[rllib] [RFC] Deprecate Python 2 / RLlib #4832
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don't you use python2? :) will we need to find a new maintainer? |
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Well, we can keep it deprecated for a while until everyone moves off. |
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Test FAILed. |
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Test FAILed. |
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@ericl I think it'd be a good idea to poll the ray-dev mailing list as well to see if people there use RLlib with Python 2. 10% is not a small number (though it's much better than the 60% that it was not too long ago). |
richardliaw
approved these changes
May 25, 2019
stefanpantic
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May 28, 2019
* [rllib] Remove dependency on TensorFlow (ray-project#4764) * remove hard tf dep * add test * comment fix * fix test * Dynamic Custom Resources - create and delete resources (ray-project#3742) * Update tutorial link in doc (ray-project#4777) * [rllib] Implement learn_on_batch() in torch policy graph * Fix `ray stop` by killing raylet before plasma (ray-project#4778) * Fatal check if object store dies (ray-project#4763) * [rllib] fix clip by value issue as TF upgraded (ray-project#4697) * fix clip_by_value issue * fix typo * [autoscaler] Fix submit (ray-project#4782) * Queue tasks in the raylet in between async callbacks (ray-project#4766) * Add a SWAP TaskQueue so that we can keep track of tasks that are temporarily dequeued * Fix bug where tasks that fail to be forwarded don't appear to be local by adding them to SWAP queue * cleanups * updates * updates * [Java][Bazel] Refine auto-generated pom files (ray-project#4780) * Bump version to 0.7.0 (ray-project#4791) * [JAVA] setDefaultUncaughtExceptionHandler to log uncaught exception in user thread. (ray-project#4798) * Add WorkerUncaughtExceptionHandler * Fix * revert bazel and pom * [tune] Fix CLI test (ray-project#4801) * Fix pom file generation (ray-project#4800) * [rllib] Support continuous action distributions in IMPALA/APPO (ray-project#4771) * [rllib] TensorFlow 2 compatibility (ray-project#4802) * Change tagline in documentation and README. (ray-project#4807) * Update README.rst, index.rst, tutorial.rst and _config.yml * [tune] Support non-arg submit (ray-project#4803) * [autoscaler] rsync cluster (ray-project#4785) * [tune] Remove extra parsing functionality (ray-project#4804) * Fix Java worker log dir (ray-project#4781) * [tune] Initial track integration (ray-project#4362) Introduces a minimally invasive utility for logging experiment results. A broad requirement for this tool is that it should integrate seamlessly with Tune execution. * [rllib] [RFC] Dynamic definition of loss functions and modularization support (ray-project#4795) * dynamic graph * wip * clean up * fix * document trainer * wip * initialize the graph using a fake batch * clean up dynamic init * wip * spelling * use builder for ppo pol graph * add ppo graph * fix naming * order * docs * set class name correctly * add torch builder * add custom model support in builder * cleanup * remove underscores * fix py2 compat * Update dynamic_tf_policy_graph.py * Update tracking_dict.py * wip * rename * debug level * rename policy_graph -> policy in new classes * fix test * rename ppo tf policy * port appo too * forgot grads * default policy optimizer * make default config optional * add config to optimizer * use lr by default in optimizer * update * comments * remove optimizer * fix tuple actions support in dynamic tf graph * [rllib] Rename PolicyGraph => Policy, move from evaluation/ to policy/ (ray-project#4819) This implements some of the renames proposed in ray-project#4813 We leave behind backwards-compatibility aliases for *PolicyGraph and SampleBatch. * [Java] Dynamic resource API in Java (ray-project#4824) * Add default values for Wgym flags * Fix import * Fix issue when starting `raylet_monitor` (ray-project#4829) * Refactor ID Serial 1: Separate ObjectID and TaskID from UniqueID (ray-project#4776) * Enable BaseId. * Change TaskID and make python test pass * Remove unnecessary functions and fix test failure and change TaskID to 16 bytes. * Java code change draft * Refine * Lint * Update java/api/src/main/java/org/ray/api/id/TaskId.java Co-Authored-By: Hao Chen <chenh1024@gmail.com> * Update java/api/src/main/java/org/ray/api/id/BaseId.java Co-Authored-By: Hao Chen <chenh1024@gmail.com> * Update java/api/src/main/java/org/ray/api/id/BaseId.java Co-Authored-By: Hao Chen <chenh1024@gmail.com> * Update java/api/src/main/java/org/ray/api/id/ObjectId.java Co-Authored-By: Hao Chen <chenh1024@gmail.com> * Address comment * Lint * Fix SINGLE_PROCESS * Fix comments * Refine code * Refine test * Resolve conflict * Fix bug in which actor classes are not exported multiple times. (ray-project#4838) * Bump Ray master version to 0.8.0.dev0 (ray-project#4845) * Add section to bump version of master branch and cleanup release docs (ray-project#4846) * Fix import * Export remote functions when first used and also fix bug in which rem… (ray-project#4844) * Export remote functions when first used and also fix bug in which remote functions and actor classes are not exported from workers during subsequent ray sessions. * Documentation update * Fix tests. * Fix grammar * Update wheel versions in documentation to 0.8.0.dev0 and 0.7.0. (ray-project#4847) * [tune] Later expansion of local_dir (ray-project#4806) * [rllib] [RFC] Deprecate Python 2 / RLlib (ray-project#4832) * Fix a typo in kubernetes yaml (ray-project#4872) * Move global state API out of global_state object. (ray-project#4857) * Install bazel in autoscaler development configs. (ray-project#4874) * [tune] Fix up Ax Search and Examples (ray-project#4851) * update Ax for cleaner API * docs update * [rllib] Update concepts docs and add "Building Policies in Torch/TensorFlow" section (ray-project#4821) * wip * fix index * fix bugs * todo * add imports * note on get ph * note on get ph * rename to building custom algs * add rnn state info * [rllib] Fix error getting kl when simple_optimizer: True in multi-agent PPO * Replace ReturnIds with NumReturns in TaskInfo to reduce the size (ray-project#4854) * Refine TaskInfo * Fix * Add a test to print task info size * Lint * Refine * Update deps commits of opencensus to support building with bzl 0.25.x (ray-project#4862) * Update deps to support bzl 2.5.x * Fix
stefanpantic
added a commit
to wingman-ai/ray
that referenced
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Jun 6, 2019
* [rllib] Remove dependency on TensorFlow (ray-project#4764) * remove hard tf dep * add test * comment fix * fix test * Dynamic Custom Resources - create and delete resources (ray-project#3742) * Update tutorial link in doc (ray-project#4777) * [rllib] Implement learn_on_batch() in torch policy graph * Fix `ray stop` by killing raylet before plasma (ray-project#4778) * Fatal check if object store dies (ray-project#4763) * [rllib] fix clip by value issue as TF upgraded (ray-project#4697) * fix clip_by_value issue * fix typo * [autoscaler] Fix submit (ray-project#4782) * Queue tasks in the raylet in between async callbacks (ray-project#4766) * Add a SWAP TaskQueue so that we can keep track of tasks that are temporarily dequeued * Fix bug where tasks that fail to be forwarded don't appear to be local by adding them to SWAP queue * cleanups * updates * updates * [Java][Bazel] Refine auto-generated pom files (ray-project#4780) * Bump version to 0.7.0 (ray-project#4791) * [JAVA] setDefaultUncaughtExceptionHandler to log uncaught exception in user thread. (ray-project#4798) * Add WorkerUncaughtExceptionHandler * Fix * revert bazel and pom * [tune] Fix CLI test (ray-project#4801) * Fix pom file generation (ray-project#4800) * [rllib] Support continuous action distributions in IMPALA/APPO (ray-project#4771) * [rllib] TensorFlow 2 compatibility (ray-project#4802) * Change tagline in documentation and README. (ray-project#4807) * Update README.rst, index.rst, tutorial.rst and _config.yml * [tune] Support non-arg submit (ray-project#4803) * [autoscaler] rsync cluster (ray-project#4785) * [tune] Remove extra parsing functionality (ray-project#4804) * Fix Java worker log dir (ray-project#4781) * [tune] Initial track integration (ray-project#4362) Introduces a minimally invasive utility for logging experiment results. A broad requirement for this tool is that it should integrate seamlessly with Tune execution. * [rllib] [RFC] Dynamic definition of loss functions and modularization support (ray-project#4795) * dynamic graph * wip * clean up * fix * document trainer * wip * initialize the graph using a fake batch * clean up dynamic init * wip * spelling * use builder for ppo pol graph * add ppo graph * fix naming * order * docs * set class name correctly * add torch builder * add custom model support in builder * cleanup * remove underscores * fix py2 compat * Update dynamic_tf_policy_graph.py * Update tracking_dict.py * wip * rename * debug level * rename policy_graph -> policy in new classes * fix test * rename ppo tf policy * port appo too * forgot grads * default policy optimizer * make default config optional * add config to optimizer * use lr by default in optimizer * update * comments * remove optimizer * fix tuple actions support in dynamic tf graph * [rllib] Rename PolicyGraph => Policy, move from evaluation/ to policy/ (ray-project#4819) This implements some of the renames proposed in