[wip] - gb200 wideep/pd fp4 pipecleaning

python/sglang/srt/eplb/expert_location.py

@@ -93,7 +93,6 @@ def init_trivial(
 
         if common is None:
             return None
-
         num_physical_experts = common["num_physical_experts"]
         model_config_for_expert_location = common["model_config_for_expert_location"]
         num_layers = model_config_for_expert_location.num_layers
@@ -103,7 +102,6 @@ def init_trivial(
             torch.arange(0, num_physical_experts).repeat(num_layers, 1)
             % num_logical_experts
         )
-
         return ExpertLocationMetadata.init_by_mapping(
             server_args,
             model_config,
@@ -135,7 +133,6 @@ def init_by_mapping(
             ep_size=common["ep_size"],
             moe_ep_rank=moe_ep_rank,
         )
-
         return ExpertLocationMetadata._init_raw(
             server_args=server_args,
             ep_size=common["ep_size"],
@@ -229,7 +226,6 @@ def _init_raw(
         logical_to_all_physical_map_num_valid = torch.count_nonzero(
             logical_to_all_physical_map != -1, dim=-1
         )
-
         return ExpertLocationMetadata(
             physical_to_logical_map=physical_to_logical_map,
             physical_to_logical_map_cpu=physical_to_logical_map.cpu(),
@@ -333,7 +329,6 @@ def _compute_logical_to_all_physical_map(
             logical_to_all_physical_map[layer_id][logical_expert_id].append(
                 physical_expert_id
             )
-
     # Replace by the physical expert on local GPU or node if possible
     if moe_ep_rank is not None:
         num_gpus_per_node = server_args.ep_size // server_args.nnodes