1. Complete the optimization of the graph code

2. Optimize the python api of graph and graph_processor
3. delete unconnected const and parameter nodes
4. fix subnode count bug and fix name scope node have not input and output bug
5. add cyclic graph and high degree graph json file
6. update parameter node to polymeric scope node
7. delele all deepcopy to improve performance
8. add data type and update the attribute scope of edge to independtend_layout
9. add add_parameter_nodes function
10. delete scope attribute in input and optimiza code
11. parse parameter data type and shape
12. fix ut and st for graph
13. fix pylint
14. fix pylint arguments-differ
15. add scope proxy node instead of node

mindinsight/backend/datavisual/train_visual_api.py

@@ -102,12 +102,11 @@ def graph_nodes():
 
     """
     name = request.args.get('name', default=None)
-    node_type = request.args.get('type', default='name_scope')
     tag = request.args.get("tag", default=None)
     train_id = get_train_id(request)
 
     graph_process = GraphProcessor(train_id, DATA_MANAGER, tag)
-    response = graph_process.get_nodes(name=name, node_type=node_type)
+    response = graph_process.list_nodes(scope=name)
     return jsonify(response)
 
 

mindinsight/datavisual/data_transform/graph/node.py

@@ -17,10 +17,11 @@ This file is used to define the node of graph and associated base types.
 """
 from enum import Enum
 
+
 class NodeTypeEnum(Enum):
     """Node type enum. The following types are new to our custom."""
     NAME_SCOPE = 'name_scope'
-    POLYMERIC_SCOPE = 'polymeric_scope'
+    AGGREGATION_SCOPE = 'aggregation_scope'
     PARAMETER = 'Parameter'
     CONST = 'Const'
 
@@ -36,32 +37,33 @@ class Node:
 
     def __init__(self, name, node_id):
         self._node_id = node_id
-        self._name = name
-        self._type = ""
+        self.name = name
+        self.type = ""
         self._attr = dict()
-        self._inputs = dict()
-        self._output_i = -1
-        self._outputs = {}
-        self._polymeric_inputs = {}
-        self._polymeric_outputs = {}
-        self._polymeric_scope_name = ""
-        self._subnode_count = 0
-        self._name_scope = ""
-        self.shape = []
+        self._input = dict()
+        self.output_i = 0
+        self._output = {}
+        self._proxy_input = {}
+        self._proxy_output = {}
+        self.subnode_count = 0
+        self.scope = ""
+        self.independent_layout = False
+        self.output_shape = []
+        self.output_data_type = ""
 
     def to_dict(self):
         """Converts the node object to dictionary format."""
         return {
-            'name': self._name,
-            'type': self._type,
+            'name': self.name,
+            'type': self.type,
             'attr': self._attr,
-            'input': self._inputs,
-            'output_i': self._output_i,
-            'output': self._outputs,
-            'polymeric_input': self._polymeric_inputs,
-            'polymeric_output': self._polymeric_outputs,
-            'subnode_count': self._subnode_count,
-            'polymeric_scope_name': self._polymeric_scope_name
+            'input': self._input,
+            'output': self._output,
+            'output_i': self.output_i,
+            'proxy_input': self._proxy_input,
+            'proxy_output': self._proxy_output,
+            'subnode_count': self.subnode_count,
+            'independent_layout': self.independent_layout
         }
 
     @property
@@ -69,32 +71,26 @@ class Node:
         """The id of this node, and id is unique in graph."""
         return self._node_id
 
-    @property
-    def name(self):
-        """Get node name."""
-        return self._name
-
-    @name.setter
-    def name(self, name):
-        """Set node name."""
-        self._name = name
+    @staticmethod
+    def create_node_name(scope, base_name):
+        """
+        The name of the node consists of the scope and the basic name.
 
-    @property
-    def node_type(self):
-        """Get node type."""
-        return self._type
+        Args:
+            scope (str): The scope of node, such as 'Default/Conv2D'
+            base_name (str): The base name of node, such as 'Add11'.
 
-    @node_type.setter
-    def node_type(self, node_type):
-        """Set node type."""
-        self._type = node_type
+        Returns:
+            str, a node name.
+        """
+        return f'{scope}/{base_name}' if scope else base_name
 
     @property
     def attr(self):
         """Get node attr."""
         return self._attr
 
-    def update_attr(self, attr_dict):
+    def add_attr(self, attr_dict):
         """
         Update node attr.
 
@@ -104,114 +100,122 @@ class Node:
         self._attr.update(attr_dict)
 
     @property
-    def inputs(self):
+    def input(self):
         """
         Get all input of current node.
 
         Returns:
-            dict[str, dict], format is {'<src_name>': {'shape': [], 'edge_type', 'scope'}}.
+            dict[str, dict], refer to the input attr.
         """
-        return self._inputs
+        return self._input
 
-    def update_input(self, input_dict):
+    def add_input(self, src_name, input_attr):
         """
         Update input.
 
         Args:
-            input_dict (dict[str, dict]): Key is a source node name, and the value is a dict.
+            src_name (stc): The source node name.
+            input_attr (dict): The attribute of the input.
 
                 - shape (list): The shape of input tensor.
                 - edge_type (str): The type of edge, optional value refer to `EdgeTypeEnum`.
-                - scope (str): The scope of this source node.
+                - data_type (str): The data type of the input.
+                - independent_layout (bool): Indicates whether the source nodes are laid out independently.
         """
-        self._inputs.update(input_dict)
+        self._input.update({src_name: input_attr})
 
-    @property
-    def output_i(self):
-        """The memory address of this node when it is in run time."""
-        return self._output_i
-
-    @output_i.setter
-    def output_i(self, output_i):
-        """Set memory address."""
-        self._output_i = output_i
-
-    @property
-    def polymeric_inputs(self):
+    def delete_input(self, src_name):
         """
-        The polymeric input is the input of the polymeric nodes.
+        Delete input attribute by the given source name.
 
-        Returns:
-            dict[str, dict], format is {'<src_name>': {'edge_type': '<value>'}}.
+        Args:
+            src_name (str): The source node name.
         """
-        return self._polymeric_inputs
-
-    def update_polymeric_input(self, polymeric_input):
-        """The polymeric input is the input of the polymeric nodes."""
-        self._polymeric_inputs.update(polymeric_input)
+        self._input.pop(src_name)
 
     @property
-    def outputs(self):
+    def output(self):
         """The output node of this node."""
-        return self._outputs
+        return self._output
 
-    def update_output(self, output):
+    def add_output(self, dst_name, output_attr):
         """
-        Update output node.
+        Add a output node to this node.
 
         Args:
-            output (dict[str, TypedDict('NodeType', {'type': str})]): Key is a dst node name, and value is a dict.
+            dst_name (str): The name of the output node.
+            output_attr (dict: Same as the input attribute.
+        """
+        self._output.update({dst_name: output_attr})
+
+    def delete_output(self, dst_name):
+        """
+        Delete a output node.
 
-                - type (str): The type of the dst node.
+        Args:
+            dst_name (str): The name of the node to be deleted.
         """
-        self._outputs.update(output)
+        self._output.pop(dst_name)
 
     @property
-    def polymeric_outputs(self):
-        """Get polymeric output."""
-        return self._polymeric_outputs
+    def proxy_input(self):
+        """Return proxy input, type is dict."""
+        return self._proxy_input
 
-    def update_polymeric_output(self, polymeric_output):
+    def add_proxy_input(self, src_name, attr):
         """
-        Update polymeric output.
+        Add a proxy input to node.
 
         Args:
-            polymeric_output (dict[str, dict): Key is the polymeric scope name of dst name, and value is dict.
-
-                - edge_type (str): The edge type of the dst node.
+            src_name (str): The name of the input node.
+            attr (dict): The attr of the input.
 
+            - edge_type (str): The edge type, refer to `EdgeTypeEnum`.
         """
-        self._polymeric_outputs.update(polymeric_output)
+        self._proxy_input.update({src_name: attr})
+
+    def delete_proxy_input(self, src_name):
+        """Delete a proxy input by the src name."""
+        self._proxy_input.pop(src_name)
 
     @property
-    def polymeric_scope_name(self):
-        """Get polymeric scope name."""
-        return self._polymeric_scope_name
+    def proxy_output(self):
+        """Get proxy output, data type is dict."""
+        return self._proxy_output
 
-    @polymeric_scope_name.setter
-    def polymeric_scope_name(self, name):
-        """Set polymeric scope name."""
-        self._polymeric_scope_name = name
+    def add_proxy_output(self, dst_name, attr):
+        """
+        Add a proxy output to node.
 
-    @property
-    def subnode_count(self):
-        """The sub node count of this node, if this node is a scope node, this count will not be zero."""
-        return self._subnode_count
+        Args:
+            dst_name (str): The name of the output node.
+            attr (dict): The attr of the output.
 
