free param.grad

colossalai/zero/sharded_model/sharded_model_v2.py

 import functools
-from ast import Try
+from asyncio.log import logger
 from collections import OrderedDict
 from typing import Any, Optional
 
@@ -21,7 +21,7 @@ from colossalai.zero.sharded_param import ShardedParamV2
 from torch.distributed import ProcessGroup
 from torch.nn.parameter import Parameter
 
-from ._zero3_utils import (cast_float_arguments, cast_tensor_to_fp16, cast_tensor_to_fp32, chunk_and_pad,
+from ._zero3_utils import (cast_float_arguments, cast_tensor_to_fp16, cast_tensor_to_fp32, chunk_and_pad, free_storage,
                            get_gradient_predivide_factor)
 
 
@@ -218,6 +218,9 @@ class ShardedModelV2(nn.Module):
             else:
                 self._reduce_scatter_callback(param, new_grad)
             orig_grad_data.record_stream(self.comm_stream)
+        empty_grad = torch.empty_like(grad)
+        free_storage(empty_grad)
+        return empty_grad
 
     def _reduce_scatter_callback(self, param: Parameter, reduced_grad: torch.Tensor) -> None:
         if self.gradient_postdivide_factor > 1: