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https://api.github.com/repos/kubeflow/pipelines/issues/9980 | https://api.github.com/repos/kubeflow/pipelines | https://api.github.com/repos/kubeflow/pipelines/issues/9980/labels{/name} | https://api.github.com/repos/kubeflow/pipelines/issues/9980/comments | https://api.github.com/repos/kubeflow/pipelines/issues/9980/events | https://github.com/kubeflow/pipelines/issues/9980 | 1,894,144,464 | I_kwDOB-71UM5w5lnQ | 9,980 | [feature] Enable Setting Image Pull Policy in V2 SDK | {
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/area sdk
### What feature would you like to see?
KFP V1 supported setting the image pull policy [link](https://github.com/kubeflow/pipelines/blob/4bee3d8dc2ee9c33d87e1058bac2a94d899dd4a5/sdk/python/kfp/deprecated/dsl/_container_op.py#L518)
This feature is currently not available in KFP V2
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### Environment
* How do you deploy Kubeflow Pipelines (KFP)? </br>
Using kubeflow sdk
* KFP version: </br>
1.7
* KFP SDK version: </br>
1.8.17
* Python base image used: </br>
Image tag: python:3.8-slim </br>
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"u... | open | false | null | [] | null | [] | 2023-09-12T09:43:48 | 2023-09-12T13:01:04 | null | NONE | null | ### Environment
* How did you deploy Kubeflow Pipelines (KFP)?
Kubeflow Pipelines as part of a full Kubeflow deployment provides all Kubeflow components and more integration with each platform
Kubeflow is deployed on top of AWS EKS cluster.
* KFP version: v2
* KFP SDK version: Issue identified in UI, possib... | {
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"I've been impacted by this change as well and I think it's a behavior change in the latest version of KFP 2.1.3 only. I was able to get my pipeline running by using KFP 2.0.1.\r\n\r\nI think the \"issue\" might be coming from the following commit https://github.com/kubeflow/pipelines/pull/9886/commits/80881c12ee2a... | 2023-09-12T08:07:41 | 2023-09-13T11:09:14 | null | NONE | null | ### Environment
#### Relevant package versions
kfp==2.1.3
google-cloud-pipeline-components==2.3.1
google-cloud-aiplatform==1.32.0
kfp-pipeline-spec== 0.2.2
kfp-server-api == 2.0.1
### Steps to reproduce
After upgrading to KFP V2, Initializing a component as follows doesn't work:
```python
from kfp.dsl... | {
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https://api.github.com/repos/kubeflow/pipelines/issues/9970 | https://api.github.com/repos/kubeflow/pipelines | https://api.github.com/repos/kubeflow/pipelines/issues/9970/labels{/name} | https://api.github.com/repos/kubeflow/pipelines/issues/9970/comments | https://api.github.com/repos/kubeflow/pipelines/issues/9970/events | https://github.com/kubeflow/pipelines/issues/9970 | 1,889,838,578 | I_kwDOB-71UM5wpKXy | 9,970 | Usage of Kubeflow Pipelines v2 | {
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"> set gpu resources (.set_gpu_limit())\r\n\r\n`set_gpu_limit()` has been renamed to [`set_accelerator_limit`](https://kubeflow-pipelines.readthedocs.io/en/sdk-2.0.1/source/dsl.html?h=set_acc#kfp.dsl.PipelineTask.set_accelerator_limit) so that is covers both GPU and TPU (on Vertex). Meanwhile, `set_gpu_limit` still... | 2023-09-11T07:20:36 | 2023-09-12T01:35:55 | null | NONE | null | Hello,
we have upgraded our Kubeflow Pipelines to version 2.0.1. We are now having a lot of trouble rewriting our code from version 1.8. We are missing the following features (maybe we just didn't find them in v2):
- set gpu resources (.set_gpu_limit())
- mount hostPath (.add_volume(), add_volume_mount())
- .s... | {
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https://api.github.com/repos/kubeflow/pipelines/issues/9962 | https://api.github.com/repos/kubeflow/pipelines | https://api.github.com/repos/kubeflow/pipelines/issues/9962/labels{/name} | https://api.github.com/repos/kubeflow/pipelines/issues/9962/comments | https://api.github.com/repos/kubeflow/pipelines/issues/9962/events | https://github.com/kubeflow/pipelines/issues/9962 | 1,887,425,701 | I_kwDOB-71UM5wf9Sl | 9,962 | [backend] Persistence Agent failing kubeflow-pipeline-mkp-test (2) | {
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Having in mind issue: [Persistence agent failing kubeflow-pipeline-mkp-test](https://github.com/kubeflow/pipelines/issues/9904) that appeared after changes in the Persistence agent manifests files - I guess that the mkp-test may fail again after the merge of [this](https://github.com/kubeflow/pi... | {
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"@fclesio, I think the best solution for what you are trying to achieve is to compose the tasks together into a sequential DAG using a pipeline. Please take a look at the docs on [data passing and task dependencies](https://www.kubeflow.org/docs/components/pipelines/v2/pipelines/pipeline-basics/#data-passing-and-ta... | 2023-09-06T20:53:45 | 2023-09-08T14:47:16 | 2023-09-07T22:50:17 | NONE | null | Thanks once again for the great library.
I have a ML pipeline that consists in 3 tasks: ETL > Pre-Processing > Modelling and Deploy.
Since those tasks are sequential, I created 3 pipelines and I used the [kfp.client.run_pipeline ](https://github.com/kubeflow/pipelines/blob/master/sdk/python/kfp/client/client.p... | {
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<!-- Please fill in those that seem relevant. -->
* How do you deploy Kubeflow Pipelines (KFP)?
<!-- For more information, see an overview of KFP installation options: https://www.kubeflow.org/docs/pipelines/installation/overview/. -->
* KFP version:
<!-- Specify the version of Kubeflow Pipelin... | {
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"**In Kfp 2.0.1 retry on policy is not present.**\r\n\r\n**Old Code**\r\n```\r\n def set_retry(self,\r\n num_retries: int,\r\n policy: Optional[str] = None,\r\n backoff_duration: Optional[str] = None,\r\n backoff_factor: Optional[float] = None,\... | 2023-08-31T12:31:13 | 2023-09-02T13:17:07 | null | NONE | null | ### Environment
<!-- Please fill in those that seem relevant. -->
* How do you deploy Kubeflow Pipelines (KFP)?
* KFP version: 2.0.0
To find the version number, See version number shows on bottom of KFP UI left sidenav. -->
* KFP SDK version: 2.0.1
### Steps to reproduce
You can run the following code t... | {
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https://api.github.com/repos/kubeflow/pipelines/issues/9949 | https://api.github.com/repos/kubeflow/pipelines | https://api.github.com/repos/kubeflow/pipelines/issues/9949/labels{/name} | https://api.github.com/repos/kubeflow/pipelines/issues/9949/comments | https://api.github.com/repos/kubeflow/pipelines/issues/9949/events | https://github.com/kubeflow/pipelines/issues/9949 | 1,875,251,131 | I_kwDOB-71UM5vxg-7 | 9,949 | Deprecated setup.cfg used in pyyaml@5.4.1 version not compatible with Python versions 3.10 and above | {
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"This is fixed. See [requirements](https://github.com/kubeflow/pipelines/blob/3b8cea060fc3088520666fea26e6452bda2fdb15/sdk/python/requirements.in#L22)."
] | 2023-08-31T10:34:16 | 2023-09-07T22:36:55 | 2023-09-07T22:36:54 | NONE | null | ### Description
`pip install -r requirements.txt` fails on Python 3.10 and 3.11 due to deprecated setup.cfg in pyyaml 5.4.1 using `license_file` instead of `license_files` . According to PyYaml this problem was fixed and recommended version is 6.0.1.
