Installation Guide

# Clone the repository
git clone https://github.com/VM230705/MAT-HPO-Library.git
cd MAT-HPO-Library

# Install dependencies
pip install torch numpy scikit-learn

# Test the installation
python test_working_examples.py

# Core ML/DL dependencies
pip install torch>=2.0.0
pip install numpy>=1.20.0
pip install scikit-learn>=1.0.0

# Optional but recommended
pip install tqdm              # Progress bars
pip install wandb             # Experiment tracking
pip install matplotlib       # Plotting
pip install seaborn          # Enhanced plotting

# For CUDA support (check your CUDA version)
pip install torch torchvision torchaudio --index-url https://download.pytorch.org/whl/cu118

# Verify GPU support
python -c "import torch; print('CUDA Available:', torch.cuda.is_available())"

# Clone the repository
git clone https://github.com/VM230705/MAT-HPO-Library.git
cd MAT-HPO-Library

# Add to Python path for development
export PYTHONPATH=$PYTHONPATH:$(pwd)

# Clone and install in development mode
git clone https://github.com/VM230705/MAT-HPO-Library.git
cd MAT-HPO-Library
pip install -e .

# This allows you to modify the code and see changes immediately

# Test basic imports
import sys
sys.path.insert(0, '.')

from MAT_HPO_LIB import MAT_HPO_Optimizer, BaseEnvironment, HyperparameterSpace
print("✅ MAT-HPO Library imported successfully!")

# Run the comprehensive functionality test
python test_working_examples.py

# Expected output:
#  MAT-HPO Library Simple Functionality Test
# ==================================================
#  Testing imports...
# ✅ Core imports successful
# ...
#  Test Results: 5/5 tests passed
#  All functionality tests passed!