Bump gym dep to 0.24

python/requirements/ml/requirements_rllib.txt

@@ -4,7 +4,7 @@
 # ---------------------
 # Atari
 autorom[accept-rom-license]
-gym>=0.21.0,<0.24.0; python_version >= '3.7'
+gym>=0.21.0,<0.24.1; python_version >= '3.7'
 gym[atari]==0.19.0; python_version < '3.7'
 # Kaggle envs.
 kaggle_environments==1.7.11

release/long_running_distributed_tests/app_config.yaml

@@ -7,7 +7,7 @@ python:
   pip_packages:
     - pytest
     - awscli
-    - gym>=0.21.0,<0.24.0
+    - gym>=0.21.0,<0.24.1
   conda_packages: []
 
 post_build_cmds:

release/long_running_tests/app_config.yaml

@@ -7,15 +7,15 @@ debian_packages:
 
 python:
   pip_packages:
-    - gym[atari]>=0.21.0,<0.24.0
+    - gym[atari]>=0.21.0,<0.24.1
     - pytest
     - tensorflow
   conda_packages: []
 
 post_build_cmds:
   - 'rm -r wrk || true && git clone https://github.com/wg/wrk.git /tmp/wrk && cd /tmp/wrk && make -j && sudo cp wrk /usr/local/bin'
   - pip3 install pytest || true
-  - pip3 install -U ray[all] gym[atari]>=0.21.0,<0.24.0 autorom[accept-rom-license]
+  - pip3 install -U ray[all] gym[atari]>=0.21.0,<0.24.1 autorom[accept-rom-license]
   - pip3 install ray[all]
   # TODO (Alex): Ideally we would install all the dependencies from the new
   # version too, but pip won't be able to find the new version of ray-cpp.

release/long_running_tests/app_config_np.yaml

@@ -7,7 +7,7 @@ debian_packages:
 
 python:
   pip_packages:
-    - gym[atari]>=0.21.0,<0.24.0
+    - gym[atari]>=0.21.0,<0.24.1
     - pygame
     - pytest
     - tensorflow
@@ -18,7 +18,7 @@ post_build_cmds:
     - 'rm -r wrk || true && git clone https://github.com/wg/wrk.git /tmp/wrk && cd /tmp/wrk && make -j && sudo cp wrk /usr/local/bin'
     - pip3 install numpy==1.19 || true
     - pip3 install pytest || true
-    - pip3 install -U ray[all] gym[atari]>=0.21.0,<0.24.0 autorom[accept-rom-license]
+    - pip3 install -U ray[all] gym[atari]>=0.21.0,<0.24.1 autorom[accept-rom-license]
     - pip3 install ray[all]
     # TODO (Alex): Ideally we would install all the dependencies from the new
     # version too, but pip won't be able to find the new version of ray-cpp.

release/rllib_tests/app_config.yaml

@@ -8,7 +8,7 @@ python:
   # These dependencies should be handled by requirements_rllib.txt and
   # requirements_ml_docker.txt
   pip_packages:
-      - gym>=0.21.0,<0.24.0
+      - gym>=0.21.0,<0.24.1
   conda_packages: []
 
 post_build_cmds:

release/tune_tests/cloud_tests/app_config.yaml

@@ -8,7 +8,7 @@ python:
     - pytest
     - awscli
     - gsutil
-    - gym>=0.21.0,<0.24.0
+    - gym>=0.21.0,<0.24.1
     - gcsfs
     - pyarrow>=6.0.1,<7.0.0
   conda_packages: []

release/tune_tests/cloud_tests/app_config_ml.yaml

@@ -8,7 +8,7 @@ python:
     - pytest
     - awscli
     - gsutil
-    - gym>=0.21.0,<0.24.0
+    - gym>=0.21.0,<0.24.1
     - gcsfs
     - pyarrow>=6.0.1,<7.0.0
   conda_packages: []

rllib/utils/pre_checks/env.py

@@ -1,5 +1,6 @@
 """Common pre-checks for all RLlib experiments."""
 from copy import copy
+import inspect
 import logging
 import gym
 import numpy as np
@@ -146,6 +147,17 @@ def check_gym_environments(env: gym.Env) -> None:
                 "to infinity, and your environment will not be "
                 "reset."
             )
+    # Raise warning if using new reset api introduces in gym 0.24
+    reset_signature = inspect.signature(env.unwrapped.reset).parameters.keys()
+    if any(k in reset_signature for k in ["seed", "return_info"]):
+        if log_once("reset_signature"):
+            logger.warning(
+                "Your env reset() method appears to take 'seed' or 'return_info'"
+                " arguments. Note that these are not yet supported in RLlib."
+                " Seeding will take place using 'env.seed()' and the info dict"
+                " will not be returned from reset."
+            )
+
     # check if sampled actions and observations are contained within their
     # respective action and observation spaces.