issue during deployement of model gcloud ml-engine versions create

0
votes

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 1.10

I got an error saying: ERROR: (gcloud.ml-engine.versions.create) FAILED_PRECONDITION: Framework can not be identified from model path. Please make sure your model file name is correct.

1
google-cloud-platformgoogle-cloud-ml
what is the value of $MODEL_BINARIES? And what are the files at that location? Are you using a TF saved model? – Bhupesh
Yes, I am using a TF saved model – Sanjay Kumar
What are the names of the files at the location you are sending out for deployment? Does it have saved_model.pb missing? Can you confirm that? – Bhupesh
If you need further help, feel free to reach out to cloudml-feedback@google.com – Bhupesh
am I supposed to email them or they have live chat option? – Sanjay Kumar

1 Answers

0
votes

Make sure that MODEL_BINARIES is a folder that contains the saved_model.pb file.

When I followed the google documentation, 

gsutil cp -r SavedModel/saved_model ${YOUR_GCS_BUCKET}/model_dir_tmp/

it just copied the file saved_model.pb into ${YOUR_GCS_BUCKET}/model_dir_tmp, instead of creating ${YOUR_GCS_BUCKET}/model_dir_tmp/saved_model.

Later, when I passed in ${YOUR_GCS_BUCKET}/model_dir_tmp/saved_model to --origin, I received the complaint about Framework can not be identified from model path.

I manually went to the cloud console webpage, and created a folder saved_model and moved the file saved_model.pb into it.