[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.

demo/json-model/json_parser.py

@@ -162,9 +162,6 @@ class Model:
 
         # Load the trees
         self.num_trees = int(model_shape["num_trees"])
-        self.leaf_size = int(model_shape["size_leaf_vector"])
-        # Right now XGBoost doesn't support vector leaf yet
-        assert self.leaf_size == 0, str(self.leaf_size)
 
         trees: List[Tree] = []
         for i in range(self.num_trees):