[DP] Tiny fix of dp and update example (#1273)

### What this PR does / why we need it?
Add `max_num_tokens_across_dp` to AscendMetadata to fix dp

This pr fixes the bug introduced by
https://github.com/vllm-project/vllm-ascend/pull/1229, which add an arg
`max_num_tokens_across_dp` when dp_size > 1.

Signed-off-by: MengqingCao <cmq0113@163.com>

vllm_ascend/attention/attention_v1.py

@@ -119,6 +119,10 @@ class AscendMetadata:
     query_start_loc: torch.Tensor
     query_lens: torch.Tensor
     seq_lens: torch.Tensor
+
+    # max value of number of tokens across dp group
+    max_num_tokens_across_dp: int = 0
+
     # Maximum query length in the batch. None for decoding.
     max_query_len: Optional[int] = None
     # (num_tokens,). The indices of the token slots that input tokens will be
@@ -155,6 +159,7 @@ class AscendAttentionMetadataBuilder:
               num_actual_tokens,
               max_query_len,
               common_prefix_len,
+              max_num_tokens_across_dp: int = 0,
               with_prefill_across_dp: bool = False):
 
         block_table = self.runner.input_batch.block_table[0].get_device_tensor(
@@ -192,6 +197,7 @@ class AscendAttentionMetadataBuilder:
             slot_mapping=slot_mapping,
             attn_mask=attn_mask,
             attn_state=attn_state,
+            max_num_tokens_across_dp=max_num_tokens_across_dp,
             with_prefill_across_dp=with_prefill_across_dp)
         return attn_metadata