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