-    @subnode_count.setter
-    def subnode_count(self, count):
-        """Set sub node count."""
-        self._subnode_count = count
+            - edge_type (str): The edge type, refer to `EdgeTypeEnum`.
+        """
+        self._proxy_output.update({dst_name: attr})
 
-    @property
-    def name_scope(self):
-        """Get name scope of this node."""
-        return self._name_scope
+    def delete_proxy_output(self, dst_name):
+        """Delete a proxy output by dst name."""
+        self._proxy_output.pop(dst_name)
 
-    @name_scope.setter
-    def name_scope(self, name_scope):
-        """Set name scope."""
-        self._name_scope = name_scope
+    @staticmethod
+    def copy_node_without_input_output(src_node, dst_node):
+        """
+        Copy a source node attribute to a new node, but not input and output.
+
+        Args:
+            src_node (Node): The copied node.
+            dst_node (Node): The destination node.
+        """
+        dst_node.type = src_node.type
+        dst_node.output_i = src_node.output_i
+        dst_node.subnode_count = src_node.subnode_count
+        dst_node.scope = src_node.scope
+        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.add_attr(src_node.attr)
 
     def __str__(self):
-        return f'<Node, name: {self._name}, type: {self._type}>'
+        return f'<Node, name: {self.name}, type: {self.type}>'

mindinsight/datavisual/processors/graph_processor.py

@@ -20,9 +20,7 @@ and the status of graph will be checked before calling `Graph` object.
 from mindinsight.datavisual.common import exceptions
 from mindinsight.datavisual.common.enums import PluginNameEnum
 from mindinsight.datavisual.common.validation import Validation
-from mindinsight.datavisual.data_transform.graph import NodeTypeEnum
 from mindinsight.datavisual.processors.base_processor import BaseProcessor
-from mindinsight.utils.exceptions import ParamValueError
 from mindinsight.datavisual.common.exceptions import NodeNotInGraphError
 
 
@@ -51,13 +49,12 @@ class GraphProcessor(BaseProcessor):
         tensors = self._data_manager.list_tensors(train_id, tag=tag)
         self._graph = tensors[0].value
 
-    def get_nodes(self, name, node_type):
+    def list_nodes(self, scope):
         """
         Get the nodes of every layer in graph.
 
         Args:
-            name (str): The name of a node.
-            node_type (Any): The type of node, either 'name_scope' or 'polymeric'.
+            scope (str): The name of a scope.
 
         Returns:
             TypedDict('Nodes', {'nodes': list[Node]}), format is {'nodes': [<Node object>]}.
@@ -81,33 +78,19 @@ class GraphProcessor(BaseProcessor):
                             }
                           },
                           "output_i" : -1,
-                          "polymeric_input" : {},
-                          "polymeric_output" : {},
-                          "polymeric_scope_name" : "",
+                          "proxy_input" : {},
+                          "proxy_output" : {},
+                          "independent_layout" : False,
                           "subnode_count" : 0,
                           "type" : "Data"
                         }
                       ]
                     }
         """
-        if node_type not in [NodeTypeEnum.NAME_SCOPE.value, NodeTypeEnum.POLYMERIC_SCOPE.value]:
-            raise ParamValueError(
-                'The node type is not support, only either %s or %s.'
-                '' % (NodeTypeEnum.NAME_SCOPE.value, NodeTypeEnum.POLYMERIC_SCOPE.value))
-
-        if name and not self._graph.exist_node(name):
-            raise NodeNotInGraphError(node_name=name, node_type=node_type)
-        nodes = []
-        if node_type == NodeTypeEnum.NAME_SCOPE.value:
-            nodes = self._graph.get_normal_nodes(name)
-
-        if node_type == NodeTypeEnum.POLYMERIC_SCOPE.value:
-            if not name:
-                raise NodeNotInGraphError(node_name=name, node_type=node_type)
-
-            polymeric_scope_name = name
-            nodes = self._graph.get_polymeric_nodes(polymeric_scope_name)
+        if scope and not self._graph.exist_node(scope):
+            raise NodeNotInGraphError(node_name=scope)
 
+        nodes = self._graph.list_node_by_scope(scope=scope)
         return {'nodes': nodes}
 
     def search_node_names(self, search_content, offset, limit):

tests/st/func/datavisual/graph/graph_results/test_query_nodes_success_result1.json

-{"nodes":[{"attr":{},"input":{},"name":"Default/conv1-Conv2d","output":{},"output_i":-1,"polymeric_input":{},"polymeric_output":{},"polymeric_scope_name":"","subnode_count":1,"type":"name_scope"},{"attr":{},"input":{},"name":"Default/bn1-BatchNorm2d","output":{},"output_i":-1,"polymeric_input":{},"polymeric_output":{},"polymeric_scope_name":"","subnode_count":14,"type":"name_scope"},{"attr":{},"input":{},"name":"Default/bn1","output":{},"output_i":-1,"polymeric_input":{},"polymeric_output":{},"polymeric_scope_name":"","subnode_count":20,"type":"name_scope"}]}
+{"nodes":[{"attr":{},"independent_layout":false,"input":{},"name":"Default","output":{},"output_i":0,"proxy_input":{},"proxy_output":{},"subnode_count":3,"type":"name_scope"}]}
\ No newline at end of file

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

-{"nodes":[{"attr":{},"input":{},"name":"Default","output":{},"output_i":-1,"polymeric_input":{},"polymeric_output":{},"polymeric_scope_name":"","subnode_count":3,"type":"name_scope"}]}
+{"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"}]}
\ No newline at end of file

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

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tests/st/func/datavisual/graph/test_query_nodes_restful_api.py

@@ -40,22 +40,17 @@ class TestQueryNodes:
     @pytest.mark.platform_x86_gpu_training
     @pytest.mark.platform_x86_ascend_training
     @pytest.mark.usefixtures("init_summary_logs")
-    @pytest.mark.parametrize("node_name, node_type, result_file", [
-        ('', "name_scope", "test_query_nodes_success_result2.json"),
-        ("Default", "name_scope", "test_query_nodes_success_result1.json"),
-        ("Default/bn1/Reshape_1_[12]", "polymeric_scope", "test_query_nodes_success_result3.json")
+    @pytest.mark.parametrize("node_name, result_file", [
+        ('', "test_query_nodes_success_result1.json"),
+        ("Default", "test_query_nodes_success_result2.json"),
+        ("Default/bn1/Reshape[12]_1", "test_query_nodes_success_result3.json")
     ])
-    def test_query_namescope_success(self, client, node_name, node_type, result_file):
+    def test_list_node_success(self, client, node_name, result_file):
         """Query the name scope node."""
         train_id = gbl.get_train_ids()[0]
 
-        if node_name:
-            params = dict(train_id=train_id,
-                          type=node_type,
-                          name=node_name)
-        else:
-            params = dict(train_id=train_id,
-                          type=node_type)
+        params = dict(train_id=train_id,
+                      name=node_name)
         url = get_url(BASE_URL, params)
         response = client.get(url)
         assert response.status_code == 200

tests/st/func/datavisual/graph/test_query_single_nodes_restful_api.py

@@ -41,7 +41,7 @@ class TestQuerySingleNode:
     @pytest.mark.platform_x86_ascend_training
     @pytest.mark.usefixtures("init_summary_logs")
     @pytest.mark.parametrize("node_name, result_file", [
-        ('Default/bn1/Reshape1', "test_query_single_node_success_result1.json")
+        ('Default/bn1', "test_query_single_node_success_result1.json")
     ])
     def test_query_single_node_success(self, client, node_name, result_file):
         """Query single node."""

tests/st/func/datavisual/graph/test_search_nodes_restful_api.py

@@ -41,7 +41,7 @@ class TestSearchNodes:
     @pytest.mark.platform_x86_ascend_training
     @pytest.mark.usefixtures("init_summary_logs")
     @pytest.mark.parametrize("search_content, offset, limit, result_file", [
-        ('Default/bn1/Reshape', 0, 1000, "test_search_nodes_success_result1.json")
+        ('Default/bn1', 0, 1000, "test_search_nodes_success_result1.json")
     ])
     def test_search_nodes_success(self, client, search_content, offset, limit, result_file):
         """Search node with parameters: offset is 0, limit is 1000."""

tests/ut/backend/datavisual/test_train_visual_api.py

@@ -22,7 +22,6 @@ from unittest.mock import Mock, patch
 
 import pytest
 
-from mindinsight.datavisual.data_transform.graph import NodeTypeEnum
 from mindinsight.datavisual.processors.graph_processor import GraphProcessor
 from mindinsight.datavisual.processors.images_processor import ImageProcessor
 from mindinsight.datavisual.processors.scalars_processor import ScalarsProcessor
@@ -227,47 +226,27 @@ class TestTrainVisual:
         assert results['error_msg'] == "Param missing. 'train_id' is required."
 
     @patch.object(GraphProcessor, '__init__')
-    def test_graph_nodes_with_type_is_invalid(self, mock_graph_processor, client):
-        """Test getting graph nodes with invalid type."""
-        mock_init = Mock(return_value=None)
-        mock_graph_processor.side_effect = mock_init
-
-        node_type = "invalid_node_type"
-        params = dict(train_id='aaa', type=node_type)
-        url = get_url(TRAIN_ROUTES['graph_nodes'], params)
-
-        response = client.get(url)
-        results = response.get_json()
-        assert response.status_code == 400
-        assert results['error_code'] == '50540002'
-        assert results['error_msg'] == "Invalid parameter value. The node type " \
-                                       "is not support, only either %s or %s." \
-                                       "" % (NodeTypeEnum.NAME_SCOPE.value,
-                                             NodeTypeEnum.POLYMERIC_SCOPE.value)
-
-    @patch.object(GraphProcessor, '__init__')
-    @patch.object(GraphProcessor, 'get_nodes')
-    def test_graph_nodes_success(self, mock_graph_processor, mock_graph_processor_1, client):
+    @patch.object(GraphProcessor, 'list_nodes')
+    def test_graph_nodes_success(self, mock_list_nodes_func, mock_init_func, client):
         """Test getting graph nodes successfully."""
 
