Source code for airflow.contrib.operators.sagemaker_base_operator

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import json

from airflow.contrib.hooks.sagemaker_hook import SageMakerHook
from airflow.models import BaseOperator
from airflow.utils.decorators import apply_defaults


[docs]class SageMakerBaseOperator(BaseOperator): """ This is the base operator for all SageMaker operators. :param config: The configuration necessary to start a training job (templated) :type config: dict :param aws_conn_id: The AWS connection ID to use. :type aws_conn_id: str """ template_fields = ['config'] template_ext = () ui_color = '#ededed' integer_fields = [] @apply_defaults def __init__(self, config, aws_conn_id='aws_default', *args, **kwargs): super(SageMakerBaseOperator, self).__init__(*args, **kwargs) self.aws_conn_id = aws_conn_id self.config = config self.hook = None def parse_integer(self, config, field): if len(field) == 1: if isinstance(config, list): for sub_config in config: self.parse_integer(sub_config, field) return head = field[0] if head in config: config[head] = int(config[head]) return if isinstance(config, list): for sub_config in config: self.parse_integer(sub_config, field) return head, tail = field[0], field[1:] if head in config: self.parse_integer(config[head], tail) return def parse_config_integers(self): # Parse the integer fields of training config to integers # in case the config is rendered by Jinja and all fields are str for field in self.integer_fields: self.parse_integer(self.config, field) def expand_role(self): pass def preprocess_config(self): self.log.info( 'Preprocessing the config and doing required s3_operations' ) self.hook = SageMakerHook(aws_conn_id=self.aws_conn_id) self.hook.configure_s3_resources(self.config) self.parse_config_integers() self.expand_role() self.log.info( 'After preprocessing the config is:\n {}'.format( json.dumps(self.config, sort_keys=True, indent=4, separators=(',', ': '))) ) def execute(self, context): raise NotImplementedError('Please implement execute() in sub class!')