Re-implement ROC-AUC. (#6747)

* Re-implement ROC-AUC.

* Binary
* MultiClass
* LTR
* Add documents.

This PR resolves a few issues:
  - Define a value when the dataset is invalid, which can happen if there's an
  empty dataset, or when the dataset contains only positive or negative values.
  - Define ROC-AUC for multi-class classification.
  - Define weighted average value for distributed setting.
  - A correct implementation for learning to rank task.  Previous
  implementation is just binary classification with averaging across groups,
  which doesn't measure ordered learning to rank.

src/common/math.h

@@ -26,6 +26,9 @@ XGBOOST_DEVICE inline float Sigmoid(float x) {
   return 1.0f / (1.0f + expf(-x));
 }
 
+template <typename T>
+XGBOOST_DEVICE inline static T Sqr(T a) { return a * a; }
+
 /*!
  * \brief Equality test for both integer and floating point.
  */