Fixing this issue may require to update requirements to accept `pyy... | {
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https://api.github.com/repos/kubeflow/pipelines/issues/9942 | https://api.github.com/repos/kubeflow/pipelines | https://api.github.com/repos/kubeflow/pipelines/issues/9942/labels{/name} | https://api.github.com/repos/kubeflow/pipelines/issues/9942/comments | https://api.github.com/repos/kubeflow/pipelines/issues/9942/events | https://github.com/kubeflow/pipelines/issues/9942 | 1,871,704,455 | I_kwDOB-71UM5vj_GH | 9,942 | [feature] Add support for Habana device cards | {
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"u... | open | false | null | [] | null | [] | 2023-08-29T13:40:47 | 2023-08-29T13:40:50 | null | NONE | null | ### Feature Area
/area sdk
/area samples
### What feature would you like to see?
I would like to have the option to choose if I would like to use Nvidia gpu cards or Habana pci cards.
The only difference is with the requests to change it from `nvidia.com/gpu` to `habana.ai/gaudi`
At the backend we are... | {
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https://api.github.com/repos/kubeflow/pipelines/issues/9941 | https://api.github.com/repos/kubeflow/pipelines | https://api.github.com/repos/kubeflow/pipelines/issues/9941/labels{/name} | https://api.github.com/repos/kubeflow/pipelines/issues/9941/comments | https://api.github.com/repos/kubeflow/pipelines/issues/9941/events | https://github.com/kubeflow/pipelines/issues/9941 | 1,871,084,656 | I_kwDOB-71UM5vhnxw | 9,941 | Kubeflow error:Invalid input error: Job has no experiment. code:3 message | {
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"You need first to create an experiment and than use it's id in run, passing it as a parameter.",
"> \r\n\r\nPlease provide advice on how to create an [experiment](https://www.kubeflow.org/docs/components/pipelines/v2/reference/api/kubeflow-pipeline-api-spec/#operation--apis-v2beta1-experiments-post) using [Kube... | 2023-08-29T07:41:43 | 2023-09-07T22:47:11 | null | NONE | null | I am following tutorial of Kubeflow Pipelines API: [[Kubeflow](https://www.kubeflow.org/docs/components/pipelines/v1/tutorials/api-pipelines/)] & [Kubeflow Pipelines API](https://www.kubeflow.org/docs/components/pipelines/v1/reference/api/kubeflow-pipeline-api-spec/)
I've installed Kubeflow on a MicroK8s and sta... | {
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https://api.github.com/repos/kubeflow/pipelines/issues/9940 | https://api.github.com/repos/kubeflow/pipelines | https://api.github.com/repos/kubeflow/pipelines/issues/9940/labels{/name} | https://api.github.com/repos/kubeflow/pipelines/issues/9940/comments | https://api.github.com/repos/kubeflow/pipelines/issues/9940/events | https://github.com/kubeflow/pipelines/issues/9940 | 1,870,687,285 | I_kwDOB-71UM5vgGw1 | 9,940 | [bug] Always 404 on kfp sdk | {
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"Which version of the KFP BE do you have deployed?\r\n\r\ncc @chensun"
] | 2023-08-29T00:25:14 | 2023-09-07T22:44:39 | null | NONE | null | I was using kfp==2.0.0b12 and everything was working great. But as soon as i got into 2.0.1 I am always getting 404 when trying to use methods from client, like this:
`kfp_server_api.exceptions.ApiException: (404)
Reason: Not Found
HTTP response headers: HTTPHeaderDict({'x-powered-by': 'Express', 'content-security... | {
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https://api.github.com/repos/kubeflow/pipelines/issues/9937 | https://api.github.com/repos/kubeflow/pipelines | https://api.github.com/repos/kubeflow/pipelines/issues/9937/labels{/name} | https://api.github.com/repos/kubeflow/pipelines/issues/9937/comments | https://api.github.com/repos/kubeflow/pipelines/issues/9937/events | https://github.com/kubeflow/pipelines/issues/9937 | 1,869,601,448 | I_kwDOB-71UM5vb9qo | 9,937 | [feature] Make Persistence Agent use SA Token when calling KF APIServer endpoints | {
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"/assign @difince "
] | 2023-08-28T11:48:07 | 2023-09-07T23:49:34 | 2023-09-07T23:49:34 | MEMBER | null | ### Feature Area
