refactor: remove the content= when adding nodes to a graph

- required by tests but can be done by the testing function itself

hdk/common/optimization/topological.py

@@ -42,7 +42,7 @@ def fuse_float_operations(op_graph: OPGraph):
 
         fused_node, node_before_subgraph = subgraph_conversion_result
 
-        nx_graph.add_node(fused_node, content=fused_node)
+        nx_graph.add_node(fused_node)
 
         if terminal_node in op_graph.output_nodes.values():
             # Output value replace it

hdk/common/tracing/tracing_helpers.py

@@ -108,11 +108,11 @@ def create_graph_from_output_tracers(
         next_tracers: Dict[BaseTracer, None] = dict()
         for tracer in current_tracers:
             current_ir_node = tracer.traced_computation
-            graph.add_node(current_ir_node, content=current_ir_node)
+            graph.add_node(current_ir_node)
 
             for input_idx, input_tracer in enumerate(tracer.inputs):
                 input_ir_node = input_tracer.traced_computation
-                graph.add_node(input_ir_node, content=input_ir_node)
+                graph.add_node(input_ir_node)
                 graph.add_edge(input_ir_node, current_ir_node, input_idx=input_idx)
                 if input_tracer not in visited_tracers:
                     next_tracers.update({input_tracer: None})

tests/common/extensions/test_table.py

@@ -50,7 +50,7 @@ def test_lookup_table_encrypted_lookup(test_helpers):
     #   (x) - (TLU)
 
     input_x = ir.Input(input_value=x, input_name="x", program_input_idx=0)
-    ref_graph.add_node(input_x, content=input_x)
+    ref_graph.add_node(input_x)
 
     output_arbitrary_function = ir.ArbitraryFunction(
         input_base_value=x,
@@ -59,7 +59,7 @@ def test_lookup_table_encrypted_lookup(test_helpers):
         op_kwargs={"table": deepcopy(table.table)},
         op_name="TLU",
     )
-    ref_graph.add_node(output_arbitrary_function, content=output_arbitrary_function)
+    ref_graph.add_node(output_arbitrary_function)
 
     ref_graph.add_edge(input_x, output_arbitrary_function, input_idx=0)
 
@@ -87,7 +87,7 @@ def test_lookup_table_encrypted_and_plain_lookup(test_helpers):
     #           (3)
 
     input_x = ir.Input(input_value=x, input_name="x", program_input_idx=0)
-    ref_graph.add_node(input_x, content=input_x)
+    ref_graph.add_node(input_x)
 
     intermediate_arbitrary_function = ir.ArbitraryFunction(
         input_base_value=x,
@@ -96,13 +96,13 @@ def test_lookup_table_encrypted_and_plain_lookup(test_helpers):
         op_kwargs={"table": deepcopy(table.table)},
         op_name="TLU",
     )
-    ref_graph.add_node(intermediate_arbitrary_function, content=intermediate_arbitrary_function)
+    ref_graph.add_node(intermediate_arbitrary_function)
 
     constant_3 = ir.Constant(3)
-    ref_graph.add_node(constant_3, content=constant_3)
+    ref_graph.add_node(constant_3)
 
     output_add = ir.Add((intermediate_arbitrary_function.outputs[0], constant_3.outputs[0]))
-    ref_graph.add_node(output_add, content=output_add)
+    ref_graph.add_node(output_add)
 
     ref_graph.add_edge(input_x, intermediate_arbitrary_function, input_idx=0)
 

tests/conftest.py

@@ -13,8 +13,16 @@ class TestHelpers:
         # edge_match is a copy of node_match
         edge_matcher = iso.categorical_multiedge_match("input_idx", None)
         node_matcher = iso.generic_node_match(
-            "content", None, lambda lhs, rhs: lhs.is_equivalent_to(rhs)
+            "_test_content", None, lambda lhs, rhs: lhs.is_equivalent_to(rhs)
         )
+
+        # Set the _test_content for each node in the graphs
+        for node in reference.nodes():
+            reference.add_node(node, _test_content=node)
+
+        for node in to_compare.nodes():
+            to_compare.add_node(node, _test_content=node)
+
         graphs_are_isomorphic = nx.is_isomorphic(
             reference,
             to_compare,

tests/helpers/test_conftest.py

@@ -31,10 +31,6 @@ def test_digraphs_are_equivalent(test_helpers):
     g_1.add_edge(t_0, t_2, input_idx=0)
     g_1.add_edge(t_1, t_2, input_idx=1)
 
-    # This updates the nodes attributes in the graph
-    for node in g_1:
-        g_1.add_node(node, content=node)
-
     t0p = TestNode("Add")
     t1p = TestNode("Mul")
     t2p = TestNode("TLU")
@@ -42,10 +38,6 @@ def test_digraphs_are_equivalent(test_helpers):
     g_2.add_edge(t1p, t2p, input_idx=1)
     g_2.add_edge(t0p, t2p, input_idx=0)
 
-    # This updates the nodes attributes in the graph
-    for node in g_2:
-        g_2.add_node(node, content=node)
-
     bad_g2 = nx.MultiDiGraph()
 
     bad_t0 = TestNode("Not Add")
@@ -53,19 +45,11 @@ def test_digraphs_are_equivalent(test_helpers):
     bad_g2.add_edge(bad_t0, t_2, input_idx=0)
     bad_g2.add_edge(t_1, t_2, input_idx=1)
 
-    # This updates the nodes attributes in the graph
-    for node in bad_g2:
-        bad_g2.add_node(node, content=node)
-
     bad_g3 = nx.MultiDiGraph()
 
     bad_g3.add_edge(t_0, t_2, input_idx=1)
     bad_g3.add_edge(t_1, t_2, input_idx=0)
 
-    # This updates the nodes attributes in the graph
-    for node in bad_g3:
-        bad_g3.add_node(node, content=node)
-
     assert test_helpers.digraphs_are_equivalent(g_1, g_2), "Graphs should be equivalent"
     assert not test_helpers.digraphs_are_equivalent(g_1, bad_g2), "Graphs should not be equivalent"
     assert not test_helpers.digraphs_are_equivalent(g_2, bad_g2), "Graphs should not be equivalent"

tests/hnumpy/test_tracing.py

@@ -100,10 +100,10 @@ def test_hnumpy_tracing_binary_op(operation, x, y, test_helpers):
         )
     )
 
-    ref_graph.add_node(input_x, content=input_x)
-    ref_graph.add_node(input_y, content=input_y)
-    ref_graph.add_node(add_node_z, content=add_node_z)
-    ref_graph.add_node(returned_final_node, content=returned_final_node)
+    ref_graph.add_node(input_x)
+    ref_graph.add_node(input_y)
+    ref_graph.add_node(add_node_z)
+    ref_graph.add_node(returned_final_node)
 
     ref_graph.add_edge(input_x, add_node_z, input_idx=0)
     ref_graph.add_edge(input_x, add_node_z, input_idx=1)