File size: 2,988 Bytes
7daf628 | 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 56 57 58 59 60 61 62 63 64 65 66 67 68 | import subprocess
import platform
def get_cpu_info_linux():
try:
result = subprocess.run(['lscpu'], capture_output=True, text=True, check=True)
print("---- CPU Info (Linux) ----")
print(result.stdout)
except FileNotFoundError:
print("lscpu command not found.")
except subprocess.CalledProcessError as e:
print(f"Error running lscpu: {e}")
def get_gpu_info_nvidia():
try:
result = subprocess.run(['nvidia-smi'], capture_output=True, text=True, check=True)
print("---- GPU Info (NVIDIA) ----")
print(result.stdout)
except FileNotFoundError:
print("nvidia-smi command not found. NVIDIA drivers might not be installed or not in PATH.")
except subprocess.CalledProcessError as e:
print(f"Error running nvidia-smi: {e}")
if __name__ == "__main__":
os_type = platform.system()
print(f"Operating System: {os_type}")
if os_type == "Linux":
get_cpu_info_linux()
get_gpu_info_nvidia() # Also try rocm-smi if you have AMD
elif os_type == "Darwin": # macOS
print("---- CPU Info (macOS) ----")
subprocess.run(['sysctl', '-n', 'machdep.cpu.brand_string'])
subprocess.run(['sysctl', '-n', 'hw.ncpu'])
# For GPU, check System Information manually or use more specific tools if available
elif os_type == "Windows":
print("---- CPU Info (Windows) ----")
subprocess.run(['wmic', 'cpu', 'get', 'Name,NumberOfCores,NumberOfLogicalProcessors'], shell=True)
print("---- GPU Info (Windows - NVIDIA Example) ----")
try:
subprocess.run(['nvidia-smi'], shell=True) # May need to ensure nvidia-smi is in PATH
except FileNotFoundError:
print("nvidia-smi not found. For GPU info, check Task Manager or DxDiag.")
else:
print(f"Unsupported OS for this script: {os_type}")
# For PyTorch to check CUDA availability and GPU details:
try:
import torch
if torch.cuda.is_available():
print("\n---- PyTorch CUDA Info ----")
print(f"CUDA Available: {torch.cuda.is_available()}")
print(f"CUDA Version (PyTorch compiled with): {torch.version.cuda}")
print(f"Number of GPUs: {torch.cuda.device_count()}")
for i in range(torch.cuda.device_count()):
print(f" GPU {i}: {torch.cuda.get_device_name(i)}")
print(f" Memory Allocated: {torch.cuda.memory_allocated(i)/1024**2:.2f} MB")
print(f" Memory Cached: {torch.cuda.memory_reserved(i)/1024**2:.2f} MB") # formerly memory_cached
props = torch.cuda.get_device_properties(i)
print(f" Total Memory: {props.total_memory/1024**2:.2f} MB")
print(f" Compute Capability: {props.major}.{props.minor}")
else:
print("\nPyTorch: CUDA is not available.")
except ImportError:
print("\nPyTorch is not installed.") |