Chex 1.86 and TF Keras - Githubissues

Runs without Error

git clone <this-repo>
cd <repo-home>
conda create -n mpc_main python=3.10
conda activate mpc_main
SYSTEM_VERSION_COMPAT=0 pip install dmlab2d

First Error pip install -e .

ERROR: Could not find a version that satisfies the requirement tensorflow==2.11.1 (from dm-meltingpot) (from versions: 2.13.0rc0, 2.13.0rc1, 2.13.0rc2, 2.13.0, 2.13.1, 2.14.0rc0, 2.14.0rc1, 2.14.0, 2.14.1, 2.15.0rc0, 2.15.0rc1, 2.15.0, 2.15.1, 2.16.0rc0, 2.16.1) ERROR: No matching distribution found for tensorflow==2.11.1

First Fix In setup.py line 121 'tensorflow==2.11.1', to 'tensorflow>=2.13.0',

Second Error sh ray_patch.sh

ERROR: Attempting to patch Failed to import TF-Keras. Please note that TF-Keras is not installed by default when you install TensorFlow Probability. This is so that JAX-only users do not have to install TensorFlow or TF-Keras. To use TensorFlow Probability with TensorFlow, please install the tf-keras or tf-keras-nightly package. This can be be done through installing the tensorflow-probability[tf] extra. /Users/camerontice/miniconda3/envs/mpc_main/lib/python3.10/site-packages/ray/rllib/policy/sample_batch.py

Fix pip install 'tensorflow-probability[tf]'

Third Error python baselines/train/run_ray_train.py

Traceback (most recent call last): File "/Users/camerontice/Desktop/meltingpot/test2/MARL-Melting-pot/baselines/train/run_ray_train.py", line 10, in from configs import get_experiment_config File "/Users/camerontice/Desktop/meltingpot/test2/MARL-Melting-pot/baselines/train/configs.py", line 1, in from meltingpot import substrate ... File "/Users/camerontice/miniconda3/envs/mpc_main/lib/python3.10/site-packages/chex/_src/pytypes.py", line 54, in PRNGKey = jax.random.KeyArray File "/Users/camerontice/miniconda3/envs/mpc_main/lib/python3.10/site-packages/jax/_src/deprecations.py", line 54, in getattr raise AttributeError(f"module {module!r} has no attribute {name!r}") AttributeError: module 'jax.random' has no attribute 'KeyArray'

Fix setup.py line 109 'chex<0.1.81', to 'chex==0.1.86'

Unresolved Error python baselines/train/run_ray_train.py --num_workers 4 --num_gpus 0 --local --no-tune --algo ppo --framework torch --exp clean_up --seed 42 --results_dir my_results --logging INFO --wandb False --downsample 8

ValueError: No default encoder config for obs space=Dict('COLLECTIVE_REWARD': Box(-inf, inf, (), float64), 'READY_TO_SHOOT': Box(-inf, inf, (), float64), 'RGB': Box(0, 255, (11, 11, 3), uint8)), lstm=False and attention=False found.

Full Traceback for Final Error (mpc_main) camerontice@Camerons-Laptop MARL-Melting-pot % python baselines/train/run_ray_train.py --num_workers 4 --num_gpus 0 --local --no-tune --algo ppo --framework torch --exp clean_up --seed 42 --results_dir my_results --logging INFO --wandb False --downsample 8

