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Create checkCUDA.py

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Robert Dunmire III
2025-01-12 13:05:18 -05:00
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checkCUDA.py
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"""
From https://github.com/rhasspy/piper/issues/24
"""
import torch
import os
def print_cuda_details():
if torch.cuda.is_available():
# GPU device details
device_id = torch.cuda.current_device()
device_name = torch.cuda.get_device_name(device_id)
total_memory = torch.cuda.get_device_properties(device_id).total_memory / (1024**3) # GB
memory_allocated = torch.cuda.memory_allocated(device_id) / (1024**3) # GB
memory_cached = torch.cuda.memory_reserved(device_id) / (1024**3) # GB
multiprocessors = torch.cuda.get_device_properties(device_id).multi_processor_count
# CUDA and PyTorch versions
cuda_version = torch.version.cuda
pytorch_version = torch.__version__
# Device properties
device_properties = torch.cuda.get_device_properties(device_id)
compute_capability = device_properties.major, device_properties.minor
# Display the details with improved formatting
print("~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~")
print(f"")
print("Checking CUDA information within the python environment...")
print(f"")
print("###########################################################")
print(f"CUDA Available: TRUE")
print(f"Using GPU: {device_name}")
print("###########################################################")
print(f"")
print(f"CUDA Version: {cuda_version}")
print(f"PyTorch Version: {pytorch_version}")
print(f"Device ID: {device_id}")
print(f"Total Memory: {total_memory:.2f} GB")
print(f"Memory Allocated: {memory_allocated:.2f} GB")
print(f"Memory Cached: {memory_cached:.2f} GB")
print(f"Multiprocessors: {multiprocessors}")
print(f"Compute Capability: {compute_capability[0]}.{compute_capability[1]}")
print(f"")
# Device Name
print(f"CUDA Device Name: {torch.cuda.get_device_name(device_id)}")
print(f"")
# CUDA Path (from environment variables)
cuda_path = os.getenv('CUDA_PATH', 'Not set')
print(f"CUDA Path: {cuda_path}")
# CUDA Toolkit Directory (check via environment variable if available)
cuda_toolkit_dir = os.getenv('CUDA_HOME', 'Not set')
print(f"CUDA Toolkit Dir: {cuda_toolkit_dir}")
# Environment Variables
print(f"\n")
print("=================================================")
print("--- Below are OS SYSTEM Environment Variables ---")
print(" not just whats available within the python VENV")
print("=================================================")
print(f"")
print(f"{'CUDA_HOME:':<25} {os.environ.get('CUDA_HOME', 'Not set')}")
print(f"")
print(f"{'CUDA_VISIBLE_DEVICES:':<25} {os.environ.get('CUDA_VISIBLE_DEVICES', 'Not set')}")
print(f"")
print(f"{'LD_LIBRARY_PATH:':<25} {os.environ.get('LD_LIBRARY_PATH', 'Not set')}")
print(f"")
print(f"{'PATH:':<25} {os.environ.get('PATH', 'Not set')}")
print(f"")
print("~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~")
else:
print("##############################################################")
print("CUDA is NOT available! You may need to reinstall Pytorch/Torch")
print("Falling back to using CPU.")
print("##############################################################")
print(f"")
# Provide details for CPU-based configurations
print(f"PyTorch Version: {torch.__version__}")
print("~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~")
# Call the function to print details
print_cuda_details()