def test_blank_config():
file_config = {}
cmdline_args = {}
env_vars = {}
f = write_file_config(file_config)
final_config = MyNLUConfig(f.name, env_vars, cmdline_args)
assert final_config.as_dict() == defaults
def test_cmdline_overrides_envvar():
file_config = {"path": "/path/to/dir"}
cmdline_args = {"path": "/another/path"}
env_vars = {"MYNLU_PATH": "/alternate/path"}
f = write_file_config(file_config)
final_config = MyNLUConfig(f.name, env_vars, cmdline_args)
assert final_config['path'] == "/another/path"
def test_file_config_unchanged():
file_config = {"path": "/path/to/dir"}
cmdline_args = {}
env_vars = {}
f = write_file_config(file_config)
final_config = MyNLUConfig(f.name, env_vars, cmdline_args)
assert final_config['path'] == "/path/to/dir"
def test_pipeline_splits_list():
file_config = {}
cmdline_args = {"pipeline": "nlp_spacy,ner_spacy"}
env_vars = {}
f = write_file_config(file_config)
final_config = MyNLUConfig(f.name, env_vars, cmdline_args)
assert final_config['pipeline'] == ["nlp_spacy", "ner_spacy"]
def app(component_builder):
"""
This fixture makes use of the IResource interface of the Klein application to mock HTTP server.
:param component_builder:
:return:
"""
if "TRAVIS_BUILD_DIR" in os.environ:
root_dir = os.environ["TRAVIS_BUILD_DIR"]
else:
root_dir = os.getcwd()
_, nlu_log_file = tempfile.mkstemp(suffix="_mynlu_logs.json")
_config = {
'write': nlu_log_file,
'port': -1, # unused in test app
"pipeline": "keyword",
"path": os.path.join(root_dir, "test_models"),
"data": os.path.join(root_dir, "data/demo-restaurants.json"),
"server_model_dirs": {
"one": "test_model_mitie",
"two": "test_model_mitie_sklearn",
"three": "test_model_spacy_sklearn",
},
"max_training_processes": 1
}
config = MyNLUConfig(cmdline_args=_config)
mynlu = MyNLU(config, component_builder, True)
return StubTreq(mynlu.app.resource())
def test_invalid_pipeline_template():
file_config = {}
cmdline_args = {"pipeline": "my_made_up_name"}
env_vars = {}
f = write_file_config(file_config)
with pytest.raises(InvalidConfigError) as execinfo:
MyNLUConfig(f.name, env_vars, cmdline_args)
assert "unknown pipeline template" in str(execinfo.value)
def base_test_conf(pipeline_template):
return MyNLUConfig(cmdline_args={
'response_log': temp_log_file_dir(),
'port': 5022,
"pipeline": registry.registered_pipeline_templates.get(pipeline_template, []),
"path": tempfile.mkdtemp(),
"data": "./data/test/demo-mynlu-small.json"
})
def test_pipeline_looksup_registry():
pipeline_template = list(registered_pipeline_templates)[0]
file_config = {}
cmdline_args = {"pipeline": pipeline_template}
env_vars = {}
f = write_file_config(file_config)
final_config = MyNLUConfig(f.name, env_vars, cmdline_args)
assert final_config['pipeline'] == registered_pipeline_templates[
pipeline_template]
def test_invalid_config_json():
file_config = """{"pipeline": [mitie]}""" # invalid json
cmdline_args = {}
env_vars = {}
with tempfile.NamedTemporaryFile("w+",
suffix="_tmp_config_file.json") as f:
f.write(file_config)
f.flush()
with pytest.raises(mynlu.config.InvalidConfigError):
MyNLUConfig(f.name, env_vars, cmdline_args)
def train(cfg_name, model_name):
from mynlu.cli.train import create_persistor
from mynlu.converters import load_data
config = MyNLUConfig(cfg_name)
trainer = Trainer(config)
training_data = load_data(config['data'])
trainer.train(training_data)
persistor = create_persistor(config)
trainer.persist("test_models", persistor, model_name=model_name)
def test_automatically_converts_to_unicode():
env_args = {
"some_test_key_u": str("some test value"),
str("some_test_key_str"): str("some test value")
}
cmd_args = {
"some_other_test_key_str": str("some test value"),
str("some_other_test_key_u"): str("some test value")
}
final_config = MyNLUConfig(CONFIG_DEFAULTS_PATH, env_args, cmd_args)
assert type(final_config["some_test_key_u"]) is Text
assert type(final_config["some_test_key_str"]) is Text
assert type(final_config["some_other_test_key_str"]) is Text
assert type(final_config["some_other_test_key_u"]) is Text
def zh_test_conf_nlp_mitie():
return MyNLUConfig(cmdline_args={
'response_log': temp_log_file_dir(),
'port': 5023,
"pipeline": ["nlp_mitie",
"tokenizer_jieba",
"ner_mitie",
"ner_synonyms",
"intent_entity_featurizer_regex",
"intent_featurizer_mitie",
"intent_classifier_sklearn"],
"path": tempfile.mkdtemp(),
"language": "zh",
"mitie_file": "./data/total_word_feature_extractor_zh.dat",
"data": "./data/test/demo-mynlu-small.json"
})
def test_default_config_file():
final_config = MyNLUConfig()
assert len(final_config) > 1
def default_config():
return MyNLUConfig(CONFIG_DEFAULTS_PATH)