Support more scipy types. (#9881)

python-package/xgboost/data.py

@@ -57,12 +57,23 @@ def _check_data_shape(data: DataType) -> None:
         raise ValueError("Please reshape the input data into 2-dimensional matrix.")
 
 
-def _is_scipy_csr(data: DataType) -> bool:
+def is_scipy_csr(data: DataType) -> bool:
+    """Predicate for scipy CSR input."""
+    is_array = False
+    is_matrix = False
     try:
-        import scipy.sparse
+        from scipy.sparse import csr_array
+
+        is_array = isinstance(data, csr_array)
     except ImportError:
-        return False
-    return isinstance(data, scipy.sparse.csr_matrix)
+        pass
+    try:
+        from scipy.sparse import csr_matrix
+
+        is_matrix = isinstance(data, csr_matrix)
+    except ImportError:
+        pass
+    return is_array or is_matrix
 
 
 def _array_interface_dict(data: np.ndarray) -> dict:
@@ -135,12 +146,23 @@ def _from_scipy_csr(
     return handle, feature_names, feature_types
 
 
-def _is_scipy_csc(data: DataType) -> bool:
+def is_scipy_csc(data: DataType) -> bool:
+    """Predicate for scipy CSC input."""
+    is_array = False
+    is_matrix = False
     try:
-        import scipy.sparse
+        from scipy.sparse import csc_array
+
+        is_array = isinstance(data, csc_array)
     except ImportError:
-        return False
-    return isinstance(data, scipy.sparse.csc_matrix)
+        pass
+    try:
+        from scipy.sparse import csc_matrix
+
+        is_matrix = isinstance(data, csc_matrix)
+    except ImportError:
+        pass
+    return is_array or is_matrix
 
 
 def _from_scipy_csc(
@@ -171,12 +193,23 @@ def _from_scipy_csc(
     return handle, feature_names, feature_types
 
 
-def _is_scipy_coo(data: DataType) -> bool:
+def is_scipy_coo(data: DataType) -> bool:
+    """Predicate for scipy COO input."""
+    is_array = False
+    is_matrix = False
     try:
-        import scipy.sparse
+        from scipy.sparse import coo_array
+
+        is_array = isinstance(data, coo_array)
     except ImportError:
-        return False
-    return isinstance(data, scipy.sparse.coo_matrix)
+        pass
+    try:
+        from scipy.sparse import coo_matrix
+
+        is_matrix = isinstance(data, coo_matrix)
+    except ImportError:
+        pass
+    return is_array or is_matrix
 
 
 def _is_np_array_like(data: DataType) -> bool:
@@ -1138,15 +1171,15 @@ def dispatch_data_backend(
     """Dispatch data for DMatrix."""
     if not _is_cudf_ser(data) and not _is_pandas_series(data):
         _check_data_shape(data)
-    if _is_scipy_csr(data):
+    if is_scipy_csr(data):
         return _from_scipy_csr(
             data, missing, threads, feature_names, feature_types, data_split_mode
         )
-    if _is_scipy_csc(data):
+    if is_scipy_csc(data):
         return _from_scipy_csc(
             data, missing, threads, feature_names, feature_types, data_split_mode
         )
-    if _is_scipy_coo(data):
+    if is_scipy_coo(data):
         return _from_scipy_csr(
             data.tocsr(),
             missing,
@@ -1396,9 +1429,15 @@ def _proxy_transform(
     if _is_np_array_like(data):
         data, _ = _ensure_np_dtype(data, data.dtype)
         return data, None, feature_names, feature_types
-    if _is_scipy_csr(data):
+    if is_scipy_csr(data):
         data = transform_scipy_sparse(data, True)
         return data, None, feature_names, feature_types
+    if is_scipy_csc(data):
+        data = transform_scipy_sparse(data.tocsr(), True)
+        return data, None, feature_names, feature_types
+    if is_scipy_coo(data):
+        data = transform_scipy_sparse(data.tocsr(), True)
+        return data, None, feature_names, feature_types
     if _is_pandas_series(data):
         import pandas as pd
 
@@ -1451,7 +1490,7 @@ def dispatch_proxy_set_data(
         _check_data_shape(data)
         proxy._set_data_from_array(data)  # pylint: disable=W0212
         return
-    if _is_scipy_csr(data):
+    if is_scipy_csr(data):
         proxy._set_data_from_csr(data)  # pylint: disable=W0212
         return
     raise err