def test_generator_proje():
"""Function to test the generator for ProjE algorithm."""
knowledge_graph = KnowledgeGraph(dataset="freebase15k", negative_sample="uniform")
knowledge_graph.force_prepare_data()
args = KGEArgParser().get_args([])
config = ProjE_pointwiseConfig(args=args)
gen = iter(Generator(config=GeneratorConfig(data='train', algo='ProjE'), model_config=config))
for i in range(1000):
data = list(next(gen))
print("----batch:", i)
hr_hr = data[0]
hr_t = data[1]
tr_tr = data[2]
tr_h = data[3]
print("hr_hr:", hr_hr)
print("hr_t:", hr_t)
print("tr_tr:", tr_tr)
print("tr_h:", tr_h)
gen.stop()
def test_generator_trane():
"""Function to test the generator for Translation distance based algorithm."""
knowledge_graph = KnowledgeGraph(dataset="freebase15k", negative_sample="uniform")
knowledge_graph.force_prepare_data()
args = KGEArgParser().get_args([])
start_time = timeit.default_timer()
config = TransEConfig(args)
gen = Generator(config=GeneratorConfig(data='train', algo='transe'), model_config=config)
print("----init time:", timeit.default_timer() - start_time)
for i in range(10):
start_time_batch = timeit.default_timer()
data = list(next(gen))
h = data[0]
r = data[1]
t = data[2]
# hr_t = data[3]
# tr_h = data[4]
print("----batch:", i, "----time:",timeit.default_timer() - start_time_batch)
print(h,r,t)
print("total time:", timeit.default_timer() - start_time)
gen.stop()
def test_fb15k_meta():
"""Function to test the the knowledge graph parse for Freebase and basic operations."""
knowledge_graph = KnowledgeGraph(dataset="freebase15k")
knowledge_graph.force_prepare_data()
knowledge_graph.dump()
assert knowledge_graph.is_cache_exists()
knowledge_graph.prepare_data()
knowledge_graph.dataset.read_metadata()
knowledge_graph.dataset.dump()
def test_fb15k_manipulate():
"""Function to test the the knowledge graph parse for Freebase and basic operations."""
knowledge_graph = KnowledgeGraph(dataset="freebase15k")
knowledge_graph.force_prepare_data()
knowledge_graph.dump()
knowledge_graph.read_cache_data('triplets_train')
knowledge_graph.read_cache_data('triplets_test')
knowledge_graph.read_cache_data('triplets_valid')
knowledge_graph.read_cache_data('hr_t')
knowledge_graph.read_cache_data('tr_h')
knowledge_graph.read_cache_data('idx2entity')
knowledge_graph.read_cache_data('idx2relation')
knowledge_graph.read_cache_data('entity2idx')
knowledge_graph.read_cache_data('relation2idx')
def test_dl50a():
"""Function to test the the knowledge graph parse for Deep learning knowledge base."""
knowledge_graph = KnowledgeGraph(dataset="deeplearning50a", negative_sample="uniform")
knowledge_graph.force_prepare_data()
knowledge_graph.dump()
def test_fb15k():
"""Function to test the the knowledge graph parse for Freebase."""
knowledge_graph = KnowledgeGraph(dataset="freebase15k", negative_sample="uniform")
knowledge_graph.force_prepare_data()
knowledge_graph.dump()
def test_yago():
"""Function to test the the knowledge graph parse for Yago Dataset."""
knowledge_graph = KnowledgeGraph(dataset="yago3_10", negative_sample="uniform")
knowledge_graph.force_prepare_data()
knowledge_graph.dump()
def test_wn18rr():
"""Function to test the the knowledge graph parse for Wordnet Dataset."""
knowledge_graph = KnowledgeGraph(dataset="wordnet18_rr", negative_sample="uniform")
knowledge_graph.force_prepare_data()
knowledge_graph.dump()
def test_benchmarks(dataset_name):
"""Function to test the the knowledge graph parse for Freebase."""
print("testing downloading from online sources of benchmarks and KG controller's handling.")
knowledge_graph = KnowledgeGraph(dataset=dataset_name)
knowledge_graph.force_prepare_data()
knowledge_graph.dump()