fix `Trainer.train(resume_from_checkpoint=False)` is causing an exception (#12981)

* fix #12970

* Update tests/test_trainer.py
Co-authored-by: Sylvain Gugger <35901082+sgugger@users.noreply.github.com>

* Update tests/test_trainer.py
Co-authored-by: Sylvain Gugger <35901082+sgugger@users.noreply.github.com>

* Update tests/test_trainer.py
Co-authored-by: Sylvain Gugger <35901082+sgugger@users.noreply.github.com>

* remove unnecessary issue link

* fix test formatting
Co-authored-by: Sylvain Gugger <35901082+sgugger@users.noreply.github.com>

src/transformers/trainer.py

@@ -1005,6 +1005,7 @@ class Trainer:
             kwargs:
                 Additional keyword arguments used to hide deprecated arguments
         """
+        resume_from_checkpoint = None if not resume_from_checkpoint else resume_from_checkpoint
 
         # memory metrics - must set up as early as possible
         self._memory_tracker.start()

tests/test_trainer.py

@@ -827,6 +827,20 @@ class TrainerIntegrationTest(TestCasePlus, TrainerIntegrationCommon):
         self.assertAlmostEqual(a, a1, delta=1e-8)
         self.assertAlmostEqual(b, b1, delta=1e-8)
 
+    # regression for this issue: https://github.com/huggingface/transformers/issues/12970
+    def test_training_with_resume_from_checkpoint_flase(self):
+        train_dataset = RegressionDataset(length=128)
+        eval_dataset = RegressionDataset()
+
+        config = RegressionModelConfig(a=0, b=2)
+        model = RegressionRandomPreTrainedModel(config)
+
+        tmp_dir = self.get_auto_remove_tmp_dir()
+        args = RegressionTrainingArguments(tmp_dir, save_steps=5, learning_rate=0.1)
+        trainer = Trainer(model, args, train_dataset=train_dataset, eval_dataset=eval_dataset)
+
+        trainer.train(resume_from_checkpoint=False)
+
     @require_torch_up_to_2_gpus
     def test_resume_training_with_gradient_accumulation(self):
         # This test will fail for more than 2 GPUs since the batch size will get bigger and with the number of