[checkpointio] fix hybrid plugin model save

colossalai/checkpoint_io/hybrid_parallel_checkpoint_io.py

@@ -21,7 +21,7 @@
     to_padded_tensor,
     to_unpadded_tensor,
 )
-from colossalai.utils import get_current_device
+from colossalai.utils import get_current_device, get_non_persistent_buffers_set
 
 from .general_checkpoint_io import GeneralCheckpointIO
 from .index_file import CheckpointIndexFile
@@ -105,8 +105,9 @@ def _model_sharder(
                 yield block, block_size
 
         # Save buffers.
+        non_persist_buffers_set = get_non_persistent_buffers_set(model)
         for name, buf in model.named_buffers():
-            if buf is not None and name not in model._non_persistent_buffers_set:
+            if buf is not None and name not in non_persist_buffers_set:
                 buffer = buf if keep_vars else buf.detach()
                 block, block_size = state_dict_sharder.append_param(prefix + name, buffer)
                 if block is not None:
@@ -352,9 +353,7 @@ def _load(name: str):
             _load(name)
 
         # Load buffers.
-        non_persistent_buffers = set()
-        for n, m in model.named_modules():
-            non_persistent_buffers |= set(".".join((n, b)) for b in m._non_persistent_buffers_set)
+        non_persistent_buffers = get_non_persistent_buffers_set(model)
         for name, buf in model.named_buffers():
             if buf is not None and name not in non_persistent_buffers:
                 _load(name)

colossalai/utils/__init__.py

@@ -5,6 +5,7 @@
     ensure_path_exists,
     free_storage,
     get_current_device,
+    get_non_persistent_buffers_set,
     is_ddp_ignored,
     set_seed,
 )
@@ -25,4 +26,5 @@
     "set_seed",
     "get_current_device",
     "is_ddp_ignored",
+    "get_non_persistent_buffers_set",
 ]

colossalai/utils/common.py

@@ -5,10 +5,11 @@
 import random
 from contextlib import contextmanager
 from pathlib import Path
-from typing import Callable
+from typing import Callable, Optional, Set
 
 import numpy as np
 import torch
+import torch.nn as nn
 
 from colossalai.accelerator import get_accelerator
 
@@ -76,3 +77,34 @@ def set_seed(seed):
     random.seed(seed)
     np.random.seed(seed)
     torch.manual_seed(seed)
+
+
+def get_non_persistent_buffers_set(
+    module, memo: Optional[Set[nn.Module]] = None, prefix: str = "", remove_duplicate: bool = True
+):
+    r"""
+    Args:
+        memo: a memo to store the set of modules already added to the result
+        prefix: a prefix that will be added to the name of the module
+        remove_duplicate: whether to remove the duplicated module instances in the result
+            or not
+    """
+
+    if memo is None:
+        memo = set()
+    self_non_persistent_set = set()
+    if module not in memo:
+        if remove_duplicate:
+            memo.add(module)
+        self_non_persistent_set = set(
+            map(lambda key: prefix + ("." if prefix else "") + key, module._non_persistent_buffers_set)
+        )
+        for name, sub_module in module._modules.items():
+            if sub_module is None:
+                continue
+            submodule_prefix = prefix + ("." if prefix else "") + name
+            child_non_persistent_set = get_non_persistent_buffers_set(
+                sub_module, memo, submodule_prefix, remove_duplicate
+            )
+            self_non_persistent_set = set.union(self_non_persistent_set, child_non_persistent_set)
+    return self_non_persistent_set

colossalai/zero/gemini/gemini_ddp.py

@@ -35,7 +35,7 @@
     to_unpadded_tensor,
 )
 from colossalai.tensor.param_op_hook import ColoParamOpHookManager
-from colossalai.utils import _cast_float, free_storage, is_ddp_ignored
+from colossalai.utils import _cast_float, free_storage, get_non_persistent_buffers_set, is_ddp_ignored
 
 from .chunk import Chunk, ChunkManager, TensorState, init_chunk_manager
 from .gemini_hook import GeminiZeROHook
@@ -187,7 +187,7 @@ def __init__(
             pin_memory=pin_memory,
         )
         super().__init__(module)
-        self._non_persistent_buffers_set = self._get_non_persistent_buffers_set(module)
+        self._non_persistent_buffers_set = get_non_persistent_buffers_set(module)
         self._cast_buffers()
 
         # register grad hook
@@ -257,36 +257,6 @@ def set_params_to_ignore(params_to_ignore: Iterable[torch.Tensor]) -> None:
         for p in params_to_ignore:
             p._ddp_to_ignore = True
 
-    def _get_non_persistent_buffers_set(
-        self, module, memo: Optional[Set[nn.Module]] = None, prefix: str = "", remove_duplicate: bool = True
-    ):
-        r"""
-        Args:
-            memo: a memo to store the set of modules already added to the result
-            prefix: a prefix that will be added to the name of the module
-            remove_duplicate: whether to remove the duplicated module instances in the result
-                or not
-        """
-
-        if memo is None:
-            memo = set()
-        self_non_persistent_set = set()
-        if module not in memo:
-            if remove_duplicate:
-                memo.add(module)
-            self_non_persistent_set = set(
-                map(lambda key: prefix + ("." if prefix else "") + key, module._non_persistent_buffers_set)
-            )
-            for name, sub_module in module._modules.items():
-                if sub_module is None:
-                    continue
-                submodule_prefix = prefix + ("." if prefix else "") + name
-                child_non_persistent_set = self._get_non_persistent_buffers_set(
-                    sub_module, memo, submodule_prefix, remove_duplicate
-                )
-                self_non_persistent_set = set.union(self_non_persistent_set, child_non_persistent_set)
-        return self_non_persistent_set
-
     def _post_forward(self):
         """This function is only triggered for inference."""
         access_list = list(self.chunk_manager.accessed_chunks)