code: def module_policy(self):
      from transformers.models.gpt2.modeling_gpt2 import GPT2LMHeadModel
  
      module_policy = super().module_policy()
  
      if self.shard_config.enable_tensor_parallelism:
          addon_module = {
              GPT2LMHeadModel: ModulePolicyDescription(
                  sub_module_replacement=[
                      SubModuleReplacementDescription(
                          suffix="lm_head",
                          target_module=col_nn.Linear1D_Col,
                          kwargs={"gather_output": True},
                      )
                  ]
              )
          }
          module_policy.update(addon_module)
  
      if self.pipeline_stage_manager is not None:
          self.set_pipeline_forward(
              model_cls=GPT2LMHeadModel,
              new_forward=GPT2PipelineForwards.gpt2_lmhead_model_forward,
              policy=module_policy,
          )
      return module_policy
  
imports: from functools import partial
  from typing import Callable, Dict, List
  from torch import Tensor, nn
  import colossalai.shardformer.layer
  from ..modeling.gpt2 import GPT2PipelineForwards, get_gpt2_flash_attention_forward, gpt2_sequence_parallel_forward_fn
  from .base_policy import ModulePolicyDescription, Policy, SubModuleReplacementDescription
label_desc: Use image node_id 1 for calling the GPT2LMHeadModelPolicy obj's underlying member method code with example usage: obj.module_policy() and returns: module_policy