ray-project#4813 We leave behind backwards-compatibility aliases for *PolicyGraph and SampleBatch. * [Java] Dynamic resource API in Java (ray-project#4824) * Add default values for Wgym flags * Fix import * Fix issue when starting `raylet_monitor` (ray-project#4829) * Refactor ID Serial 1: Separate ObjectID and TaskID from UniqueID (ray-project#4776) * Enable BaseId. * Change TaskID and make python test pass * Remove unnecessary functions and fix test failure and change TaskID to 16 bytes. * Java code change draft * Refine * Lint * Update java/api/src/main/java/org/ray/api/id/TaskId.java Co-Authored-By: Hao Chen <chenh1024@gmail.com> * Update java/api/src/main/java/org/ray/api/id/BaseId.java Co-Authored-By: Hao Chen <chenh1024@gmail.com> * Update java/api/src/main/java/org/ray/api/id/BaseId.java Co-Authored-By: Hao Chen <chenh1024@gmail.com> * Update java/api/src/main/java/org/ray/api/id/ObjectId.java Co-Authored-By: Hao Chen <chenh1024@gmail.com> * Address comment * Lint * Fix SINGLE_PROCESS * Fix comments * Refine code * Refine test * Resolve conflict * Fix bug in which actor classes are not exported multiple times. (ray-project#4838) * Bump Ray master version to 0.8.0.dev0 (ray-project#4845) * Add section to bump version of master branch and cleanup release docs (ray-project#4846) * Fix import * Export remote functions when first used and also fix bug in which rem… (ray-project#4844) * Export remote functions when first used and also fix bug in which remote functions and actor classes are not exported from workers during subsequent ray sessions. * Documentation update * Fix tests. * Fix grammar * Update wheel versions in documentation to 0.8.0.dev0 and 0.7.0. (ray-project#4847) * [tune] Later expansion of local_dir (ray-project#4806) * [rllib] [RFC] Deprecate Python 2 / RLlib (ray-project#4832) * Fix a typo in kubernetes yaml (ray-project#4872) * Move global state API out of global_state object. (ray-project#4857) * Install bazel in autoscaler development configs. (ray-project#4874) * [tune] Fix up Ax Search and Examples (ray-project#4851) * update Ax for cleaner API * docs update * [rllib] Update concepts docs and add "Building Policies in Torch/TensorFlow" section (ray-project#4821) * wip * fix index * fix bugs * todo * add imports * note on get ph * note on get ph * rename to building custom algs * add rnn state info * [rllib] Fix error getting kl when simple_optimizer: True in multi-agent PPO * Replace ReturnIds with NumReturns in TaskInfo to reduce the size (ray-project#4854) * Refine TaskInfo * Fix * Add a test to print task info size * Lint * Refine * Update deps commits of opencensus to support building with bzl 0.25.x (ray-project#4862) * Update deps to support bzl 2.5.x * Fix * Upgrade arrow to latest master (ray-project#4858) * [tune] Auto-init Ray + default SearchAlg (ray-project#4815) * Bump version from 0.8.0.dev0 to 0.7.1. (ray-project#4890) * [rllib] Allow access to batches prior to postprocessing (ray-project#4871) * [rllib] Fix Multidiscrete support (ray-project#4869) * Refactor redis callback handling (ray-project#4841) * Add CallbackReply * Fix * fix linting by format.sh * Fix linting * Address comments. * Fix * Initial high-level code structure of CoreWorker. (ray-project#4875) * Drop duplicated string format (ray-project#4897) This string format is unnecessary. java_worker_options has been appended to the commandline later. * Refactor ID Serial 2: change all ID functions to `CamelCase` (ray-project#4896) * Hotfix for change of from_random to FromRandom (ray-project#4909) * [rllib] Fix documentation on custom policies (ray-project#4910) * wip * add docs * lint * todo sections * fix doc * [rllib] Allow Torch policies access to full action input dict in extra_action_out_fn (ray-project#4894) * fix torch extra out * preserve setitem * fix docs * [tune] Pretty print params json in logger.py (ray-project#4903) * [sgd] Distributed Training via PyTorch (ray-project#4797) Implements distributed SGD using distributed PyTorch. * [rllib] Rough port of DQN to build_tf_policy() pattern (ray-project#4823) * fetching objects in parallel in _get_arguments_for_execution (ray-project#4775) * [tune] Disallow setting resources_per_trial when it is already configured (ray-project#4880) * disallow it * import fix * fix example * fix test * fix tests * Update mock.py * fix * make less convoluted * fix tests * [rllib] Rename PolicyEvaluator => RolloutWorker (ray-project#4820) * Fix local cluster yaml (ray-project#4918) * [tune] Directional metrics for components (ray-project#4120) (ray-project#4915) * [Core Worker] implement ObjectInterface and add test framework (ray-project#4899) * [tune] Make PBT Quantile fraction configurable (ray-project#4912) * Better organize ray_common module (ray-project#4898) * Fix error * Fix compute actions return value
