class SagemakerClient: def __init__(self): self.client = Session(profile_name="default").client( "sagemaker", region_name="us-west-2") def submit_transform_job(self): model_name = self.client.list_models( NameContains="sample-model5", SortOrder='Descending', SortBy='CreationTime')["Models"][0]["ModelName"] transform_params = { "TransformJobName": "sample-transform9", "ModelName": model_name, "MaxConcurrentTransforms": 2, "MaxPayloadInMB": 50, "BatchStrategy": "MultiRecord", "TransformOutput": { "S3OutputPath": "s3://test-ubuntu-sagemaker/output-data-prediction/" }, "TransformInput": { "DataSource": { "S3DataSource": { "S3DataType": "S3Prefix", "S3Uri": "s3://test-ubuntu-sagemaker/input-data-prediction/" } }, "ContentType": "text/csv", "SplitType": "Line" }, "TransformResources": { "InstanceType": "ml.c4.xlarge", "InstanceCount": 1 } } self.client.create_transform_job(**transform_params)