code: def build_model(
      config: Union[
          DictConfig, "mmf.models.base_model.BaseModel.Config"
      ],
  ) -> "mmf.models.base_model.BaseModel":
      from mmf.models.base_model import BaseModel
  
      # If it is not an OmegaConf object, create the object
      if not isinstance(config, DictConfig) and isinstance(
          config, BaseModel.Config
      ):
          config = OmegaConf.structured(config)
  
      model_name = config.model
      model_class = registry.get_model_class(model_name)
  
      if model_class is None:
          raise RuntimeError(
              f"No model registered for name: {model_name}"
          )
      model = model_class(config)
  
      if hasattr(model, "build"):
          """Model build involves checkpoint loading
          If the checkpoint is not available the underlying
          methods try to download it.
          Let master build the model (download the checkpoints) while
          other ranks wait for the sync message
          Once the master has downloaded the checkpoint and built the
          model it sends the sync message, completing the synchronization
          now other cores can proceed to build the model
          using already downloaded checkpoint.
          """
          if is_main():
              model_class.load_requirements(model_class, config=config)
              model.build()
              synchronize()
          else:
              synchronize()
              model.build()
          model.init_losses()
      return model
  
imports: import logging
  import os
  import warnings
  from enum import Enum
  from typing import Any, Dict, List, Optional, Tuple, Union
  import mmf
  import pytorch_lightning
  import torch
  from mmf.common.meter import Meter
  from mmf.common.registry import registry
  from mmf.datasets.iteration_strategies import ConstantIterationStrategy, IterationStrategy, SizeProportionalIterationStrategy
  from mmf.datasets.processors.processors import Processor
  from mmf.utils.configuration import Configuration, get_global_config
  from mmf.utils.distributed import is_dist_initialized, is_main, is_xla, synchronize
  from mmf.utils.general import get_optimizer_parameters
  from omegaconf import DictConfig, OmegaConf
  from packaging import version
label_desc: Use image node_id 4 for calling a global function with example usage: build_model(config) and returns: model