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Avoid comparison to None in Tok2Vec
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@ -227,6 +227,8 @@ def drop_layer(layer, factor=2.):
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def Tok2Vec(width, embed_size, pretrained_dims=0):
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if pretrained_dims is None:
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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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