datavisual: reconstruct debugger graph

mindinsight/datavisual/data_transform/graph/graph.py

@@ -52,6 +52,9 @@ class Graph:
         self._const_node_temp_cache = {}
         self._parameter_node_temp_cache = {}
 
+        self._leaf_nodes = {}
+        self._full_name_map_name = {}
+
     def build_graph(self, proto_data):
         """This method is used to build the graph."""
         logger.info("Start to build graph")
@@ -68,6 +71,8 @@ class Graph:
         # Since const nodes are not aggregated, adding them at the end can save a lot of computation.
         self._add_variable_nodes(NodeTypeEnum.CONST.value)
         self._calc_subnode_count()
+        self._leaf_nodes = self._get_leaf_nodes()
+        self._full_name_map_name = self._get_leaf_node_full_name_map()
 
         precision = 6
         time_consuming = round(time.time() - start_time, precision)
@@ -75,6 +80,32 @@ class Graph:
                     self.normal_node_count, len(self._const_node_temp_cache),
                     len(self._parameter_node_temp_cache), time_consuming)
 
+    def _get_leaf_nodes(self):
+        """
+        Get all leaf nodes, including normal leaf nodes, const nodes and param nodes.
+        """
+        leaf_nodes = {}
+        for node_name, node in self._normal_node_map.items():
+            # update full name
+            if not node.full_name:
+                node.full_name = node.name
+            if not node.type or node.type.endswith('_scope'):
+                continue
+            leaf_nodes[node_name] = node
+
+        return leaf_nodes
+
+    def _get_leaf_node_full_name_map(self):
+        """Get node by debugger name."""
+        full_name_map = {}
+        for name, node in self._leaf_nodes.items():
+            if not node.full_name:
+                logger.warning("Node %s does not have full name.", name)
+                continue
+            full_name_map[node.full_name] = name
+
+        return full_name_map
+
     def exist_node(self, name):
         """
         Check node exist in graph.

mindinsight/datavisual/data_transform/graph/msgraph.py

@@ -64,6 +64,7 @@ class MSGraph(Graph):
             else:
                 node_name = node_proto.full_name
             node = Node(name=node_name, node_id=node_proto.name)
+            node.full_name = node_proto.full_name
             node.type = node_proto.op_type
 
             self._parse_attributes(node_proto.attribute, node)
@@ -72,7 +73,8 @@ class MSGraph(Graph):
             node.output_i = node_proto.output_i
             node.scope = node_proto.scope
             node.output_shape = self._get_shape_by_parse_type_proto(node_proto.output_type)
-            node.output_data_type = self._get_data_type_by_parse_type_proto(node_proto.output_type)
+            node.output_nums = len(node.output_shape)
+            node.output_data_type = self._get_data_type_by_parse_type_proto(node_proto.output_type, node)
 
             self._cache_node(node)
 
@@ -90,10 +92,11 @@ class MSGraph(Graph):
                 continue
             node = Node(name=parameter.name, node_id=parameter.name)
             node.type = NodeTypeEnum.PARAMETER.value
-            node.output_data_type = self._get_data_type_by_parse_type_proto(parameter.type)
             node.output_shape = self._get_shape_by_parse_type_proto(parameter.type)
+            node.output_nums = len(node.output_shape)
+            node.output_data_type = self._get_data_type_by_parse_type_proto(parameter.type, node)
             attr = dict(
-                type=self._get_data_type_by_parse_type_proto(parameter.type),
+                type=self._get_data_type_by_parse_type_proto(parameter.type, node),
                 shape=str(self._get_shape_by_parse_type_proto(parameter.type))
             )
             node.add_attr(attr)
@@ -117,11 +120,18 @@ class MSGraph(Graph):
             node = Node(name=const.key, node_id=const.key)
             node.type = NodeTypeEnum.CONST.value
             node.add_attr({const.key: str(const.value)})
+
             if const.value.dtype == DataType.DT_TENSOR:
-                shape = []
-                for dim in const.value.tensor_val.dims:
-                    shape.append(dim)
-                node.output_shape = shape
+                shape = list(const.value.tensor_val.dims)
+                node.output_shape.append(shape)
+                if const.value.tensor_val.HasField('data_type'):
+                    node.elem_types.append(DataType.Name(const.value.tensor_val.data_type))
+            else:
+                node.elem_types.append(DataType.Name(const.value.dtype))
+                # dim is zero
+                node.output_shape.append([])
+
+            node.output_nums = len(node.output_shape)
 
             self._cache_node(node)
 
