Avoid calling _free_fp16_param_shard() too early with PR 1159

fairscale/nn/data_parallel/fully_sharded_data_parallel.py

@@ -1733,7 +1733,7 @@ def _post_backward_hook(self, param: Parameter, *unused: Any) -> None:
             # Free full params.
             self._free_full_params([param])
 
-        if self.mixed_precision:
+        if self.mixed_precision and (self._require_backward_grad_sync or self.reshard_after_forward):
             # This is a no-op if reshard_after_forward is True, since we already
             # free the param shard when rebuilding the full params in the
             # pre_backward_hook.
@@ -1861,7 +1861,7 @@ def _post_reduction_hook(self, param: Parameter, reduced_grad: torch.Tensor) ->
     def _post_backward_reshard_hook(self, param: Parameter, *unused: Any) -> None:
         if self._should_free_in_backward():
             self._free_full_params([param])
-        if self.mixed_precision:
+        if self.mixed_precision and (self._require_backward_grad_sync or self.reshard_after_forward):
             self._free_fp16_param_shard([param])
         self._use_fp32_param_shard([param])
 
@@ -1937,7 +1937,7 @@ def _finalize_parameters(fsdp_module: FullyShardedDataParallel) -> None:
                     # For the 1st layer, if the forward inputs did not require
                     # gradient, then we cannot run a reshard hook for it, and
                     # we instead free here.
-                    if p._full_param_padded.untyped_storage().size() > 0:
+                    if p._is_sharded and p._full_param_padded.untyped_storage().size() > 0:
                         fsdp_module._post_backward_reshard_hook(p)
                     continue