-        def mock_get_nodes(name, node_type):
-            return dict(name=name, node_type=node_type)
+        def mock_list_nodes(scope):
+            return dict(scope=scope)
 
-        mock_graph_processor.side_effect = mock_get_nodes
+        mock_list_nodes_func.side_effect = mock_list_nodes
 
         mock_init = Mock(return_value=None)
-        mock_graph_processor_1.side_effect = mock_init
+        mock_init_func.side_effect = mock_init
 
         test_train_id = 'aaa'
         test_node_name = 'bbb'
-        test_node_type = NodeTypeEnum.NAME_SCOPE.value
-        params = dict(train_id=test_train_id, name=test_node_name, type=test_node_type)
+        params = dict(train_id=test_train_id, name=test_node_name)
         url = get_url(TRAIN_ROUTES['graph_nodes'], params)
 
         response = client.get(url)
         assert response.status_code == 200
         results = response.get_json()
-        assert results == dict(name=test_node_name, node_type=test_node_type)
+        assert results == dict(scope=test_node_name)
 
     def test_graph_node_names_with_train_id_is_none(self, client):
         """Test getting graph node names with train id is none."""

tests/ut/datavisual/processors/graph_results/test_get_nodes_success_expected_results1.json

-{
-  "nodes" : [
-    {
-      "attr" : {},
-      "input" : {},
-      "name" : "Default",
-      "output" : {},
-      "output_i" : -1,
-      "polymeric_input" : {},
-      "polymeric_output" : {},
-      "polymeric_scope_name" : "",
-      "subnode_count" : 3,
-      "type" : "name_scope"
-    }
-  ]
-}
+{"nodes":[{"attr":{},"independent_layout":false,"input":{},"name":"Default","output":{},"output_i":0,"proxy_input":{},"proxy_output":{},"subnode_count":3,"type":"name_scope"}]}
\ No newline at end of file

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

-{
-  "nodes" : [
-    {
-      "attr" :
-      {
-        "output_names" : "dtype: DT_GRAPHS\nvalues {\n  dtype: DT_FLOAT64\n  str_val: \"output\"\n}\n",
-        "pad_mode" : "dtype: DT_FLOAT64\nstr_val: \"same\"\n"
-      },
-      "input" : {},
-      "name" : "Default/conv1-Conv2d/Conv2D1",
-      "output" : {},
-      "output_i" : 0,
-      "polymeric_input" : {},
-      "polymeric_output" : {},
-      "polymeric_scope_name" : "",
-      "subnode_count" : 0,
-      "type" : "Conv2D"
-    }
-  ]
-}
\ No newline at end of file
+{"nodes":[{"attr":{"output_names":"dtype: DT_GRAPHS\nvalues {\n  dtype: DT_FLOAT64\n  str_val: \"output\"\n}\n","pad_mode":"dtype: DT_FLOAT64\nstr_val: \"same\"\n"},"independent_layout":false,"input":{"Default/conv1-Conv2d/Parameter[12]_2/conv1.weight":{"data_type":"","edge_type":"data","independent_layout":true,"shape":[64,3,7,7]},"Default/conv1-Conv2d/Parameter[12]_2/x":{"data_type":"","edge_type":"data","independent_layout":true,"shape":[1,3,224,224]},"Default/conv1-Conv2d/Parameter[12]_2/x1":{"data_type":"","edge_type":"data","independent_layout":true,"shape":[1,3,224,224]},"Default/conv1-Conv2d/Parameter[12]_2/x10":{"data_type":"","edge_type":"data","independent_layout":true,"shape":[1,3,224,224]},"Default/conv1-Conv2d/Parameter[12]_2/x2":{"data_type":"","edge_type":"data","independent_layout":true,"shape":[1,3,224,224]},"Default/conv1-Conv2d/Parameter[12]_2/x3":{"data_type":"","edge_type":"data","independent_layout":true,"shape":[1,3,224,224]},"Default/conv1-Conv2d/Parameter[12]_2/x4":{"data_type":"","edge_type":"data","independent_layout":true,"shape":[1,3,224,224]},"Default/conv1-Conv2d/Parameter[12]_2/x5":{"data_type":"","edge_type":"data","independent_layout":true,"shape":[1,3,224,224]},"Default/conv1-Conv2d/Parameter[12]_2/x6":{"data_type":"","edge_type":"data","independent_layout":true,"shape":[1,3,224,224]},"Default/conv1-Conv2d/Parameter[12]_2/x7":{"data_type":"","edge_type":"data","independent_layout":true,"shape":[1,3,224,224]},"Default/conv1-Conv2d/Parameter[12]_2/x8":{"data_type":"","edge_type":"data","independent_layout":true,"shape":[1,3,224,224]},"Default/conv1-Conv2d/Parameter[12]_2/x9":{"data_type":"","edge_type":"data","independent_layout":true,"shape":[1,3,224,224]}},"name":"Default/conv1-Conv2d/Conv2D55","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":{"Default/conv1-Conv2d/Parameter[12]_2":{"edge_type":"data"}},"proxy_output":{},"subnode_count":0,"type":"Conv2D"},{"attr":{},"independent_layout":true,"input":{},"name":"Default/conv1-Conv2d/Parameter[12]_2","output":{"Default/conv1-Conv2d/Conv2D55":{"data_type":"","edge_type":"data","independent_layout":true,"shape":[64,3,7,7]}},"output_i":0,"proxy_input":{},"proxy_output":{"Default/conv1-Conv2d/Conv2D55":{"edge_type":"data"}},"subnode_count":12,"type":"aggregation_scope"}]}
\ No newline at end of file

tests/ut/datavisual/processors/graph_results/test_get_nodes_success_expected_results3.json