stefanpantic
added a commit
to wingman-ai/ray
that referenced
this pull request
Jun 21, 2019
* [rllib] Remove dependency on TensorFlow (ray-project#4764) * remove hard tf dep * add test * comment fix * fix test * Dynamic Custom Resources - create and delete resources (ray-project#3742) * Update tutorial link in doc (ray-project#4777) * [rllib] Implement learn_on_batch() in torch policy graph * Fix `ray stop` by killing raylet before plasma (ray-project#4778) * Fatal check if object store dies (ray-project#4763) * [rllib] fix clip by value issue as TF upgraded (ray-project#4697) * fix clip_by_value issue * fix typo * [autoscaler] Fix submit (ray-project#4782) * Queue tasks in the raylet in between async callbacks (ray-project#4766) * Add a SWAP TaskQueue so that we can keep track of tasks that are temporarily dequeued * Fix bug where tasks that fail to be forwarded don't appear to be local by adding them to SWAP queue * cleanups * updates * updates * [Java][Bazel] Refine auto-generated pom files (ray-project#4780) * Bump version to 0.7.0 (ray-project#4791) * [JAVA] setDefaultUncaughtExceptionHandler to log uncaught exception in user thread. (ray-project#4798) * Add WorkerUncaughtExceptionHandler * Fix * revert bazel and pom * [tune] Fix CLI test (ray-project#4801) * Fix pom file generation (ray-project#4800) * [rllib] Support continuous action distributions in IMPALA/APPO (ray-project#4771) * [rllib] TensorFlow 2 compatibility (ray-project#4802) * Change tagline in documentation and README. (ray-project#4807) * Update README.rst, index.rst, tutorial.rst and _config.yml * [tune] Support non-arg submit (ray-project#4803) * [autoscaler] rsync cluster (ray-project#4785) * [tune] Remove extra parsing functionality (ray-project#4804) * Fix Java worker log dir (ray-project#4781) * [tune] Initial track integration (ray-project#4362) Introduces a minimally invasive utility for logging experiment results. A broad requirement for this tool is that it should integrate seamlessly with Tune execution. * [rllib] [RFC] Dynamic definition of loss functions and modularization support (ray-project#4795) * dynamic graph * wip * clean up * fix * document trainer * wip * initialize the graph using a fake batch * clean up dynamic init * wip * spelling * use builder for ppo pol graph * add ppo graph * fix naming * order * docs * set class name correctly * add torch builder * add custom model support in builder * cleanup * remove underscores * fix py2 compat * Update dynamic_tf_policy_graph.py * Update tracking_dict.py * wip * rename * debug level * rename policy_graph -> policy in new classes * fix test * rename ppo tf policy * port appo too * forgot grads * default policy optimizer * make default config optional * add config to optimizer * use lr by default in optimizer * update * comments * remove optimizer * fix tuple actions support in dynamic tf graph * [rllib] Rename PolicyGraph => Policy, move from evaluation/ to policy/ (ray-project#4819) This implements some of the renames proposed in ray-project#4813 We leave behind backwards-compatibility aliases for *PolicyGraph and SampleBatch. * [Java] Dynamic resource API in Java (ray-project#4824) * Add default values for Wgym flags * Fix import * Fix issue when starting `raylet_monitor` (ray-project#4829) * Refactor ID Serial 1: Separate ObjectID and TaskID from UniqueID (ray-project#4776) * Enable BaseId. * Change TaskID and make python test pass * Remove unnecessary functions and fix test failure and change TaskID to 16 bytes. * Java code change draft * Refine * Lint * Update java/api/src/main/java/org/ray/api/id/TaskId.java Co-Authored-By: Hao Chen <chenh1024@gmail.com> * Update java/api/src/main/java/org/ray/api/id/BaseId.java Co-Authored-By: Hao Chen <chenh1024@gmail.com> * Update java/api/src/main/java/org/ray/api/id/BaseId.java Co-Authored-By: Hao Chen <chenh1024@gmail.com> * Update java/api/src/main/java/org/ray/api/id/ObjectId.java Co-Authored-By: Hao Chen <chenh1024@gmail.com> * Address comment * Lint * Fix SINGLE_PROCESS * Fix comments * Refine code * Refine test * Resolve conflict * Fix bug in which actor classes are not exported multiple times. (ray-project#4838) * Bump Ray master version to 0.8.0.dev0 (ray-project#4845) * Add section to bump version of master branch and cleanup release docs (ray-project#4846) * Fix import * Export remote functions when first used and also fix bug in which rem… (ray-project#4844) * Export remote functions when first used and also fix bug in which remote functions and actor classes are not exported from workers during subsequent ray sessions. * Documentation update * Fix tests. * Fix grammar * Update wheel versions in documentation to 0.8.0.dev0 and 0.7.0. (ray-project#4847) * [tune] Later