Remove gym from skrl.utils

skrl/utils/model_instantiators/jax/categorical.py

@@ -1,7 +1,6 @@
 from typing import Any, Mapping, Optional, Sequence, Tuple, Union
 
 import textwrap
-import gym
 import gymnasium
 
 import flax.linen as nn  # noqa
@@ -14,8 +13,8 @@
 from skrl.utils.spaces.jax import unflatten_tensorized_space  # noqa
 
 
-def categorical_model(observation_space: Optional[Union[int, Tuple[int], gym.Space, gymnasium.Space]] = None,
-                      action_space: Optional[Union[int, Tuple[int], gym.Space, gymnasium.Space]] = None,
+def categorical_model(observation_space: Optional[Union[int, Tuple[int], gymnasium.Space]] = None,
+                      action_space: Optional[Union[int, Tuple[int], gymnasium.Space]] = None,
                       device: Optional[Union[str, jax.Device]] = None,
                       unnormalized_log_prob: bool = True,
                       network: Sequence[Mapping[str, Any]] = [],
@@ -27,10 +26,10 @@ def categorical_model(observation_space: Optional[Union[int, Tuple[int], gym.Spa
 
     :param observation_space: Observation/state space or shape (default: None).
                               If it is not None, the num_observations property will contain the size of that space
-    :type observation_space: int, tuple or list of integers, gym.Space, gymnasium.Space or None, optional
+    :type observation_space: int, tuple or list of integers, gymnasium.Space or None, optional
     :param action_space: Action space or shape (default: None).
                          If it is not None, the num_actions property will contain the size of that space
-    :type action_space: int, tuple or list of integers, gym.Space, gymnasium.Space or None, optional
+    :type action_space: int, tuple or list of integers, gymnasium.Space or None, optional
     :param device: Device on which a tensor/array is or will be allocated (default: ``None``).
                    If None, the device will be either ``"cuda"`` if available or ``"cpu"``
     :type device: str or jax.Device, optional

skrl/utils/model_instantiators/jax/deterministic.py

@@ -1,7 +1,6 @@
 from typing import Any, Mapping, Optional, Sequence, Tuple, Union
 
 import textwrap
-import gym
 import gymnasium
 
 import flax.linen as nn  # noqa
@@ -14,8 +13,8 @@
 from skrl.utils.spaces.jax import unflatten_tensorized_space  # noqa
 
 
-def deterministic_model(observation_space: Optional[Union[int, Tuple[int], gym.Space, gymnasium.Space]] = None,
-                        action_space: Optional[Union[int, Tuple[int], gym.Space, gymnasium.Space]] = None,
+def deterministic_model(observation_space: Optional[Union[int, Tuple[int], gymnasium.Space]] = None,
+                        action_space: Optional[Union[int, Tuple[int], gymnasium.Space]] = None,
                         device: Optional[Union[str, jax.Device]] = None,
                         clip_actions: bool = False,
                         network: Sequence[Mapping[str, Any]] = [],
@@ -27,10 +26,10 @@ def deterministic_model(observation_space: Optional[Union[int, Tuple[int], gym.S
 
     :param observation_space: Observation/state space or shape (default: None).
                               If it is not None, the num_observations property will contain the size of that space
-    :type observation_space: int, tuple or list of integers, gym.Space, gymnasium.Space or None, optional
+    :type observation_space: int, tuple or list of integers, gymnasium.Space or None, optional
     :param action_space: Action space or shape (default: None).
                          If it is not None, the num_actions property will contain the size of that space
-    :type action_space: int, tuple or list of integers, gym.Space, gymnasium.Space or None, optional
+    :type action_space: int, tuple or list of integers, gymnasium.Space or None, optional
     :param device: Device on which a tensor/array is or will be allocated (default: ``None``).
                    If None, the device will be either ``"cuda"`` if available or ``"cpu"``
     :type device: str or jax.Device, optional

skrl/utils/model_instantiators/jax/gaussian.py

@@ -1,7 +1,6 @@
 from typing import Any, Mapping, Optional, Sequence, Tuple, Union
 
 import textwrap
-import gym
 import gymnasium
 
 import flax.linen as nn  # noqa
@@ -14,8 +13,8 @@
 from skrl.utils.spaces.jax import unflatten_tensorized_space  # noqa
 
 
-def gaussian_model(observation_space: Optional[Union[int, Tuple[int], gym.Space, gymnasium.Space]] = None,
-                   action_space: Optional[Union[int, Tuple[int], gym.Space, gymnasium.Space]] = None,
+def gaussian_model(observation_space: Optional[Union[int, Tuple[int], gymnasium.Space]] = None,
+                   action_space: Optional[Union[int, Tuple[int], gymnasium.Space]] = None,
                    device: Optional[Union[str, jax.Device]] = None,
                    clip_actions: bool = False,
                    clip_log_std: bool = True,
@@ -31,10 +30,10 @@ def gaussian_model(observation_space: Optional[Union[int, Tuple[int], gym.Space,
 
