[dask] Refactor meta data handling.

python-package/xgboost/dask.py

@@ -213,9 +213,6 @@ def __init__(self,
                 _expect((dd.DataFrame, da.Array, dd.Series), type(label)))
 
         self.worker_map = None
-        self.has_label = label is not None
-        self.has_weights = weight is not None
-
         self.is_quantile = False
 
         self._init = client.sync(self.map_local_data,
@@ -269,14 +266,17 @@ def check_columns(parts):
                 w_parts = w_parts.flatten().tolist()
 
         parts = [X_parts]
+        meta_names = []
         if label is not None:
             assert len(X_parts) == len(
                 y_parts), inconsistent(X_parts, 'X', y_parts, 'labels')
             parts.append(y_parts)
+            meta_names.append('labels')
         if weights is not None:
             assert len(X_parts) == len(
                 w_parts), inconsistent(X_parts, 'X', w_parts, 'weights')
             parts.append(w_parts)
+            meta_names.append('weights')
         parts = list(map(delayed, zip(*parts)))
 
         parts = client.compute(parts)
@@ -298,6 +298,7 @@ def check_columns(parts):
             worker_map[next(iter(workers))].append(key_to_partition[key])
 
         self.worker_map = worker_map
+        self.meta_names = meta_names
 
         return self
 
@@ -308,8 +309,7 @@ def create_fn_args(self):
         '''
         return {'feature_names': self.feature_names,
                 'feature_types': self.feature_types,
-                'has_label': self.has_label,
-                'has_weights': self.has_weights,
+                'meta_names': self.meta_names,
                 'missing': self.missing,
                 'worker_map': self.worker_map,
                 'is_quantile': self.is_quantile}
@@ -326,7 +326,7 @@ def _get_worker_x_ordered(worker_map, partition_order, worker):
     return result
 
 
-def _get_worker_parts(has_label, has_weights, worker_map, worker):
+def _get_worker_parts(worker_map, meta_names, worker):
     '''Get mapped parts of data in each worker from DaskDMatrix.'''
     list_of_parts = worker_map[worker.address]
     assert list_of_parts, 'data in ' + worker.address + ' was moved.'
@@ -336,17 +336,19 @@ def _get_worker_parts(has_label, has_weights, worker_map, worker):
     # this should be equal to `worker._get_client`.
     client = get_client()
     list_of_parts = client.gather(list_of_parts)
+    data = None
+    labels = None
+    weights = None
+
+    local_data = list(zip(*list_of_parts))
+    data = local_data[0]
+
+    for i, part in enumerate(local_data[1:]):
+        if meta_names[i] == 'labels':
+            labels = part
+        if meta_names[i] == 'weights':
+            weights = part
 
-    if has_label:
-        if has_weights:
-            data, labels, weights = zip(*list_of_parts)
-        else:
-            data, labels = zip(*list_of_parts)
-            weights = None
-    else:
-        data = [d[0] for d in list_of_parts]
-        labels = None
-        weights = None
     return data, labels, weights
 
 
@@ -473,8 +475,7 @@ def create_fn_args(self):
 
 
 def _create_device_quantile_dmatrix(feature_names, feature_types,
-                                    has_label,
-                                    has_weights, missing, worker_map,
+                                    meta_names, missing, worker_map,
                                     max_bin):
     worker = distributed_get_worker()
     if worker.address not in set(worker_map.keys()):
@@ -490,8 +491,7 @@ def _create_device_quantile_dmatrix(feature_names, feature_types,
                                   max_bin=max_bin)
         return d
 
-    data, labels, weights = _get_worker_parts(has_label, has_weights,
-                                              worker_map, worker)
+    data, labels, weights = _get_worker_parts(worker_map, meta_names, worker)
     it = DaskPartitionIter(data=data, label=labels, weight=weights)
 
     dmatrix = DeviceQuantileDMatrix(it,
@@ -503,8 +503,8 @@ def _create_device_quantile_dmatrix(feature_names, feature_types,
     return dmatrix
 
 
-def _create_dmatrix(feature_names, feature_types, has_label,
-                    has_weights, missing, worker_map):
+def _create_dmatrix(feature_names, feature_types, meta_names, missing,
+                    worker_map):
     '''Get data that local to worker from DaskDMatrix.
 
       Returns
@@ -524,18 +524,13 @@ def _create_dmatrix(feature_names, feature_types, has_label,
                     feature_types=feature_types)
         return d
 
-    data, labels, weights = _get_worker_parts(has_label, has_weights,
-                                              worker_map, worker)
+    data, labels, weights = _get_worker_parts(worker_map, meta_names, worker)
     data = concat(data)
 
-    if has_label:
+    if labels:
         labels = concat(labels)
-    else:
-        labels = None
-    if has_weights:
+    if weights:
         weights = concat(weights)
-    else:
-        weights = None
     dmatrix = DMatrix(data,
                       labels,
                       weight=weights,