* Ditch most of the seeding.py and replace np_random with the numpy default_rng. Let's see if tests pass
* Updated a bunch of RNG calls from the RandomState API to Generator API
* black; didn't expect that, did ya?
* Undo a typo
* blaaack
* More typo fixes
* Fixed setting/getting state in multidiscrete spaces
* Fix typo, fix a test to work with the new sampling
* Correctly (?) pass the randomly generated seed if np_random is called with None as seed
* Convert the Discrete sample to a python int (as opposed to np.int64)
* Remove some redundant imports
* First version of the compatibility layer for old-style RNG. Mainly to trigger tests.
* Removed redundant f-strings
* Style fixes, removing unused imports
* Try to make tests pass by removing atari from the dockerfile
* Try to make tests pass by removing atari from the setup
* Try to make tests pass by removing atari from the setup
* Try to make tests pass by removing atari from the setup
* First attempt at deprecating `env.seed` and supporting `env.reset(seed=seed)` instead. Tests should hopefully pass but throw up a million warnings.
* black; didn't expect that, didya?
* Rename the reset parameter in VecEnvs back to `seed`
* Updated tests to use the new seeding method
* Removed a bunch of old `seed` calls.
Fixed a bug in AsyncVectorEnv
* Stop Discrete envs from doing part of the setup (and using the randomness) in init (as opposed to reset)
* Add explicit seed to wrappers reset
* Remove an accidental return
* Re-add some legacy functions with a warning.
* Use deprecation instead of regular warnings for the newly deprecated methods/functions
This commit adds the [flappy-bird-gym](https://github.com/Talendar/flappy-bird-gym) package to `third_party_environments.md`. It's the first result on Google when searching for "flappy bird gym environment".