code: def modeling_arguments(
      parser: argparse.ArgumentParser,
  ) -> argparse.ArgumentParser:
      # text encoder arguments (usually for multi-modal tasks)
      parser = arguments_text_encoder(parser)
      # image projection head arguments (usually for multi-modal tasks)
      parser = arguments_image_projection_head(parser)
      # model arguments
      parser = arguments_model(parser)
      # neural network layer argumetns
      parser = arguments_nn_layers(parser)
      # EMA arguments
      parser = arguments_ema(parser)
      # anchor generator arguments (for object detection)
      parser = arguments_anchor_gen(parser)
      # box matcher arguments (for object detection)
      parser = arguments_box_matcher(parser)
      # neural aug arguments
      parser = arguments_neural_augmentor(parser)
  
      # Add teacher as a prefix to enable distillation tasks
      # keep it as the last entry
      parser = extend_selected_args_with_prefix(
          parser,
          match_prefix="--model.",
          additional_prefix="--teacher.model.",
      )
  
      return parser
  
file_path: ml-cvnets/cvnets/__init__.py
imports: import argparse
  from cvnets.anchor_generator import arguments_anchor_gen
  from cvnets.image_projection_layers import arguments_image_projection_head
  from cvnets.layers import arguments_nn_layers
  from cvnets.matcher_det import arguments_box_matcher
  from cvnets.misc.averaging_utils import EMA, arguments_ema
  from cvnets.misc.common import parameter_list
  from cvnets.models import arguments_model, get_model
  from cvnets.models.detection import DetectionPredTuple
  from cvnets.neural_augmentor import arguments_neural_augmentor
  from cvnets.text_encoders import arguments_text_encoder
  from options.utils import extend_selected_args_with_prefix
label_desc: Use image node_id 1 for calling a global function with example usage: modeling_arguments(parser) and returns: parser