[shardformer] Fix serialization error with Tensor Parallel state savi…

…ng (#5018)

* Fix serialization error with Tensor Parallel state saving

* Refactor state_dict CPU transfer using tree_map

colossalai/checkpoint_io/utils.py

@@ -11,6 +11,7 @@
 import torch.nn as nn
 from packaging.version import Version
 from torch.optim import Optimizer
+from torch.utils._pytree import tree_map
 
 from colossalai.tensor.d_tensor import (
     is_customized_distributed_tensor,
@@ -293,7 +294,6 @@ def shard_optimizer_checkpoint(state_dict: dict, max_shard_size: int = 1024) ->
 # Helper functions for saving state dict
 # ======================================
 
-
 def save_state_dict(state_dict: dict, checkpoint_file_path: str, use_safetensors: bool) -> None:
     """
     Save state dict to checkpoint.
@@ -303,16 +303,19 @@ def save_state_dict(state_dict: dict, checkpoint_file_path: str, use_safetensors
         checkpoint_file_path (str): path to the checkpoint file.
         use_safetensors (bool): whether to use safetensors to save the checkpoint.
     """
+    # Move all tensors in the state_dict to CPU before saving to avoid serialization issues
+    state_dict_cpu = tree_map(lambda x: x.cpu() if torch.is_tensor(x) else x, state_dict)
+
     if use_safetensors:
         assert is_safetensors_available(), "safetensors is not available."
         assert checkpoint_file_path.endswith(
             ".safetensors"
         ), "safetensors only supports .safetensors suffix for checkpoint file."
         from safetensors.torch import save_file as safe_save_file
 
-        safe_save_file(state_dict, checkpoint_file_path, metadata={"format": "pt"})
+        safe_save_file(state_dict_cpu, checkpoint_file_path, metadata={"format": "pt"})
     else:
-        torch.save(state_dict, checkpoint_file_path)
+        torch.save(state_dict_cpu, checkpoint_file_path)
 
 
 def save_param_groups(state_dict: dict, group_file_path: str) -> None: