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@pytest .mark .canary_quick
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- @pytest .mark .skip (reason = "Test fails during release build with no stack trace" )
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def test_byo_airflow_config_uploads_data_source_to_s3_when_inputs_provided (
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sagemaker_session , cpu_instance_type
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):
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@pytest .mark .canary_quick
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def test_kmeans_airflow_config_uploads_data_source_to_s3 (sagemaker_session , cpu_instance_type ):
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with timeout (seconds = AIRFLOW_CONFIG_TIMEOUT_IN_SECONDS ):
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data_path = os .path .join (DATA_DIR , "one_p_mnist" , "mnist.pkl.gz" )
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)
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- @pytest .mark .canary_quick
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def test_fm_airflow_config_uploads_data_source_to_s3 (sagemaker_session , cpu_instance_type ):
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with timeout (seconds = AIRFLOW_CONFIG_TIMEOUT_IN_SECONDS ):
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data_path = os .path .join (DATA_DIR , "one_p_mnist" , "mnist.pkl.gz" )
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@pytest .mark .canary_quick
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def test_ipinsights_airflow_config_uploads_data_source_to_s3 (sagemaker_session , cpu_instance_type ):
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with timeout (seconds = AIRFLOW_CONFIG_TIMEOUT_IN_SECONDS ):
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data_path = os .path .join (DATA_DIR , "ipinsights" )
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)
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- @pytest .mark .canary_quick
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def test_knn_airflow_config_uploads_data_source_to_s3 (sagemaker_session , cpu_instance_type ):
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with timeout (seconds = AIRFLOW_CONFIG_TIMEOUT_IN_SECONDS ):
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data_path = os .path .join (DATA_DIR , "one_p_mnist" , "mnist.pkl.gz" )
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reason = "LDA image is not supported in certain regions" ,
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)
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@pytest .mark .canary_quick
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def test_lda_airflow_config_uploads_data_source_to_s3 (sagemaker_session , cpu_instance_type ):
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with timeout (seconds = AIRFLOW_CONFIG_TIMEOUT_IN_SECONDS ):
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data_path = os .path .join (DATA_DIR , "lda" )
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def test_linearlearner_airflow_config_uploads_data_source_to_s3 (
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sagemaker_session , cpu_instance_type
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):
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@pytest .mark .canary_quick
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def test_ntm_airflow_config_uploads_data_source_to_s3 (sagemaker_session , cpu_instance_type ):
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with timeout (seconds = AIRFLOW_CONFIG_TIMEOUT_IN_SECONDS ):
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data_path = os .path .join (DATA_DIR , "ntm" )
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def test_pca_airflow_config_uploads_data_source_to_s3 (sagemaker_session , cpu_instance_type ):
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with timeout (seconds = AIRFLOW_CONFIG_TIMEOUT_IN_SECONDS ):
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data_path = os .path .join (DATA_DIR , "one_p_mnist" , "mnist.pkl.gz" )
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def test_rcf_airflow_config_uploads_data_source_to_s3 (sagemaker_session , cpu_instance_type ):
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with timeout (seconds = AIRFLOW_CONFIG_TIMEOUT_IN_SECONDS ):
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# Generate a thousand 14-dimensional datapoints.
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@pytest .mark .canary_quick
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def test_chainer_airflow_config_uploads_data_source_to_s3 (sagemaker_session , chainer_full_version ):
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with timeout (seconds = AIRFLOW_CONFIG_TIMEOUT_IN_SECONDS ):
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script_path = os .path .join (DATA_DIR , "chainer_mnist" , "mnist.py" )
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def test_mxnet_airflow_config_uploads_data_source_to_s3 (
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sagemaker_session , cpu_instance_type , mxnet_full_version
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):
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@pytest .mark .canary_quick
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def test_sklearn_airflow_config_uploads_data_source_to_s3 (
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sagemaker_session , cpu_instance_type , sklearn_full_version
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):
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@pytest .mark .canary_quick
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def test_tf_airflow_config_uploads_data_source_to_s3 (sagemaker_session , cpu_instance_type ):
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with timeout (seconds = AIRFLOW_CONFIG_TIMEOUT_IN_SECONDS ):
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tf = TensorFlow (
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def test_xgboost_airflow_config_uploads_data_source_to_s3 (sagemaker_session , cpu_instance_type ):
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with timeout (seconds = AIRFLOW_CONFIG_TIMEOUT_IN_SECONDS ):
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@@ -593,7 +576,6 @@ def test_xgboost_airflow_config_uploads_data_source_to_s3(sagemaker_session, cpu
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@pytest .mark .canary_quick
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def test_pytorch_airflow_config_uploads_data_source_to_s3_when_inputs_not_provided (
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sagemaker_session , cpu_instance_type
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):
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