rename input to children, output to parent

mindspore/dataset/engine/iterators.py

@@ -38,13 +38,13 @@ def _cleanup():
 
 def alter_tree(node):
     """Traversing the python Dataset tree/graph to perform some alteration to some specific nodes."""
-    if not node.input:
+    if not node.children:
         return _alter_node(node)
 
     converted_children = []
-    for input_op in node.input:
+    for input_op in node.children:
         converted_children.append(alter_tree(input_op))
-    node.input = converted_children
+    node.children = converted_children
     return _alter_node(node)
 
 
@@ -86,14 +86,14 @@ class Iterator:
 
     def __is_tree_node(self, node):
         """Check if a node is tree node."""
-        if not node.input:
-            if len(node.output) > 1:
+        if not node.children:
+            if len(node.parent) > 1:
                 return False
 
-        if len(node.output) > 1:
+        if len(node.parent) > 1:
             return False
 
-        for input_node in node.input:
+        for input_node in node.children:
             cls = self.__is_tree_node(input_node)
             if not cls:
                 return False
@@ -174,7 +174,7 @@ class Iterator:
         op_type = self.__get_dataset_type(node)
         c_node = self.depipeline.AddNodeToTree(op_type, node.get_args())
 
-        for py_child in node.input:
+        for py_child in node.children:
             c_child = self.__convert_node_postorder(py_child)
             self.depipeline.AddChildToParentNode(c_child, c_node)
 
@@ -184,7 +184,7 @@ class Iterator:
         """Recursively get batch node in the dataset tree."""
         if isinstance(dataset, de.BatchDataset):
             return
-        for input_op in dataset.input:
+        for input_op in dataset.children:
             self.__batch_node(input_op, level + 1)
 
     @staticmethod
@@ -194,11 +194,11 @@ class Iterator:
         ptr = hex(id(dataset))
         for _ in range(level):
             logger.info("\t", end='')
-        if not dataset.input:
+        if not dataset.children:
             logger.info("-%s (%s)", name, ptr)
         else:
             logger.info("+%s (%s)", name, ptr)
-        for input_op in dataset.input:
+        for input_op in dataset.children:
             Iterator.__print_local(input_op, level + 1)
 
     def print(self):

mindspore/dataset/engine/serializer_deserializer.py

@@ -182,11 +182,11 @@ def traverse(node):
             node_repr['shard_id'] = None
 
     # Leaf node doesn't have input attribute.
-    if not node.input:
+    if not node.children:
         return node_repr
 
     # Recursively traverse the child and assign it to the current node_repr['children'].
-    for child in node.input:
+    for child in node.children:
         node_repr["children"].append(traverse(child))
 
     return node_repr
@@ -226,11 +226,11 @@ def construct_pipeline(node):
     # Instantiate python Dataset object based on the current dictionary element
     dataset = create_node(node)
     # Initially it is not connected to any other object.
-    dataset.input = []
+    dataset.children = []
 
     # Construct the children too and add edge between the children and parent.
     for child in node['children']:
-        dataset.input.append(construct_pipeline(child))
+        dataset.children.append(construct_pipeline(child))
 
     return dataset
 

tests/ut/python/dataset/test_iterator.py

@@ -103,7 +103,7 @@ def test_tree_copy():
     itr = data1.create_tuple_iterator()
 
     assert id(data1) != id(itr.dataset)
-    assert id(data) != id(itr.dataset.input[0])
+    assert id(data) != id(itr.dataset.children[0])
     assert id(data1.operations[0]) == id(itr.dataset.operations[0])
 
     itr.release()