Release 0 4 17 (#985)
* Envision near real time (#785)
* Added frame_time in envision State, frame_time is the elapsed simulation time
* Added "near real-time" and "uncapped" mode in Envision
* add optimization to get frame_time from frame in server.py by using ijson instead of json loading the entire frame
Co-authored-by: Stephen Hockema <[email protected]>
* Zoo manager spawned as a subprocess (#814)
* Envision fixes (#810)
* Fixed race condition with seek flushing.
* formatting
* also limit stateQueue size while I'm at it.
* More options for buffer overflow.
* added comment
* Quiet Envision logs (#820)
* Quiet error received when initially unable to connect to Envision.
* output a warning on the first failed connection only.
* formatting
* added to CHANGELOG
* Quiet pybullet import msgs (#821)
* quiet "pybullet build time: ..." messages on stdout when pybullet is imported.
* added CHANGELOG entry
* formatting
* typo fix in CHANGELOG
* fixed typo in filename
* fixed backwards polarity on dones check (#824)
* fix rounding cf timestp_sec to ensure we always keep enough digits (#825)
* ULTRA Update callbacks (#818)
* update episode callback
* Apply suggestions from code review
Co-authored-by: christianjans <[email protected]>
Co-authored-by: christianjans <[email protected]>
* Added a new pypi instructions file to update general user installation instructions
* Ignore tune test in ULTRA's heavy CI tests (#811)
* Make naming consistent for task 2's levels (#806)
* Fixed typo in instructions
* Cleaned up the instructions to only include the pip install instructions
* Added further instructions about the modules involved in the package and how to use them to create environments and scenarios
* updated CHANGELOG.md
* updated README_pypi.md based on changes requested
* fixed a few more minor typos
* added command to remove all .coverageXX files after the tests commands exit
* added a separate recipe to remove all the coverage files
* minor bug fix
* remove __init__.py files from scenarios and examples modules so that they are removed from python installation package or pip
* Revert "remove __init__.py files from scenarios and examples modules so that they are removed from python installation package or pip"
This reverts commit bdf80e02
* remove __init__.py file from scenarios module so that it is removed from python installation package or pip
* rename the __init__.py file to argument_parser.py for examples folder
* renamed README_pypi.md
* Add social vehicles controlled by custom policy through bubbles (#793)
* Add ability to include bubbles in scenarios
* Add 'bubbles' to task configs
* Add stops test
* Add bubbles test
* Refactor stops implementation in generate_scenarios.py
* Refactor stops generation
* Add type hints and docstrings
* Remove stops from default bubble scenarios
* Add __init__.py to tests/tune/ (#840)
* Fix README typos in ULTRA (#764)
* Fix typos in ultra/README.md
* Fix typo in the citation
* Fix headless argument behaviour in ULTRA (#737)
* Fix headless argument in ULTRA scripts
* Change headless flag to behave like SMARTS
* Control number of episodes in ULTRA tests (rllib and train) (#739)
* Make evaluations run in parallel to training
* Add rollout_fragment_length and max_episode_steps to rllib
* Add new flags to documentation
* Fix flag in example
* Ensure evaluation is not run in test_train.py
* Check if log_dir doesn't exist in test_train.py
* Fix typo in argument and set eval_episodes to 0
* Check if not exists for paths
* Fix formatting
* Update evaluate and train to evaluate per episode (#639)
* Update evaluate and train to eval per episode
* Fix tests and change normalization
* Fix formatting
* Record episode for train/eval at the same time
* Train performance averages last eval_rate episodes
* Add gap_mode and calculate generalization gap
* Enable explore during eval for better comparison
* Fix formatting
* Fix averaging in record_episode
* Only average scalars in record_episode
* Check for scalar when calculating gap
* Fix formatting
* Fix bugs introduced by merge
* Fix calculate_gap
* Fix averaging over episodes
* Fix formatting
* Check eval_episodes is 0 before evaluation
* Evaluate on train and test without exploration
* Make train/test occur in one ray.get
* Remove episode_count
* Remove episode_count from tests
* Remove averaging over training episodes
* Restructure evaluation_check with eval_mode = False
* Fix formatting
* try split ci test method
* Check for valid eval_episodes inside evaluation_check
* Removed averaging feature of record_episode
* Fix formatting
Co-authored-by: Jenish Patel <[email protected]>
* Merge with ultra-rllib-speedup-tests
* Rename evaluation_task_id for training
* Simplify argument to ray.wait(...)
