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<li class="toctree-l1"><a class="reference internal" href="../../../../introduction/basic_usage/">Basic Usage</a></li>
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<li class="toctree-l1"><a class="reference internal" href="../../../../introduction/train_agent/">Training an Agent</a></li>
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<li class="toctree-l2"><a class="reference internal" href="../../../../environments/atari/solaris/">Solaris</a></li>
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<li class="toctree-l2"><a class="reference internal" href="../../../../environments/atari/space_invaders/">SpaceInvaders</a></li>
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<li class="toctree-l2"><a class="reference internal" href="../../../../environments/atari/surround/">Surround</a></li>
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<li class="toctree-l2"><a class="reference internal" href="../../../../environments/atari/tennis/">Tennis</a></li>
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<li class="toctree-l2"><a class="reference internal" href="../../../../environments/atari/tetris/">Tetris</a></li>
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<li class="toctree-l2"><a class="reference internal" href="../../../../environments/atari/tutankham/">Tutankham</a></li>
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<li class="toctree-l2"><a class="reference internal" href="../../../../environments/atari/up_n_down/">UpNDown</a></li>
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<li class="toctree-l2"><a class="reference internal" href="../../../../environments/atari/venture/">Venture</a></li>
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<li class="toctree-l2"><a class="reference internal" href="../../../../environments/atari/video_checkers/">VideoCheckers</a></li>
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<li class="toctree-l2"><a class="reference internal" href="../../../../environments/atari/video_chess/">VideoChess</a></li>
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<li class="toctree-l2"><a class="reference internal" href="../../../../environments/atari/video_cube/">VideoCube</a></li>
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<li class="toctree-l2"><a class="reference internal" href="../../../../environments/atari/video_pinball/">VideoPinball</a></li>
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<li class="toctree-l2"><a class="reference internal" href="../../../../environments/atari/wizard_of_wor/">WizardOfWor</a></li>
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<li class="toctree-l2"><a class="reference internal" href="../../../../environments/atari/word_zapper/">WordZapper</a></li>
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<li class="toctree-l2"><a class="reference internal" href="../../../../environments/atari/yars_revenge/">YarsRevenge</a></li>
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<li class="toctree-l2"><a class="reference internal" href="../../../../environments/atari/zaxxon/">Zaxxon</a></li>
|
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</li>
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<li class="toctree-l1"><a class="reference internal" href="../../../../environments/third_party_environments/">Third-Party Environments</a></li>
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<p class="caption" role="heading"><span class="caption-text">Tutorials</span></p>
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<ul>
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<h1>Source code for gymnasium.wrappers.stateful_observation</h1><div class="highlight"><pre>
|
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<span></span><span class="sd">"""A collection of stateful observation wrappers.</span>
|
||
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|
|
||
|
|
<span class="sd">* ``DelayObservation`` - A wrapper for delaying the returned observation</span>
|
||
|
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<span class="sd">* ``TimeAwareObservation`` - A wrapper for adding time aware observations to environment observation</span>
|
||
|
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<span class="sd">* ``FrameStackObservation`` - Frame stack the observations</span>
|
||
|
|
<span class="sd">* ``NormalizeObservation`` - Normalized the observations to have unit variance with a moving mean</span>
|
||
|
|
<span class="sd">* ``MaxAndSkipObservation`` - Return only every ``skip``-th frame (frameskipping) and return the max between the two last frames.</span>
|
||
|
|
<span class="sd">"""</span>
|
||
|
|
<span class="kn">from</span> <span class="nn">__future__</span> <span class="kn">import</span> <span class="n">annotations</span>
|
||
|
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|
||
|
|
<span class="kn">from</span> <span class="nn">collections</span> <span class="kn">import</span> <span class="n">deque</span>
|
||
|
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<span class="kn">from</span> <span class="nn">copy</span> <span class="kn">import</span> <span class="n">deepcopy</span>
|
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<span class="kn">from</span> <span class="nn">typing</span> <span class="kn">import</span> <span class="n">Any</span><span class="p">,</span> <span class="n">Final</span><span class="p">,</span> <span class="n">SupportsFloat</span>
|
||
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|
||
|
|
<span class="kn">import</span> <span class="nn">numpy</span> <span class="k">as</span> <span class="nn">np</span>
|
||
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|
||
|
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<span class="kn">import</span> <span class="nn">gymnasium</span> <span class="k">as</span> <span class="nn">gym</span>
|
||
|
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<span class="kn">import</span> <span class="nn">gymnasium.spaces</span> <span class="k">as</span> <span class="nn">spaces</span>
|
||
|
|
<span class="kn">from</span> <span class="nn">gymnasium.core</span> <span class="kn">import</span> <span class="n">ActType</span><span class="p">,</span> <span class="n">ObsType</span><span class="p">,</span> <span class="n">WrapperActType</span><span class="p">,</span> <span class="n">WrapperObsType</span>
|
||
|
|
<span class="kn">from</span> <span class="nn">gymnasium.spaces</span> <span class="kn">import</span> <span class="n">Box</span><span class="p">,</span> <span class="n">Dict</span><span class="p">,</span> <span class="n">Tuple</span>
|
||
|
|
<span class="kn">from</span> <span class="nn">gymnasium.vector.utils</span> <span class="kn">import</span> <span class="n">batch_space</span><span class="p">,</span> <span class="n">concatenate</span><span class="p">,</span> <span class="n">create_empty_array</span>
|
||
|
|
<span class="kn">from</span> <span class="nn">gymnasium.wrappers.utils</span> <span class="kn">import</span> <span class="n">RunningMeanStd</span><span class="p">,</span> <span class="n">create_zero_array</span>
|
||
|
|
|
||
|
|
|
||
|
|
<span class="n">__all__</span> <span class="o">=</span> <span class="p">[</span>
|
||
|
|
<span class="s2">"DelayObservation"</span><span class="p">,</span>
|
||
|
|
<span class="s2">"TimeAwareObservation"</span><span class="p">,</span>
|
||
|
|
<span class="s2">"FrameStackObservation"</span><span class="p">,</span>
|
||
|
|
<span class="s2">"NormalizeObservation"</span><span class="p">,</span>
|
||
|
|
<span class="s2">"MaxAndSkipObservation"</span><span class="p">,</span>
|
||
|
|
<span class="p">]</span>
|
||
|
|
|
||
|
|
|
||
|
|
<div class="viewcode-block" id="DelayObservation">
|
||
|
|
<a class="viewcode-back" href="../../../../api/wrappers/observation_wrappers/#gymnasium.wrappers.DelayObservation">[docs]</a>
|
||
|
|
<span class="k">class</span> <span class="nc">DelayObservation</span><span class="p">(</span>
|
||
|
|
<span class="n">gym</span><span class="o">.</span><span class="n">ObservationWrapper</span><span class="p">[</span><span class="n">ObsType</span><span class="p">,</span> <span class="n">ActType</span><span class="p">,</span> <span class="n">ObsType</span><span class="p">],</span> <span class="n">gym</span><span class="o">.</span><span class="n">utils</span><span class="o">.</span><span class="n">RecordConstructorArgs</span>
|
||
|
|
<span class="p">):</span>
|
||
|
|
<span class="w"> </span><span class="sd">"""Adds a delay to the returned observation from the environment.</span>
|
||
|
|
|
||
|
|
<span class="sd"> Before reaching the :attr:`delay` number of timesteps, returned observations is an array of zeros with</span>
|
||
|
|
<span class="sd"> the same shape as the observation space.</span>
|
||
|
|
|
||
|
|
<span class="sd"> No vector version of the wrapper exists.</span>
|
||
|
|
|
||
|
|
<span class="sd"> Note:</span>
|
||
|
|
<span class="sd"> This does not support random delay values, if users are interested, please raise an issue or pull request to add this feature.</span>
|
||
|
|
|
||
|
|
<span class="sd"> Example:</span>
|
||
|
|
<span class="sd"> >>> import gymnasium as gym</span>
|
||
|
|
<span class="sd"> >>> env = gym.make("CartPole-v1")</span>
|
||
|
|
<span class="sd"> >>> env.reset(seed=123)</span>
|
||
|
|
<span class="sd"> (array([ 0.01823519, -0.0446179 , -0.02796401, -0.03156282], dtype=float32), {})</span>
|
||
|
|
|
||
|
|
<span class="sd"> >>> env = DelayObservation(env, delay=2)</span>
|
||
|
|
<span class="sd"> >>> env.reset(seed=123)</span>
|
||
|
|
<span class="sd"> (array([0., 0., 0., 0.], dtype=float32), {})</span>
|
||
|
|
<span class="sd"> >>> env.step(env.action_space.sample())</span>
|
||
|
|
<span class="sd"> (array([0., 0., 0., 0.], dtype=float32), 1.0, False, False, {})</span>
|
||
|
|
<span class="sd"> >>> env.step(env.action_space.sample())</span>
|
||
|
|
<span class="sd"> (array([ 0.01823519, -0.0446179 , -0.02796401, -0.03156282], dtype=float32), 1.0, False, False, {})</span>
|
||
|
|
|
||
|
|
<span class="sd"> Change logs:</span>
|
||
|
|
<span class="sd"> * v1.0.0 - Initially added</span>
|
||
|
|
<span class="sd"> """</span>
|
||
|
|
|
||
|
|
<span class="k">def</span> <span class="fm">__init__</span><span class="p">(</span><span class="bp">self</span><span class="p">,</span> <span class="n">env</span><span class="p">:</span> <span class="n">gym</span><span class="o">.</span><span class="n">Env</span><span class="p">[</span><span class="n">ObsType</span><span class="p">,</span> <span class="n">ActType</span><span class="p">],</span> <span class="n">delay</span><span class="p">:</span> <span class="nb">int</span><span class="p">):</span>
|
||
|
|
<span class="w"> </span><span class="sd">"""Initialises the DelayObservation wrapper with an integer.</span>
|
||
|
|
|
||
|
|
<span class="sd"> Args:</span>
|
||
|
|
<span class="sd"> env: The environment to wrap</span>
|
||
|
|
<span class="sd"> delay: The number of timesteps to delay observations</span>
|
||
|
|
<span class="sd"> """</span>
|
||
|
|
<span class="k">if</span> <span class="ow">not</span> <span class="n">np</span><span class="o">.</span><span class="n">issubdtype</span><span class="p">(</span><span class="nb">type</span><span class="p">(</span><span class="n">delay</span><span class="p">),</span> <span class="n">np</span><span class="o">.</span><span class="n">integer</span><span class="p">):</span>
|
||
|
|
<span class="k">raise</span> <span class="ne">TypeError</span><span class="p">(</span>
|
||
|
|
