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kubeflow/fairing/deployers/tfjob/tfjob.py

@@ -1,13 +1,12 @@
 import copy
 import logging
 
-from kubernetes import client as k8s_client
-
 from kubeflow.fairing.constants import constants
 from kubeflow.fairing.deployers.job.job import Job
 from kubeflow.training import V1ReplicaSpec, V1RunPolicy
 from kubeflow.training import V1TFJob
 from kubeflow.training import V1TFJobSpec
+from kubernetes import client as k8s_client
 
 logger = logging.getLogger(__name__)
 

kubeflow/fairing/kubernetes/manager.py

@@ -1,16 +1,14 @@
 import logging
+
 import retrying
 import yaml
-
-from kubernetes import client, config, watch
 from kfserving import KFServingClient
-
-from kubeflow.training import TFJobClient
-from kubeflow.training import PyTorchJobClient
-
-from kubeflow.fairing.utils import is_running_in_k8s, camel_to_snake
-from kubeflow.fairing.constants import constants
 from kubeflow.fairing import utils
+from kubeflow.fairing.constants import constants
+from kubeflow.fairing.utils import is_running_in_k8s, camel_to_snake
+from kubeflow.training import PyTorchJobClient
+from kubeflow.training import TFJobClient
+from kubernetes import client, config, watch
 
 logger = logging.getLogger(__name__)
 
@@ -92,7 +90,6 @@ def delete_tf_job(self, name, namespace):
             persist_config=self.persist_config)
         return tfjob_client.delete(name, namespace=namespace)
 
-
     def create_pytorch_job(self, namespace, pytorchjob):
         """Create the provided PyTorchJob in the specified namespace.
         The PyTorchJob version is defined in PYTORCH_JOB_VERSION in kubeflow.pytorch.constants.
@@ -163,8 +160,8 @@ def create_isvc(self, namespace, isvc):
             return created_isvc
         except client.rest.ApiException:
             raise RuntimeError("Failed to create InferenceService. Perhaps the CRD "
-                               "InferenceService version {} is not installed? "\
-                                   .format(constants.KFSERVING_VERSION))
+                               "InferenceService version {} is not installed? " \
+                               .format(constants.KFSERVING_VERSION))
 
     def delete_isvc(self, name, namespace):
         """Delete the provided InferenceService in the specified namespace.
@@ -232,7 +229,7 @@ def create_secret(self, namespace, secret):
         api_instance = client.CoreV1Api()
         return api_instance.create_namespaced_secret(namespace, secret)
 
-    def get_service_external_endpoint(self, name, namespace, selectors=None): #pylint:disable=inconsistent-return-statements
+    def get_service_external_endpoint(self, name, namespace, selectors=None):  # pylint:disable=inconsistent-return-statements
         """Get the service external endpoint as http://ip_or_hostname:5000/predict.
 
         :param name: The sevice name
@@ -255,10 +252,10 @@ def get_service_external_endpoint(self, name, namespace, selectors=None): #pylin
                              event['type'],
                              event['object'])
                 ing = svc.status.load_balancer.ingress
-                if ing is not None and len(ing) > 0: #pylint:disable=len-as-condition
+                if ing is not None and len(ing) > 0:  # pylint:disable=len-as-condition
                     # temporarily disable hostname. It's causing CI to fail when
                     # run through papermill
-                    #url = "http://{}:5000/predict".format(ing[0].ip or ing[0].hostname)
+                    # url = "http://{}:5000/predict".format(ing[0].ip or ing[0].hostname)
                     url = "http://{}:5000/predict".format(ing[0].ip)
                     return url
         except ValueError as v:
@@ -334,8 +331,7 @@ def log(self, name, namespace, selectors=None, container='', follow=True):
             finally:
                 tail.release_conn()
 
-
-    def apply_namespaced_object(self, spec, mode='create'): #pylint:disable=too-many-branches
+    def apply_namespaced_object(self, spec, mode='create'):  # pylint:disable=too-many-branches
         """Run apply on the provided Kubernetes specs.
 
         :param specs: The YAML specs to apply.
@@ -403,7 +399,6 @@ def apply_namespaced_object(self, spec, mode='create'): #pylint:disable=too-many
 
         return result
 
-
     def apply_namespaced_objects(self, specs, mode='create'):
         """Run apply on the provided Kubernetes specs.