def check_env(env: GymEnv, observation_space: gym.spaces.Space,
action_space: gym.spaces.Space):
"""
Checks the validity of the environment to load vs the one used for training.
Checked parameters:
- observation_space
- action_space
:param env: (GymEnv)
:param observation_space: (gym.spaces.Space)
:param action_space: (gym.spaces.Space)
"""
if (observation_space != env.observation_space
# Special cases for images that need to be transposed
and
not (is_image_space(env.observation_space) and
observation_space == VecTransposeImage.transpose_space(
env.observation_space))):
raise ValueError(
f'Observation spaces do not match: {observation_space} != {env.observation_space}'
)
if action_space != env.action_space:
raise ValueError(
f'Action spaces do not match: {action_space} != {env.action_space}'
)
def check_for_correct_spaces(env: GymEnv, observation_space: gym.spaces.Space,
action_space: gym.spaces.Space):
"""
Checks that the environment has same spaces as provided ones. Used by BaseAlgorithm to check if
spaces match after loading the model with given env.
Checked parameters:
- observation_space
- action_space
:param env: (GymEnv) Environment to check for valid spaces
:param observation_space: (gym.spaces.Space) Observation space to check against
:param action_space: (gym.spaces.Space) Action space to check against
"""
if (observation_space != env.observation_space
# Special cases for images that need to be transposed
and
not (is_image_space(env.observation_space) and observation_space
== VecTransposeImage.transpose_space(env.observation_space))):
raise ValueError(
f"Observation spaces do not match: {observation_space} != {env.observation_space}"
)
if action_space != env.action_space:
raise ValueError(
f"Action spaces do not match: {action_space} != {env.action_space}"
)