2024-04-22 11:42:51,127 WARNING deprecation.py:50 -- DeprecationWarning: DirectStepOptimizer has been deprecated. This will raise an error in the future! 2024-04-22 11:42:51,370 - DEBUG - Popen(['git', 'version'], cwd=/Users/camerontice/Desktop/meltingpot/test2/MARL-Melting-pot, stdin=None, shell=False, universal_newlines=False) 2024-04-22 11:42:51,383 - DEBUG - Popen(['git', 'version'], cwd=/Users/camerontice/Desktop/meltingpot/test2/MARL-Melting-pot, stdin=None, shell=False, universal_newlines=False) 2024-04-22 11:42:51,398 - DEBUG - Trying paths: ['/Users/camerontice/.docker/config.json', '/Users/camerontice/.dockercfg'] 2024-04-22 11:42:51,398 - DEBUG - Found file at path: /Users/camerontice/.docker/config.json 2024-04-22 11:42:51,398 - DEBUG - Found 'credsStore' section 2024-04-22 11:42:51,432 - DEBUG - [Tracing] Create new propagation context: {'trace_id': '22b069ba99ac4023be6cf6fd3f7f1aaa', 'span_id': '93f5b62e623a58dd', 'parent_span_id': None, 'dynamic_sampling_context': None} Running trails with the following arguments: Namespace(num_workers=4, num_gpus=0, local=True, no_tune=True, algo='ppo', framework='torch', exp='clean_up', seed=42, results_dir='my_results', logging='INFO', wandb=True, downsample=True, as_test=False) 2024-04-22 11:42:51,484 - DEBUG - Attempting to acquire lock 14508453040 on /tmp/ray/session_2024-04-22_11-42-51_484519_88590/ports_by_node.json.lock 2024-04-22 11:42:51,485 - DEBUG - Lock 14508453040 acquired on /tmp/ray/session_2024-04-22_11-42-51_484519_88590/ports_by_node.json.lock 2024-04-22 11:42:51,485 - DEBUG - Attempting to release lock 14508453040 on /tmp/ray/session_2024-04-22_11-42-51_484519_88590/ports_by_node.json.lock 2024-04-22 11:42:51,485 - DEBUG - Lock 14508453040 released on /tmp/ray/session_2024-04-22_11-42-51_484519_88590/ports_by_node.json.lock 2024-04-22 11:42:51,485 - DEBUG - Attempting to acquire lock 14508453568 on /tmp/ray/session_2024-04-22_11-42-51_484519_88590/ports_by_node.json.lock 2024-04-22 11:42:51,485 - DEBUG - Lock 14508453568 acquired on /tmp/ray/session_2024-04-22_11-42-51_484519_88590/ports_by_node.json.lock 2024-04-22 11:42:51,485 - DEBUG - Attempting to release lock 14508453568 on /tmp/ray/session_2024-04-22_11-42-51_484519_88590/ports_by_node.json.lock 2024-04-22 11:42:51,485 - DEBUG - Lock 14508453568 released on /tmp/ray/session_2024-04-22_11-42-51_484519_88590/ports_by_node.json.lock 2024-04-22 11:42:51,485 - DEBUG - Attempting to acquire lock 14508453040 on /tmp/ray/session_2024-04-22_11-42-51_484519_88590/ports_by_node.json.lock 2024-04-22 11:42:51,485 - DEBUG - Lock 14508453040 acquired on /tmp/ray/session_2024-04-22_11-42-51_484519_88590/ports_by_node.json.lock 2024-04-22 11:42:51,485 - DEBUG - Attempting to release lock 14508453040 on /tmp/ray/session_2024-04-22_11-42-51_484519_88590/ports_by_node.json.lock 2024-04-22 11:42:51,485 - DEBUG - Lock 14508453040 released on /tmp/ray/session_2024-04-22_11-42-51_484519_88590/ports_by_node.json.lock 2024-04-22 11:42:51,485 - DEBUG - Attempting to acquire lock 14508450928 on /tmp/ray/session_2024-04-22_11-42-51_484519_88590/ports_by_node.json.lock 2024-04-22 11:42:51,485 - DEBUG - Lock 14508450928 acquired on /tmp/ray/session_2024-04-22_11-42-51_484519_88590/ports_by_node.json.lock 2024-04-22 11:42:51,486 - DEBUG - Attempting to release lock 14508450928 on /tmp/ray/session_2024-04-22_11-42-51_484519_88590/ports_by_node.json.lock 2024-04-22 11:42:51,486 - DEBUG - Lock 14508450928 released on /tmp/ray/session_2024-04-22_11-42-51_484519_88590/ports_by_node.json.lock /Users/camerontice/miniconda3/envs/mpc_main/lib/python3.10/subprocess.py:1796: RuntimeWarning: os.fork() was called. os.fork() is incompatible with multithreaded code, and JAX is multithreaded, so this will likely lead to a deadlock. self.pid = _posixsubprocess.fork_exec( /Users/camerontice/miniconda3/envs/mpc_main/lib/python3.10/subprocess.py:1796: RuntimeWarning: os.fork() was called. os.fork() is incompatible with multithreaded code, and JAX is multithreaded, so this will likely lead to a deadlock. self.pid = _posixsubprocess.fork_exec( 2024-04-22 11:42:53,056 INFO worker.py:1612 -- Started a local Ray instance. View the dashboard at 127.0.0.1:8265 2024-04-22 11:42:53,398 WARNING algorithm_config.py:2534 -- Setting exploration_config={} because you set _enable_rl_module_api=True. When RLModule API are enabled, exploration_config can not be set. If you want to implement custom exploration behaviour, please modify the forward_exploration method of the RLModule at hand. On configs that have a default exploration config, this must be done with config.exploration_config={}. The selected option is not tested. You may encounter issues if you use the baseline policy configurations with non-tested algorithms WARNING! No wandb API key found, running without wandb! /Users/camerontice/miniconda3/envs/mpc_main/lib/python3.10/site-packages/ray/air/config.py:803: UserWarning: Setting a RunConfig.local_dir is deprecated and will be removed in the future. If you are not using remote storage,set the RunConfig.storage_path instead. Otherwise, set theRAY_AIR_LOCAL_CACHE_DIR environment variable to control the local cache location. warnings.warn( 2024-04-22 11:42:53,628 INFO tune.py:666 -- [output] This will use the new output engine with verbosity 0. To disable the new output and use the legacy output engine, set the environment variable RAY_AIR_NEW_OUTPUT=0. For more information, please see https://github.com/ray-project/ray/issues/36949 2024-04-22 11:42:53,637 WARNING deprecation.py:50 -- DeprecationWarning: build_tf_policy has been deprecated. This will raise an error in the future! 2024-04-22 11:42:53,639 WARNING deprecation.py:50 -- DeprecationWarning: build_policy_class has been deprecated. This will raise an error in the future! 2024-04-22 11:42:53,656 WARNING algorithm_config.py:2534 -- Setting exploration_config={} because you set _enable_rl_module_api=True. When RLModule API are enabled, exploration_config can not be set. If you want to implement custom exploration behaviour, please modify the forward_exploration method of the RLModule at hand. On configs that have a default exploration config, this must be done with config.exploration_config={}. /Users/camerontice/miniconda3/envs/mpc_main/lib/python3.10/site-packages/gymnasium/spaces/box.py:127: UserWarning: WARN: Box bound precision lowered by casting to float32 logger.warn(f"Box bound precision lowered by casting to {self.dtype}") /Users/camerontice/miniconda3/envs/mpc_main/lib/python3.10/site-packages/gymnasium/utils/passive_env_checker.py:141: UserWarning: WARN: The obs returned by the reset() method was expecting numpy array dtype to be float32, actual type: float64 logger.warn( /Users/camerontice/miniconda3/envs/mpc_main/lib/python3.10/site-packages/gymnasium/utils/passive_env_checker.py:165: UserWarning: WARN: The obs returned by the reset() method is not within the observation space. logger.warn(f"{pre} is not within the observation space.") 2024-04-22 11:42:53,680 WARNING algorithm_config.py:2534 -- Setting exploration_config={} because you set _enable_rl_module_api=True. When RLModule API are enabled, exploration_config can not be set. If you want to implement custom exploration behaviour, please modify the forward_exploration method of the RLModule at hand. On configs that have a default exploration config, this must be done with config.exploration_config={}. ╭────────────────────────────────────────────────────────╮ │ Configuration for experiment clean_up │ ├────────────────────────────────────────────────────────┤ │ Search algorithm BasicVariantGenerator │ │ Scheduler FIFOScheduler │ │ Number of trials 1 │ ╰────────────────────────────────────────────────────────╯