* Remove print statements
* Fix defaults
* Fix eval-rate in docs
* Initial changes (#744)
Co-authored-by: christianjans <[email protected]>
Co-authored-by: Jenish Patel <[email protected]>
Co-authored-by: christianjans <[email protected]>
* Bump 0.4.15 -> 0.4.16
* Make format
* Update missing version numbers
* switched import statement to relative import
* bug fix
* made a new bin folder and moved gen_header.sh and header_test.sh to that folder
* made a new etc folder and moved the third party folder into it
* moved tools folder to etc folder
* moved extras folder to etc
* moved tools folder to examples folder
* moved benchmark folder to etc folder
* moved benchmark folder to cases folder and updated import statements
* updated Makefile with proposed changes
* moved install_deps.sh to etc/setup
* updated Makefile based on changes proposed
* moved docker files to etc/docker folder
* fixed script paths in Makefile
* fixed script paths in ci files
* bug fix
* bug fix
* added recipe to remove coverageXXX and coverage.XXX files in Makefile
* added README.pypi.md to etc/setup
* fixed paths for dockerfile and made path changes in README.md
* updated CHANGELOG.md
* added __init__.py to scenarios and examples and removed them from pip installation in setup.py
* updated based on proposed changes
* revert back to absolute paths
* added __init__.py
* update CHANGELOG.md
* new Imitation action space (#854)
* first pass at new Imitation action space
also fixed bug for non-dynamic vehicles not getting actions
* Only do non-dynamic actions for agents not owned by a Provider
* use actual mass from chassis instead of hardcoding
* added hack to allow setting the initial vehicle speed
* don't use Sumo here by default
* added CHANGELOG entries
* update from review: normalize by 4-wheel torque
* ULTRA Improve high density traffic (#783)
* experiment with different begin time functions
* fixed map position in gif
* added legends
* WIP: experimenting with different combinations of traffic settings
* save begin time settings
* added more maps to high-density task, constrict stopwatcher begin time and t-intersection distribution improved from high-density traffic
* formatted
* clean up
* final traffic settings saved
* added mid-density to compare, modified high-density distribution
* simplified the high density traffic to lessen congestion
* more tuning
* more tuning
* added video analysis test
* clean up
* Apply suggestions from code review
Co-authored-by: christianjans <[email protected]>
* changes from code review
* comment changes
* slight mod to traffic distribution & relaxed stopwatcher begin times
* Update begin_time_init_funcs.py
Co-authored-by: christianjans <[email protected]>
* remove debugging levels
* small fix
Co-authored-by: christianjans <[email protected]>
* Remove extra comma in ULTRA citation (#849)
* Remove extra comma in README citation
* Use period instead of comma
* revert back the file to prevent ci-test from failing for now
* bug fix
* reproducing bug
* reproducing bug
* bug fix
* Fixed the bug by turning off the wrong_way event when vehicle goes into an intersection.
Updated CHANGELOG.md.
* Traffic History Dones (#827)
* better handling of Dones for traffic history
- detect vehicles dropping out of history
- added ExitGoal for imitation learning agents
* Updated CHANGELOG.
* back out deprecation fix
* allow for collisions to be reported in Events even if goal reached
* Changed ExitGoal to TraverseGoal.
Backed out semantic change to done Events.
(feedback from dicussions)
* type hints
* updates from review & formatting
* merge
* Multiple replacement of history vehicles (#836)
* First pass at multi-agent IL example
* choose only overlapping vehicles to replace
also, refactored TrafficHistory to clean up database queries
* moved TraffiCHistory class to its own file
* minor none check for replaced history vehicles
* refactored overlapping_choice into TrafficHistory
* updates from review
* allow -k as a shortcut for --replacements-per-episode
* formatting
* added some type hints
* more type hints
* updates from review
* updates from review
* formatting
* more type hints
* fixed weird bug in last PR
* updated based on changes proposed
* updated based on changes proposed
* updated based on changes proposed
* removed the additional files to reproduce the bug
* refactoring
* reformatting sensors.py
* reformatted sensors.py through black
* updated CHANGELOG.md
* added max-steps arg (#861)
* Fix permission error.
