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Fix tests due to breaking change in accelerate (#39451)

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* update values

* fix
This commit is contained in:
Marc Sun
2025-07-17 14:51:50 +02:00
committed by GitHub
parent 26fed50460
commit 565dd0bad7
2 changed files with 6 additions and 6 deletions
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10
tests/trainer/test_trainer.py
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@@ -3394,7 +3394,7 @@ class TrainerIntegrationTest(TestCasePlus, TrainerIntegrationCommon):
) )
trainer = Trainer(model, args, train_dataset=train_dataset, callbacks=[MockCudaOOMCallback()]) trainer = Trainer(model, args, train_dataset=train_dataset, callbacks=[MockCudaOOMCallback()])
trainer.train() trainer.train()
self.assertEqual(trainer._train_batch_size, 8) self.assertEqual(trainer._train_batch_size, 14)
def test_auto_batch_size_with_resume_from_checkpoint(self): def test_auto_batch_size_with_resume_from_checkpoint(self):
train_dataset = RegressionDataset(length=128) train_dataset = RegressionDataset(length=128)
@@ -3414,16 +3414,16 @@ class TrainerIntegrationTest(TestCasePlus, TrainerIntegrationCommon):
) )
trainer = Trainer(model, args, train_dataset=train_dataset, callbacks=[MockCudaOOMCallback()]) trainer = Trainer(model, args, train_dataset=train_dataset, callbacks=[MockCudaOOMCallback()])
trainer.train() trainer.train()
# After `auto_find_batch_size` is ran we should now be at 8 # After `auto_find_batch_size` is ran we should now be at 16*0.9=14
self.assertEqual(trainer._train_batch_size, 8) self.assertEqual(trainer._train_batch_size, 14)
# We can then make a new Trainer # We can then make a new Trainer
trainer = Trainer(model, args, train_dataset=train_dataset) trainer = Trainer(model, args, train_dataset=train_dataset)
# Check we are at 16 to start # Check we are at 16 to start
self.assertEqual(trainer._train_batch_size, 16 * max(trainer.args.n_gpu, 1)) self.assertEqual(trainer._train_batch_size, 16 * max(trainer.args.n_gpu, 1))
trainer.train(resume_from_checkpoint=True) trainer.train(resume_from_checkpoint=True)
# We should be back to 8 again, picking up based upon the last ran Trainer # We should be back to 14 again, picking up based upon the last ran Trainer
self.assertEqual(trainer._train_batch_size, 8) self.assertEqual(trainer._train_batch_size, 14)
# regression for this issue: https://github.com/huggingface/transformers/issues/12970 # regression for this issue: https://github.com/huggingface/transformers/issues/12970
def test_training_with_resume_from_checkpoint_false(self): def test_training_with_resume_from_checkpoint_false(self):

2
tests/trainer/test_trainer_utils.py
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@@ -464,7 +464,7 @@ class TrainerUtilsTest(unittest.TestCase):
raise RuntimeError("CUDA out of memory.") raise RuntimeError("CUDA out of memory.")
mock_training_loop_function() mock_training_loop_function()
self.assertEqual(batch_sizes, [64, 32, 16]) self.assertEqual(batch_sizes, [64, 57, 51, 45, 40, 36, 32, 28, 25, 22, 19, 17, 15])
@require_accelerate @require_accelerate
def test_executable_batch_size_no_search(self): def test_executable_batch_size_no_search(self):