<!-- Uncomment the labels below which are relevant to this feature: -->
<!-- /area frontend -->
</area backend>
<!-- /area sdk -->
<!-- /area samples -->
<!-- /area components -->
### What feature would you like to see?
Currently, when the Persistence Agent (PA) calls KFPipeline APIs - ... | {
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https://api.github.com/repos/kubeflow/pipelines/issues/9933 | https://api.github.com/repos/kubeflow/pipelines | https://api.github.com/repos/kubeflow/pipelines/issues/9933/labels{/name} | https://api.github.com/repos/kubeflow/pipelines/issues/9933/comments | https://api.github.com/repos/kubeflow/pipelines/issues/9933/events | https://github.com/kubeflow/pipelines/issues/9933 | 1,867,215,948 | I_kwDOB-71UM5vS3RM | 9,933 | module 'kfp.components' has no attribute 'create_component_from_func' | {
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"For KFP SDK v2, please use the `@dsl.component` decorator. See [documentation on Lightweight Python Components](https://www.kubeflow.org/docs/components/pipelines/v2/components/lightweight-python-components/) for more information."
] | 2023-08-25T15:02:38 | 2023-09-07T22:42:16 | 2023-09-07T22:42:15 | NONE | null | ### Environment
I am trying to build the Kubeflow pipeline. i am using version 2.0.1.
I am getting this error:
module 'kfp.components' has no attribute 'create_component_from_func'
And along i i followed the document of KFPv2 there are some code already written in docs for the testing it has already created s... | {
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https://api.github.com/repos/kubeflow/pipelines/issues/9924 | https://api.github.com/repos/kubeflow/pipelines | https://api.github.com/repos/kubeflow/pipelines/issues/9924/labels{/name} | https://api.github.com/repos/kubeflow/pipelines/issues/9924/comments | https://api.github.com/repos/kubeflow/pipelines/issues/9924/events | https://github.com/kubeflow/pipelines/issues/9924 | 1,863,477,869 | I_kwDOB-71UM5vEmpt | 9,924 | [backend] Cannot inject environment variables and volumes into components with the KFP CLI | {
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"u... | open | false | null | [] | null | [] | 2023-08-23T14:40:25 | 2023-08-23T14:40:25 | null | NONE | null | ### Environment
* How did you deploy Kubeflow Pipelines (KFP)?
Full Kubeflow Deployment
* KFP version: 1.7.0 (we are using Kubeflow 1.7.0)
* KFP SDK version: 2.0.1
### Steps to reproduce
The injection of environment variables and secrets into components is not working correctly with kfpv2. Please loo... | {
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https://api.github.com/repos/kubeflow/pipelines/issues/9906 | https://api.github.com/repos/kubeflow/pipelines | https://api.github.com/repos/kubeflow/pipelines/issues/9906/labels{/name} | https://api.github.com/repos/kubeflow/pipelines/issues/9906/comments | https://api.github.com/repos/kubeflow/pipelines/issues/9906/events | https://github.com/kubeflow/pipelines/issues/9906 | 1,857,198,876 | I_kwDOB-71UM5uspsc | 9,906 | [frontend] No Logs tab in UI | {
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"Hi @Saurav-D,\r\n\r\nLogs are available in KFP 2.0.0. It is expected to be included in Kubeflow 1.8 (releasing in 2023 Q4)"
] | 2023-08-18T19:33:17 | 2023-08-24T22:48:53 | 2023-08-24T22:48:52 | NONE | null | ### Environment
* How did you deploy Kubeflow Pipelines (KFP)?
AWS, Terraform, Vanilla
* KFP version:
KFP 1.7
pipeline: 2.0.0-alpha.7
### Steps to reproduce
Run any pipeline
### Expected result
Logs tab with logs. Right now, I just see Input/Output and Task Details. Also, I don't see pod ID.
