code: def set_model_specific_opts_before_model_building(
      opts: argparse.Namespace,
  ) -> Dict[str, Any]:
      """Override library-level defaults with model-specific default values.
  
      Args:
          opts: Command-line arguments
  
      Returns:
          A dictionary containing the name of arguments that are updated along with their original values.
          This dictionary is used in `unset_model_specific_opts_after_model_building` function to unset the
          model-specific to library-specific defaults.
      """
  
      cls_act_fn = getattr(opts, "model.classification.activation.name")
      default_opts_info = {}
      if cls_act_fn is not None:
          # Override the default activation arguments with classification network specific arguments
          default_act_fn = getattr(
              opts, "model.activation.name", "relu"
          )
          default_act_inplace = getattr(
              opts, "model.activation.inplace", False
          )
          default_act_neg_slope = getattr(
              opts, "model.activation.neg_slope", 0.1
          )
  
          setattr(opts, "model.activation.name", cls_act_fn)
          setattr(
              opts,
              "model.activation.inplace",
              getattr(
                  opts, "model.classification.activation.inplace", False
              ),
          )
          setattr(
              opts,
              "model.activation.neg_slope",
              getattr(
                  opts, "model.classification.activation.neg_slope", 0.1
              ),
          )
  
          default_opts_info["model.activation.name"] = default_act_fn
          default_opts_info[
              "model.activation.inplace"
          ] = default_act_inplace
          default_opts_info[
              "model.activation.neg_slope"
          ] = default_act_neg_slope
      return default_opts_info
  
imports: import argparse
  from typing import Any, Dict, List, Mapping, Optional, Tuple
  import torch
  from torch import Tensor, nn
  from torch.utils.checkpoint import checkpoint
  from common import is_test_env
  from cvnets.layers import LinearLayer
  from cvnets.misc.init_utils import initialize_fc_layer
  from cvnets.models import MODEL_REGISTRY, BaseAnyNNModel
  from cvnets.neural_augmentor import build_neural_augmentor
  from utils import logger
label_desc: Use image node_id 1 for calling a global function with example usage: set_model_specific_opts_before_model_building(opts) and returns: default_opts_info