Restore unknown data support. (#6595)

python-package/xgboost/core.py

@@ -262,25 +262,6 @@ def c_array(ctype, values):
     return (ctype * len(values))(*values)
 
 
-def _convert_unknown_data(data, meta=None, meta_type=None):
-    if meta is not None:
-        try:
-            data = np.array(data, dtype=meta_type)
-        except Exception as e:
-            raise TypeError('Can not handle data from {}'.format(
-                type(data).__name__)) from e
-    else:
-        warnings.warn(
-            'Unknown data type: ' + str(type(data)) +
-            ', coverting it to csr_matrix')
-        try:
-            data = scipy.sparse.csr_matrix(data)
-        except Exception as e:
-            raise TypeError('Can not initialize DMatrix from'
-                            ' {}'.format(type(data).__name__)) from e
-    return data
-
-
 class DataIter:
     '''The interface for user defined data iterator. Currently is only
     supported by Device DMatrix.
@@ -542,7 +523,7 @@ class DMatrix:                  # pylint: disable=too-many-instance-attributes
         if group is not None:
             self.set_group(group)
         if qid is not None:
-            dispatch_meta_backend(matrix=self, data=qid, name='qid')
+            self.set_uint_info('qid', qid)
         if label_lower_bound is not None:
             self.set_float_info('label_lower_bound', label_lower_bound)
         if label_upper_bound is not None:

python-package/xgboost/data.py

@@ -517,6 +517,24 @@ def _has_array_protocol(data):
     return hasattr(data, '__array__')
 
 
+def _convert_unknown_data(data):
+    warnings.warn(
+        f'Unknown data type: {type(data)}, trying to convert it to csr_matrix',
+        UserWarning
+    )
+    try:
+        import scipy
+    except ImportError:
+        return None
+
+    try:
+        data = scipy.sparse.csr_matrix(data)
+    except Exception:           # pylint: disable=broad-except
+        return None
+
+    return data
+
+
 def dispatch_data_backend(data, missing, threads,
                           feature_names, feature_types,
                           enable_categorical=False):
@@ -570,6 +588,11 @@ def dispatch_data_backend(data, missing, threads,
                                    feature_types)
     if _has_array_protocol(data):
         pass
+
+    converted = _convert_unknown_data(data)
+    if converted:
+        return _from_scipy_csr(data, missing, feature_names, feature_types)
+
     raise TypeError('Not supported type for data.' + str(type(data)))
 
 

python-package/xgboost/tracker.py

@@ -63,8 +63,9 @@ def get_host_ip(hostIP=None):
         try:
             hostIP = socket.gethostbyname(socket.getfqdn())
         except gaierror:
-            logging.warning(
+            logging.debug(
-                'gethostbyname(socket.getfqdn()) failed... trying on hostname()')
+                'gethostbyname(socket.getfqdn()) failed... trying on hostname()'
+            )
             hostIP = socket.gethostbyname(socket.gethostname())
         if hostIP.startswith("127."):
             s = socket.socket(socket.AF_INET, socket.SOCK_DGRAM)

tests/python/test_dmatrix.py

@@ -296,3 +296,12 @@ class TestDMatrix:
         param = {'max_depth': 3, 'objective': 'binary:logistic', 'verbosity': 0}
         bst = xgb.train(param, dtrain, 5, watchlist)
         bst.predict(dtrain)
+
+    def test_unknown_data(self):
+        class Data:
+            pass
+
+        with pytest.raises(TypeError):
+            with pytest.warns(UserWarning):
+                d = Data()
+                xgb.DMatrix(d)