* moved the script etc/setup folder
* ULTRA Simple level (#857)
* added simple level
* classified simple levels, position offsets
Classified simple levels into v0, v1, v2. Move the position offsets to route distribution
* small modification
* pos_offset not mandatory
* tweaked distribution flags & formatted
* moved cross intersection types to test section in levels
* bubbles flags added
* renamed simple distribution, added a more general simple level
* reinstated blocks distribution
* Apply suggestions from code review
Co-authored-by: christianjans <[email protected]>
* moved debugging levels from task1 -> taskX
Co-authored-by: christianjans <[email protected]>
* update based on proposed changes
* path fix
* reformatted file using black
* renamed etc folder to conf, moved README.pypi.md to utils/setup and supervisord.conf to examples
* renamed cases to baselines
* removed CONTRIBUTING.md from docs and updated the top level one
* fixed CI test path
* os path fix
* reformatting file using black
* Bugfix memory issues (#852)
* Cap threadpoolexecutor virtual memory growth
* Fix sumo memory growth
* Make format
* Apply suggestions
* Update reset of sumo to every 50
* Add fixes to changelog
* TODO to remove fix when memory growth fixed
* revert back to 4 grpc connection workers
* Make format
* Bugfix remove unused `make` pview (#845)
* Remove pview for unused .egg files
* Update changelog
* refactored repeating code to a class method
* updated CHANGELOG.md
* reformatted code
* removed unit test file from another branch
* ULTRA Update existing maps (#868)
* update existing maps
* formatted
* changes from review
* only observe cars for imitation learning (#874)
* only observe cars for imitation learning data collection
* added type hint
* revert to absolute paths
* prevent pybullet from updating during setup with python3.8
* updated CONTRIBUTING.md
* resolve merge issue
* ULTRA Add medium level (#869)
* added medium level
* adjusted traffic distr. in medium level
* removed curvy_t intersection type
* updated simple level
moved existing simple level into taskX
* cleaned up taskX config
* changed level's total
* Update ultra/ultra/scenarios/taskX/config.yaml
Co-authored-by: christianjans <[email protected]>
* updated simple level
Co-authored-by: christianjans <[email protected]>
* updated CHANGELOG.md
* removed unwanted packages
* updated requirements.txt
* updated CHANGELOG.md
* Changes based on reviews
* Created a seperate setup.py for benchmark to remove opencv-python from SMARTS in general.
* updated requirements.txt
* updated requirements.txt
* updated requirements.txt
* examples and bug fixes for imitation learning (#878)
* examples and bug fixes for imitation learning
* added PR number to CHANGELOG
* took out debugging hack
* use BoxChassis (kinematics only, no physics) by default for Imitation action space
* modified placeholder agent to replay from saved pkl files.
+-get starting speed for mission, bug fixes
* formatting
* remove unnecessary dependencies
* better rounding for history time query
* do collision processing for non-dynamic action spaces too
* fixed overzelous removal of provider type check + updates from review
* added a few more type hints
* reverted more over-zealousness re provider merging
* fixed minor bug for when speed==0.
* updates from review: better timestep_sec rounding
* backed out Observation change + misc updates from review
* re-compute traffic history speeds based on actual positions
* Moved speed re-computation to genhistories to get out of step loop.
- use next pos instead of prev pos in speed computation
Fixed minor bug with obs_time hack.
