[Misc] Make `download_weights_from_hf` more reliable (#23863)

Signed-off-by: Harry Mellor <19981378+hmellor@users.noreply.github.com>

vllm/model_executor/model_loader/weight_utils.py

@@ -278,33 +278,48 @@ def download_weights_from_hf(
     Returns:
         str: The path to the downloaded model weights.
     """
+    assert len(allow_patterns) > 0
     local_only = huggingface_hub.constants.HF_HUB_OFFLINE
     if not local_only:
-        # Before we download we look at that is available:
-        fs = HfFileSystem()
-        file_list = fs.ls(model_name_or_path, detail=False, revision=revision)
-
-        # depending on what is available we download different things
-        for pattern in allow_patterns:
-            matching = fnmatch.filter(file_list, pattern)
-            if len(matching) > 0:
-                allow_patterns = [pattern]
+        # Attempt to reduce allow_patterns to a single pattern
+        # so we only have to call snapshot_download once.
+        try:
+            fs = HfFileSystem()
+            file_list = fs.ls(model_name_or_path,
+                              detail=False,
+                              revision=revision)
+
+            # Use the first pattern found in the HF repo's files.
+            for pattern in allow_patterns:
+                matching = fnmatch.filter(file_list, pattern)
+                if len(matching) > 0:
+                    allow_patterns = [pattern]
                 break
+        except Exception as e:
+            logger.warning(
+                "Failed to get file list for '%s'. Trying each pattern in "
+                "allow_patterns individually until weights have been "
+                "downloaded. Error: %s", model_name_or_path, e)
 
     logger.info("Using model weights format %s", allow_patterns)
     # Use file lock to prevent multiple processes from
     # downloading the same model weights at the same time.
     with get_lock(model_name_or_path, cache_dir):
         start_time = time.perf_counter()
-        hf_folder = snapshot_download(
-            model_name_or_path,
-            allow_patterns=allow_patterns,
-            ignore_patterns=ignore_patterns,
-            cache_dir=cache_dir,
-            tqdm_class=DisabledTqdm,
-            revision=revision,
-            local_files_only=local_only,
-        )
+        for allow_pattern in allow_patterns:
+            hf_folder = snapshot_download(
+                model_name_or_path,
+                allow_patterns=allow_pattern,
+                ignore_patterns=ignore_patterns,
+                cache_dir=cache_dir,
+                tqdm_class=DisabledTqdm,
+                revision=revision,
+                local_files_only=local_only,
+            )
+            # If we have downloaded weights for this allow_pattern,
+            # we don't need to check the rest.
+            if any(Path(hf_folder).glob(allow_pattern)):
+                break
         time_taken = time.perf_counter() - start_time
         if time_taken > 0.5:
             logger.info("Time spent downloading weights for %s: %.6f seconds",