-
-{
-  "nodes" : [
-    {
-      "attr" : {},
-      "input" :
-      {
-        "Default/bn1/Add50" :
-        {
-          "edge_type" : "data",
-          "scope" : "polymeric_scope",
-          "shape" : [1, 1024, 14, 14]
-        },
-        "Default/bn1/conv1.weight" :
-        {
-          "edge_type" : "data",
-          "scope" : "polymeric_scope",
-          "shape" : [64, 3, 7, 7]
-        },
-        "Default/bn1/x" :
-        {
-          "edge_type" : "data",
-          "scope" : "polymeric_scope",
-          "shape" : [1, 3, 224, 224]
-        },
-        "Default/bn1/x1" :
-        {
-          "edge_type" : "data",
-          "scope" : "polymeric_scope",
-          "shape" : [1, 3, 224, 224]
-        },
-        "Default/bn1/x10" :
-        {
-          "edge_type" : "data",
-          "scope" : "polymeric_scope",
-          "shape" : [1, 3, 224, 224]
-        },
-        "Default/bn1/x2" :
-        {
-          "edge_type" : "data",
-          "scope" : "polymeric_scope",
-          "shape" : [1, 3, 224, 224]
-        },
-        "Default/bn1/x3" :
-        {
-          "edge_type" : "data",
-          "scope" : "polymeric_scope",
-          "shape" : [1, 3, 224, 224]
-        },
-        "Default/bn1/x4" :
-        {
-          "edge_type" : "data",
-          "scope" : "polymeric_scope",
-          "shape" : [1, 3, 224, 224]
-        },
-        "Default/bn1/x5" :
-        {
-          "edge_type" : "data",
-          "scope" : "polymeric_scope",
-          "shape" : [1, 3, 224, 224]
-        },
-        "Default/bn1/x6" :
-        {
-          "edge_type" : "data",
-          "scope" : "polymeric_scope",
-          "shape" : [1, 3, 224, 224]
-        },
-        "Default/bn1/x7" :
-        {
-          "edge_type" : "data",
-          "scope" : "polymeric_scope",
-          "shape" : [1, 3, 224, 224]
-        },
-        "Default/bn1/x8" :
-        {
-          "edge_type" : "data",
-          "scope" : "polymeric_scope",
-          "shape" : [1, 3, 224, 224]
-        },
-        "Default/bn1/x9" :
-        {
-          "edge_type" : "data",
-          "scope" : "polymeric_scope",
-          "shape" : [1, 3, 224, 224]
-        }
-      },
-      "name" : "Default/bn1/Reshape1",
-      "output" : {},
-      "output_i" : 0,
-      "polymeric_input" :
-      {
-        "Default/bn1/Add50" :
-        {
-          "edge_type" : "data"
-        },
-        "Default/bn1/conv1.weight" :
-        {
-          "edge_type" : "data"
-        },
-        "Default/bn1/x" :
-        {
-          "edge_type" : "data"
-        },
-        "Default/bn1/x1" :
-        {
-          "edge_type" : "data"
-        },
-        "Default/bn1/x10" :
-        {
-          "edge_type" : "data"
-        },
-        "Default/bn1/x2" :
-        {
-          "edge_type" : "data"
-        },
-        "Default/bn1/x3" :
-        {
-          "edge_type" : "data"
-        },
-        "Default/bn1/x4" :
-        {
-          "edge_type" : "data"
-        },
-        "Default/bn1/x5" :
-        {
-          "edge_type" : "data"
-        },
-        "Default/bn1/x6" :
-        {
-          "edge_type" : "data"
-        },
-        "Default/bn1/x7" :
-        {
-          "edge_type" : "data"
-        },
-        "Default/bn1/x8" :
-        {
-          "edge_type" : "data"
-        },
-        "Default/bn1/x9" :
-        {
-          "edge_type" : "data"
-        }
-      },
-      "polymeric_output" : {},
-      "polymeric_scope_name" : "Default/bn1/Reshape_1_[12]",
-      "subnode_count" : 0,
-      "type" : "Reshape"
-    },
-    {
-      "attr" : {},
-      "input" :
-      {
-        "Default/bn1/Add51" :
-        {
-          "edge_type" : "data",
-          "scope" : "polymeric_scope",
-          "shape" : [1, 1024, 14, 14]
-        }
-      },
-      "name" : "Default/bn1/Reshape2",
-      "output" : {},
-      "output_i" : 0,
-      "polymeric_input" :
-      {
-        "Default/bn1/Add51" :
-        {
-          "edge_type" : "data"
-        }
-      },
-      "polymeric_output" : {},
-      "polymeric_scope_name" : "Default/bn1/Reshape_1_[12]",
-      "subnode_count" : 0,
-      "type" : "Reshape"
-    },
-    {
-      "attr" : {},
-      "input" :
-      {
-        "Default/bn1/Add52" :
-        {
-          "edge_type" : "data",
-          "scope" : "polymeric_scope",
-          "shape" : [1, 1024, 14, 14]
-        }
-      },
-      "name" : "Default/bn1/Reshape3",
-      "output" : {},
-      "output_i" : 0,
-      "polymeric_input" :
-      {
-        "Default/bn1/Add52" :
-        {
-          "edge_type" : "data"
-        }
-      },
-      "polymeric_output" : {},
-      "polymeric_scope_name" : "Default/bn1/Reshape_1_[12]",
-      "subnode_count" : 0,
-      "type" : "Reshape"
-    },
-    {
-      "attr" : {},
-      "input" :
-      {
-        "Default/bn1/Add53" :
-        {
-          "edge_type" : "data",
-          "scope" : "polymeric_scope",
-          "shape" : [1, 1024, 14, 14]
-        }
-      },
-      "name" : "Default/bn1/Reshape4",
-      "output" : {},
-      "output_i" : 0,
-      "polymeric_input" :
-      {
-        "Default/bn1/Add53" :
-        {
-          "edge_type" : "data"
-        }
-      },
-      "polymeric_output" : {},
-      "polymeric_scope_name" : "Default/bn1/Reshape_1_[12]",
-      "subnode_count" : 0,
-      "type" : "Reshape"
-    },
-    {
-      "attr" : {},
-      "input" :
-      {
-        "Default/bn1/Add54" :
-        {
-          "edge_type" : "data",
-          "scope" : "polymeric_scope",
-          "shape" : [1, 1024, 14, 14]
-        }
-      },
-      "name" : "Default/bn1/Reshape5",
-      "output" : {},
-      "output_i" : 0,
-      "polymeric_input" :
-      {
-        "Default/bn1/Add54" :
-        {
-          "edge_type" : "data"
-        }
-      },
-      "polymeric_output" : {},
-      "polymeric_scope_name" : "Default/bn1/Reshape_1_[12]",
-      "subnode_count" : 0,
-      "type" : "Reshape"
-    },
-    {
-      "attr" : {},
-      "input" :
-      {
-        "Default/bn1/x" :
-        {
-          "edge_type" : "data",
-          "scope" : "polymeric_scope",
-          "shape" : [1, 3, 224, 224]
-        }
-      },
-      "name" : "Default/bn1/Reshape6",
-      "output" : {},
-      "output_i" : 0,
-      "polymeric_input" :
-      {
-        "Default/bn1/x" :
-        {
-          "edge_type" : "data"
-        }
-      },
-      "polymeric_output" : {},
-      "polymeric_scope_name" : "Default/bn1/Reshape_1_[12]",
-      "subnode_count" : 0,
-      "type" : "Reshape"
-    },
-    {
-      "attr" : {},
-      "input" :
-      {
-        "Default/bn1/x" :
-        {
-          "edge_type" : "data",
-          "scope" : "polymeric_scope",
-          "shape" : [1, 3, 224, 224]
-        }
-      },
-      "name" : "Default/bn1/Reshape7",
-      "output" : {},
-      "output_i" : 0,
-      "polymeric_input" :
-      {
-        "Default/bn1/x" :
-        {
-          "edge_type" : "data"
-        }
-      },
-      "polymeric_output" : {},
-      "polymeric_scope_name" : "Default/bn1/Reshape_1_[12]",
-      "subnode_count" : 0,
-      "type" : "Reshape"
-    },
-    {
-      "attr" : {},
-      "input" :
-      {
-        "Default/bn1/x" :
-        {
-          "edge_type" : "data",
-          "scope" : "polymeric_scope",
-          "shape" : [1, 3, 224, 224]
-        }
-      },
-      "name" : "Default/bn1/Reshape8",
-      "output" : {},
-      "output_i" : 0,
-      "polymeric_input" :
-      {
-        "Default/bn1/x" :
-        {
-          "edge_type" : "data"
-        }
-      },
-      "polymeric_output" : {},
-      "polymeric_scope_name" : "Default/bn1/Reshape_1_[12]",
-      "subnode_count" : 0,
-      "type" : "Reshape"
-    },
-    {
-      "attr" : {},
-      "input" :
-      {
-        "Default/bn1/x" :
-        {
-          "edge_type" : "data",
-          "scope" : "polymeric_scope",
-          "shape" : [1, 3, 224, 224]
-        }
-      },
-      "name" : "Default/bn1/Reshape9",
-      "output" : {},
-      "output_i" : 0,
-      "polymeric_input" :
-      {
-        "Default/bn1/x" :
-        {
-          "edge_type" : "data"
-        }
-      },
-      "polymeric_output" : {},
-      "polymeric_scope_name" : "Default/bn1/Reshape_1_[12]",
-      "subnode_count" : 0,
-      "type" : "Reshape"
-    },
-    {
-      "attr" : {},
-      "input" :
-      {
-        "Default/bn1/x" :
-        {
-          "edge_type" : "data",
-          "scope" : "polymeric_scope",
-          "shape" : [1, 3, 224, 224]
-        }
-      },
-      "name" : "Default/bn1/Reshape10",
-      "output" : {},
-      "output_i" : 0,
-      "polymeric_input" :
-      {
-        "Default/bn1/x" :
-        {
-          "edge_type" : "data"
-        }
-      },
-      "polymeric_output" : {},
-      "polymeric_scope_name" : "Default/bn1/Reshape_1_[12]",
-      "subnode_count" : 0,
-      "type" : "Reshape"
-    },
-    {
-      "attr" : {},
-      "input" :
-      {
-        "Default/bn1/x" :
-        {
-          "edge_type" : "data",
-          "scope" : "polymeric_scope",
-          "shape" : [1, 3, 224, 224]
-        }
-      },
-      "name" : "Default/bn1/Reshape11",
-      "output" : {},
-      "output_i" : 0,
-      "polymeric_input" :
-      {
-        "Default/bn1/x" :
-        {
-          "edge_type" : "data"
-        }
-      },
-      "polymeric_output" : {},
-      "polymeric_scope_name" : "Default/bn1/Reshape_1_[12]",
-      "subnode_count" : 0,
-      "type" : "Reshape"
-    },
-    {
-      "attr" : {},
-      "input" :
-      {
-        "Default/bn1/x" :
-        {
-          "edge_type" : "data",
-          "scope" : "polymeric_scope",
-          "shape" : [1, 3, 224, 224]
-        }
-      },
-      "name" : "Default/bn1/Reshape12",
-      "output" : {},
-      "output_i" : 0,
-      "polymeric_input" :
-      {
-        "Default/bn1/x" :
-        {
-          "edge_type" : "data"
-        }
-      },
-      "polymeric_output" : {},
-      "polymeric_scope_name" : "Default/bn1/Reshape_1_[12]",
-      "subnode_count" : 0,
-      "type" : "Reshape"
-    }
-  ]
-}
+{"nodes":[{"attr":{},"independent_layout":false,"input":{"Default/bn1/Add[5]_0/Add50":{"data_type":"DT_STRING","edge_type":"data","independent_layout":false,"shape":[1,1024,14,14]}},"name":"Default/bn1/Reshape[12]_1/Reshape1","output":{},"output_i":0,"proxy_input":{},"proxy_output":{},"subnode_count":0,"type":"Reshape"},{"attr":{},"independent_layout":false,"input":{"Default/bn1/Add[5]_0/Add51":{"data_type":"DT_STRING","edge_type":"data","independent_layout":false,"shape":[1,1024,14,14]}},"name":"Default/bn1/Reshape[12]_1/Reshape2","output":{},"output_i":0,"proxy_input":{},"proxy_output":{},"subnode_count":0,"type":"Reshape"},{"attr":{},"independent_layout":false,"input":{"Default/bn1/Add[5]_0/Add52":{"data_type":"DT_STRING","edge_type":"data","independent_layout":false,"shape":[1,1024,14,14]}},"name":"Default/bn1/Reshape[12]_1/Reshape3","output":{},"output_i":0,"proxy_input":{},"proxy_output":{},"subnode_count":0,"type":"Reshape"},{"attr":{},"independent_layout":false,"input":{"Default/bn1/Add[5]_0/Add53":{"data_type":"DT_STRING","edge_type":"data","independent_layout":false,"shape":[1,1024,14,14]}},"name":"Default/bn1/Reshape[12]_1/Reshape4","output":{},"output_i":0,"proxy_input":{},"proxy_output":{},"subnode_count":0,"type":"Reshape"},{"attr":{},"independent_layout":false,"input":{"Default/bn1/Add[5]_0/Add54":{"data_type":"DT_STRING","edge_type":"data","independent_layout":false,"shape":[1,1024,14,14]}},"name":"Default/bn1/Reshape[12]_1/Reshape5","output":{},"output_i":0,"proxy_input":{},"proxy_output":{},"subnode_count":0,"type":"Reshape"},{"attr":{},"independent_layout":false,"input":{"Default/conv1-Conv2d/Conv2D55":{"data_type":"DT_STRING","edge_type":"data","independent_layout":false,"shape":[1,64,112,112]}},"name":"Default/bn1/Reshape[12]_1/Reshape6","output":{},"output_i":0,"proxy_input":{},"proxy_output":{},"subnode_count":0,"type":"Reshape"},{"attr":{},"independent_layout":false,"input":{"Default/bn1/x":{"data_type":"","edge_type":"data","independent_layout":false,"shape":[1,3,224,224]}},"name":"Default/bn1/Reshape[12]_1/Reshape7","output":{},"output_i":0,"proxy_input":{},"proxy_output":{},"subnode_count":0,"type":"Reshape"},{"attr":{},"independent_layout":false,"input":{"Default/bn1/x":{"data_type":"","edge_type":"data","independent_layout":false,"shape":[1,3,224,224]}},"name":"Default/bn1/Reshape[12]_1/Reshape8","output":{},"output_i":0,"proxy_input":{},"proxy_output":{},"subnode_count":0,"type":"Reshape"},{"attr":{},"independent_layout":false,"input":{"Default/bn1/x":{"data_type":"","edge_type":"data","independent_layout":false,"shape":[1,3,224,224]}},"name":"Default/bn1/Reshape[12]_1/Reshape9","output":{},"output_i":0,"proxy_input":{},"proxy_output":{},"subnode_count":0,"type":"Reshape"},{"attr":{},"independent_layout":false,"input":{"Default/bn1/x":{"data_type":"","edge_type":"data","independent_layout":false,"shape":[1,3,224,224]}},"name":"Default/bn1/Reshape[12]_1/Reshape10","output":{},"output_i":0,"proxy_input":{},"proxy_output":{},"subnode_count":0,"type":"Reshape"},{"attr":{},"independent_layout":false,"input":{"Default/bn1/x":{"data_type":"","edge_type":"data","independent_layout":false,"shape":[1,3,224,224]}},"name":"Default/bn1/Reshape[12]_1/Reshape11","output":{},"output_i":0,"proxy_input":{},"proxy_output":{},"subnode_count":0,"type":"Reshape"},{"attr":{},"independent_layout":false,"input":{"Default/bn1/x":{"data_type":"","edge_type":"data","independent_layout":false,"shape":[1,3,224,224]}},"name":"Default/bn1/Reshape[12]_1/Reshape12","output":{},"output_i":0,"proxy_input":{},"proxy_output":{},"subnode_count":0,"type":"Reshape"}]}
\ No newline at end of file

