docstr: Fetch a specific pre-trained variant for the backbone configuration
  
  Args:
      dataset (str): dataset the variant was trained on
      lr_schd (int): learning schedule
      crop_size (tuple): input crop size
  
  Returns:
      dict: pre-trained variant information
docstr_tok: ["Fetch","a","specific","pre-trained","variant","for","the","backbone","configuration","Args",":","dataset","(","str",")",":","dataset","the","variant","was","trained","on","lr_schd","(","int",")",":","learning","schedule","crop_size","(","tuple",")",":","input","crop","size","Returns",":","dict",":","pre-trained","variant","information"]
code: def get_pre_trained_variant(
      self, dataset: str, lr_schd: int, crop_size: tuple
  ):
      """Fetch a specific pre-trained variant for the backbone configuration
  
      Args:
          dataset (str): dataset the variant was trained on
          lr_schd (int): learning schedule
          crop_size (tuple): input crop size
  
      Returns:
          dict: pre-trained variant information
      """
  
      variant = list(
          filter(
              lambda x: x["pre_training_dataset"] == dataset
              and x["lr_schd"] == lr_schd
              and x["crop_size"] == crop_size,
              self.pre_trained_variants,
          )
      )
  
      if not len(variant):
          raise PreTrainedVariantNotFound
  
      return variant[0]
  
file_path: icevision/icevision/models/mmseg/utils.py
imports: from icevision.imports import *
  from icevision.utils import *
  from icevision.models.backbone_config import BackboneConfig
  from icevision.core.exceptions import PreTrainedVariantNotFound
  from icevision.models.mmseg.download_configs import download_mmseg_configs
  from mmseg.models.segmentors import *
  from mmcv import Config
label_desc: Use image node_id 4 for calling the MMSegBackboneConfig obj's underlying member method code with example usage: obj.get_pre_trained_variant(dataset, lr_schd, crop_size) and returns: variant