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from sagemaker .sklearn .processing import SKLearnProcessor
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from sagemaker .pytorch .processing import PyTorchProcessor
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from sagemaker .tensorflow .processing import TensorFlowProcessor
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- from sagemaker .xgboost .processing import XGBoostEstimator
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+ from sagemaker .xgboost .processing import XGBoostProcessor
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from sagemaker .mxnet .processing import MXNetProcessor
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from sagemaker .network import NetworkConfig
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from sagemaker .processing import FeatureStoreOutput
@@ -355,7 +355,7 @@ def test_pytorch_processor_with_required_parameters(
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pytorch_image_uri = (
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"763104351884.dkr.ecr.us-west-2.amazonaws.com/pytorch-training:{}-cpu-py3"
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).format (pytorch_training_version )
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-
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+
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expected_args ["app_specification" ]["ImageUri" ] = pytorch_image_uri
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sagemaker_session .process .assert_called_with (** expected_args )
@@ -368,7 +368,7 @@ def test_xgboost_processor_with_required_parameters(
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):
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botocore_resolver .return_value .construct_endpoint .return_value = {"hostname" : ECR_HOSTNAME }
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- processor = XGBoostEstimator (
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+ processor = XGBoostProcessor (
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role = ROLE ,
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instance_type = "ml.m4.xlarge" ,
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framework_version = xgboost_framework_version ,
@@ -388,7 +388,7 @@ def test_xgboost_processor_with_required_parameters(
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xgboost_image_uri = (
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"246618743249.dkr.ecr.us-west-2.amazonaws.com/sagemaker-xgboost:{}"
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).format (xgboost_framework_version )
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-
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+
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expected_args ["app_specification" ]["ImageUri" ] = xgboost_image_uri
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sagemaker_session .process .assert_called_with (** expected_args )
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