code: def _gen_replicate_strategy(
      mesh: DeviceMesh, input_specs: Optional[List[DTensorSpec]] = None
  ) -> PlacementStrategy:
      """Util function to generate a replicate strategy."""
      return PlacementStrategy(
          output_spec=DTensorSpec(mesh=mesh, placements=(Replicate(),)),
          input_specs=input_specs,
      )
  
imports: import operator
  from contextlib import contextmanager
  from enum import Enum
  from typing import Any, cast, Dict, List, Optional, Tuple
  import torch
  import torch.distributed.distributed_c10d
  import torch.fx
  import torch.library
  import torch.nn
  import torch.utils._pytree
  from torch.distributed._spmd.batch_dim_utils import BatchDimAnalyzer
  from torch.distributed._tensor import DeviceMesh, distribute_tensor, Replicate, Shard
  from torch.distributed._tensor._utils import compute_local_shape
  from torch.distributed._tensor.op_schema import OpStrategy, PlacementStrategy, StrategyType, TupleStrategy
  from torch.distributed._tensor.placement_types import _Partial, DTensorSpec, Placement
  from torch.distributed._tensor.redistribute import redistribute_local_tensor
  from torch.fx import GraphModule
  from torch.fx.experimental.proxy_tensor import make_fx
  from torch.fx.passes.shape_prop import _extract_tensor_metadata
  from torch.nn.utils._named_member_accessor import NamedMemberAccessor
label_desc: Use image node_id 3 for calling a global function with example usage: _gen_replicate_strategy(mesh, input_specs) and returns: PlacementStrategy