Obtain CSR matrix from DMatrix. (#8269)

tests/python/test_dmatrix.py

@@ -1,13 +1,14 @@
-# -*- coding: utf-8 -*-
 import os
 import tempfile
-import numpy as np
-import xgboost as xgb
-import scipy.sparse
-import pytest
-from scipy.sparse import rand, csr_matrix
 
+import numpy as np
+import pytest
+import scipy.sparse
 import testing as tm
+from hypothesis import given, settings, strategies
+from scipy.sparse import csr_matrix, rand
+
+import xgboost as xgb
 
 rng = np.random.RandomState(1)
 
@@ -433,3 +434,22 @@ class TestDMatrix:
 
     def test_base_margin(self):
         set_base_margin_info(np.asarray, xgb.DMatrix, "hist")
+
+    @given(
+        strategies.integers(0, 1000),
+        strategies.integers(0, 100),
+        strategies.fractions(0, 1),
+    )
+    @settings(deadline=None, print_blob=True)
+    def test_to_csr(self, n_samples, n_features, sparsity) -> None:
+        if n_samples == 0 or n_features == 0 or sparsity == 1.0:
+            csr = scipy.sparse.csr_matrix(np.empty((0, 0)))
+        else:
+            csr = tm.make_sparse_regression(n_samples, n_features, sparsity, False)[
+                0
+            ].astype(np.float32)
+        m = xgb.DMatrix(data=csr)
+        ret = m.get_data()
+        np.testing.assert_equal(csr.indptr, ret.indptr)
+        np.testing.assert_equal(csr.data, ret.data)
+        np.testing.assert_equal(csr.indices, ret.indices)