def test_generator_parameter(self):
g = create_test_graph()
g = StellarGraph(g)
# rw = UniformRandomWalk(g)
sampler = UnsupervisedSampler(G=g)
# generator should be provided with a valid batch size. i.e. an integer >=1
sample_gen = sampler.generator(batch_size=None)
with pytest.raises(ValueError):
next(sample_gen)
sample_gen = sampler.generator(batch_size="x")
with pytest.raises(TypeError):
next(sample_gen)
sample_gen = sampler.generator(batch_size=0)
with pytest.raises(ValueError):
next(sample_gen)
sample_gen = sampler.generator(batch_size=3)
with pytest.raises(ValueError):
next(sample_gen)
def test_generator_multiple_batches(self):
n_feat = 4
batch_size = 4
number_of_batches = 3
G = example_Graph_2(n_feat)
sampler = UnsupervisedSampler(G=G)
sample_gen = sampler.generator(batch_size)
batches = []
for batch in range(number_of_batches):
batches.append(next(sample_gen))
assert len(batches) == number_of_batches
def test_generator_samples(self):
n_feat = 4
batch_size = 4
G = example_Graph_2(n_feat)
sampler = UnsupervisedSampler(G=G)
sample_gen = sampler.generator(batch_size)
samples = next(sample_gen)
# return two lists: [(target,context)] pairs and [1/0] binary labels
assert len(samples) == 2
# each (target, context) pair has a matching label
assert len(samples[0]) == len(samples[1])
# batch-size number of samples are returned if batch_size is even
assert len(samples[0]) == batch_size
