[skipci] [Doctest] added contrib metrics AveragePrecision, PrecisionRecallCurve, ROC_AUC and RocCurve

[Ishan-Kumar2]

Addresses #2265

Description:
added doctests for contrib metrics AveragePrecision, PrecisionRecallCurve, ROC_AUC and RocCurve
Not sure about the list of floats outputs, please let me know if there is a better way to handle those.
@ydcjeff @sdesrozis

Check list:

• New tests are added (if a new feature is added)
• New doc strings: description and/or example code are in RST format
• Documentation is updated (if required)

[sdesrozis]

@Ishan-Kumar2 Thanks a lot for your help ! I left some minor comments.

[sdesrozis]

Thinking about it, it is worth to keep the current example to show the way to respect the data format, maybe as a note or an example following the one you did. What do you think ?

Note:
     AveragePrecision expects y to be comprised of 0's and 1's. y_pred must either be probability estimates or confidence values. To apply an activation to y_pred, use output_transform as shown below:

        .. code-block:: python

            def activated_output_transform(output):
                y_pred, y = output
                y_pred = torch.softmax(y_pred, dim=1)
                return y_pred, y

            avg_precision = AveragePrecision(activated_output_transform)

[Ishan-Kumar2]

Yup, makes sense to have it in the docs somewhere, I have added it now!

[sdesrozis]

@Ishan-Kumar2 Thank you ! LGTM