     :param observation_space: Observation/state space or shape (default: None).
                               If it is not None, the num_observations property will contain the size of that space
-    :type observation_space: int, tuple or list of integers, gym.Space, gymnasium.Space or None, optional
+    :type observation_space: int, tuple or list of integers, gymnasium.Space or None, optional
     :param action_space: Action space or shape (default: None).
                          If it is not None, the num_actions property will contain the size of that space
-    :type action_space: int, tuple or list of integers, gym.Space, gymnasium.Space or None, optional
+    :type action_space: int, tuple or list of integers, gymnasium.Space or None, optional
     :param device: Device on which a tensor/array is or will be allocated (default: ``None``).
                    If None, the device will be either ``"cuda"`` if available or ``"cpu"``
     :type device: str or jax.Device, optional

skrl/utils/model_instantiators/torch/categorical.py

@@ -1,7 +1,6 @@
 from typing import Any, Mapping, Optional, Sequence, Tuple, Union
 
 import textwrap
-import gym
 import gymnasium
 
 import torch
@@ -13,8 +12,8 @@
 from skrl.utils.spaces.torch import unflatten_tensorized_space  # noqa
 
 
-def categorical_model(observation_space: Optional[Union[int, Tuple[int], gym.Space, gymnasium.Space]] = None,
-                      action_space: Optional[Union[int, Tuple[int], gym.Space, gymnasium.Space]] = None,
+def categorical_model(observation_space: Optional[Union[int, Tuple[int], gymnasium.Space]] = None,
+                      action_space: Optional[Union[int, Tuple[int], gymnasium.Space]] = None,
                       device: Optional[Union[str, torch.device]] = None,
                       unnormalized_log_prob: bool = True,
                       network: Sequence[Mapping[str, Any]] = [],
@@ -26,10 +25,10 @@ def categorical_model(observation_space: Optional[Union[int, Tuple[int], gym.Spa
 
     :param observation_space: Observation/state space or shape (default: None).
                               If it is not None, the num_observations property will contain the size of that space
-    :type observation_space: int, tuple or list of integers, gym.Space, gymnasium.Space or None, optional
+    :type observation_space: int, tuple or list of integers, gymnasium.Space or None, optional
     :param action_space: Action space or shape (default: None).
                          If it is not None, the num_actions property will contain the size of that space
-    :type action_space: int, tuple or list of integers, gym.Space, gymnasium.Space or None, optional
+    :type action_space: int, tuple or list of integers, gymnasium.Space or None, optional
     :param device: Device on which a tensor/array is or will be allocated (default: ``None``).
                    If None, the device will be either ``"cuda"`` if available or ``"cpu"``
     :type device: str or torch.device, optional

skrl/utils/model_instantiators/torch/deterministic.py

@@ -1,7 +1,6 @@
 from typing import Any, Mapping, Optional, Sequence, Tuple, Union
 
 import textwrap
-import gym
 import gymnasium
 
 import torch
@@ -13,8 +12,8 @@
 from skrl.utils.spaces.torch import unflatten_tensorized_space  # noqa
 
 
-def deterministic_model(observation_space: Optional[Union[int, Tuple[int], gym.Space, gymnasium.Space]] = None,
-                        action_space: Optional[Union[int, Tuple[int], gym.Space, gymnasium.Space]] = None,
+def deterministic_model(observation_space: Optional[Union[int, Tuple[int], gymnasium.Space]] = None,
+                        action_space: Optional[Union[int, Tuple[int], gymnasium.Space]] = None,
                         device: Optional[Union[str, torch.device]] = None,
                         clip_actions: bool = False,
                         network: Sequence[Mapping[str, Any]] = [],
@@ -26,10 +25,10 @@ def deterministic_model(observation_space: Optional[Union[int, Tuple[int], gym.S
 
     :param observation_space: Observation/state space or shape (default: None).
                               If it is not None, the num_observations property will contain the size of that space
-    :type observation_space: int, tuple or list of integers, gym.Space, gymnasium.Space or None, optional
+    :type observation_space: int, tuple or list of integers, gymnasium.Space or None, optional
     :param action_space: Action space or shape (default: None).
                          If it is not None, the num_actions property will contain the size of that space
-    :type action_space: int, tuple or list of integers, gym.Space, gymnasium.Space or None, optional
+    :type action_space: int, tuple or list of integers, gymnasium.Space or None, optional
     :param device: Device on which a tensor/array is or will be allocated (default: ``None``).
                    If None, the device will be either ``"cuda"`` if available or ``"cpu"``
     :type device: str or torch.device, optional

skrl/utils/model_instantiators/torch/gaussian.py

@@ -1,7 +1,6 @@
 from typing import Any, Mapping, Optional, Sequence, Tuple, Union
 
 import textwrap
-import gym
 import gymnasium
 
 import torch
@@ -13,8 +12,8 @@
 from skrl.utils.spaces.torch import unflatten_tensorized_space  # noqa
 
