修正了loss为nan的错误

model/model.py

@@ -94,7 +94,7 @@ class Attention(nn.Module):
                 x: torch.Tensor,
                 pos_cis: torch.Tensor,
                 past_key_value: Optional[Tuple[torch.Tensor, torch.Tensor]] = None,
-                use_cache=False,
+                use_cache=True,
                 db_value=None):
         bsz, seq_len, _ = x.shape #bsz: 批量大小, seq_len: 序列长度, _: 隐藏维度
         xq, xk, xv = self.wq(x), self.wk(x), self.wv(x) #将输入张量x分别通过线性层wq, wk, wv进行变换，得到查询、键和值。
@@ -373,7 +373,7 @@ class MiniMindBlock(nn.Module):
         #     self.product_key_topk = min(16, self.num_keys)  # 确保不超过num_keys
         #     self.num_experts_per_head_topk = 1  # 最终每个头选取的专家数
 
-    def forward(self, x, db_value, pos_cis, past_key_value=None, use_cache=False):
+    def forward(self, x, db_value, pos_cis, past_key_value=None, use_cache=True):
         # import pdb;pdb.set_trace()
         # db_value = None