add: test cases of _remove_auxiliary_nodes()

In this commit, I have implemented example test cases to test method: _remove_auxiliary_nodes in @pytest.mark.parametrize. Also,fixed the import error of networkx.

tests/shared/core/training_data/test_visualization.py

@@ -10,6 +10,8 @@
 from rasa.shared.nlu.training_data.message import Message
 from rasa.shared.nlu.training_data.training_data import TrainingData
 
+import pytest
+
 
 def test_style_transfer():
     r = visualization._transfer_style({"class": "dashed great"}, {"class": "myclass"})
@@ -190,19 +192,35 @@ def test_story_visualization_with_merging(domain: Domain):
     assert 20 < len(generated_graph.edges()) < 33
 
 
-def test_remove_auxiliary_nodes():
+@pytest.mark.parametrize("input_nodes, input_edges, remove_count, expected_nodes, expected_edges", [
+    (
+        [-2, -1, 0, 1, 2, 3, 4, 5],
+        [(-2, 0), (-1, 0), (0, 1), (1, 2), (2, 3), (3, 4), (4, 5)],
+        3,
+        set([0, 1, 2, 3, 4, 5, -1]),
+        [(-1, 0), (0, 1), (1, 2), (2, 3), (3, 4), (4, 5)]
+    ),
+    (
+        [-3, -2, -1, 0, 1, 2, 3, 4, 5],
+        [(-3, -2), (-2, -1), (-1, 0), (0, 1), (1, 2), (2, 3), (3, 4), (4, 5)],
+        4,
+        set([-3, -1, 0, 1, 2, 3, 4, 5]),
+        [(-1, 0), (0, 1), (1, 2), (2, 3), (3, 4), (4, 5)]
+    )
+])
+def test_remove_auxiliary_nodes(input_nodes, input_edges, remove_count, expected_nodes, expected_edges):
+    import networkx as nx
+
     # Create a sample graph
     graph = nx.MultiDiGraph()
-    graph.add_nodes_from([-2, -1, 0, 1, 2, 3, 4, 5])
-    graph.add_edges_from([(-2, 0), (-1, 0), (0, 1), (1, 2), (2, 3), (3, 4), (4, 5)])
+    graph.add_nodes_from(input_nodes)
+    graph.add_edges_from(input_edges)
 
     # Call the method to remove auxiliary nodes
-    visualization._remove_auxiliary_nodes(graph, 3)
+    visualization._remove_auxiliary_nodes(graph, remove_count)
 
     # Check if the expected nodes are removed
-    expected_nodes = set([0, 1, 2, 3, 4, 5, -1])
     assert set(graph.nodes()) == expected_nodes, "Nodes mismatch"
 
     # Check if the edges are updated correctly
-    expected_edges = [(-1, 0), (0, 1), (1, 2), (2, 3), (3, 4), (4, 5)]
     assert list(graph.edges()) == expected_edges, "Edges mismatch"