[MT-TREE] Support prediction cache and model slicing. (#8968)

- Fix prediction range.
- Support prediction cache in mt-hist.
- Support model slicing.
- Make the booster a Python iterable by defining `__iter__`.
- Cleanup removed/deprecated parameters.
- A new field in the output model `iteration_indptr` for pointing to the ranges of trees for each iteration.

tests/cpp/helpers.h

@@ -9,8 +9,10 @@
 #include <xgboost/base.h>
 #include <xgboost/context.h>
 #include <xgboost/json.h>
+#include <xgboost/learner.h>  // for LearnerModelParam
+#include <xgboost/model.h>    // for Configurable
 
-#include <cstdint>  // std::int32_t
+#include <cstdint>            // std::int32_t
 #include <cstdio>
 #include <fstream>
 #include <iostream>
@@ -22,7 +24,6 @@
 #include "../../src/collective/communicator-inl.h"
 #include "../../src/common/common.h"
 #include "../../src/data/array_interface.h"
-#include "../../src/gbm/gbtree_model.h"
 #include "filesystem.h"  // dmlc::TemporaryDirectory
 #include "xgboost/linalg.h"
 
@@ -362,9 +363,6 @@ std::unique_ptr<DMatrix> CreateSparsePageDMatrixWithRC(
     size_t n_rows, size_t n_cols, size_t page_size, bool deterministic,
     const dmlc::TemporaryDirectory& tempdir = dmlc::TemporaryDirectory());
 
-gbm::GBTreeModel CreateTestModel(LearnerModelParam const* param, Context const* ctx,
-                                 size_t n_classes = 1);
-
 std::unique_ptr<GradientBooster> CreateTrainedGBM(std::string name, Args kwargs, size_t kRows,
                                                   size_t kCols,
                                                   LearnerModelParam const* learner_model_param,