def test_feature_importance():
num_significant_features = 6
ion_instance_id = ION1.ION_INSTANCE_ID
ion_node_id = ION1.NODE_1_ID
pipeline_instance_id = ION1.PIPELINE_INST_ID_1
set_mlops_env(ion_id=ion_instance_id, ion_node_id=ion_node_id, model_id=ION1.MODEL_ID)
rest_helper = MlOpsRestFactory().get_rest_helper(MLOpsMode.AGENT, mlops_server="localhost",
mlops_port="3456", token="")
rest_helper.set_prefix(Constants.URL_MLOPS_PREFIX)
with requests_mock.mock() as m:
m.get(rest_helper.url_get_workflow_instance(ion_instance_id), json=test_workflow_instances)
m.get(rest_helper.url_get_ees(), json=test_ee_info)
m.get(rest_helper.url_get_agents(), json=test_agents_info)
m.get(rest_helper.url_get_model_list(), json=test_models_info)
m.get(rest_helper.url_get_health_thresholds(ion_instance_id), json=test_health_info)
m.get(rest_helper.url_get_model_stats(ION1.MODEL_ID), json=test_model_stats)
m.get(rest_helper.url_get_uuid("model"), json={"id": "model_5906255e-0a3d-4fef-8653-8d41911264fb"})
m.post(rest_helper.url_post_stat(pipeline_instance_id), json={})
# Test Python channel
mlops.init(ctx=None, mlops_mode=MLOpsMode.AGENT)
published_model = mlops.Model(name="dtr_mlops_model",
model_format=ModelFormat.SPARKML,
description="model of decision tree regression with explainability")
published_model.feature_importance(model=FinalModel, feature_names=FinalModel.feature_names,
num_significant_features=num_significant_features)
mlops.done()
def test_suppress_connection_errors():
import requests
from parallelm.mlops.events.event import Event
from parallelm.mlops.mlops_env_constants import MLOpsEnvConstants
ion_instance_id = ION1.ION_INSTANCE_ID
ion_node_id = ION1.NODE_1_ID
token = ION1.TOKEN
pipeline_instance_id = ION1.PIPELINE_INST_ID_1
set_mlops_env(ion_id=ion_instance_id,
ion_node_id=ion_node_id,
token=token,
model_id=ION1.MODEL_ID)
os.environ[MLOpsEnvConstants.MLOPS_AGENT_PUBLIC_ADDRESS] = "placeholder"
rest_helper = MlOpsRestFactory().get_rest_helper(MLOpsMode.AGENT,
mlops_server="localhost",
mlops_port="3456",
token=token)
rest_helper.set_prefix(Constants.URL_MLOPS_PREFIX)
with requests_mock.mock() as m:
m.get(rest_helper.url_get_workflow_instance(ion_instance_id),
json=test_workflow_instances)
m.get(rest_helper.url_get_health_thresholds(ion_instance_id),
json=test_health_info)
m.get(rest_helper.url_get_ees(), json=test_ee_info)
m.get(rest_helper.url_get_agents(), json=test_agents_info)
m.get(rest_helper.url_get_model_list(), json=test_models_info)
m.get(rest_helper.url_get_model_stats(ION1.MODEL_ID),
json=test_model_stats)
m.post(rest_helper.url_post_event(pipeline_instance_id),
exc=requests.exceptions.ConnectionError)
m.post(rest_helper.url_post_stat(pipeline_instance_id),
exc=requests.exceptions.ConnectionError)
pm.init(ctx=None, mlops_mode=MLOpsMode.AGENT)
event_obj = Event(label="event_name",
event_type=EventType.System,
description=None,
data="123",
is_alert=False,
timestamp=None)
with pytest.raises(MLOpsConnectionException):
pm.set_event(name="event_name", data="123", type=EventType.System)
with pytest.raises(MLOpsConnectionException):
pm.event(event_obj)
with pytest.raises(MLOpsConnectionException):
pm.set_stat("stat_same", 3)
pm.suppress_connection_errors(True)
pm.set_event(name="event_name", data="123", type=EventType.System)
pm.event(event_obj)
pm.set_stat("stat_same", 3)
pm.suppress_connection_errors(False)
pm.done()