@@ -136,17 +146,24 @@ class MSGraph(Graph):
             list, a list of shape.
         """
         shapes = []
+        if type_proto.HasField('data_type'):
+            if type_proto.data_type != DataType.DT_TENSOR and \
+                    type_proto.data_type != DataType.DT_TUPLE:
+                # Append an empty list as a placeholder
+                # for the convenience of output number calculation.
+                shapes.append([])
+                return shapes
         if type_proto.HasField('tensor_type'):
             tensor_type = type_proto.tensor_type
             tensor_shape_proto = tensor_type.shape
-            for dim in tensor_shape_proto.dim:
-                shapes.append(dim.size)
+            shape = [dim.size for dim in tensor_shape_proto.dim]
+            shapes.append(shape)
         if type_proto.HasField('sequence_type'):
             for elem_type in type_proto.sequence_type.elem_types:
-                shapes.append(self._get_shape_by_parse_type_proto(elem_type))
+                shapes.extend(self._get_shape_by_parse_type_proto(elem_type))
         return shapes
 
-    def _get_data_type_by_parse_type_proto(self, type_proto):
+    def _get_data_type_by_parse_type_proto(self, type_proto, node):
         """
         Get data type by parse type proto object.
 
@@ -165,14 +182,17 @@ class MSGraph(Graph):
             tensor_type_proto = type_proto.tensor_type
             value = type_proto.tensor_type.elem_type
             elem_type_name = self._get_data_type_name_by_value(tensor_type_proto, value, field_name='elem_type')
+            node.elem_types.append(elem_type_name)
             return f'{data_type_name}[{elem_type_name}]'
 
         if type_proto.data_type == DataType.DT_TUPLE:
             data_types = []
             for elem_type in type_proto.sequence_type.elem_types:
-                data_types.append(self._get_data_type_by_parse_type_proto(elem_type))
+                data_types.append(self._get_data_type_by_parse_type_proto(elem_type, node))
             return f'{data_type_name}{str(data_types)}'
 
+        node.elem_types.append(data_type_name)
+
         return data_type_name
 
     def _parse_inputs(self, input_protos, node):

mindinsight/datavisual/data_transform/graph/node.py

@@ -50,6 +50,9 @@ class Node:
         self.independent_layout = False
         self.output_shape = []
         self.output_data_type = ""
+        self.output_nums = 0
+        self.elem_types = []
+        self.full_name = ""
 
     def to_dict(self):
         """Converts the node object to dictionary format."""
@@ -208,6 +211,7 @@ class Node:
             src_node (Node): The copied node.
             dst_node (Node): The destination node.
         """
+        dst_node.full_name = src_node.full_name
         dst_node.type = src_node.type
         dst_node.output_i = src_node.output_i
         dst_node.subnode_count = src_node.subnode_count
@@ -215,6 +219,8 @@ class Node:
         dst_node.independent_layout = src_node.independent_layout
         dst_node.output_shape = src_node.output_shape
         dst_node.output_data_type = src_node.output_data_type
+        dst_node.output_nums = src_node.output_nums
+        dst_node.elem_types = src_node.elem_types
         dst_node.add_attr(src_node.attr)
 
     def __str__(self):

tests/st/func/datavisual/graph/graph_results/test_query_nodes_success_result2.json