... | {
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https://api.github.com/repos/kubeflow/pipelines/issues/9904 | https://api.github.com/repos/kubeflow/pipelines | https://api.github.com/repos/kubeflow/pipelines/issues/9904/labels{/name} | https://api.github.com/repos/kubeflow/pipelines/issues/9904/comments | https://api.github.com/repos/kubeflow/pipelines/issues/9904/events | https://github.com/kubeflow/pipelines/issues/9904 | 1,856,240,751 | I_kwDOB-71UM5uo_xv | 9,904 | [backend] Persistence agent failing `kubeflow-pipeline-mkp-test` | {
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"### Exploration\r\n\r\nI granted `roles/iam.serviceAccountTokenCreator` to the GCE default service account: https://cloud.google.com/iam/docs/service-account-permissions#token-creator-role, and retried the mkt-test. If this permission unblocks the test, then we will need to do one of the followings:\r\n\r\n1. Make... | 2023-08-18T07:49:37 | 2023-08-21T20:08:43 | 2023-08-21T20:08:43 | COLLABORATOR | null | ### Environment
Currently `/test kubeflow-pipeline-mkp-test` is failing on HEAD.
### Steps to reproduce
In https://github.com/kubeflow/pipelines/commit/cb18d00bbbaed9cd77fc50dce739ed62c72b2356#diff-7df17678529866306ef6665ffbeeda377a1e869aca24856f7cf8a99891877fe8, service account token projection is introduce... | {
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https://api.github.com/repos/kubeflow/pipelines/issues/9893 | https://api.github.com/repos/kubeflow/pipelines | https://api.github.com/repos/kubeflow/pipelines/issues/9893/labels{/name} | https://api.github.com/repos/kubeflow/pipelines/issues/9893/comments | https://api.github.com/repos/kubeflow/pipelines/issues/9893/events | https://github.com/kubeflow/pipelines/issues/9893 | 1,855,183,517 | I_kwDOB-71UM5uk9qd | 9,893 | [bug] Can't increase/attach shared memory to pipeline task in kfp sdk v2, e.g. PyTorch training fails. | {
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"Hi @hsteude!\r\n\r\nYou can specify memory requests using SDK: `.set_memory_request()` and `.set_memory_limit()`: https://kubeflow-pipelines.readthedocs.io/en/sdk-2.0.1/source/dsl.html?h=set_memory#kfp.dsl.PipelineTask.set_memory_request",
"Hi @gkcalat and thanks for your answer!\r\n\r\nUnfortunately, using `.se... | 2023-08-17T15:01:45 | 2023-09-06T11:48:12 | 2023-08-24T22:54:22 | CONTRIBUTOR | null | ### Environment
* How do you deploy Kubeflow Pipelines (KFP)?
Manifests
* KFP version:
2.0.0
* KFP SDK version:
2.0.1
### Steps to reproduce
Create and run a simple PyTorch (lightning) training pipeline:
```python
from kfp import dsl
from kfp.client import Client
# define pytorch (lightning) tr... | {
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"/assign @difince ",
"Fixed by https://github.com/kubeflow/pipelines/pull/9892"
] | 2023-08-17T14:04:00 | 2023-08-17T17:09:24 | 2023-08-17T17:09:24 | MEMBER | null | ### Environment
The issue is introduced by [PR](https://github.com/kubeflow/pipelines/pull/9699)
1. `DefaultTokenRefresherInterval` of 1 hour is initialized in nanoseconds (3600000000000) see here:
https://github.com/kubeflow/pipelines/blob/cb18d00bbbaed9cd77fc50dce739ed62c72b2356/backend/src/agent/persistence/m... | {
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The listruns query is also very slow (seconds for large run_details tables).
