pad_to_worst_case_seq_len boolean, for testing memory limits (#498)

* pad_to_worst_case_seq_len boolean, for testing memory limits

* remove collator_pad_to_longest option since it does nothing

see docs: https://huggingface.co/docs/transformers/main_classes/data_collator#transformers.DataCollatorWithPadding.padding

True and "longest" mean the same thing

* rename to `pad_to_sequence_len, and ensure 64 alignment

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Co-authored-by: Aman Karmani <aman@tmm1.net>

src/axolotl/utils/trainer.py

@@ -585,10 +585,10 @@ def setup_trainer(cfg, train_dataset, eval_dataset, model, tokenizer, total_num_
         callbacks.append(SaveBetterTransformerModelCallback)
 
     data_collator_kwargs = {
-        "padding": True,
+        "padding": True,  # True/"longest" is the default
     }
-    if cfg.collator_pad_to_longest:
-        data_collator_kwargs["padding"] = "longest"
+    if cfg.pad_to_sequence_len:
+        data_collator_kwargs["pad_to_multiple_of"] = 64 * round(cfg.sequence_len / 64)
     else:
         # A100 is best at 64, while others at 8. Let's use the larger so we don't have to check
         # https://docs.nvidia.com/deeplearning/performance/dl-performance-matrix-multiplication/index.html