avoid insert getnext op twice when eval or train twice with data sink mode

mindspore/train/dataset_helper.py

@@ -39,6 +39,32 @@ def _send_data_no_flag(dataset, epoch_num):
     exec_dataset.send(epoch_num)
 
 
+class _DataWrapper(nn.Cell):
+    """
+    Wraps the input network with a dataset which automatically fetches data with 'GetNext' function from the
+    dataset channel 'queue_name' and performs the forward computation.
+    """
+
+    def __init__(self, network, dataset_types, dataset_shapes, queue_name):
+        super(_DataWrapper, self).__init__(auto_prefix=False, flags=network.get_flags())
+        # Also copy the flag in `network` construct
+        flags = getattr(network.__class__.construct, "_mindspore_flags", {})
+        self.info = (dataset_types, dataset_shapes)
+        self.add_flags(**flags)
+        self.get_next = P.GetNext(dataset_types, dataset_shapes, len(dataset_types), queue_name)
+        self.network = network
+
+    def construct(self):
+        outputs = self.get_next()
+        return self.network(*outputs)
+
+
+def _generate_dataset_sink_mode_net(network, dataset_shapes, dataset_types, queue_name):
+    if not isinstance(network, _DataWrapper):
+        network = _DataWrapper(network, dataset_types, dataset_shapes, queue_name)
+    return network
+
+
 def connect_network_with_dataset(network, dataset_helper):
     """
     Connect the `network` with dataset in `dataset_helper`.
@@ -70,24 +96,6 @@ def connect_network_with_dataset(network, dataset_helper):
         >>> net_with_get_next = connect_network_with_dataset(net, dataset_helper)
     """
 
-    class _DataWrapper(nn.Cell):
-        """
-        Wraps the input network with a dataset which automatically fetches data with 'GetNext' function from the
-        dataset channel 'queue_name' and performs the forward computation.
-        """
-
-        def __init__(self, network, dataset_types, dataset_shapes, queue_name):
-            super(_DataWrapper, self).__init__(auto_prefix=False, flags=network.get_flags())
-            # Also copy the flag in `network` construct
-            flags = getattr(network.__class__.construct, "_mindspore_flags", {})
-            self.add_flags(**flags)
-            self.get_next = P.GetNext(dataset_types, dataset_shapes, len(dataset_types), queue_name)
-            self.network = network
-
-        def construct(self):
-            outputs = self.get_next()
-            return self.network(*outputs)
-
     dataset_iter = dataset_helper.iter
     dataset = dataset_iter.dataset
 
@@ -98,11 +106,14 @@ def connect_network_with_dataset(network, dataset_helper):
     if ms_role in ("MS_PSERVER", "MS_SCHED"):
         return network
 
-    if (hasattr(dataset_iter, "sink_size") and dataset_iter.sink_size == 1) \
-            and (hasattr(dataset_iter, "sink_count") and dataset_iter.sink_count == 1) \
-            and context.get_context("device_target") == "Ascend" \
-            and context.get_context("mode") == context.GRAPH_MODE \
-            and ms_role != "MS_WORKER":
+    queue_name = dataset.__transfer_dataset__.queue_name
+    if hasattr(dataset_iter, "sink_size") and \
+       dataset_iter.sink_size == 1 and \
+       hasattr(dataset_iter, "sink_count") and \
+       dataset_iter.sink_count == 1 and \
+       context.get_context("device_target") == "Ascend" and \
+       context.get_context("mode") == context.GRAPH_MODE and \
+       ms_role != "MS_WORKER":
 
         if not hasattr(dataset_iter, '__network__'):
             dataset_iter.__network__ = network
@@ -118,21 +129,19 @@ def connect_network_with_dataset(network, dataset_helper):
             if _need_to_full():
                 device_num = _get_device_num()
                 dataset_shapes = _to_full_shapes(dataset_shapes, device_num)
-            network = _DataWrapper(network, dataset_types, dataset_shapes, dataset.__transfer_dataset__.queue_name)
+
+            network = _generate_dataset_sink_mode_net(network, dataset_shapes, dataset_types, queue_name)
             dataset_iter.__network_manage__ = dataset_iter.__network_manage__ if hasattr(
                 dataset_iter, '__network_manage__') else dict()
             dataset_iter.__network_manage__[key] = network
-
         return network
 
-    if not hasattr(dataset, '__me_inited__') and context.get_context("device_target") in ("Ascend", "GPU")\
-        and not context.get_context("enable_ge"):
+    if not hasattr(dataset, '__me_inited__') and \
+       not context.get_context("enable_ge") and \
+       context.get_context("device_target") in ("Ascend", "GPU"):
         dataset.__me_inited__ = True
-
         dataset_types, dataset_shapes = dataset_helper.types_shapes()
-        queue_name = dataset.__transfer_dataset__.queue_name
-
-        network = _DataWrapper(network, dataset_types, dataset_shapes, queue_name)
+        network = _generate_dataset_sink_mode_net(network, dataset_shapes, dataset_types, queue_name)
     return network