戒酒的李白
44 lines
1.5 KiB
Python
44 lines
1.5 KiB
Python
import numpy as np
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from typing import List
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from bertopic.backend._base import BaseEmbedder
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from bertopic.backend._utils import select_backend
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class WordDocEmbedder(BaseEmbedder):
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"""Combine a document- and word-level embedder."""
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def __init__(self, embedding_model, word_embedding_model):
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super().__init__()
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self.embedding_model = select_backend(embedding_model)
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self.word_embedding_model = select_backend(word_embedding_model)
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def embed_words(self, words: List[str], verbose: bool = False) -> np.ndarray:
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"""Embed a list of n words into an n-dimensional
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matrix of embeddings.
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Arguments:
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words: A list of words to be embedded
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verbose: Controls the verbosity of the process
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Returns:
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Word embeddings with shape (n, m) with `n` words
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that each have an embeddings size of `m`
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"""
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return self.word_embedding_model.embed(words, verbose)
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def embed_documents(self, document: List[str], verbose: bool = False) -> np.ndarray:
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"""Embed a list of n words into an n-dimensional
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matrix of embeddings.
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Arguments:
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document: A list of documents to be embedded
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verbose: Controls the verbosity of the process
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Returns:
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Document embeddings with shape (n, m) with `n` documents
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that each have an embeddings size of `m`
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"""
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return self.embedding_model.embed(document, verbose)
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