docstr: This a utility function which helps to control the layer norm behavior
  `before` and `after` specific components using one variable in config.
  If self.normalize_before is set to True, output is true only when `before`
  is True
docstr_tok: ["This","a","utility","function","which","helps","to","control","the","layer","norm","behavior","`","before","`","and","`","after","`","specific","components","using","one","variable","in","config",".","If","self.normalize_before","is","set","to","True",",","output","is","true","only","when","`","before","`","is","True"]
code: def maybe_layer_norm(self, before: bool = False, after: bool = False):
      """This a utility function which helps to control the layer norm behavior
      `before` and `after` specific components using one variable in config.
      If self.normalize_before is set to True, output is true only when `before`
      is True
      """
      assert before ^ after, "Incorrect usage"
      return after ^ self.normalize_before
  
imports: import math
  from typing import Dict, List, Optional, Tuple, Union
  import torch
  import torch.nn
  import torch.nn.functional
  from pytext.config import ConfigBase
  from pytext.config.module_config import ModuleConfig
  from pytext.models.module import create_module
  from pytext.models.seq_models.base import PlaceholderAttentionIdentity
  from pytext.models.seq_models.positional import build_positional_embedding, PostionalEmbedCombine, PostionalEmbedType
  from pytext.models.seq_models.utils import Linear, log_and_overwrite
  from torch import Tensor
  from torch.nn import LayerNorm
  from .attention import MultiheadAttention
  from .base import PlaceholderIdentity, PyTextIncrementalDecoderComponent, PyTextSeq2SeqModule
  from .light_conv import LightweightConv
  from .projection_layers import DecoderWithLinearOutputProjection, DecoupledDecoderHead
  from .utils import extract_ontology_vocab
label_desc: Use image node_id 4 for calling the LightConvDecoderLayer obj's underlying member method code with example usage: obj.maybe_layer_norm(before, after) and returns: unknown