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当打开sequence packing做sft时，若一个pack中的子序列长度恰好为上下文窗口长度等边界情况时，原代码会在训练中遇到该问题时报错：
[rank1]: tokens, labels, loss_mask, attention_mask, position_ids, num_seqs, packed_seq_params = get_batch(data_iterator)
[rank1]: ^^^^^^^^^^^^^^^^^^^^^^^^
[rank1]: File "/volume/data/lzh/Pai-Megatron-Patch-main/megatron_patch/template/helper.py", line 103, in get_batch
[rank1]: max_seqlen = torch.max(seqlens.max(), position_ids.max() + 1)
[rank1]: ^^^^^^^^^^^^^
[rank1]: RuntimeError: max(): Expected reduction dim to be specified for input.numel() == 0. Specify the reduction dim with the 'dim' argument.
修改后的代码解决了边界问题且为更健壮的实现。