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.
      """
      seg_act_fn = getattr(opts, "model.segmentation.activation.name")
      if seg_act_fn is not None:
          # Override the general activation 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", seg_act_fn)
          setattr(
              opts,
              "model.activation.inplace",
              getattr(
                  opts, "model.segmentation.activation.inplace", False
              ),
          )
          setattr(
              opts,
              "model.activation.neg_slope",
              getattr(
                  opts, "model.segmentation.activation.neg_slope", 0.1
              ),
          )
          return {
              "model.activation.name": default_act_fn,
              "model.activation.inplace": default_act_inplace,
              "model.activation.neg_slope": default_act_neg_slope,
          }
      return {}
  
file_path: ml-cvnets/cvnets/models/segmentation/base_seg.py
imports: import argparse
  from typing import Any, Dict
  import torch
  from cvnets.models import MODEL_REGISTRY, BaseAnyNNModel
  from cvnets.models.classification.base_image_encoder import BaseImageEncoder
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: dict, dict