tests/ut/datavisual/processors/graph_results/test_get_nodes_success_expected_results4.json

+{"nodes":[{"attr":{},"independent_layout":false,"input":{"Default/bn1-BatchNorm2d/Parameter[22]_3/x":{"data_type":"","edge_type":"data","independent_layout":true,"shape":[1,3,224,224]},"Default/bn1-BatchNorm2d/Parameter[22]_3/x1":{"data_type":"","edge_type":"data","independent_layout":true,"shape":[1,3,224,224]},"Default/bn1-BatchNorm2d/Parameter[22]_3/x10":{"data_type":"","edge_type":"data","independent_layout":true,"shape":[1,3,224,224]},"Default/bn1-BatchNorm2d/Parameter[22]_3/x2":{"data_type":"","edge_type":"data","independent_layout":true,"shape":[1,3,224,224]},"Default/bn1-BatchNorm2d/Parameter[22]_3/x3":{"data_type":"","edge_type":"data","independent_layout":true,"shape":[1,3,224,224]},"Default/bn1-BatchNorm2d/Parameter[22]_3/x4":{"data_type":"","edge_type":"data","independent_layout":true,"shape":[1,3,224,224]},"Default/bn1-BatchNorm2d/Parameter[22]_3/x5":{"data_type":"","edge_type":"data","independent_layout":true,"shape":[1,3,224,224]},"Default/bn1-BatchNorm2d/Parameter[22]_3/x6":{"data_type":"","edge_type":"data","independent_layout":true,"shape":[1,3,224,224]},"Default/bn1-BatchNorm2d/Parameter[22]_3/x7":{"data_type":"","edge_type":"data","independent_layout":true,"shape":[1,3,224,224]},"Default/bn1-BatchNorm2d/Parameter[22]_3/x8":{"data_type":"","edge_type":"data","independent_layout":true,"shape":[1,3,224,224]},"Default/bn1-BatchNorm2d/Parameter[22]_3/x9":{"data_type":"","edge_type":"data","independent_layout":true,"shape":[1,3,224,224]},"Default/bn1-BatchNorm2d/cst13":{"data_type":"","edge_type":"data","independent_layout":false,"shape":[]}},"name":"Default/bn1-BatchNorm2d/tuple_getitem56","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":{"Default/bn1-BatchNorm2d/Parameter[22]_3":{"edge_type":"data"}},"proxy_output":{},"subnode_count":0,"type":"tuple_getitem"},{"attr":{},"independent_layout":false,"input":{"Default/bn1-BatchNorm2d/Parameter[22]_3/conv1.weight":{"data_type":"","edge_type":"data","independent_layout":true,"shape":[64,3,7,7]},"Default/bn1-BatchNorm2d/Parameter[22]_3/x11":{"data_type":"","edge_type":"data","independent_layout":true,"shape":[1,3,224,224]},"Default/bn1-BatchNorm2d/Parameter[22]_3/x12":{"data_type":"","edge_type":"data","independent_layout":true,"shape":[1,3,224,224]},"Default/bn1-BatchNorm2d/Parameter[22]_3/x13":{"data_type":"","edge_type":"data","independent_layout":true,"shape":[1,3,224,224]},"Default/bn1-BatchNorm2d/Parameter[22]_3/x14":{"data_type":"","edge_type":"data","independent_layout":true,"shape":[1,3,224,224]},"Default/bn1-BatchNorm2d/Parameter[22]_3/x15":{"data_type":"","edge_type":"data","independent_layout":true,"shape":[1,3,224,224]},"Default/bn1-BatchNorm2d/Parameter[22]_3/x16":{"data_type":"","edge_type":"data","independent_layout":true,"shape":[1,3,224,224]},"Default/bn1-BatchNorm2d/Parameter[22]_3/x17":{"data_type":"","edge_type":"data","independent_layout":true,"shape":[1,3,224,224]},"Default/bn1-BatchNorm2d/Parameter[22]_3/x18":{"data_type":"","edge_type":"data","independent_layout":true,"shape":[1,3,224,224]},"Default/bn1-BatchNorm2d/Parameter[22]_3/x19":{"data_type":"","edge_type":"data","independent_layout":true,"shape":[1,3,224,224]},"Default/bn1-BatchNorm2d/Parameter[22]_3/x20":{"data_type":"","edge_type":"data","independent_layout":true,"shape":[1,3,224,224]},"Default/bn1-BatchNorm2d/cst25":{"data_type":"","edge_type":"data","independent_layout":false,"shape":[]}},"name":"Default/bn1-BatchNorm2d/tuple_getitem105","output":{},"output_i":0,"proxy_input":{"Default/bn1-BatchNorm2d/Parameter[22]_3":{"edge_type":"data"}},"proxy_output":{},"subnode_count":0,"type":"tuple_getitem"},{"attr":{},"independent_layout":true,"input":{},"name":"Default/bn1-BatchNorm2d/Parameter[22]_3","output":{"Default/bn1-BatchNorm2d/tuple_getitem105":{"data_type":"","edge_type":"data","independent_layout":true,"shape":[64,3,7,7]},"Default/bn1-BatchNorm2d/tuple_getitem56":{"data_type":"","edge_type":"data","independent_layout":true,"shape":[1,3,224,224]}},"output_i":0,"proxy_input":{},"proxy_output":{"Default/bn1-BatchNorm2d/tuple_getitem105":{"edge_type":"data"},"Default/bn1-BatchNorm2d/tuple_getitem56":{"edge_type":"data"}},"subnode_count":22,"type":"aggregation_scope"},{"attr":{"cst13":"dtype: DT_INT32\nint_val: 0\n"},"independent_layout":false,"input":{},"name":"Default/bn1-BatchNorm2d/cst13","output":{"Default/bn1-BatchNorm2d/tuple_getitem56":{"data_type":"","edge_type":"data","independent_layout":false,"shape":[]}},"output_i":0,"proxy_input":{},"proxy_output":{},"subnode_count":0,"type":"Const"},{"attr":{"cst25":"dtype: DT_INT32\nint_val: 0\n"},"independent_layout":false,"input":{},"name":"Default/bn1-BatchNorm2d/cst25","output":{"Default/bn1-BatchNorm2d/tuple_getitem105":{"data_type":"","edge_type":"data","independent_layout":false,"shape":[]}},"output_i":0,"proxy_input":{},"proxy_output":{},"subnode_count":0,"type":"Const"}]}
\ No newline at end of file

tests/ut/datavisual/processors/graph_results/test_search_node_names_with_offset_expected_results1.json

