def test_random_seed(component_builder, tmpdir):
"""test if train result is the same for two runs of tf embedding"""
_config = utilities.base_test_conf("supervised_embeddings")
# set fixed random seed to 1
_config.set_component_attr(5, random_seed=1)
# first run
(trained_a, _, persisted_path_a) = train(
_config,
path=tmpdir.strpath + "_a",
data=DEFAULT_DATA_PATH,
component_builder=component_builder,
)
# second run
(trained_b, _, persisted_path_b) = train(
_config,
path=tmpdir.strpath + "_b",
data=DEFAULT_DATA_PATH,
component_builder=component_builder,
)
loaded_a = Interpreter.load(persisted_path_a, component_builder)
loaded_b = Interpreter.load(persisted_path_b, component_builder)
result_a = loaded_a.parse("hello")["intent"]["confidence"]
result_b = loaded_b.parse("hello")["intent"]["confidence"]
assert result_a == result_b
def test_train_model_empty_pipeline(component_builder):
# Should return an empty pipeline
_config = utilities.base_test_conf(pipeline_template=None)
with pytest.raises(ValueError):
train(_config,
data=DEFAULT_DATA_PATH,
component_builder=component_builder)
def test_handles_pipeline_with_non_existing_component(component_builder):
_config = utilities.base_test_conf("pretrained_embeddings_spacy")
_config.pipeline.append({"name": "my_made_up_component"})
with pytest.raises(Exception) as execinfo:
train(_config, data=DEFAULT_DATA_PATH,
component_builder=component_builder)
assert "Failed to find component" in str(execinfo.value)
def trained_moodbot_path():
_, _, persisted_path = train(
data="examples/moodbot/data/nlu.md",
nlu_config="examples/moodbot/config.yml",
path=MOODBOT_MODEL_PATH,
)
return persisted_path
def test_train_named_model(component_builder, tmpdir):
_config = utilities.base_test_conf("keyword")
(trained, _, persisted_path) = train(
_config,
path=tmpdir.strpath,
data=DEFAULT_DATA_PATH,
component_builder=component_builder,
)
assert trained.pipeline
normalized_path = os.path.dirname(os.path.normpath(persisted_path))
# should be saved in a dir named after a project
assert normalized_path == tmpdir.strpath
def test_train_model(pipeline_template, component_builder, tmpdir):
_config = utilities.base_test_conf(pipeline_template)
(trained, _, persisted_path) = train(
_config,
path=tmpdir.strpath,
data=DEFAULT_DATA_PATH,
component_builder=component_builder)
assert trained.pipeline
loaded = Interpreter.load(persisted_path, component_builder)
assert loaded.pipeline
assert loaded.parse("hello") is not None
assert loaded.parse("Hello today is Monday, again!") is not None
def test_train_model_noents(language, pipeline, component_builder, tmpdir):
_config = RasaNLUModelConfig({"pipeline": pipeline, "language": language})
(trained, _, persisted_path) = train(
_config,
path=tmpdir.strpath,
data="./data/test/demo-rasa-noents.json",
component_builder=component_builder)
assert trained.pipeline
loaded = Interpreter.load(persisted_path, component_builder)
assert loaded.pipeline
assert loaded.parse("hello") is not None
assert loaded.parse("Hello today is Monday, again!") is not None
def test_train_model_on_test_pipelines(language, pipeline,
component_builder, tmpdir):
_config = RasaNLUModelConfig({"pipeline": pipeline, "language": language})
(trained, _, persisted_path) = train(
_config,
path=tmpdir.strpath,
data=DEFAULT_DATA_PATH,
component_builder=component_builder)
assert trained.pipeline
loaded = Interpreter.load(persisted_path, component_builder)
assert loaded.pipeline
assert loaded.parse("hello") is not None
assert loaded.parse("Hello today is Monday, again!") is not None