content: import os
  from omegaconf import OmegaConf
  from packaging import version
  from typing import Dict, Optional, Tuple, List
  from dataclasses import dataclass
  
  
  # ============ Register OmegaConf Recolvers ============= #
  OmegaConf.register_new_resolver('calc_exp_lr_decay_rate', lambda factor, n: factor**(1./n), replace=True)
  OmegaConf.register_new_resolver('add', lambda a, b: a + b, replace=True)
  OmegaConf.register_new_resolver('sub', lambda a, b: a - b, replace=True)
  OmegaConf.register_new_resolver('mul', lambda a, b: a * b, replace=True)
  OmegaConf.register_new_resolver('div', lambda a, b: a / b, replace=True)
  OmegaConf.register_new_resolver('idiv', lambda a, b: a // b, replace=True)
  OmegaConf.register_new_resolver('basename', lambda p: os.path.basename(p), replace=True)
  # ======================================================= #
  
  
  def prompt(question):
      inp = input(f"{question} (y/n)").lower().strip()
      if inp and inp == 'y':
          return True
      if inp and inp == 'n':
          return False
      return prompt(question)
  
  @dataclass
  class MVConfig:
      pretrained_unet_path: str
      revision: Optional[str]
      validation_dataset: Dict
      save_dir: str
      seed: Optional[int]
      validation_batch_size: int
      dataloader_num_workers: int
  
      local_rank: int
  
      pipe_kwargs: Dict
      pipe_validation_kwargs: Dict
      unet_from_pretrained_kwargs: Dict
      validation_guidance_scales: List[float]
      validation_grid_nrow: int
      camera_embedding_lr_mult: float
  
      num_views: int
      camera_embedding_type: str
  
      pred_type: str  # joint, or ablation
  
      enable_xformers_memory_efficient_attention: bool
  
      cond_on_normals: bool
      cond_on_colors: bool
  
  def load_config(*yaml_files, cli_args=[]):
      yaml_confs = [OmegaConf.load(f) for f in yaml_files]
      cli_conf = OmegaConf.from_cli(cli_args)
      conf = OmegaConf.merge(*yaml_confs, cli_conf)
      OmegaConf.resolve(conf)
      
      schema = OmegaConf.structured(MVConfig)
      conf = OmegaConf.merge(schema, conf)
      return conf
  
  def config_to_primitive(config, resolve=True):
      return OmegaConf.to_container(config, resolve=resolve)
  
  
  def dump_config(path, config):
      with open(path, 'w') as fp:
          OmegaConf.save(config=config, f=fp)
  
  def get_rank():
      # SLURM_PROCID can be set even if SLURM is not managing the multiprocessing,
      # therefore LOCAL_RANK needs to be checked first
      rank_keys = ("RANK", "LOCAL_RANK", "SLURM_PROCID", "JSM_NAMESPACE_RANK")
      for key in rank_keys:
          rank = os.environ.get(key)
          if rank is not None:
              return int(rank)
      return 0
  
  
  def parse_version(ver):
      return version.parse(ver)
  