-{"names":["Default/bn1-BatchNorm2d/cst25","Default/bn1-BatchNorm2d/tuple_getitem105","Default/bn1-BatchNorm2d/tuple_getitem53"]}
\ No newline at end of file
+{"names":["Default/bn1-BatchNorm2d/Parameter[22]_3/conv1.weight","Default/bn1-BatchNorm2d/Parameter[22]_3/x","Default/bn1-BatchNorm2d/Parameter[22]_3/x1"]}
\ No newline at end of file

tests/ut/datavisual/processors/graph_results/test_search_node_names_with_search_content_expected_results1.json

-
-{
-  "names" : ["Default", "Default/bn1", "Default/bn1-BatchNorm2d", "Default/bn1-BatchNorm2d/conv1.weight", "Default/bn1-BatchNorm2d/cst25", "Default/bn1-BatchNorm2d/tuple_getitem105", "Default/bn1-BatchNorm2d/tuple_getitem53", "Default/bn1-BatchNorm2d/x11", "Default/bn1-BatchNorm2d/x12", "Default/bn1-BatchNorm2d/x13", "Default/bn1-BatchNorm2d/x14", "Default/bn1-BatchNorm2d/x15", "Default/bn1-BatchNorm2d/x16", "Default/bn1-BatchNorm2d/x17", "Default/bn1-BatchNorm2d/x18", "Default/bn1-BatchNorm2d/x19", "Default/bn1-BatchNorm2d/x20", "Default/bn1/Add50", "Default/bn1/Add51", "Default/bn1/Add52", "Default/bn1/Add53", "Default/bn1/Add54", "Default/bn1/Reshape1", "Default/bn1/Reshape10", "Default/bn1/Reshape11", "Default/bn1/Reshape12", "Default/bn1/Reshape2", "Default/bn1/Reshape3", "Default/bn1/Reshape4", "Default/bn1/Reshape5", "Default/bn1/Reshape6", "Default/bn1/Reshape7", "Default/bn1/Reshape8", "Default/bn1/Reshape9", "Default/bn1/Reshape_1_[12]", "Default/bn1/conv1.weight", "Default/bn1/cst13", "Default/bn1/x", "Default/bn1/x1", "Default/bn1/x10", "Default/bn1/x11", "Default/bn1/x2", "Default/bn1/x3", "Default/bn1/x4", "Default/bn1/x5", "Default/bn1/x6", "Default/bn1/x7", "Default/bn1/x8", "Default/bn1/x9", "Default/conv1-Conv2d", "Default/conv1-Conv2d/Conv2D1"]
-}
\ No newline at end of file
+{"names":["Default","Default/bn1","Default/bn1-BatchNorm2d","Default/bn1-BatchNorm2d/Parameter[22]_3","Default/bn1-BatchNorm2d/Parameter[22]_3/conv1.weight","Default/bn1-BatchNorm2d/Parameter[22]_3/x","Default/bn1-BatchNorm2d/Parameter[22]_3/x1","Default/bn1-BatchNorm2d/Parameter[22]_3/x10","Default/bn1-BatchNorm2d/Parameter[22]_3/x11","Default/bn1-BatchNorm2d/Parameter[22]_3/x12","Default/bn1-BatchNorm2d/Parameter[22]_3/x13","Default/bn1-BatchNorm2d/Parameter[22]_3/x14","Default/bn1-BatchNorm2d/Parameter[22]_3/x15","Default/bn1-BatchNorm2d/Parameter[22]_3/x16","Default/bn1-BatchNorm2d/Parameter[22]_3/x17","Default/bn1-BatchNorm2d/Parameter[22]_3/x18","Default/bn1-BatchNorm2d/Parameter[22]_3/x19","Default/bn1-BatchNorm2d/Parameter[22]_3/x2","Default/bn1-BatchNorm2d/Parameter[22]_3/x20","Default/bn1-BatchNorm2d/Parameter[22]_3/x3","Default/bn1-BatchNorm2d/Parameter[22]_3/x4","Default/bn1-BatchNorm2d/Parameter[22]_3/x5","Default/bn1-BatchNorm2d/Parameter[22]_3/x6","Default/bn1-BatchNorm2d/Parameter[22]_3/x7","Default/bn1-BatchNorm2d/Parameter[22]_3/x8","Default/bn1-BatchNorm2d/Parameter[22]_3/x9","Default/bn1-BatchNorm2d/cst13","Default/bn1-BatchNorm2d/cst25","Default/bn1-BatchNorm2d/tuple_getitem105","Default/bn1-BatchNorm2d/tuple_getitem56","Default/bn1/Add[5]_0","Default/bn1/Add[5]_0/Add50","Default/bn1/Add[5]_0/Add51","Default/bn1/Add[5]_0/Add52","Default/bn1/Add[5]_0/Add53","Default/bn1/Add[5]_0/Add54","Default/bn1/Reshape[12]_1","Default/bn1/Reshape[12]_1/Reshape1","Default/bn1/Reshape[12]_1/Reshape10","Default/bn1/Reshape[12]_1/Reshape11","Default/bn1/Reshape[12]_1/Reshape12","Default/bn1/Reshape[12]_1/Reshape2","Default/bn1/Reshape[12]_1/Reshape3","Default/bn1/Reshape[12]_1/Reshape4","Default/bn1/Reshape[12]_1/Reshape5","Default/bn1/Reshape[12]_1/Reshape6","Default/bn1/Reshape[12]_1/Reshape7","Default/bn1/Reshape[12]_1/Reshape8","Default/bn1/Reshape[12]_1/Reshape9","Default/bn1/x","Default/bn1/x11","Default/conv1-Conv2d","Default/conv1-Conv2d/Conv2D55","Default/conv1-Conv2d/Parameter[12]_2","Default/conv1-Conv2d/Parameter[12]_2/conv1.weight","Default/conv1-Conv2d/Parameter[12]_2/x","Default/conv1-Conv2d/Parameter[12]_2/x1","Default/conv1-Conv2d/Parameter[12]_2/x10","Default/conv1-Conv2d/Parameter[12]_2/x2","Default/conv1-Conv2d/Parameter[12]_2/x3","Default/conv1-Conv2d/Parameter[12]_2/x4","Default/conv1-Conv2d/Parameter[12]_2/x5","Default/conv1-Conv2d/Parameter[12]_2/x6","Default/conv1-Conv2d/Parameter[12]_2/x7","Default/conv1-Conv2d/Parameter[12]_2/x8","Default/conv1-Conv2d/Parameter[12]_2/x9"]}
\ No newline at end of file

tests/ut/datavisual/processors/graph_results/test_search_node_names_with_search_content_expected_results2.json

