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SDK+Frontend - Fixed the task display name annotation key (#1526) 

Turns out, Kubernetes only allows a single slash character in annotation key.
This commit is contained in:
Alexey Volkov 2019-06-18 14:50:33 -07:00 committed by Kubernetes Prow Robot
parent b935836c30
commit cd0aeb6c62
4 changed files with 4 additions and 4 deletions
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2
frontend/src/lib/WorkflowParser.test.ts
View File

@ -312,7 +312,7 @@ describe('WorkflowParser', () => {
{
metadata: {
annotations: {
'kubeflow.org/pipelines/task_display_name': 'Customized name',
'pipelines.kubeflow.org/task_display_name': 'Customized name',
}
},
name: 'some-template',

2
frontend/src/lib/WorkflowParser.ts
View File

@ -83,7 +83,7 @@ export default class WorkflowParser {
if (workflow.spec && workflow.spec.templates) {
const tmpl = workflow.spec.templates.find(t => !!t && !!t.name && t.name === node.templateName);
if (tmpl && tmpl.metadata && tmpl.metadata.annotations) {
const displayName = tmpl.metadata.annotations['kubeflow.org/pipelines/task_display_name'];
const displayName = tmpl.metadata.annotations['pipelines.kubeflow.org/task_display_name'];
if (displayName) {
nodeLabel = displayName;
}

2
sdk/python/kfp/compiler/_op_to_template.py
View File

@ -255,6 +255,6 @@ def _op_to_template(op: BaseOp):
# Display name
if processed_op.display_name:
template.setdefault('metadata', {}).setdefault('annotations', {})['kubeflow.org/pipelines/task_display_name'] = processed_op.display_name
template.setdefault('metadata', {}).setdefault('annotations', {})['pipelines.kubeflow.org/task_display_name'] = processed_op.display_name
return template

2
sdk/python/tests/compiler/compiler_tests.py
View File

@ -525,7 +525,7 @@ implementation:
workflow_dict = kfp.compiler.Compiler()._compile(some_pipeline)
template = workflow_dict['spec']['templates'][0]
self.assertEqual(template['metadata']['annotations']['kubeflow.org/pipelines/task_display_name'], 'Custom name')
self.assertEqual(template['metadata']['annotations']['pipelines.kubeflow.org/task_display_name'], 'Custom name')
def test_op_transformers(self):
def some_op():