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Support bilstm_depth option in parser
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@ -58,6 +58,7 @@ cdef class Parser:
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subword_features = util.env_opt('subword_features',
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subword_features = util.env_opt('subword_features',
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cfg.get('subword_features', True))
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cfg.get('subword_features', True))
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conv_depth = util.env_opt('conv_depth', cfg.get('conv_depth', 4))
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conv_depth = util.env_opt('conv_depth', cfg.get('conv_depth', 4))
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bilstm_depth = util.env_opt('bilstm_depth', cfg.get('bilstm_depth', 0))
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if depth != 1:
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if depth != 1:
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raise ValueError(TempErrors.T004.format(value=depth))
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raise ValueError(TempErrors.T004.format(value=depth))
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parser_maxout_pieces = util.env_opt('parser_maxout_pieces',
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parser_maxout_pieces = util.env_opt('parser_maxout_pieces',
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@ -70,7 +71,8 @@ cdef class Parser:
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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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conv_depth=conv_depth,
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conv_depth=conv_depth,
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subword_features=subword_features,
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subword_features=subword_features,
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pretrained_vectors=pretrained_vectors)
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pretrained_vectors=pretrained_vectors,
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bilstm_depth=bilstm_depth)
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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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@ -87,6 +89,7 @@ cdef class Parser:
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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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'pretrained_vectors': pretrained_vectors,
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'bilstm_depth': bilstm_depth
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}
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}
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return ParserModel(tok2vec, lower, upper), cfg
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return ParserModel(tok2vec, lower, upper), cfg
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