[DLLM] Implement initial dynamic batching for diffusion LLM (#14883)

python/sglang/srt/managers/utils.py

@@ -2,7 +2,7 @@ from __future__ import annotations
 
 import dataclasses
 import logging
-from typing import TYPE_CHECKING, List, Optional
+from typing import TYPE_CHECKING, List, Optional, Union
 
 import torch
 
@@ -24,7 +24,7 @@ logger = logging.getLogger(__name__)
 class GenerationBatchResult:
     logits_output: Optional[LogitsProcessorOutput] = None
     pp_hidden_states_proxy_tensors: Optional[PPProxyTensors] = None
-    next_token_ids: Optional[torch.Tensor] = None
+    next_token_ids: Optional[Union[torch.Tensor, List[torch.Tensor]]] = None
     num_accepted_tokens: int = 0
     accept_length_per_req_cpu: Optional[List[int]] = None
     can_run_cuda_graph: bool = False