code: def get_model(
      opts: argparse.Namespace,
      category: Optional[str] = None,
      model_name: Optional[str] = None,
      *args,
      **kwargs,
  ) -> BaseAnyNNModel:
      """Create a task-specific model from command-line arguments. If model category (or task) and name are
      passed as an argument, then they are used. Otherwise, `dataset.category` and `model.{category}.name` are
      read from command-line arguments to read model category and name, respectively.
  
      Args:
          opts: Command-line arguments
          category: Category or task (e.g., segmentation)
          model_name: Model name for a specific task (e.g., vit for classification)
  
      Returns:
          An instance of `cvnets.models.BaseAnyNNModel`.
      """
  
      if category is None:
          category = getattr(opts, "dataset.category")
  
      if model_name is None:
          model_name = getattr(opts, f"model.{category}.name")
  
      if model_name == "__base__":
          # __base__ is used to register the task-specific base classes. These classes often
          # provide functionalities that can be re-used by sub-classes, but does not provide
          # task-specific models.
          logger.error(
              f"For {category} task, model name can't be __base__. Please check."
          )
  
      model = MODEL_REGISTRY[model_name, category].build_model(
          opts, *args, **kwargs
      )
  
      # for some categories, we do not have pre-trained path (e.g., segmentation_head).
      # Therefore, we need to set the default value.
      pretrained_wts_path = getattr(
          opts, f"model.{category}.pretrained", None
      )
      if pretrained_wts_path is not None:
          pretrained_model_path = get_local_path(
              opts, path=pretrained_wts_path
          )
          model = load_pretrained_model(
              model=model, wt_loc=pretrained_model_path, opts=opts
          )
  
      model = freeze_modules_based_on_opts(opts, model)
      return model
  
file_path: ml-cvnets/cvnets/models/__init__.py
imports: import argparse
  from typing import Optional
  from cvnets.misc.common import freeze_modules_based_on_opts, load_pretrained_model
  from cvnets.models.base_model import BaseAnyNNModel
  from utils import logger
  from utils.download_utils import get_local_path
  from utils.registry import Registry
label_desc: Use image node_id 1 for calling a global function with example usage: get_model(opts, category, model_name) and returns: model