code: def get_hidden_heads(self):
      hidden_heads = (
          getattr(
              self.client_module.self_attn.q_proj.weight,
              "ds_shape",
              self.client_module.self_attn.q_proj.weight.shape,
          )[1],
          self.client_module.self_attn.num_heads,
          self.client_module.input_layernorm.variance_epsilon,
          getattr(
              self.client_module.mlp.gate_proj.weight,
              "ds_shape",
              self.client_module.mlp.gate_proj.weight.shape,
          )[0],
      )
      return hidden_heads
  
imports: from .base import *
  from .features import HybridSplitQKVContainer, HybridGatedMLPContainer, MetaTensorContainer
  from deepspeed.utils.types import ActivationFuncType, NormType
  from deepspeed.model_implementations.transformers.ds_gpt import DeepSpeedGPTInference
  import torch
  from torch.nn.parameter import Parameter
  from ..policy import TransformerPolicy, transformer_param_names, maybe_copy, maybe_copy_qkv, maybe_copy_geglu, maybe_get_lora
label_desc: Use image node_id 2 for calling the LLAMALayerPolicy obj's underlying member method code with example usage: obj.get_hidden_heads() and returns: hidden_heads