v0.0.5

[LongxingTan]

Description

This PR update

• training without valid data works also fine
• install tensorflow indepently because in Mac M1, the tensorflow is called tensorflow-macos

Checklist

• [ x ] Linked issues (if existing)
• [ x ] Amended changelog.md for large changes (and added myself there as contributor)
• [ x ] Added/modified tests
• [ x ] Used pre-commit hooks when committing to ensure that code is compliant with hooks. Install hooks with pre-commit install. To run hooks independent of commit, execute pre-commit run --all-files

Thank you for joining. Have fun coding!

[codecov[bot]]

Codecov Report

Base: 86.78% // Head: 86.79% // Increases project coverage by +0.00% :tada:

Coverage data is based on head (0c02a28) compared to base (9e6a6c2). Patch coverage: 52.94% of modified lines in pull request are covered.

Additional details and impacted files

```diff @@ Coverage Diff @@ ## master #26 +/- ## ======================================= Coverage 86.78% 86.79% ======================================= Files 27 27 Lines 2013 2014 +1 ======================================= + Hits 1747 1748 +1 Misses 266 266 ``` | Flag | Coverage Δ | | |---|---|---| | cpu | `86.79% <52.94%> (+<0.01%)` | :arrow_up: | | unittest | `86.79% <52.94%> (+<0.01%)` | :arrow_up: | Flags with carried forward coverage won't be shown. [Click here](https://docs.codecov.io/docs/carryforward-flags?utm_medium=referral&utm_source=github&utm_content=comment&utm_campaign=pr+comments&utm_term=None#carryforward-flags-in-the-pull-request-comment) to find out more. | [Impacted Files](https://codecov.io/gh/LongxingTan/Time-series-prediction/pull/26?src=pr&el=tree&utm_medium=referral&utm_source=github&utm_content=comment&utm_campaign=pr+comments&utm_term=None) | Coverage Δ | | |---|---|---| | [tfts/models/seq2seq.py](https://codecov.io/gh/LongxingTan/Time-series-prediction/pull/26/diff?src=pr&el=tree&utm_medium=referral&utm_source=github&utm_content=comment&utm_campaign=pr+comments&utm_term=None#diff-dGZ0cy9tb2RlbHMvc2VxMnNlcS5weQ==) | `82.99% <ø> (ø)` | | | [tfts/trainer.py](https://codecov.io/gh/LongxingTan/Time-series-prediction/pull/26/diff?src=pr&el=tree&utm_medium=referral&utm_source=github&utm_content=comment&utm_campaign=pr+comments&utm_term=None#diff-dGZ0cy90cmFpbmVyLnB5) | `79.21% <42.85%> (+0.11%)` | :arrow_up: | | [tfts/models/auto\_model.py](https://codecov.io/gh/LongxingTan/Time-series-prediction/pull/26/diff?src=pr&el=tree&utm_medium=referral&utm_source=github&utm_content=comment&utm_campaign=pr+comments&utm_term=None#diff-dGZ0cy9tb2RlbHMvYXV0b19tb2RlbC5weQ==) | `69.23% <100.00%> (ø)` | | | [tfts/models/autoformer.py](https://codecov.io/gh/LongxingTan/Time-series-prediction/pull/26/diff?src=pr&el=tree&utm_medium=referral&utm_source=github&utm_content=comment&utm_campaign=pr+comments&utm_term=None#diff-dGZ0cy9tb2RlbHMvYXV0b2Zvcm1lci5weQ==) | `93.97% <100.00%> (ø)` | | Help us with your feedback. Take ten seconds to tell us [how you rate us](https://about.codecov.io/nps?utm_medium=referral&utm_source=github&utm_content=comment&utm_campaign=pr+comments&utm_term=None). Have a feature suggestion? [Share it here.](https://app.codecov.io/gh/feedback/?utm_medium=referral&utm_source=github&utm_content=comment&utm_campaign=pr+comments&utm_term=None)

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