* don't check position on first step
* enforce vehicle history limit to cars
* fix for isclose() near 0
* move filtering by position to the end of genhistories (so all are used in smoothing stuff for edge effects)
* change back to scalar acceleration for Imitation action space
* formatting
* use current and next pos to compute history speed
* record and save the first observation (prior to step) too
* fixed history replay 1-off timestep issue
also added mission start adjustment hack for front bumper
* ULTRA add `--durations` flag to ULTRA CI tests (#885)
* added durations flag
* test pypi ultra test
* minor name fix
* history agent vehicle sizing (#886)
* allow traffic history agent vehicles' sizes to be set
* simplified controller calculations (should not change them)
* oops
* use angular_velocity for position updates too
* use current angular_velocity instead of next
* reverted angular_velocity correction to position in controller
also fixed bug to prevent stepping pybullet twice
* Refactor Waypoints (#872)
* waypoints/lanepoits refactor: first pass
* incremental
* move lanepoints into sumo_road_network
* moved Waypoints (back) into MissionPlanner
* added some type hints
* minor cleanup
* updated comment
* added WaypointsCache and other minor performance optimizations
* debugged waypoints cache
* removed no-longer used method
* updates from review
* fixed typos
* reduced lane-following lookahead to 10
* revert lane_following_controller lookahead reduction
* added CHANGELOG entry
* update per review: fixed hash for LinkedLanePoints
* added more type hints per review
* remove start/end offset from simple level (#891)
* Proper shutdown of RemoteAgentBuffer after code crash (#822)
* Removed atexit destroy in RemoteAgentBuffer.
* fix internal holes in sumo road network
* Updated CHANGELOG.md
* code reformatting
* code reformatting
* comments
* fixed all holes that were at extremely sharp turn (almost perpendicular).
* traffic-history data speed and heading tweaks. (#896)
* re-calculate speeds and headings based on position changes for both NGSIM and INTERACTION datasets
* comment
* ULTRA Update `docs/setup.md` (#903)
* updated setup.md
* remove manual black installation step
* added install_deps.sh into ultra
* Update ultra/docs/setup.md
Co-authored-by: christianjans <[email protected]>
* empty commit
Co-authored-by: christianjans <[email protected]>
* added an experiment utility file to replace context of supervisord.conf
* reformatting
* removed supervisord from dependencies and requirements
* Ensured unique deque objects were used in framestack. (#894)
* Updated README.md
* updated CHANGELOG.md
* updated requirements.txt
* updated requirements.txt
* updated requirements.txt
* resolving merge conflict
* resolving merge conflict
* resolving merge conflict
* path fixes
* path fixes
* Fix args count error caused by `websocket` (#906)
* Fix vargs error sometimes caused by websocket
* Change vargs to 2 additional defaults
* Add fix to changelog
* ignore options not defined in the command
* reformatting
* open new web browser tab automatically
* reformatting
* added scl zoo command to installl agents at the specified paths
* Updated CHANGELOG.md
* update tensorflow for Rl_Agent
* Update getting_started.md (#925)
* update tensorflow for Rl_Agent
* added test file for rl-agent
* updated the wheel file for rl-agent installation
* updated based on reviews
* added another option to change port
* Small fix to docs/getting_started.md (#931)
* cleanup
* reformatting and more detail to error output
* reformatting and more detail to error output
* bump up the version number, update scenarios for rl-agent
* updated wheel file for rl-agent
* updated CHANGELOG.md
* updated README.md and cleanup the environment before installing the agents.
* updated README.md and cleanup the environment before installing the agents.
* Add flag to disable mission shuffling when generating scenarios in ULTRA (#927)
* Add option to generate scenarios without shuffling missions
* Add comments to mission shuffling tests
* Fix comments' flag names
* Warning if port passed without starting envision.
* Warning if port passed without starting envision.
* remove argument parser (#935)
* refactoring
* revert changes
* bug fix
* bug fix
* ULTRA Migrate from step-based to episode-based sampling (#932)
* change agent_itr to episode.index
* formatted
* recording data episodically in tune.py and train.py
* change recording_step inside evaluate_saved_model()
* added episode indices test
* Update ultra/tests/test_evaluate.py
Co-authored-by: christianjans <[email protected]>
* Update ultra/tests/test_evaluate.py
Co-authored-by: christianjans <[email protected]>
Co-authored-by: christianjans <[email protected]>
* replace the panda3d.Quat.xform method to remove dependency from panda3D package
* wrap the import statements and ShowBaseInstance class in try block and warn user if they have not installed the [render] dependencies.
* make sure the CI tests install dependencies before rendering camera observations
* remove panda3d from dependencies in setup.py
* Updated CHANGELOG.md
* ULTRA Run tests in forked subprocesses (#937)
* forked train test
* remove backslash
* try forking evaluate test
* small fix
* small fix
* small fix
* comment added
* update documentation about rendering and camera based observations
* moved helper functions to utils/math
* reformat the try block to raise RendererException with warning message. Comments.
