[shardformer] fix llama error when transformers upgraded. (#5055)

* fix-llama

* Update llama.py

colossalai/shardformer/modeling/llama.py

@@ -1,5 +1,5 @@
 import warnings
-from typing import List, Optional, Tuple
+from typing import List, Optional, Tuple, Union
 
 import torch
 from torch.nn import BCEWithLogitsLoss, CrossEntropyLoss, MSELoss
@@ -13,6 +13,11 @@ from transformers.utils import logging
 
 from colossalai.pipeline.stage_manager import PipelineStageManager
 
+try:
+    from transformers.models.llama.modeling_llama import _prepare_4d_causal_attention_mask
+    LATEST_VERSION = True
+except ImportError:
+    LATEST_VERSION = False
 
 class LlamaPipelineForwards:
     """
@@ -97,9 +102,14 @@ class LlamaPipelineForwards:
             attention_mask = torch.ones(
                 (batch_size, seq_length_with_past), dtype=torch.bool, device=hidden_states.device
             )
-        attention_mask = self._prepare_decoder_attention_mask(
+        if LATEST_VERSION:
-            attention_mask, (batch_size, seq_length), hidden_states, past_key_values_length
+            attention_mask = _prepare_4d_causal_attention_mask(
-        )
+                attention_mask, (batch_size, seq_length), hidden_states, past_key_values_length
+            )
+        else:
+            attention_mask = self._prepare_decoder_attention_mask(
+                attention_mask, (batch_size, seq_length), hidden_states, past_key_values_length
+            )
 
         if self.gradient_checkpointing and self.training:
             if use_cache: