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<section id="spaces">
<h1>Spaces<a class="headerlink" href="#spaces" title="Permalink to this heading">#</a></h1>
<dl class="py class">
<dt class="sig sig-object py" id="gymnasium.spaces.Space">
<em class="property"><span class="pre">class</span><span class="w"> </span></em><span class="sig-prename descclassname"><span class="pre">gymnasium.spaces.</span></span><span class="sig-name descname"><span class="pre">Space</span></span><span class="sig-paren">(</span><em class="sig-param"><span class="n"><span class="pre">shape</span></span><span class="p"><span class="pre">:</span></span><span class="w"> </span><span class="n"><span class="pre">Optional</span><span class="p"><span class="pre">[</span></span><span class="pre">Sequence</span><span class="p"><span class="pre">[</span></span><span class="pre">int</span><span class="p"><span class="pre">]</span></span><span class="p"><span class="pre">]</span></span></span><span class="w"> </span><span class="o"><span class="pre">=</span></span><span class="w"> </span><span class="default_value"><span class="pre">None</span></span></em>, <em class="sig-param"><span class="n"><span class="pre">dtype</span></span><span class="p"><span class="pre">:</span></span><span class="w"> </span><span class="n"><span class="pre">Optional</span><span class="p"><span class="pre">[</span></span><span class="pre">Union</span><span class="p"><span class="pre">[</span></span><span class="pre">Type</span><span class="p"><span class="pre">,</span></span><span class="w"> </span><span class="pre">str</span><span class="p"><span class="pre">,</span></span><span class="w"> </span><span class="pre">dtype</span><span class="p"><span class="pre">]</span></span><span class="p"><span class="pre">]</span></span></span><span class="w"> </span><span class="o"><span class="pre">=</span></span><span class="w"> </span><span class="default_value"><span class="pre">None</span></span></em>, <em class="sig-param"><span class="n"><span class="pre">seed</span></span><span class="p"><span class="pre">:</span></span><span class="w"> </span><span class="n"><span class="pre">Optional</span><span class="p"><span class="pre">[</span></span><span class="pre">Union</span><span class="p"><span class="pre">[</span></span><span class="pre">int</span><span class="p"><span class="pre">,</span></span><span class="w"> </span><span class="pre">Generator</span><span class="p"><span class="pre">]</span></span><span class="p"><span class="pre">]</span></span></span><span class="w"> </span><span class="o"><span class="pre">=</span></span><span class="w"> </span><span class="default_value"><span class="pre">None</span></span></em><span class="sig-paren">)</span><a class="headerlink" href="#gymnasium.spaces.Space" title="Permalink to this definition">#</a></dt>
<dd><p>Superclass that is used to define observation and action spaces.</p>
<p>Spaces are crucially used in Gym to define the format of valid actions and observations.
They serve various purposes:</p>
<ul class="simple">
<li><p>They clearly define how to interact with environments, i.e. they specify what actions need to look like
and what observations will look like</p></li>
<li><p>They allow us to work with highly structured data (e.g. in the form of elements of <a class="reference internal" href="#gymnasium.spaces.Dict" title="gymnasium.spaces.Dict"><code class="xref py py-class docutils literal notranslate"><span class="pre">Dict</span></code></a> spaces)
and painlessly transform them into flat arrays that can be used in learning code</p></li>
<li><p>They provide a method to sample random elements. This is especially useful for exploration and debugging.</p></li>
</ul>
<p>Different spaces can be combined hierarchically via container spaces (<a class="reference internal" href="#gymnasium.spaces.Tuple" title="gymnasium.spaces.Tuple"><code class="xref py py-class docutils literal notranslate"><span class="pre">Tuple</span></code></a> and <a class="reference internal" href="#gymnasium.spaces.Dict" title="gymnasium.spaces.Dict"><code class="xref py py-class docutils literal notranslate"><span class="pre">Dict</span></code></a>) to build a
more expressive space</p>
<div class="admonition warning">
<p class="admonition-title">Warning</p>
<p>Custom observation &amp; action spaces can inherit from the <code class="docutils literal notranslate"><span class="pre">Space</span></code>
class. However, most use-cases should be covered by the existing space
classes (e.g. <a class="reference internal" href="#gymnasium.spaces.Box" title="gymnasium.spaces.Box"><code class="xref py py-class docutils literal notranslate"><span class="pre">Box</span></code></a>, <a class="reference internal" href="#gymnasium.spaces.Discrete" title="gymnasium.spaces.Discrete"><code class="xref py py-class docutils literal notranslate"><span class="pre">Discrete</span></code></a>, etc…), and container classes (:class`Tuple` &amp;
<a class="reference internal" href="#gymnasium.spaces.Dict" title="gymnasium.spaces.Dict"><code class="xref py py-class docutils literal notranslate"><span class="pre">Dict</span></code></a>). Note that parametrized probability distributions (through the
<a class="reference internal" href="#gymnasium.spaces.Space.sample" title="gymnasium.spaces.Space.sample"><code class="xref py py-meth docutils literal notranslate"><span class="pre">Space.sample()</span></code></a> method), and batching functions (in <code class="xref py py-class docutils literal notranslate"><span class="pre">gymnasium.vector.VectorEnv</span></code>), are
only well-defined for instances of spaces provided in gymnasium by default.
Moreover, some implementations of Reinforcement Learning algorithms might
not handle custom spaces properly. Use custom spaces with care.</p>
</div>
<p>Constructor of <a class="reference internal" href="#gymnasium.spaces.Space" title="gymnasium.spaces.Space"><code class="xref py py-class docutils literal notranslate"><span class="pre">Space</span></code></a>.</p>
<dl class="field-list simple">
<dt class="field-odd">Parameters<span class="colon">:</span></dt>
<dd class="field-odd"><ul class="simple">
<li><p><strong>shape</strong> (<em>Optional</em><em>[</em><a class="reference internal" href="#gymnasium.spaces.Sequence" title="gymnasium.spaces.Sequence"><em>Sequence</em></a><em>[</em><em>int</em><em>]</em><em>]</em>) – If elements of the space are numpy arrays, this should specify their shape.</p></li>
<li><p><strong>dtype</strong> (<em>Optional</em><em>[</em><em>Type</em><em> | </em><em>str</em><em>]</em>) – If elements of the space are numpy arrays, this should specify their dtype.</p></li>
<li><p><strong>seed</strong> – Optionally, you can use this argument to seed the RNG that is used to sample from the space</p></li>
</ul>
</dd>
</dl>
</dd></dl>
<section id="general-functions">
<h2>General Functions<a class="headerlink" href="#general-functions" title="Permalink to this heading">#</a></h2>
<p>Each space implements the following functions:</p>
<dl class="py function">
<dt class="sig sig-object py" id="gymnasium.spaces.Space.sample">
<span class="sig-prename descclassname"><span class="pre">gymnasium.spaces.Space.</span></span><span class="sig-name descname"><span class="pre">sample</span></span><span class="sig-paren">(</span><em class="sig-param"><span class="n"><span class="pre">self</span></span></em>, <em class="sig-param"><span class="n"><span class="pre">mask</span></span><span class="p"><span class="pre">:</span></span><span class="w"> </span><span class="n"><span class="pre">Optional</span><span class="p"><span class="pre">[</span></span><span class="pre">Any</span><span class="p"><span class="pre">]</span></span></span><span class="w"> </span><span class="o"><span class="pre">=</span></span><span class="w"> </span><span class="default_value"><span class="pre">None</span></span></em><span class="sig-paren">)</span> <span class="sig-return"><span class="sig-return-icon">&#x2192;</span> <span class="sig-return-typehint"><span class="pre">T_cov</span></span></span><a class="headerlink" href="#gymnasium.spaces.Space.sample" title="Permalink to this definition">#</a></dt>
<dd><p>Randomly sample an element of this space.</p>
<p>Can be uniform or non-uniform sampling based on boundedness of space.</p>
<dl class="field-list simple">
<dt class="field-odd">Parameters<span class="colon">:</span></dt>
<dd class="field-odd"><p><strong>mask</strong> – A mask used for sampling, expected <code class="docutils literal notranslate"><span class="pre">dtype=np.int8</span></code> and see sample implementation for expected shape.</p>
</dd>
<dt class="field-even">Returns<span class="colon">:</span></dt>
<dd class="field-even"><p><strong>A sampled actions from the space</strong></p>
</dd>
</dl>
</dd></dl>
<dl class="py function">
<dt class="sig sig-object py" id="gymnasium.spaces.Space.contains">
<span class="sig-prename descclassname"><span class="pre">gymnasium.spaces.Space.</span></span><span class="sig-name descname"><span class="pre">contains</span></span><span class="sig-paren">(</span><em class="sig-param"><span class="n"><span class="pre">self</span></span></em>, <em class="sig-param"><span class="n"><span class="pre">x</span></span></em><span class="sig-paren">)</span> <span class="sig-return"><span class="sig-return-icon">&#x2192;</span> <span class="sig-return-typehint"><span class="pre">bool</span></span></span><a class="headerlink" href="#gymnasium.spaces.Space.contains" title="Permalink to this definition">#</a></dt>
<dd><p>Return boolean specifying if x is a valid member of this space.</p>
</dd></dl>
<dl class="py property">
<dt class="sig sig-object py" id="gymnasium.spaces.Space.shape">
<em class="property"><span class="pre">property</span><span class="w"> </span></em><span class="sig-prename descclassname"><span class="pre">Space.</span></span><span class="sig-name descname"><span class="pre">shape</span></span><em class="property"><span class="p"><span class="pre">:</span></span><span class="w"> </span><span class="pre">Optional</span><span class="p"><span class="pre">[</span></span><span class="pre">Tuple</span><span class="p"><span class="pre">[</span></span><span class="pre">int</span><span class="p"><span class="pre">,</span></span><span class="w"> </span><span class="p"><span class="pre">...</span></span><span class="p"><span class="pre">]</span></span><span class="p"><span class="pre">]</span></span></em><a class="headerlink" href="#gymnasium.spaces.Space.shape" title="Permalink to this definition">#</a></dt>
<dd><p>Return the shape of the space as an immutable property.</p>
</dd></dl>
<dl class="py property">
<dt class="sig sig-object py" id="gymnasium.spaces.Space.dtype">
<em class="property"><span class="pre">property</span><span class="w"> </span></em><span class="sig-prename descclassname"><span class="pre">gymnasium.spaces.Space.</span></span><span class="sig-name descname"><span class="pre">dtype</span></span><a class="headerlink" href="#gymnasium.spaces.Space.dtype" title="Permalink to this definition">#</a></dt>
<dd><p>Return the data type of this space.</p>
</dd></dl>
<dl class="py function">
<dt class="sig sig-object py" id="gymnasium.spaces.Space.seed">
<span class="sig-prename descclassname"><span class="pre">gymnasium.spaces.Space.</span></span><span class="sig-name descname"><span class="pre">seed</span></span><span class="sig-paren">(</span><em class="sig-param"><span class="n"><span class="pre">self</span></span></em>, <em class="sig-param"><span class="n"><span class="pre">seed</span></span><span class="p"><span class="pre">:</span></span><span class="w"> </span><span class="n"><span class="pre">Optional</span><span class="p"><span class="pre">[</span></span><span class="pre">int</span><span class="p"><span class="pre">]</span></span></span><span class="w"> </span><span class="o"><span class="pre">=</span></span><span class="w"> </span><span class="default_value"><span class="pre">None</span></span></em><span class="sig-paren">)</span> <span class="sig-return"><span class="sig-return-icon">&#x2192;</span> <span class="sig-return-typehint"><span class="pre">list</span></span></span><a class="headerlink" href="#gymnasium.spaces.Space.seed" title="Permalink to this definition">#</a></dt>
<dd><p>Seed the PRNG of this space and possibly the PRNGs of subspaces.</p>
</dd></dl>
<dl class="py function">
<dt class="sig sig-object py" id="gymnasium.spaces.Space.to_jsonable">
<span class="sig-prename descclassname"><span class="pre">gymnasium.spaces.Space.</span></span><span class="sig-name descname"><span class="pre">to_jsonable</span></span><span class="sig-paren">(</span><em class="sig-param"><span class="n"><span class="pre">self</span></span></em>, <em class="sig-param"><span class="n"><span class="pre">sample_n</span></span><span class="p"><span class="pre">:</span></span><span class="w"> </span><span class="n"><span class="pre">Sequence</span><span class="p"><span class="pre">[</span></span><span class="pre">T_cov</span><span class="p"><span class="pre">]</span></span></span></em><span class="sig-paren">)</span> <span class="sig-return"><span class="sig-return-icon">&#x2192;</span> <span class="sig-return-typehint"><span class="pre">list</span></span></span><a class="headerlink" href="#gymnasium.spaces.Space.to_jsonable" title="Permalink to this definition">#</a></dt>
<dd><p>Convert a batch of samples from this space to a JSONable data type.</p>
</dd></dl>
<dl class="py function">
<dt class="sig sig-object py" id="gymnasium.spaces.Space.from_jsonable">
<span class="sig-prename descclassname"><span class="pre">gymnasium.spaces.Space.</span></span><span class="sig-name descname"><span class="pre">from_jsonable</span></span><span class="sig-paren">(</span><em class="sig-param"><span class="n"><span class="pre">self</span></span></em>, <em class="sig-param"><span class="n"><span class="pre">sample_n</span></span><span class="p"><span class="pre">:</span></span><span class="w"> </span><span class="n"><span class="pre">list</span></span></em><span class="sig-paren">)</span> <span class="sig-return"><span class="sig-return-icon">&#x2192;</span> <span class="sig-return-typehint"><span class="pre">List</span><span class="p"><span class="pre">[</span></span><span class="pre">T_cov</span><span class="p"><span class="pre">]</span></span></span></span><a class="headerlink" href="#gymnasium.spaces.Space.from_jsonable" title="Permalink to this definition">#</a></dt>
<dd><p>Convert a JSONable data type to a batch of samples from this space.</p>
</dd></dl>
</section>
<section id="fundamental-spaces">
<h2>Fundamental Spaces<a class="headerlink" href="#fundamental-spaces" title="Permalink to this heading">#</a></h2>
<section id="box">
<h3>Box<a class="headerlink" href="#box" title="Permalink to this heading">#</a></h3>
<dl class="py class">
<dt class="sig sig-object py" id="gymnasium.spaces.Box">
<em class="property"><span class="pre">class</span><span class="w"> </span></em><span class="sig-prename descclassname"><span class="pre">gymnasium.spaces.</span></span><span class="sig-name descname"><span class="pre">Box</span></span><span class="sig-paren">(</span><em class="sig-param"><span class="pre">low:</span> <span class="pre">~typing.Union[~typing.SupportsFloat,</span> <span class="pre">~numpy.ndarray],</span> <span class="pre">high:</span> <span class="pre">~typing.Union[~typing.SupportsFloat,</span> <span class="pre">~numpy.ndarray],</span> <span class="pre">shape:</span> <span class="pre">~typing.Optional[~typing.Sequence[int]]</span> <span class="pre">=</span> <span class="pre">None,</span> <span class="pre">dtype:</span> <span class="pre">~typing.Type</span> <span class="pre">=</span> <span class="pre">&lt;class</span> <span class="pre">'numpy.float32'&gt;,</span> <span class="pre">seed:</span> <span class="pre">~typing.Optional[~typing.Union[int,</span> <span class="pre">~numpy.random._generator.Generator]]</span> <span class="pre">=</span> <span class="pre">None</span></em><span class="sig-paren">)</span><a class="headerlink" href="#gymnasium.spaces.Box" title="Permalink to this definition">#</a></dt>
<dd><p>A (possibly unbounded) box in <span class="math notranslate nohighlight">\(\mathbb{R}^n\)</span>.</p>
<p>Specifically, a Box represents the Cartesian product of n closed intervals.
Each interval has the form of one of <span class="math notranslate nohighlight">\([a, b]\)</span>, <span class="math notranslate nohighlight">\((-\infty, b]\)</span>,
<span class="math notranslate nohighlight">\([a, \infty)\)</span>, or <span class="math notranslate nohighlight">\((-\infty, \infty)\)</span>.</p>
<p>There are two common use cases:</p>
<ul>
<li><p>Identical bound for each dimension:</p>
<div class="highlight-default notranslate"><div class="highlight"><pre><span></span><span class="gp">&gt;&gt;&gt; </span><span class="n">Box</span><span class="p">(</span><span class="n">low</span><span class="o">=-</span><span class="mf">1.0</span><span class="p">,</span> <span class="n">high</span><span class="o">=</span><span class="mf">2.0</span><span class="p">,</span> <span class="n">shape</span><span class="o">=</span><span class="p">(</span><span class="mi">3</span><span class="p">,</span> <span class="mi">4</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="go">Box(3, 4)</span>
</pre></div>
</div>
</li>
<li><p>Independent bound for each dimension:</p>
<div class="highlight-default notranslate"><div class="highlight"><pre><span></span><span class="gp">&gt;&gt;&gt; </span><span class="n">Box</span><span class="p">(</span><span class="n">low</span><span class="o">=</span><span class="n">np</span><span class="o">.</span><span class="n">array</span><span class="p">([</span><span class="o">-</span><span class="mf">1.0</span><span class="p">,</span> <span class="o">-</span><span class="mf">2.0</span><span class="p">]),</span> <span class="n">high</span><span class="o">=</span><span class="n">np</span><span class="o">.</span><span class="n">array</span><span class="p">([</span><span class="mf">2.0</span><span class="p">,</span> <span class="mf">4.0</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="go">Box(2,)</span>
</pre></div>
</div>
</li>
</ul>
<p>Constructor of <a class="reference internal" href="#gymnasium.spaces.Box" title="gymnasium.spaces.Box"><code class="xref py py-class docutils literal notranslate"><span class="pre">Box</span></code></a>.</p>
<p>The argument <code class="docutils literal notranslate"><span class="pre">low</span></code> specifies the lower bound of each dimension and <code class="docutils literal notranslate"><span class="pre">high</span></code> specifies the upper bounds.
I.e., the space that is constructed will be the product of the intervals <span class="math notranslate nohighlight">\([\text{low}[i], \text{high}[i]]\)</span>.</p>
<p>If <code class="docutils literal notranslate"><span class="pre">low</span></code> (or <code class="docutils literal notranslate"><span class="pre">high</span></code>) is a scalar, the lower bound (or upper bound, respectively) will be assumed to be
this value across all dimensions.</p>
<dl class="field-list simple">
<dt class="field-odd">Parameters<span class="colon">:</span></dt>
<dd class="field-odd"><ul class="simple">
<li><p><strong>low</strong> (<em>Union</em><em>[</em><em>SupportsFloat</em><em>, </em><em>np.ndarray</em><em>]</em>) – Lower bounds of the intervals.</p></li>
<li><p><strong>high</strong> (<em>Union</em><em>[</em><em>SupportsFloat</em><em>, </em><em>np.ndarray</em><em>]</em>) – Upper bounds of the intervals.</p></li>
<li><p><strong>shape</strong> (<em>Optional</em><em>[</em><a class="reference internal" href="#gymnasium.spaces.Sequence" title="gymnasium.spaces.Sequence"><em>Sequence</em></a><em>[</em><em>int</em><em>]</em><em>]</em>) – The shape is inferred from the shape of <cite>low</cite> or <cite>high</cite> <cite>np.ndarray`s with
`low</cite> and <cite>high</cite> scalars defaulting to a shape of (1,)</p></li>
<li><p><strong>dtype</strong> – The dtype of the elements of the space. If this is an integer type, the <a class="reference internal" href="#gymnasium.spaces.Box" title="gymnasium.spaces.Box"><code class="xref py py-class docutils literal notranslate"><span class="pre">Box</span></code></a> is essentially a discrete space.</p></li>
<li><p><strong>seed</strong> – Optionally, you can use this argument to seed the RNG that is used to sample from the space.</p></li>
</ul>
</dd>
<dt class="field-even">Raises<span class="colon">:</span></dt>
<dd class="field-even"><p><strong>ValueError</strong> – If no shape information is provided (shape is None, low is None and high is None) then a
value error is raised.</p>
</dd>
</dl>
<dl class="py method">
<dt class="sig sig-object py" id="gymnasium.spaces.Box.is_bounded">
<span class="sig-name descname"><span class="pre">is_bounded</span></span><span class="sig-paren">(</span><em class="sig-param"><span class="n"><span class="pre">manner</span></span><span class="p"><span class="pre">:</span></span><span class="w"> </span><span class="n"><span class="pre">str</span></span><span class="w"> </span><span class="o"><span class="pre">=</span></span><span class="w"> </span><span class="default_value"><span class="pre">'both'</span></span></em><span class="sig-paren">)</span> <span class="sig-return"><span class="sig-return-icon">&#x2192;</span> <span class="sig-return-typehint"><span class="pre">bool</span></span></span><a class="headerlink" href="#gymnasium.spaces.Box.is_bounded" title="Permalink to this definition">#</a></dt>
<dd><p>Checks whether the box is bounded in some sense.</p>
<dl class="field-list simple">
<dt class="field-odd">Parameters<span class="colon">:</span></dt>
<dd class="field-odd"><p><strong>manner</strong> (<em>str</em>) – One of <code class="docutils literal notranslate"><span class="pre">&quot;both&quot;</span></code>, <code class="docutils literal notranslate"><span class="pre">&quot;below&quot;</span></code>, <code class="docutils literal notranslate"><span class="pre">&quot;above&quot;</span></code>.</p>
</dd>
<dt class="field-even">Returns<span class="colon">:</span></dt>
<dd class="field-even"><p><strong>If the space is bounded</strong></p>
</dd>
<dt class="field-odd">Raises<span class="colon">:</span></dt>
<dd class="field-odd"><p><strong>ValueError</strong> – If <cite>manner</cite> is neither <code class="docutils literal notranslate"><span class="pre">&quot;both&quot;</span></code> nor <code class="docutils literal notranslate"><span class="pre">&quot;below&quot;</span></code> or <code class="docutils literal notranslate"><span class="pre">&quot;above&quot;</span></code></p>
</dd>
</dl>
</dd></dl>
<dl class="py method">
<dt class="sig sig-object py" id="gymnasium.spaces.Box.sample">
<span class="sig-name descname"><span class="pre">sample</span></span><span class="sig-paren">(</span><em class="sig-param"><span class="n"><span class="pre">mask</span></span><span class="p"><span class="pre">:</span></span><span class="w"> </span><span class="n"><span class="pre">None</span></span><span class="w"> </span><span class="o"><span class="pre">=</span></span><span class="w"> </span><span class="default_value"><span class="pre">None</span></span></em><span class="sig-paren">)</span> <span class="sig-return"><span class="sig-return-icon">&#x2192;</span> <span class="sig-return-typehint"><span class="pre">ndarray</span></span></span><a class="headerlink" href="#gymnasium.spaces.Box.sample" title="Permalink to this definition">#</a></dt>
<dd><p>Generates a single random sample inside the Box.</p>
<p>In creating a sample of the box, each coordinate is sampled (independently) from a distribution
that is chosen according to the form of the interval:</p>
<ul class="simple">
<li><p><span class="math notranslate nohighlight">\([a, b]\)</span> : uniform distribution</p></li>
<li><p><span class="math notranslate nohighlight">\([a, \infty)\)</span> : shifted exponential distribution</p></li>
<li><p><span class="math notranslate nohighlight">\((-\infty, b]\)</span> : shifted negative exponential distribution</p></li>
<li><p><span class="math notranslate nohighlight">\((-\infty, \infty)\)</span> : normal distribution</p></li>
</ul>
<dl class="field-list simple">
<dt class="field-odd">Parameters<span class="colon">:</span></dt>
<dd class="field-odd"><p><strong>mask</strong> – A mask for sampling values from the Box space, currently unsupported.</p>
</dd>
<dt class="field-even">Returns<span class="colon">:</span></dt>
<dd class="field-even"><p><strong>A sampled value from the Box</strong></p>
</dd>
</dl>
</dd></dl>
</dd></dl>
</section>
<section id="discrete">
<h3>Discrete<a class="headerlink" href="#discrete" title="Permalink to this heading">#</a></h3>
<dl class="py class">
<dt class="sig sig-object py" id="gymnasium.spaces.Discrete">
<em class="property"><span class="pre">class</span><span class="w"> </span></em><span class="sig-prename descclassname"><span class="pre">gymnasium.spaces.</span></span><span class="sig-name descname"><span class="pre">Discrete</span></span><span class="sig-paren">(</span><em class="sig-param"><span class="n"><span class="pre">n</span></span><span class="p"><span class="pre">:</span></span><span class="w"> </span><span class="n"><span class="pre">int</span></span></em>, <em class="sig-param"><span class="n"><span class="pre">seed</span></span><span class="p"><span class="pre">:</span></span><span class="w"> </span><span class="n"><span class="pre">Optional</span><span class="p"><span class="pre">[</span></span><span class="pre">Union</span><span class="p"><span class="pre">[</span></span><span class="pre">int</span><span class="p"><span class="pre">,</span></span><span class="w"> </span><span class="pre">Generator</span><span class="p"><span class="pre">]</span></span><span class="p"><span class="pre">]</span></span></span><span class="w"> </span><span class="o"><span class="pre">=</span></span><span class="w"> </span><span class="default_value"><span class="pre">None</span></span></em>, <em class="sig-param"><span class="n"><span class="pre">start</span></span><span class="p"><span class="pre">:</span></span><span class="w"> </span><span class="n"><span class="pre">int</span></span><span class="w"> </span><span class="o"><span class="pre">=</span></span><span class="w"> </span><span class="default_value"><span class="pre">0</span></span></em><span class="sig-paren">)</span><a class="headerlink" href="#gymnasium.spaces.Discrete" title="Permalink to this definition">#</a></dt>
<dd><p>A space consisting of finitely many elements.</p>
<p>This class represents a finite subset of integers, more specifically a set of the form <span class="math notranslate nohighlight">\(\{ a, a+1, \dots, a+n-1 \}\)</span>.</p>
<p>Example:</p>
<div class="highlight-default notranslate"><div class="highlight"><pre><span></span><span class="gp">&gt;&gt;&gt; </span><span class="n">Discrete</span><span class="p">(</span><span class="mi">2</span><span class="p">)</span> <span class="c1"># {0, 1}</span>
<span class="gp">&gt;&gt;&gt; </span><span class="n">Discrete</span><span class="p">(</span><span class="mi">3</span><span class="p">,</span> <span class="n">start</span><span class="o">=-</span><span class="mi">1</span><span class="p">)</span> <span class="c1"># {-1, 0, 1}</span>
</pre></div>
</div>
<p>Constructor of <a class="reference internal" href="#gymnasium.spaces.Discrete" title="gymnasium.spaces.Discrete"><code class="xref py py-class docutils literal notranslate"><span class="pre">Discrete</span></code></a> space.</p>
<p>This will construct the space <span class="math notranslate nohighlight">\(\{\text{start}, ..., \text{start} + n - 1\}\)</span>.</p>
<dl class="field-list simple">
<dt class="field-odd">Parameters<span class="colon">:</span></dt>
<dd class="field-odd"><ul class="simple">
<li><p><strong>n</strong> (<em>int</em>) – The number of elements of this space.</p></li>
<li><p><strong>seed</strong> – Optionally, you can use this argument to seed the RNG that is used to sample from the <code class="docutils literal notranslate"><span class="pre">Dict</span></code> space.</p></li>
<li><p><strong>start</strong> (<em>int</em>) – The smallest element of this space.</p></li>
</ul>
</dd>
</dl>
<dl class="py method">
<dt class="sig sig-object py" id="gymnasium.spaces.Discrete.sample">
<span class="sig-name descname"><span class="pre">sample</span></span><span class="sig-paren">(</span><em class="sig-param"><span class="n"><span class="pre">mask</span></span><span class="p"><span class="pre">:</span></span><span class="w"> </span><span class="n"><span class="pre">Optional</span><span class="p"><span class="pre">[</span></span><span class="pre">ndarray</span><span class="p"><span class="pre">]</span></span></span><span class="w"> </span><span class="o"><span class="pre">=</span></span><span class="w"> </span><span class="default_value"><span class="pre">None</span></span></em><span class="sig-paren">)</span> <span class="sig-return"><span class="sig-return-icon">&#x2192;</span> <span class="sig-return-typehint"><span class="pre">int</span></span></span><a class="headerlink" href="#gymnasium.spaces.Discrete.sample" title="Permalink to this definition">#</a></dt>
<dd><p>Generates a single random sample from this space.</p>
<p>A sample will be chosen uniformly at random with the mask if provided</p>
<dl class="field-list simple">
<dt class="field-odd">Parameters<span class="colon">:</span></dt>
<dd class="field-odd"><p><strong>mask</strong> – An optional mask for if an action can be selected.
