def ignore_test_trainer_persist(self):
"""
test pipeline persist, metadata will be saved
:return:
"""
test_config = "tests/data/test_config/test_config.json"
config = AnnotatorConfig(test_config)
trainer = Trainer(config)
assert len(trainer.pipeline) > 0
# char_tokenizer component should been created
assert trainer.pipeline[0] is not None
# create tmp train set
tmp_path = create_tmp_test_jsonfile("tmp.json")
train_data = load_local_data(tmp_path)
# rm tmp train set
rm_tmp_file("tmp.json")
trainer.train(train_data)
persisted_path = trainer.persist(config['path'], config['project'],
config['fixed_model_name'])
# load persisted metadata
metadata_path = os.path.join(persisted_path, 'metadata.json')
with io.open(metadata_path) as f:
metadata = json.load(f)
assert 'trained_at' in metadata
# rm tmp files and dirs
shutil.rmtree(config['path'], ignore_errors=False)
def ignore_test_pipeline_flow(self):
"""
test trainer's train func for pipeline
:return:
"""
test_config = "tests/data/test_config/test_config.json"
config = AnnotatorConfig(test_config)
trainer = Trainer(config)
assert len(trainer.pipeline) > 0
# create tmp train set
tmp_path = create_tmp_test_jsonfile("tmp.json")
train_data = load_local_data(tmp_path)
# rm tmp train set
rm_tmp_file("tmp.json")
interpreter = trainer.train(train_data)
assert interpreter is not None
out1 = interpreter.parse(("点连接拿红包啦"))
# test persist and load
persisted_path = trainer.persist(config['path'], config['project'],
config['fixed_model_name'])
interpreter_loaded = Interpreter.load(persisted_path, config)
out2 = interpreter_loaded.parse("点连接拿红包啦")
assert out1.get("classifylabel").get("name") == out2.get(
"classifylabel").get("name")
# remove tmp models
shutil.rmtree(config['path'], ignore_errors=True)
def ignore_test_load_and_persist_without_train(self):
"""
test save and load model without train
:return:
"""
test_config = "tests/data/test_config/test_config.json"
config = AnnotatorConfig(test_config)
trainer = Trainer(config)
assert len(trainer.pipeline) > 0
# create tmp train set
tmp_path = create_tmp_test_jsonfile("tmp.json")
train_data = load_local_data(tmp_path)
# rm tmp train set
rm_tmp_file("tmp.json")
# interpreter = trainer.train(train_data)
# test persist and load
persisted_path = trainer.persist(config['path'], config['project'],
config['fixed_model_name'])
interpreter_loaded = Interpreter.load(persisted_path, config)
assert interpreter_loaded.pipeline
assert interpreter_loaded.parse("hello") is not None
assert interpreter_loaded.parse(
"Hello today is Monday, again!") is not None
# remove tmp models
shutil.rmtree(config['path'], ignore_errors=False)
def ignore_test_pipeline_flow(self):
"""
test trainer's train func for pipeline
:return:
"""
test_config = "tests/data/test_config/test_config.json"
config = AnnotatorConfig(test_config)
trainer = Trainer(config)
assert len(trainer.pipeline) > 0
# create tmp train set
tmp_path = create_tmp_test_jsonfile("tmp.json")
train_data = load_local_data(tmp_path)
# rm tmp train set
rm_tmp_file("tmp.json")
interpreter = trainer.train(train_data)
assert interpreter is not None
out1 = interpreter.parse(("点连接拿红包啦"))
# test persist and load
persisted_path = trainer.persist(config['path'],
config['project'],
config['fixed_model_name'])
interpreter_loaded = Interpreter.load(persisted_path, config)
out2 = interpreter_loaded.parse("点连接拿红包啦")
assert out1.get("classifylabel").get("name") == out2.get("classifylabel").get("name")
# remove tmp models
shutil.rmtree(config['path'], ignore_errors=True)
def ignore_test_load_and_persist_without_train(self):
"""
test save and load model without train
:return:
"""
test_config = "tests/data/test_config/test_config.json"
config = AnnotatorConfig(test_config)
trainer = Trainer(config)
assert len(trainer.pipeline) > 0
# create tmp train set
tmp_path = create_tmp_test_jsonfile("tmp.json")
train_data = load_local_data(tmp_path)
# rm tmp train set
rm_tmp_file("tmp.json")
# interpreter = trainer.train(train_data)
# test persist and load
persisted_path = trainer.persist(config['path'],
config['project'],
config['fixed_model_name'])
interpreter_loaded = Interpreter.load(persisted_path, config)
