code: def _deep_norm_alpha(c: Configs):
      """
      #### Calculate $\alpha$
  
      $\alpha = (2M)^{\frac{1}{4}}$
      """
      return (2.0 * c.n_layers) ** (1.0 / 4.0)
  
file_path: annotated_deep_learning_paper_implementations/labml_nn/normalization/deep_norm/experiment.py
imports: import copy
  import torch
  import torch.nn
  from labml import experiment
  from labml.configs import option
  from labml_helpers.module import Module
  from labml_nn.experiments.nlp_autoregression import NLPAutoRegressionConfigs
  from labml_nn.normalization.deep_norm import DeepNormTransformerLayer
  from labml_nn.transformers import MultiHeadAttention
  from labml_nn.transformers.feed_forward import FeedForward
label_desc: Use image node_id 1 for calling a global function with example usage: _deep_norm_alpha(c) and returns: unknown