[Feat]Make full graph mode compalible with MTP (#3276)

### What this PR does / why we need it?
Make the Full Graph mode can run with MTP.

### Does this PR introduce _any_ user-facing change?

### How was this patch tested?

- vLLM version: v0.11.0rc3
- vLLM main: https://github.com/vllm-project/vllm/commit/v0.11.0

Signed-off-by: anon189Ty <Stari_Falcon@outlook.com>

vllm_ascend/compilation/acl_graph.py

@@ -245,7 +245,8 @@ def update_attn_params(update_stream, forward_context, runtime_shape):
             event.record(update_stream)
 
 
-def update_mla_attn_params(update_stream, forward_context, runtime_shape):
+def update_mla_attn_params(update_stream, forward_context, runtime_shape,
+                           speculative_config):
     graph_params = get_graph_params()
     # FIXME: Behold! We are using a temporary hack here to update the args
     # for each layer's attention op in the graph.
@@ -260,9 +261,19 @@ def update_mla_attn_params(update_stream, forward_context, runtime_shape):
          seq_lens_list, actual_seq_lengths, workspace, attn_output,
          softmax_lse) = param
         seq_lens_list = forward_context.attn_metadata[key].decode.seq_lens_list
-        seq_lens_list = seq_lens_list + [0] * (runtime_shape -
-                                               len(seq_lens_list))
-
+        if speculative_config and speculative_config.method == "deepseek_mtp":
+            actual_seq_lengths = forward_context.attn_metadata[
+                key].decode.actual_seq_lengths_q
+            spec_multiple = speculative_config.num_speculative_tokens + 1
+            seq_lens_list = seq_lens_list + [0] * (
+                runtime_shape // spec_multiple - len(seq_lens_list))
+            actual_seq_lengths = [
+                spec_multiple * (i + 1)
+                for i in range(runtime_shape // spec_multiple)
+            ]
+        else:
+            seq_lens_list = seq_lens_list + [0] * (runtime_shape -
+                                                   len(seq_lens_list))
         with torch.npu.stream(update_stream):
             torch.npu.graph_task_update_begin(update_stream, handle)