gnes.indexer.chunk.numpy module¶
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class
gnes.indexer.chunk.numpy.
NumpyIndexer
(is_binary=False, *args, **kwargs)[source]¶ Bases:
gnes.indexer.base.BaseChunkIndexer
An exhaustive search indexer using numpy The distance is computed as L1 distance normalized by the number of dimension
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add
(keys, vectors, weights, *args, **kwargs)[source]¶ adding new chunks and their vector representations
Parameters: - keys (
List
[Tuple
[int
,Any
]]) – list of (doc_id, offset) tuple - vectors (
ndarray
) – vector representations - weights (
List
[float
]) – weight of the chunks
- keys (
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train
(*args, **kwargs)¶ Train the model, need to be overrided
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