Model can't find encoding_available variable [BUG]

Describe the bug After fitting TCN model, when attempting to backtest program spits out error regarding self.encoders.encoding_available

Error

AttributeError                            Traceback (most recent call last)
/tmp/ipykernel_1955/95313221.py in <module>
      7     retrain=False,
      8     num_samples=1,
----> 9     verbose=True,
     10 )

/lib/python3.7/site-packages/darts/utils/utils.py in sanitized_method(self, *args, **kwargs)
    170 
    171                 getattr(self, sanity_check_method)(*only_args.values(), **only_kwargs)
--> 172             return method_to_sanitize(self, *only_args.values(), **only_kwargs)
    173 
    174         return sanitized_method

/lib/python3.7/site-packages/darts/models/forecasting/forecasting_model.py in historical_forecasts(self, series, past_covariates, future_covariates, num_samples, start, forecast_horizon, stride, retrain, overlap_end, last_points_only, verbose)
    421                 past_covariates=past_covariates,
    422                 future_covariates=future_covariates,
--> 423                 num_samples=num_samples,
    424             )
    425 

/lib/python3.7/site-packages/darts/models/forecasting/forecasting_model.py in _predict_wrapper(self, n, series, past_covariates, future_covariates, num_samples)
   1008             past_covariates=past_covariates,
   1009             future_covariates=future_covariates,
-> 1010             num_samples=num_samples,
   1011         )
   1012 

/lib/python3.7/site-packages/darts/utils/torch.py in decorator(self, *args, **kwargs)
     68         with fork_rng():
     69             manual_seed(self._random_instance.randint(0, high=MAX_TORCH_SEED_VALUE))
---> 70             return decorated(self, *args, **kwargs)
     71 
     72     return decorator

/lib/python3.7/site-packages/darts/models/forecasting/torch_forecasting_model.py in predict(self, n, series, past_covariates, future_covariates, trainer, batch_size, verbose, n_jobs, roll_size, num_samples, num_loader_workers)
   1076         )
   1077 
-> 1078         if self.encoders.encoding_available:
   1079             past_covariates, future_covariates = self.encoders.encode_inference(
   1080                 n=n,

AttributeError: 'NoneType' object has no attribute 'encoding_available'

To Reproduce

backtest_series = model.historical_forecasts(
    series_transformed,
    start=series_transformed.get_timestamp_at_point(0.6),
    forecast_horizon=7,
    stride=5,
    retrain=False,
    num_samples=1, 
    verbose=True,
)

Expected behavior I expect to backtest on fitted model

System

• Python version: 3.7.11
• darts version 0.17.1

[dennisbader]

Can you try model = TCNModel.load_model('dt-model.pth.tar') and see if this resolves the issue? load_model() is a class method and returns the loaded model as a new TCNModel object.

[dennisbader]

Hey @Joe-TheBro, I tried your code snippet and it runs without issues…

This seems strange to me. The encoders should be initialized when model.fit() is called.

Here are some questions:

• Can you verify your darts version by printing print(darts.__version__)
• As I can see, you used a jupyter notebook to run the code (is that correct?).
• Is it possible that your model.fit() failed and that your model is still in its initial state?
• Can you print print(model.epochs_trained) and check if this is > 0?