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ROLE = "SageMakerRole"
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PREFIX = "sagemaker/beta-automl-xgboost"
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- HOSTING_INSTANCE_TYPE = "ml.c4.xlarge"
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AUTO_ML_INSTANCE_TYPE = "ml.m5.2xlarge"
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INSTANCE_COUNT = 1
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RESOURCE_POOLS = [{"InstanceType" : AUTO_ML_INSTANCE_TYPE , "PoolSize" : INSTANCE_COUNT }]
@@ -216,7 +215,7 @@ def test_best_candidate(sagemaker_session):
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tests .integ .test_region () in tests .integ .NO_AUTO_ML_REGIONS ,
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reason = "AutoML is not supported in the region yet." ,
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)
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- def test_deploy_best_candidate (sagemaker_session ):
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+ def test_deploy_best_candidate (sagemaker_session , cpu_instance_type ):
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auto_ml_utils .create_auto_ml_job_if_not_exist (sagemaker_session )
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auto_ml = AutoML (
@@ -229,7 +228,7 @@ def test_deploy_best_candidate(sagemaker_session):
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auto_ml .deploy (
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candidate = best_candidate ,
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initial_instance_count = INSTANCE_COUNT ,
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- instance_type = HOSTING_INSTANCE_TYPE ,
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+ instance_type = cpu_instance_type ,
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endpoint_name = endpoint_name ,
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)
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@@ -244,7 +243,7 @@ def test_deploy_best_candidate(sagemaker_session):
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tests .integ .test_region () in tests .integ .NO_AUTO_ML_REGIONS ,
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reason = "AutoML is not supported in the region yet." ,
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)
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- def test_candidate_estimator_default_rerun_and_deploy (sagemaker_session ):
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+ def test_candidate_estimator_default_rerun_and_deploy (sagemaker_session , cpu_instance_type ):
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auto_ml_utils .create_auto_ml_job_if_not_exist (sagemaker_session )
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auto_ml = AutoML (
@@ -261,7 +260,7 @@ def test_candidate_estimator_default_rerun_and_deploy(sagemaker_session):
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candidate_estimator .fit (inputs )
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auto_ml .deploy (
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initial_instance_count = INSTANCE_COUNT ,
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- instance_type = HOSTING_INSTANCE_TYPE ,
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+ instance_type = cpu_instance_type ,
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candidate = candidate ,
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endpoint_name = endpoint_name ,
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)
@@ -277,7 +276,7 @@ def test_candidate_estimator_default_rerun_and_deploy(sagemaker_session):
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tests .integ .test_region () in tests .integ .NO_AUTO_ML_REGIONS ,
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reason = "AutoML is not supported in the region yet." ,
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)
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- def test_candidate_estimator_rerun_with_optional_args (sagemaker_session ):
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+ def test_candidate_estimator_rerun_with_optional_args (sagemaker_session , cpu_instance_type ):
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auto_ml_utils .create_auto_ml_job_if_not_exist (sagemaker_session )
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auto_ml = AutoML (
@@ -294,7 +293,7 @@ def test_candidate_estimator_rerun_with_optional_args(sagemaker_session):
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candidate_estimator .fit (inputs , encrypt_inter_container_traffic = True )
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auto_ml .deploy (
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initial_instance_count = INSTANCE_COUNT ,
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- instance_type = HOSTING_INSTANCE_TYPE ,
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+ instance_type = cpu_instance_type ,
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candidate = candidate ,
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endpoint_name = endpoint_name ,
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)
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