code: def _add_network_size_args(parser):
      group = parser.add_argument_group(title="network size")
  
      group.add_argument(
          "--num-layers",
          type=int,
          default=None,
          help="Number of transformer layers.",
      )
      group.add_argument(
          "--hidden-size",
          type=int,
          default=None,
          help="Tansformer hidden size.",
      )
      group.add_argument(
          "--ffn-hidden-size",
          type=int,
          default=None,
          help="Transformer Feed-Forward Network hidden size. "
          "This is set to 4*hidden-size if not provided",
      )
      group.add_argument(
          "--num-attention-heads",
          type=int,
          default=None,
          help="Number of transformer attention heads.",
      )
      group.add_argument(
          "--kv-channels",
          type=int,
          default=None,
          help="Projection weights dimension in multi-head "
          "attention. This is set to "
          "   args.hidden_size // args.num_attention_heads "
          "if not provided.",
      )
      group.add_argument(
          "--max-position-embeddings",
          type=int,
          default=None,
          help="Maximum number of position embeddings to use. "
          "This is the size of position embedding.",
      )
      group.add_argument(
          "--make-vocab-size-divisible-by",
          type=int,
          default=128,
          help="Pad the vocab size to be divisible by this value."
          "This is added for computational efficieny reasons.",
      )
      group.add_argument(
          "--layernorm-epsilon",
          type=float,
          default=1e-5,
          help="Layer norm epsilon.",
      )
      group.add_argument(
          "--apply-residual-connection-post-layernorm",
          action="store_true",
          help="If set, use original BERT residula connection "
          "ordering.",
      )
      group.add_argument(
          "--openai-gelu",
          action="store_true",
          help="Use OpenAIs GeLU implementation. This option"
          "should not be used unless for backward compatibility"
          "reasons.",
      )
      group.add_argument(
          "--onnx-safe",
          type=bool,
          required=False,
          help="Use workarounds for known problems with "
          "Torch ONNX exporter",
      )
      group.add_argument(
          "--bert-no-binary-head",
          action="store_false",
          help="Disable BERT binary head.",
          dest="bert_binary_head",
      )
      group.add_argument(
          "--num-experts",
          type=int,
          default=None,
          help="Number of Experts in Switch Transformer (None means no Switch)",
      )
  
      return parser
  
imports: import argparse
  import os
  import torch
label_desc: Use image node_id 5 for calling a global function with example usage: _add_network_size_args(parser) and returns: parser