Expected <cite>np.ndarray</cite> of shape <cite>(n,)</cite> and dtype <cite>np.int8</cite> where <cite>1</cite> represents valid actions and <cite>0</cite> invalid / infeasible actions.
If there are no possible actions (i.e. <cite>np.all(mask == 0)</cite>) then <cite>space.start</cite> will be returned.</p>
</dd>
<dt class="field-even">Returns<span class="colon">:</span></dt>
<dd class="field-even"><p><strong>A sampled integer from the space</strong></p>
</dd>
</dl>
</dd></dl>
</dd></dl>
</section>
<section id="multibinary">
<h3>MultiBinary<a class="headerlink" href="#multibinary" title="Permalink to this heading">#</a></h3>
<dl class="py class">
<dt class="sig sig-object py" id="gymnasium.spaces.MultiBinary">
<em class="property"><span class="pre">class</span><span class="w"> </span></em><span class="sig-prename descclassname"><span class="pre">gymnasium.spaces.</span></span><span class="sig-name descname"><span class="pre">MultiBinary</span></span><span class="sig-paren">(</span><em class="sig-param"><span class="n"><span class="pre">n</span></span><span class="p"><span class="pre">:</span></span><span class="w"> </span><span class="n"><span class="pre">Union</span><span class="p"><span class="pre">[</span></span><span class="pre">ndarray</span><span class="p"><span class="pre">,</span></span><span class="w"> </span><span class="pre">Sequence</span><span class="p"><span class="pre">[</span></span><span class="pre">int</span><span class="p"><span class="pre">]</span></span><span class="p"><span class="pre">,</span></span><span class="w"> </span><span class="pre">int</span><span class="p"><span class="pre">]</span></span></span></em>, <em class="sig-param"><span class="n"><span class="pre">seed</span></span><span class="p"><span class="pre">:</span></span><span class="w"> </span><span class="n"><span class="pre">Optional</span><span class="p"><span class="pre">[</span></span><span class="pre">Union</span><span class="p"><span class="pre">[</span></span><span class="pre">int</span><span class="p"><span class="pre">,</span></span><span class="w"> </span><span class="pre">Generator</span><span class="p"><span class="pre">]</span></span><span class="p"><span class="pre">]</span></span></span><span class="w"> </span><span class="o"><span class="pre">=</span></span><span class="w"> </span><span class="default_value"><span class="pre">None</span></span></em><span class="sig-paren">)</span><a class="headerlink" href="#gymnasium.spaces.MultiBinary" title="Permalink to this definition">#</a></dt>
<dd><p>An n-shape binary space.</p>
<p>Elements of this space are binary arrays of a shape that is fixed during construction.</p>
<p>Example Usage:</p>
<div class="highlight-default notranslate"><div class="highlight"><pre><span></span><span class="gp">&gt;&gt;&gt; </span><span class="n">observation_space</span> <span class="o">=</span> <span class="n">MultiBinary</span><span class="p">(</span><span class="mi">5</span><span class="p">)</span>
<span class="gp">&gt;&gt;&gt; </span><span class="n">observation_space</span><span class="o">.</span><span class="n">sample</span><span class="p">()</span>
<span class="go"> array([0, 1, 0, 1, 0], dtype=int8)</span>
<span class="gp">&gt;&gt;&gt; </span><span class="n">observation_space</span> <span class="o">=</span> <span class="n">MultiBinary</span><span class="p">([</span><span class="mi">3</span><span class="p">,</span> <span class="mi">2</span><span class="p">])</span>
<span class="gp">&gt;&gt;&gt; </span><span class="n">observation_space</span><span class="o">.</span><span class="n">sample</span><span class="p">()</span>
<span class="go"> array([[0, 0],</span>
<span class="go"> [0, 1],</span>
<span class="go"> [1, 1]], dtype=int8)</span>
</pre></div>
</div>
<p>Constructor of <a class="reference internal" href="#gymnasium.spaces.MultiBinary" title="gymnasium.spaces.MultiBinary"><code class="xref py py-class docutils literal notranslate"><span class="pre">MultiBinary</span></code></a> space.</p>
<dl class="field-list simple">
<dt class="field-odd">Parameters<span class="colon">:</span></dt>
<dd class="field-odd"><ul class="simple">
<li><p><strong>n</strong> – This will fix the shape of elements of the space. It can either be an integer (if the space is flat)
or some sort of sequence (tuple, list or np.ndarray) if there are multiple axes.</p></li>
<li><p><strong>seed</strong> – Optionally, you can use this argument to seed the RNG that is used to sample from the space.</p></li>
</ul>
</dd>
</dl>
<dl class="py method">
<dt class="sig sig-object py" id="gymnasium.spaces.MultiBinary.sample">
<span class="sig-name descname"><span class="pre">sample</span></span><span class="sig-paren">(</span><em class="sig-param"><span class="n"><span class="pre">mask</span></span><span class="p"><span class="pre">:</span></span><span class="w"> </span><span class="n"><span class="pre">Optional</span><span class="p"><span class="pre">[</span></span><span class="pre">ndarray</span><span class="p"><span class="pre">]</span></span></span><span class="w"> </span><span class="o"><span class="pre">=</span></span><span class="w"> </span><span class="default_value"><span class="pre">None</span></span></em><span class="sig-paren">)</span> <span class="sig-return"><span class="sig-return-icon">&#x2192;</span> <span class="sig-return-typehint"><span class="pre">ndarray</span></span></span><a class="headerlink" href="#gymnasium.spaces.MultiBinary.sample" title="Permalink to this definition">#</a></dt>
<dd><p>Generates a single random sample from this space.</p>
<p>A sample is drawn by independent, fair coin tosses (one toss per binary variable of the space).</p>
<dl class="field-list simple">
<dt class="field-odd">Parameters<span class="colon">:</span></dt>
<dd class="field-odd"><p><strong>mask</strong> – An optional np.ndarray to mask samples with expected shape of <code class="docutils literal notranslate"><span class="pre">space.shape</span></code>.
For mask == 0 then the samples will be 0 and mask == 1 then random samples will be generated.
