Conditionally import HiCacheHF3FS (#8598)

Co-authored-by: Zhiqiang Xie <xiezhq@stanford.edu>

python/sglang/srt/managers/cache_controller.py

@@ -25,12 +25,6 @@ if TYPE_CHECKING:
     from sglang.srt.mem_cache.allocator import BaseTokenToKVPoolAllocator
     from sglang.srt.mem_cache.memory_pool_host import HostKVCache
 
-from sglang.srt.mem_cache.hicache_storage import HiCacheFile, get_hash_str
-from sglang.srt.mem_cache.mooncake_store.mooncake_store import (
-    MooncakeStore,
-    get_hash_str_mooncake,
-)
-from sglang.srt.mem_cache.storage.hf3fs.storage_hf3fs import HiCacheHF3FS
 
 logger = logging.getLogger(__name__)
 
@@ -251,16 +245,7 @@ class HiCacheController:
         self.enable_storage = False
         # todo: move backend initialization to storage backend module
         if storage_backend is not None:
-            # create a new communication group for synchronizing storage operations across TP workers
-            self.tp_world_size = torch.distributed.get_world_size(group=tp_group)
-            if self.tp_world_size > 1:
-                group_ranks = torch.distributed.get_process_group_ranks(tp_group)
-                self.prefetch_tp_group = torch.distributed.new_group(
-                    group_ranks, backend="gloo"
-                )
-                self.backup_tp_group = torch.distributed.new_group(
-                    group_ranks, backend="gloo"
-                )
+            from sglang.srt.mem_cache.hicache_storage import HiCacheFile, get_hash_str
 
             if storage_backend == "file":
                 self.storage_backend = HiCacheFile()
@@ -271,11 +256,19 @@ class HiCacheController:
                 self.storage_backend = HiCacheNixl()
                 self.get_hash_str = get_hash_str
             elif storage_backend == "mooncake":
+                from sglang.srt.mem_cache.mooncake_store.mooncake_store import (
+                    MooncakeStore,
+                    get_hash_str_mooncake,
+                )
+
                 self.storage_backend = MooncakeStore()
                 self.get_hash_str = get_hash_str_mooncake
                 self.storage_backend.register_buffer(self.mem_pool_host.kv_buffer)
             elif storage_backend == "hf3fs":
                 from sglang.srt.distributed import get_tensor_model_parallel_rank
+                from sglang.srt.mem_cache.storage.hf3fs.storage_hf3fs import (
+                    HiCacheHF3FS,
+                )
 
                 rank = get_tensor_model_parallel_rank()
                 bytes_per_page = (
@@ -293,6 +286,16 @@ class HiCacheController:
             self.enable_storage = True
             # todo: threshold policy for prefetching
             self.prefetch_threshold = max(prefetch_threshold, self.page_size)
+            # create a new communication group for synchronizing storage operations across TP workers
+            self.tp_world_size = torch.distributed.get_world_size(group=tp_group)
+            if self.tp_world_size > 1:
+                group_ranks = torch.distributed.get_process_group_ranks(tp_group)
+                self.prefetch_tp_group = torch.distributed.new_group(
+                    group_ranks, backend="gloo"
+                )
+                self.backup_tp_group = torch.distributed.new_group(
+                    group_ranks, backend="gloo"
+                )
 
         self.load_cache_event = load_cache_event
         self.layer_done_counter = LayerDoneCounter(self.mem_pool_device.layer_num)