@@ -1 +1 @@
-{"nodes":[{"attr":{},"independent_layout":false,"input":{},"name":"Default/conv1-Conv2d","output":{"Default/bn1/Reshape[12]_1/Reshape6":{"data_type":"DT_STRING","edge_type":"data","independent_layout":false,"shape":[1,64,112,112]}},"output_i":0,"proxy_input":{},"proxy_output":{},"subnode_count":2,"type":"name_scope"},{"attr":{},"independent_layout":false,"input":{},"name":"Default/bn1-BatchNorm2d","output":{"Default/bn1/Add[5]_0/Add53":{"data_type":"DT_STRING","edge_type":"data","independent_layout":false,"shape":[1,128,28,28]}},"output_i":0,"proxy_input":{},"proxy_output":{},"subnode_count":5,"type":"name_scope"},{"attr":{},"independent_layout":false,"input":{"Default/bn1-BatchNorm2d/tuple_getitem56":{"data_type":"DT_STRING","edge_type":"data","independent_layout":false,"shape":[1,128,28,28]},"Default/conv1-Conv2d/Conv2D55":{"data_type":"DT_STRING","edge_type":"data","independent_layout":false,"shape":[1,64,112,112]}},"name":"Default/bn1","output":{},"output_i":0,"proxy_input":{},"proxy_output":{},"subnode_count":4,"type":"name_scope"}]}
+{"nodes": [{"name": "Default/conv1-Conv2d", "type": "name_scope", "attr": {}, "input": {}, "output": {"Default/bn1/Reshape[12]_1/Reshape6": {"shape": [[]], "edge_type": "data", "independent_layout": false, "data_type": "DT_STRING"}}, "output_i": 0, "proxy_input": {}, "proxy_output": {}, "subnode_count": 2, "independent_layout": false}, {"name": "Default/bn1-BatchNorm2d", "type": "name_scope", "attr": {}, "input": {}, "output": {"Default/bn1/Add[5]_0/Add53": {"shape": [[]], "edge_type": "data", "independent_layout": false, "data_type": "DT_STRING"}}, "output_i": 0, "proxy_input": {}, "proxy_output": {}, "subnode_count": 5, "independent_layout": false}, {"name": "Default/bn1", "type": "name_scope", "attr": {}, "input": {"Default/bn1-BatchNorm2d/tuple_getitem56": {"shape": [[]], "edge_type": "data", "independent_layout": false, "data_type": "DT_STRING"}, "Default/conv1-Conv2d/Conv2D55": {"shape": [[]], "edge_type": "data", "independent_layout": false, "data_type": "DT_STRING"}}, "output": {}, "output_i": 0, "proxy_input": {}, "proxy_output": {}, "subnode_count": 4, "independent_layout": false}]}

tests/st/func/datavisual/graph/graph_results/test_query_nodes_success_result3.json