It must also be migrated to joins or something other more performant
Already this small database leads to 15 seconds per listruns api ca... | {
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* How did you deploy Kubeflow Pipelines (KFP)? Kubeflow 1.7/1.8
<!-- For more information, see an overview of KFP installation options: https://www.kubeflow.org/docs/pipelines/installation/overview/. -->
* KFP version: 2.0.0alpha7, but its also in the master branch
<!-- Specify the version of Ku... | {
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https://api.github.com/repos/kubeflow/pipelines/issues/9883 | https://api.github.com/repos/kubeflow/pipelines | https://api.github.com/repos/kubeflow/pipelines/issues/9883/labels{/name} | https://api.github.com/repos/kubeflow/pipelines/issues/9883/comments | https://api.github.com/repos/kubeflow/pipelines/issues/9883/events | https://github.com/kubeflow/pipelines/issues/9883 | 1,853,599,683 | I_kwDOB-71UM5ue6_D | 9,883 | 8/16/23 Presumbit e2e test failure | {
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"The frontend test failure seems to be flaky. \r\n\r\nIn another run, it failed on basic sample tests:\r\n```\r\nintegration-test-q5mqw-2112930252: Traceback (most recent call last):\r\nintegration-test-q5mqw-2112930252: File \"exit_handler.py\", line 26, in <module>\r\nintegration-test-q5mqw-2112930252: @com... | 2023-08-16T16:54:10 | 2023-08-17T09:33:39 | 2023-08-17T09:33:39 | COLLABORATOR | null | ERROR: type should be string, got "\r\nhttps://oss.gprow.dev/view/gs/oss-prow/pr-logs/pull/kubeflow_pipelines/9873/kubeflow-pipeline-e2e-test/1691525546791407616\r\n```\r\nintegration-test-g8t6t-369894966: [0-0] AssertionError in \"deploy helloworld sample run.shows a 4-node static graph\"\r\nintegration-test-g8t6t-369894966: AssertionError [ERR_ASSERTION]: should have a 4-node graph, instead has: 0\r\nintegration-test-g8t6t-369894966: at Context.<anonymous> (/src/helloworld.spec.js:70:5)\r\nintegration-test-g8t6t-369894966: at processTicksAndRejections (node:internal/process/task_queues:96:5)\r\nintegration-test-g8t6t-369894966: 19:49:32.603 WARN [SeleniumSpanExporter$1.lambda$export$3] - {\"traceId\": \"2ae031a384cadb8eb7f70e9a187d622b\",\"eventTime\": 1692128972602956682,\"eventName\": \"HTTP request execution complete\",\"attributes\": {\"http.flavor\": 1,\"http.handler_class\": \"org.openqa.selenium.remote.http.Route$PredicatedRoute\",\"http.host\": \"127.0.0.1:4444\",\"http.method\": \"POST\",\"http.request_content_length\": \"8346\",\"http.scheme\": \"HTTP\",\"http.status_code\": 404,\"http.target\": \"\\u002fsession\\u002fd0c75f008d8950640953b1914f2f233a\\u002fexecute\\u002fsync\",\"http.user_agent\": \"webdriver\\u002f8.3.2\"}}\r\nintegration-test-g8t6t-369894966: \r\nintegration-test-g8t6t-369894966: 19:49:33.711 WARN [SeleniumSpanExporter$1.lambda$export$3] - {\"traceId\": \"72fe6381777527734f56dd38817f7a8e\",\"eventTime\": 1692128973710578070,\"eventName\": \"HTTP request execution complete\",\"attributes\": {\"http.flavor\": 1,\"http.handler_class\": \"org.openqa.selenium.remote.http.Route$PredicatedRoute\",\"http.host\": \"127.0.0.1:4444\",\"http.method\": \"POST\",\"http.request_content_length\": \"8346\",\"http.scheme\": \"HTTP\",\"http.status_code\": 404,\"http.target\": \"\\u002fsession\\u002fd0c75f008d8950640953b1914f2f233a\\u002fexecute\\u002fsync\",\"http.user_agent\": \"webdriver\\u002f8.3.2\"}}\r\nintegration-test-g8t6t-369894966: \r\nintegration-test-g8t6t-369894966: Handling connection for 3000\r\nintegration-test-g8t6t-369894966: Handling connection for 3000\r\nintegration-test-g8t6t-369894966: 19:50:20.670 INFO [LocalSessionMap.lambda$new$0] - Deleted session from local Session Map, Id: d0c75f008d8950640953b1914f2f233a\r\nintegration-test-g8t6t-369894966: 19:50:20.672 INFO [GridModel.release] - Releasing slot for session id d0c75f008d8950640953b1914f2f233a\r\nintegration-test-g8t6t-369894966: 19:50:20.675 INFO [SessionSlot.stop] - Stopping session d0c75f008d8950640953b1914f2f233a\r\nintegration-test-g8t6t-369894966: [0-0] FAILED in chrome - file:///helloworld.spec.js\r\n```" | {
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<!-- Uncomment the labels below which are relevant to this feature: -->
