MCP Memory Service

#!/usr/bin/env python3 # Copyright 2024 Heinrich Krupp # # Licensed under the Apache License, Version 2.0 (the "License"); # you may not use this file except in compliance with the License. # You may obtain a copy of the License at # # http://www.apache.org/licenses/LICENSE-2.0 # # Unless required by applicable law or agreed to in writing, software # distributed under the License is distributed on an "AS IS" BASIS, # WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied. # See the License for the specific language governing permissions and # limitations under the License. """ Verify PyTorch installation and functionality. This script attempts to import PyTorch and run basic operations. """ import os import sys # Disable sitecustomize.py and other import hooks to prevent recursion issues os.environ["PYTHONNOUSERSITE"] = "1" # Disable user site-packages os.environ["PYTHONPATH"] = "" # Clear PYTHONPATH def print_info(text): """Print formatted info text.""" print(f"[INFO] {text}") def print_error(text): """Print formatted error text.""" print(f"[ERROR] {text}") def print_success(text): """Print formatted success text.""" print(f"[SUCCESS] {text}") def print_warning(text): """Print formatted warning text.""" print(f"[WARNING] {text}") def verify_torch(): """Verify PyTorch installation and functionality.""" print_info("Verifying PyTorch installation") # Add site-packages to sys.path site_packages = os.path.join(sys.prefix, 'Lib', 'site-packages') if site_packages not in sys.path: sys.path.insert(0, site_packages) # Print sys.path for debugging print_info("Python path:") for path in sys.path: print(f" - {path}") # Try to import torch try: print_info("Attempting to import torch") import torch print_success(f"PyTorch is installed (version {torch.__version__})") print_info(f"PyTorch location: {torch.__file__}") # Check if CUDA is available if torch.cuda.is_available(): print_success(f"CUDA is available (version {torch.version.cuda})") print_info(f"GPU: {torch.cuda.get_device_name(0)}") # Test a simple CUDA operation try: x = torch.rand(5, 3).cuda() y = torch.rand(5, 3).cuda() z = x + y print_success("Basic CUDA tensor operations work correctly") except Exception as e: print_warning(f"CUDA tensor operations failed: {e}") print_warning("Falling back to CPU mode") else: print_info("CUDA is not available, using CPU-only mode") # Test a simple tensor operation try: x = torch.rand(5, 3) y = torch.rand(5, 3) z = x + y print_success("Basic tensor operations work correctly") except Exception as e: print_error(f"Failed to perform basic tensor operations: {e}") return False return True except ImportError as e: print_error(f"PyTorch is not installed: {e}") return False except Exception as e: print_error(f"Error checking PyTorch installation: {e}") import traceback traceback.print_exc() return False def main(): """Main function.""" if verify_torch(): print_success("PyTorch verification completed successfully") else: print_error("PyTorch verification failed") sys.exit(1) if __name__ == "__main__": main()