code: def __init__(self, devices, split_sharding_idx):
      self.devices = devices
      self.split_sharding_idx = split_sharding_idx
      self.rowwise_spec = ChunkShardingSpec(dim=0, placements=devices)
      self.colwise_spec = ChunkShardingSpec(dim=1, placements=devices)
  
imports: import sys
  import copy
  import torch
  import torch.nn
  from torch.testing._internal.common_distributed import requires_nccl, skip_if_lt_x_gpu
  from torch.distributed._shard import shard_module
  from torch.distributed._shard.sharding_plan import ShardingPlan
  from torch.distributed._shard.sharder import Sharder
  from torch.distributed._shard.sharding_spec import ChunkShardingSpec
  from torch.distributed._shard.sharded_tensor import ShardedTensor
  from torch.testing._internal.common_utils import TEST_WITH_DEV_DBG_ASAN, run_tests
  from torch.testing._internal.distributed._shard.sharded_tensor import TEST_GPU_NUM, ShardedTensorTestBase, with_comms
label_desc: Use image node_id 1 to create a new CustomSharder object from inherited base classes: Sharder with example: obj = CustomSharder(devices, split_sharding_idx)