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. """ Verification script for PyTorch installation on Windows. This script checks if PyTorch is properly installed and configured for Windows. """ import os import sys import platform import subprocess import importlib.util def print_header(text): """Print a formatted header.""" print("\n" + "=" * 80) print(f" {text}") print("=" * 80) def print_info(text): """Print formatted info text.""" print(f" → {text}") def print_success(text): """Print formatted success text.""" print(f" ✅ {text}") def print_error(text): """Print formatted error text.""" print(f" ❌ ERROR: {text}") def print_warning(text): """Print formatted warning text.""" print(f" ⚠️ {text}") def check_system(): """Check if running on Windows.""" system = platform.system().lower() if system != "windows": print_warning(f"This script is designed for Windows, but you're running on {system.capitalize()}") else: print_info(f"Running on {platform.system()} {platform.release()}") print_info(f"Python version: {platform.python_version()}") print_info(f"Architecture: {platform.machine()}") return system == "windows" def check_pytorch_installation(): """Check if PyTorch is installed and properly configured.""" try: import torch print_success(f"PyTorch is installed (version {torch.__version__})") # Check if PyTorch was installed from the correct index URL if hasattr(torch, '_C'): print_success("PyTorch C extensions are available") else: print_warning("PyTorch C extensions might not be properly installed") # Check CUDA availability 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)}") print_info(f"GPU Memory: {torch.cuda.get_device_properties(0).total_memory / (1024**3):.2f} GB") else: print_info("CUDA is not available, using CPU only") # Check if DirectML is available try: import torch_directml print_success(f"DirectML is available (version {torch_directml.__version__})") # Check for Intel ARC GPU try: ps_cmd = "Get-WmiObject Win32_VideoController | Select-Object Name | Format-List" gpu_output = subprocess.check_output(['powershell', '-Command', ps_cmd], stderr=subprocess.DEVNULL, universal_newlines=True) if 'Intel(R) Arc(TM)' in gpu_output or 'Intel ARC' in gpu_output: print_success("Intel ARC GPU detected, DirectML support is available") elif 'Intel' in gpu_output: print_success("Intel GPU detected, DirectML support is available") elif 'AMD' in gpu_output or 'Radeon' in gpu_output: print_success("AMD GPU detected, DirectML support is available") except (subprocess.SubprocessError, FileNotFoundError): pass # Test a simple DirectML tensor operation try: dml = torch_directml.device() x_dml = torch.rand(5, 3, device=dml) y_dml = torch.rand(5, 3, device=dml) z_dml = x_dml + y_dml print_success("DirectML tensor operations work correctly") except Exception as e: print_warning(f"DirectML tensor operations failed: {e}") except ImportError: print_info("DirectML is not available") # Check for Intel/AMD GPUs that could benefit from DirectML try: ps_cmd = "Get-WmiObject Win32_VideoController | Select-Object Name | Format-List" gpu_output = subprocess.check_output(['powershell', '-Command', ps_cmd], stderr=subprocess.DEVNULL, universal_newlines=True) if 'Intel(R) Arc(TM)' in gpu_output or 'Intel ARC' in gpu_output: print_warning("Intel ARC GPU detected, but DirectML is not installed") print_info("Consider installing torch-directml for better performance") elif 'Intel' in gpu_output or 'AMD' in gpu_output or 'Radeon' in gpu_output: print_warning("Intel/AMD GPU detected, but DirectML is not installed") print_info("Consider installing torch-directml for better performance") except (subprocess.SubprocessError, FileNotFoundError): pass # 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: print_error("PyTorch is not installed") return False except Exception as e: print_error(f"Error checking PyTorch installation: {e}") return False def suggest_installation(): """Suggest PyTorch installation commands.""" print_header("Installation Suggestions") print_info("To install PyTorch for Windows, use one of the following commands:") print_info("\nFor CUDA support (NVIDIA GPUs):") print("pip install torch torchvision torchaudio --index-url https://download.pytorch.org/whl/cu118") print_info("\nFor CPU-only:") print("pip install torch torchvision torchaudio --index-url https://download.pytorch.org/whl/cpu") print_info("\nFor DirectML support (AMD/Intel GPUs):") print("pip install torch torchvision torchaudio --index-url https://download.pytorch.org/whl/cpu") print("pip install torch-directml>=0.2.0") print_info("\nFor Intel ARC Pro Graphics:") print("pip install torch==2.2.0 torchvision==2.2.0 torchaudio==2.2.0 --index-url https://download.pytorch.org/whl/cpu") print("pip install torch-directml>=0.2.0") print_info("\nFor dual GPU setups (NVIDIA + Intel):") print("pip install torch==2.2.0 torchvision==2.2.0 torchaudio==2.2.0 --index-url https://download.pytorch.org/whl/cu118") print("pip install torch-directml>=0.2.0") print_info("\nAfter installing PyTorch, run this script again to verify the installation.") def main(): """Main function.""" print_header("PyTorch Windows Installation Verification") is_windows = check_system() if not is_windows: print_warning("This script is designed for Windows, but may still provide useful information") pytorch_installed = check_pytorch_installation() if not pytorch_installed: suggest_installation() return 1 print_header("Verification Complete") print_success("PyTorch is properly installed and configured for Windows") return 0 if __name__ == "__main__": sys.exit(main())