Make vllm compatible with verl (#12824)

Co-authored-by: zhangshulai <zhangshulai@bytedance.com>

vllm/distributed/parallel_state.py

@@ -1024,13 +1024,6 @@ def initialize_model_parallel(
     backend = backend or torch.distributed.get_backend(
         get_world_group().device_group)
 
-    if (world_size
-            != tensor_model_parallel_size * pipeline_model_parallel_size):
-        raise RuntimeError(
-            f"world_size ({world_size}) is not equal to "
-            f"tensor_model_parallel_size ({tensor_model_parallel_size}) x "
-            f"pipeline_model_parallel_size ({pipeline_model_parallel_size})")
-
     # Build the tensor model-parallel groups.
     num_tensor_model_parallel_groups: int = (world_size //
                                              tensor_model_parallel_size)

vllm/executor/uniproc_executor.py

@@ -101,7 +101,7 @@ class ExecutorWithExternalLauncher(UniProcExecutor):
         # - MASTER_PORT
         distributed_init_method = "env://"
         rank = int(os.environ["RANK"])
-        local_rank = rank
+        local_rank = int(os.environ["LOCAL_RANK"])
         is_driver_worker = True
         kwargs = dict(
             vllm_config=self.vllm_config,