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change: remove slow test_run_xxx_monitor_baseline tests #2148

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Merged
merged 3 commits into from
Feb 16, 2021
Merged

change: remove slow test_run_xxx_monitor_baseline tests #2148

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9c7afa2
change: remove slow test_run_xxx_monitor_baseline tests
Feb 16, 2021
c741b83
fix pylint error
Feb 16, 2021
22bf0bf
Merge branch 'master' into remove-test
icywang86rui Feb 16, 2021
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1 change: 1 addition & 0 deletions src/sagemaker/analytics.py
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Original file line number Diff line number Diff line change
Expand Up @@ -43,6 +43,7 @@ class AnalyticsMetricsBase(with_metaclass(ABCMeta, object)):
"""

def __init__(self):
"""Initializes ``AnalyticsMetricsBase`` instance."""
self._dataframe = None

def export_csv(self, filename):
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122 changes: 0 additions & 122 deletions tests/integ/test_clarify_model_monitor.py
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Expand Up @@ -304,76 +304,6 @@ def test_run_bias_monitor(
scheduled_bias_monitor.delete_monitoring_schedule()


@pytest.mark.skipif(
tests.integ.test_region() in tests.integ.NO_MODEL_MONITORING_REGIONS,
reason="ModelMonitoring is not yet supported in this region.",
)
def test_run_bias_monitor_baseline(
sagemaker_session,
data_config,
model_config,
bias_config,
model_predicted_label_config,
endpoint_name,
ground_truth_input,
upload_actual_data,
):
monitor = ModelBiasMonitor(
role=ROLE,
instance_count=INSTANCE_COUNT,
instance_type=INSTANCE_TYPE,
volume_size_in_gb=VOLUME_SIZE_IN_GB,
max_runtime_in_seconds=MAX_RUNTIME_IN_SECONDS,
sagemaker_session=sagemaker_session,
tags=TEST_TAGS,
)

baselining_job_name = utils.unique_name_from_base("bias-baselining-job")
print("Creating baselining job: {}".format(baselining_job_name))
monitor.suggest_baseline(
data_config=data_config,
bias_config=bias_config,
model_config=model_config,
model_predicted_label_config=model_predicted_label_config,
job_name=baselining_job_name,
)
assert (
monitor.latest_baselining_job_config.probability_threshold_attribute
== BIAS_PROBABILITY_THRESHOLD
)
monitoring_schedule_name = utils.unique_name_from_base("bias-suggest-baseline")
s3_uri_monitoring_output = os.path.join(
"s3://",
sagemaker_session.default_bucket(),
endpoint_name,
monitoring_schedule_name,
"monitor_output",
)
# Let's test if the schedule can pick up analysis_config from baselining job
monitor.create_monitoring_schedule(
output_s3_uri=s3_uri_monitoring_output,
monitor_schedule_name=monitoring_schedule_name,
endpoint_input=EndpointInput(
endpoint_name=endpoint_name,
destination=ENDPOINT_INPUT_LOCAL_PATH,
start_time_offset=START_TIME_OFFSET,
end_time_offset=END_TIME_OFFSET,
),
ground_truth_input=ground_truth_input,
schedule_cron_expression=CRON,
)
_verify_execution_status(monitor)

_verify_bias_job_description(
sagemaker_session=sagemaker_session,
monitor=monitor,
endpoint_name=endpoint_name,
ground_truth_input=ground_truth_input,
)

monitor.delete_monitoring_schedule()


@pytest.fixture
def explainability_monitor(sagemaker_session):
monitor = ModelExplainabilityMonitor(
Expand Down Expand Up @@ -485,58 +415,6 @@ def test_run_explainability_monitor(
scheduled_explainability_monitor.delete_monitoring_schedule()


@pytest.mark.skipif(
tests.integ.test_region() in tests.integ.NO_MODEL_MONITORING_REGIONS,
reason="ModelMonitoring is not yet supported in this region.",
)
def test_run_explainability_monitor_baseline(
sagemaker_session, shap_config, data_config, model_config, endpoint_name, upload_actual_data
):
monitor = ModelExplainabilityMonitor(
role=ROLE,
instance_count=INSTANCE_COUNT,
instance_type=INSTANCE_TYPE,
volume_size_in_gb=VOLUME_SIZE_IN_GB,
max_runtime_in_seconds=MAX_RUNTIME_IN_SECONDS,
sagemaker_session=sagemaker_session,
tags=TEST_TAGS,
)

baselining_job_name = utils.unique_name_from_base("explainability-baselining-job")
print("Creating baselining job: {}".format(baselining_job_name))
monitor.suggest_baseline(
data_config=data_config,
explainability_config=shap_config,
model_config=model_config,
job_name=baselining_job_name,
)
monitoring_schedule_name = utils.unique_name_from_base("explainability-suggest-baseline")
s3_uri_monitoring_output = os.path.join(
"s3://",
sagemaker_session.default_bucket(),
endpoint_name,
monitoring_schedule_name,
"monitor_output",
)
# Let's test if the schedule can pick up analysis_config from baselining job
monitor.create_monitoring_schedule(
output_s3_uri=s3_uri_monitoring_output,
monitor_schedule_name=monitoring_schedule_name,
endpoint_input=endpoint_name,
schedule_cron_expression=CRON,
)

_verify_execution_status(monitor)

_verify_explainability_job_description(
sagemaker_session=sagemaker_session,
monitor=monitor,
endpoint_name=endpoint_name,
)

monitor.delete_monitoring_schedule()


def _verify_monitoring_schedule(monitor, schedule_status, schedule_cron_expression=CRON):
desc = monitor.describe_schedule()
assert desc["MonitoringScheduleName"] == monitor.monitoring_schedule_name
Expand Down