class_docstr: This dimension is a member of a decomposition of the input dim.
  
  Note that input_dim itself could be a Flattened set of input dims.
code: def inputs(self) -> Iterable[DimSpec]:
      return (self.input_dim,)
  
imports: from dataclasses import dataclass
  from typing import Callable, cast, Dict, Iterable, Optional, Sequence, Set, Tuple, Union
  import torch
  from torch import Tensor
  from torch._subclasses.fake_tensor import unset_fake_temporarily
  from torch.distributed._tensor._utils import compute_local_shape
  from torch.distributed._tensor.api import Shard
  from torch.distributed._tensor.op_schema import OpSchema, OutputSharding, RuntimeSchemaInfo
  from torch.distributed._tensor.ops.utils import normalize_dim, normalize_dims, prod, register_prop_rule
  from torch.distributed._tensor.placement_types import DTensorSpec, Placement, Replicate
  from torch.fx.experimental.proxy_tensor import disable_proxy_modes_tracing
label_desc: Use image node_id 2 for calling the Split obj's underlying member method code with example usage: obj.inputs() and returns: self