-{"names":["Default/bn1","Default/bn1-BatchNorm2d","Default/bn1-BatchNorm2d/conv1.weight","Default/bn1-BatchNorm2d/cst25","Default/bn1-BatchNorm2d/tuple_getitem105","Default/bn1-BatchNorm2d/tuple_getitem53","Default/bn1-BatchNorm2d/x11","Default/bn1-BatchNorm2d/x12","Default/bn1-BatchNorm2d/x13","Default/bn1-BatchNorm2d/x14","Default/bn1-BatchNorm2d/x15","Default/bn1-BatchNorm2d/x16","Default/bn1-BatchNorm2d/x17","Default/bn1-BatchNorm2d/x18","Default/bn1-BatchNorm2d/x19","Default/bn1-BatchNorm2d/x20","Default/bn1/Add50","Default/bn1/Add51","Default/bn1/Add52","Default/bn1/Add53","Default/bn1/Add54","Default/bn1/Reshape1","Default/bn1/Reshape10","Default/bn1/Reshape11","Default/bn1/Reshape12","Default/bn1/Reshape2","Default/bn1/Reshape3","Default/bn1/Reshape4","Default/bn1/Reshape5","Default/bn1/Reshape6","Default/bn1/Reshape7","Default/bn1/Reshape8","Default/bn1/Reshape9","Default/bn1/Reshape_1_[12]","Default/bn1/conv1.weight","Default/bn1/cst13","Default/bn1/x","Default/bn1/x1","Default/bn1/x10","Default/bn1/x11","Default/bn1/x2","Default/bn1/x3","Default/bn1/x4","Default/bn1/x5","Default/bn1/x6","Default/bn1/x7","Default/bn1/x8","Default/bn1/x9"]}
+{"names":["Default/bn1","Default/bn1-BatchNorm2d","Default/bn1-BatchNorm2d/Parameter[22]_3","Default/bn1-BatchNorm2d/Parameter[22]_3/conv1.weight","Default/bn1-BatchNorm2d/Parameter[22]_3/x","Default/bn1-BatchNorm2d/Parameter[22]_3/x1","Default/bn1-BatchNorm2d/Parameter[22]_3/x10","Default/bn1-BatchNorm2d/Parameter[22]_3/x11","Default/bn1-BatchNorm2d/Parameter[22]_3/x12","Default/bn1-BatchNorm2d/Parameter[22]_3/x13","Default/bn1-BatchNorm2d/Parameter[22]_3/x14","Default/bn1-BatchNorm2d/Parameter[22]_3/x15","Default/bn1-BatchNorm2d/Parameter[22]_3/x16","Default/bn1-BatchNorm2d/Parameter[22]_3/x17","Default/bn1-BatchNorm2d/Parameter[22]_3/x18","Default/bn1-BatchNorm2d/Parameter[22]_3/x19","Default/bn1-BatchNorm2d/Parameter[22]_3/x2","Default/bn1-BatchNorm2d/Parameter[22]_3/x20","Default/bn1-BatchNorm2d/Parameter[22]_3/x3","Default/bn1-BatchNorm2d/Parameter[22]_3/x4","Default/bn1-BatchNorm2d/Parameter[22]_3/x5","Default/bn1-BatchNorm2d/Parameter[22]_3/x6","Default/bn1-BatchNorm2d/Parameter[22]_3/x7","Default/bn1-BatchNorm2d/Parameter[22]_3/x8","Default/bn1-BatchNorm2d/Parameter[22]_3/x9","Default/bn1-BatchNorm2d/cst13","Default/bn1-BatchNorm2d/cst25","Default/bn1-BatchNorm2d/tuple_getitem105","Default/bn1-BatchNorm2d/tuple_getitem56","Default/bn1/Add[5]_0","Default/bn1/Add[5]_0/Add50","Default/bn1/Add[5]_0/Add51","Default/bn1/Add[5]_0/Add52","Default/bn1/Add[5]_0/Add53","Default/bn1/Add[5]_0/Add54","Default/bn1/Reshape[12]_1","Default/bn1/Reshape[12]_1/Reshape1","Default/bn1/Reshape[12]_1/Reshape10","Default/bn1/Reshape[12]_1/Reshape11","Default/bn1/Reshape[12]_1/Reshape12","Default/bn1/Reshape[12]_1/Reshape2","Default/bn1/Reshape[12]_1/Reshape3","Default/bn1/Reshape[12]_1/Reshape4","Default/bn1/Reshape[12]_1/Reshape5","Default/bn1/Reshape[12]_1/Reshape6","Default/bn1/Reshape[12]_1/Reshape7","Default/bn1/Reshape[12]_1/Reshape8","Default/bn1/Reshape[12]_1/Reshape9","Default/bn1/x","Default/bn1/x11"]}
\ No newline at end of file

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

-{"children":{"children":{},"nodes":[{"attr":{},"input":{},"name":"Default/conv1-Conv2d","output":{},"output_i":-1,"polymeric_input":{},"polymeric_output":{},"polymeric_scope_name":"","subnode_count":1,"type":"name_scope"},{"attr":{},"input":{},"name":"Default/bn1-BatchNorm2d","output":{},"output_i":-1,"polymeric_input":{},"polymeric_output":{},"polymeric_scope_name":"","subnode_count":14,"type":"name_scope"},{"attr":{},"input":{},"name":"Default/bn1","output":{},"output_i":-1,"polymeric_input":{},"polymeric_output":{},"polymeric_scope_name":"","subnode_count":20,"type":"name_scope"}],"scope_name":"Default"},"nodes":[{"attr":{},"input":{},"name":"Default","output":{},"output_i":-1,"polymeric_input":{},"polymeric_output":{},"polymeric_scope_name":"","subnode_count":3,"type":"name_scope"}],"scope_name":""}
+{"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":""}
\ No newline at end of file

tests/ut/datavisual/processors/test_graph_processor.py

@@ -118,26 +118,27 @@ class TestGraphProcessor:
         assert mock_get_train_job_by_plugin.called
 
     @pytest.mark.usefixtures('load_graph_record')
-    @pytest.mark.parametrize("name, node_type", [("not_exist_name", "name_scope"), ("", "polymeric_scope")])
-    def test_get_nodes_with_not_exist_name(self, name, node_type):
+    @pytest.mark.parametrize("name", ["not_exist_name"])
+    def test_get_nodes_with_not_exist_name(self, name):
         """Test getting nodes with not exist name."""
         with pytest.raises(NodeNotInGraphError) as exc_info:
             graph_processor = GraphProcessor(self._train_id, self._mock_data_manager)
-            graph_processor.get_nodes(name, node_type)
+            graph_processor.list_nodes(name)
 
         assert 'Can not find node in graph by the given node name' in exc_info.value.message
 
     @pytest.mark.usefixtures('load_graph_record')
     @pytest.mark.parametrize(
-        "name, node_type, result_file",
-        [(None, 'name_scope', 'test_get_nodes_success_expected_results1.json'),
-         ('Default/conv1-Conv2d', 'name_scope', 'test_get_nodes_success_expected_results2.json'),
-         ('Default/bn1/Reshape_1_[12]', 'polymeric_scope', 'test_get_nodes_success_expected_results3.json')])
-    def test_get_nodes_success(self, name, node_type, result_file):
+        "name, result_file",
+        [(None, 'test_get_nodes_success_expected_results1.json'),
+         ('Default/conv1-Conv2d', 'test_get_nodes_success_expected_results2.json'),
+         ('Default/bn1/Reshape[12]_1', 'test_get_nodes_success_expected_results3.json'),
+         ('Default/bn1-BatchNorm2d', 'test_get_nodes_success_expected_results4.json'),
+         ])
+    def test_get_nodes_success(self, name, result_file):
         """Test getting nodes successfully."""
-
         graph_processor = GraphProcessor(self._train_id, self._mock_data_manager)
-        results = graph_processor.get_nodes(name, node_type)
+        results = graph_processor.list_nodes(name)
 
         expected_file_path = os.path.join(self.graph_results_dir, result_file)
         compare_result_with_file(results, expected_file_path)