The expected mask shape is the space shape and mask dtype is <cite>np.int8</cite>.</p>
</dd>
<dt class="field-even">Returns<span class="colon">:</span></dt>
<dd class="field-even"><p><strong>Sampled values from space</strong></p>
</dd>
</dl>
</dd></dl>
</dd></dl>
</section>
<section id="multidiscrete">
<h3>MultiDiscrete<a class="headerlink" href="#multidiscrete" title="Permalink to this heading">#</a></h3>
<dl class="py class">
<dt class="sig sig-object py" id="gymnasium.spaces.MultiDiscrete">
<em class="property"><span class="pre">class</span><span class="w"> </span></em><span class="sig-prename descclassname"><span class="pre">gymnasium.spaces.</span></span><span class="sig-name descname"><span class="pre">MultiDiscrete</span></span><span class="sig-paren">(</span><em class="sig-param"><span class="pre">nvec:</span> <span class="pre">~typing.Union[~numpy.ndarray,</span> <span class="pre">list],</span> <span class="pre">dtype=&lt;class</span> <span class="pre">'numpy.int64'&gt;,</span> <span class="pre">seed:</span> <span class="pre">~typing.Optional[~typing.Union[int,</span> <span class="pre">~numpy.random._generator.Generator]]</span> <span class="pre">=</span> <span class="pre">None</span></em><span class="sig-paren">)</span><a class="headerlink" href="#gymnasium.spaces.MultiDiscrete" title="Permalink to this definition">#</a></dt>
<dd><p>This represents the cartesian product of arbitrary <a class="reference internal" href="#gymnasium.spaces.Discrete" title="gymnasium.spaces.Discrete"><code class="xref py py-class docutils literal notranslate"><span class="pre">Discrete</span></code></a> spaces.</p>
<p>It is useful to represent game controllers or keyboards where each key can be represented as a discrete action space.</p>
<div class="admonition note">
<p class="admonition-title">Note</p>
<p>Some environment wrappers assume a value of 0 always represents the NOOP action.</p>
</div>
<p>e.g. Nintendo Game Controller - Can be conceptualized as 3 discrete action spaces:</p>
<ol class="arabic simple">
<li><p>Arrow Keys: Discrete 5 - NOOP[0], UP[1], RIGHT[2], DOWN[3], LEFT[4] - params: min: 0, max: 4</p></li>
<li><p>Button A: Discrete 2 - NOOP[0], Pressed[1] - params: min: 0, max: 1</p></li>
<li><p>Button B: Discrete 2 - NOOP[0], Pressed[1] - params: min: 0, max: 1</p></li>
</ol>
<p>It can be initialized as <code class="docutils literal notranslate"><span class="pre">MultiDiscrete([</span> <span class="pre">5,</span> <span class="pre">2,</span> <span class="pre">2</span> <span class="pre">])</span></code> such that a sample might be <code class="docutils literal notranslate"><span class="pre">array([3,</span> <span class="pre">1,</span> <span class="pre">0])</span></code>.</p>
<p>Although this feature is rarely used, <a class="reference internal" href="#gymnasium.spaces.MultiDiscrete" title="gymnasium.spaces.MultiDiscrete"><code class="xref py py-class docutils literal notranslate"><span class="pre">MultiDiscrete</span></code></a> spaces may also have several axes
if <code class="docutils literal notranslate"><span class="pre">nvec</span></code> has several axes:</p>
<p>Example:</p>
<div class="highlight-default notranslate"><div class="highlight"><pre><span></span><span class="o">&gt;&gt;</span> <span class="n">d</span> <span class="o">=</span> <span class="n">MultiDiscrete</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="mi">1</span><span class="p">,</span> <span class="mi">2</span><span class="p">],</span> <span class="p">[</span><span class="mi">3</span><span class="p">,</span> <span class="mi">4</span><span class="p">]]))</span>
<span class="o">&gt;&gt;</span> <span class="n">d</span><span class="o">.</span><span class="n">sample</span><span class="p">()</span>
<span class="n">array</span><span class="p">([[</span><span class="mi">0</span><span class="p">,</span> <span class="mi">0</span><span class="p">],</span>
<span class="p">[</span><span class="mi">2</span><span class="p">,</span> <span class="mi">3</span><span class="p">]])</span>
</pre></div>
</div>
<p>Constructor of <a class="reference internal" href="#gymnasium.spaces.MultiDiscrete" title="gymnasium.spaces.MultiDiscrete"><code class="xref py py-class docutils literal notranslate"><span class="pre">MultiDiscrete</span></code></a> space.</p>
<p>The argument <code class="docutils literal notranslate"><span class="pre">nvec</span></code> will determine the number of values each categorical variable can take.</p>
<dl class="field-list simple">
<dt class="field-odd">Parameters<span class="colon">:</span></dt>
<dd class="field-odd"><ul class="simple">
<li><p><strong>nvec</strong> – vector of counts of each categorical variable. This will usually be a list of integers. However,
you may also pass a more complicated numpy array if you’d like the space to have several axes.</p></li>
<li><p><strong>dtype</strong> – This should be some kind of integer type.</p></li>
<li><p><strong>seed</strong> – Optionally, you can use this argument to seed the RNG that is used to sample from the space.</p></li>
</ul>
</dd>
</dl>
<dl class="py method">
<dt class="sig sig-object py" id="gymnasium.spaces.MultiDiscrete.sample">
<span class="sig-name descname"><span class="pre">sample</span></span><span class="sig-paren">(</span><em class="sig-param"><span class="n"><span class="pre">mask</span></span><span class="p"><span class="pre">:</span></span><span class="w"> </span><span class="n"><span class="pre">Optional</span><span class="p"><span class="pre">[</span></span><span class="pre">tuple</span><span class="p"><span class="pre">]</span></span></span><span class="w"> </span><span class="o"><span class="pre">=</span></span><span class="w"> </span><span class="default_value"><span class="pre">None</span></span></em><span class="sig-paren">)</span> <span class="sig-return"><span class="sig-return-icon">&#x2192;</span> <span class="sig-return-typehint"><span class="pre">ndarray</span></span></span><a class="headerlink" href="#gymnasium.spaces.MultiDiscrete.sample" title="Permalink to this definition">#</a></dt>
<dd><p>Generates a single random sample this space.</p>
<dl class="field-list simple">
<dt class="field-odd">Parameters<span class="colon">:</span></dt>
<dd class="field-odd"><p><strong>mask</strong> – An optional mask for multi-discrete, expects tuples with a <cite>np.ndarray</cite> mask in the position of each
action with shape <cite>(n,)</cite> where <cite>n</cite> is the number of actions and <cite>dtype=np.int8</cite>.
