Refactor sequence length overflow handling in pretraining module

- Introduced DEFAULT_SEQUENCE_LEN_OVERFLOW_HANDLING constant in utils.py.
- Updated encode_packed_pretraining function to use this constant instead of a hardcoded value.

src/axolotl/utils/data/pretraining.py

@@ -11,6 +11,7 @@ from torch.utils.data import RandomSampler
 from transformers import PreTrainedTokenizerBase
 
 from axolotl.utils.collators import PretrainingBatchSamplerDataCollatorForSeq2Seq
+from axolotl.utils.data.utils import DEFAULT_SEQUENCE_LEN_OVERFLOW_HANDLING
 from axolotl.utils.samplers import MultipackBatchSampler, get_dataset_lengths
 from axolotl.utils.trainer import process_pretraining_datasets_for_packing
 
@@ -261,7 +262,7 @@ def encode_packed_pretraining(
         drop_attention_mask=multipack_attn,
         # pass through handling mode from config via ds_wrapper function
         handling=getattr(ds_wrapper, "cfg", {}).get(
-            "sequence_len_overflow_handling", "drop"
+            "sequence_len_overflow_handling", DEFAULT_SEQUENCE_LEN_OVERFLOW_HANDLING
         ),
     )
 

src/axolotl/utils/data/utils.py

@@ -17,6 +17,8 @@ from axolotl.utils.trainer import truncate_or_drop_long_seq
 
 LOG = logging.getLogger(__name__)
 
+DEFAULT_SEQUENCE_LEN_OVERFLOW_HANDLING = "drop"
+
 
 class RetryStrategy(Enum):
     """