@@ -1 +1 @@
-{"nodes":[{"name":"Default/bn1/Reshape[12]_1/Reshape1","type":"Reshape","attr":{},"input":{"Default/bn1/Add[5]_0/Add50":{"shape":[1,1024,14,14],"edge_type":"data","independent_layout":false,"data_type":"DT_STRING"}},"output":{},"output_i":0,"proxy_input":{},"proxy_output":{},"subnode_count":0,"independent_layout":false},{"name":"Default/bn1/Reshape[12]_1/Reshape2","type":"Reshape","attr":{},"input":{"Default/bn1/Add[5]_0/Add51":{"shape":[1,1024,14,14],"edge_type":"data","independent_layout":false,"data_type":"DT_STRING"}},"output":{},"output_i":0,"proxy_input":{},"proxy_output":{},"subnode_count":0,"independent_layout":false},{"name":"Default/bn1/Reshape[12]_1/Reshape3","type":"Reshape","attr":{},"input":{"Default/bn1/Add[5]_0/Add52":{"shape":[1,1024,14,14],"edge_type":"data","independent_layout":false,"data_type":"DT_STRING"}},"output":{},"output_i":0,"proxy_input":{},"proxy_output":{},"subnode_count":0,"independent_layout":false},{"name":"Default/bn1/Reshape[12]_1/Reshape4","type":"Reshape","attr":{},"input":{"Default/bn1/Add[5]_0/Add53":{"shape":[1,1024,14,14],"edge_type":"data","independent_layout":false,"data_type":"DT_STRING"}},"output":{},"output_i":0,"proxy_input":{},"proxy_output":{},"subnode_count":0,"independent_layout":false},{"name":"Default/bn1/Reshape[12]_1/Reshape5","type":"Reshape","attr":{},"input":{"Default/bn1/Add[5]_0/Add54":{"shape":[1,1024,14,14],"edge_type":"data","independent_layout":false,"data_type":"DT_STRING"}},"output":{},"output_i":0,"proxy_input":{},"proxy_output":{},"subnode_count":0,"independent_layout":false},{"name":"Default/bn1/Reshape[12]_1/Reshape6","type":"Reshape","attr":{},"input":{"Default/conv1-Conv2d/Conv2D55":{"shape":[1,64,112,112],"edge_type":"data","independent_layout":false,"data_type":"DT_STRING"}},"output":{},"output_i":0,"proxy_input":{},"proxy_output":{},"subnode_count":0,"independent_layout":false},{"name":"Default/bn1/Reshape[12]_1/Reshape7","type":"Reshape","attr":{},"input":{"Default/bn1/x":{"shape":[1,3,224,224],"edge_type":"data","independent_layout":false,"data_type":"DT_STRING"}},"output":{},"output_i":0,"proxy_input":{},"proxy_output":{},"subnode_count":0,"independent_layout":false},{"name":"Default/bn1/Reshape[12]_1/Reshape8","type":"Reshape","attr":{},"input":{"Default/bn1/x":{"shape":[1,3,224,224],"edge_type":"data","independent_layout":false,"data_type":"DT_STRING"}},"output":{},"output_i":0,"proxy_input":{},"proxy_output":{},"subnode_count":0,"independent_layout":false},{"name":"Default/bn1/Reshape[12]_1/Reshape9","type":"Reshape","attr":{},"input":{"Default/bn1/x":{"shape":[1,3,224,224],"edge_type":"data","independent_layout":false,"data_type":"DT_STRING"}},"output":{},"output_i":0,"proxy_input":{},"proxy_output":{},"subnode_count":0,"independent_layout":false},{"name":"Default/bn1/Reshape[12]_1/Reshape10","type":"Reshape","attr":{},"input":{"Default/bn1/x":{"shape":[1,3,224,224],"edge_type":"data","independent_layout":false,"data_type":"DT_STRING"}},"output":{},"output_i":0,"proxy_input":{},"proxy_output":{},"subnode_count":0,"independent_layout":false},{"name":"Default/bn1/Reshape[12]_1/Reshape11","type":"Reshape","attr":{},"input":{"Default/bn1/x":{"shape":[1,3,224,224],"edge_type":"data","independent_layout":false,"data_type":"DT_STRING"}},"output":{},"output_i":0,"proxy_input":{},"proxy_output":{},"subnode_count":0,"independent_layout":false},{"name":"Default/bn1/Reshape[12]_1/Reshape12","type":"Reshape","attr":{},"input":{"Default/bn1/x":{"shape":[1,3,224,224],"edge_type":"data","independent_layout":false,"data_type":"DT_STRING"}},"output":{},"output_i":0,"proxy_input":{},"proxy_output":{},"subnode_count":0,"independent_layout":false}]}
