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Add predict step accumulation (#7767)

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* Add eval_accumulation_step and clean distributed eval

* Add TPU test

* Add TPU stuff

* Fix arg name

* Fix Seq2SeqTrainer

* Fix total_size

* Update src/transformers/trainer_pt_utils.py

Co-authored-by: Lysandre Debut <lysandre@huggingface.co>

* Doc and add test to TPU

* Add unit test

* Adapt name

Co-authored-by: Lysandre Debut <lysandre@huggingface.co>
This commit is contained in:
Sylvain Gugger
2020-10-14 11:41:45 -04:00
committed by GitHub
parent 8feb0cc967
commit a1d1b332d0
10 changed files with 413 additions and 47 deletions
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21
tests/test_trainer_distributed.py
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@@ -13,15 +13,14 @@
# CUDA_VISIBLE_DEVICES=-1 python ./tests/test_trainer_distributed.py
#
import logging
import sys
from typing import Dict
from transformers import EvalPrediction, HfArgumentParser, TrainingArguments, is_torch_available
from transformers.utils import logging
logger = logging.getLogger(__name__)
logger = logging.get_logger(__name__)
if is_torch_available():
@@ -101,4 +100,20 @@ if __name__ == "__main__":
logger.error(p.metrics)
exit(1)
trainer.args.eval_accumulation_steps = 2
metrics = trainer.evaluate()
logger.info(metrics)
if metrics["eval_success"] is not True:
logger.error(metrics)
exit(1)
p = trainer.predict(dataset)
logger.info(p.metrics)
if p.metrics["eval_success"] is not True:
logger.error(p.metrics)
exit(1)
trainer.args.eval_accumulation_steps = None
logger.info("🔥 All distributed tests successful")