def execute(self, context): hook = CloudAutoMLHook(gcp_conn_id=self.gcp_conn_id) self.log.info("Creating model.") operation = hook.create_model( model=self.model, location=self.location, project_id=self.project_id, retry=self.retry, timeout=self.timeout, metadata=self.metadata, ) result = MessageToDict(operation.result()) model_id = hook.extract_object_id(result) self.log.info("Model created: %s", model_id) self.xcom_push(context, key="model_id", value=model_id) return result
def execute(self, context): hook = CloudAutoMLHook(gcp_conn_id=self.gcp_conn_id) self.log.info("Creating dataset") result = hook.create_dataset( dataset=self.dataset, location=self.location, project_id=self.project_id, retry=self.retry, timeout=self.timeout, metadata=self.metadata, ) result = MessageToDict(result) dataset_id = hook.extract_object_id(result) self.log.info("Creating completed. Dataset id: %s", dataset_id) self.xcom_push(context, key="dataset_id", value=dataset_id) return result
def execute(self, context): hook = CloudAutoMLHook(gcp_conn_id=self.gcp_conn_id) self.log.info("Requesting datasets") page_iterator = hook.list_datasets( location=self.location, project_id=self.project_id, retry=self.retry, timeout=self.timeout, metadata=self.metadata, ) result = [MessageToDict(dataset) for dataset in page_iterator] self.log.info("Datasets obtained.") self.xcom_push( context, key="dataset_id_list", value=[hook.extract_object_id(d) for d in result], ) return result