explosion/spaCy
1
1
Fork 0
mirror of https://github.com/explosion/spaCy.git synced 2025-04-27 04:13:41 +03:00
Code Issues Packages Projects Releases Wiki Activity

Make training.loop return nlp object and path (#6520)

Browse Source
This commit is contained in:
Ines Montani 2020-12-08 07:55:55 +01:00 committed by GitHub
parent 2c27093c5f
commit 6cfa66ed1c
No known key found for this signature in database
GPG Key ID: 4AEE18F83AFDEB23
1 changed files with 8 additions and 7 deletions
Show Stats Download Patch File Download Diff File Expand all files Collapse all files

15
spacy/training/loop.py
View File

@ -28,7 +28,7 @@ def train(
use_gpu: int = -1, use_gpu: int = -1,
stdout: IO = sys.stdout, stdout: IO = sys.stdout,
stderr: IO = sys.stderr, stderr: IO = sys.stderr,
) -> None: ) -> Tuple["Language", Optional[Path]]:
"""Train a pipeline. """Train a pipeline.
nlp (Language): The initialized nlp object with the full config. nlp (Language): The initialized nlp object with the full config.
@ -40,7 +40,7 @@ def train(
stderr (file): A second file-like object to write output messages. To disable stderr (file): A second file-like object to write output messages. To disable
printing, set to io.StringIO. printing, set to io.StringIO.
RETURNS (Path / None): The path to the final exported model. RETURNS (tuple): The final nlp object and the path to the exported model.
""" """
# We use no_print here so we can respect the stdout/stderr options. # We use no_print here so we can respect the stdout/stderr options.
msg = Printer(no_print=True) msg = Printer(no_print=True)
@ -105,17 +105,18 @@ def train(
raise e raise e
finally: finally:
finalize_logger() finalize_logger()
if optimizer.averages:
nlp.use_params(optimizer.averages)
if output_path is not None: if output_path is not None:
final_model_path = output_path / DIR_MODEL_LAST final_model_path = output_path / DIR_MODEL_LAST
if optimizer.averages: nlp.to_disk(final_model_path)
with nlp.use_params(optimizer.averages):
nlp.to_disk(final_model_path)
else:
nlp.to_disk(final_model_path)
# This will only run if we don't hit an error # This will only run if we don't hit an error
stdout.write( stdout.write(
msg.good("Saved pipeline to output directory", final_model_path) + "\n" msg.good("Saved pipeline to output directory", final_model_path) + "\n"
) )
return (nlp, final_model_path)
else:
return (nlp, None)
def train_while_improving( def train_while_improving(