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Update run_ner.py to fix AttributeError: Trainer object has no attribute is_world_master #40

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Update run_ner.py to fix AttributeError: Trainer object has no attribute is_world_master #40

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8 changes: 4 additions & 4 deletions named-entity-recognition/run_ner.py
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Original file line number Diff line number Diff line change
Expand Up @@ -246,7 +246,7 @@ def compute_metrics(p: EvalPrediction) -> Dict:
trainer.save_model()
# For convenience, we also re-save the tokenizer to the same directory,
# so that you can share your model easily on huggingface.co/models =)
if trainer.is_world_master():
if trainer.is_world_process_zero():
tokenizer.save_pretrained(training_args.output_dir)

# Evaluation
Expand All @@ -257,7 +257,7 @@ def compute_metrics(p: EvalPrediction) -> Dict:
result = trainer.evaluate()

output_eval_file = os.path.join(training_args.output_dir, "eval_results.txt")
if trainer.is_world_master():
if trainer.is_world_process_zero():
with open(output_eval_file, "w") as writer:
logger.info("***** Eval results *****")
for key, value in result.items():
Expand All @@ -284,7 +284,7 @@ def compute_metrics(p: EvalPrediction) -> Dict:

# Save predictions
output_test_results_file = os.path.join(training_args.output_dir, "test_results.txt")
if trainer.is_world_master():
if trainer.is_world_process_zero():
with open(output_test_results_file, "w") as writer:
logger.info("***** Test results *****")
for key, value in metrics.items():
Expand All @@ -293,7 +293,7 @@ def compute_metrics(p: EvalPrediction) -> Dict:


output_test_predictions_file = os.path.join(training_args.output_dir, "test_predictions.txt")
if trainer.is_world_master():
if trainer.is_world_process_zero():
with open(output_test_predictions_file, "w") as writer:
with open(os.path.join(data_args.data_dir, "test.txt"), "r") as f:
example_id = 0
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