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@ -105,15 +105,16 @@ def MultiHashEmbed_v1(
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width=width,
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rows=rows,
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attrs=[NORM, PREFIX, SUFFIX, SHAPE] if also_embed_subwords else [NORM],
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include_static_vectors=also_use_static_vectors
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include_static_vectors=also_use_static_vectors,
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)
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@registry.architectures.register("spacy.MultiHashEmbed.v2")
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def MultiHashEmbed(
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width: int,
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rows: int,
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attrs: Union[List[Union[str, int]], Dict[Union[str, int], float]],
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include_static_vectors: bool
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include_static_vectors: bool,
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) -> Model[List[Doc], List[Floats2d]]:
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"""Construct an embedding layer that separately embeds a number of lexical
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attributes using hash embedding, concatenates the results, and passes it
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