Precise the shape of the input arrays of functions in dtw_variants.py

[YannCabanes]

Specify the possible shapes of the input arrays of the metric functions of the file dtw_variants.py in the docstrings. For example:

s1 : array-like, shape=(sz1, d) or (sz1,)
    A time series. If shape is (sz1,), the time series is assumed to be univariate.

or

dataset1 : array-like, shape=(n_ts, sz, d) or (n_ts, sz) or (sz,)
    A dataset of time series. If shape is (n_ts, sz), the dataset is composed of univariate time series. 
    If shape is (sz,), the dataset is a composed of a unique univariate time series.

[codecov-commenter]

Codecov Report

All modified lines are covered by tests :white_check_mark:

Comparison is base (1c4c70c) 93.32% compared to head (f1267ac) 93.33%.

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Additional details and impacted files

```diff @@ Coverage Diff @@ ## main #486 +/- ## ======================================= Coverage 93.32% 93.33% ======================================= Files 67 67 Lines 5727 5732 +5 ======================================= + Hits 5345 5350 +5 Misses 382 382 ``` | [Files](https://app.codecov.io/gh/tslearn-team/tslearn/pull/486?src=pr&el=tree&utm_medium=referral&utm_source=github&utm_content=comment&utm_campaign=pr+comments&utm_term=tslearn-team) | Coverage Δ | | |---|---|---| | [tslearn/metrics/dtw\_variants.py](https://app.codecov.io/gh/tslearn-team/tslearn/pull/486?src=pr&el=tree&utm_medium=referral&utm_source=github&utm_content=comment&utm_campaign=pr+comments&utm_term=tslearn-team#diff-dHNsZWFybi9tZXRyaWNzL2R0d192YXJpYW50cy5weQ==) | `95.73% <100.00%> (+0.03%)` | :arrow_up: |

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