File size: 1,090 Bytes
7197456 9c85732 622f8d4 aa239ce 61f930c 622f8d4 f199171 9c85732 8c2b61b 622f8d4 f199171 9c85732 7197456 9c85732 61f930c 7197456 367d07a 61f930c 7197456 b194cd1 7197456 3f8ee6d 7b99542 34619cb 7b99542 7197456 10ecedc 7197456 |
1 2 3 4 5 6 7 8 9 10 11 12 13 14 15 16 17 18 19 20 21 22 23 24 25 26 27 28 29 30 31 32 33 34 35 36 37 38 39 40 41 42 43 44 45 46 47 48 49 50 51 52 53 54 55 |
import spaces
import gradio as gr
import platform
import os;
import socket;
import torch
device = torch.device("cuda" if torch.cuda.is_available() else "cpu")
def sysinfo(device):
RandomTensor = torch.randn(1, 2) # Example audio tensor
tensorExample = RandomTensor.to(device)
tocpu = tensorExample.cpu().squeeze().half().tolist()
return f"""
hostname: {platform.node()} {socket.gethostname()}
device: {device}
tensor: {tensorExample}
toCpu: {tocpu}
""";
@spaces.GPU
def gpu():
return sysinfo("cuda:0");
def nogpu():
return sysinfo("cpu");
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"
)
|