code: def arguments_nn_layers(parser: argparse.ArgumentParser):
      # Retrieve layer specific arguments
      parser = layer_specific_args(parser)
  
      # activation and normalization arguments
      from cvnets.layers.activation import arguments_activation_fn
  
      parser = arguments_activation_fn(parser)
  
      from cvnets.layers.normalization import arguments_norm_layers
  
      parser = arguments_norm_layers(parser)
  
      return parser
  
imports: import argparse
  import importlib
  import inspect
  import os
  from cvnets.layers.adaptive_pool import AdaptiveAvgPool2d
  from cvnets.layers.base_layer import BaseLayer
  from cvnets.layers.conv_layer import ConvLayer1d, ConvLayer2d, ConvLayer3d, NormActLayer, SeparableConv1d, SeparableConv2d, SeparableConv3d, TransposeConvLayer2d
  from cvnets.layers.dropout import Dropout, Dropout2d
  from cvnets.layers.embedding import Embedding
  from cvnets.layers.flatten import Flatten
  from cvnets.layers.global_pool import GlobalPool
  from cvnets.layers.identity import Identity
  from cvnets.layers.linear_attention import LinearSelfAttention
  from cvnets.layers.linear_layer import GroupLinear, LinearLayer
  from cvnets.layers.multi_head_attention import MultiHeadAttention
  from cvnets.layers.normalization_layers import AdjustBatchNormMomentum, get_normalization_layer, norm_layers_tuple
  from cvnets.layers.pixel_shuffle import PixelShuffle
  from cvnets.layers.pooling import AvgPool2d, MaxPool2d
  from cvnets.layers.positional_embedding import PositionalEmbedding
  from cvnets.layers.single_head_attention import SingleHeadAttention
  from cvnets.layers.softmax import Softmax
  from cvnets.layers.stochastic_depth import StochasticDepth
  from cvnets.layers.upsample import UpSample
label_desc: Use image node_id 2 for calling a global function with example usage: arguments_nn_layers(parser) and returns: parser