[breaking] Add prediction fucntion for DMatrix and use inplace predict for dask. (#6668)

* Add a new API function for predicting on `DMatrix`.  This function aligns
with rest of the `XGBoosterPredictFrom*` functions on semantic of function
arguments.
* Purge `ntree_limit` from libxgboost, use iteration instead.
* [dask] Use `inplace_predict` by default for dask sklearn models.
* [dask] Run prediction shape inference on worker instead of client.

The breaking change is in the Python sklearn `apply` function, I made it to be
consistent with other prediction functions where `best_iteration` is used by
default.

tests/cpp/test_learner.cc

@@ -221,9 +221,10 @@ TEST(Learner, MultiThreadedPredict) {
       auto &entry = learner->GetThreadLocal().prediction_entry;
       HostDeviceVector<float> predictions;
       for (size_t iter = 0; iter < kIters; ++iter) {
-        learner->Predict(p_data, false, &entry.predictions);
-        learner->Predict(p_data, false, &predictions, 0, true);  // leaf
-        learner->Predict(p_data, false, &predictions, 0, false, true);  // contribs
+        learner->Predict(p_data, false, &entry.predictions, 0, 0);
+
+        learner->Predict(p_data, false, &predictions, 0, 0, false, true);  // leaf
+        learner->Predict(p_data, false, &predictions, 0, 0, false, false, true);  // contribs
       }
     });
   }