61db445481f516b0d3b21ccfde890fd2b5c34877,tests/integ/test_mxnet_train.py,,test_deploy_model,#Any#Any#Any#,70

Before Change

        )
        predictor = model.deploy(1, "ml.m4.xlarge", endpoint_name=endpoint_name)

        data = numpy.zeros(shape=(1, 1, 28, 28))
        result = predictor.predict(data)
        assert result is not None

    predictor.delete_model()

After Change

    with timeout_and_delete_endpoint_by_name(endpoint_name, sagemaker_session):
        desc = sagemaker_session.sagemaker_client.describe_training_job(
            TrainingJobName=mxnet_training_job
        )
        model_data = desc["ModelArtifacts"]["S3ModelArtifacts"]
        script_path = os.path.join(DATA_DIR, "mxnet_mnist", "mnist.py")
        model = MXNetModel(
            model_data,

Instances