code: def module_policy(self):
      from transformers.models.falcon.modeling_falcon import (
          FalconAttention,
          FalconDecoderLayer,
          FalconModel,
      )
  
      if (
          not self.model.config.new_decoder_architecture
          and self.model.config.multi_query
      ):
          warnings.warn(
              "Falcon dosen't support tensor parallelism when (not new_decoder_architecture and multi_query) is True, will ignore the tensor parallelism flag."
          )
          self.shard_config.enable_tensor_parallelism = False
  
      if self.shard_config.enable_sequence_parallelism:
          self.shard_config.enable_sequence_parallelism = False
          warnings.warn(
              "Falcon doesn't support sequence parallelism now, will ignore the sequence parallelism flag."
          )
  
      policy = {}
      if self.shard_config.enable_tensor_parallelism:
          attn_attribute_replacement = {
              "self_attention.hidden_size": self.model.config.hidden_size
              // self.shard_config.tensor_parallel_size,
              "self_attention.split_size": self.model.config.hidden_size
              // self.shard_config.tensor_parallel_size,
              "self_attention.num_heads": self.model.config.num_attention_heads
              // self.shard_config.tensor_parallel_size,
              "self_attention.num_kv_heads": self.model.config.num_kv_heads
              // self.shard_config.tensor_parallel_size,
          }
  
          policy[FalconDecoderLayer] = ModulePolicyDescription(
              attribute_replacement=attn_attribute_replacement,
              method_replacement={
                  "forward": get_tp_falcon_decoder_layer_forward()
              },
              sub_module_replacement=[
                  SubModuleReplacementDescription(
                      suffix="self_attention.query_key_value",
                      target_module=col_nn.Linear1D_Col,
                  ),
                  SubModuleReplacementDescription(
                      suffix="self_attention.dense",
                      target_module=col_nn.Linear1D_Row,
                  ),
                  SubModuleReplacementDescription(
                      suffix="self_attention.attention_dropout",
                      target_module=col_nn.DropoutForParallelInput,
                  ),
                  SubModuleReplacementDescription(
                      suffix="mlp.dense_h_to_4h",
                      target_module=col_nn.Linear1D_Col,
                  ),
                  SubModuleReplacementDescription(
                      suffix="mlp.dense_4h_to_h",
                      target_module=col_nn.Linear1D_Row,
                  ),
              ],
          )
  
          policy[FalconModel] = ModulePolicyDescription(
              attribute_replacement={
                  "num_heads": self.model.config.num_attention_heads
                  // self.shard_config.tensor_parallel_size,
              },
              method_replacement={
                  "build_alibi_tensor": build_falcon_alibi_tensor_fn(
                      self.shard_config.tensor_parallel_process_group
                  )
              },
              sub_module_replacement=[
                  SubModuleReplacementDescription(
                      suffix="word_embeddings",
                      target_module=col_nn.VocabParallelEmbedding1D,
                  )
              ],
          )
  
      # optimization configuration
      if self.shard_config.enable_fused_normalization:
          # handle falcon model
          self.append_or_create_submodule_replacement(
              description=[
                  SubModuleReplacementDescription(
                      suffix="ln_f",
                      target_module=col_nn.FusedLayerNorm,
                  ),
              ],
              policy=policy,
              target_key=FalconModel,
          )
  
          # handle falcon decoder layer
          self.append_or_create_submodule_replacement(
              description=[
                  SubModuleReplacementDescription(
                      suffix="ln_attn",
                      target_module=col_nn.FusedLayerNorm,
                      ignore_if_not_exist=True,
                  ),
                  SubModuleReplacementDescription(
                      suffix="ln_mlp",
                      target_module=col_nn.FusedLayerNorm,
                      ignore_if_not_exist=True,
                  ),
                  SubModuleReplacementDescription(
                      suffix="input_layernorm",
                      target_module=col_nn.FusedLayerNorm,
                      ignore_if_not_exist=True,
                  ),
                  SubModuleReplacementDescription(
                      suffix="post_attention_layernorm",
                      target_module=col_nn.FusedLayerNorm,
                      ignore_if_not_exist=True,
                  ),
              ],
              policy=policy,
              target_key=FalconDecoderLayer,
          )
  
      if self.shard_config.enable_flash_attention:
          self.append_or_create_method_replacement(
              description={
                  "forward": get_falcon_flash_attention_forward()
              },
              policy=policy,
              target_key=FalconAttention,
          )
      return policy
  
imports: import warnings
  from functools import partial
  from typing import Callable, Dict, List
  from torch import Tensor, nn
  from torch.nn import Module
  import colossalai.shardformer.layer
  from ..modeling.falcon import FalconPipelineForwards, build_falcon_alibi_tensor_fn, get_falcon_flash_attention_forward, get_tp_falcon_decoder_layer_forward
  from .base_policy import ModulePolicyDescription, Policy, SubModuleReplacementDescription
label_desc: Use image node_id 4 for calling the FalconPolicy obj's underlying member method code with example usage: obj.module_policy() and returns: policy