DataModule error when using 1-pressure level variable about climate-learn HOT 10 CLOSED

data_module = DataModule(
    dataset = "ERA5",
    task = "forecasting",
    root_dir = DATADIR,
    in_vars = ["geopotential"],
    out_vars = ["geopotential_500"],
    train_start_year = Year(2015),
    val_start_year = Year(2016),
    test_start_year = Year(2017),
    end_year = Year(2018),
    pred_range = Days(3),
    subsample = Hours(1),
    batch_size = 128,
    num_workers = 1
)

      67 if len(xr_data.shape) == 3:  # 8760, 32, 64
     68     xr_data = xr_data.expand_dims(dim="level", axis=1)
---> 69     data_dict[var].append(xr_data)

        KeyError                                  Traceback (most recent call last)
        Cell In[8], line 1
        ----> 1 data_module = DataModule(
              2     dataset = "ERA5",
              3     task = "forecasting",
              4     root_dir = DATADIR,
              5     in_vars = ["2m_temperature"],
              6     out_vars = ["geopotential"],
              7     train_start_year = Year(2015),
              8     val_start_year = Year(2016),
              9     test_start_year = Year(2017),
             10     end_year = Year(2018),
             11     pred_range = Days(3),
             12     subsample = Hours(1),
             13     batch_size = 128,
             14     num_workers = 1
             15 )
        
        File ~/climate-learn/src/climate_learn/data/module.py:112, in DataModule.__init__(self, dataset, task, root_dir, in_vars, out_vars, train_start_year, val_start_year, test_start_year, end_year, root_highres_dir, history, window, pred_range, subsample, batch_size, num_workers, pin_memory)
            109 caller = eval(f"{dataset.upper()}{task_string}")
            111 train_years = range(train_start_year, val_start_year)
        --> 112 self.train_dataset = caller(
            113     root_dir,
            114     root_highres_dir,
            115     in_vars,
            116     out_vars,
            117     history,
            118     window,
            119     pred_range.hours(),
            120     train_years,
            121     subsample.hours(),
            122     "train",
            123 )
            125 val_years = range(val_start_year, test_start_year)
            126 self.val_dataset = caller(
            127     root_dir,
            128     root_highres_dir,
           (...)
            136     "val",
            137 )
        
        File ~/climate-learn/src/climate_learn/data/modules/era5_module.py:114, in ERA5Forecasting.__init__(self, root_dir, root_highres_dir, in_vars, out_vars, history, window, pred_range, years, subsample, split)
            112 print(f"Creating {split} dataset")
            113 unique_vars = list(set(in_vars) | set(out_vars))
        --> 114 super().__init__(root_dir, root_highres_dir, unique_vars, years, split)
            116 self.in_vars = list(self.data_dict.keys())
            117 self.out_vars = out_vars
        
        File ~/climate-learn/src/climate_learn/data/modules/era5_module.py:28, in ERA5.__init__(self, root_dir, root_highres_dir, variables, years, split)
             25 self.years = years
             26 self.split = split
        ---> 28 self.data_dict = self.load_from_nc(self.root_dir)
             29 if self.root_highres_dir is not None:
             30     self.data_highres_dict = self.load_from_nc(self.root_highres_dir)
        
        File ~/climate-learn/src/climate_learn/data/modules/era5_module.py:69, in ERA5.load_from_nc(self, data_dir)
             67 if len(xr_data.shape) == 3:  # 8760, 32, 64
             68     xr_data = xr_data.expand_dims(dim="level", axis=1)
        ---> 69     data_dict[var].append(xr_data)
             70 else:  # pressure level
             71     for level in DEFAULT_PRESSURE_LEVELS:
        
        - KeyError: 'geopotential'