 
-def gaussian_model(observation_space: Optional[Union[int, Tuple[int], gym.Space, gymnasium.Space]] = None,
-                   action_space: Optional[Union[int, Tuple[int], gym.Space, gymnasium.Space]] = None,
+def gaussian_model(observation_space: Optional[Union[int, Tuple[int], gymnasium.Space]] = None,
+                   action_space: Optional[Union[int, Tuple[int], gymnasium.Space]] = None,
                    device: Optional[Union[str, torch.device]] = None,
                    clip_actions: bool = False,
                    clip_log_std: bool = True,
@@ -30,10 +29,10 @@ def gaussian_model(observation_space: Optional[Union[int, Tuple[int], gym.Space,
 
     :param observation_space: Observation/state space or shape (default: None).
                               If it is not None, the num_observations property will contain the size of that space
-    :type observation_space: int, tuple or list of integers, gym.Space, gymnasium.Space or None, optional
+    :type observation_space: int, tuple or list of integers, gymnasium.Space or None, optional
     :param action_space: Action space or shape (default: None).
                          If it is not None, the num_actions property will contain the size of that space
-    :type action_space: int, tuple or list of integers, gym.Space, gymnasium.Space or None, optional
+    :type action_space: int, tuple or list of integers, gymnasium.Space or None, optional
     :param device: Device on which a tensor/array is or will be allocated (default: ``None``).
                    If None, the device will be either ``"cuda"`` if available or ``"cpu"``
     :type device: str or torch.device, optional

skrl/utils/model_instantiators/torch/multivariate_gaussian.py

@@ -1,7 +1,6 @@
 from typing import Any, Mapping, Optional, Sequence, Tuple, Union
 
 import textwrap
-import gym
 import gymnasium
 
 import torch
@@ -13,8 +12,8 @@
 from skrl.utils.spaces.torch import unflatten_tensorized_space  # noqa
 
 
-def multivariate_gaussian_model(observation_space: Optional[Union[int, Tuple[int], gym.Space, gymnasium.Space]] = None,
-                                action_space: Optional[Union[int, Tuple[int], gym.Space, gymnasium.Space]] = None,
+def multivariate_gaussian_model(observation_space: Optional[Union[int, Tuple[int], gymnasium.Space]] = None,
+                                action_space: Optional[Union[int, Tuple[int], gymnasium.Space]] = None,
                                 device: Optional[Union[str, torch.device]] = None,
                                 clip_actions: bool = False,
                                 clip_log_std: bool = True,
@@ -30,10 +29,10 @@ def multivariate_gaussian_model(observation_space: Optional[Union[int, Tuple[int
 
     :param observation_space: Observation/state space or shape (default: None).
                               If it is not None, the num_observations property will contain the size of that space
-    :type observation_space: int, tuple or list of integers, gym.Space, gymnasium.Space or None, optional
+    :type observation_space: int, tuple or list of integers, gymnasium.Space or None, optional
     :param action_space: Action space or shape (default: None).
                          If it is not None, the num_actions property will contain the size of that space
-    :type action_space: int, tuple or list of integers, gym.Space, gymnasium.Space or None, optional
+    :type action_space: int, tuple or list of integers, gymnasium.Space or None, optional
     :param device: Device on which a tensor/array is or will be allocated (default: ``None``).
                    If None, the device will be either ``"cuda"`` if available or ``"cpu"``
     :type device: str or torch.device, optional

skrl/utils/model_instantiators/torch/shared.py

@@ -1,7 +1,6 @@
 from typing import Any, Mapping, Optional, Sequence, Tuple, Union
 
 import textwrap
-import gym
 import gymnasium
 
 import torch
@@ -13,8 +12,8 @@
 from skrl.utils.spaces.torch import unflatten_tensorized_space  # noqa
 
 
-def shared_model(observation_space: Optional[Union[int, Tuple[int], gym.Space, gymnasium.Space]] = None,
-                 action_space: Optional[Union[int, Tuple[int], gym.Space, gymnasium.Space]] = None,
+def shared_model(observation_space: Optional[Union[int, Tuple[int], gymnasium.Space]] = None,
+                 action_space: Optional[Union[int, Tuple[int], gymnasium.Space]] = None,
                  device: Optional[Union[str, torch.device]] = None,
                  structure: str = "",
                  roles: Sequence[str] = [],
@@ -25,10 +24,10 @@ def shared_model(observation_space: Optional[Union[int, Tuple[int], gym.Space, g
 
     :param observation_space: Observation/state space or shape (default: None).
                               If it is not None, the num_observations property will contain the size of that space
-    :type observation_space: int, tuple or list of integers, gym.Space, gymnasium.Space or None, optional
+    :type observation_space: int, tuple or list of integers, gymnasium.Space or None, optional
     :param action_space: Action space or shape (default: None).
                          If it is not None, the num_actions property will contain the size of that space
-    :type action_space: int, tuple or list of integers, gym.Space, gymnasium.Space or None, optional
+    :type action_space: int, tuple or list of integers, gymnasium.Space or None, optional
     :param device: Device on which a tensor/array is or will be allocated (default: ``None``).
                    If None, the device will be either ``"cuda"`` if available or ``"cpu"``
     :type device: str or torch.device, optional