class_docstr: A PlaceholderHandler which deals with the sharding strategies for Placeholder Node.
class_docstr_tok: ["A","PlaceholderHandler","which","deals","with","the","sharding","strategies","for","Placeholder","Node","."]
code: def get_operation_data_mapping(self) -> Dict[str, OperationData]:
      # use transposed shape for strategies
      # the strategies will be transformed back to its original shape in self.post_process
      physical_output = OperationData(
          name=str(self.node),
          type=OperationDataType.OUTPUT,
          data=self.node._meta_data,
      )
  
      mapping = {"output": physical_output}
  
      return mapping
  
file_path: ColossalAI/colossalai/auto_parallel/tensor_shard/node_handler/placeholder_handler.py
imports: from typing import Dict, List
  from torch.fx.node import Node
  from colossalai.device.device_mesh import DeviceMesh
  from ..sharding_strategy import OperationData, OperationDataType, StrategiesVector
  from .node_handler import NodeHandler
  from .strategy import PlaceholderGenerator, StrategyGenerator
label_desc: Use image node_id 3 for calling the PlaceholderHandler obj's underlying member method code with example usage: obj.get_operation_data_mapping() and returns: mapping