def test_trainer_dataframe():
session = create_sagemaker_session(describe_training_result=_describe_training_result(),
metric_stats_results=_metric_stats_results())
trainer = TrainingJobAnalytics("my-training-job", ["train:acc"], sagemaker_session=session)
df = trainer.dataframe()
assert df is not None
assert len(df) == 3
assert min(df['value']) == 77.1
assert max(df['value']) == 97.1
# Export to CSV and check that file exists
tmp_name = "/tmp/unit-test-%s.csv" % uuid.uuid4()
assert not os.path.isfile(tmp_name)
trainer.export_csv(tmp_name)
assert os.path.isfile(tmp_name)
os.unlink(tmp_name)
def test_trainer_dataframe():
describe_training_result = {
'TrainingStartTime': datetime.datetime(2018, 5, 16, 1, 2, 3),
'TrainingEndTime': datetime.datetime(2018, 5, 16, 5, 6, 7),
}
metric_stats_results = {
'Datapoints': [
{
'Average': 77.1,
'Timestamp': datetime.datetime(2018, 5, 16, 1, 3, 3),
},
{
'Average': 87.1,
'Timestamp': datetime.datetime(2018, 5, 16, 1, 8, 3),
},
{
'Average': 97.1,
'Timestamp': datetime.datetime(2018, 5, 16, 2, 3, 3),
},
]
}
session = sagemaker_session(
describe_training_result=describe_training_result,
metric_stats_results=metric_stats_results)
trainer = TrainingJobAnalytics("my-training-job", ["train:acc"],
sagemaker_session=session)
df = trainer.dataframe()
assert df is not None
assert len(df) == 3
assert min(df['value']) == 77.1
assert max(df['value']) == 97.1
# Export to CSV and check that file exists
tmp_name = "/tmp/unit-test-%s.csv" % uuid.uuid4()
assert not os.path.isfile(tmp_name)
trainer.export_csv(tmp_name)
assert os.path.isfile(tmp_name)
os.unlink(tmp_name)