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Multiple lines in Parameter descriptions #7

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@SvenMantowsky

First of all - hats off to you jwlodek. This is almost the only package I found which is working almost perfect.
Not sure if this package is still maintained but i thought I give it a shot:

I converted several files with np docs in them and discovered a problem, where multiple lines of description are split in several lines in the markdown.

Example doc:

Parameters
----------
model_scores_cali: np.ndarray[float]
    2D-Array containing model outputs in form of a specific score (e.g. softmax). 
    The rows correspond to different data-points and the columns correspond to the 
    classes of the classification task. Note that the calibration data should not 
    have been used for model training.
cali_label: np.ndarray[str | int]
    Contains integer or string ground-truth labels. The i-th entry corresponds to
    the i-th row of model_scores_cali.
model_scores_val: np.ndarray[float]
    Contains 'validation' data with same structure as model_scores_cali. Prediction
    sets will be formed for this data.

Result:

Parameters

Parameter Type Doc
model_scores_cali np.ndarray[float] 2D-Array containing model outputs in form of a specific score (e.g. softmax).
Unknown The rows correspond to different data-points and the columns correspond to the classes of the classification task. Note that the calibration data should not
Unknown have been used for model training. cali_label: np.ndarray[str
Unknown Contains integer or string ground-truth labels. The i-th entry corresponds to the i-th row of model_scores_cali.
model_scores_val np.ndarray[float] Contains 'validation' data with same structure as model_scores_cali. Prediction
Unknown sets will be formed for this data. val_label: None
Unknown If the ground-truth labels of model_scores_val are known, they can be used as input here in order to compute the empirical coverage of correct predictions.

If you have an easy fix for this i would appreciate it very much. But if you no longer maintain this repo - maybe you can point me in the direction where to look so i can save some time and create a PR you could maybe approve.

THX and have a nice week.

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