XGBoost Framework Processor

XGBoost is an open-source machine learning framework. The XGBoostProcessor in the Amazon SageMaker Python SDK provides you with the ability to run processing jobs with XGBoost scripts. When you use the XGBoostProcessor, you can leverage an Amazon-built Docker container with a managed XGBoost environment so that you don’t need to bring your own container.

The following code example shows how you can use the XGBoostProcessor to run your Processing job using a Docker image provided and maintained by SageMaker AI. Note that when you run the job, you can specify a directory containing your scripts and dependencies in the source_dir argument, and you can have a requirements.txt file located inside your source_dir directory that specifies the dependencies for your processing script(s). SageMaker Processing installs the dependencies in requirements.txt in the container for you.

from sagemaker.xgboost import XGBoostProcessor
from sagemaker.processing import ProcessingInput, ProcessingOutput
from sagemaker import get_execution_role

#Initialize the XGBoostProcessor
xgb = XGBoostProcessor(
    framework_version='1.2-2',
    role=get_execution_role(),
    instance_type='ml.m5.xlarge',
    instance_count=1,
    base_job_name='frameworkprocessor-XGB',
)

#Run the processing job
xgb.run(
    code='processing-script.py',
    source_dir='scripts',
    inputs=[
        ProcessingInput(
            input_name='data',
            source=f's3://{BUCKET}/{S3_INPUT_PATH}',
            destination='/opt/ml/processing/input/data'
        )
    ],
    outputs=[
        ProcessingOutput(
            output_name='processed_data',
            source='/opt/ml/processing/output/',
            destination=f's3://{BUCKET}/{S3_OUTPUT_PATH}'
        )
    ]
)

If you have a requirements.txt file, it should be a list of libraries you want to install in the container. The path for source_dir can be a relative, absolute, or Amazon S3 URI path. However, if you use an Amazon S3 URI, then it must point to a tar.gz file. You can have multiple scripts in the directory you specify for source_dir. To learn more about the XGBoostProcessor class, see XGBoost Estimator in the Amazon SageMaker Python SDK.