ke function to detect edge labels in subgraph_matching kernel not working.

[georgia-max]

Describe the bug
I am trying to get the similarity scores between the two graphs using the SubgraphMatching Kernel, that take into account both node labels and edge labels : SubgraphMatching(normalize=True, ke=custom_edge_kernel, kv = custom_label_kernel)

This should result in a score that is not equal to 1 since one of the edge_labels is different. However, I am getting a score of 1.

To Reproduce

from grakel import Graph
from grakel.kernels import SubgraphMatching

# Define a custom edge kernel function
def custom_edge_kernel(label1, label2):
    # Example: Assign partial similarity for mismatched labels
    print(label1, label2)
    if label1 == label2:
        return 1  # Perfect match
    else:
        return 0.5  # Partial similarity for mismatched labels
def custom_label_kernel(label1, label2):
    # Example: Assign partial similarity for mismatched labels
    # print(label1, label2)
    if label1 == label2:
        return 1  # Perfect match
    else:
        return 0.5  # Partial similarity for mismatched labels

# Define two graphs with labeled edges and nodes
graph1 = {
    "edge": {(0, 1):1, (1, 2):1},
    # "edge": {0:{1:1}, 1:{2:1}},
    "node_labels": {0: 'A', 1: 'B', 2: 'A'},
    "edge_labels": {(0, 1): 'X', (1, 2): 'Z'}  # Edge labels
}

graph2 = {
    "edge": {(0, 1):1, (1, 2):1},
    # "edge": {0:{1:1}, 1:{2:1}},

    "node_labels": {0: 'A', 1: 'B', 2: 'A'},
    "edge_labels": {(0, 1): 'X', (1, 2): 'Y'}  # Note: Different edge label 'Z'
}

# Create Graph objects
G1 = Graph(
    initialization_object = graph1["edge_labels"], 
    node_labels=graph1["node_labels"], 
    edge_labels=graph1["edge_labels"], 
    graph_format="all"
)
G2 = Graph(
    initialization_object = graph2["edge_labels"], 
    node_labels=graph2["node_labels"], 
    edge_labels=graph2["edge_labels"], 
    graph_format="all"
)


# Initialize Subgraph Matching Kernel with custom edge kernel
sm_kernel = SubgraphMatching(normalize=True, ke=custom_edge_kernel, kv = custom_label_kernel)

# Compute the kernel matrix
K = sm_kernel.fit_transform([G1, G2])

# Output the kernel matrix
print("Kernel Matrix:")
print(K)

my result running the code is:

Kernel Matrix: [[1. 1.] [1. 1.]]