<span class="sa">f</span><span class="s2">"The delay is expected to be an integer, actual type: </span><span class="si">{</span><span class="nb">type</span><span class="p">(</span><span class="n">delay</span><span class="p">)</span><span class="si">}</span><span class="s2">"</span>
|
||
|
|
<span class="p">)</span>
|
||
|
|
<span class="k">if</span> <span class="ow">not</span> <span class="mi">0</span> <span class="o"><=</span> <span class="n">delay</span><span class="p">:</span>
|
||
|
|
<span class="k">raise</span> <span class="ne">ValueError</span><span class="p">(</span>
|
||
|
|
<span class="sa">f</span><span class="s2">"The delay needs to be greater than zero, actual value: </span><span class="si">{</span><span class="n">delay</span><span class="si">}</span><span class="s2">"</span>
|
||
|
|
<span class="p">)</span>
|
||
|
|
|
||
|
|
<span class="n">gym</span><span class="o">.</span><span class="n">utils</span><span class="o">.</span><span class="n">RecordConstructorArgs</span><span class="o">.</span><span class="fm">__init__</span><span class="p">(</span><span class="bp">self</span><span class="p">,</span> <span class="n">delay</span><span class="o">=</span><span class="n">delay</span><span class="p">)</span>
|
||
|
|
<span class="n">gym</span><span class="o">.</span><span class="n">ObservationWrapper</span><span class="o">.</span><span class="fm">__init__</span><span class="p">(</span><span class="bp">self</span><span class="p">,</span> <span class="n">env</span><span class="p">)</span>
|
||
|
|
|
||
|
|
<span class="bp">self</span><span class="o">.</span><span class="n">delay</span><span class="p">:</span> <span class="n">Final</span><span class="p">[</span><span class="nb">int</span><span class="p">]</span> <span class="o">=</span> <span class="nb">int</span><span class="p">(</span><span class="n">delay</span><span class="p">)</span>
|
||
|
|
<span class="bp">self</span><span class="o">.</span><span class="n">observation_queue</span><span class="p">:</span> <span class="n">Final</span><span class="p">[</span><span class="n">deque</span><span class="p">]</span> <span class="o">=</span> <span class="n">deque</span><span class="p">()</span>
|
||
|
|
|
||
|
|
<span class="k">def</span> <span class="nf">reset</span><span class="p">(</span>
|
||
|
|
<span class="bp">self</span><span class="p">,</span> <span class="o">*</span><span class="p">,</span> <span class="n">seed</span><span class="p">:</span> <span class="nb">int</span> <span class="o">|</span> <span class="kc">None</span> <span class="o">=</span> <span class="kc">None</span><span class="p">,</span> <span class="n">options</span><span class="p">:</span> <span class="nb">dict</span><span class="p">[</span><span class="nb">str</span><span class="p">,</span> <span class="n">Any</span><span class="p">]</span> <span class="o">|</span> <span class="kc">None</span> <span class="o">=</span> <span class="kc">None</span>
|
||
|
|
<span class="p">)</span> <span class="o">-></span> <span class="nb">tuple</span><span class="p">[</span><span class="n">ObsType</span><span class="p">,</span> <span class="nb">dict</span><span class="p">[</span><span class="nb">str</span><span class="p">,</span> <span class="n">Any</span><span class="p">]]:</span>
|
||
|
|
<span class="w"> </span><span class="sd">"""Resets the environment, clearing the observation queue."""</span>
|
||
|
|
<span class="bp">self</span><span class="o">.</span><span class="n">observation_queue</span><span class="o">.</span><span class="n">clear</span><span class="p">()</span>
|
||
|
|
|
||
|
|
<span class="k">return</span> <span class="nb">super</span><span class="p">()</span><span class="o">.</span><span class="n">reset</span><span class="p">(</span><span class="n">seed</span><span class="o">=</span><span class="n">seed</span><span class="p">,</span> <span class="n">options</span><span class="o">=</span><span class="n">options</span><span class="p">)</span>
|
||
|
|
|
||
|
|
<span class="k">def</span> <span class="nf">observation</span><span class="p">(</span><span class="bp">self</span><span class="p">,</span> <span class="n">observation</span><span class="p">:</span> <span class="n">ObsType</span><span class="p">)</span> <span class="o">-></span> <span class="n">ObsType</span><span class="p">:</span>
|
||
|
|
<span class="w"> </span><span class="sd">"""Return the delayed observation."""</span>
|
||
|
|
<span class="bp">self</span><span class="o">.</span><span class="n">observation_queue</span><span class="o">.</span><span class="n">append</span><span class="p">(</span><span class="n">observation</span><span class="p">)</span>
|
||
|
|
|
||
|
|
<span class="k">if</span> <span class="nb">len</span><span class="p">(</span><span class="bp">self</span><span class="o">.</span><span class="n">observation_queue</span><span class="p">)</span> <span class="o">></span> <span class="bp">self</span><span class="o">.</span><span class="n">delay</span><span class="p">:</span>
|
||
|
|
<span class="k">return</span> <span class="bp">self</span><span class="o">.</span><span class="n">observation_queue</span><span class="o">.</span><span class="n">popleft</span><span class="p">()</span>
|
||
|
|
<span class="k">else</span><span class="p">:</span>
|
||
|
|
<span class="k">return</span> <span class="n">create_zero_array</span><span class="p">(</span><span class="bp">self</span><span class="o">.</span><span class="n">observation_space</span><span class="p">)</span></div>
|
||
|
|
|
||
|
|
|
||
|
|
|
||
|
|
<div class="viewcode-block" id="TimeAwareObservation">
|
||
|
|
<a class="viewcode-back" href="../../../../api/wrappers/observation_wrappers/#gymnasium.wrappers.TimeAwareObservation">[docs]</a>
|
||
|
|
<span class="k">class</span> <span class="nc">TimeAwareObservation</span><span class="p">(</span>
|
||
|
|
<span class="n">gym</span><span class="o">.</span><span class="n">ObservationWrapper</span><span class="p">[</span><span class="n">WrapperObsType</span><span class="p">,</span> <span class="n">ActType</span><span class="p">,</span> <span class="n">ObsType</span><span class="p">],</span>
|
||
|
|
<span class="n">gym</span><span class="o">.</span><span class="n">utils</span><span class="o">.</span><span class="n">RecordConstructorArgs</span><span class="p">,</span>
|
||
|
|
<span class="p">):</span>
|
||
|
|
<span class="w"> </span><span class="sd">"""Augment the observation with the number of time steps taken within an episode.</span>
|
||
|
|
|
||
|
|
<span class="sd"> The :attr:`normalize_time` if ``True`` represents time as a normalized value between [0,1]</span>
|
||
|
|
<span class="sd"> otherwise if ``False``, the current timestep is an integer.</span>
|
||
|
|
|
||
|
|
<span class="sd"> For environments with ``Dict`` observation spaces, the time information is automatically</span>
|
||
|
|
<span class="sd"> added in the key `"time"` (can be changed through :attr:`dict_time_key`) and for environments with ``Tuple``</span>
|
||
|
|
<span class="sd"> observation space, the time information is added as the final element in the tuple.</span>
|
||
|
|
<span class="sd"> Otherwise, the observation space is transformed into a ``Dict`` observation space with two keys,</span>
|
||
|
|
<span class="sd"> `"obs"` for the base environment's observation and `"time"` for the time information.</span>
|
||
|
|
|
||
|
|
<span class="sd"> To flatten the observation, use the :attr:`flatten` parameter which will use the</span>
|
||
|
|
<span class="sd"> :func:`gymnasium.spaces.utils.flatten` function.</span>
|
||
|
|
|
||
|
|
<span class="sd"> No vector version of the wrapper exists.</span>
|
||
|
|
|
||
|
|
<span class="sd"> Example:</span>
|
||
|
|
<span class="sd"> >>> import gymnasium as gym</span>
|
||
|
|
<span class="sd"> >>> from gymnasium.wrappers import TimeAwareObservation</span>
|
||
|
|
<span class="sd"> >>> env = gym.make("CartPole-v1")</span>
|
||
|
|
<span class="sd"> >>> env = TimeAwareObservation(env)</span>
|
||
|
|
<span class="sd"> >>> env.observation_space</span>
|
||
|
|
<span class="sd"> Box([-4.80000019e+00 -3.40282347e+38 -4.18879032e-01 -3.40282347e+38</span>
|
||
|
|
<span class="sd"> 0.00000000e+00], [4.80000019e+00 3.40282347e+38 4.18879032e-01 3.40282347e+38</span>
|
||
|
|
<span class="sd"> 5.00000000e+02], (5,), float64)</span>
|
||
|
|
<span class="sd"> >>> env.reset(seed=42)[0]</span>
|
||
|
|
<span class="sd"> array([ 0.0273956 , -0.00611216, 0.03585979, 0.0197368 , 0. ])</span>
|
||
|
|
<span class="sd"> >>> _ = env.action_space.seed(42)</span>
|
||
|
|
<span class="sd"> >>> env.step(env.action_space.sample())[0]</span>
|
||
|
|
<span class="sd"> array([ 0.02727336, -0.20172954, 0.03625453, 0.32351476, 1. ])</span>
|
||
|
|
|
||
|
|
<span class="sd"> Normalize time observation space example:</span>
|
||
|
|
<span class="sd"> >>> env = gym.make('CartPole-v1')</span>
|
||
|
|
<span class="sd"> >>> env = TimeAwareObservation(env, normalize_time=True)</span>
|
||
|
|
<span class="sd"> >>> env.observation_space</span>
|
||
|
|
<span class="sd"> Box([-4.8000002e+00 -3.4028235e+38 -4.1887903e-01 -3.4028235e+38</span>
|
||
|
|
<span class="sd"> 0.0000000e+00], [4.8000002e+00 3.4028235e+38 4.1887903e-01 3.4028235e+38 1.0000000e+00], (5,), float32)</span>
|
||
|
|
<span class="sd"> >>> env.reset(seed=42)[0]</span>
|
||
|
|
<span class="sd"> array([ 0.0273956 , -0.00611216, 0.03585979, 0.0197368 , 0. ],</span>
|
||
|
|
<span class="sd"> dtype=float32)</span>
|
||
|
|
<span class="sd"> >>> _ = env.action_space.seed(42)</span>
|
||
|
|
<span class="sd"> >>> env.step(env.action_space.sample())[0]</span>
|
||
|
|
<span class="sd"> array([ 0.02727336, -0.20172954, 0.03625453, 0.32351476, 0.002 ],</span>
|
||
|
|
<span class="sd"> dtype=float32)</span>
|
||
|
|
|
||
|
|
<span class="sd"> Flatten observation space example:</span>
|
||
|
|
<span class="sd"> >>> env = gym.make("CartPole-v1")</span>
|
||
|
|
<span class="sd"> >>> env = TimeAwareObservation(env, flatten=False)</span>
|
||
|
|
<span class="sd"> >>> env.observation_space</span>
|
||
|
|
<span class="sd"> Dict('obs': Box([-4.8000002e+00 -3.4028235e+38 -4.1887903e-01 -3.4028235e+38], [4.8000002e+00 3.4028235e+38 4.1887903e-01 3.4028235e+38], (4,), float32), 'time': Box(0, 500, (1,), int32))</span>
|
||
|
|
<span class="sd"> >>> env.reset(seed=42)[0]</span>
|
||
|
|
<span class="sd"> {'obs': array([ 0.0273956 , -0.00611216, 0.03585979, 0.0197368 ], dtype=float32), 'time': array([0], dtype=int32)}</span>
|
||
|
|
<span class="sd"> >>> _ = env.action_space.seed(42)</span>
|
||
|
|
<span class="sd"> >>> env.step(env.action_space.sample())[0]</span>
|
||
|
|
<span class="sd"> {'obs': array([ 0.02727336, -0.20172954, 0.03625453, 0.32351476], dtype=float32), 'time': array([1], dtype=int32)}</span>
|
||
|
|
|
||
|
|
<span class="sd"> Change logs:</span>
|
||
|
|
<span class="sd"> * v0.18.0 - Initially added</span>
|
||
|
|
<span class="sd"> * v1.0.0 - Remove vector environment support, add ``flatten`` and ``normalize_time`` parameters</span>
|
||
|
|
<span class="sd"> """</span>
|
||
|
|
|
||
|
|
<span class="k">def</span> <span class="fm">__init__</span><span class="p">(</span>
|
||
|
|
<span class="bp">self</span><span class="p">,</span>
|
||
|
|
<span class="n">env</span><span class="p">:</span> <span class="n">gym</span><span class="o">.</span><span class="n">Env</span><span class="p">[</span><span class="n">ObsType</span><span class="p">,</span> <span class="n">ActType</span><span class="p">],</span>
|
||
|
|
<span class="n">flatten</span><span class="p">:</span> <span class="nb">bool</span> <span class="o">=</span> <span class="kc">True</span><span class="p">,</span>
|
||
|
|
<span class="n">normalize_time</span><span class="p">:</span> <span class="nb">bool</span> <span class="o">=</span> <span class="kc">False</span><span class="p">,</span>
|
||
|
|
<span class="o">*</span><span class="p">,</span>
|
||
|
|
<span class="n">dict_time_key</span><span class="p">:</span> <span class="nb">str</span> <span class="o">=</span> <span class="s2">"time"</span><span class="p">,</span>
|
||
|
|
<span class="p">):</span>
|
||
|
|
<span class="w"> </span><span class="sd">"""Initialize :class:`TimeAwareObservation`.</span>
|
||
|
|
|
||
|
|
<span class="sd"> Args:</span>
|
||
|
|
<span class="sd"> env: The environment to apply the wrapper</span>
|
||
|
|
<span class="sd"> flatten: Flatten the observation to a `Box` of a single dimension</span>
|
||
|
|
<span class="sd"> normalize_time: if `True` return time in the range [0,1]</span>
|
||
|
|
<span class="sd"> otherwise return time as remaining timesteps before truncation</span>
|
||
|
|
<span class="sd"> dict_time_key: For environment with a ``Dict`` observation space, the key for the time space. By default, `"time"`.</span>
|
||
|
|
<span class="sd"> """</span>
|
||
|
|
<span class="n">gym</span><span class="o">.</span><span class="n">utils</span><span class="o">.</span><span class="n">RecordConstructorArgs</span><span class="o">.</span><span class="fm">__init__</span><span class="p">(</span>
|
||
|
|
<span class="bp">self</span><span class="p">,</span>
|
||
|
|
<span class="n">flatten</span><span class="o">=</span><span class="n">flatten</span><span class="p">,</span>
|
||
|
|
<span class="n">normalize_time</span><span class="o">=</span><span class="n">normalize_time</span><span class="p">,</span>
|
||
|
|
<span class="n">dict_time_key</span><span class="o">=</span><span class="n">dict_time_key</span><span class="p">,</span>
|
||
|
|
<span class="p">)</span>
|
||
|
|
<span class="n">gym</span><span class="o">.</span><span class="n">ObservationWrapper</span><span class="o">.</span><span class="fm">__init__</span><span class="p">(</span><span class="bp">self</span><span class="p">,</span> <span class="n">env</span><span class="p">)</span>
|
||
|
|
|
||
|
|
<span class="bp">self</span><span class="o">.</span><span class="n">flatten</span><span class="p">:</span> <span class="n">Final</span><span class="p">[</span><span class="nb">bool</span><span class="p">]</span> <span class="o">=</span> <span class="n">flatten</span>
|
||
|
|
<span class="bp">self</span><span class="o">.</span><span class="n">normalize_time</span><span class="p">:</span> <span class="n">Final</span><span class="p">[</span><span class="nb">bool</span><span class="p">]</span> <span class="o">=</span> <span class="n">normalize_time</span>
|
||
|
|
|
||
|
|
<span class="c1"># We don't need to keep if a TimeLimit wrapper exists as `spec` will do that work for us now</span>
|
||
|
|
<span class="k">if</span> <span class="n">env</span><span class="o">.</span><span class="n">spec</span> <span class="ow">is</span> <span class="ow">not</span> <span class="kc">None</span> <span class="ow">and</span> <span class="n">env</span><span class="o">.</span><span class="n">spec</span><span class="o">.</span><span class="n">max_episode_steps</span> <span class="ow">is</span> <span class="ow">not</span> <span class="kc">None</span><span class="p">:</span>
|
||
|
|
<span class="bp">self</span><span class="o">.</span><span class="n">max_timesteps</span> <span class="o">=</span> <span class="n">env</span><span class="o">.</span><span class="n">spec</span><span class="o">.</span><span class="n">max_episode_steps</span>
|
||
|
|
<span class="k">else</span><span class="p">:</span>
|
||
|
|
<span class="k">raise</span> <span class="ne">ValueError</span><span class="p">(</span>
|
||
|
|
<span class="s2">"The environment must be wrapped by a TimeLimit wrapper or the spec specify a `max_episode_steps`."</span>
|
||
|
|
<span class="p">)</span>
|
||
|
|
|
||
|
|
<span class="bp">self</span><span class="o">.</span><span class="n">timesteps</span><span class="p">:</span> <span class="nb">int</span> <span class="o">=</span> <span class="mi">0</span>
|
||
|
|
|
||
|
|
<span class="c1"># Find the normalized time space</span>
|
||
|
|
<span class="k">if</span> <span class="bp">self</span><span class="o">.</span><span class="n">normalize_time</span><span class="p">:</span>
|
||
|
|
<span class="bp">self</span><span class="o">.</span><span class="n">_time_preprocess_func</span> <span class="o">=</span> <span class="k">lambda</span> <span class="n">time</span><span class="p">:</span> <span class="n">np</span><span class="o">.</span><span class="n">array</span><span class="p">(</span>
|
||
|
|
<span class="p">[</span><span class="n">time</span> <span class="o">/</span> <span class="bp">self</span><span class="o">.</span><span class="n">max_timesteps</span><span class="p">],</span> <span class="n">dtype</span><span class="o">=</span><span class="n">np</span><span class="o">.</span><span class="n">float32</span>
|
||
|
|
<span class="p">)</span>
|
||
|
|
<span class="n">time_space</span> <span class="o">=</span> <span class="n">Box</span><span class="p">(</span><span class="mf">0.0</span><span class="p">,</span> <span class="mf">1.0</span><span class="p">)</span>
|
||
|
|
<span class="k">else</span><span class="p">:</span>
|
||
|
|
<span class="bp">self</span><span class="o">.</span><span class="n">_time_preprocess_func</span> <span class="o">=</span> <span class="k">lambda</span> <span class="n">time</span><span class="p">:</span> <span class="n">np</span><span class="o">.</span><span class="n">array</span><span class="p">([</span><span class="n">time</span><span class="p">],</span> <span class="n">dtype</span><span class="o">=</span><span class="n">np</span><span class="o">.</span><span class="n">int32</span><span class="p">)</span>
|
||
|
|
<span class="n">time_space</span> <span class="o">=</span> <span class="n">Box</span><span class="p">(</span><span class="mi">0</span><span class="p">,</span> <span class="bp">self</span><span class="o">.</span><span class="n">max_timesteps</span><span class="p">,</span> <span class="n">dtype</span><span class="o">=</span><span class="n">np</span><span class="o">.</span><span class="n">int32</span><span class="p">)</span>
|
||
|
|
|
||
|
|
<span class="c1"># Find the observation space</span>
|
||
|
|
<span class="k">if</span> <span class="nb">isinstance</span><span class="p">(</span><span class="n">env</span><span class="o">.</span><span class="n">observation_space</span><span class="p">,</span> <span class="n">Dict</span><span class="p">):</span>
|
||
|
|
<span class="k">assert</span> <span class="n">dict_time_key</span> <span class="ow">not</span> <span class="ow">in</span> <span class="n">env</span><span class="o">.</span><span class="n">observation_space</span><span class="o">.</span><span class="n">keys</span><span class="p">()</span>
|
||
|
|
<span class="n">observation_space</span> <span class="o">=</span> <span class="n">Dict</span><span class="p">(</span>
|
||
|
|
<span class="p">{</span><span class="n">dict_time_key</span><span class="p">:</span> <span class="n">time_space</span><span class="p">,</span> <span class="o">**</span><span class="n">env</span><span class="o">.</span><span class="n">observation_space</span><span class="o">.</span><span class="n">spaces</span><span class="p">}</span>
|
||
|
|
<span class="p">)</span>
|
||
|
|
<span class="bp">self</span><span class="o">.</span><span class="n">_append_data_func</span> <span class="o">=</span> <span class="k">lambda</span> <span class="n">obs</span><span class="p">,</span> <span class="n">time</span><span class="p">:</span> <span class="p">{</span><span class="n">dict_time_key</span><span class="p">:</span> <span class="n">time</span><span class="p">,</span> <span class="o">**</span><span class="n">obs</span><span class="p">}</span>
|
||
|
|
<span class="k">elif</span> <span class="nb">isinstance</span><span class="p">(</span><span class="n">env</span><span class="o">.</span><span class="n">observation_space</span><span class="p">,</span> <span class="n">Tuple</span><span class="p">):</span>
|
||
|
|
<span class="n">observation_space</span> <span class="o">=</span> <span class="n">Tuple</span><span class="p">(</span><span class="n">env</span><span class="o">.</span><span class="n">observation_space</span><span class="o">.</span><span class="n">spaces</span> <span class="o">+</span> <span class="p">(</span><span class="n">time_space</span><span class="p">,))</span>
|
||
|
|
<span class="bp">self</span><span class="o">.</span><span class="n">_append_data_func</span> <span class="o">=</span> <span class="k">lambda</span> <span class="n">obs</span><span class="p">,</span> <span class="n">time</span><span class="p">:</span> <span class="n">obs</span> <span class="o">+</span> <span class="p">(</span><span class="n">time</span><span class="p">,)</span>
|
||
|
|
<span class="k">else</span><span class="p">:</span>
|
||
|
|
<span class="n">observation_space</span> <span class="o">=</span> <span class="n">Dict</span><span class="p">(</span><span class="n">obs</span><span class="o">=</span><span class="n">env</span><span class="o">.</span><span class="n">observation_space</span><span class="p">,</span> <span class="n">time</span><span class="o">=</span><span class="n">time_space</span><span class="p">)</span>
|
||
|
|
<span class="bp">self</span><span class="o">.</span><span class="n">_append_data_func</span> <span class="o">=</span> <span class="k">lambda</span> <span class="n">obs</span><span class="p">,</span> <span class="n">time</span><span class="p">:</span> <span class="p">{</span><span class="s2">"obs"</span><span class="p">:</span> <span class="n">obs</span><span class="p">,</span> <span class="s2">"time"</span><span class="p">:</span> <span class="n">time</span><span class="p">}</span>
|
||
|
|
|
||
|
|
<span class="c1"># If to flatten the observation space</span>
|
||
|
|
<span class="k">if</span> <span class="bp">self</span><span class="o">.</span><span class="n">flatten</span><span class="p">:</span>
|
||
|
|
<span class="bp">self</span><span class="o">.</span><span class="n">observation_space</span><span class="p">:</span> <span class="n">gym</span><span class="o">.</span><span class="n">Space</span><span class="p">[</span><span class="n">WrapperObsType</span><span class="p">]</span> <span class="o">=</span> <span class="n">spaces</span><span class="o">.</span><span class="n">flatten_space</span><span class="p">(</span>
|
||
|
|
<span class="n">observation_space</span>
|
||
|
|
<span class="p">)</span>
|
||
|
|
<span class="bp">self</span><span class="o">.</span><span class="n">_obs_postprocess_func</span> <span class="o">=</span> <span class="k">lambda</span> <span class="n">obs</span><span class="p">:</span> <span class="n">spaces</span><span class="o">.</span><span class="n">flatten</span><span class="p">(</span>
|
||
|
|
<span class="n">observation_space</span><span class="p">,</span> <span class="n">obs</span>
|
||
|
|
<span class="p">)</span>
|
||
|
|
<span class="k">else</span><span class="p">:</span>
|
||
|
|
<span class="bp">self</span><span class="o">.</span><span class="n">observation_space</span><span class="p">:</span> <span class="n">gym</span><span class="o">.</span><span class="n">Space</span><span class="p">[</span><span class="n">WrapperObsType</span><span class="p">]</span> <span class="o">=</span> <span class="n">observation_space</span>
|
||
|
|
<span class="bp">self</span><span class="o">.</span><span class="n">_obs_postprocess_func</span> <span class="o">=</span> <span class="k">lambda</span> <span class="n">obs</span><span class="p">:</span> <span class="n">obs</span>
|
||
|
|
|
||
|
|
<span class="k">def</span> <span class="nf">observation</span><span class="p">(</span><span class="bp">self</span><span class="p">,</span> <span class="n">observation</span><span class="p">:</span> <span class="n">ObsType</span><span class="p">)</span> <span class="o">-></span> <span class="n">WrapperObsType</span><span class="p">:</span>
|
||
|
|
<span class="w"> </span><span class="sd">"""Adds to the observation with the current time information.</span>
|
||
|
|
|
||
|
|
<span class="sd"> Args:</span>
|
||
|
|
<span class="sd"> observation: The observation to add the time step to</span>
|
||
|
|
|
||
|
|
<span class="sd"> Returns:</span>
|
||
|
|
<span class="sd"> The observation with the time information appended to it</span>
|
||
|
|
<span class="sd"> """</span>
|
||
|
|
<span class="k">return</span> <span class="bp">self</span><span class="o">.</span><span class="n">_obs_postprocess_func</span><span class="p">(</span>
|
||
|
|
<span class="bp">self</span><span class="o">.</span><span class="n">_append_data_func</span><span class="p">(</span>
|
||
|
|
<span class="n">observation</span><span class="p">,</span> <span class="bp">self</span><span class="o">.</span><span class="n">_time_preprocess_func</span><span class="p">(</span><span class="bp">self</span><span class="o">.</span><span class="n">timesteps</span><span class="p">)</span>
|
||
|
|
<span class="p">)</span>
|
||
|
|
<span class="p">)</span>
|
||
|
|
|
||
|
|
<span class="k">def</span> <span class="nf">step</span><span class="p">(</span>
|
||
|
|
<span class="bp">self</span><span class="p">,</span> <span class="n">action</span><span class="p">:</span> <span class="n">ActType</span>
|
||
|
|
<span class="p">)</span> <span class="o">-></span> <span class="nb">tuple</span><span class="p">[</span><span class="n">WrapperObsType</span><span class="p">,</span> <span class="n">SupportsFloat</span><span class="p">,</span> <span class="nb">bool</span><span class="p">,</span> <span class="nb">bool</span><span class="p">,</span> <span class="nb">dict</span><span class="p">[</span><span class="nb">str</span><span class="p">,</span> <span class="n">Any</span><span class="p">]]:</span>
|
||
|
|
<span class="w"> </span><span class="sd">"""Steps through the environment, incrementing the time step.</span>
|
||
|
|
|
||
|
|
<span class="sd"> Args:</span>
|
||
|
|
<span class="sd"> action: The action to take</span>
|
||
|
|
|
||
|
|
<span class="sd"> Returns:</span>
|
||
|
|
<span class="sd"> The environment's step using the action with the next observation containing the timestep info</span>
|
||
|
|
<span class="sd"> """</span>
|
||
|
|
<span class="bp">self</span><span class="o">.</span><span class="n">timesteps</span> <span class="o">+=</span> <span class="mi">1</span>
|
||
|
|
|
||
|
|
<span class="k">return</span> <span class="nb">super</span><span class="p">()</span><span class="o">.</span><span class="n">step</span><span class="p">(</span><span class="n">action</span><span class="p">)</span>
|
||
|
|
|
||
|
|
<span class="k">def</span> <span class="nf">reset</span><span class="p">(</span>
|
||
|
|
<span class="bp">self</span><span class="p">,</span> <span class="o">*</span><span class="p">,</span> <span class="n">seed</span><span class="p">:</span> <span class="nb">int</span> <span class="o">|</span> <span class="kc">None</span> <span class="o">=</span> <span class="kc">None</span><span class="p">,</span> <span class="n">options</span><span class="p">:</span> <span class="nb">dict</span><span class="p">[</span><span class="nb">str</span><span class="p">,</span> <span class="n">Any</span><span class="p">]</span> <span class="o">|</span> <span class="kc">None</span> <span class="o">=</span> <span class="kc">None</span>
|
||
|
|
<span class="p">)</span> <span class="o">-></span> <span class="nb">tuple</span><span class="p">[</span><span class="n">WrapperObsType</span><span class="p">,</span> <span class="nb">dict</span><span class="p">[</span><span class="nb">str</span><span class="p">,</span> <span class="n">Any</span><span class="p">]]:</span>
|
||
|
|
<span class="w"> </span><span class="sd">"""Reset the environment setting the time to zero.</span>
|
||
|
|
|
||
|
|
<span class="sd"> Args:</span>
|
||
|
|
<span class="sd"> seed: The seed to reset the environment</span>
|
||
|
|
<span class="sd"> options: The options used to reset the environment</span>
|
||
|
|
|
||
|
|
<span class="sd"> Returns:</span>
|
||
|
|
<span class="sd"> Resets the environment with the initial timestep info added the observation</span>
|
||
|
|
<span class="sd"> """</span>
|
||
|
|
<span class="bp">self</span><span class="o">.</span><span class="n">timesteps</span> <span class="o">=</span> <span class="mi">0</span>
|
||
|
|
|
||
|
|
<span class="k">return</span> <span class="nb">super</span><span class="p">()</span><span class="o">.</span><span class="n">reset</span><span class="p">(</span><span class="n">seed</span><span class="o">=</span><span class="n">seed</span><span class="p">,</span> <span class="n">options</span><span class="o">=</span><span class="n">options</span><span class="p">)</span></div>
|
||
|
|
|
||
|
|
|
||
|
|
|
||
|
|
<div class="viewcode-block" id="FrameStackObservation">
|
||
|
|
<a class="viewcode-back" href="../../../../api/wrappers/observation_wrappers/#gymnasium.wrappers.FrameStackObservation">[docs]</a>
|
||
|
|
<span class="k">class</span> <span class="nc">FrameStackObservation</span><span class="p">(</span>
|
||
|
|
<span class="n">gym</span><span class="o">.</span><span class="n">Wrapper</span><span class="p">[</span><span class="n">WrapperObsType</span><span class="p">,</span> <span class="n">ActType</span><span class="p">,</span> <span class="n">ObsType</span><span class="p">,</span> <span class="n">ActType</span><span class="p">],</span>
|
||
|
|
<span class="n">gym</span><span class="o">.</span><span class="n">utils</span><span class="o">.</span><span class="n">RecordConstructorArgs</span><span class="p">,</span>
|
||
|
|
<span class="p">):</span>
|
||
|
|
<span class="w"> </span><span class="sd">"""Stacks the observations from the last ``N`` time steps in a rolling manner.</span>
|
||
|
|
|
||
|
|
<span class="sd"> For example, if the number of stacks is 4, then the returned observation contains</span>
|
||
|
|
<span class="sd"> the most recent 4 observations. For environment 'Pendulum-v1', the original observation</span>
|
||
|
|
<span class="sd"> is an array with shape [3], so if we stack 4 observations, the processed observation</span>
|
||
|
|
<span class="sd"> has shape [4, 3].</span>
|
||
|
|
|
||
|
|
<span class="sd"> Users have options for the padded observation used:</span>
|
||
|
|
|
||
|
|
<span class="sd"> * "reset" (default) - The reset value is repeated</span>
|
||
|
|
<span class="sd"> * "zero" - A "zero"-like instance of the observation space</span>
|
||
|
|
<span class="sd"> * custom - An instance of the observation space</span>
|
||
|
|
|
||
|
|
<span class="sd"> No vector version of the wrapper exists.</span>
|
||
|
|
|
||
|
|
<span class="sd"> Example:</span>
|
||
|
|
<span class="sd"> >>> import gymnasium as gym</span>
|
||
|
|
<span class="sd"> >>> from gymnasium.wrappers import FrameStackObservation</span>
|
||
|
|
<span class="sd"> >>> env = gym.make("CarRacing-v2")</span>
|
||
|
|
<span class="sd"> >>> env = FrameStackObservation(env, stack_size=4)</span>
|
||
|
|
<span class="sd"> >>> env.observation_space</span>
|
||
|
|
<span class="sd"> Box(0, 255, (4, 96, 96, 3), uint8)</span>
|
||
|
|
<span class="sd"> >>> obs, _ = env.reset()</span>
|
||
|
|
<span class="sd"> >>> obs.shape</span>
|
||
|
|
<span class="sd"> (4, 96, 96, 3)</span>
|
||
|
|
|
||
|
|
<span class="sd"> Example with different padding observations:</span>
|
||
|
|
<span class="sd"> >>> env = gym.make("CartPole-v1")</span>
|
||
|
|
<span class="sd"> >>> env.reset(seed=123)</span>
|
||
|
|
<span class="sd"> (array([ 0.01823519, -0.0446179 , -0.02796401, -0.03156282], dtype=float32), {})</span>
|
||
|
|
<span class="sd"> >>> stacked_env = FrameStackObservation(env, 3) # the default is padding_type="reset"</span>
|
||
|
|
<span class="sd"> >>> stacked_env.reset(seed=123)</span>
|
||
|
|
<span class="sd"> (array([[ 0.01823519, -0.0446179 , -0.02796401, -0.03156282],</span>
|
||
|
|
<span class="sd"> [ 0.01823519, -0.0446179 , -0.02796401, -0.03156282],</span>
|
||
|
|
<span class="sd"> [ 0.01823519, -0.0446179 , -0.02796401, -0.03156282]],</span>
|
||
|
|
<span class="sd"> dtype=float32), {})</span>
|
||
|
|
|
||
|
|
|
||
|
|
<span class="sd"> >>> stacked_env = FrameStackObservation(env, 3, padding_type="zero")</span>
|
||
|
|
<span class="sd"> >>> stacked_env.reset(seed=123)</span>
|
||
|
|
<span class="sd"> (array([[ 0. , 0. , 0. , 0. ],</span>
|
||
|
|
<span class="sd"> [ 0. , 0. , 0. , 0. ],</span>
|
||
|
|
<span class="sd"> [ 0.01823519, -0.0446179 , -0.02796401, -0.03156282]],</span>
|
||
|
|
<span class="sd"> dtype=float32), {})</span>
|
||
|
|
<span class="sd"> >>> stacked_env = FrameStackObservation(env, 3, padding_type=np.array([1, -1, 0, 2], dtype=np.float32))</span>
|
||
|
|
<span class="sd"> >>> stacked_env.reset(seed=123)</span>
|
||
|
|
<span class="sd"> (array([[ 1. , -1. , 0. , 2. ],</span>
|
||
|
|
<span class="sd"> [ 1. , -1. , 0. , 2. ],</span>
|
||
|
|
<span class="sd"> [ 0.01823519, -0.0446179 , -0.02796401, -0.03156282]],</span>
|
||
|
|
<span class="sd"> dtype=float32), {})</span>
|
||
|
|
|
||
|
|
<span class="sd"> Change logs:</span>
|
||
|
|
<span class="sd"> * v0.15.0 - Initially add as ``FrameStack`` with support for lz4</span>
|
||
|
|
<span class="sd"> * v1.0.0 - Rename to ``FrameStackObservation`` and remove lz4 and ``LazyFrame`` support</span>
|
||
|
|
<span class="sd"> along with adding the ``padding_type`` parameter</span>
|
||
|
|
|
||
|
|
<span class="sd"> """</span>
|
||
|
|
|
||
|
|
<span class="k">def</span> <span class="fm">__init__</span><span class="p">(</span>
|
||
|
|
<span class="bp">self</span><span class="p">,</span>
|
||
|
|
<span class="n">env</span><span class="p">:</span> <span class="n">gym</span><span class="o">.</span><span class="n">Env</span><span class="p">[</span><span class="n">ObsType</span><span class="p">,</span> <span class="n">ActType</span><span class="p">],</span>
|
||
|
|
<span class="n">stack_size</span><span class="p">:</span> <span class="nb">int</span><span class="p">,</span>
|
||
|
|
<span class="o">*</span><span class="p">,</span>
|
||
|
|
<span class="n">padding_type</span><span class="p">:</span> <span class="nb">str</span> <span class="o">|</span> <span class="n">ObsType</span> <span class="o">=</span> <span class="s2">"reset"</span><span class="p">,</span>
|
||
|
|
<span class="p">):</span>
|
||
|
|
<span class="w"> </span><span class="sd">"""Observation wrapper that stacks the observations in a rolling manner.</span>
|
||
|
|
|
||
|
|
<span class="sd"> Args:</span>
|
||
|
|
<span class="sd"> env: The environment to apply the wrapper</span>
|
||
|
|
<span class="sd"> stack_size: The number of frames to stack.</span>
|
||
|
|
<span class="sd"> padding_type: The padding type to use when stacking the observations, options: "reset", "zero", custom obs</span>
|
||
|
|
<span class="sd"> """</span>
|
||
|
|
<span class="n">gym</span><span class="o">.</span><span class="n">utils</span><span class="o">.</span><span class="n">RecordConstructorArgs</span><span class="o">.</span><span class="fm">__init__</span><span class="p">(</span>
|
||
|
|
<span class="bp">self</span><span class="p">,</span> <span class="n">stack_size</span><span class="o">=</span><span class="n">stack_size</span><span class="p">,</span> <span class="n">padding_type</span><span class="o">=</span><span class="n">padding_type</span>
|
||
|
|
<span class="p">)</span>
|
||
|
|
<span class="n">gym</span><span class="o">.</span><span class="n">Wrapper</span><span class="o">.</span><span class="fm">__init__</span><span class="p">(</span><span class="bp">self</span><span class="p">,</span> <span class="n">env</span><span class="p">)</span>
|
||
|
|
|
||
|
|
<span class="k">if</span> <span class="ow">not</span> <span class="n">np</span><span class="o">.</span><span class="n">issubdtype</span><span class="p">(</span><span class="nb">type</span><span class="p">(</span><span class="n">stack_size</span><span class="p">),</span> <span class="n">np</span><span class="o">.</span><span class="n">integer</span><span class="p">):</span>
|
||
|
|
<span class="k">raise</span> <span class="ne">TypeError</span><span class="p">(</span>
|
||
|
|
<span class="sa">f</span><span class="s2">"The stack_size is expected to be an integer, actual type: </span><span class="si">{</span><span class="nb">type</span><span class="p">(</span><span class="n">stack_size</span><span class="p">)</span><span class="si">}</span><span class="s2">"</span>
|
||
|
|
<span class="p">)</span>
|
||
|
|
<span class="k">if</span> <span class="ow">not</span> <span class="mi">1</span> <span class="o"><</span> <span class="n">stack_size</span><span class="p">:</span>
|
||
|
|
<span class="k">raise</span> <span class="ne">ValueError</span><span class="p">(</span>
|
||
|
|
<span class="sa">f</span><span class="s2">"The stack_size needs to be greater than one, actual value: </span><span class="si">{</span><span class="n">stack_size</span><span class="si">}</span><span class="s2">"</span>
|
||
|
|
<span class="p">)</span>
|
||
|
|
<span class="k">if</span> <span class="nb">isinstance</span><span class="p">(</span><span class="n">padding_type</span><span class="p">,</span> <span class="nb">str</span><span class="p">)</span> <span class="ow">and</span> <span class="p">(</span>
|
||
|
|
<span class="n">padding_type</span> <span class="o">==</span> <span class="s2">"reset"</span> <span class="ow">or</span> <span class="n">padding_type</span> <span class="o">==</span> <span class="s2">"zero"</span>
|
||
|
|
<span class="p">):</span>
|
||
|
|
<span class="bp">self</span><span class="o">.</span><span class="n">padding_value</span><span class="p">:</span> <span class="n">ObsType</span> <span class="o">=</span> <span class="n">create_zero_array</span><span class="p">(</span><span class="n">env</span><span class="o">.</span><span class="n">observation_space</span><span class="p">)</span>
|
||
|
|
<span class="k">elif</span> <span class="n">padding_type</span> <span class="ow">in</span> <span class="n">env</span><span class="o">.</span><span class="n">observation_space</span><span class="p">:</span>
|
||
|
|
<span class="bp">self</span><span class="o">.</span><span class="n">padding_value</span> <span class="o">=</span> <span class="n">padding_type</span>
|
||
|
|
<span class="n">padding_type</span> <span class="o">=</span> <span class="s2">"_custom"</span>
|
||
|
|
<span class="k">else</span><span class="p">:</span>
|
||
|
|
<span class="k">if</span> <span class="nb">isinstance</span><span class="p">(</span><span class="n">padding_type</span><span class="p">,</span> <span class="nb">str</span><span class="p">):</span>
|
||
|
|
<span class="k">raise</span> <span class="ne">ValueError</span><span class="p">(</span> <span class="c1"># we are guessing that the user just entered the "reset" or "zero" wrong</span>
|
||
|
|
<span class="sa">f</span><span class="s2">"Unexpected `padding_type`, expected 'reset', 'zero' or a custom observation space, actual value: </span><span class="si">{</span><span class="n">padding_type</span><span class="si">!r}</span><span class="s2">"</span>
|
||
|
|
<span class="p">)</span>
|
||
|
|
<span class="k">else</span><span class="p">:</span>
|
||
|
|
<span class="k">raise</span> <span class="ne">ValueError</span><span class="p">(</span>
|
||
|
|
<span class="sa">f</span><span class="s2">"Unexpected `padding_type`, expected 'reset', 'zero' or a custom observation space, actual value: </span><span class="si">{</span><span class="n">padding_type</span><span class="si">!r}</span><span class="s2"> not an instance of env observation (</span><span class="si">{</span><span class="n">env</span><span class="o">.</span><span class="n">observation_space</span><span class="si">}</span><span class="s2">)"</span>
|
||
|
|
<span class="p">)</span>
|
||
|
|
|
||
|
|
<span class="bp">self</span><span class="o">.</span><span class="n">observation_space</span> <span class="o">=</span> <span class="n">batch_space</span><span class="p">(</span><span class="n">env</span><span class="o">.</span><span class="n">observation_space</span><span class="p">,</span> <span class="n">n</span><span class="o">=</span><span class="n">stack_size</span><span class="p">)</span>
|
||
|
|
<span class="bp">self</span><span class="o">.</span><span class="n">stack_size</span><span class="p">:</span> <span class="n">Final</span><span class="p">[</span><span class="nb">int</span><span class="p">]</span> <span class="o">=</span> <span class="n">stack_size</span>
|
||
|
|
<span class="bp">self</span><span class="o">.</span><span class="n">padding_type</span><span class="p">:</span> <span class="n">Final</span><span class="p">[</span><span class="nb">str</span><span class="p">]</span> <span class="o">=</span> <span class="n">padding_type</span>
|
||
|
|
|
||
|
|
<span class="bp">self</span><span class="o">.</span><span class="n">obs_queue</span> <span class="o">=</span> <span class="n">deque</span><span class="p">(</span>
|
||
|
|
<span class="p">[</span><span class="bp">self</span><span class="o">.</span><span class="n">padding_value</span> <span class="k">for</span> <span class="n">_</span> <span class="ow">in</span> <span class="nb">range</span><span class="p">(</span><span class="bp">self</span><span class="o">.</span><span class="n">stack_size</span><span class="p">)],</span> <span class="n">maxlen</span><span class="o">=</span><span class="bp">self</span><span class="o">.</span><span class="n">stack_size</span>
|
||
|
|
<span class="p">)</span>
|
||
|
|
<span class="bp">self</span><span class="o">.</span><span class="n">stacked_obs</span> <span class="o">=</span> <span class="n">create_empty_array</span><span class="p">(</span><span class="n">env</span><span class="o">.</span><span class="n">observation_space</span><span class="p">,</span> <span class="n">n</span><span class="o">=</span><span class="bp">self</span><span class="o">.</span><span class="n">stack_size</span><span class="p">)</span>
|
||
|
|
|
||
|
|
<span class="k">def</span> <span class="nf">step</span><span class="p">(</span>
|
||
|
|
<span class="bp">self</span><span class="p">,</span> <span class="n">action</span><span class="p">:</span> <span class="n">WrapperActType</span>
|
||
|
|
<span class="p">)</span> <span class="o">-></span> <span class="nb">tuple</span><span class="p">[</span><span class="n">WrapperObsType</span><span class="p">,</span> <span class="n">SupportsFloat</span><span class="p">,</span> <span class="nb">bool</span><span class="p">,</span> <span class="nb">bool</span><span class="p">,</span> <span class="nb">dict</span><span class="p">[</span><span class="nb">str</span><span class="p">,</span> <span class="n">Any</span><span class="p">]]:</span>
|
||
|
|
<span class="w"> </span><span class="sd">"""Steps through the environment, appending the observation to the frame buffer.</span>
|
||
|
|
|
||
|
|
<span class="sd"> Args:</span>
|
||
|
|
<span class="sd"> action: The action to step through the environment with</span>
|
||
|
|
|
||
|
|
<span class="sd"> Returns:</span>
|
||
|
|
<span class="sd"> Stacked observations, reward, terminated, truncated, and info from the environment</span>
|
||
|
|
<span class="sd"> """</span>
|
||
|
|
<span class="n">obs</span><span class="p">,</span> <span class="n">reward</span><span class="p">,</span> <span class="n">terminated</span><span class="p">,</span> <span class="n">truncated</span><span class="p">,</span> <span class="n">info</span> <span class="o">=</span> <span class="bp">self</span><span class="o">.</span><span class="n">env</span><span class="o">.</span><span class="n">step</span><span class="p">(</span><span class="n">action</span><span class="p">)</span>
|
||
|
|
<span class="bp">self</span><span class="o">.</span><span class="n">obs_queue</span><span class="o">.</span><span class="n">append</span><span class="p">(</span><span class="n">obs</span><span class="p">)</span>
|
||
|
|
|
||
|
|
<span class="n">updated_obs</span> <span class="o">=</span> <span class="n">deepcopy</span><span class="p">(</span>
|
||
|
|
<span class="n">concatenate</span><span class="p">(</span><span class="bp">self</span><span class="o">.</span><span class="n">env</span><span class="o">.</span><span class="n">observation_space</span><span class="p">,</span> <span class="bp">self</span><span class="o">.</span><span class="n">obs_queue</span><span class="p">,</span> <span class="bp">self</span><span class="o">.</span><span class="n">stacked_obs</span><span class="p">)</span>
|
||
|
|
<span class="p">)</span>
|
||
|
|
<span class="k">return</span> <span class="n">updated_obs</span><span class="p">,</span> <span class="n">reward</span><span class="p">,</span> <span class="n">terminated</span><span class="p">,</span> <span class="n">truncated</span><span class="p">,</span> <span class="n">info</span>
|
||
|
|
|
||
|
|
<span class="k">def</span> <span class="nf">reset</span><span class="p">(</span>
|
||
|
|
<span class="bp">self</span><span class="p">,</span> <span class="o">*</span><span class="p">,</span> <span class="n">seed</span><span class="p">:</span> <span class="nb">int</span> <span class="o">|</span> <span class="kc">None</span> <span class="o">=</span> <span class="kc">None</span><span class="p">,</span> <span class="n">options</span><span class="p">:</span> <span class="nb">dict</span><span class="p">[</span><span class="nb">str</span><span class="p">,</span> <span class="n">Any</span><span class="p">]</span> <span class="o">|</span> <span class="kc">None</span> <span class="o">=</span> <span class="kc">None</span>
|
||
|
|
<span class="p">)</span> <span class="o">-></span> <span class="nb">tuple</span><span class="p">[</span><span class="n">WrapperObsType</span><span class="p">,</span> <span class="nb">dict</span><span class="p">[</span><span class="nb">str</span><span class="p">,</span> <span class="n">Any</span><span class="p">]]:</span>
|
||
|
|
<span class="w"> </span><span class="sd">"""Reset the environment, returning the stacked observation and info.</span>
|
||
|
|
|
||
|
|
<span class="sd"> Args:</span>
|
||
|
|
<span class="sd"> seed: The environment seed</span>
|
||
|
|
<span class="sd"> options: The reset options</span>
|
||
|
|
|
||
|
|
<span class="sd"> Returns:</span>
|
||
|
|
<span class="sd"> The stacked observations and info</span>
|
||
|
|
<span class="sd"> """</span>
|
||
|
|
<span class="n">obs</span><span class="p">,</span> <span class="n">info</span> <span class="o">=</span> <span class="bp">self</span><span class="o">.</span><span class="n">env</span><span class="o">.</span><span class="n">reset</span><span class="p">(</span><span class="n">seed</span><span class="o">=</span><span class="n">seed</span><span class="p">,</span> <span class="n">options</span><span class="o">=</span><span class="n">options</span><span class="p">)</span>
|
||
|
|
|
||
|
|
<span class="k">if</span> <span class="bp">self</span><span class="o">.</span><span class="n">padding_type</span> <span class="o">==</span> <span class="s2">"reset"</span><span class="p">:</span>
|
||
|
|
<span class="bp">self</span><span class="o">.</span><span class="n">padding_value</span> <span class="o">=</span> <span class="n">obs</span>
|
||
|
|
<span class="k">for</span> <span class="n">_</span> <span class="ow">in</span> <span class="nb">range</span><span class="p">(</span><span class="bp">self</span><span class="o">.</span><span class="n">stack_size</span> <span class="o">-</span> <span class="mi">1</span><span class="p">):</span>
|
||
|
|
<span class="bp">self</span><span class="o">.</span><span class="n">obs_queue</span><span class="o">.</span><span class="n">append</span><span class="p">(</span><span class="bp">self</span><span class="o">.</span><span class="n">padding_value</span><span class="p">)</span>
|
||
|
|
<span class="bp">self</span><span class="o">.</span><span class="n">obs_queue</span><span class="o">.</span><span class="n">append</span><span class="p">(</span><span class="n">obs</span><span class="p">)</span>
|
||
|
|
|
||
|
|
<span class="n">updated_obs</span> <span class="o">=</span> <span class="n">deepcopy</span><span class="p">(</span>
|
||
|
|
<span class="n">concatenate</span><span class="p">(</span><span class="bp">self</span><span class="o">.</span><span class="n">env</span><span class="o">.</span><span class="n">observation_space</span><span class="p">,</span> <span class="bp">self</span><span class="o">.</span><span class="n">obs_queue</span><span class="p">,</span> <span class="bp">self</span><span class="o">.</span><span class="n">stacked_obs</span><span class="p">)</span>
|
||
|
|
<span class="p">)</span>
|
||
|
|
<span class="k">return</span> <span class="n">updated_obs</span><span class="p">,</span> <span class="n">info</span></div>
|
||
|
|
|
||
|
|
|
||
|
|
|
||
|
|
<div class="viewcode-block" id="NormalizeObservation">
|
||
|
|
<a class="viewcode-back" href="../../../../api/wrappers/observation_wrappers/#gymnasium.wrappers.NormalizeObservation">[docs]</a>
|
||
|
|
<span class="k">class</span> <span class="nc">NormalizeObservation</span><span class="p">(</span>
|
||
|
|
<span class="n">gym</span><span class="o">.</span><span class="n">ObservationWrapper</span><span class="p">[</span><span class="n">WrapperObsType</span><span class="p">,</span> <span class="n">ActType</span><span class="p">,</span> <span class="n">ObsType</span><span class="p">],</span>
|
||
|
|
<span class="n">gym</span><span class="o">.</span><span class="n">utils</span><span class="o">.</span><span class="n">RecordConstructorArgs</span><span class="p">,</span>
|
||
|
|
<span class="p">):</span>
|
||
|
|
<span class="w"> </span><span class="sd">"""Normalizes observations to be centered at the mean with unit variance.</span>
|
||
|
|
|
||
|
|
<span class="sd"> The property :attr:`update_running_mean` allows to freeze/continue the running mean calculation of the observation</span>
|
||
|
|
<span class="sd"> statistics. If ``True`` (default), the ``RunningMeanStd`` will get updated every time ``step`` or ``reset`` is called.</span>
|
||
|
|
<span class="sd"> If ``False``, the calculated statistics are used but not updated anymore; this may be used during evaluation.</span>
|
||
|
|
|
||
|
|
<span class="sd"> A vector version of the wrapper exists :class:`gymnasium.wrappers.vector.NormalizeObservation`.</span>
|
||
|
|
|
||
|
|
<span class="sd"> Note:</span>
|
||
|
|
<span class="sd"> The normalization depends on past trajectories and observations will not be normalized correctly if the wrapper was</span>
|
||
|
|
<span class="sd"> newly instantiated or the policy was changed recently.</span>
|
||
|
|
|
||
|
|
<span class="sd"> Example:</span>
|
||
|
|
<span class="sd"> >>> import numpy as np</span>
|
||
|
|
<span class="sd"> >>> import gymnasium as gym</span>
|
||
|
|
<span class="sd"> >>> env = gym.make("CartPole-v1")</span>
|
||
|
|
<span class="sd"> >>> obs, info = env.reset(seed=123)</span>
|
||
|
|
<span class="sd"> >>> term, trunc = False, False</span>
|
||
|
|
<span class="sd"> >>> while not (term or trunc):</span>
|
||
|
|
<span class="sd"> ... obs, _, term, trunc, _ = env.step(1)</span>
|
||
|
|
<span class="sd"> ...</span>
|
||
|
|
<span class="sd"> >>> obs</span>
|
||
|
|
<span class="sd"> array([ 0.1511158 , 1.7183299 , -0.25533703, -2.8914354 ], dtype=float32)</span>
|
||
|
|
<span class="sd"> >>> env = gym.make("CartPole-v1")</span>
|
||
|
|
<span class="sd"> >>> env = NormalizeObservation(env)</span>
|
||
|
|
<span class="sd"> >>> obs, info = env.reset(seed=123)</span>
|
||
|
|
<span class="sd"> >>> term, trunc = False, False</span>
|
||
|
|
<span class="sd"> >>> while not (term or trunc):</span>
|
||
|
|
<span class="sd"> ... obs, _, term, trunc, _ = env.step(1)</span>
|
||
|
|
<span class="sd"> >>> obs</span>
|
||
|
|
<span class="sd"> array([ 2.0059888, 1.5676788, -1.9944268, -1.6120394], dtype=float32)</span>
|
||
|
|
|
||
|
|
<span class="sd"> Change logs:</span>
|
||
|
|
<span class="sd"> * v0.21.0 - Initially add</span>
|
||
|
|
<span class="sd"> * v1.0.0 - Add `update_running_mean` attribute to allow disabling of updating the running mean / standard, particularly useful for evaluation time.</span>
|
||
|
|
<span class="sd"> """</span>
|
||
|
|
|
||
|
|
<span class="k">def</span> <span class="fm">__init__</span><span class="p">(</span><span class="bp">self</span><span class="p">,</span> <span class="n">env</span><span class="p">:</span> <span class="n">gym</span><span class="o">.</span><span class="n">Env</span><span class="p">[</span><span class="n">ObsType</span><span class="p">,</span> <span class="n">ActType</span><span class="p">],</span> <span class="n">epsilon</span><span class="p">:</span> <span class="nb">float</span> <span class="o">=</span> <span class="mf">1e-8</span><span class="p">):</span>
|
||
|
|
<span class="w"> </span><span class="sd">"""This wrapper will normalize observations such that each observation is centered with unit variance.</span>
|
||
|
|
|
||
|
|
<span class="sd"> Args:</span>
|
||
|
|
<span class="sd"> env (Env): The environment to apply the wrapper</span>
|
||
|
|
<span class="sd"> epsilon: A stability parameter that is used when scaling the observations.</span>
|
||
|
|
<span class="sd"> """</span>
|
||
|
|
<span class="n">gym</span><span class="o">.</span><span class="n">utils</span><span class="o">.</span><span class="n">RecordConstructorArgs</span><span class="o">.</span><span class="fm">__init__</span><span class="p">(</span><span class="bp">self</span><span class="p">,</span> <span class="n">epsilon</span><span class="o">=</span><span class="n">epsilon</span><span class="p">)</span>
|
||
|
|
<span class="n">gym</span><span class="o">.</span><span class="n">ObservationWrapper</span><span class="o">.</span><span class="fm">__init__</span><span class="p">(</span><span class="bp">self</span><span class="p">,</span> <span class="n">env</span><span class="p">)</span>
|
||
|
|
|
||
|
|
<span class="bp">self</span><span class="o">.</span><span class="n">obs_rms</span> <span class="o">=</span> <span class="n">RunningMeanStd</span><span class="p">(</span>
|
||
|
|
<span class="n">shape</span><span class="o">=</span><span class="bp">self</span><span class="o">.</span><span class="n">observation_space</span><span class="o">.</span><span class="n">shape</span><span class="p">,</span> <span class="n">dtype</span><span class="o">=</span><span class="bp">self</span><span class="o">.</span><span class="n">observation_space</span><span class="o">.</span><span class="n">dtype</span>
|
||
|
|
<span class="p">)</span>
|
||
|
|
<span class="bp">self</span><span class="o">.</span><span class="n">epsilon</span> <span class="o">=</span> <span class="n">epsilon</span>
|
||
|
|
<span class="bp">self</span><span class="o">.</span><span class="n">_update_running_mean</span> <span class="o">=</span> <span class="kc">True</span>
|
||
|
|
|
||
|
|
<span class="nd">@property</span>
|
||
|
|
<span class="k">def</span> <span class="nf">update_running_mean</span><span class="p">(</span><span class="bp">self</span><span class="p">)</span> <span class="o">-></span> <span class="nb">bool</span><span class="p">:</span>
|
||
|
|
<span class="w"> </span><span class="sd">"""Property to freeze/continue the running mean calculation of the observation statistics."""</span>
|
||
|
|
<span class="k">return</span> <span class="bp">self</span><span class="o">.</span><span class="n">_update_running_mean</span>
|
||
|
|
|
||
|
|
<span class="nd">@update_running_mean</span><span class="o">.</span><span class="n">setter</span>
|
||
|
|
<span class="k">def</span> <span class="nf">update_running_mean</span><span class="p">(</span><span class="bp">self</span><span class="p">,</span> <span class="n">setting</span><span class="p">:</span> <span class="nb">bool</span><span class="p">):</span>
|
||
|
|
<span class="w"> </span><span class="sd">"""Sets the property to freeze/continue the running mean calculation of the observation statistics."""</span>
|
||
|
|
<span class="bp">self</span><span class="o">.</span><span class="n">_update_running_mean</span> <span class="o">=</span> <span class="n">setting</span>
|
||
|
|
|
||
|
|
<span class="k">def</span> <span class="nf">observation</span><span class="p">(</span><span class="bp">self</span><span class="p">,</span> <span class="n">observation</span><span class="p">:</span> <span class="n">ObsType</span><span class="p">)</span> <span class="o">-></span> <span class="n">WrapperObsType</span><span class="p">:</span>
|
||
|
|
<span class="w"> </span><span class="sd">"""Normalises the observation using the running mean and variance of the observations."""</span>
|
||
|
|
<span class="k">if</span> <span class="bp">self</span><span class="o">.</span><span class="n">_update_running_mean</span><span class="p">:</span>
|
||
|
|
<span class="bp">self</span><span class="o">.</span><span class="n">obs_rms</span><span class="o">.</span><span class="n">update</span><span class="p">(</span><span class="n">np</span><span class="o">.</span><span class="n">array</span><span class="p">([</span><span class="n">observation</span><span class="p">]))</span>
|
||
|
|
<span class="k">return</span> <span class="p">(</span><span class="n">observation</span> <span class="o">-</span> <span class="bp">self</span><span class="o">.</span><span class="n">obs_rms</span><span class="o">.</span><span class="n">mean</span><span class="p">)</span> <span class="o">/</span> <span class="n">np</span><span class="o">.</span><span class="n">sqrt</span><span class="p">(</span>
|
||
|
|
<span class="bp">self</span><span class="o">.</span><span class="n">obs_rms</span><span class="o">.</span><span class="n">var</span> <span class="o">+</span> <span class="bp">self</span><span class="o">.</span><span class="n">epsilon</span>
|
||
|
|
<span class="p">)</span></div>
|
||
|
|
|
||
|
|
|
||
|
|
|
||
|
|
<div class="viewcode-block" id="MaxAndSkipObservation">
|
||
|
|
<a class="viewcode-back" href="../../../../api/wrappers/observation_wrappers/#gymnasium.wrappers.MaxAndSkipObservation">[docs]</a>
|
||
|
|
<span class="k">class</span> <span class="nc">MaxAndSkipObservation</span><span class="p">(</span>
|
||
|
|
<span class="n">gym</span><span class="o">.</span><span class="n">Wrapper</span><span class="p">[</span><span class="n">WrapperObsType</span><span class="p">,</span> <span class="n">ActType</span><span class="p">,</span> <span class="n">ObsType</span><span class="p">,</span> <span class="n">ActType</span><span class="p">],</span>
|
||
|
|
<span class="n">gym</span><span class="o">.</span><span class="n">utils</span><span class="o">.</span><span class="n">RecordConstructorArgs</span><span class="p">,</span>
|
||
|
|
<span class="p">):</span>
|
||
|
|
<span class="w"> </span><span class="sd">"""Skips the N-th frame (observation) and return the max values between the two last observations.</span>
|
||
|
|
|
||
|
|
<span class="sd"> No vector version of the wrapper exists.</span>
|
||
|
|
|
||
|
|
<span class="sd"> Note:</span>
|
||
|
|
<span class="sd"> This wrapper is based on the wrapper from [stable-baselines3](https://stable-baselines3.readthedocs.io/en/master/_modules/stable_baselines3/common/atari_wrappers.html#MaxAndSkipEnv)</span>
|
||
|
|
|
||
|
|
<span class="sd"> Example:</span>
|
||
|
|
<span class="sd"> >>> import gymnasium as gym</span>
|
||
|
|
<span class="sd"> >>> env = gym.make("CartPole-v1")</span>
|
||
|
|
<span class="sd"> >>> obs0, *_ = env.reset(seed=123)</span>
|
||
|
|
<span class="sd"> >>> obs1, *_ = env.step(1)</span>
|
||
|
|
<span class="sd"> >>> obs2, *_ = env.step(1)</span>
|
||
|
|
<span class="sd"> >>> obs3, *_ = env.step(1)</span>
|
||
|
|
<span class="sd"> >>> obs4, *_ = env.step(1)</span>
|
||
|
|
<span class="sd"> >>> skip_and_max_obs = np.max(np.stack([obs3, obs4], axis=0), axis=0)</span>
|
||
|
|
<span class="sd"> >>> env = gym.make("CartPole-v1")</span>
|
||
|
|
<span class="sd"> >>> wrapped_env = MaxAndSkipObservation(env)</span>
|
||
|
|
<span class="sd"> >>> wrapped_obs0, *_ = wrapped_env.reset(seed=123)</span>
|
||
|
|
<span class="sd"> >>> wrapped_obs1, *_ = wrapped_env.step(1)</span>
|
||
|
|
<span class="sd"> >>> np.all(obs0 == wrapped_obs0)</span>
|
||
|
|
<span class="sd"> True</span>
|
||
|
|
<span class="sd"> >>> np.all(wrapped_obs1 == skip_and_max_obs)</span>
|
||
|
|
<span class="sd"> True</span>
|
||
|
|
|
||
|
|
<span class="sd"> Change logs:</span>
|
||
|
|
<span class="sd"> * v1.0.0 - Initially add</span>
|
||
|
|
<span class="sd"> """</span>
|
||
|
|
|
||
|
|
<span class="k">def</span> <span class="fm">__init__</span><span class="p">(</span><span class="bp">self</span><span class="p">,</span> <span class="n">env</span><span class="p">:</span> <span class="n">gym</span><span class="o">.</span><span class="n">Env</span><span class="p">[</span><span class="n">ObsType</span><span class="p">,</span> <span class="n">ActType</span><span class="p">],</span> <span class="n">skip</span><span class="p">:</span> <span class="nb">int</span> <span class="o">=</span> <span class="mi">4</span><span class="p">):</span>
|
||
|
|
<span class="w"> </span><span class="sd">"""This wrapper will return only every ``skip``-th frame (frameskipping) and return the max between the two last frames.</span>
|
||
|
|
|
||
|
|
<span class="sd"> Args:</span>
|
||
|
|
<span class="sd"> env (Env): The environment to apply the wrapper</span>
|
||
|
|
<span class="sd"> skip: The number of frames to skip</span>
|
||
|
|
<span class="sd"> """</span>
|
||
|
|
<span class="n">gym</span><span class="o">.</span><span class="n">utils</span><span class="o">.</span><span class="n">RecordConstructorArgs</span><span class="o">.</span><span class="fm">__init__</span><span class="p">(</span><span class="bp">self</span><span class="p">,</span> <span class="n">skip</span><span class="o">=</span><span class="n">skip</span><span class="p">)</span>
|
||
|
|
<span class="n">gym</span><span class="o">.</span><span class="n">Wrapper</span><span class="o">.</span><span class="fm">__init__</span><span class="p">(</span><span class="bp">self</span><span class="p">,</span> <span class="n">env</span><span class="p">)</span>
|
||
|
|
|
||
|
|
<span class="k">if</span> <span class="ow">not</span> <span class="n">np</span><span class="o">.</span><span class="n">issubdtype</span><span class="p">(</span><span class="nb">type</span><span class="p">(</span><span class="n">skip</span><span class="p">),</span> <span class="n">np</span><span class="o">.</span><span class="n">integer</span><span class="p">):</span>
|
||
|
|
<span class="k">raise</span> <span class="ne">TypeError</span><span class="p">(</span>
|
||
|
|
<span class="sa">f</span><span class="s2">"The skip is expected to be an integer, actual type: </span><span class="si">{</span><span class="nb">type</span><span class="p">(</span><span class="n">skip</span><span class="p">)</span><span class="si">}</span><span class="s2">"</span>
|
||
|
|
<span class="p">)</span>
|
||
|
|
<span class="k">if</span> <span class="n">skip</span> <span class="o"><</span> <span class="mi">2</span><span class="p">:</span>
|
||
|
|
<span class="k">raise</span> <span class="ne">ValueError</span><span class="p">(</span>
|
||
|
|
<span class="sa">f</span><span class="s2">"The skip value needs to be equal or greater than two, actual value: </span><span class="si">{</span><span class="n">skip</span><span class="si">}</span><span class="s2">"</span>
|
||
|
|
<span class="p">)</span>
|
||
|
|
<span class="k">if</span> <span class="n">env</span><span class="o">.</span><span class="n">observation_space</span><span class="o">.</span><span class="n">shape</span> <span class="ow">is</span> <span class="kc">None</span><span class="p">:</span>
|
||
|
|
<span class="k">raise</span> <span class="ne">ValueError</span><span class="p">(</span><span class="s2">"The observation space must have the shape attribute."</span><span class="p">)</span>
|
||
|
|
|
||
|
|
<span class="bp">self</span><span class="o">.</span><span class="n">_skip</span> <span class="o">=</span> <span class="n">skip</span>
|
||
|
|
<span class="bp">self</span><span class="o">.</span><span class="n">_obs_buffer</span> <span class="o">=</span> <span class="n">np</span><span class="o">.</span><span class="n">zeros</span><span class="p">(</span>
|
||
|
|
<span class="p">(</span><span class="mi">2</span><span class="p">,</span> <span class="o">*</span><span class="n">env</span><span class="o">.</span><span class="n">observation_space</span><span class="o">.</span><span class="n">shape</span><span class="p">),</span> <span class="n">dtype</span><span class="o">=</span><span class="n">env</span><span class="o">.</span><span class="n">observation_space</span><span class="o">.</span><span class="n">dtype</span>
|
||
|
|
<span class="p">)</span>
|
||
|
|
|
||
|
|
<span class="k">def</span> <span class="nf">step</span><span class="p">(</span>
|
||
|
|
<span class="bp">self</span><span class="p">,</span> <span class="n">action</span><span class="p">:</span> <span class="n">WrapperActType</span>
|
||
|
|
<span class="p">)</span> <span class="o">-></span> <span class="nb">tuple</span><span class="p">[</span><span class="n">WrapperObsType</span><span class="p">,</span> <span class="n">SupportsFloat</span><span class="p">,</span> <span class="nb">bool</span><span class="p">,</span> <span class="nb">bool</span><span class="p">,</span> <span class="nb">dict</span><span class="p">[</span><span class="nb">str</span><span class="p">,</span> <span class="n">Any</span><span class="p">]]:</span>
|
||
|
|
<span class="w"> </span><span class="sd">"""Step the environment with the given action for ``skip`` steps.</span>
|
||
|
|
|
||
|
|
<span class="sd"> Repeat action, sum reward, and max over last observations.</span>
|
||
|
|
|
||
|
|
<span class="sd"> Args:</span>
|
||
|
|
<span class="sd"> action: The action to step through the environment with</span>
|
||
|
|
<span class="sd"> Returns:</span>
|
||
|
|
<span class="sd"> Max of the last two observations, reward, terminated, truncated, and info from the environment</span>
|
||
|
|
<span class="sd"> """</span>
|
||
|
|
<span class="n">total_reward</span> <span class="o">=</span> <span class="mf">0.0</span>
|
||
|
|
<span class="n">terminated</span> <span class="o">=</span> <span class="n">truncated</span> <span class="o">=</span> <span class="kc">False</span>
|
||
|
|
<span class="n">info</span> <span class="o">=</span> <span class="p">{}</span>
|
||
|
|
<span class="k">for</span> <span class="n">i</span> <span class="ow">in</span> <span class="nb">range</span><span class="p">(</span><span class="bp">self</span><span class="o">.</span><span class="n">_skip</span><span class="p">):</span>
|
||
|
|
<span class="n">obs</span><span class="p">,</span> <span class="n">reward</span><span class="p">,</span> <span class="n">terminated</span><span class="p">,</span> <span class="n">truncated</span><span class="p">,</span> <span class="n">info</span> <span class="o">=</span> <span class="bp">self</span><span class="o">.</span><span class="n">env</span><span class="o">.</span><span class="n">step</span><span class="p">(</span><span class="n">action</span><span class="p">)</span>
|
||
|
|
<span class="k">if</span> <span class="n">i</span> <span class="o">==</span> <span class="bp">self</span><span class="o">.</span><span class="n">_skip</span> <span class="o">-</span> <span class="mi">2</span><span class="p">:</span>
|
||
|
|
<span class="bp">self</span><span class="o">.</span><span class="n">_obs_buffer</span><span class="p">[</span><span class="mi">0</span><span class="p">]</span> <span class="o">=</span> <span class="n">obs</span>
|
||
|
|
<span class="k">if</span> <span class="n">i</span> <span class="o">==</span> <span class="bp">self</span><span class="o">.</span><span class="n">_skip</span> <span class="o">-</span> <span class="mi">1</span><span class="p">:</span>
|
||
|
|
<span class="bp">self</span><span class="o">.</span><span class="n">_obs_buffer</span><span class="p">[</span><span class="mi">1</span><span class="p">]</span> <span class="o">=</span> <span class="n">obs</span>
|
||
|
|
<span class="n">total_reward</span> <span class="o">+=</span> <span class="nb">float</span><span class="p">(</span><span class="n">reward</span><span class="p">)</span>
|
||
|
|
<span class="k">if</span> <span class="n">terminated</span> <span class="ow">or</span> <span class="n">truncated</span><span class="p">:</span>
|
||
|
|
<span class="k">break</span>
|
||
|
|
<span class="n">max_frame</span> <span class="o">=</span> <span class="n">np</span><span class="o">.</span><span class="n">max</span><span class="p">(</span><span class="bp">self</span><span class="o">.</span><span class="n">_obs_buffer</span><span class="p">,</span> <span class="n">axis</span><span class="o">=</span><span class="mi">0</span><span class="p">)</span>
|
||
|
|
|
||
|
|
<span class="k">return</span> <span class="n">max_frame</span><span class="p">,</span> <span class="n">total_reward</span><span class="p">,</span> <span class="n">terminated</span><span class="p">,</span> <span class="n">truncated</span><span class="p">,</span> <span class="n">info</span></div>
|
||
|
|
|
||
|
|
</pre></div>
|
||
|
|
</article>
|
||
|
|
</div>
|
||
|
|
<footer>
|
||
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|
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|
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<div class="bottom-of-page">
|
||
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<div class="left-details">
|
||
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<div class="copyright">
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Copyright © 2023 Farama Foundation
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<!--
|
||
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Made with <a href="https://www.sphinx-doc.org/">Sphinx</a> and <a class="muted-link" href="https://pradyunsg.me">@pradyunsg</a>'s
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menuBtn.setAttribute("aria-expanded", "false");
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menuContainer.setAttribute("aria-hidden", "true");
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} else {
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menuBtn.setAttribute("aria-expanded", "true");
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menuContainer.setAttribute("aria-hidden", "false");
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}
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document.querySelector(".farama-header-menu").classList.toggle("active");
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document.querySelector(".farama-header-menu__btn").addEventListener("click", toggleMenu);
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document.getElementById("farama-close-menu").addEventListener("click", toggleMenu);
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<script async src="https://www.googletagmanager.com/gtag/js?id=G-6H9C8TWXZ8"></script>
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window.dataLayer = window.dataLayer || [];
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function gtag(){dataLayer.push(arguments);}
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gtag('js', new Date());
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gtag('config', 'G-6H9C8TWXZ8');
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boxElem.classList.add("cookie-alert");
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const containerElem = document.createElement("div");
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containerElem.classList.add("cookie-alert__container");
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const textElem = document.createElement("p");
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textElem.innerHTML = `This page uses <a href="https://analytics.google.com/">
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Google Analytics</a> to collect statistics.`;
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containerElem.appendChild(textElem);
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const declineBtn = Object.assign(document.createElement("button"),
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||
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{
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innerText: "Deny",
|
||
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className: "farama-btn cookie-alert__button",
|
||
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id: "cookie-alert__decline",
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||
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}
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);
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declineBtn.addEventListener("click", () => {
|
||
|
|
localStorage.setItem("acceptedCookieAlert", false);
|
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boxElem.remove();
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});
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const acceptBtn = Object.assign(document.createElement("button"),
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||
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{
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innerText: "Allow",
|
||
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className: "farama-btn cookie-alert__button",
|
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id: "cookie-alert__accept",
|
||
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}
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||
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);
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acceptBtn.addEventListener("click", () => {
|
||
|
|
localStorage.setItem("acceptedCookieAlert", true);
|
||
|
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boxElem.remove();
|
||
|
|
enableGtag();
|
||
|
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});
|
||
|
|
|
||
|
|
containerElem.appendChild(declineBtn);
|
||
|
|
containerElem.appendChild(acceptBtn);
|
||
|
|
boxElem.appendChild(containerElem);
|
||
|
|
document.body.appendChild(boxElem);
|
||
|
|
} else if (localStorage.getItem("acceptedCookieAlert") === "true") {
|
||
|
|
enableGtag();
|
||
|
|
}
|
||
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})()
|
||
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</script>
|
||
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|
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<script src="../../../../_static/documentation_options.js?v=ed34540e"></script>
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<script src="../../../../_static/doctools.js?v=888ff710"></script>
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<script src="../../../../_static/sphinx_highlight.js?v=dc90522c"></script>
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<script src="../../../../_static/scripts/furo.js?v=7660844c"></script>
|
||
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|
|
||
|
|
<script>
|
||
|
|
|
||
|
|
const createProjectsList = (projects, displayImages) => {
|
||
|
|
const ulElem = Object.assign(document.createElement('ul'),
|
||
|
|
{
|
||
|
|
className:'farama-header-menu-list',
|
||
|
|
}
|
||
|
|
)
|
||
|
|
for (let project of projects) {
|
||
|
|
const liElem = document.createElement("li");
|
||
|
|
const aElem = Object.assign(document.createElement("a"),
|
||
|
|
{
|
||
|
|
href: project.link
|
||
|
|
}
|
||
|
|
);
|
||
|
|
liElem.appendChild(aElem);
|
||
|
|
if (displayImages) {
|
||
|
|
const imgElem = Object.assign(document.createElement("img"),
|
||
|
|
{
|
||
|
|
src: project.image ? imagesBasepath + project.image : imagesBasepath + "/farama_black.svg",
|
||
|
|
alt: `${project.name} logo`,
|
||
|
|
className: "farama-black-logo-invert"
|
||
|
|
}
|
||
|
|
);
|
||
|
|
aElem.appendChild(imgElem);
|
||
|
|
}
|
||
|
|
aElem.appendChild(document.createTextNode(project.name));
|
||
|
|
ulElem.appendChild(liElem);
|
||
|
|
}
|
||
|
|
return ulElem;
|
||
|
|
}
|
||
|
|
|
||
|
|
// Create menu with Farama projects by using the API at farama.org/api/projects.json
|
||
|
|
const createCORSRequest = (method, url) => {
|
||
|
|
let xhr = new XMLHttpRequest();
|
||
|
|
xhr.responseType = 'json';
|
||
|
|
|
||
|
|
if ("withCredentials" in xhr) {
|
||
|
|
xhr.open(method, url, true);
|
||
|
|
} else if (typeof XDomainRequest != "undefined") {
|
||
|
|
// IE8 & IE9
|
||
|
|
xhr = new XDomainRequest();
|
||
|
|
xhr.open(method, url);
|
||
|
|
} else {
|
||
|
|
// CORS not supported.
|
||
|
|
xhr = null;
|
||
|
|
}
|
||
|
|
return xhr;
|
||
|
|
};
|
||
|
|
|
||
|
|
const url = 'https://farama.org/api/projects.json';
|
||
|
|
const imagesBasepath = "https://farama.org/assets/images"
|
||
|
|
const method = 'GET';
|
||
|
|
let xhr = createCORSRequest(method, url);
|
||
|
|
|
||
|
|
xhr.onload = () => {
|
||
|
|
const jsonResponse = xhr.response;
|
||
|
|
const sections = {
|
||
|
|
"Core Projects": [],
|
||
|
|
"Mature Projects": {
|
||
|
|
"Documentation": [],
|
||
|
|
"Repositories": [],
|
||
|
|
},
|
||
|
|
"Incubating Projects": {
|
||
|
|
"Documentation": [],
|
||
|
|
"Repositories": [],
|
||
|
|
},
|
||
|
|
"Foundation": [
|
||
|
|
{
|
||
|
|
name: "About",
|
||
|
|
link: "https://farama.org/about"
|
||
|
|
},
|
||
|
|
{
|
||
|
|
name: "Standards",
|
||
|
|
link: "https://farama.org/project_standards",
|
||
|
|
},
|
||
|
|
{
|
||
|
|
name: "Donate",
|
||
|
|
link: "https://farama.org/donations"
|
||
|
|
}
|
||
|
|
]
|
||
|
|
}
|
||
|
|
|
||
|
|
// Categorize projects
|
||
|
|
Object.keys(jsonResponse).forEach(key => {
|
||
|
|
projectJson = jsonResponse[key];
|
||
|
|
if (projectJson.website !== null) {
|
||
|
|
projectJson.link = projectJson.website;
|
||
|
|
} else {
|
||
|
|
projectJson.link = projectJson.github;
|
||
|
|
}
|
||
|
|
if (projectJson.type === "core") {
|
||
|
|
sections["Core Projects"].push(projectJson)
|
||
|
|
} else if (projectJson.type == "mature") {
|
||
|
|
if (projectJson.website !== null) {
|
||
|
|
sections["Mature Projects"]["Documentation"].push(projectJson)
|
||
|
|
} else {
|
||
|
|
sections["Mature Projects"]["Repositories"].push(projectJson)
|
||
|
|
}
|
||
|
|
} else {
|
||
|
|
if (projectJson.website !== null) {
|
||
|
|
sections["Incubating Projects"]["Documentation"].push(projectJson)
|
||
|
|
} else {
|
||
|
|
sections["Incubating Projects"]["Repositories"].push(projectJson)
|
||
|
|
}
|
||
|
|
}
|
||
|
|
})
|
||
|
|
|
||
|
|
const menuContainer = document.querySelector(".farama-header-menu__body");
|
||
|
|
|
||
|
|
Object.keys(sections).forEach((key, i) => {
|
||
|
|
const sectionElem = Object.assign(
|
||
|
|
document.createElement('div'), {
|
||
|
|
className:'farama-header-menu__section',
|
||
|
|
}
|
||
|
|
)
|
||
|
|
sectionElem.appendChild(Object.assign(document.createElement('span'),
|
||
|
|
{
|
||
|
|
className:'farama-header-menu__section-title' ,
|
||
|
|
innerText: key
|
||
|
|
}
|
||
|
|
))
|
||
|
|
// is not a list
|
||
|
|
if (sections[key].constructor !== Array) {
|
||
|
|
const subSections = sections[key];
|
||
|
|
const subSectionContainerElem = Object.assign(
|
||
|
|
document.createElement('div'), {
|
||
|
|
className:'farama-header-menu__subsections-container',
|
||
|
|
style: 'display: flex'
|
||
|
|
}
|
||
|
|
)
|
||
|
|
Object.keys(subSections).forEach((subKey, i) => {
|
||
|
|
const subSectionElem = Object.assign(
|
||
|
|
document.createElement('div'), {
|
||
|
|
className:'farama-header-menu__subsection',
|
||
|
|
}
|
||
|
|
)
|
||
|
|
subSectionElem.appendChild(Object.assign(document.createElement('span'),
|
||
|
|
{
|
||
|
|
className:'farama-header-menu__subsection-title' ,
|
||
|
|
innerText: subKey
|
||
|
|
}
|
||
|
|
))
|
||
|
|
const ulElem = createProjectsList(subSections[subKey], key !== 'Foundation');
|
||
|
|
subSectionElem.appendChild(ulElem);
|
||
|
|
subSectionContainerElem.appendChild(subSectionElem);
|
||
|
|
})
|
||
|
|
sectionElem.appendChild(subSectionContainerElem);
|
||
|
|
} else {
|
||
|
|
const projects = sections[key];
|
||
|
|
const ulElem = createProjectsList(projects, true);
|
||
|
|
sectionElem.appendChild(ulElem);
|
||
|
|
}
|
||
|
|
menuContainer.appendChild(sectionElem)
|
||
|
|
});
|
||
|
|
}
|
||
|
|
|
||
|
|
xhr.onerror = function() {
|
||
|
|
console.error("Unable to load projects");
|
||
|
|
};
|
||
|
|
|
||
|
|
xhr.send();
|
||
|
|
</script>
|
||
|
|
|
||
|
|
|
||
|
|
<script>
|
||
|
|
const versioningConfig = {
|
||
|
|
githubUser: 'Farama-Foundation',
|
||
|
|
githubRepo: 'Gymnasium',
|
||
|
|
};
|
||
|
|
fetch('/main/_static/versioning/versioning_menu.html').then(response => {
|
||
|
|
if (response.status === 200) {
|
||
|
|
response.text().then(text => {
|
||
|
|
const container = document.createElement("div");
|
||
|
|
container.innerHTML = text;
|
||
|
|
document.querySelector("body").appendChild(container);
|
||
|
|
// innerHtml doenst evaluate scripts, we need to add them dynamically
|
||
|
|
Array.from(container.querySelectorAll("script")).forEach(oldScript => {
|
||
|
|
const newScript = document.createElement("script");
|
||
|
|
Array.from(oldScript.attributes).forEach(attr => newScript.setAttribute(attr.name, attr.value));
|
||
|
|
newScript.appendChild(document.createTextNode(oldScript.innerHTML));
|
||
|
|
oldScript.parentNode.replaceChild(newScript, oldScript);
|
||
|
|
});
|
||
|
|
});
|
||
|
|
} else {
|
||
|
|
console.warn("Unable to load versioning menu", response);
|
||
|
|
}
|
||
|
|
});
|
||
|
|
</script>
|
||
|
|
|
||
|
|
</body>
|
||
|
|
</html>
|