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Remove unused 'preprocess' argument in Tok2Vec'
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039d609362
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@ -226,7 +226,7 @@ def drop_layer(layer, factor=2.):
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return model
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def Tok2Vec(width, embed_size, preprocess=True, pretrained_dims=0):
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def Tok2Vec(width, embed_size, pretrained_dims=0):
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cols = [ID, NORM, PREFIX, SUFFIX, SHAPE, ORTH]
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with Model.define_operators({'>>': chain, '|': concatenate, '**': clone, '+': add}):
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norm = HashEmbed(width, embed_size, column=cols.index(NORM), name='embed_norm')
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@ -242,7 +242,7 @@ def Tok2Vec(width, embed_size, preprocess=True, pretrained_dims=0):
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>> LN(Maxout(width, width*4, pieces=3)), column=5)
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)
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)
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if pretrained_dims:
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if pretrained_dims >= 1:
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embed = concatenate_lists(trained_vectors, SpacyVectors)
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else:
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embed = trained_vectors
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