From be18c38f1f04982a988bbfde61aed3216027a66e Mon Sep 17 00:00:00 2001 From: pseudo-rnd-thoughts Date: Sat, 28 Sep 2024 22:30:13 +0100 Subject: [PATCH] Revert #1154 (Fix NumPy DocTests) --- gymnasium/spaces/dict.py | 2 +- gymnasium/spaces/discrete.py | 4 ++-- gymnasium/spaces/oneof.py | 4 ++-- gymnasium/spaces/tuple.py | 2 +- gymnasium/wrappers/stateful_observation.py | 4 ++-- gymnasium/wrappers/stateful_reward.py | 4 ++-- gymnasium/wrappers/transform_action.py | 2 +- gymnasium/wrappers/transform_observation.py | 8 ++++---- gymnasium/wrappers/transform_reward.py | 2 +- gymnasium/wrappers/vector/dict_info_to_list.py | 4 ++-- gymnasium/wrappers/vector/stateful_observation.py | 6 +++--- gymnasium/wrappers/vector/stateful_reward.py | 8 ++++---- gymnasium/wrappers/vector/vectorize_action.py | 2 +- gymnasium/wrappers/vector/vectorize_observation.py | 8 ++++---- 14 files changed, 30 insertions(+), 30 deletions(-) diff --git a/gymnasium/spaces/dict.py b/gymnasium/spaces/dict.py index 49ff4c907..128cf8c71 100644 --- a/gymnasium/spaces/dict.py +++ b/gymnasium/spaces/dict.py @@ -20,7 +20,7 @@ class Dict(Space[typing.Dict[str, Any]], typing.Mapping[str, Space[Any]]): >>> from gymnasium.spaces import Dict, Box, Discrete >>> observation_space = Dict({"position": Box(-1, 1, shape=(2,)), "color": Discrete(3)}, seed=42) >>> observation_space.sample() - {'color': np.int64(0), 'position': array([-0.3991573 , 0.21649833], dtype=float32)} + {'color': 0, 'position': array([-0.3991573 , 0.21649833], dtype=float32)} With a nested dict: diff --git a/gymnasium/spaces/discrete.py b/gymnasium/spaces/discrete.py index 9a4575252..41b9c356a 100644 --- a/gymnasium/spaces/discrete.py +++ b/gymnasium/spaces/discrete.py @@ -18,10 +18,10 @@ class Discrete(Space[np.int64]): >>> from gymnasium.spaces import Discrete >>> observation_space = Discrete(2, seed=42) # {0, 1} >>> observation_space.sample() - np.int64(0) + 0 >>> observation_space = Discrete(3, start=-1, seed=42) # {-1, 0, 1} >>> observation_space.sample() - np.int64(-1) + -1 """ def __init__( diff --git a/gymnasium/spaces/oneof.py b/gymnasium/spaces/oneof.py index 50e463be4..08aa50a5a 100644 --- a/gymnasium/spaces/oneof.py +++ b/gymnasium/spaces/oneof.py @@ -19,9 +19,9 @@ class OneOf(Space[Any]): >>> from gymnasium.spaces import OneOf, Box, Discrete >>> observation_space = OneOf((Discrete(2), Box(-1, 1, shape=(2,))), seed=123) >>> observation_space.sample() # the first element is the space index (Box in this case) and the second element is the sample from Box - (np.int64(0), np.int64(0)) + (0, 0) >>> observation_space.sample() # this time the Discrete space was sampled as index=0 - (np.int64(1), array([-0.00711833, -0.7257502 ], dtype=float32)) + (1, array([-0.00711833, -0.7257502 ], dtype=float32)) >>> observation_space[0] Discrete(2) >>> observation_space[1] diff --git a/gymnasium/spaces/tuple.py b/gymnasium/spaces/tuple.py index 05a1f652a..b14527650 100644 --- a/gymnasium/spaces/tuple.py +++ b/gymnasium/spaces/tuple.py @@ -19,7 +19,7 @@ class Tuple(Space[typing.Tuple[Any, ...]], typing.Sequence[Any]): >>> from gymnasium.spaces import Tuple, Box, Discrete >>> observation_space = Tuple((Discrete(2), Box(-1, 1, shape=(2,))), seed=42) >>> observation_space.sample() - (np.int64(0), array([-0.3991573 , 0.21649833], dtype=float32)) + (0, array([-0.3991573 , 0.21649833], dtype=float32)) """ def __init__( diff --git a/gymnasium/wrappers/stateful_observation.py b/gymnasium/wrappers/stateful_observation.py index edffe3d77..1ac798034 100644 --- a/gymnasium/wrappers/stateful_observation.py +++ b/gymnasium/wrappers/stateful_observation.py @@ -557,9 +557,9 @@ class MaxAndSkipObservation( >>> wrapped_obs0, *_ = wrapped_env.reset(seed=123) >>> wrapped_obs1, *_ = wrapped_env.step(1) >>> np.all(obs0 == wrapped_obs0) - np.True_ + True >>> np.all(wrapped_obs1 == skip_and_max_obs) - np.True_ + True Change logs: * v1.0.0 - Initially add diff --git a/gymnasium/wrappers/stateful_reward.py b/gymnasium/wrappers/stateful_reward.py index 67e2b784f..cfcc9995e 100644 --- a/gymnasium/wrappers/stateful_reward.py +++ b/gymnasium/wrappers/stateful_reward.py @@ -58,7 +58,7 @@ class NormalizeReward( ... >>> env.close() >>> np.var(episode_rewards) - np.float64(0.0008876301247721108) + 0.0008876301247721108 Example with the normalize reward wrapper: >>> import numpy as np @@ -76,7 +76,7 @@ class NormalizeReward( >>> env.close() >>> # will approach 0.99 with more episodes >>> np.var(episode_rewards) - np.float64(0.010162116476634746) + 0.010162116476634746 Change logs: * v0.21.0 - Initially added diff --git a/gymnasium/wrappers/transform_action.py b/gymnasium/wrappers/transform_action.py index a069ab04f..8ab5bb581 100644 --- a/gymnasium/wrappers/transform_action.py +++ b/gymnasium/wrappers/transform_action.py @@ -146,7 +146,7 @@ class RescaleAction( >>> wrapped_env = RescaleAction(env, min_action=min_action, max_action=max_action) >>> wrapped_env_obs, _, _, _, _ = wrapped_env.step(max_action) >>> np.all(obs == wrapped_env_obs) - np.True_ + True Change logs: * v0.15.4 - Initially added diff --git a/gymnasium/wrappers/transform_observation.py b/gymnasium/wrappers/transform_observation.py index 824a401c3..0dafe69a8 100644 --- a/gymnasium/wrappers/transform_observation.py +++ b/gymnasium/wrappers/transform_observation.py @@ -594,11 +594,11 @@ class AddRenderObservation( >>> obs, _ = env.reset(seed=123) >>> image = env.render() >>> np.all(obs == image) - np.True_ + True >>> obs, *_ = env.step(env.action_space.sample()) >>> image = env.render() >>> np.all(obs == image) - np.True_ + True Example - Add the rendered image to the original observation as a dictionary item: >>> env = gym.make("CartPole-v1", render_mode="rgb_array") @@ -611,11 +611,11 @@ class AddRenderObservation( >>> obs["state"] array([ 0.01823519, -0.0446179 , -0.02796401, -0.03156282], dtype=float32) >>> np.all(obs["pixels"] == env.render()) - np.True_ + True >>> obs, reward, terminates, truncates, info = env.step(env.action_space.sample()) >>> image = env.render() >>> np.all(obs["pixels"] == image) - np.True_ + True Change logs: * v0.15.0 - Initially added as ``PixelObservationWrapper`` diff --git a/gymnasium/wrappers/transform_reward.py b/gymnasium/wrappers/transform_reward.py index b17308c25..d30248b09 100644 --- a/gymnasium/wrappers/transform_reward.py +++ b/gymnasium/wrappers/transform_reward.py @@ -77,7 +77,7 @@ class ClipReward(TransformReward[ObsType, ActType], gym.utils.RecordConstructorA >>> _ = env.reset() >>> _, rew, _, _, _ = env.step(1) >>> rew - np.float64(0.5) + 0.5 Change logs: * v1.0.0 - Initially added diff --git a/gymnasium/wrappers/vector/dict_info_to_list.py b/gymnasium/wrappers/vector/dict_info_to_list.py index c66783fc3..c7afa537a 100644 --- a/gymnasium/wrappers/vector/dict_info_to_list.py +++ b/gymnasium/wrappers/vector/dict_info_to_list.py @@ -54,13 +54,13 @@ class DictInfoToList(VectorWrapper): >>> _ = envs.action_space.seed(123) >>> _, _, _, _, infos = envs.step(envs.action_space.sample()) >>> infos - {'x_position': array([0.03332211, 0.10172355]), '_x_position': array([ True, True]), 'x_velocity': array([-0.06296527, 0.89345848]), '_x_velocity': array([ True, True]), 'reward_run': array([-0.06296527, 0.89345848]), '_reward_run': array([ True, True]), 'reward_ctrl': array([-0.24503504, -0.21944423], dtype=float32), '_reward_ctrl': array([ True, True])} + {'x_position': array([0.03332211, 0.10172355]), '_x_position': array([ True, True]), 'x_velocity': array([-0.06296527, 0.89345848]), '_x_velocity': array([ True, True]), 'reward_run': array([-0.06296527, 0.89345848]), '_reward_run': array([ True, True]), 'reward_ctrl': array([-0.24503503, -0.21944423]), '_reward_ctrl': array([ True, True])} >>> envs = DictInfoToList(envs) >>> _ = envs.reset(seed=123) >>> _ = envs.action_space.seed(123) >>> _, _, _, _, infos = envs.step(envs.action_space.sample()) >>> infos - [{'x_position': np.float64(0.0333221090036294), 'x_velocity': np.float64(-0.06296527291998574), 'reward_run': np.float64(-0.06296527291998574), 'reward_ctrl': np.float32(-0.24503504)}, {'x_position': np.float64(0.10172354684460168), 'x_velocity': np.float64(0.8934584807363618), 'reward_run': np.float64(0.8934584807363618), 'reward_ctrl': np.float32(-0.21944423)}] + [{'x_position': 0.0333221090036294, 'x_velocity': -0.06296527291998574, 'reward_run': -0.06296527291998574, 'reward_ctrl': -0.2450350284576416}, {'x_position': 0.10172354684460168, 'x_velocity': 0.8934584807363618, 'reward_run': 0.8934584807363618, 'reward_ctrl': -0.21944422721862794}] Change logs: * v0.24.0 - Initially added as ``VectorListInfo`` diff --git a/gymnasium/wrappers/vector/stateful_observation.py b/gymnasium/wrappers/vector/stateful_observation.py index 266c488d1..9c80d85d0 100644 --- a/gymnasium/wrappers/vector/stateful_observation.py +++ b/gymnasium/wrappers/vector/stateful_observation.py @@ -35,9 +35,9 @@ class NormalizeObservation(VectorObservationWrapper, gym.utils.RecordConstructor >>> for _ in range(100): ... obs, *_ = envs.step(envs.action_space.sample()) >>> np.mean(obs) - np.float32(0.024251968) + 0.024251968 >>> np.std(obs) - np.float32(0.62259156) + 0.62259156 >>> envs.close() Example with the normalize reward wrapper: @@ -49,7 +49,7 @@ class NormalizeObservation(VectorObservationWrapper, gym.utils.RecordConstructor >>> for _ in range(100): ... obs, *_ = envs.step(envs.action_space.sample()) >>> np.mean(obs) - np.float32(-0.2359734) + -0.2359734 >>> np.std(obs) np.float32(1.1938739) >>> envs.close() diff --git a/gymnasium/wrappers/vector/stateful_reward.py b/gymnasium/wrappers/vector/stateful_reward.py index 2e0e8ea50..14cd03f4f 100644 --- a/gymnasium/wrappers/vector/stateful_reward.py +++ b/gymnasium/wrappers/vector/stateful_reward.py @@ -50,9 +50,9 @@ class NormalizeReward(VectorWrapper, gym.utils.RecordConstructorArgs): ... >>> envs.close() >>> np.mean(episode_rewards) - np.float64(-0.03359492141887935) + -0.03359492141887935 >>> np.std(episode_rewards) - np.float64(0.029028230434438706) + 0.029028230434438706 Example with the normalize reward wrapper: >>> import gymnasium as gym @@ -68,9 +68,9 @@ class NormalizeReward(VectorWrapper, gym.utils.RecordConstructorArgs): ... >>> envs.close() >>> np.mean(episode_rewards) - np.float64(-0.1598639586606745) + -0.1598639586606745 >>> np.std(episode_rewards) - np.float64(0.27800309628058434) + 0.27800309628058434 """ def __init__( diff --git a/gymnasium/wrappers/vector/vectorize_action.py b/gymnasium/wrappers/vector/vectorize_action.py index f0f0b8e57..646889dce 100644 --- a/gymnasium/wrappers/vector/vectorize_action.py +++ b/gymnasium/wrappers/vector/vectorize_action.py @@ -33,7 +33,7 @@ class TransformAction(VectorActionWrapper): >>> obs array([[-0.46553135, -0.00142543], [-0.498371 , -0.00715587], - [-0.46515748, -0.00624371]], dtype=float32) + [-0.4651575 , -0.00624371]], dtype=float32) Example - With action transformation: >>> import gymnasium as gym diff --git a/gymnasium/wrappers/vector/vectorize_observation.py b/gymnasium/wrappers/vector/vectorize_observation.py index 88bd539ad..68b5ef8b6 100644 --- a/gymnasium/wrappers/vector/vectorize_observation.py +++ b/gymnasium/wrappers/vector/vectorize_observation.py @@ -321,15 +321,15 @@ class RescaleObservation(VectorizeTransformObservation): >>> envs = gym.make_vec("MountainCar-v0", num_envs=3, vectorization_mode="sync") >>> obs, info = envs.reset(seed=123) >>> obs.min() - np.float32(-0.46352962) + -0.46352962 >>> obs.max() - np.float32(0.0) + 0.0 >>> envs = RescaleObservation(envs, min_obs=-5.0, max_obs=5.0) >>> obs, info = envs.reset(seed=123) >>> obs.min() - np.float32(-0.90849805) + -0.90849805 >>> obs.max() - np.float32(0.0) + 0.0 >>> envs.close() """