capreolus.reranker
¶
Submodules¶
capreolus.reranker.CDSSM
capreolus.reranker.ConvKNRM
capreolus.reranker.DRMM
capreolus.reranker.DRMMTKS
capreolus.reranker.DSSM
capreolus.reranker.DUET
capreolus.reranker.DeepTileBar
capreolus.reranker.HINT
capreolus.reranker.KNRM
capreolus.reranker.PACRR
capreolus.reranker.POSITDRMM
capreolus.reranker.TFBERTMaxP
capreolus.reranker.TFKNRM
capreolus.reranker.TFVanillaBert
capreolus.reranker.TK
capreolus.reranker.birch
capreolus.reranker.common
capreolus.reranker.parade
Package Contents¶
Classes¶
Reranker |
Base class for Reranker modules. The purpose of a Reranker is to predict relevance scores for input documents. Rerankers are generally supervised methods implemented in PyTorch or TensorFlow. |
-
class
capreolus.reranker.
Reranker
(config=None, provide=None, share_dependency_objects=False, build=True)[source]¶ Bases:
capreolus.ModuleBase
Base class for Reranker modules. The purpose of a Reranker is to predict relevance scores for input documents. Rerankers are generally supervised methods implemented in PyTorch or TensorFlow.
- Modules should provide:
- a
build_model
method that initializes the model used - a
score
and atest
method that take a representation created by anExtractor
module as input and return document scores - a
load_weights
and asave_weights
method, if the base class’ PyTorch methods cannot be used
- a