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Demo

This directory contains assets for setting up a demo of the code search example. It is primarily intended for use by Kubeflow contributors working on the shared demo.

Users looking to run the example should follow the README.md in the parent directory.

GCP Resources

We are using the following project

Deploying the services

  1. Deploy the TFServing server

    ks12 show  cs_demo -c t2t-code-search-serving
    
  2. Deploy the UI and nmslib index server

    ks12 apply  cs_demo -c search-index-server
    
  3. Copy the GCP service account to the namespace where the servers run

    • The serving piece runs in a different namespace from Kubeflow
    • We need to copy the GCP service account to that namespace because the pod will try to mount it.
    kubectl -n kubeflow get secret user-gcp-sa -o json | jq -r '.data["user-gcp-sa.json"]' | base64 -d > ${SECRET_FILE}
    kubectl -n cs-web-app create secret generic user-gcp-sa --from-file=user-gcp-sa.json=${SECRET_FILE}
    

Install Argo CD

kubectl create namespace argocd
cd cs-demo-1103/k8s_specs
kubectl apply -f argocd.yaml

Create the app

SRC_URL=https://github.com/kubeflow/examples.git
KS_PATH=code_search/kubeflow
argocd app create code-search --name kubeflow --repo $SRC_URL --path ${KS_PATH} --env ${KS_ENV}

Results

2018-11-05

jlewi@ ran experiments that produced the following results

What location Description
Preprocessed data gs://code-search-demo/20181104/data/func-doc-pairs-00???-of-00100.csv This is the output of the Dataflow preprocessing job
Training data gs://code-search-demo/20181104/data/kf_github_function_docstring-train-00???-of-00100 TFRecord files produced by running T2T datagen

Models

hparams Location
transformer_tine gs://code-search-demo/models/20181105-tinyparams/
transformer_base_single_gpu gs://code-search-demo/models/20181105-single-gpu
transformer_base gs://code-search-demo/models/20181107-dist-sync-gpu

Performance

hparams Resources Steps/sec
transformer_tiny 1 CPU worker ~1.8 global step /sec
transformer_base_single_gpu 1 GPU worker (K80) ~3.22611 global step /sec
transformer_base 1 chief with K80, 8 workers with 1 K80, sync training ~ 0.0588723 global step /sec
transformer_base 1 chief (no GPU), 8 workers (no GPU), sync training ~ 0.707014 global step /sec