+{"nodes": [{"name": "Default/bn1/Reshape[12]_1/Reshape1", "type": "Reshape", "attr": {}, "input": {"Default/bn1/Add[5]_0/Add50": {"shape": [[]], "edge_type": "data", "independent_layout": false, "data_type": "DT_STRING"}}, "output": {}, "output_i": 0, "proxy_input": {}, "proxy_output": {}, "subnode_count": 0, "independent_layout": false}, {"name": "Default/bn1/Reshape[12]_1/Reshape2", "type": "Reshape", "attr": {}, "input": {"Default/bn1/Add[5]_0/Add51": {"shape": [[]], "edge_type": "data", "independent_layout": false, "data_type": "DT_STRING"}}, "output": {}, "output_i": 0, "proxy_input": {}, "proxy_output": {}, "subnode_count": 0, "independent_layout": false}, {"name": "Default/bn1/Reshape[12]_1/Reshape3", "type": "Reshape", "attr": {}, "input": {"Default/bn1/Add[5]_0/Add52": {"shape": [[]], "edge_type": "data", "independent_layout": false, "data_type": "DT_STRING"}}, "output": {}, "output_i": 0, "proxy_input": {}, "proxy_output": {}, "subnode_count": 0, "independent_layout": false}, {"name": "Default/bn1/Reshape[12]_1/Reshape4", "type": "Reshape", "attr": {}, "input": {"Default/bn1/Add[5]_0/Add53": {"shape": [[]], "edge_type": "data", "independent_layout": false, "data_type": "DT_STRING"}}, "output": {}, "output_i": 0, "proxy_input": {}, "proxy_output": {}, "subnode_count": 0, "independent_layout": false}, {"name": "Default/bn1/Reshape[12]_1/Reshape5", "type": "Reshape", "attr": {}, "input": {"Default/bn1/Add[5]_0/Add54": {"shape": [[]], "edge_type": "data", "independent_layout": false, "data_type": "DT_STRING"}}, "output": {}, "output_i": 0, "proxy_input": {}, "proxy_output": {}, "subnode_count": 0, "independent_layout": false}, {"name": "Default/bn1/Reshape[12]_1/Reshape6", "type": "Reshape", "attr": {}, "input": {"Default/conv1-Conv2d/Conv2D55": {"shape": [[]], "edge_type": "data", "independent_layout": false, "data_type": "DT_STRING"}}, "output": {}, "output_i": 0, "proxy_input": {}, "proxy_output": {}, "subnode_count": 0, "independent_layout": false}, {"name": "Default/bn1/Reshape[12]_1/Reshape7", "type": "Reshape", "attr": {}, "input": {"Default/bn1/x": {"shape": [[]], "edge_type": "data", "independent_layout": false, "data_type": "DT_STRING"}}, "output": {}, "output_i": 0, "proxy_input": {}, "proxy_output": {}, "subnode_count": 0, "independent_layout": false}, {"name": "Default/bn1/Reshape[12]_1/Reshape8", "type": "Reshape", "attr": {}, "input": {"Default/bn1/x": {"shape": [[]], "edge_type": "data", "independent_layout": false, "data_type": "DT_STRING"}}, "output": {}, "output_i": 0, "proxy_input": {}, "proxy_output": {}, "subnode_count": 0, "independent_layout": false}, {"name": "Default/bn1/Reshape[12]_1/Reshape9", "type": "Reshape", "attr": {}, "input": {"Default/bn1/x": {"shape": [[]], "edge_type": "data", "independent_layout": false, "data_type": "DT_STRING"}}, "output": {}, "output_i": 0, "proxy_input": {}, "proxy_output": {}, "subnode_count": 0, "independent_layout": false}, {"name": "Default/bn1/Reshape[12]_1/Reshape10", "type": "Reshape", "attr": {}, "input": {"Default/bn1/x": {"shape": [[]], "edge_type": "data", "independent_layout": false, "data_type": "DT_STRING"}}, "output": {}, "output_i": 0, "proxy_input": {}, "proxy_output": {}, "subnode_count": 0, "independent_layout": false}, {"name": "Default/bn1/Reshape[12]_1/Reshape11", "type": "Reshape", "attr": {}, "input": {"Default/bn1/x": {"shape": [[]], "edge_type": "data", "independent_layout": false, "data_type": "DT_STRING"}}, "output": {}, "output_i": 0, "proxy_input": {}, "proxy_output": {}, "subnode_count": 0, "independent_layout": false}, {"name": "Default/bn1/Reshape[12]_1/Reshape12", "type": "Reshape", "attr": {}, "input": {"Default/bn1/x": {"shape": [[]], "edge_type": "data", "independent_layout": false, "data_type": "DT_STRING"}}, "output": {}, "output_i": 0, "proxy_input": {}, "proxy_output": {}, "subnode_count": 0, "independent_layout": false}]}

