Error while creating model valuations using ModelEvaluationClassificationOp

[trk]

Hello GCP Community,

I am encountering an issue while attempting to access data in the `ModelEvaluationClassificationOp` which is a pre-built gcp component. The error message I am receiving is:

"LookUpInode: input/output error, Error in iterating through objects: storage: bucket doesn't exist."

Here are the details of the relevant code snippet:

`ModelEvaluationClassificationOp` expects two GCS input paths (`ground_truth_gcs_source` and `predictions_gcs_source`), but I am encountering difficulties accessing the specified buckets.
ground_truth_gcs_source: list[str] = ["gs://trk-ai-models/sklearn-income-pred-model/income_classification_ml_metadata/input_predcition_data/gcs_groundtruth.jsonl"]
predictions_gcs_source: dsl.Input[system.Artifact] = "gs://trk-ai-models/sklearn-income-pred-model/income_classification_ml_metadata/output_predictions_data/prediction-test_income_model-2024_03_19T06_00_04_089Z"

I have verified that the specified buckets and respective files in Cloud Storage exist and are accessible.

 reference snippet : https://github.com/kubeflow/pipelines/blob/master/components/google-cloud/google_cloud_pipeline_comp...

please provide guidance on how to resolve this issue or suggest troubleshooting steps?

Thank you in advance for your assistance.

[nceniza]

I would suggest to file a support case for this as engineers have a better visibility of your project and your project's resource usage that will help them to investigate the issue you are having. 

https://cloud.google.com/contact

[trk]

Can I contact through the basic support plan, or do I need to have a standard support plan? If not, are there any alternatives to raise a support ticket without any cost?

[jsndai]

Hi,

---

"LookUpInode: input/output error, Error in iterating through objects: storage: bucket doesn't exist."

---

This warning message might be misleading and unrelated to the real error that caused your component to fail. It was fixed in the newer versions of the `google-cloud-pipeline-components` Python package. I recommend upgrading this package to the latest version `2.14.0` and import the `evaluation_automl_tabular_classification_pipeline` from there.

Thanks,
Jason Dai