Pytorch-forecasting

Fixed

Fix bug where predictions were not correctly logged in case of `decoder_length == 1`.

Added

- Add favicon to docs page

---

Update build system requirements to be parsed correctly when installing with `pip install git+https://github.com/jdb78/pytorch-forecasting`

---

- Add tests for MacOS
- Automatic releases
- Coverage reporting

---

This release improves robustness of the code.

- Fixing bug across code, in particularly

- Ensuring that code works on GPUs
- Adding tests for models, dataset and normalisers
- Test using GitHub Actions (tests on GPU are still missing)

- Extend documentation by improving docstrings and adding two tutorials.
- Improving default arguments for TimeSeriesDataSet to avoid surprises

---

Added

- Basic tests for data and model (mostly integration tests)
- Automatic target normalization
- Improved visualization and logging of temporal fusion transformer
- Model bugfixes and performance improvements for temporal fusion transformer

Modified

- Metrics are reduced to calculating loss. Target transformations are done by new target transformer