generate_candidates() doesn't work as expected - generates same triplet

Description

The function generate_candidates(X, strategy='graph_degree', target_rel='y', max_candidates=3) generates different output then shown in the example in the file, which is not correct as it is generating 3x the same array

Actual Behavior

import numpy as np
import networkx as nx
        
X = np.array([['a', 'y', 'b'],
            ['b', 'y', 'a'],
            ['a', 'y', 'c'],
            ['c', 'y', 'a'],
            ['a', 'y', 'd'],
            ['c', 'y', 'd'],
            ['b', 'y', 'c'],
            ['f', 'y', 'e']])
X_candidates = generate_candidates(X, strategy='graph_degree', target_rel='y', max_candidates=3)
array([['b', 'y', 'c'],
       ['b', 'y', 'c'],
       ['b', 'y', 'c']], dtype=object)

Expected Behavior

import numpy as np
import networkx as nx
        
X = np.array([['a', 'y', 'b'],
            ['b', 'y', 'a'],
            ['a', 'y', 'c'],
            ['c', 'y', 'a'],
            ['a', 'y', 'd'],
            ['c', 'y', 'd'],
            ['b', 'y', 'c'],
            ['f', 'y', 'e']])
X_candidates = generate_candidates(X, strategy='graph_degree', target_rel='y', max_candidates=3)
# ([['a', 'y', 'e'],
# ['f', 'y', 'a'],
# ['c', 'y', 'e']])

Steps to Reproduce

Run above mentioned code, ampligraph version = 1.4.0, numpy version = 1.19.5, networkx version=2.3

Start at the generate_candidates() entry point and run the reproduction with the stated AmpliGraph, NumPy, and NetworkX versions. Compare the graph_degree output with the expected three distinct candidate triplets; done means the function no longer returns the same triplet for every candidate.