tiny fix
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@ -100,7 +100,7 @@ def preprocess_dataset(
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return model_inputs
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def preprocess_packed_supervised_dataset(examples: Dict[str, List[Any]]) -> Dict[str, Any]:
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# build inputs with format `<bos> X Y <eos>` and labels with format `<ignore> ... <ignore> Y <eos>`
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# build inputs with format `<bos> X Y <eos>` and labels with format `<bos> X Y <eos>`
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# we do not mask the inputs in packed training.
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model_inputs = {"input_ids": [], "attention_mask": [], "labels": []}
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input_ids, labels = [], []
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@ -173,7 +173,7 @@ class LlamaFlashAttention2(LlamaAttention):
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state = state.reshape(bsz * num_group, group_size, self.num_heads, self.head_dim)
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if attention_mask is not None:
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logger.warning_once("Padded sequences are less efficient.")
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logger.warning_once("Padded sequences are less efficient in FlashAttention.")
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batch_size = query_states.shape[0]
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# -q_len: assumes left padding
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unpadded_q, indices_q, cu_seqlens_q, max_seqlen_q = unpad_input(query_states, attention_mask[:, -q_len:])
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