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Merge pull request #6123 from svlandeg/fix/frozen

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Ines Montani 2020-09-23 13:04:44 +02:00 committed by GitHub
commit af92d79e92
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2 changed files with 8 additions and 4 deletions
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6
spacy/cli/train.py
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@ -152,7 +152,8 @@ def train(
exclude=frozen_components,
)
msg.info(f"Training. Initial learn rate: {optimizer.learn_rate}")
print_row, finalize_logger = train_logger(nlp)
with nlp.select_pipes(disable=frozen_components):
print_row, finalize_logger = train_logger(nlp)
try:
progress = tqdm.tqdm(total=T_cfg["eval_frequency"], leave=False)
@ -163,7 +164,8 @@ def train(
progress.close()
print_row(info)
if is_best_checkpoint and output_path is not None:
update_meta(T_cfg, nlp, info)
with nlp.select_pipes(disable=frozen_components):
update_meta(T_cfg, nlp, info)
with nlp.use_params(optimizer.averages):
nlp.to_disk(output_path / "model-best")
progress = tqdm.tqdm(total=T_cfg["eval_frequency"], leave=False)

6
spacy/training/loggers.py
View File

@ -11,9 +11,11 @@ def console_logger():
def setup_printer(
nlp: "Language",
) -> Tuple[Callable[[Dict[str, Any]], None], Callable]:
# we assume here that only components are enabled that should be trained & logged
logged_pipes = nlp.pipe_names
score_cols = list(nlp.config["training"]["score_weights"])
score_widths = [max(len(col), 6) for col in score_cols]
loss_cols = [f"Loss {pipe}" for pipe in nlp.pipe_names]
loss_cols = [f"Loss {pipe}" for pipe in logged_pipes]
loss_widths = [max(len(col), 8) for col in loss_cols]
table_header = ["E", "#"] + loss_cols + score_cols + ["Score"]
table_header = [col.upper() for col in table_header]
@ -26,7 +28,7 @@ def console_logger():
try:
losses = [
"{0:.2f}".format(float(info["losses"][pipe_name]))
for pipe_name in nlp.pipe_names
for pipe_name in logged_pipes
]
except KeyError as e:
raise KeyError(