View detailed results here: /Users/camerontice/Desktop/meltingpot/test2/MARL-Melting-pot/my_results/torch/clean_up To visualize your results with TensorBoard, run: tensorboard --logdir /Users/camerontice/Desktop/meltingpot/test2/MARL-Melting-pot/my_results/torch/clean_up

2024-04-22 11:42:53,799 WARNING algorithm_config.py:2534 -- Setting exploration_config={} because you set _enable_rl_module_api=True. When RLModule API are enabled, exploration_config can not be set. If you want to implement custom exploration behaviour, please modify the forward_exploration method of the RLModule at hand. On configs that have a default exploration config, this must be done with config.exploration_config={}. :job_id:01000000 :job_id:01000000 2024-04-22 11:42:53,824 WARNING worker.py:854 -- ray.get_gpu_ids() will always return the empty list when called from the driver. This is because Ray does not manage GPU allocations to the driver process. :task_name:bundle_reservation_check_func :task_name:bundle_reservation_check_func :actor_name:PPO :actor_name:PPO 2024-04-22 11:42:53,841 WARNING algorithm_config.py:2534 -- Setting exploration_config={} because you set _enable_rl_module_api=True. When RLModule API are enabled, exploration_config can not be set. If you want to implement custom exploration behaviour, please modify the forward_exploration method of the RLModule at hand. On configs that have a default exploration config, this must be done with config.exploration_config={}. 2024-04-22 11:42:53,841 WARNING algorithm_config.py:656 -- Cannot create PPOConfig from given config_dict! Property stdout_file__ not supported. :actor_name:RolloutWorker :actor_name:RolloutWorker /Users/camerontice/miniconda3/envs/mpc_main/lib/python3.10/site-packages/gymnasium/spaces/box.py:227: UserWarning: WARN: Casting input x to numpy array. logger.warn("Casting input x to numpy array.") 2024-04-22 11:42:54,995 WARNING algorithm_config.py:2534 -- Setting exploration_config={} because you set _enable_rl_module_api=True. When RLModule API are enabled, exploration_config can not be set. If you want to implement custom exploration behaviour, please modify the forward_exploration method of the RLModule at hand. On configs that have a default exploration config, this must be done with config.exploration_config={}. [2024-04-22 11:42:54,999 E 88590 9807680] core_worker.cc:1705: Pushed Error with JobID: 01000000 of type: task with message: ray::RolloutWorker.init() (pid=88590, ip=127.0.0.1, actor_id=cbf960f61968bb00ce1891d601000000, repr=<ray.rllib.evaluation.rollout_worker._modify_class..Class object at 0x3e6436c80>) File "/Users/camerontice/miniconda3/envs/mpc_main/lib/python3.10/site-packages/ray/rllib/evaluation/rollout_worker.py", line 525, in init self._update_policy_map(policy_dict=self.policy_dict) File "/Users/camerontice/miniconda3/envs/mpc_main/lib/python3.10/site-packages/ray/rllib/evaluation/rollout_worker.py", line 1727, in _update_policy_map self._build_policy_map( File "/Users/camerontice/miniconda3/envs/mpc_main/lib/python3.10/site-packages/ray/rllib/evaluation/rollout_worker.py", line 1838, in _build_policy_map new_policy = create_policy_for_framework( File "/Users/camerontice/miniconda3/envs/mpc_main/lib/python3.10/site-packages/ray/rllib/utils/policy.py", line 142, in create_policy_for_framework return policy_class(observation_space, action_space, merged_config) File "/Users/camerontice/miniconda3/envs/mpc_main/lib/python3.10/site-packages/ray/rllib/algorithms/ppo/ppo_torch_policy.py", line 49, in init TorchPolicyV2.init( File "/Users/camerontice/miniconda3/envs/mpc_main/lib/python3.10/site-packages/ray/rllib/policy/torch_policy_v2.py", line 92, in init model = self.make_rl_module() File "/Users/camerontice/miniconda3/envs/mpc_main/lib/python3.10/site-packages/ray/rllib/policy/policy.py", line 424, in make_rl_module marl_module = marl_spec.build() File "/Users/camerontice/miniconda3/envs/mpc_main/lib/python3.10/site-packages/ray/rllib/core/rl_module/marl_module.py", line 462, in build module = self.marl_module_class(module_config) File "/Users/camerontice/miniconda3/envs/mpc_main/lib/python3.10/site-packages/ray/rllib/core/rl_module/rl_module.py", line 315, in new_init previous_init(self, *args, **kwargs) File "/Users/camerontice/miniconda3/envs/mpc_main/lib/python3.10/site-packages/ray/rllib/core/rl_module/marl_module.py", line 58, in init super().init(config or MultiAgentRLModuleConfig()) File "/Users/camerontice/miniconda3/envs/mpc_main/lib/python3.10/site-packages/ray/rllib/core/rl_module/rl_module.py", line 307, in init self.setup() File "/Users/camerontice/miniconda3/envs/mpc_main/lib/python3.10/site-packages/ray/rllib/core/rl_module/marl_module.py", line 65, in setup self._rl_modules[module_id] = module_spec.build() File "/Users/camerontice/miniconda3/envs/mpc_main/lib/python3.10/site-packages/ray/rllib/core/rl_module/rl_module.py", line 104, in build module = self.module_class(module_config) File "/Users/camerontice/miniconda3/envs/mpc_main/lib/python3.10/site-packages/ray/rllib/core/rl_module/rl_module.py", line 315, in new_init previous_init(self, *args, *kwargs) File "/Users/camerontice/miniconda3/envs/mpc_main/lib/python3.10/site-packages/ray/rllib/core/rl_module/rl_module.py", line 315, in new_init previous_init(self, args, **kwargs) File "/Users/camerontice/miniconda3/envs/mpc_main/lib/python3.10/site-packages/ray/rllib/core/rl_module/torch/torch_rl_module.py", line 82, in init RLModule.init(self, *args, **kwargs) File "/Users/camerontice/miniconda3/envs/mpc_main/lib/python3.10/site-packages/ray/rllib/core/rl_module/rl_module.py", line 307, in init self.setup() File "/Users/camerontice/miniconda3/envs/mpc_main/lib/python3.10/site-packages/ray/rllib/algorithms/ppo/ppo_rl_module.py", line 20, in setup catalog = self.config.get_catalog() File "/Users/camerontice/miniconda3/envs/mpc_main/lib/python3.10/site-packages/ray/rllib/core/rl_module/rl_module.py", line 189, in get_catalog return self.catalog_class( File "/Users/camerontice/miniconda3/envs/mpc_main/lib/python3.10/site-packages/ray/rllib/algorithms/ppo/ppo_catalog.py", line 67, in init super().init( File "/Users/camerontice/miniconda3/envs/mpc_main/lib/python3.10/site-packages/ray/rllib/core/models/catalog.py", line 106, in init self.__post_init() File "/Users/camerontice/miniconda3/envs/mpc_main/lib/python3.10/site-packages/ray/rllib/core/models/catalog.py", line 135, in post_init self.encoder_config = self.get_encoder_config( File "/Users/camerontice/miniconda3/envs/mpc_main/lib/python3.10/site-packages/ray/rllib/core/models/catalog.py", line 249, in get_encoder_config tokenizer_config=cls.get_tokenizer_config( File "/Users/camerontice/miniconda3/envs/mpc_main/lib/python3.10/site-packages/ray/rllib/core/models/catalog.py", line 333, in get_tokenizer_config return cls.get_encoder_config( File "/Users/camerontice/miniconda3/envs/mpc_main/lib/python3.10/site-packages/ray/rllib/core/models/catalog.py", line 307, in get_encoder_config raise ValueError( ValueError: No default encoder config for obs space=Dict('COLLECTIVE_REWARD': Box(-inf, inf, (), float64), 'READY_TO_SHOOT': Box(-inf, inf, (), float64), 'RGB': Box(0, 255, (11, 11, 3), uint8)), lstm=False and attention=False found. at time: 1.7138e+09 2024-04-22 11:42:54,999 ERROR actor.py:970 -- Exception raised in creation task: The actor died because of an error raised in its creation task, ray::RolloutWorker.init() (pid=88590, ip=127.0.0.1, actor_id=cbf960f61968bb00ce1891d601000000, repr=<ray.rllib.evaluation.rollout_worker._modify_class..Class object at 0x3e6436c80>) File "/Users/camerontice/miniconda3/envs/mpc_main/lib/python3.10/site-packages/ray/rllib/evaluation/rollout_worker.py", line 525, in init__ self._update_policy_map(policy_dict=self.policy_dict) File "/Users/camerontice/miniconda3/envs/mpc_main/lib/python3.10/site-packages/ray/rllib/evaluation/rollout_worker.py", line 1727, in _update_policy_map self._build_policy_map( File "/Users/camerontice/miniconda3/envs/mpc_main/lib/python3.10/site-packages/ray/rllib/evaluation/rollout_worker.py", line 1838, in _build_policy_map new_policy = create_policy_for_framework( File "/Users/camerontice/miniconda3/envs/mpc_main/lib/python3.10/site-packages/ray/rllib/utils/policy.py", line 142, in create_policy_for_framework return policy_class(observation_space, action_space, merged_config) File "/Users/camerontice/miniconda3/envs/mpc_main/lib/python3.10/site-packages/ray/rllib/algorithms/ppo/ppo_torch_policy.py", line 49, in init TorchPolicyV2.init( File "/Users/camerontice/miniconda3/envs/mpc_main/lib/python3.10/site-packages/ray/rllib/policy/torch_policy_v2.py", line 92, in init model = self.make_rl_module() File "/Users/camerontice/miniconda3/envs/mpc_main/lib/python3.10/site-packages/ray/rllib/policy/policy.py", line 424, in make_rl_module marl_module = marl_spec.build() File "/Users/camerontice/miniconda3/envs/mpc_main/lib/python3.10/site-packages/ray/rllib/core/rl_module/marl_module.py", line 462, in build module = self.marl_module_class(module_config) File "/Users/camerontice/miniconda3/envs/mpc_main/lib/python3.10/site-packages/ray/rllib/core/rl_module/rl_module.py", line 315, in new_init previous_init(self, *args, **kwargs) File "/Users/camerontice/miniconda3/envs/mpc_main/lib/python3.10/site-packages/ray/rllib/core/rl_module/marl_module.py", line 58, in init super().init(config or MultiAgentRLModuleConfig()) File "/Users/camerontice/miniconda3/envs/mpc_main/lib/python3.10/site-packages/ray/rllib/core/rl_module/rl_module.py", line 307, in init self.setup() File "/Users/camerontice/miniconda3/envs/mpc_main/lib/python3.10/site-packages/ray/rllib/core/rl_module/marl_module.py", line 65, in setup self._rl_modules[module_id] = module_spec.build() File "/Users/camerontice/miniconda3/envs/mpc_main/lib/python3.10/site-packages/ray/rllib/core/rl_module/rl_module.py", line 104, in build module = self.module_class(module_config) File "/Users/camerontice/miniconda3/envs/mpc_main/lib/python3.10/site-packages/ray/rllib/core/rl_module/rl_module.py", line 315, in new_init previous_init(self, *args, kwargs) File "/Users/camerontice/miniconda3/envs/mpc_main/lib/python3.10/site-packages/ray/rllib/core/rl_module/rl_module.py", line 315, in new_init previous_init(self, *args, *kwargs) File "/Users/camerontice/miniconda3/envs/mpc_main/lib/python3.10/site-packages/ray/rllib/core/rl_module/torch/torch_rl_module.py", line 82, in init RLModule.init(self, args, kwargs) File "/Users/camerontice/miniconda3/envs/mpc_main/lib/python3.10/site-packages/ray/rllib/core/rl_module/rl_module.py", line 307, in init self.setup() File "/Users/camerontice/miniconda3/envs/mpc_main/lib/python3.10/site-packages/ray/rllib/algorithms/ppo/ppo_rl_module.py", line 20, in setup catalog = self.config.get_catalog() File "/Users/camerontice/miniconda3/envs/mpc_main/lib/python3.10/site-packages/ray/rllib/core/rl_module/rl_module.py", line 189, in get_catalog return self.catalog_class( File "/Users/camerontice/miniconda3/envs/mpc_main/lib/python3.10/site-packages/ray/rllib/algorithms/ppo/ppo_catalog.py", line 67, in init super().init( File "/Users/camerontice/miniconda3/envs/mpc_main/lib/python3.10/site-packages/ray/rllib/core/models/catalog.py", line 106, in init self.post_init() File "/Users/camerontice/miniconda3/envs/mpc_main/lib/python3.10/site-packages/ray/rllib/core/models/catalog.py", line 135, in __post_init self.encoder_config = self.get_encoder_config( File "/Users/camerontice/miniconda3/envs/mpc_main/lib/python3.10/site-packages/ray/rllib/core/models/catalog.py", line 249, in get_encoder_config tokenizer_config=cls.get_tokenizer_config( File "/Users/camerontice/miniconda3/envs/mpc_main/lib/python3.10/site-packages/ray/rllib/core/models/catalog.py", line 333, in get_tokenizer_config return cls.get_encoder_config( File "/Users/camerontice/miniconda3/envs/mpc_main/lib/python3.10/site-packages/ray/rllib/core/models/catalog.py", line 307, in get_encoder_config raise ValueError( ValueError: No default encoder config for obs space=Dict('COLLECTIVE_REWARD': Box(-inf, inf, (), float64), 'READY_TO_SHOOT': Box(-inf, inf, (), float64), 'RGB': Box(0, 255, (11, 11, 3), uint8)), lstm=False and attention=False found.

SoyGema / MARL-Melting-pot

Chex 1.86 and TF Keras #7