Centroid Classifier Refactor:
- **Normalization Improvements:** Introduced `_normalize` method for efficient tensor normalization using `torch.nn.functional.normalize`.
- **Training Enhancements:**
- `train` method now calculates centroids using mean embeddings for each label.
- Centroids are stored and normalized upon training.
- **Prediction Optimization:**
- Improved `predict` and `predict_one` methods to utilize normalized centroids.
- Replaced cosine similarity calculations with dot product for faster computations.
Interface Changes:
- Updated `get_embeddings` method to yield `torch.Tensor` instead of `numpy.ndarray`.
- Removed redundant code and streamlined embedding extraction process.
Embedding Model Initialization:
- Ensured the embedding model is set to evaluation mode immediately after loading to improve inference efficiency (`self._model.eval()`).