From 8f42f8d305787cb74bf7d85ef16c9cd40b948895 Mon Sep 17 00:00:00 2001 From: Matthew Honnibal Date: Sun, 17 Sep 2017 12:30:16 -0500 Subject: [PATCH] Remove unused 'preprocess' argument in Tok2Vec' --- spacy/_ml.py | 4 ++-- 1 file changed, 2 insertions(+), 2 deletions(-) diff --git a/spacy/_ml.py b/spacy/_ml.py index 2f6a36942..2b9a98fd2 100644 --- a/spacy/_ml.py +++ b/spacy/_ml.py @@ -226,7 +226,7 @@ def drop_layer(layer, factor=2.): return model -def Tok2Vec(width, embed_size, preprocess=True, pretrained_dims=0): +def Tok2Vec(width, embed_size, 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') @@ -242,7 +242,7 @@ def Tok2Vec(width, embed_size, preprocess=True, pretrained_dims=0): >> LN(Maxout(width, width*4, pieces=3)), column=5) ) ) - if pretrained_dims: + if pretrained_dims >= 1: embed = concatenate_lists(trained_vectors, SpacyVectors) else: embed = trained_vectors