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Pass Tok2Vec settings a bit better
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12
spacy/_ml.py
12
spacy/_ml.py
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@ -406,15 +406,11 @@ def Tok2Vec(width, embed_size, **kwargs):
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pretrained_vectors = kwargs.get("pretrained_vectors", None)
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pretrained_vectors = kwargs.get("pretrained_vectors", None)
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cnn_maxout_pieces = kwargs.get("cnn_maxout_pieces", 3)
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cnn_maxout_pieces = kwargs.get("cnn_maxout_pieces", 3)
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subword_features = kwargs.get("subword_features", True)
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subword_features = kwargs.get("subword_features", True)
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char_embed = util.env_opt("char_embed", kwargs.get("char_embed", False))
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char_embed = kwargs.get("char_embed", False)
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conv_depth = kwargs.get("conv_depth", 4)
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conv_depth = kwargs.get("conv_depth", 4)
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bilstm_depth = util.env_opt("bilstm_depth", kwargs.get("bilstm_depth", 0))
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bilstm_depth = kwargs.get("bilstm_depth", 0)
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self_attn_depth = util.env_opt("self_attn_depth", kwargs.get("self_attn_depth", 0))
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self_attn_depth = kwargs.get("self_attn_depth", 0)
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conv_window = util.env_opt("conv_window", kwargs.get("cnn_window", 1))
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conv_window = kwargs.get("conv_window", 1)
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kwargs.setdefault("bilstm_depth", bilstm_depth)
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kwargs.setdefault("self_attn_depth", self_attn_depth)
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kwargs.setdefault("char_embed", char_embed)
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kwargs.setdefault("conv_window", conv_window)
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if char_embed and self_attn_depth:
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if char_embed and self_attn_depth:
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return Tok2Vec_chars_selfattention(width, embed_size, **kwargs)
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return Tok2Vec_chars_selfattention(width, embed_size, **kwargs)
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elif char_embed and bilstm_depth:
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elif char_embed and bilstm_depth:
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