[CI/Build] Consolidate model loader tests and requirements (#25765)

Signed-off-by: DarkLight1337 <tlleungac@connect.ust.hk>

vllm/model_executor/model_loader/weight_utils.py

@@ -639,6 +639,19 @@ def runai_safetensors_weights_iterator(
         yield from tensor_iter
 
 
+def _init_loader(
+    pg: torch.distributed.ProcessGroup,
+    device: torch.device,
+    f_list: list[str],
+    *,
+    nogds: bool = False,
+):
+    loader = SafeTensorsFileLoader(pg, device, nogds=nogds)
+    rank_file_map = {i: [f] for i, f in enumerate(f_list)}
+    loader.add_filenames(rank_file_map)
+    return loader
+
+
 def fastsafetensors_weights_iterator(
     hf_weights_files: list[str],
     use_tqdm_on_load: bool,
@@ -656,17 +669,31 @@ def fastsafetensors_weights_iterator(
         for i in range(0, len(hf_weights_files), pg.size())
     ]
 
+    nogds = False
+
     for f_list in tqdm(
             weight_files_sub_lists,
             desc="Loading safetensors using Fastsafetensor loader",
             disable=not enable_tqdm(use_tqdm_on_load),
             bar_format=_BAR_FORMAT,
     ):
-        loader = SafeTensorsFileLoader(pg, device)
-        rank_file_map = {i: [f] for i, f in enumerate(f_list)}
-        loader.add_filenames(rank_file_map)
+        loader = _init_loader(pg, device, f_list, nogds=nogds)
         try:
-            fb = loader.copy_files_to_device()
+            try:
+                fb = loader.copy_files_to_device()
+            except RuntimeError as e:
+                if "gds" not in str(e):
+                    raise
+
+                loader.close()
+                nogds = True
+                logger.warning_once(
+                    "GDS not enabled, setting `nogds=True`.\n"
+                    "For more information, see: https://github.com/foundation-model-stack/fastsafetensors?tab=readme-ov-file#basic-api-usages"
+                )
+                loader = _init_loader(pg, device, f_list, nogds=nogds)
+                fb = loader.copy_files_to_device()
+
             try:
                 keys = list(fb.key_to_rank_lidx.keys())
                 for k in keys: