def test_algorithm_create_transformer_without_completed_training_job(session):
session.sagemaker_client.describe_algorithm = Mock(return_value=DESCRIBE_ALGORITHM_RESPONSE)
estimator = AlgorithmEstimator(
algorithm_arn="arn:aws:sagemaker:us-east-2:1234:algorithm/scikit-decision-trees",
role="SageMakerRole",
train_instance_type="ml.m4.xlarge",
train_instance_count=1,
sagemaker_session=session,
)
with pytest.raises(RuntimeError) as error:
estimator.transformer(instance_count=1, instance_type="ml.m4.xlarge")
assert "No finished training job found associated with this estimator" in str(error)
def test_algorithm_create_transformer_with_product_id(create_model,
sagemaker_session):
response = copy.deepcopy(DESCRIBE_ALGORITHM_RESPONSE)
response['ProductId'] = 'some-product-id'
sagemaker_session.sagemaker_client.describe_algorithm = Mock(
return_value=response)
estimator = AlgorithmEstimator(
algorithm_arn=
'arn:aws:sagemaker:us-east-2:1234:algorithm/scikit-decision-trees',
role='SageMakerRole',
train_instance_type='ml.m4.xlarge',
train_instance_count=1,
sagemaker_session=sagemaker_session,
)
estimator.latest_training_job = _TrainingJob(sagemaker_session,
'some-job-name')
model = Mock()
model.name = 'my-model'
create_model.return_value = model
transformer = estimator.transformer(instance_count=1,
instance_type='ml.m4.xlarge')
assert transformer.env is None
def test_algorithm_create_transformer(create_model, sagemaker_session):
sagemaker_session.sagemaker_client.describe_algorithm = Mock(
return_value=DESCRIBE_ALGORITHM_RESPONSE)
estimator = AlgorithmEstimator(
algorithm_arn=
'arn:aws:sagemaker:us-east-2:1234:algorithm/scikit-decision-trees',
role='SageMakerRole',
train_instance_type='ml.m4.xlarge',
train_instance_count=1,
sagemaker_session=sagemaker_session,
)
estimator.latest_training_job = _TrainingJob(sagemaker_session,
'some-job-name')
model = Mock()
model.name = 'my-model'
create_model.return_value = model
transformer = estimator.transformer(instance_count=1,
instance_type='ml.m4.xlarge')
assert isinstance(transformer, Transformer)
create_model.assert_called()
assert transformer.model_name == 'my-model'
