code: def __init__(
      self,
      client_module,
      inference=True,
      megatron_v2=True,
      split_qkv=False,
  ):
      super().__init__(
          inference, megatron_v2=megatron_v2, split_qkv=split_qkv
      )
      self.client_module = client_module
      if GPTNEOXLayerPolicy._orig_layer_class is None:
          if pkg_version.parse(torch.__version__) <= pkg_version.parse(
              "1.2"
          ):
              GPTNEOXLayerPolicy._orig_layer_class = None
          else:
              try:
                  from transformers import GPTNeoXLayer
  
                  GPTNEOXLayerPolicy._orig_layer_class = GPTNeoXLayer
              except ImportError:
                  GPTNEOXLayerPolicy._orig_layer_class = None
  
imports: from .base import *
  from .features.meta_tensor import MetaTensorContainer
  from .features.hybrid_megatron import HybridMegatronContainer
  from deepspeed.model_implementations.transformers.ds_gpt import DeepSpeedGPTInference
  import torch
  from ..policy import TransformerPolicy
  from ..policy import transformer_param_names
  from ..policy import maybe_copy
  from packaging import version
  from ..policy import maybe_get_lora
label_desc: Use image node_id 1 to create a new GPTNEOXLayerPolicy object from inherited base classes: TransformerPolicy with example: obj = GPTNEOXLayerPolicy(client_module, inference, megatron_v2, split_qkv)