[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/predictor/test_gpu_predictor.cu

@@ -45,7 +45,6 @@ TEST(GPUPredictor, Basic) {
     PredictionCacheEntry cpu_out_predictions;
 
     gpu_predictor->PredictBatch(dmat.get(), &gpu_out_predictions, model, 0);
-    ASSERT_EQ(model.trees.size(), gpu_out_predictions.version);
     cpu_predictor->PredictBatch(dmat.get(), &cpu_out_predictions, model, 0);
 
     std::vector<float>& gpu_out_predictions_h = gpu_out_predictions.predictions.HostVector();