tryolabs/luminoth

Read metadata from job in Google Cloud

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#208 opened on Aug 16, 2018

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Type: Enhancementgood first issue

Description

Investigate if with the job id alone, we are able to get stuff like:

{
  "scaleTier": "BASIC_GPU",
  "packageUris": [
    "gs://luminoth-alan-train-jobs/lumi_train_20180815_173243/packages/luminoth-0.1.3.dev1.tar.gz"
  ],
  "pythonModule": "luminoth.train",
  "args": [
    "--config",
    "gs://luminoth-alan-train-jobs/lumi_train_20180815_173243/config.yml"
  ],
  "region": "us-central1",
  "runtimeVersion": "1.9",
  "jobDir": "gs://luminoth-alan-train-jobs/lumi_train_20180815_173243"
}

Thus we can leverage this for:

  • Passing fewer parameters for evaluate.
  • Not needing to use tf.gfile.ListDirectory to find the package.
  • Pass fewer parameters while resuming, or make resume a standalone command (to discuss).

Contributor guide

Tech stack
pythongcptensorflow
Domain
backendcloudmachine learning
Issue type
research
DifficultyEstimated implementation difficulty for a new contributor, from 1 for very small changes to 5 for expert-level work.
3
Estimated timeA rough time range for an experienced contributor to investigate, implement, test, and prepare a pull request.
1-3 hours
Activity statusHow available the issue appears right now: fresh, active, stale, blocked, or waiting on maintainer input.
stale
ClarityHow clearly the issue explains the expected change, acceptance criteria, and next step.
needs investigation
Prerequisites
Knowledge of Google Cloud MLPythonLuminoth codebase
Newbie friendlinessA 1-100 score estimating how approachable this issue is for first-time contributors.
20
Research direction
Investigate Google Cloud AI Platform API to retrieve job metadata using job ID alone. Look at Luminoth's evaluate and resume commands in the codebase (e.g., luminoth/commands/) to understand current parameter passing. Explore using metadata to reduce parameters for evaluate and resume.
Read metadata from job in Google Cloud · tryolabs/luminoth#208 | Good First Issue