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Disable report callbacks for certain training tests (#38088)

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* Disable report callbacks for certain training tests

* Disable report callbacks for test_auto_batch_size_finder
This commit is contained in:
ivarflakstad
2025-05-13 14:49:55 +02:00
committed by GitHub
parent ab65ba47ad
commit e27d230ddd
1 changed files with 5 additions and 3 deletions
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8
tests/trainer/test_trainer.py
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@@ -1368,6 +1368,7 @@ class TrainerIntegrationTest(TestCasePlus, TrainerIntegrationCommon):
per_device_train_batch_size=2, per_device_train_batch_size=2,
torch_compile=True, torch_compile=True,
max_steps=1, # compile happens on the first step max_steps=1, # compile happens on the first step
report_to="none",
) )
trainer = Trainer(model=tiny_llama, args=args, train_dataset=train_dataset) # noqa trainer = Trainer(model=tiny_llama, args=args, train_dataset=train_dataset) # noqa
trainer.train() trainer.train()
@@ -3300,6 +3301,7 @@ class TrainerIntegrationTest(TestCasePlus, TrainerIntegrationCommon):
--num_train_epochs 1 --num_train_epochs 1
--output_dir {tmpdir} --output_dir {tmpdir}
--auto_find_batch_size 0 --auto_find_batch_size 0
--report_to none
""".split() """.split()
with self.assertRaises(RuntimeError): with self.assertRaises(RuntimeError):
with patch.object(sys, "argv", testargs): with patch.object(sys, "argv", testargs):
@@ -4560,7 +4562,7 @@ class TrainerIntegrationTest(TestCasePlus, TrainerIntegrationCommon):
config = RegressionModelConfig(a=1.5, b=2.5) config = RegressionModelConfig(a=1.5, b=2.5)
trainer = Trainer( trainer = Trainer(
model=RegressionPreTrainedModel(config), model=RegressionPreTrainedModel(config),
args=TrainingArguments(output_dir=tmp_dir), args=TrainingArguments(output_dir=tmp_dir, report_to="none"),
processing_class=image_processor, processing_class=image_processor,
) )
trainer.save_model() trainer.save_model()
@@ -4576,7 +4578,7 @@ class TrainerIntegrationTest(TestCasePlus, TrainerIntegrationCommon):
config = RegressionModelConfig(a=1.5, b=2.5) config = RegressionModelConfig(a=1.5, b=2.5)
trainer = Trainer( trainer = Trainer(
model=RegressionPreTrainedModel(config), model=RegressionPreTrainedModel(config),
args=TrainingArguments(output_dir=tmp_dir), args=TrainingArguments(output_dir=tmp_dir, report_to="none"),
processing_class=feature_extractor, processing_class=feature_extractor,
) )
trainer.save_model() trainer.save_model()
@@ -4596,7 +4598,7 @@ class TrainerIntegrationTest(TestCasePlus, TrainerIntegrationCommon):
config = RegressionModelConfig(a=1.5, b=2.5) config = RegressionModelConfig(a=1.5, b=2.5)
trainer = Trainer( trainer = Trainer(
model=RegressionPreTrainedModel(config), model=RegressionPreTrainedModel(config),
args=TrainingArguments(output_dir=tmp_dir), args=TrainingArguments(output_dir=tmp_dir, report_to="none"),
processing_class=processor, processing_class=processor,
) )
trainer.save_model() trainer.save_model()