Update SDK docs for KFP extensions to follow Sphinx guidelines

kubeflow · Jul 16, 2020 · b7b132f · b7b132f
1 parent 0c861f2
commit b7b132f
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Showing 7 changed files with 24 additions and 23 deletions.
diff --git a/docs/conf.py b/docs/conf.py
@@ -106,7 +106,6 @@
 # The name of the Pygments (syntax highlighting) style to use.
 pygments_style = None
 
-
 # -- Options for HTML output -------------------------------------------------
 
 # The theme to use for HTML and HTML Help pages.  See the documentation for

diff --git a/docs/index.rst b/docs/index.rst
@@ -3,20 +3,20 @@
    You can adapt this file completely to your liking, but it should at least
    contain the root `toctree` directive.
 
-Welcome to Kubeflow Pipelines SDK API reference
-================================================
+Kubeflow Pipelines SDK API
+==========================
 
 Main documentation: https://www.kubeflow.org/docs/pipelines/
 
 Source code: https://github.com/kubeflow/pipelines/
 
 .. toctree::
    :maxdepth: 3
-   :caption: Contents:
+   :caption: Contents
 
+   self
    source/kfp
 
-
 .. * :ref:`modindex`
 .. * :ref:`kfp-ref`
 .. * :ref:`search`

diff --git a/sdk/python/kfp/aws.py b/sdk/python/kfp/aws.py
@@ -15,9 +15,11 @@
 def use_aws_secret(secret_name='aws-secret', aws_access_key_id_name='AWS_ACCESS_KEY_ID', aws_secret_access_key_name='AWS_SECRET_ACCESS_KEY'):
     """An operator that configures the container to use AWS credentials.
 
-        AWS doesn't create secret along with kubeflow deployment and it requires users
-        to manually create credential secret with proper permissions.
-        ---
+    AWS doesn't create secret along with kubeflow deployment and it requires users
+    to manually create credential secret with proper permissions.
+
+    ::
+
         apiVersion: v1
         kind: Secret
         metadata:

diff --git a/sdk/python/kfp/azure.py b/sdk/python/kfp/azure.py
@@ -15,11 +15,10 @@
 def use_azure_secret(secret_name='azcreds'):
     """An operator that configures the container to use Azure user credentials.
 
-        The azcreds secret is created as part of the kubeflow deployment that
-        stores the client ID and secrets for the kubeflow azure service principal.
+    The azcreds secret is created as part of the kubeflow deployment that
+    stores the client ID and secrets for the kubeflow azure service principal.
 
-        With this service principal, the container has a range of Azure APIs to
-        access to. 
+    With this service principal, the container has a range of Azure APIs to access to.
     """
 
     def _use_azure_secret(task):

diff --git a/sdk/python/kfp/dsl/_container_op.py b/sdk/python/kfp/dsl/_container_op.py
@@ -569,8 +569,6 @@ class UserContainer(Container):
     Attributes:
       swagger_types (dict): The key is attribute name
                             and the value is attribute type.
-      attribute_map (dict): The key is attribute name
-                            and the value is json key in definition.
 
     Example:
         ::

diff --git a/sdk/python/kfp/gcp.py b/sdk/python/kfp/gcp.py
@@ -17,9 +17,9 @@
 
 def use_gcp_secret(secret_name='user-gcp-sa', secret_file_path_in_volume=None, volume_name=None, secret_volume_mount_path='/secret/gcp-credentials'):
     """An operator that configures the container to use GCP service account by service account key
-        stored in a Kubernetes secret.
+    stored in a Kubernetes secret.
 
-        For cluster setup and alternatives to using service account key, check https://www.kubeflow.org/docs/gke/authentication-pipelines/.
+    For cluster setup and alternatives to using service account key, check https://www.kubeflow.org/docs/gke/authentication-pipelines/.
     """
 
     # permitted values for secret_name = ['admin-gcp-sa', 'user-gcp-sa']
@@ -95,9 +95,10 @@ def use_preemptible_nodepool(toleration: V1Toleration = V1Toleration(effect='NoS
                                                              value='true'),
                               hard_constraint: bool = False):
   """An operator that configures the GKE preemptible in a container op.
+
   Args:
-    toleration (V1Toleration): toleration to pods, default is the preemptible label.
-    hard_constraint (bool): the constraint of scheduling the pods on preemptible
+    toleration: toleration to pods, default is the preemptible label.
+    hard_constraint: the constraint of scheduling the pods on preemptible
         nodepools is hard. (Default: False)
   """
 
@@ -127,7 +128,7 @@ def add_gpu_toleration(toleration: V1Toleration = V1Toleration(
     """An operator that configures the GKE GPU nodes in a container op.
 
     Args:
-      toleration {V1Toleration} -- toleration to pods, default is the nvidia.com/gpu label.
+      toleration: toleration to pods, default is the nvidia.com/gpu label.
     """
 
     def _set_toleration(task):

diff --git a/sdk/python/kfp/onprem.py b/sdk/python/kfp/onprem.py
@@ -1,9 +1,11 @@
 
 def mount_pvc(pvc_name='pipeline-claim', volume_name='pipeline', volume_mount_path='/mnt/pipeline'):
-    """
-        Modifier function to apply to a Container Op to simplify volume, volume mount addition and
-        enable better reuse of volumes, volume claims across container ops.
-        Usage:
+    """Modifier function to apply to a Container Op to simplify volume, volume mount addition and
+    enable better reuse of volumes, volume claims across container ops.
+
+    Example:
+        ::
+
             train = train_op(...)
             train.apply(mount_pvc('claim-name', 'pipeline', '/mnt/pipeline'))
     """