<!-- /area frontend -->
<!-- /area backend -->
/area sdk
<!-- /area samples -->
/area components
### What feature would you like to see?
Allow dataflow to be launched with a fixed python and beam sdk version.
A... | {
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https://api.github.com/repos/kubeflow/pipelines/issues/9980 | https://api.github.com/repos/kubeflow/pipelines | https://api.github.com/repos/kubeflow/pipelines/issues/9980/labels{/name} | https://api.github.com/repos/kubeflow/pipelines/issues/9980/comments | https://api.github.com/repos/kubeflow/pipelines/issues/9980/events | https://github.com/kubeflow/pipelines/issues/9980 | 1,894,144,464 | I_kwDOB-71UM5w5lnQ | 9,980 | [feature] Enable Setting Image Pull Policy in V2 SDK | {
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/area sdk
### What feature would you like to see?
KFP V1 supported setting the image pull policy [link](https://github.com/kubeflow/pipelines/blob/4bee3d8dc2ee9c33d87e1058bac2a94d899dd4a5/sdk/python/kfp/deprecated/dsl/_container_op.py#L518)
This feature is currently not available in KFP V2
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### Environment
* How do you deploy Kubeflow Pipelines (KFP)? </br>
Using kubeflow sdk
* KFP version: </br>
1.7
* KFP SDK version: </br>
1.8.17
* Python base image used: </br>
Image tag: python:3.8-slim </br>
... | {
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* How did you deploy Kubeflow Pipelines (KFP)?
Kubeflow Pipelines as part of a full Kubeflow deployment provides all Kubeflow components and more integration with each platform
Kubeflow is deployed on top of AWS EKS cluster.
* KFP version: v2
* KFP SDK version: Issue identified in UI, possib... | {
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"I've been impacted by this change as well and I think it's a behavior change in the latest version of KFP 2.1.3 only. I was able to get my pipeline running by using KFP 2.0.1.\r\n\r\nI think the \"issue\" might be coming from the following commit https://github.com/kubeflow/pipelines/pull/9886/commits/80881c12ee2a... | 2023-09-12T08:07:41 | 2023-09-13T11:09:14 | null | NONE | null | ### Environment
#### Relevant package versions
kfp==2.1.3
google-cloud-pipeline-components==2.3.1
google-cloud-aiplatform==1.32.0
kfp-pipeline-spec== 0.2.2
kfp-server-api == 2.0.1
### Steps to reproduce
After upgrading to KFP V2, Initializing a component as follows doesn't work:
```python
from kfp.dsl... | {
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https://api.github.com/repos/kubeflow/pipelines/issues/9970 | https://api.github.com/repos/kubeflow/pipelines | https://api.github.com/repos/kubeflow/pipelines/issues/9970/labels{/name} | https://api.github.com/repos/kubeflow/pipelines/issues/9970/comments | https://api.github.com/repos/kubeflow/pipelines/issues/9970/events | https://github.com/kubeflow/pipelines/issues/9970 | 1,889,838,578 | I_kwDOB-71UM5wpKXy | 9,970 | Usage of Kubeflow Pipelines v2 | {
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"> set gpu resources (.set_gpu_limit())\r\n\r\n`set_gpu_limit()` has been renamed to [`set_accelerator_limit`](https://kubeflow-pipelines.readthedocs.io/en/sdk-2.0.1/source/dsl.html?h=set_acc#kfp.dsl.PipelineTask.set_accelerator_limit) so that is covers both GPU and TPU (on Vertex). Meanwhile, `set_gpu_limit` still... | 2023-09-11T07:20:36 | 2023-09-12T01:35:55 | null | NONE | null | Hello,
