code: def get_triton_layernorm_forward():
      if HAS_TRITON_NORM:
  
          def _triton_layernorm_forward(
              self: LayerNorm, hidden_states: torch.Tensor
          ):
              return layer_norm(
                  hidden_states, self.weight.data, self.bias, self.eps
              )
  
          return _triton_layernorm_forward
      else:
          return None
  
file_path: ColossalAI/colossalai/legacy/inference/tensor_parallel/policies/bloom.py
imports: from functools import partial
  import torch
  from torch.nn import LayerNorm
  import colossalai.shardformer.layer
  from colossalai.shardformer.policies.base_policy import ModulePolicyDescription, SubModuleReplacementDescription
  from colossalai.shardformer.policies.bloom import BloomForCausalLMPolicy
  from ..modeling.bloom import BloomInferenceForwards
label_desc: Use image node_id 1 for calling a global function with example usage: get_triton_layernorm_forward() and returns: _triton_layernorm_forward, None, layer_norm