Create a end-to-end kubeflow example using seq2seq model (3/n) #31
Conversation
This file contains bidirectional Unicode text that may be interpreted or compiled differently than what appears below. To review, open the file in an editor that reveals hidden Unicode characters.
Learn more about bidirectional Unicode characters
* Create a simple tornado server to serve the model * TODO: Create a docker image for the server and deploy on kubeflow Related to #11
|
Review status: 0 of 3 files reviewed at latest revision, 1 unresolved discussion. github_issue_summarization/serving_the_model.md, line 5 at r2 (raw file):
Can you add a comment explaining why we don't use TFServing. Comments from Reviewable |
added 2 commits
March 7, 2018 15:32
|
Review status: 0 of 3 files reviewed at latest revision, 1 unresolved discussion. github_issue_summarization/serving_the_model.md, line 5 at r2 (raw file): Previously, jlewi (Jeremy Lewi) wrote…
Done. Comments from Reviewable |
|
/lgtm |
|
[APPROVALNOTIFIER] This PR is APPROVED This pull-request has been approved by: jlewi The full list of commands accepted by this bot can be found here. The pull request process is described here
Needs approval from an approver in each of these files:
Approvers can indicate their approval by writing |
k8s-ci-robot
pushed a commit
that referenced
this pull request
Apr 6, 2018
…nd Kubeflow (#42) * Add awscli tools container. * Add initial readme. * Add argo skeleton. * Run a an argo job. * Artifact support and argo test * Use built container (#3) * Fix artifacts and secrets * Add work in progress tfflow (#14) * Add kvc deployment to workflow. * Switch aws repo. * wip. * Add working tfflow job. * Add sidecar that waits for MASTER completion * Pass in job-name * Add volumemanager info step * Add input parameters to step * Adds nodeaffinity and hostpath * Add fixes for workflow (#17) - Use correct images for worker and ps - Use correct aws keys - Change volumemanager to mnist - Comment unused steps - Fix volume mount to correct containers * Fix hostpath for tfjob * Download all mnist files * added GCS stored artifacts comptability to Argo * Add initial inference workflow. (#30) * Initial serving step (#31) * Adds fixes to initial serving step * Ready for rough demo: Workflow in working state * Move conflicting readme. * Initial commit, everything boots without crashing. * Working, with some python errors. * Adding explicit flags * Working with ins-outs * Letting training job exit on success * Adding documentation skeletion * trying to properly save model * Almost working * Working * Adding export script, refactored to allow model more reusability * Starting documentation * little further on docs * More doc updates, fixing sleep logic * adding urls for mnist data * Removing download logic, it's to tied in with build-in tf examples. * Added argo workflow instructions, minor cleanups. * Adding mnist client. * Fixing typos * Adding instructions for installing components. * Added ksonnet container * Adding new entrypoint. * Added helm install instructions for kvc * doing things with variables * Typos. * Added better namespace support * S3 refactor. * Added missing region variables. * Adding tensorboard support. * Addding Container for Tensorboard. * Added temporary flag, added install instructions for CLI. * Removing invalid ksonnet environment. * Updating readme * Cleanup currently unused pieces * Add missint cluster-role * Minor cleanup. * Adding more parameters. * added changes to allow model to train on multiple workers and fixed some doc typos * Adding flag to enable/disable model serving. Adding s3 urls as outputs for future querying, renaming info step. * Adding seperate deployer workflow. * Split serving working. * Adding split workflow. * More parameters. * updates as to elson comments * Revert "added changes to allow model to train on multiple workers and fixed s…" * Initial working pure-s3 workflow. * Removed wait sidecars. * Remove unused flag. * Added part two, minor doc fixes * Inverted links... * Adding diff. * Fix url syntax * Documentation updates. * Added AWS Cli * Parameterized export. * Fixing image in s3 version. * Fixed documentation issues. * KVC snippet changes, need to find last working helm chart. * Temporarily pinning kvc version. * working master model and some doc typos fixes (#13) * added changes to allow model to train on multiple workers and fixed some doc typos * Adding flag to enable/disable model serving. Adding s3 urls as outputs for future querying, renaming info step. * Adding seperate deployer workflow. * Split serving working. * Adding split workflow. * More parameters. * updates as to elson comments * working master model and some doc typos * fixes as to Elson * Removign whitespace differences * updating diff * Changing parameters. * Undoing whitespace. * Changing termination policy on s3 version due to unknown issue. * Updating mnist diff. * Changing train steps. * Syncing Demo changes. * Update README.md * Going S3-native for initial example. Getting rid of Master. * Minor documentation tweaks, adding params, swapping aws cli for minio. * Updating KVC version. * Switching ksonnet repo, removing model name from client. * Updating git url. * Adding certificate hack to avoid RBAC errors. * Pinning KVC to commit while working on PR. * Updating version. * Updates README with additional details (#14) * Updates README with additional details * Adding clarity to kubectl config commands * Fixed comma placement * Refactoring notes for github and kubernetes credentials. * Forgot to add an overview of the argo template. * Updating example based on feedback. - Removed superflous images - Clarified use of KVC - Added unaltered model - Variable cleanup * Refactored grpc image into generic base image. * minor cleanup of resubmitting section. * Switching Argo deployment to ksonnet, conslidating install instructions. * Removing old cruft, clarifying cluster requirements. * [WIP] Switching out model (#15) * Switching to new mnist example. * Parameterized model, testing export. * Got CNN model exporting. * Attempting to do distributed training with Estimator, removed seperate export. * Adding master back, otherwise Estimator complains about not having a chief. * Switching to tf.estimator.train_and_evaluate. * Minor path/var name refactor. * Adding test data and new client. * Fixed documentation to reflect new client. * Getting rid of tf job shim. * Removing KVC from example, renaming directory * Modifying parent README * Removed reference to export. * Adding reference to export. * Removing unused Dockerfile. * Removing uneeded files, simplifying how to get status, refactor model serving workflow step. * Renaming directory * Minor doc improvements, removed extra clis. * Making SSL configurable for clusters without secured s3 endpoints. * Added a tf-user account for workflow. Fixed serving bug. * Updating gke version. * Re-ran through instructions, fixed errata. * Fixing lint issues * Pylint errors * Pylint errors * Adding parenthesis back. * pylint Hacks * Disabling argument filter, model bombs without empty arg. * Removing unneeded lambdas
Sign up for free
to join this conversation on GitHub.
Already have an account?
Sign in to comment
Add this suggestion to a batch that can be applied as a single commit.
This suggestion is invalid because no changes were made to the code.
Suggestions cannot be applied while the pull request is closed.
Suggestions cannot be applied while viewing a subset of changes.
Only one suggestion per line can be applied in a batch.
Add this suggestion to a batch that can be applied as a single commit.
Applying suggestions on deleted lines is not supported.
You must change the existing code in this line in order to create a valid suggestion.
Outdated suggestions cannot be applied.
This suggestion has been applied or marked resolved.
Suggestions cannot be applied from pending reviews.
Suggestions cannot be applied on multi-line comments.
Suggestions cannot be applied while the pull request is queued to merge.
Suggestion cannot be applied right now. Please check back later.
Related to #11
This change is