* rename the dependency name from render to camera-obs
* Multi-agent FrameStack wrapper (#916)
* Added multi-agent FrameStack wrapper and test.
* cleaner way to make renderer optional
* formatting
* Refactor ULTRA adapter to support benchmarking (#871)
* Initial ideas for refactored adapter
* Define the reward and observation adapters
* Finish basic adapter types in adapter.py
* Get PPO baseline to run
* Get SAC baseline to run
* Get TD3 baseline to run
* Get RLlib training to work
* Get DQN baseline to run
* Get BDQN baseline to run
* Get ULTRA Tune to run
* Pass ULTRA CI tests
* Format the code
* Move adapters to own directory
* Remove original adapter and state preprocessors
* Add discrete action Gym space
* Implement default image observation adapter function
* Simplify required_interface_fromtypes function
* Initialize ultra_scores from enum type
* Comment constants in default vector and reward
* Change adapter CI test to use new adapters
* Use seed from parameters for social vehicle config in RLlib
* Add docstrings to adapters
* Convert TODO regarding ULTRA score to NOTE in ULTRA environments
* Fix small logic errors in default_observation_image_adapter
* Apply small changes from review
* Create deepcopy of observation before performing vector adaptation
* Add initial documentation for default adapters
* Add reason for sorting social vehicles by distance in adapters.md
* Keep consistent line length in adapters.md
* Add comments to image adapter constants
* Edit docstring of image adapter function
* Change image observation adapter to produce a 3D array
* Test adapter's Gym space in adapter tests
* Change gray-scale weighting to (0.1, 0.8, 0.1)
* Fix 'enironment' typo and describe the_environment_reward in docs/adapters.md
* Keep variable name of the rewards obtained from the environment consistent
* User assertIn instead of assertTrue for testing containing in test_adapter.py
* Add default info adapter to remove reward adapter's NeighborhoodVehicles dependency (#902)
* Initial changes
* Format the code
* Remove ultra_scores from the ULTRA environment
* Add info adapter documentation
* Add info adapter test
* Move shared adapter constants a common file
* Make trimming of extra social vehiccles explicit
* Replace RLlib environment info adaptation with default info adapter in agent
* minor bug fix. Reformatting
* Say which tests are run in ULTRA CI tests rather than use `--ignore` (#941)
* Explicitly say which tests are run in heavy and light
* Fix 'analysys' spelling mistake
* ULTRA Minimalize `train.py` script (#904)
* Initial ideas for refactored adapter
* Define the reward and observation adapters
* Finish basic adapter types in adapter.py
* Get PPO baseline to run
* Get SAC baseline to run
* Get TD3 baseline to run
* Get RLlib training to work
* Get DQN baseline to run
* Get BDQN baseline to run
* Get ULTRA Tune to run
* Pass ULTRA CI tests
* Format the code
* Move adapters to own directory
* Remove original adapter and state preprocessors
* Add discrete action Gym space
* Implement default image observation adapter function
* Simplify required_interface_fromtypes function
* Initialize ultra_scores from enum type
* Comment constants in default vector and reward
* Change adapter CI test to use new adapters
* Use seed from parameters for social vehicle config in RLlib
* Add docstrings to adapters
* Convert TODO regarding ULTRA score to NOTE in ULTRA environments
* Fix small logic errors in default_observation_image_adapter
* Apply small changes from review
* Create deepcopy of observation before performing vector adaptation
* Add initial documentation for default adapters
* save work
* moved parsing outside of main
* made build_agent() public
* empty commit
* added max_steps args
* empty commit
* small fix
* changes from code review
* small fix
* bypass hard coded file name
* clean up
Co-authored-by: christianjans <[email protected]>
* Add trajectory interpolation provider.
