* Use the nicer tf.gfile interface for search index creation
* Update documentation and more maintainable interface to search server
* Add ability to control number of outputs
* Serve React UI from the Flask server
* Update Dockerfile for the unified server and ui
* Upgrade TFJob and Ksonnet app
* Container name should be tensorflow. See #563.
* Working single node training and serving on Kubeflow
* Add issue link for fixme
* Remove redundant create secrets and use Kubeflow provided secrets
* Update T2T problems to workaround memory limitations
* Add max_samples_for_vocab to prevent memory overflow
* Fix a base URL to download data from, sweet spot for max samples
* Convert class variables to class properties
* Fix lint errors
* Use Python2/3 compatible code for StringIO
* Fix lint errors
* Fix source data files format
* Move to Text2TextProblem instead of TranslateProblem
* Update details for num_shards and T2T problem dataset
* Update to a new dataflow package
* [WIP] updating docstrings, fixing redundancies
* Limit the scope of Github Transform pipeline, make everything unicode
* Add ability to start github pipelines from transformed bigquery dataset
* Upgrade batch prediction pipeline to be modular
* Fix lint errors
* Add write disposition to BigQuery transform
* Update documentation format
* Nicer names for modules
* Add unicode encoding to parsed function docstring tuples
* Use Apache Beam options parser to expose all CLI arguments
* Refactor the dataflow package
* Create placeholder for new prediction pipeline
* [WIP] add dofn for encoding
* Merge all modules under single package
* Pipeline data flow complete, wip prediction values
* Fallback to custom commands for extra dependency
* Working Dataflow runner installs, separate docker-related folder
* [WIP] Updated local user journey in README, fully working commands, easy container translation
* Working Batch Predictions.
* Remove docstring embeddings
* Complete batch prediction pipeline
* Update Dockerfiles and T2T Ksonnet components
* Fix linting
* Downgrade runtime to Python2, wip memory issues so use lesser data
* Pin master to index 0.
* Working batch prediction pipeline
* Modular Github Batch Prediction Pipeline, stores back to BigQuery
* Fix lint errors
* Fix module-wide imports, pin batch-prediction version
* Fix relative import, update docstrings
* Add references to issue and current workaround for Batch Prediction dependency.
* Add auto-downloads for the data
* Make top() a no-op, working export
* Fix lint errors
* Integrate NMSlib server with TF Serving
* Clarify data URLs purpose
* Initialize search UI. Needs connection to search service
* Fix page title
* Add component for code search results, dummy values for now
* Fix title and manifest
* Add mock loading UI. Need to fill in real API results
* Wrap application into Dockerfile
* Add similarity transformer body
* Update pipeline to Write a single CSV file
* Fix lint errors
* Use CSV writer to handle formatting rows
* Use direct transformer encoding methods with variable scopes
* Complete end-to-end training with new model and problem
* Read from mutliple csv files
* Add new TF-Serving component with sample task
* Unify nmslib and t2t packages, need to be cohesive
* [WIP] update references to the package
* Replace old T2T problem
* Add representative code for encoding/decoding from tf serving service
* Add rest API port to TF serving (replaces custom http proxy)
* Fix linting
* Add NMSLib creator and server components
* Add docs to CLI module
* Add jobs derived from t2t component, GCP credentials assumed
* Add script to create IAM role bindings for Docker container to use
* Fix names to hyphens
* Add t2t-exporter wrapper
* Fix typos
* A temporary workaround for tensorflow/tensor2tensor#879
* Complete working pipeline of datagen, trainer and exporter
* Add docstring to create_secrets.sh
* Add a utility python package for indexing and serving the index
* Add CLI arguments, conditional GCS download
* Complete skeleton CLIs for serving and index creation
* Fix lint issues
* [WIP] initialize ksonnet app
* Push images to GCR
* Upgrade Docker container to run T2T entrypoint with appropriate env vars
* Add a tf-job based t2t-job
* Fix GPU parameters
* New tensor2tensor problem for function summarization
* Consolidate README with improved docs
* Remove old readme
* Add T2T Trainer using Transformer Networks
* Fix missing requirement for t2t-trainer
* Code Search Preprocessing Pipeline
* Add missing pipeline execution to git tree
* Move the preprocessing step into its own package
* Add docstrings
* Fix pylint errors
Sanyam Kapoor
Sanyam Kapoor