assert interpreter_loaded.pipeline
assert interpreter_loaded.parse("hello") is not None
assert interpreter_loaded.parse("Hello today is Monday, again!") is not None
# remove tmp models
shutil.rmtree(config['path'], ignore_errors=False)
def ignore_test_trainer_persist(self):
"""
test pipeline persist, metadata will be saved
:return:
"""
test_config = "tests/data/test_config/test_config.json"
config = AnnotatorConfig(test_config)
trainer = Trainer(config)
assert len(trainer.pipeline) > 0
# char_tokenizer component should been created
assert trainer.pipeline[0] is not None
# create tmp train set
tmp_path = create_tmp_test_jsonfile("tmp.json")
train_data = load_local_data(tmp_path)
# rm tmp train set
rm_tmp_file("tmp.json")
trainer.train(train_data)
persisted_path = trainer.persist(config['path'],
config['project'],
config['fixed_model_name'])
# load persisted metadata
metadata_path = os.path.join(persisted_path, 'metadata.json')
with io.open(metadata_path) as f:
metadata = json.load(f)
assert 'trained_at' in metadata
# rm tmp files and dirs
shutil.rmtree(config['path'], ignore_errors=False)
def ignore_test_load_local_data(self):
"""
test load local json format data
:return:
"""
tmp_path = create_tmp_test_jsonfile("tmp.json")
train_data = load_local_data(tmp_path)
rm_tmp_file("tmp.json")
assert train_data is not None
assert len(train_data.training_examples) == 1000
assert "text" not in train_data.training_examples[0].data
assert "label" in train_data.training_examples[0].data
def ignore_test_load_local_data(self):
"""
test load local json format data
:return:
"""
tmp_path = create_tmp_test_jsonfile("tmp.json")
train_data = load_local_data(tmp_path)
rm_tmp_file("tmp.json")
assert train_data is not None
assert len(train_data.training_examples) == 1000
assert "text" not in train_data.training_examples[0].data
assert "label" in train_data.training_examples[0].data
def ignore_test_train_model_empty_pipeline(self):
"""
train model with no component
:return:
"""
test_config = "tests/data/test_config/test_config.json"
config = AnnotatorConfig(test_config)
config['pipeline'] = []
tmp_path = create_tmp_test_jsonfile("tmp.json")
train_data = load_local_data(tmp_path)
rm_tmp_file("tmp.json")
with pytest.raises(ValueError):
trainer = Trainer(config)
trainer.train(train_data)
def ignore_test_train_model_empty_pipeline(self):
"""
train model with no component
:return:
"""
test_config = "tests/data/test_config/test_config.json"
config = AnnotatorConfig(test_config)
config['pipeline'] = []
tmp_path = create_tmp_test_jsonfile("tmp.json")
train_data = load_local_data(tmp_path)
rm_tmp_file("tmp.json")
with pytest.raises(ValueError):
trainer = Trainer(config)
trainer.train(train_data)
def ignore_test_handles_pipeline_with_non_existing_component(self):
"""
handle no exist component in pipeline
:return:
"""
test_config = "tests/data/test_config/test_config.json"
config = AnnotatorConfig(test_config)
config['pipeline'].append("unknown_component")
tmp_path = create_tmp_test_jsonfile("tmp.json")
train_data = load_local_data(tmp_path)
rm_tmp_file("tmp.json")
with pytest.raises(Exception) as execinfo:
trainer = Trainer(config)
trainer.train(train_data)
assert "Failed to find component" in str(execinfo.value)
def ignore_test_handles_pipeline_with_non_existing_component(self):
"""
handle no exist component in pipeline
:return:
"""
test_config = "tests/data/test_config/test_config.json"
config = AnnotatorConfig(test_config)
config['pipeline'].append("unknown_component")
tmp_path = create_tmp_test_jsonfile("tmp.json")
train_data = load_local_data(tmp_path)
rm_tmp_file("tmp.json")
with pytest.raises(Exception) as execinfo:
trainer = Trainer(config)
trainer.train(train_data)
assert "Failed to find component" in str(execinfo.value)
def setup_class(cls):
""" setup any state specific to the execution of the given class (which
usually contains tests).
"""
# create test data for test case
create_tmp_test_jsonfile("test_data.json")
def setup_class(cls):
""" setup any state specific to the execution of the given class (which
usually contains tests).
"""
# create test data for test case
create_tmp_test_jsonfile("test_data.json")