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import spaces
import gradio as gr
import platform
import os;
import socket;
import torch
device = "cuda";
if not torch.cuda.is_available() and device == "cuda":
raise RuntimeError("CUDA device unavailable, please use Dockerfile.cpu instead.")
print("DEVICE: ", device);
RandomTensor = torch.randn(1, 2) # Example audio tensor
RandomTensor.to(device)
def sysinfo(device):
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"
)
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