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