[scikit-learn] Google Cloud ML Engine Error with Sklearn

[Liam Geron]

Hi scikit learn contributors,

I am currently attempting to transfer our preexisting models into cloud ML
for scalability, however I am encountering bugs while running through some
tutorial code found here (
https://github.com/GoogleCloudPlatform/cloudml-samples/blob/master/sklearn/notebooks/Online%20Prediction%20with%20scikit-learn.ipynb
).

On both my local machine in a virtual environment and on the cloud shell
I'm encountering errors when it comes to version creation and online
prediction. For version creation on my local machine and on the cloud shell
I'm encountering this error: *"ERROR: (gcloud.ml-engine.versions.create)
Bad model detected with error:  "Failed to load model: Could not load the
model: /tmp/model/0001/model.joblib. 32. (Error code: 0)""* with Python
3.6.4 (local) and Python 3.5.6 (cloud shell) when running the command:

*"gcloud ml-engine versions create $VERSION_NAME \*
*    --model $MODEL_NAME \*
*    --config config.yaml"*

This is running with joblib version "0.13.1" and sklearn version "0.19.1".

Any help would be greatly appreciated.

Thank you,
Liam Geron
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