batch_pipeline/pipelines/pipeline.py [41:80]:
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    CacheConfig,
)
from sagemaker.workflow.quality_check_step import (
    DataQualityCheckConfig,
    ModelQualityCheckConfig,
    QualityCheckStep,
)
from sagemaker.drift_check_baselines import DriftCheckBaselines
from sagemaker.workflow.check_job_config import CheckJobConfig
from sagemaker.workflow.step_collections import RegisterModel
from sagemaker.workflow.functions import Join
from sagemaker.workflow.execution_variables import ExecutionVariables
from sagemaker.utils import name_from_base


BASE_DIR = os.path.dirname(os.path.realpath(__file__))


def get_session(region, default_bucket):
    """Gets the sagemaker session based on the region.
    Args:
        region: the aws region to start the session
        default_bucket: the bucket to use for storing the artifacts
    Returns:
        `sagemaker.session.Session instance
    """

    boto_session = boto3.Session(region_name=region)

    sagemaker_client = boto_session.client("sagemaker")
    runtime_client = boto_session.client("sagemaker-runtime")
    return sagemaker.session.Session(
        boto_session=boto_session,
        sagemaker_client=sagemaker_client,
        sagemaker_runtime_client=runtime_client,
        default_bucket=default_bucket,
    )


def get_pipeline(
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build_pipeline/pipelines/pipeline.py [47:86]:
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    CacheConfig,
)
from sagemaker.workflow.quality_check_step import (
    DataQualityCheckConfig,
    ModelQualityCheckConfig,
    QualityCheckStep,
)
from sagemaker.drift_check_baselines import DriftCheckBaselines
from sagemaker.workflow.check_job_config import CheckJobConfig
from sagemaker.workflow.step_collections import RegisterModel
from sagemaker.workflow.functions import Join
from sagemaker.workflow.execution_variables import ExecutionVariables
from sagemaker.utils import name_from_base


BASE_DIR = os.path.dirname(os.path.realpath(__file__))


def get_session(region, default_bucket):
    """Gets the sagemaker session based on the region.
    Args:
        region: the aws region to start the session
        default_bucket: the bucket to use for storing the artifacts
    Returns:
        `sagemaker.session.Session instance
    """

    boto_session = boto3.Session(region_name=region)

    sagemaker_client = boto_session.client("sagemaker")
    runtime_client = boto_session.client("sagemaker-runtime")
    return sagemaker.session.Session(
        boto_session=boto_session,
        sagemaker_client=sagemaker_client,
        sagemaker_runtime_client=runtime_client,
        default_bucket=default_bucket,
    )


def get_pipeline(
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