Only mask values == 1 are possible to sample unless all mask values for an action are 0 then the default action 0 is sampled.</p>
</dd>
<dt class="field-even">Returns<span class="colon">:</span></dt>
<dd class="field-even"><p><strong>An `np.ndarray` of shape `space.shape`</strong></p>
</dd>
</dl>
</dd></dl>
</dd></dl>
</section>
<section id="text">
<h3>Text<a class="headerlink" href="#text" title="Permalink to this heading">#</a></h3>
<dl class="py class">
<dt class="sig sig-object py" id="gymnasium.spaces.Text">
<em class="property"><span class="pre">class</span><span class="w"> </span></em><span class="sig-prename descclassname"><span class="pre">gymnasium.spaces.</span></span><span class="sig-name descname"><span class="pre">Text</span></span><span class="sig-paren">(</span><em class="sig-param"><span class="n"><span class="pre">max_length</span></span><span class="p"><span class="pre">:</span></span><span class="w"> </span><span class="n"><span class="pre">int</span></span></em>, <em class="sig-param"><span class="o"><span class="pre">*</span></span></em>, <em class="sig-param"><span class="n"><span class="pre">min_length</span></span><span class="p"><span class="pre">:</span></span><span class="w"> </span><span class="n"><span class="pre">int</span></span><span class="w"> </span><span class="o"><span class="pre">=</span></span><span class="w"> </span><span class="default_value"><span class="pre">1</span></span></em>, <em class="sig-param"><span class="n"><span class="pre">charset</span></span><span class="p"><span class="pre">:</span></span><span class="w"> </span><span class="n"><span class="pre">Union</span><span class="p"><span class="pre">[</span></span><span class="pre">Set</span><span class="p"><span class="pre">[</span></span><span class="pre">str</span><span class="p"><span class="pre">]</span></span><span class="p"><span class="pre">,</span></span><span class="w"> </span><span class="pre">str</span><span class="p"><span class="pre">]</span></span></span><span class="w"> </span><span class="o"><span class="pre">=</span></span><span class="w"> </span><span class="default_value"><span class="pre">frozenset({'0',</span> <span class="pre">'1',</span> <span class="pre">'2',</span> <span class="pre">'3',</span> <span class="pre">'4',</span> <span class="pre">'5',</span> <span class="pre">'6',</span> <span class="pre">'7',</span> <span class="pre">'8',</span> <span class="pre">'9',</span> <span class="pre">'A',</span> <span class="pre">'B',</span> <span class="pre">'C',</span> <span class="pre">'D',</span> <span class="pre">'E',</span> <span class="pre">'F',</span> <span class="pre">'G',</span> <span class="pre">'H',</span> <span class="pre">'I',</span> <span class="pre">'J',</span> <span class="pre">'K',</span> <span class="pre">'L',</span> <span class="pre">'M',</span> <span class="pre">'N',</span> <span class="pre">'O',</span> <span class="pre">'P',</span> <span class="pre">'Q',</span> <span class="pre">'R',</span> <span class="pre">'S',</span> <span class="pre">'T',</span> <span class="pre">'U',</span> <span class="pre">'V',</span> <span class="pre">'W',</span> <span class="pre">'X',</span> <span class="pre">'Y',</span> <span class="pre">'Z',</span> <span class="pre">'a',</span> <span class="pre">'b',</span> <span class="pre">'c',</span> <span class="pre">'d',</span> <span class="pre">'e',</span> <span class="pre">'f',</span> <span class="pre">'g',</span> <span class="pre">'h',</span> <span class="pre">'i',</span> <span class="pre">'j',</span> <span class="pre">'k',</span> <span class="pre">'l',</span> <span class="pre">'m',</span> <span class="pre">'n',</span> <span class="pre">'o',</span> <span class="pre">'p',</span> <span class="pre">'q',</span> <span class="pre">'r',</span> <span class="pre">'s',</span> <span class="pre">'t',</span> <span class="pre">'u',</span> <span class="pre">'v',</span> <span class="pre">'w',</span> <span class="pre">'x',</span> <span class="pre">'y',</span> <span class="pre">'z'})</span></span></em>, <em class="sig-param"><span class="n"><span class="pre">seed</span></span><span class="p"><span class="pre">:</span></span><span class="w"> </span><span class="n"><span class="pre">Optional</span><span class="p"><span class="pre">[</span></span><span class="pre">Union</span><span class="p"><span class="pre">[</span></span><span class="pre">int</span><span class="p"><span class="pre">,</span></span><span class="w"> </span><span class="pre">Generator</span><span class="p"><span class="pre">]</span></span><span class="p"><span class="pre">]</span></span></span><span class="w"> </span><span class="o
<dd><p>A space representing a string comprised of characters from a given charset.</p>
<dl>
<dt>Example::</dt><dd><div class="doctest highlight-default notranslate"><div class="highlight"><pre><span></span><span class="gp">&gt;&gt;&gt; </span><span class="c1"># {&quot;&quot;, &quot;B5&quot;, &quot;hello&quot;, ...}</span>
<span class="gp">&gt;&gt;&gt; </span><span class="n">Text</span><span class="p">(</span><span class="mi">5</span><span class="p">)</span>
<span class="gp">&gt;&gt;&gt; </span><span class="c1"># {&quot;0&quot;, &quot;42&quot;, &quot;0123456789&quot;, ...}</span>
<span class="gp">&gt;&gt;&gt; </span><span class="kn">import</span> <span class="nn">string</span>
<span class="gp">&gt;&gt;&gt; </span><span class="n">Text</span><span class="p">(</span><span class="n">min_length</span> <span class="o">=</span> <span class="mi">1</span><span class="p">,</span>
<span class="gp">... </span> <span class="n">max_length</span> <span class="o">=</span> <span class="mi">10</span><span class="p">,</span>
<span class="gp">... </span> <span class="n">charset</span> <span class="o">=</span> <span class="n">string</span><span class="o">.</span><span class="n">digits</span><span class="p">)</span>
</pre></div>
</div>
</dd>
</dl>
<p>Constructor of <a class="reference internal" href="#gymnasium.spaces.Text" title="gymnasium.spaces.Text"><code class="xref py py-class docutils literal notranslate"><span class="pre">Text</span></code></a> space.</p>
<p>Both bounds for text length are inclusive.</p>
<dl class="field-list simple">
<dt class="field-odd">Parameters<span class="colon">:</span></dt>
<dd class="field-odd"><ul class="simple">
<li><p><strong>min_length</strong> (<em>int</em>) – Minimum text length (in characters). Defaults to 1 to prevent empty strings.</p></li>
<li><p><strong>max_length</strong> (<em>int</em>) – Maximum text length (in characters).</p></li>
<li><p><strong>charset</strong> (<em>Union</em><em>[</em><em>set</em><em>]</em><em>, </em><em>str</em>) – Character set, defaults to the lower and upper english alphabet plus latin digits.</p></li>
<li><p><strong>seed</strong> – The seed for sampling from the space.</p></li>
</ul>
</dd>
</dl>
<dl class="py method">
<dt class="sig sig-object py" id="gymnasium.spaces.Text.sample">
<span class="sig-name descname"><span class="pre">sample</span></span><span class="sig-paren">(</span><em class="sig-param"><span class="n"><span class="pre">mask</span></span><span class="p"><span class="pre">:</span></span><span class="w"> </span><span class="n"><span class="pre">Optional</span><span class="p"><span class="pre">[</span></span><span class="pre">Tuple</span><span class="p"><span class="pre">[</span></span><span class="pre">Optional</span><span class="p"><span class="pre">[</span></span><span class="pre">int</span><span class="p"><span class="pre">]</span></span><span class="p"><span class="pre">,</span></span><span class="w"> </span><span class="pre">Optional</span><span class="p"><span class="pre">[</span></span><span class="pre">ndarray</span><span class="p"><span class="pre">]</span></span><span class="p"><span class="pre">]</span></span><span class="p"><span class="pre">]</span></span></span><span class="w"> </span><span class="o"><span class="pre">=</span></span><span class="w"> </span><span class="default_value"><span class="pre">None</span></span></em><span class="sig-paren">)</span> <span class="sig-return"><span class="sig-return-icon">&#x2192;</span> <span class="sig-return-typehint"><span class="pre">str</span></span></span><a class="headerlink" href="#gymnasium.spaces.Text.sample" title="Permalink to this definition">#</a></dt>
<dd><p>Generates a single random sample from this space with by default a random length between <cite>min_length</cite> and <cite>max_length</cite> and sampled from the <cite>charset</cite>.</p>
<dl class="field-list simple">
<dt class="field-odd">Parameters<span class="colon">:</span></dt>
<dd class="field-odd"><p><strong>mask</strong> – An optional tuples of length and mask for the text.