we have upgraded our Kubeflow Pipelines to version 2.0.1. We are now having a lot of trouble rewriting our code from version 1.8. We are missing the following features (maybe we just didn't find them in v2):
- set gpu resources (.set_gpu_limit())
- mount hostPath (.add_volume(), add_volume_mount())
- .s... | {
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https://api.github.com/repos/kubeflow/pipelines/issues/9962 | https://api.github.com/repos/kubeflow/pipelines | https://api.github.com/repos/kubeflow/pipelines/issues/9962/labels{/name} | https://api.github.com/repos/kubeflow/pipelines/issues/9962/comments | https://api.github.com/repos/kubeflow/pipelines/issues/9962/events | https://github.com/kubeflow/pipelines/issues/9962 | 1,887,425,701 | I_kwDOB-71UM5wf9Sl | 9,962 | [backend] Persistence Agent failing kubeflow-pipeline-mkp-test (2) | {
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Having in mind issue: [Persistence agent failing kubeflow-pipeline-mkp-test](https://github.com/kubeflow/pipelines/issues/9904) that appeared after changes in the Persistence agent manifests files - I guess that the mkp-test may fail again after the merge of [this](https://github.com/kubeflow/pi... | {
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https://api.github.com/repos/kubeflow/pipelines/issues/9960 | https://api.github.com/repos/kubeflow/pipelines | https://api.github.com/repos/kubeflow/pipelines/issues/9960/labels{/name} | https://api.github.com/repos/kubeflow/pipelines/issues/9960/comments | https://api.github.com/repos/kubeflow/pipelines/issues/9960/events | https://github.com/kubeflow/pipelines/issues/9960 | 1,884,738,276 | I_kwDOB-71UM5wVtLk | 9,960 | What's the current behaviour with the run_pipeline? | {
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"@fclesio, I think the best solution for what you are trying to achieve is to compose the tasks together into a sequential DAG using a pipeline. Please take a look at the docs on [data passing and task dependencies](https://www.kubeflow.org/docs/components/pipelines/v2/pipelines/pipeline-basics/#data-passing-and-ta... | 2023-09-06T20:53:45 | 2023-09-08T14:47:16 | 2023-09-07T22:50:17 | NONE | null | Thanks once again for the great library.
I have a ML pipeline that consists in 3 tasks: ETL > Pre-Processing > Modelling and Deploy.
Since those tasks are sequential, I created 3 pipelines and I used the [kfp.client.run_pipeline ](https://github.com/kubeflow/pipelines/blob/master/sdk/python/kfp/client/client.p... | {
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<!-- Please fill in those that seem relevant. -->
* How do you deploy Kubeflow Pipelines (KFP)?
<!-- For more information, see an overview of KFP installation options: https://www.kubeflow.org/docs/pipelines/installation/overview/. -->
* KFP version:
<!-- Specify the version of Kubeflow Pipelin... | {
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Dataset Card for Dataset Name
Dataset Summary
GitHub Issues is a dataset consisting of the top 5_000 GitHub issues, as of 2023-09-02, associated with the KubeFlow Pipelines repository. It is intended for educational purposes and can be used for semantic search or multilabel text classification. The contents of each GitHub issue are in English and concern the domain of datasets for NLP, computer vision, and beyond.
Languages
Contains language commonly found in English software development.
Contributions
Thanks to @hjerpe for adding this dataset.
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