tests/utils/log_generators/cyclic_graph.json

+{
+  "node": [
+    {
+      "input": [
+        {
+          "name": "data",
+          "type": "DATA_EDGE"
+        }
+      ],
+      "name": "1",
+      "opType": "Conv2D",
+      "scope": "Default",
+      "attribute": [
+        {
+          "name": "output_names",
+          "value": {
+            "dtype": "DT_GRAPHS",
+            "values": [
+              {
+                "dtype": "DT_FLOAT64",
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+          "type": "DATA_EDGE"
+        }
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+      "opType": "Conv2D",
+      "scope": "Default",
+      "attribute": [
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+          "name": "output_names",
+          "value": {
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+            "values": [
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+                "dtype": "DT_FLOAT64",
+                "strVal": "output"
+              }
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+          }
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+        "tensorType": {
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+        }
+      }
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+          "type": "DATA_EDGE"
+        }
+      ],
+      "name": "4",
+      "opType": "Add",
+      "scope": "Default",
+      "attribute": [
+        {
+          "name": "output_names",
+          "value": {
+            "dtype": "DT_GRAPHS",
+            "values": [
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+                "dtype": "DT_FLOAT64",
+                "strVal": "output"
+              }
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+          }
+        }
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+        "dataType": "DT_STRING",
+        "tensorType": {
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+          }
+        }
+      }
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+    {
+      "input": [
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+          "type": "DATA_EDGE"
+        }
+      ],
+      "name": "5",
+      "opType": "Conv2D",
+      "scope": "Default",
+      "attribute": [
+        {
+          "name": "output_names",
+          "value": {
+            "dtype": "DT_GRAPHS",
+            "values": [
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+                "dtype": "DT_FLOAT64",
+                "strVal": "output"
+              }
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+          "type": "DATA_EDGE"
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+      "opType": "Add",
+      "scope": "Default",
+      "attribute": [
+        {
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+          "value": {
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+          "type": "DATA_EDGE"
+        }
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+      "scope": "Default",
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+                "strVal": "output"
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+              }
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+          "type": "DATA_EDGE"
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+      "scope": "Default",
+      "attribute": [
+        {
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+          "value": {
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+                "strVal": "output"
+              }
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+          "type": "DATA_EDGE"
+        }
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+      "opType": "Conv2D",
+      "scope": "Default",
+      "attribute": [
+        {
+          "name": "output_names",
+          "value": {
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+                "strVal": "output"
+              }
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+          }
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+          "type": "DATA_EDGE"
+        }
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+      "scope": "Default",
+      "attribute": [
+        {
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+          "value": {
+            "dtype": "DT_GRAPHS",
+            "values": [
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+                "strVal": "output"
+              }
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+          }
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+        "tensorType": {
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+          "type": "DATA_EDGE"
+        }
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+      "opType": "Conv2D",
+      "scope": "Default",
+      "attribute": [
+        {
+          "name": "output_names",
+          "value": {
+            "dtype": "DT_GRAPHS",
+            "values": [
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+                "strVal": "output"
+              }
+            ]
+          }
+        }
+      ],
+      "outputType": {
+        "dataType": "DT_STRING",
+        "tensorType": {
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+              }
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+          }
+        }
+      }
+    },
+    {
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+          "type": "DATA_EDGE"
+        }
+      ],
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+      "opType": "Conv2D",
+      "scope": "Default",
+      "attribute": [
+        {
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+          "value": {
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+            "values": [
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+                "strVal": "output"
+              }
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+          }
+        }
+      ],
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+        "tensorType": {
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+              }
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+          }
+        }
+      }
+    },
+    {
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+          "type": "DATA_EDGE"
+        }
+      ],
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+      "opType": "Conv2D",
+      "scope": "Default",
+      "attribute": [
+        {
+          "name": "output_names",
+          "value": {
+            "dtype": "DT_GRAPHS",
+            "values": [
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+                "strVal": "output"
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+        "tensorType": {
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+          "shape": {
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+    {
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+          "name": "9",
+          "type": "DATA_EDGE"
+        }
+      ],
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+      "opType": "Conv2D",
+      "scope": "Default",
+      "attribute": [
+        {
+          "name": "output_names",
+          "value": {
+            "dtype": "DT_GRAPHS",
+            "values": [
+              {
+                "dtype": "DT_FLOAT64",
+                "strVal": "output"
+              }
+            ]
+          }
+        }
+      ],
+      "outputType": {
+        "dataType": "DT_STRING",
+        "tensorType": {
+          "elemType": "DT_FLOAT16",
+          "shape": {
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+              {
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+              }
+            ]
+          }
+        }
+      }
+    },
+    {
+      "input": [
+        {
+          "name": "14",
+          "type": "DATA_EDGE"
+        }
+      ],
+      "name": "15",
+      "opType": "Conv2D",
+      "scope": "Default",
+      "attribute": [
+        {
+          "name": "output_names",
+          "value": {
+            "dtype": "DT_GRAPHS",
+            "values": [
+              {
+                "dtype": "DT_FLOAT64",
+                "strVal": "output"
+              }
+            ]
+          }
+        }
+      ],
+      "outputType": {
+        "dataType": "DT_STRING",
+        "tensorType": {
+          "elemType": "DT_FLOAT16",
+          "shape": {
+            "dim": [
+              {
+                "size": "1"
+              }
+            ]
+          }
+        }
+      }
+    },
+    {
+      "input": [
+        {
+          "name": "15",
+          "type": "DATA_EDGE"
+        }
+      ],
+      "name": "16",
+      "opType": "Conv2D",
+      "scope": "Default",
+      "attribute": [
+        {
+          "name": "output_names",
+          "value": {
+            "dtype": "DT_GRAPHS",
+            "values": [
+              {
+                "dtype": "DT_FLOAT64",
+                "strVal": "output"
+              }
+            ]
+          }
+        }
+      ],
+      "outputType": {
+        "dataType": "DT_STRING",
+        "tensorType": {
+          "elemType": "DT_FLOAT16",
+          "shape": {
+            "dim": [
+              {
+                "size": "1"
+              }
+            ]
+          }
+        }
+      }
+    }
+  ],
+  "name": "849_848_847_424_1_construct",
+  "parameters": [
+    {
+      "name": "data",
+      "type": {
+        "dataType": "DT_STRING",
+        "tensorType": {
+          "elemType": "DT_FLOAT16",
+          "shape": {
+            "dim": [
+              {
+                "size": "1"
+              },
+              {
+                "size": "3"
+              },
+              {
+                "size": "224"
+              },
+              {
+                "size": "224"
+              }
+            ]
+          }
+        }
+      }
+    }
+  ]
+}

tests/utils/log_generators/graph_base.json

@@ -51,7 +51,7 @@
           "type": "DATA_EDGE"
         }
       ],
-      "name": "1",
+      "name": "55",
       "opType": "Conv2D",
       "scope": "Default/conv1-Conv2d",
       "attribute": [
@@ -149,7 +149,7 @@
           "type": "DATA_EDGE"
         }
       ],
-      "name": "53",
+      "name": "56",
       "opType": "tuple_getitem",
       "scope": "Default/bn1-BatchNorm2d",
       "outputType": {
@@ -354,7 +354,7 @@
     {
       "input": [
         {
-          "name": "x11",
+          "name": "56",
           "type": "DATA_EDGE"
         }
       ],
@@ -585,7 +585,7 @@
     {
       "input": [
         {
-          "name": "x",
+          "name": "55",
           "type": "DATA_EDGE"
         }
       ],

tests/utils/log_generators/high_degree_graph.json

+{
+  "node": [
+    {
+      "input": [
+        {
+          "name": "6",
+          "type": "DATA_EDGE"
+        }
+      ],
+      "name": "1",
+      "opType": "Conv2D",
+      "scope": "Default",
+      "attribute": [
+        {
+          "name": "output_names",
+          "value": {
+            "dtype": "DT_GRAPHS",
+            "values": [
+              {
+                "dtype": "DT_FLOAT64",
+                "strVal": "output"
+              }
+            ]
+          }
+        }
+      ],
+      "outputType": {
+        "dataType": "DT_STRING",
+        "tensorType": {
+          "elemType": "DT_FLOAT16",
+          "shape": {
+            "dim": [
+              {
+                "size": "1"
+              }
+            ]
+          }
+        }
+      }
+    },
+    {
+      "input": [
+        {
+          "name": "7",
+          "type": "DATA_EDGE"
+        }
+      ],
+      "name": "2",
+      "opType": "Conv2D",
+      "scope": "Default",
+      "attribute": [
+        {
+          "name": "output_names",
+          "value": {
+            "dtype": "DT_GRAPHS",
+            "values": [
+              {
+                "dtype": "DT_FLOAT64",
+                "strVal": "output"
+              }
+            ]
+          }
+        }
+      ],
+      "outputType": {
+        "dataType": "DT_STRING",
+        "tensorType": {
+          "elemType": "DT_FLOAT16",
+          "shape": {
+            "dim": [
+              {
+                "size": "1"
+              }
+            ]
+          }
+        }
+      }
+    },
+    {
+      "input": [
+        {
+          "name": "8",
+          "type": "DATA_EDGE"
+        }
+      ],
+      "name": "3",
+      "opType": "Conv2D",
+      "scope": "Default",
+      "attribute": [
+        {
+          "name": "output_names",
+          "value": {
+            "dtype": "DT_GRAPHS",
+            "values": [
+              {
+                "dtype": "DT_FLOAT64",
+                "strVal": "output"
+              }
+            ]
+          }
+        }
+      ],
+      "outputType": {
+        "dataType": "DT_STRING",
+        "tensorType": {
+          "elemType": "DT_FLOAT16",
+          "shape": {
+            "dim": [
+              {
+                "size": "1"
+              }
+            ]
+          }
+        }
+      }
+    },
+    {
+      "input": [
+        {
+          "name": "14",
+          "type": "DATA_EDGE"
+        }
+      ],
+      "name": "4",
+      "opType": "Conv2D",
+      "scope": "Default",
+      "attribute": [
+        {
+          "name": "output_names",
+          "value": {
+            "dtype": "DT_GRAPHS",
+            "values": [
+              {
+                "dtype": "DT_FLOAT64",
+                "strVal": "output"
+              }
+            ]
+          }
+        }
+      ],
+      "outputType": {
+        "dataType": "DT_STRING",
+        "tensorType": {
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+          "shape": {
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+              }
+            ]
+          }
+        }
+      }
+    },
+    {
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+        {
+          "name": "10",
+          "type": "DATA_EDGE"
+        }
+      ],
+      "name": "5",
+      "opType": "Conv2D",
+      "scope": "Default",
+      "attribute": [
+        {
+          "name": "output_names",
+          "value": {
+            "dtype": "DT_GRAPHS",
+            "values": [
+              {
+                "dtype": "DT_FLOAT64",
+                "strVal": "output"
+              }
+            ]
+          }
+        }
+      ],
+      "outputType": {
+        "dataType": "DT_STRING",
+        "tensorType": {
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+              }
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+      }
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+          "type": "DATA_EDGE"
+        }
+      ],
+      "name": "6",
+      "opType": "Add",
+      "scope": "Default",
+      "attribute": [
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+          "value": {
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+                "strVal": "output"
+              }
+            ]
+          }
+        }
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+          "name": "data",
+          "type": "DATA_EDGE"
+        }
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+      "opType": "Sub",
+      "scope": "Default",
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+          "type": "DATA_EDGE"
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+      "scope": "Default",
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+          "type": "DATA_EDGE"
+        }
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+      "opType": "Reshape",
+      "scope": "Default",
+      "attribute": [
+        {
+          "name": "output_names",
+          "value": {
+            "dtype": "DT_GRAPHS",
+            "values": [
+              {
+                "dtype": "DT_FLOAT64",
+                "strVal": "output"
+              }
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+          }
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+      "outputType": {
+        "dataType": "DT_STRING",
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+        }
+      }
+    },
+    {
+      "input": [
+        {
+          "name": "data",
+          "type": "DATA_EDGE"
+        }
+      ],
+      "name": "10",
+      "opType": "Mul",
+      "scope": "Default",
+      "attribute": [
+        {
+          "name": "output_names",
+          "value": {
+            "dtype": "DT_GRAPHS",
+            "values": [
+              {
+                "dtype": "DT_FLOAT64",
+                "strVal": "output"
+              }
+            ]
+          }
+        }
+      ],
+      "outputType": {
+        "dataType": "DT_STRING",
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