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Fix finite IterableDataset test on multiple GPUs (#14445)

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Sylvain Gugger 2021-11-18 10:25:06 -05:00 committed by GitHub
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commit 83ef8bcac2
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1 changed files with 5 additions and 1 deletions
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tests/test_trainer.py
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@ -1069,13 +1069,17 @@ class TrainerIntegrationTest(TestCasePlus, TrainerIntegrationCommon):
self.assertIsInstance(loader.sampler, torch.utils.data.dataloader._InfiniteConstantSampler) self.assertIsInstance(loader.sampler, torch.utils.data.dataloader._InfiniteConstantSampler)
def test_training_finite_iterable_dataset(self): def test_training_finite_iterable_dataset(self):
num_gpus = max(1, get_gpu_count())
if num_gpus > 2:
return
config = RegressionModelConfig() config = RegressionModelConfig()
model = RegressionPreTrainedModel(config) model = RegressionPreTrainedModel(config)
batch_size = 1 batch_size = 1
num_samples = 10 num_samples = 10
available_steps = num_samples // batch_size available_steps = num_samples // (batch_size * num_gpus)
data = FiniteIterableDataset(length=num_samples) data = FiniteIterableDataset(length=num_samples)
train_args = TrainingArguments( train_args = TrainingArguments(