CODEWITHSUNDEEP
tensorflowgoogle-cloud-platformgoogle-cloud-ml
prsr
prsr

Reputation: 21

Error creating model version using "gcloud ml-engine versions create"

When I create a version of a machine learning model (whether it is my own model or the ML Engine census example) using the command:

gcloud ml-engine versions create v1 \ --model $MODEL_NAME \ --origin $MODEL_BINARIES \ --runtime-version 1.4

I get an error saying: ERROR: (gcloud.ml-engine.versions.create) Failed accessing the model. Please make sure that the Cloud ML Api was enabled recently and retry. If that doesn't resolve this issue, please contact Cloud ML.

Things I tried:

  1. Different versions of --runtime-version
  2. Re-enabled ML Engine API, created models again, created successful jobs multiple times.
  3. To confirm that it is not an error with my own model, I again implemented the ML engine census tutorial from scratch. This tutorial had worked perfectly for me when I had tried in Feb 2018.

I still get the same error even for the tutorial.

Any pointers on how to fix this?

Has anyone tried to create model version as shown in the tutorial since April 19, 2018?

I'd appreciate your help.

Upvotes: 2

Views: 5131

Answers (3)

Mayantha Fernando
Mayantha Fernando

Reputation: 61

Run this command:

gsutil ls -r $OUTPUT_PATH/export

In the output, you can see a number (like 1569256565). It's the new timestamp

Run this command with the new timestamp :

MODEL_BINARIES=$OUTPUT_PATH/export/census/<timestamp>/

Upvotes: 1

Solomon Igori
Solomon Igori

Reputation: 11

After running this code:

gsutil ls -r $OUTPUT_PATH/export

It will generate a new timestamp in the path link Use that timestamp

Upvotes: 1

Lak
Lak

Reputation: 4166

Check that modelbinaries is the full path folder that contains the checkpoints. Typically, this will be gs://.../.../.../timestamp, i.e. end with a timestamp

Upvotes: 0

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