expansion of local_dir (ray-project#4806) * [rllib] [RFC] Deprecate Python 2 / RLlib (ray-project#4832) * Fix a typo in kubernetes yaml (ray-project#4872) * Move global state API out of global_state object. (ray-project#4857) * Install bazel in autoscaler development configs. (ray-project#4874) * [tune] Fix up Ax Search and Examples (ray-project#4851) * update Ax for cleaner API * docs update * [rllib] Update concepts docs and add "Building Policies in Torch/TensorFlow" section (ray-project#4821) * wip * fix index * fix bugs * todo * add imports * note on get ph * note on get ph * rename to building custom algs * add rnn state info * [rllib] Fix error getting kl when simple_optimizer: True in multi-agent PPO * Replace ReturnIds with NumReturns in TaskInfo to reduce the size (ray-project#4854) * Refine TaskInfo * Fix * Add a test to print task info size * Lint * Refine * Update deps commits of opencensus to support building with bzl 0.25.x (ray-project#4862) * Update deps to support bzl 2.5.x * Fix * Upgrade arrow to latest master (ray-project#4858) * [tune] Auto-init Ray + default SearchAlg (ray-project#4815) * Bump version from 0.8.0.dev0 to 0.7.1. (ray-project#4890) * [rllib] Allow access to batches prior to postprocessing (ray-project#4871) * [rllib] Fix Multidiscrete support (ray-project#4869) * Refactor redis callback handling (ray-project#4841) * Add CallbackReply * Fix * fix linting by format.sh * Fix linting * Address comments. * Fix * Initial high-level code structure of CoreWorker. (ray-project#4875) * Drop duplicated string format (ray-project#4897) This string format is unnecessary. java_worker_options has been appended to the commandline later. * Refactor ID Serial 2: change all ID functions to `CamelCase` (ray-project#4896) * Hotfix for change of from_random to FromRandom (ray-project#4909) * [rllib] Fix documentation on custom policies (ray-project#4910) * wip * add docs * lint * todo sections * fix doc * [rllib] Allow Torch policies access to full action input dict in extra_action_out_fn (ray-project#4894) * fix torch extra out * preserve setitem * fix docs * [tune] Pretty print params json in logger.py (ray-project#4903) * [sgd] Distributed Training via PyTorch (ray-project#4797) Implements distributed SGD using distributed PyTorch. * [rllib] Rough port of DQN to build_tf_policy() pattern (ray-project#4823) * fetching objects in parallel in _get_arguments_for_execution (ray-project#4775) * [tune] Disallow setting resources_per_trial when it is already configured (ray-project#4880) * disallow it * import fix * fix example * fix test * fix tests * Update mock.py * fix * make less convoluted * fix tests * [rllib] Rename PolicyEvaluator => RolloutWorker (ray-project#4820) * Fix local cluster yaml (ray-project#4918) * [tune] Directional metrics for components (ray-project#4120) (ray-project#4915) * [Core Worker] implement ObjectInterface and add test framework (ray-project#4899) * [tune] Make PBT Quantile fraction configurable (ray-project#4912) * Better organize ray_common module (ray-project#4898) * Fix error * [tune] Add requirements-dev.txt and update docs for contributing (ray-project#4925) * Add requirements-dev.txt and update docs. * Update doc/source/tune-contrib.rst Co-Authored-By: Richard Liaw <rliaw@berkeley.edu> * Unpin everything except for yapf. * Fix compute actions return value * Bump version from 0.7.1 to 0.8.0.dev1. (ray-project#4937) * Update version number in documentation after release 0.7.0 -> 0.7.1 and 0.8.0.dev0 -> 0.8.0.dev1. (ray-project#4941) * [doc] Update developer docs with bazel instructions (ray-project#4944) * [C++] Add hash table to Redis-Module (ray-project#4911) * Flush lineage cache on task submission instead of execution (ray-project#4942) * [rllib] Add docs on how to use TF eager execution (ray-project#4927) * [rllib] Port remainder of algorithms to build_trainer() pattern (ray-project#4920) * Fix resource bookkeeping bug with acquiring unknown resource. (ray-project#4945) * Update aws keys for uploading wheels to s3. (ray-project#4948) * Upload wheels on Travis to branchname/commit_id. (ray-project#4949) * [Java] Fix serializing issues of `RaySerializer` (ray-project#4887) * Fix * Address comment. * fix (ray-project#4950) * [Java] Add inner class `Builder` to build call options. (ray-project#4956) * Add Builder class * format * Refactor by IDE * Remove uncessary dependency * Make release stress tests work and improve them. (ray-project#4955) * Use proper session directory for debug_string.txt (ray-project#4960) * [core] Use int64_t instead of int to keep track of fractional resources (ray-project#4959) * [core worker] add task submission & execution interface (ray-project#4922) * [sgd] Add non-distributed PyTorch runner (ray-project#4933) * Add non-distributed PyTorch runner * use dist.is_available() instead of checking OS * Nicer exception * Fix bug in choosing port * Refactor some code * Address comments * Address comments * Flush all tasks from local lineage cache after a node failure (ray-project#4964) * Remove typing from setup.py install_requirements. (ray-project#4971) * [Java] Fix bug of `BaseID` in multi-threading case. (ray-project#4974) * [rllib] Fix DDPG example (ray-project#4973) * Upgrade CI clang-format to 6.0 (ray-project#4976) * [Core worker] add store & task provider (ray-project#4966) * Fix bugs in the a3c code template. (ray-project#4984) * Inherit Function Docstrings and other metedata (ray-project#4985) * Fix a crash when unknown worker registering to raylet (ray-project#4992) * [gRPC] Use gRPC for inter-node-manager communication (ray-project#4968)
stefanpantic
added a commit
to wingman-ai/ray
that referenced
this pull request
Jun 26, 2019
* [rllib] Remove dependency on TensorFlow (ray-project#4764) * remove hard tf dep * add test * comment fix * fix test * Dynamic Custom Resources - create and delete resources (ray-project#3742) * Update tutorial link in doc (ray-project#4777) * [rllib] Implement learn_on_batch() in torch policy graph * Fix `ray stop` by killing raylet before plasma (ray-project#4778) * Fatal check if object store dies (ray-project#4763) * [rllib] fix clip by value issue as TF upgraded (ray-project#4697) * fix clip_by_value issue * fix typo * [autoscaler] Fix submit (ray-project#4782) * Queue tasks in the raylet in between async callbacks (ray-project#4766) * Add a SWAP TaskQueue so that we can keep track of tasks that are temporarily dequeued * Fix bug where tasks that fail to be forwarded don't appear to be local by adding them to SWAP queue * cleanups * updates * updates * [Java][Bazel] Refine auto-generated pom files (ray-project#4780) * Bump version to 0.7.0 (ray-project#4791) * [JAVA] setDefaultUncaughtExceptionHandler to log uncaught exception in user thread. (ray-project#4798) * Add WorkerUncaughtExceptionHandler * Fix * revert bazel and pom * [tune] Fix CLI test (ray-project#4801) * Fix pom file generation (ray-project#4800) * [rllib] Support continuous action distributions in IMPALA/APPO (ray-project#4771) * [rllib] TensorFlow 2 compatibility (ray-project#4802) * Change tagline in documentation and README. (ray-project#4807) * Update README.rst, index.rst, tutorial.rst and _config.yml * [tune] Support non-arg submit (ray-project#4803) * [autoscaler] rsync cluster (ray-project#4785) * [tune] Remove extra parsing functionality (ray-project#4804) * Fix Java worker log dir (ray-project#4781) * [tune] Initial track integration (ray-project#4362) Introduces a minimally invasive utility for logging experiment results. A broad requirement for this tool is that it should integrate seamlessly with Tune execution. * [rllib] [RFC] Dynamic definition of loss functions and modularization support (ray-project#4795) * dynamic graph * wip * clean up * fix * document trainer * wip * initialize the graph using a fake batch * clean up dynamic init * wip * spelling * use builder for ppo pol graph * add ppo graph * fix naming * order * docs * set class name correctly * add torch builder * add custom model support in builder * cleanup * remove underscores * fix py2 compat * Update dynamic_tf_policy_graph.py * Update tracking_dict.py * wip * rename * debug level * rename policy_graph -> policy in new classes * fix test * rename ppo tf policy * port appo too * forgot grads * default policy optimizer * make default config optional * add config to optimizer * use lr by default in optimizer * update * comments * remove optimizer * fix tuple actions support in dynamic tf graph * [rllib] Rename PolicyGraph => Policy, move from evaluation/ to policy/ (ray-project#4819) This implements some of the renames proposed in ray-project#4813 We leave behind backwards-compatibility aliases for *PolicyGraph and SampleBatch. * [Java] Dynamic resource API in Java (ray-project#4824) * Add default values for Wgym flags * Fix import * Fix issue when starting `raylet_monitor` (ray-project#4829) * Refactor ID Serial 1: Separate ObjectID and TaskID from UniqueID (ray-project#4776) * Enable BaseId. * Change TaskID and make python test pass * Remove unnecessary functions and fix test failure and change TaskID to 16 bytes. * Java code change draft * Refine * Lint * Update java/api/src/main/java/org/ray/api/id/TaskId.java Co-Authored-By: Hao Chen <chenh1024@gmail.com> * Update java/api/src/main/java/org/ray/api/id/BaseId.java Co-Authored-By: Hao Chen <chenh1024@gmail.com> * Update java/api/src/main/java/org/ray/api/id/BaseId.java Co-Authored-By: Hao Chen <chenh1024@gmail.com> * Update java/api/src/main/java/org/ray/api/id/ObjectId.java