| """ | |
| Protein Sequence-Level Prediction with Multiple Token Aggregation Methods. | |
| Extracts residue embeddings from ESM2 (frozen backbone) and performs | |
| sequence-level prediction (e.g., localization) using 6 aggregation strategies: | |
| 1. Mean pooling | |
| 2. Max pooling | |
| 3. CLS token | |
| 4. GLOT (cosine-similarity token graph) | |
| 5. GLOT-Residue (protein residue contact graph via graphein) | |
| 6. Covariance pooling | |
| Reference: | |
| - GLOT: "Towards Improved Sentence Representations using Token Graphs" (arXiv:2603.03389) | |
| - Covariance Pooling: https://www.goodfire.ai/research/covariance-pooling | |
| - Graphein: https://graphein.ai/ | |
| """ | |
| from .model import ProteinSequenceClassifier | |
| from .aggregators import ( | |
| MeanPooling, | |
| MaxPooling, | |
| CLSPooling, | |
| GLOTPooling, | |
| GLOTResidueGraphPooling, | |
| CovariancePooling, | |
| ) | |
| __all__ = [ | |
| "ProteinSequenceClassifier", | |
| "MeanPooling", | |
| "MaxPooling", | |
| "CLSPooling", | |
| "GLOTPooling", | |
| "GLOTResidueGraphPooling", | |
| "CovariancePooling", | |
| ] | |