* Update scenario building documentation and arguments in ULTRA (#944)
* Fix scl scenario build command in docs
* added default value to pool_dir arg
* make path relative to base ultra dir
* update scenario README
* add logic clause to allow build_scenarios() function calls to not mandate using pool_dir argument
* Change pool_dir initialization in build_scenarios
Co-authored-by: Jenish Patel <[email protected]>
* Add frame stacking to ULTRA (#948)
* Initial changes
* Add initial environment documentation
* Fix ULTRA environment and adapter test to pass tests
* Clean up the ULTRA environment and environment test
* Add note to RLlib training about SMARTS observations adaptation
* Update ULTRA environment documentation
* update MANIFEST.in (#956)
* fix multi-display envision
* prevent envision to reconnect to a simulation every 3 second
* prevent envision to reconnect to a simulation every 3 second
* prevent envision to reconnect to a simulation every 3 second. bug fixes.
* Updated CHANGELOG.md
* Build and Update the envision distribution based on changes.
* Bug fixes. Major reformatting for .js files.
* build and update map
* fix envision to check for a new simulation every 3 seconds and not redirect when switched to a multi-instance display.
* build and update the distribution. Reformatting.
* typo fix
* changes based on reviews
* fork all light base tests and observe duration (#967)
* ULTRA Evaluate specific models (#915)
* refactor existing evaluate_saved_models
* fixed bug
* updated evaluation process, fixed tune test issue
* Update getting_started.md
* updated getting_started.md documentation
* clean up
* added exceptions
* small fix
Co-authored-by: christianjans <[email protected]>
Co-authored-by: christianjans <[email protected]>
Co-authored-by: christianjans <[email protected]>
* ULTRA baselines with new adapters (#958)
* Initial ideas for refactored adapter
* Define the reward and observation adapters
* Finish basic adapter types in adapter.py
* Get PPO baseline to run
* Get SAC baseline to run
* Get TD3 baseline to run
* Get RLlib training to work
* Get DQN baseline to run
* Get BDQN baseline to run
* Get ULTRA Tune to run
* Pass ULTRA CI tests
* Format the code
* Move adapters to own directory
* Remove original adapter and state preprocessors
* Add discrete action Gym space
* Implement default image observation adapter function
* Simplify required_interface_fromtypes function
* Initialize ultra_scores from enum type
* Comment constants in default vector and reward
* Change adapter CI test to use new adapters
* Use seed from parameters for social vehicle config in RLlib
* Add docstrings to adapters
* Convert TODO regarding ULTRA score to NOTE in ULTRA environments
* Fix small logic errors in default_observation_image_adapter
* Apply small changes from review
* Create deepcopy of observation before performing vector adaptation
* Add initial documentation for default adapters
* Add reason for sorting social vehicles by distance in adapters.md
* Keep consistent line length in adapters.md
* Add comments to image adapter constants
* Edit docstring of image adapter function
* Change image observation adapter to produce a 3D array
* Initial changes
* Fix bug in image replay buffer dataset
* Add initial replay buffer test
* Clean up replay buffer test
* Make CNNs exclusively process images
* Remove BDQN's explore.py and network.py
* Remove extra import of DQNWithSocialEncoder
* ULTRA Sanity check on baselines (#965)
* added test to train all baselines
* formatted
* added evaluation to baseline tests
* fix agent interface numbering (#978)
Co-authored-by: Rutvik Gupta <[email protected]>
* fixed genhistories bug introduced in PR #896.
* Graceful shutdown of zoo when daemon process terminates abruptly (#924)
* Update version number
Co-authored-by: Jeffer Jingfei Peng <[email protected]>
Co-authored-by: Stephen Hockema <[email protected]>
Co-authored-by: adai <[email protected]>
Co-authored-by: sah-huawei <[email protected]>
Co-authored-by: JenishPatel99 <[email protected]>
Co-authored-by: christianjans <[email protected]>
Co-authored-by: Rutvik Gupta <[email protected]>
Co-authored-by: Rutvik Gupta <[email protected]>
Co-authored-by: Alex Lewandowski <[email protected]>
Co-authored-by: christianjans <[email protected]>
Co-authored-by: Jenish Patel <[email protected]>
Co-authored-by: Adaickalavan Meiyappan 84166141 <[email protected]>
Co-authored-by: guptarut <https://markus.cs.teach.edu/git/csc209-2020-01/guptarut>
Co-authored-by: Valax Kong <[email protected]>