tests/st/func/datavisual/graph/graph_results/test_query_single_node_success_result1.json

@@ -1 +1 @@
-{"children":{"children":{},"nodes":[{"attr":{},"independent_layout":false,"input":{},"name":"Default/conv1-Conv2d","output":{"Default/bn1/Reshape[12]_1/Reshape6":{"data_type":"DT_STRING","edge_type":"data","independent_layout":false,"shape":[1,64,112,112]}},"output_i":0,"proxy_input":{},"proxy_output":{},"subnode_count":2,"type":"name_scope"},{"attr":{},"independent_layout":false,"input":{},"name":"Default/bn1-BatchNorm2d","output":{"Default/bn1/Add[5]_0/Add53":{"data_type":"DT_STRING","edge_type":"data","independent_layout":false,"shape":[1,128,28,28]}},"output_i":0,"proxy_input":{},"proxy_output":{},"subnode_count":5,"type":"name_scope"},{"attr":{},"independent_layout":false,"input":{"Default/bn1-BatchNorm2d/tuple_getitem56":{"data_type":"DT_STRING","edge_type":"data","independent_layout":false,"shape":[1,128,28,28]},"Default/conv1-Conv2d/Conv2D55":{"data_type":"DT_STRING","edge_type":"data","independent_layout":false,"shape":[1,64,112,112]}},"name":"Default/bn1","output":{},"output_i":0,"proxy_input":{},"proxy_output":{},"subnode_count":4,"type":"name_scope"}],"scope_name":"Default"},"nodes":[{"attr":{},"independent_layout":false,"input":{},"name":"Default","output":{},"output_i":0,"proxy_input":{},"proxy_output":{},"subnode_count":3,"type":"name_scope"}],"scope_name":""}
+{"nodes": [{"name": "Default", "type": "name_scope", "attr": {}, "input": {}, "output": {}, "output_i": 0, "proxy_input": {}, "proxy_output": {}, "subnode_count": 3, "independent_layout": false}], "scope_name": "", "children": {"nodes": [{"name": "Default/conv1-Conv2d", "type": "name_scope", "attr": {}, "input": {}, "output": {"Default/bn1/Reshape[12]_1/Reshape6": {"shape": [[]], "edge_type": "data", "independent_layout": false, "data_type": "DT_STRING"}}, "output_i": 0, "proxy_input": {}, "proxy_output": {}, "subnode_count": 2, "independent_layout": false}, {"name": "Default/bn1-BatchNorm2d", "type": "name_scope", "attr": {}, "input": {}, "output": {"Default/bn1/Add[5]_0/Add53": {"shape": [[]], "edge_type": "data", "independent_layout": false, "data_type": "DT_STRING"}}, "output_i": 0, "proxy_input": {}, "proxy_output": {}, "subnode_count": 5, "independent_layout": false}, {"name": "Default/bn1", "type": "name_scope", "attr": {}, "input": {"Default/bn1-BatchNorm2d/tuple_getitem56": {"shape": [[]], "edge_type": "data", "independent_layout": false, "data_type": "DT_STRING"}, "Default/conv1-Conv2d/Conv2D55": {"shape": [[]], "edge_type": "data", "independent_layout": false, "data_type": "DT_STRING"}}, "output": {}, "output_i": 0, "proxy_input": {}, "proxy_output": {}, "subnode_count": 4, "independent_layout": false}], "scope_name": "Default", "children": {}}}

tests/ut/datavisual/processors/graph_results/test_get_nodes_success_expected_results2.json

@@ -1 +1 @@
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tests/ut/datavisual/processors/graph_results/test_get_nodes_success_expected_results3.json

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tests/ut/datavisual/processors/graph_results/test_search_single_node_success_expected_results1.json

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