Comments (1)
Thanks for reporting! Currently torch version 1.5.1 is required. So at this stage I suggest you create a separate virtual environment to use darts. Sorry for the trouble, maybe in the future we can make this easier, please stay tuned for new releases of Darts.
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Related Issues (20)
- [Question] Is it possible to override the models' data loading methods? HOT 4
- Saving/loading model with a checkpoint callback HOT 2
- [BUG] TimeSeries should support the fill_missing_dates=False without freq HOT 1
- [BUG] Error when loading a saved TFTModel checkpoint HOT 2
- What is the difference between variable importance for the encoder and decoder in TFTExplainer? HOT 1
- Rolling prediction ;validation model HOT 1
- Tsmixer incorrect loss_fn/likelihood documentation HOT 1
- [BUG] darts should provide way to input multiprocessing_context parameter for dataloader when fit HOT 3
- [BUG] darts should support re-training base on the old checkpoint, not reset the model HOT 2
- Add KAN (Kolmogorov-Arnold Network) to Darts HOT 5
- Gridlines automatically created in matplotlib and seaborn plots [BUG] HOT 3
- How to mask or ignore target features during model training HOT 13
- Quantile forecasts are identical for all forecast horizons (XGBoost) HOT 2
- [BUG] TSMixer TimeBatchNorm2d using BatchNorm instead of LayerNorm HOT 6
- [BUG] Deterministic TFT model prediction not reproducable HOT 2
- TSMixer ConditionalMixer Skip Connections HOT 1
- [BUG] PLForecastingModule._calculate_metrics should call log_dict with batch_size HOT 2
- [BUG] TorchMetrics loop implementation isn't compatible with stateful metrics HOT 1
- [BUG] TCNModel changes the shape of data erroneously before loss evaluation HOT 3
- [BUG] TFTModel returns StopIteration on decoder_vsn() call in forward() HOT 5
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