* pong on pixels working (not cleaned up)
* make training compatible with all atari games
* cartpole runs
* Update documentation and usage for policy gradients.
* Compile the Ray redis module with C++.
* Redo parsing of object table notifications with flatbuffers.
* Update redis module python tests.
* Redo parsing of task table notifications with flatbuffers.
* Fix linting.
* Redo parsing of db client notifications with flatbuffers.
* Redo publishing of local scheduler heartbeats with flatbuffers.
* Fix linting.
* Remove usage of fixed-width formatting of scheduling state in channel name.
* Reply with flatbuffer object to task table queries, also simplify redis string to flatbuffer string conversion.
* Fix linting and tests.
* fix
* cleanup
* simplify logic in ReplyWithTask
* Initial conversion
* Further changes
* fixes
* some changes
* Fixes
* Added data pipeline
* Added updates to cifar
* Currently borken need sep pr
* Added test for retriving variables from an optimizer
* Removed FlAG ref in environment variables
* Added comments to test
* Addressed comments
* Added updates
* Made further changes for tfutils
* Fixed finalized bug
* Removed ipython
* Added accuracy printing
* Temp commit
* added fixes
* changes
* Added writing to file
* Fixes for gpus
* Cleaned up code
* Temp commit
* Gpu support fully implemented
* Updated to use num_gpus for actors
* Finished testing gpus implementation
* Changed to be more in line with origin implementation
* Updated test to use actors
* Added support for cpu only systems
* Now works with no cpus
* Minor changes and some documentation.
* Attempt to start web UI when starting Ray.
* Add instructions for using web UI to cluster documentation.
* Don't check if port 8080 is open.
* Remove print statement.
* Added example for compute grads in ray
* Added formatting
* Removed need for placeholders in apply gradient
* Streamlined examples
* Fixed docs
* Added formatting
* Removed old references
* Simplified code some
* Addressed comments
* Changes to first code block
* Added test for training and updated code snippets
* Formatting
* Removed mean
* Removed all mention of mean
* Added comments
* Added comments
* start updating cluster documentation with parallel ssh
* add using ray on a large cluster
* revert changes to using ray on a cluster
* update cluster documentation
* update title
* Some formatting changes, and added some notes.
* clarification
* Add warning about public versus private IP addresses.
* Typos and wording.
* Clarifications.
* Clarifications.
* Added test for retriving variables from an optimizer
* Added comments to test
* Addressed comments
* Fixed travis bug
* Added fix to circular controls
* Added set for explored operations and duplicate prefix stripping
* Removed embeded ipython
* Removed prefix, use seperate graph for each network
* Removed redundant imports
* Addressed comments and added separate graph to initializer
* fix typos
* get rid of prefix in documentation
* Remove start_ray_local from ray.init and change default number of workers to 10.
* Remove alexnet example.
* Move array methods to experimental.
* Remove TRPO example.
* Remove old files.
* Compile plasma when we build numbuf.
* Address comments.
* Updated code to mesh with get_weights returning a dict and new tf code
* Added tf.global_variables_initalizer to hyperopt example as well
* Small fix.
* Small name change.
* Added helper class for getting tf variables from loss function
* Updated usage and documentation
* Removed try-catches
* Added futures
* Added documentation
* fixes and tests
* more tests
* install tensorflow in travis
* Initial integration of webui with ray
* Re-organized calling of build-webui in setup.py
* Fixed Lint comments on js code
* Fixed more lint issues
* Fixed various issues
* Fixed directory in services.py
* Small changes.
* Changes to match lint
* Small cleanups in worker.py.
* Remove dependencies on subprocess32, graphviz, protobuf, and ipython.
* Retry starting the plasma manager if the port is in use.
* Whitespace
* Move start_plasma_manager into plasma.py.
