add gpu info

.gitignore

@@ -0,0 +1 @@
+.idea

app.py

@@ -1,15 +1,49 @@
-import os
-os.system('pip install transformers -U')
-os.system('pip install modelscope -U')
-os.system('pip install accelerate')
-os.system('pip install psutil')
 
+import os
+##
 # 获取全部环境变量
 env_vars = os.environ
 
 # 遍历并打印环境变量
 for key, value in env_vars.items():
     print(f"{key}: {value}")
+##
+import subprocess
+import json
+
+# 运行nvidia-smi命令并以JSON格式获取输出
+result = subprocess.run(
+    ['nvidia-smi', '--query-gpu=index,name,memory.total,memory.used,memory.free,utilization.gpu,temperature.gpu',
+     '--format=csv,noheader,nounits', '--json'],
+    stdout=subprocess.PIPE, stderr=subprocess.PIPE, text=True
+)
+
+# 解析输出
+if result.stdout:
+    gpu_info_json = result.stdout
+
+    # 将JSON字符串转换成Python字典
+    gpu_info = json.loads(gpu_info_json)
+
+    # 打印全部GPU信息
+    print(json.dumps(gpu_info, indent=4))
+else:
+    print("Error:", result.stderr)
+
+##
+import GPUtil
+
+# 获取所有可用的GPU列表
+gpus = GPUtil.getGPUs()
+
+# 遍历列表，打印每个GPU的详细信息
+for gpu in gpus:
+    print(f"GPU ID: {gpu.id}, Name: {gpu.name}")
+    print(f"  Total Memory: {gpu.memoryTotal}MB")
+    print(f"  Used Memory: {gpu.memoryUsed}MB")
+    print(f"  Free Memory: {gpu.memoryFree}MB")
+    print(f"  GPU Utilization: {gpu.load*100}%")
+    print(f"  GPU Temperature: {gpu.temperature}C\n")
 
 import spaces
 from threading import Thread

requirements.txt

@@ -0,0 +1,5 @@
+transformers
+modelscope
+accelerate
+psutil
+gputil