Cast the input data to backend option and test functions in metrics for different input data types and different backend options.

[YannCabanes]

In the functions of the folder tslearn/metrics supporting the backend optional input parameter be, cast the input data to the backend option when possible (using be.array). Test the functions of the file test_metrics.py for different input data types (list, numpy, pytorch) and different backend options (numpy, pytorch, None). Two nested for loops are used.

Therefore the following generic metric function is tested for different input data types and backend options:

def metric_function(s1, s2, be=None):
    be = instantiate_backend(be, s1, s2)
    s1 = be.array(s1)
    s2 = be.array(s2)
    ...

[codecov-commenter]

Codecov Report

Patch coverage: 99.46% and project coverage change: +0.10% :tada:

Comparison is base (cac29f5) 92.79% compared to head (78517d9) 92.90%.

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Additional details and impacted files

```diff @@ Coverage Diff @@ ## main #479 +/- ## ========================================== + Coverage 92.79% 92.90% +0.10% ========================================== Files 67 67 Lines 5583 5680 +97 ========================================== + Hits 5181 5277 +96 - Misses 402 403 +1 ``` | [Files Changed](https://app.codecov.io/gh/tslearn-team/tslearn/pull/479?src=pr&el=tree&utm_medium=referral&utm_source=github&utm_content=comment&utm_campaign=pr+comments&utm_term=tslearn-team) | Coverage Δ | | |---|---|---| | [tslearn/tests/test\_metrics.py](https://app.codecov.io/gh/tslearn-team/tslearn/pull/479?src=pr&el=tree&utm_medium=referral&utm_source=github&utm_content=comment&utm_campaign=pr+comments&utm_term=tslearn-team#diff-dHNsZWFybi90ZXN0cy90ZXN0X21ldHJpY3MucHk=) | `99.21% <99.36%> (-0.15%)` | :arrow_down: | | [tslearn/backend/\_\_init\_\_.py](https://app.codecov.io/gh/tslearn-team/tslearn/pull/479?src=pr&el=tree&utm_medium=referral&utm_source=github&utm_content=comment&utm_campaign=pr+comments&utm_term=tslearn-team#diff-dHNsZWFybi9iYWNrZW5kL19faW5pdF9fLnB5) | `100.00% <100.00%> (ø)` | | | [tslearn/backend/backend.py](https://app.codecov.io/gh/tslearn-team/tslearn/pull/479?src=pr&el=tree&utm_medium=referral&utm_source=github&utm_content=comment&utm_campaign=pr+comments&utm_term=tslearn-team#diff-dHNsZWFybi9iYWNrZW5kL2JhY2tlbmQucHk=) | `85.71% <100.00%> (+3.89%)` | :arrow_up: | | [tslearn/backend/numpy\_backend.py](https://app.codecov.io/gh/tslearn-team/tslearn/pull/479?src=pr&el=tree&utm_medium=referral&utm_source=github&utm_content=comment&utm_campaign=pr+comments&utm_term=tslearn-team#diff-dHNsZWFybi9iYWNrZW5kL251bXB5X2JhY2tlbmQucHk=) | `94.11% <100.00%> (+0.17%)` | :arrow_up: | | [tslearn/backend/pytorch\_backend.py](https://app.codecov.io/gh/tslearn-team/tslearn/pull/479?src=pr&el=tree&utm_medium=referral&utm_source=github&utm_content=comment&utm_campaign=pr+comments&utm_term=tslearn-team#diff-dHNsZWFybi9iYWNrZW5kL3B5dG9yY2hfYmFja2VuZC5weQ==) | `75.98% <100.00%> (+0.35%)` | :arrow_up: | | [tslearn/metrics/dtw\_variants.py](https://app.codecov.io/gh/tslearn-team/tslearn/pull/479?src=pr&el=tree&utm_medium=referral&utm_source=github&utm_content=comment&utm_campaign=pr+comments&utm_term=tslearn-team#diff-dHNsZWFybi9tZXRyaWNzL2R0d192YXJpYW50cy5weQ==) | `95.52% <100.00%> (+0.03%)` | :arrow_up: | | [tslearn/metrics/softdtw\_variants.py](https://app.codecov.io/gh/tslearn-team/tslearn/pull/479?src=pr&el=tree&utm_medium=referral&utm_source=github&utm_content=comment&utm_campaign=pr+comments&utm_term=tslearn-team#diff-dHNsZWFybi9tZXRyaWNzL3NvZnRkdHdfdmFyaWFudHMucHk=) | `93.90% <100.00%> (+0.19%)` | :arrow_up: |

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