code: def random_op_strategy(
      mesh: DeviceMesh, op_schema: OpSchema
  ) -> StrategyType:
      self_strategy = op_schema.args_schema[0]
      assert isinstance(self_strategy, OpStrategy)
  
      random_strategy = OpStrategy([])
      for arg_strategy in self_strategy.strategies:
          arg_spec = arg_strategy.out_spec
          if is_tensor_partial(arg_spec):
              # TODO: figure out how inplace random op should behave when it's partial
              raise RuntimeError(
                  f"{op_schema.op} with _Partial is not supported yet!"
              )
          random_strategy.strategies.append(
              PlacementStrategy(output_spec=arg_spec)
          )
  
      return random_strategy
  
imports: import torch
  from torch.distributed._tensor.op_schema import OpSchema, OpStrategy, PlacementStrategy, StrategyType
  from torch.distributed._tensor.ops.utils import is_tensor_partial, register_op_strategy
  from torch.distributed.device_mesh import DeviceMesh
label_desc: Use image node_id 1 for calling a global function with example usage: random_op_strategy(mesh, op_schema) and returns: random_strategy