Co-Authored-By: Hao Chen <chenh1024@gmail.com> * Address comment * Lint * Fix SINGLE_PROCESS * Fix comments * Refine code * Refine test * Resolve conflict * Fix bug in which actor classes are not exported multiple times. (ray-project#4838) * Bump Ray master version to 0.8.0.dev0 (ray-project#4845) * Add section to bump version of master branch and cleanup release docs (ray-project#4846) * Fix import * Export remote functions when first used and also fix bug in which rem… (ray-project#4844) * Export remote functions when first used and also fix bug in which remote functions and actor classes are not exported from workers during subsequent ray sessions. * Documentation update * Fix tests. * Fix grammar * Update wheel versions in documentation to 0.8.0.dev0 and 0.7.0. (ray-project#4847) * [tune] Later expansion of local_dir (ray-project#4806) * [rllib] [RFC] Deprecate Python 2 / RLlib (ray-project#4832) * Fix a typo in kubernetes yaml (ray-project#4872) * Move global state API out of global_state object. (ray-project#4857) * Install bazel in autoscaler development configs. (ray-project#4874) * [tune] Fix up Ax Search and Examples (ray-project#4851) * update Ax for cleaner API * docs update * [rllib] Update concepts docs and add "Building Policies in Torch/TensorFlow" section (ray-project#4821) * wip * fix index * fix bugs * todo * add imports * note on get ph * note on get ph * rename to building custom algs * add rnn state info * [rllib] Fix error getting kl when simple_optimizer: True in multi-agent PPO * Replace ReturnIds with NumReturns in TaskInfo to reduce the size (ray-project#4854) * Refine TaskInfo * Fix * Add a test to print task info size * Lint * Refine * Update deps commits of opencensus to support building with bzl 0.25.x (ray-project#4862) * Update deps to support bzl 2.5.x * Fix * Upgrade arrow to latest master (ray-project#4858) * [tune] Auto-init Ray + default SearchAlg (ray-project#4815) * Bump version from 0.8.0.dev0 to 0.7.1. (ray-project#4890) * [rllib] Allow access to batches prior to postprocessing (ray-project#4871) * [rllib] Fix Multidiscrete support (ray-project#4869) * Refactor redis callback handling (ray-project#4841) * Add CallbackReply * Fix * fix linting by format.sh * Fix linting * Address comments. * Fix * Initial high-level code structure of CoreWorker. (ray-project#4875) * Drop duplicated string format (ray-project#4897) This string format is unnecessary. java_worker_options has been appended to the commandline later. * Refactor ID Serial 2: change all ID functions to `CamelCase` (ray-project#4896) * Hotfix for change of from_random to FromRandom (ray-project#4909) * [rllib] Fix documentation on custom policies (ray-project#4910) * wip * add docs * lint * todo sections * fix doc * [rllib] Allow Torch policies access to full action input dict in extra_action_out_fn (ray-project#4894) * fix torch extra out * preserve setitem * fix docs * [tune] Pretty print params json in logger.py (ray-project#4903) * [sgd] Distributed Training via PyTorch (ray-project#4797) Implements distributed SGD using distributed PyTorch. * [rllib] Rough port of DQN to build_tf_policy() pattern (ray-project#4823) * fetching objects in parallel in _get_arguments_for_execution (ray-project#4775) * [tune] Disallow setting resources_per_trial when it is already configured (ray-project#4880) * disallow it * import fix * fix example * fix test * fix tests * Update mock.py * fix * make less convoluted * fix tests * [rllib] Rename PolicyEvaluator => RolloutWorker (ray-project#4820) * Fix local cluster yaml (ray-project#4918) * [tune] Directional metrics for components (ray-project#4120) (ray-project#4915) * [Core Worker] implement ObjectInterface and add test framework (ray-project#4899) * [tune] Make PBT Quantile fraction configurable (ray-project#4912) * Better organize ray_common module (ray-project#4898) * Fix error * [tune] Add requirements-dev.txt and update docs for contributing (ray-project#4925) * Add requirements-dev.txt and update docs. * Update doc/source/tune-contrib.rst Co-Authored-By: Richard Liaw <rliaw@berkeley.edu> * Unpin everything except for yapf. * Fix compute actions return value * Bump version from 0.7.1 to 0.8.0.dev1. (ray-project#4937) * Update version number in documentation after release 0.7.0 -> 0.7.1 and 0.8.0.dev0 -> 0.8.0.dev1. (ray-project#4941) * [doc] Update developer docs with bazel instructions (ray-project#4944) * [C++] Add hash table to Redis-Module (ray-project#4911) * Flush lineage cache on task submission instead of execution (ray-project#4942) * [rllib] Add docs on how to use TF eager execution (ray-project#4927) * [rllib] Port remainder of algorithms to build_trainer() pattern (ray-project#4920) * Fix resource bookkeeping bug with