Move Python testing utilities into xgboost module. (#8379)

- Add typehints.
- Fixes for pylint.

Co-authored-by: Hyunsu Philip Cho <chohyu01@cs.washington.edu>

tests/python-gpu/test_gpu_prediction.py

@@ -6,7 +6,7 @@ from hypothesis import assume, given, settings, strategies
 from xgboost.compat import PANDAS_INSTALLED
 
 import xgboost as xgb
-from xgboost import testing
+from xgboost import testing as tm
 
 if PANDAS_INSTALLED:
     from hypothesis.extra.pandas import column, data_frames, range_indexes
@@ -16,7 +16,6 @@ else:
     column, data_frames, range_indexes = noop, noop, noop
 
 sys.path.append("tests/python")
-import testing as tm
 from test_predict import run_predict_leaf  # noqa
 from test_predict import run_threaded_predict  # noqa
 
@@ -33,7 +32,7 @@ predict_parameter_strategy = strategies.fixed_dictionaries({
     'num_parallel_tree': strategies.sampled_from([1, 4]),
 })
 
-pytestmark = testing.timeout(20)
+pytestmark = tm.timeout(20)
 
 
 class TestGPUPredict:
@@ -227,8 +226,8 @@ class TestGPUPredict:
     @pytest.mark.skipif(**tm.no_cupy())
     @pytest.mark.skipif(**tm.no_cudf())
     def test_inplace_predict_cudf(self):
-        import cupy as cp
         import cudf
+        import cupy as cp
         import pandas as pd
         rows = 1000
         cols = 10
@@ -379,8 +378,8 @@ class TestGPUPredict:
     @pytest.mark.skipif(**tm.no_cupy())
     @pytest.mark.parametrize("n_classes", [2, 3])
     def test_predict_dart(self, n_classes):
-        from sklearn.datasets import make_classification
         import cupy as cp
+        from sklearn.datasets import make_classification
         n_samples = 1000
         X_, y_ = make_classification(
             n_samples=n_samples, n_informative=5, n_classes=n_classes