[shardformer] support sharded checkpoint IO for models of HybridParallelPlugin (#4506)

* add APIs

* implement save_sharded_model

* add test for hybrid checkpointio

* implement naive loading for sharded model

* implement efficient sharded model loading

* open a new file for hybrid checkpoint_io

* small fix

* fix circular importing

* fix docstring

* arrange arguments and apis

* small fix

colossalai/shardformer/layer/parallel_module.py

@@ -10,6 +10,7 @@ import torch.nn as nn
 from torch.distributed import ProcessGroup
 from torch.nn.modules.module import _EXTRA_STATE_KEY_SUFFIX, Module
 
+from colossalai.checkpoint_io.utils import gather_distributed_param
 from colossalai.tensor.d_tensor import (
     distribute_tensor,
     distribute_tensor_with_customization,
@@ -56,13 +57,7 @@ class ParallelModule(nn.Module, ABC):
         """
         for name, param in self._parameters.items():
             if param is not None:
-                param_ = param if keep_vars else param.detach()
-                if is_distributed_tensor(param_):
-                    destination[prefix + name] = to_global(param_)
-                elif is_customized_distributed_tensor(param_):
-                    destination[prefix + name] = to_global_for_customized_distributed_tensor(param_)
-                else:
-                    destination[prefix + name] = param_
+                destination[prefix + name] = gather_distributed_param(param, keep_vars=keep_vars)
 
         for name, buf in self._buffers.items():
             if buf is not None and name not in self._non_persistent_buffers_set: