mirror of
https://github.com/Farama-Foundation/Gymnasium.git
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925823661d
* First find/replace, now tests * Fixes to the vector env * Make seed keyword only in wrappers * (try to) fix the bug with old environments using new wrappers (with the seed keyword) * black * Change **kwargs to options, try to make it work; black * Add OrderEnforcing wrapper to wrapper exports Add a test for compatibility with old (pybullet-like) envs * Add OrderEnforcing wrapper to wrapper exports Add a test for compatibility with old (pybullet-like) envs black * Update the env checker * Update the env checker * Update the env checker to use inspect (might fail tests, let's see) * Allow the signature to include kwargs in env_checker * Minor fix
121 lines
3.9 KiB
Python
121 lines
3.9 KiB
Python
"""Tests for the filter observation wrapper."""
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from typing import Optional
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import pytest
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import numpy as np
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import gym
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from gym.spaces import Dict, Box, Discrete, Tuple
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from gym.wrappers import FilterObservation, FlattenObservation
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class FakeEnvironment(gym.Env):
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def __init__(self, observation_space):
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self.observation_space = observation_space
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self.obs_keys = self.observation_space.spaces.keys()
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self.action_space = Box(shape=(1,), low=-1, high=1, dtype=np.float32)
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def render(self, width=32, height=32, *args, **kwargs):
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del args
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del kwargs
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image_shape = (height, width, 3)
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return np.zeros(image_shape, dtype=np.uint8)
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def reset(self, *, seed: Optional[int] = None, options: Optional[dict] = None):
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super().reset(seed=seed)
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observation = self.observation_space.sample()
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return observation
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def step(self, action):
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del action
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observation = self.observation_space.sample()
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reward, terminal, info = 0.0, False, {}
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return observation, reward, terminal, info
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NESTED_DICT_TEST_CASES = (
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(
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Dict(
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{
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"key1": Box(shape=(2,), low=-1, high=1, dtype=np.float32),
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"key2": Dict(
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{
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"subkey1": Box(shape=(2,), low=-1, high=1, dtype=np.float32),
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"subkey2": Box(shape=(2,), low=-1, high=1, dtype=np.float32),
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}
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),
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}
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),
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(6,),
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),
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(
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Dict(
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{
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"key1": Box(shape=(2, 3), low=-1, high=1, dtype=np.float32),
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"key2": Box(shape=(), low=-1, high=1, dtype=np.float32),
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"key3": Box(shape=(2,), low=-1, high=1, dtype=np.float32),
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}
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),
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(9,),
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),
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(
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Dict(
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{
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"key1": Tuple(
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(
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Box(shape=(2,), low=-1, high=1, dtype=np.float32),
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Box(shape=(2,), low=-1, high=1, dtype=np.float32),
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)
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),
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"key2": Box(shape=(), low=-1, high=1, dtype=np.float32),
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"key3": Box(shape=(2,), low=-1, high=1, dtype=np.float32),
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}
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),
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(7,),
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),
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(
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Dict(
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{
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"key1": Tuple((Box(shape=(2,), low=-1, high=1, dtype=np.float32),)),
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"key2": Box(shape=(), low=-1, high=1, dtype=np.float32),
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"key3": Box(shape=(2,), low=-1, high=1, dtype=np.float32),
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}
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),
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(5,),
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),
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(
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Dict(
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{
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"key1": Tuple(
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(Dict({"key9": Box(shape=(2,), low=-1, high=1, dtype=np.float32)}),)
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),
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"key2": Box(shape=(), low=-1, high=1, dtype=np.float32),
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"key3": Box(shape=(2,), low=-1, high=1, dtype=np.float32),
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}
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),
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(5,),
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),
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)
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class TestNestedDictWrapper:
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@pytest.mark.parametrize("observation_space, flat_shape", NESTED_DICT_TEST_CASES)
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def test_nested_dicts_size(self, observation_space, flat_shape):
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env = FakeEnvironment(observation_space=observation_space)
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# Make sure we are testing the right environment for the test.
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observation_space = env.observation_space
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assert isinstance(observation_space, Dict)
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wrapped_env = FlattenObservation(FilterObservation(env, env.obs_keys))
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assert wrapped_env.observation_space.shape == flat_shape
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assert wrapped_env.observation_space.dtype == np.float32
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@pytest.mark.parametrize("observation_space, flat_shape", NESTED_DICT_TEST_CASES)
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def test_nested_dicts_ravel(self, observation_space, flat_shape):
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env = FakeEnvironment(observation_space=observation_space)
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wrapped_env = FlattenObservation(FilterObservation(env, env.obs_keys))
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obs = wrapped_env.reset()
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assert obs.shape == wrapped_env.observation_space.shape
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