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Set pretrained_vectors in parser cfg
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@ -255,8 +255,9 @@ cdef class Parser:
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raise ValueError("Currently history size is hard-coded to 0")
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raise ValueError("Currently history size is hard-coded to 0")
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if hist_width != 0:
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if hist_width != 0:
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raise ValueError("Currently history width is hard-coded to 0")
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raise ValueError("Currently history width is hard-coded to 0")
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pretrained_vectors = cfg.get('pretrained_vectors', None)
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tok2vec = Tok2Vec(token_vector_width, embed_size,
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tok2vec = Tok2Vec(token_vector_width, embed_size,
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pretrained_vectors=cfg.get('pretrained_vectors', None))
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pretrained_vectors=pretrained_vectors)
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tok2vec = chain(tok2vec, flatten)
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tok2vec = chain(tok2vec, flatten)
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lower = PrecomputableAffine(hidden_width,
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lower = PrecomputableAffine(hidden_width,
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nF=cls.nr_feature, nI=token_vector_width,
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nF=cls.nr_feature, nI=token_vector_width,
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@ -275,6 +276,7 @@ cdef class Parser:
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'token_vector_width': token_vector_width,
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'token_vector_width': token_vector_width,
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'hidden_width': hidden_width,
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'hidden_width': hidden_width,
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'maxout_pieces': parser_maxout_pieces,
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'maxout_pieces': parser_maxout_pieces,
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'pretrained_vectors': pretrained_vectors,
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'hist_size': hist_size,
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'hist_size': hist_size,
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'hist_width': hist_width
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'hist_width': hist_width
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}
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}
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