[TPU] Doc, fix xla_spawn.py, only preprocess dataset once (#4223)

* [TPU] Doc, fix xla_spawn.py, only preprocess dataset once

* Update examples/README.md

* [xla_spawn] Add `_mp_fn` to other Trainer scripts

* [TPU] Fix: eval dataloader was None
This commit is contained in:
Julien Chaumond
2020-05-08 14:10:05 -04:00
committed by GitHub
parent 274d850d34
commit 7b75aa9fa5
10 changed files with 88 additions and 47 deletions

View File

@@ -134,16 +134,8 @@ def main():
)
# Get datasets
train_dataset = (
GlueDataset(data_args, tokenizer=tokenizer, local_rank=training_args.local_rank)
if training_args.do_train
else None
)
eval_dataset = (
GlueDataset(data_args, tokenizer=tokenizer, local_rank=training_args.local_rank, evaluate=True)
if training_args.do_eval
else None
)
train_dataset = GlueDataset(data_args, tokenizer=tokenizer) if training_args.do_train else None
eval_dataset = GlueDataset(data_args, tokenizer=tokenizer, evaluate=True) if training_args.do_eval else None
def compute_metrics(p: EvalPrediction) -> Dict:
if output_mode == "classification":
@@ -181,9 +173,7 @@ def main():
eval_datasets = [eval_dataset]
if data_args.task_name == "mnli":
mnli_mm_data_args = dataclasses.replace(data_args, task_name="mnli-mm")
eval_datasets.append(
GlueDataset(mnli_mm_data_args, tokenizer=tokenizer, local_rank=training_args.local_rank, evaluate=True)
)
eval_datasets.append(GlueDataset(mnli_mm_data_args, tokenizer=tokenizer, evaluate=True))
for eval_dataset in eval_datasets:
result = trainer.evaluate(eval_dataset=eval_dataset)