acquiring unknown resource. (ray-project#4945) * Update aws keys for uploading wheels to s3. (ray-project#4948) * Upload wheels on Travis to branchname/commit_id. (ray-project#4949) * [Java] Fix serializing issues of `RaySerializer` (ray-project#4887) * Fix * Address comment. * fix (ray-project#4950) * [Java] Add inner class `Builder` to build call options. (ray-project#4956) * Add Builder class * format * Refactor by IDE * Remove uncessary dependency * Make release stress tests work and improve them. (ray-project#4955) * Use proper session directory for debug_string.txt (ray-project#4960) * [core] Use int64_t instead of int to keep track of fractional resources (ray-project#4959) * [core worker] add task submission & execution interface (ray-project#4922) * [sgd] Add non-distributed PyTorch runner (ray-project#4933) * Add non-distributed PyTorch runner * use dist.is_available() instead of checking OS * Nicer exception * Fix bug in choosing port * Refactor some code * Address comments * Address comments * Flush all tasks from local lineage cache after a node failure (ray-project#4964) * Remove typing from setup.py install_requirements. (ray-project#4971) * [Java] Fix bug of `BaseID` in multi-threading case. (ray-project#4974) * [rllib] Fix DDPG example (ray-project#4973) * Upgrade CI clang-format to 6.0 (ray-project#4976) * [Core worker] add store & task provider (ray-project#4966) * Fix bugs in the a3c code template. (ray-project#4984) * Inherit Function Docstrings and other metedata (ray-project#4985) * Fix a crash when unknown worker registering to raylet (ray-project#4992) * [gRPC] Use gRPC for inter-node-manager communication (ray-project#4968) * Fix Java CI failure (ray-project#4995) * fix handling of non-integral timeout values in signal.receive (ray-project#5002) * temp fix for build (ray-project#5006) * [tune] Tutorial UX Changes (ray-project#4990) * add integration, iris, ASHA, recursive changes, set reuse_actors=True, and enable Analysis as a return object * docstring * fix up example * fix * cleanup tests * experiment analysis * Fix valgrind build by installing new version of valgrind (ray-project#5008) * Fix no cpus test (ray-project#5009) * Fix tensorflow-1.14 installation in jenkins (ray-project#5007) * Add dynamic worker options for worker command. (ray-project#4970) * Add fields for fbs * WIP * Fix complition errors * Add java part * FIx * Fix * Fix * Fix lint * Refine API * address comments and add test * Fix * Address comment. * Address comments. * Fix linting * Refine * Fix lint * WIP: address comment. * Fix java * Fix py * Refin * Fix * Fix * Fix linting * Fix lint * Address comments * WIP * Fix * Fix * minor refine * Fix lint * Fix raylet test. * Fix lint * Update src/ray/raylet/worker_pool.h Co-Authored-By: Hao Chen <chenh1024@gmail.com> * Update java/runtime/src/main/java/org/ray/runtime/AbstractRayRuntime.java Co-Authored-By: Hao Chen <chenh1024@gmail.com> * Address comments. * Address comments. * Fix test. * Update src/ray/raylet/worker_pool.h Co-Authored-By: Hao Chen <chenh1024@gmail.com> * Address comments. * Address comments. * Fix * Fix lint * Fix lint * Fix * Address comments. * Fix linting * [docs] docs for running Tensorboard without sudo (ray-project#5015) * Instructions for running Tensorboard without sudo When we run Tensorboard to visualize the results of Ray outputs on multi-user clusters where we don't have sudo access, such as RISE clusters, a few commands need to first be run to make sure tensorboard can edit the tmp directory. This is a pretty common usecase so I figured we may as well put it in the documentation for Tune. * Update tune-usage.rst * [ci] Change Jenkins to py3 (ray-project#5022) * conda3 * integration * add nevergrad, remotedata * pytest 0.3.1 * otherdockers * setup * tune * [gRPC] Migrate gcs data structures to protobuf (ray-project#5024) * [rllib] Add QMIX mixer parameters to optimizer param list (ray-project#5014) * add mixer params * Update qmix_policy.py * [grpc] refactor rpc server to support multiple io services (ray-project#5023) * [rllib] Give error if sample_async is used with pytorch for A3C (ray-project#5000) * give error if sample_async is used with pytorch * update * Update a3c.py * [tune] Update MNIST Example (ray-project#4991) * Add entropy coeff schedule * Revert "Merge with ray master" This reverts commit 108bfa2, reversing changes made to 2e0eec9. * Revert "Revert "Merge with ray master"" This reverts commit 92c0f88. * Remove entropy decay stuff
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What do these changes do?
This deprecates Python 2 for RLlib (just RLlib, not ray core). Currently less than 10% of pip installs are for Python 2.
The main advantage of moving to Python 3 is the addition of type annotations.