code: def module_policy(self):
      from transformers.models.vit.modeling_vit import (
          ViTForImageClassification,
          ViTModel,
      )
  
      policy = super().module_policy()
      if self.shard_config.enable_tensor_parallelism:
          new_item = {
              ViTForImageClassification: ModulePolicyDescription(
                  sub_module_replacement=[
                      SubModuleReplacementDescription(
                          suffix="classifier",
                          target_module=Linear1D_Col,
                          kwargs=dict(gather_output=True),
                      )
                  ]
              )
          }
          policy.update(new_item)
  
      if self.shard_config.pipeline_stage_manager is not None:
          self.set_pipeline_forward(
              model_cls=ViTModel,
              pipeline_forward=ViTModel_pipeline_forward,
              policy=policy,
          )
          self.set_pipeline_forward(
              model_cls=ViTForImageClassification,
              pipeline_forward=ViTForImageClassification_pipeline_forward,
              policy=policy,
          )
  
      return policy
  
imports: import warnings
  from typing import Callable, Dict, List, Union
  import torch.nn
  import colossalai.shardformer.layer
  from colossalai.shardformer.layer import DropoutForReplicatedInput, Linear1D_Col
  from ..modeling.jit import get_jit_fused_dropout_add_func
  from ..modeling.vit import ViTForImageClassification_pipeline_forward, ViTForMaskedImageModeling_pipeline_forward, ViTModel_pipeline_forward, get_jit_fused_vit_output_forward, get_vit_flash_self_attention_forward
  from .base_policy import ModulePolicyDescription, Policy, SubModuleReplacementDescription
label_desc: Use image node_id 1 for calling the ViTForImageClassificationPolicy obj's underlying member method code with example usage: obj.module_policy() and returns: policy