From 5ba970b4954e7bfe1904eb31a284e11abbf4e7ff Mon Sep 17 00:00:00 2001 From: Jeffrey Gerard Date: Thu, 12 Oct 2017 12:34:46 -0700 Subject: [PATCH] minor cleanup --- examples/training/train_ner_standalone.py | 5 +++-- 1 file changed, 3 insertions(+), 2 deletions(-) diff --git a/examples/training/train_ner_standalone.py b/examples/training/train_ner_standalone.py index 3c2c2781a..0c5094bb7 100644 --- a/examples/training/train_ner_standalone.py +++ b/examples/training/train_ner_standalone.py @@ -6,7 +6,7 @@ To achieve that, it duplicates some of spaCy's internal functionality. Specifically, in this example, we don't use spaCy's built-in Language class to wire together the Vocab, Tokenizer and EntityRecognizer. Instead, we write -our own simle Pipeline class, so that it's easier to see how the pieces +our own simple Pipeline class, so that it's easier to see how the pieces interact. Input data: @@ -149,7 +149,8 @@ def report_scores(i, loss, scores): precision = '%.2f' % scores['ents_p'] recall = '%.2f' % scores['ents_r'] f_measure = '%.2f' % scores['ents_f'] - print('Epoch %d: %d %s %s %s' % (i, int(loss), precision, recall, f_measure)) + print('Epoch %d: %d %s %s %s' % ( + i, int(loss), precision, recall, f_measure)) def read_examples(path):