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Bump gym dep to 0.24 (#26190)
Co-authored-by: Steven Morad <smorad@anyscale.com> Co-authored-by: Avnish <avnishnarayan@gmail.com> Co-authored-by: Avnish Narayan <38871737+avnishn@users.noreply.github.com>
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7 changed files with 19 additions and 7 deletions
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@ -4,7 +4,7 @@
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# ---------------------
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# Atari
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autorom[accept-rom-license]
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gym>=0.21.0,<0.24.0; python_version >= '3.7'
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gym>=0.21.0,<0.24.1; python_version >= '3.7'
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gym[atari]==0.19.0; python_version < '3.7'
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# Kaggle envs.
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kaggle_environments==1.7.11
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@ -7,7 +7,7 @@ python:
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pip_packages:
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- pytest
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- awscli
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- gym>=0.21.0,<0.24.0
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- gym>=0.21.0,<0.24.1
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conda_packages: []
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post_build_cmds:
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@ -7,7 +7,7 @@ debian_packages:
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python:
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pip_packages:
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- gym[atari]>=0.21.0,<0.24.0
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- "gym[atari]>=0.21.0,<0.24.1"
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- pytest
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- tensorflow
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conda_packages: []
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@ -15,7 +15,7 @@ python:
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post_build_cmds:
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- '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'
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- pip3 install pytest || true
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- pip3 install -U ray[all] gym[atari]>=0.21.0,<0.24.0 autorom[accept-rom-license]
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- pip3 install -U ray[all] "gym[atari]>=0.21.0,<0.24.1" autorom[accept-rom-license]
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- pip3 install ray[all]
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# TODO (Alex): Ideally we would install all the dependencies from the new
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# version too, but pip won't be able to find the new version of ray-cpp.
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@ -8,7 +8,7 @@ python:
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# These dependencies should be handled by requirements_rllib.txt and
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# requirements_ml_docker.txt
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pip_packages:
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- gym>=0.21.0,<0.24.0
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- gym>=0.21.0,<0.24.1
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conda_packages: []
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post_build_cmds:
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@ -8,7 +8,7 @@ python:
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- pytest
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- awscli
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- gsutil
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- gym>=0.21.0,<0.24.0
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- gym>=0.21.0,<0.24.1
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- gcsfs
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- pyarrow>=6.0.1,<7.0.0
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conda_packages: []
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@ -8,7 +8,7 @@ python:
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- pytest
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- awscli
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- gsutil
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- gym>=0.21.0,<0.24.0
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- gym>=0.21.0,<0.24.1
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- gcsfs
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- pyarrow>=6.0.1,<7.0.0
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conda_packages: []
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@ -1,5 +1,6 @@
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"""Common pre-checks for all RLlib experiments."""
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from copy import copy
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import inspect
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import logging
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import gym
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import numpy as np
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@ -146,6 +147,17 @@ def check_gym_environments(env: gym.Env) -> None:
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"to infinity, and your environment will not be "
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"reset."
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)
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# Raise warning if using new reset api introduces in gym 0.24
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reset_signature = inspect.signature(env.unwrapped.reset).parameters.keys()
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if any(k in reset_signature for k in ["seed", "return_info"]):
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if log_once("reset_signature"):
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logger.warning(
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"Your env reset() method appears to take 'seed' or 'return_info'"
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" arguments. Note that these are not yet supported in RLlib."
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" Seeding will take place using 'env.seed()' and the info dict"
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" will not be returned from reset."
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)
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# check if sampled actions and observations are contained within their
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# respective action and observation spaces.
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