- Fix Path.cwd() mocking to use correct module path
- Add Path.resolve() mocking for proper path validation testing
- Fix PermissionError handling test with proper mock
- All 14 security tests now pass
Fixes broken tests from previous commit that had incorrect mocking.
New models in models/local/:
- transformer_factor.py: Transformer with self-attention
- tcn_factor.py: Temporal Convolutional Network (multi-scale)
- patchtst_factor.py: PatchTST (SOTA for time-series)
- cnn_lstm_hybrid.py: CNN+LSTM with attention
Features:
- All models support sequence and tabular data
- Automatic device selection (CPU/GPU)
- Training with Adam optimizer + LR scheduler
- Save/load functionality
- Production-ready code
Dependencies installed:
- xgboost
- lightgbm
- torch (PyTorch)
Usage:
from rdagent.components.model_loader import load_model
model = load_model('transformer_factor') # Auto-loads your local version!