Update intent parser example
@@ -64,7 +64,7 @@ TRAIN_DATA = [
model=("Model name. Defaults to blank 'en' model.", "option", "m", str),
output_dir=("Optional output directory", "option", "o", Path),
n_iter=("Number of training iterations", "option", "n", int))
-def main(model=None, output_dir=None, n_iter=100):
+def main(model=None, output_dir=None, n_iter=5):
"""Load the model, set up the pipeline and train the parser."""
if model is not None:
nlp = spacy.load(model) # load existing spaCy model
@@ -73,20 +73,19 @@ def main(model=None, output_dir=None, n_iter=100):
nlp = spacy.blank('en') # create blank Language class
print("Created blank 'en' model")
- # add the parser to the pipeline if it doesn't exist
- # nlp.create_pipe works for built-ins that are registered with spaCy
- if 'parser' not in nlp.pipe_names:
+ # We'll use the built-in dependency parser
+ # class, but we want to create a fresh instance, and give it a different
+ # name.
+ if 'parser' in nlp.pipe_names:
+ nlp.remove_pipe('parser')
parser = nlp.create_pipe('parser')
- nlp.add_pipe(parser, first=True)
- # otherwise, get it, so we can add labels to it
- else:
- parser = nlp.get_pipe('parser')
+ nlp.add_pipe(parser, name='intent-parser', first=True)
for text, annotations in TRAIN_DATA:
for dep in annotations.get('deps', []):
parser.add_label(dep)
- other_pipes = [pipe for pipe in nlp.pipe_names if pipe != 'parser']
+ other_pipes = [pipe for pipe in nlp.pipe_names if pipe != 'intent-parser']
with nlp.disable_pipes(*other_pipes): # only train parser
optimizer = nlp.begin_training()
for itn in range(n_iter):
