Support scipy sparse in dask. (#7457)

python-package/xgboost/compat.py

@@ -112,12 +112,10 @@ except pkg_resources.DistributionNotFound:
 
 
 try:
-    import sparse
     import scipy.sparse as scipy_sparse
     from scipy.sparse import csr_matrix as scipy_csr
     SCIPY_INSTALLED = True
 except ImportError:
-    sparse = False
     scipy_sparse = False
     scipy_csr: Any = object
     SCIPY_INSTALLED = False

python-package/xgboost/dask.py

@@ -33,7 +33,7 @@ from . import rabit, config
 from .callback import TrainingCallback
 
 from .compat import LazyLoader
-from .compat import sparse, scipy_sparse
+from .compat import scipy_sparse
 from .compat import PANDAS_INSTALLED, DataFrame, Series, pandas_concat
 from .compat import lazy_isinstance
 
@@ -186,10 +186,13 @@ def concat(value: Any) -> Any:  # pylint: disable=too-many-return-statements
     '''To be replaced with dask builtin.'''
     if isinstance(value[0], numpy.ndarray):
         return numpy.concatenate(value, axis=0)
+    if scipy_sparse and isinstance(value[0], scipy_sparse.csr_matrix):
+        return scipy_sparse.vstack(value, format="csr")
+    if scipy_sparse and isinstance(value[0], scipy_sparse.csc_matrix):
+        return scipy_sparse.vstack(value, format="csc")
     if scipy_sparse and isinstance(value[0], scipy_sparse.spmatrix):
+        # other sparse format will be converted to CSR.
         return scipy_sparse.vstack(value, format='csr')
-    if sparse and isinstance(value[0], sparse.SparseArray):
-        return sparse.concatenate(value, axis=0)
     if PANDAS_INSTALLED and isinstance(value[0], (DataFrame, Series)):
         return pandas_concat(value, axis=0)
     if lazy_isinstance(value[0], 'cudf.core.dataframe', 'DataFrame') or \