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)
