"""
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",
]