[Loader] Add values natural order check to layers grouped validation

fastdeploy/model_executor/load_weight_utils.py

@@ -40,7 +40,7 @@
 from tqdm import tqdm
 
 from fastdeploy import envs
-from fastdeploy.config import FDConfig, LoadConfig
+from fastdeploy.config import FDConfig
 from fastdeploy.model_executor.layers.linear import KVBatchLinear
 from fastdeploy.model_executor.utils import multi_switch_config_context
 
@@ -72,6 +72,11 @@ def layers_are_grouped(keys):
     return True
 
 
+def values_are_naturally_ordered(values):
+    """Check if values are sorted in natural order."""
+    return list(values) == sorted(values, key=natural_key)
+
+
 def pdparams_weight_iterator(paddle_file_list: list[str]):
     for pdparams_file in tqdm(
         paddle_file_list,
@@ -117,18 +122,20 @@ def get_model_path(fd_config: FDConfig):
     return model_path
 
 
-def get_weight_iterator(model_path: str, load_config: Optional[LoadConfig] = None):
+def get_weight_iterator(model_path: str, fd_config: Optional[FDConfig] = None):
     files_list, ordered_weight_map, use_safetensors, is_layers_are_grouped = get_all_weights_file(model_path)
     if use_safetensors:
+        load_config = fd_config.load_config if fd_config else None
         extra_config = load_config.model_loader_extra_config if load_config else None
+        parallel_config = fd_config.parallel_config if fd_config else None
         if extra_config is not None and extra_config.get("enable_multithread_load", False):
             weights_iterator = multi_thread_safetensors_weights_iterator(
                 files_list,
                 max_workers=extra_config.get("num_threads", DEFAULT_NUM_THREADS),
                 disable_mmap=extra_config.get("disable_mmap", False),
             )
         else:
-            if is_layers_are_grouped:
+            if is_layers_are_grouped or (parallel_config is not None and parallel_config.tensor_parallel_size == 1):
                 weights_iterator = safetensors_weights_iterator(files_list)
             else:
                 weights_iterator = safetensors_weights_iterator_ordered(ordered_weight_map)
@@ -532,7 +539,10 @@ def get_all_weights_file(model_path: str):
             with index_file.open("r") as f:
                 weight_map = json.load(f)["weight_map"]
             keys = list(weight_map.keys())
-            is_layers_are_grouped = layers_are_grouped(keys)
+            values = list(weight_map.values())
+            is_keys_orders = layers_are_grouped(keys)
+            is_values_naturally_ordered = values_are_naturally_ordered(values)
+            is_layers_are_grouped = is_keys_orders and is_values_naturally_ordered
             ordered_weight_map = {
                 key: str(model_path / weight_map[key]) for key in sorted(weight_map.keys(), key=natural_key)
             }

fastdeploy/model_executor/model_loader/default_loader_v1.py

@@ -57,7 +57,7 @@ def clean_memory_fragments(self) -> None:
     @measure_time()
     def load_weights(self, model, fd_config: FDConfig, enable_cache: bool = False) -> None:
         model_path = get_model_path(fd_config)
-        weights_iterator = get_weight_iterator(model_path, fd_config.load_config)
+        weights_iterator = get_weight_iterator(model_path, fd_config)
         if enable_cache:
             load_weights_from_cache(model, weights_iterator)
         else: