu]);
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btngpun.click(nogpu, None, [outnpu]);
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if __name__ == "__main__":
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demo.launch(
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share=False,
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debug=False,
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server_port=7860,
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server_name="0.0.0.0"
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)
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