Repository: huggingface/transformers
Pull request: Fix grad accum arbitrary value

# What does this PR do?

The test for the "brokenness" of gradient accumulation loss uses an arbitrary value to check if not passing "num_items_in_batch" results in a loss different from normal training loss. This value got smaller after I made some changes to the test (mostly trying to make it more understandable).
See changes in https://github.com/huggingface/transformers/pull/36424/files#diff-ac9b69e204d41f7ddf23e8bd5b53a2a0ffa64c4784101abeef3b5d4c14342656R823-R905

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Changed files:
filename: src/transformers/utils/import_utils.py
patch: @@ -813,7 +813,7 @@ def is_torch_hpu_available():
 
         def patched_masked_fill_(self, mask, value):
             if self.dtype == torch.int64:
-                logger.warning(
+                logger.warning_once(
                     "In-place tensor.masked_fill_(mask, value) is not supported for int64 tensors on Gaudi1. "
                     "This operation will be performed out-of-place using tensor[mask] = value."
                 )

filename: tests/trainer/test_trainer.py
patch: @@ -896,9 +896,8 @@ def tokenize_function(examples):
 
         # all diff truth should be quite close
         self.assertLess(max(diff_truth), 0.01, f"Difference {max(diff_truth)} is not within 0.01")
-
-        # max diff broken should be very off
-        self.assertGreater(max(diff_broken), 1.3, f"Difference {max(diff_broken)} is not greater than 1.3")
+        # max diff broken should be very off ("very off" is arbitrary, but as long as it's bigger than 0.1, it's fine)
+        self.assertGreater(max(diff_broken), 0.7, f"Difference {max(diff_broken)} is not greater than 0.7")
 
         loss_base = sum(base_loss_callback.losses)
         loss_broken = sum(broken_loss_callback.losses)