code: def _check_apply(self, fsdp):
      # Assert linear weights are not all 1.0
      self.check_weights(
          fsdp,
          lambda param: torch.empty_like(param).fill_(1.0),
          self.assertNotEqual,
      )
  
      fsdp.apply(self._init_linear_weights)
  
      # Ensure all weights are 1.0
      self.check_weights(
          fsdp,
          lambda param: torch.empty_like(param).fill_(1.0),
          self.assertEqual,
      )
  
file_path: pytorch/test/distributed/fsdp/test_fsdp_apply.py
imports: import sys
  import torch
  import torch.distributed
  import torch.nn
  from torch.distributed.fsdp import FullyShardedDataParallel
  from torch.testing._internal.common_distributed import skip_if_lt_x_gpu
  from torch.testing._internal.common_fsdp import CUDAInitMode, FSDPInitMode, FSDPTest, NestedWrappedModule, TransformerWithSharedParams
  from torch.testing._internal.common_utils import run_tests, TEST_WITH_DEV_DBG_ASAN
label_desc: Use image node_id 4 for calling the TestApply obj's underlying member method code with example usage: obj._check_apply(fsdp) without return types