Avoid comparison to None in Tok2Vec
@@ -227,6 +227,8 @@ def drop_layer(layer, factor=2.):
def Tok2Vec(width, embed_size, pretrained_dims=0):
+ if pretrained_dims is None:
+ pretrained_dims = 0
cols = [ID, NORM, PREFIX, SUFFIX, SHAPE, ORTH]
with Model.define_operators({'>>': chain, '|': concatenate, '**': clone, '+': add}):
norm = HashEmbed(width, embed_size, column=cols.index(NORM), name='embed_norm')