The length is expected to be between the <cite>min_length</cite> and <cite>max_length</cite> otherwise a random integer between <cite>min_length</cite> and <cite>max_length</cite> is selected.
For the mask, we expect a numpy array of length of the charset passed with <cite>dtype == np.int8</cite>.
If the charlist mask is all zero then an empty string is returned no matter the <cite>min_length</cite></p>
</dd>
<dt class="field-even">Returns<span class="colon">:</span></dt>
<dd class="field-even"><p><strong>A sampled string from the space</strong></p>
</dd>
</dl>
</dd></dl>
</dd></dl>
</section>
</section>
<section id="composite-spaces">
<h2>Composite Spaces<a class="headerlink" href="#composite-spaces" title="Permalink to this heading">#</a></h2>
<section id="dict">
<h3>Dict<a class="headerlink" href="#dict" title="Permalink to this heading">#</a></h3>
<dl class="py class">
<dt class="sig sig-object py" id="gymnasium.spaces.Dict">
<em class="property"><span class="pre">class</span><span class="w"> </span></em><span class="sig-prename descclassname"><span class="pre">gymnasium.spaces.</span></span><span class="sig-name descname"><span class="pre">Dict</span></span><span class="sig-paren">(</span><em class="sig-param"><span class="n"><span class="pre">spaces</span></span><span class="p"><span class="pre">:</span></span><span class="w"> </span><span class="n"><span class="pre">Optional</span><span class="p"><span class="pre">[</span></span><span class="pre">Union</span><span class="p"><span class="pre">[</span></span><span class="pre">Dict</span><span class="p"><span class="pre">[</span></span><span class="pre">str</span><span class="p"><span class="pre">,</span></span><span class="w"> </span><a class="reference internal" href="#gymnasium.spaces.Space" title="gymnasium.spaces.space.Space"><span class="pre">Space</span></a><span class="p"><span class="pre">]</span></span><span class="p"><span class="pre">,</span></span><span class="w"> </span><span class="pre">Sequence</span><span class="p"><span class="pre">[</span></span><span class="pre">Tuple</span><span class="p"><span class="pre">[</span></span><span class="pre">str</span><span class="p"><span class="pre">,</span></span><span class="w"> </span><a class="reference internal" href="#gymnasium.spaces.Space" title="gymnasium.spaces.space.Space"><span class="pre">Space</span></a><span class="p"><span class="pre">]</span></span><span class="p"><span class="pre">]</span></span><span class="p"><span class="pre">]</span></span><span class="p"><span class="pre">]</span></span></span><span class="w"> </span><span class="o"><span class="pre">=</span></span><span class="w"> </span><span class="default_value"><span class="pre">None</span></span></em>, <em class="sig-param"><span class="n"><span class="pre">seed</span></span><span class="p"><span class="pre">:</span></span><span class="w"> </span><span class="n"><span class="pre">Optional</span><span class="p"><span class="pre">[</span></span><span class="pre">Union</span><span class="p"><span class="pre">[</span></span><span class="pre">dict</span><span class="p"><span class="pre">,</span></span><span class="w"> </span><span class="pre">int</span><span class="p"><span class="pre">,</span></span><span class="w"> </span><span class="pre">Generator</span><span class="p"><span class="pre">]</span></span><span class="p"><span class="pre">]</span></span></span><span class="w"> </span><span class="o"><span class="pre">=</span></span><span class="w"> </span><span class="default_value"><span class="pre">None</span></span></em>, <em class="sig-param"><span class="o"><span class="pre">**</span></span><span class="n"><span class="pre">spaces_kwargs</span></span><span class="p"><span class="pre">:</span></span><span class="w"> </span><span class="n"><a class="reference internal" href="#gymnasium.spaces.Space" title="gymnasium.spaces.space.Space"><span class="pre">Space</span></a></span></em><span class="sig-paren">)</span><a class="headerlink" href="#gymnasium.spaces.Dict" title="Permalink to this definition">#</a></dt>
<dd><p>A dictionary of <a class="reference internal" href="#gymnasium.spaces.Space" title="gymnasium.spaces.Space"><code class="xref py py-class docutils literal notranslate"><span class="pre">Space</span></code></a> instances.</p>
<p>Elements of this space are (ordered) dictionaries of elements from the constituent spaces.</p>
<p>Example usage:</p>
<div class="doctest highlight-default notranslate"><div class="highlight"><pre><span></span><span class="gp">&gt;&gt;&gt; </span><span class="kn">from</span> <span class="nn">gymnasium.spaces</span> <span class="kn">import</span> <span class="n">Dict</span><span class="p">,</span> <span class="n">Discrete</span>
<span class="gp">&gt;&gt;&gt; </span><span class="n">observation_space</span> <span class="o">=</span> <span class="n">Dict</span><span class="p">({</span><span class="s2">&quot;position&quot;</span><span class="p">:</span> <span class="n">Discrete</span><span class="p">(</span><span class="mi">2</span><span class="p">),</span> <span class="s2">&quot;velocity&quot;</span><span class="p">:</span> <span class="n">Discrete</span><span class="p">(</span><span class="mi">3</span><span class="p">)})</span>
<span class="gp">&gt;&gt;&gt; </span><span class="n">observation_space</span><span class="o">.</span><span class="n">sample</span><span class="p">()</span>
<span class="go">OrderedDict([(&#39;position&#39;, 1), (&#39;velocity&#39;, 2)])</span>
</pre></div>
</div>
<p>Example usage [nested]:</p>
<div class="highlight-default notranslate"><div class="highlight"><pre><span></span><span class="gp">&gt;&gt;&gt; </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">Discrete</span><span class="p">,</span> <span class="n">MultiBinary</span><span class="p">,</span> <span class="n">MultiDiscrete</span>
<span class="gp">&gt;&gt;&gt; </span><span class="n">Dict</span><span class="p">(</span>
<span class="gp">... </span> <span class="p">{</span>
<span class="gp">... </span> <span class="s2">&quot;ext_controller&quot;</span><span class="p">:</span> <span class="n">MultiDiscrete</span><span class="p">([</span><span class="mi">5</span><span class="p">,</span> <span class="mi">2</span><span class="p">,</span> <span class="mi">2</span><span class="p">]),</span>
<span class="gp">... </span> <span class="s2">&quot;inner_state&quot;</span><span class="p">:</span> <span class="n">Dict</span><span class="p">(</span>
<span class="gp">... </span> <span class="p">{</span>
<span class="gp">... </span> <span class="s2">&quot;charge&quot;</span><span class="p">:</span> <span class="n">Discrete</span><span class="p">(</span><span class="mi">100</span><span class="p">),</span>
<span class="gp">... </span> <span class="s2">&quot;system_checks&quot;</span><span class="p">:</span> <span class="n">MultiBinary</span><span class="p">(</span><span class="mi">10</span><span class="p">),</span>
<span class="gp">... </span> <span class="s2">&quot;job_status&quot;</span><span class="p">:</span> <span class="n">Dict</span><span class="p">(</span>
<span class="gp">... </span> <span class="p">{</span>
<span class="gp">... </span> <span class="s2">&quot;task&quot;</span><span class="p">:</span> <span class="n">Discrete</span><span class="p">(</span><span class="mi">5</span><span class="p">),</span>
<span class="gp">... </span> <span class="s2">&quot;progress&quot;</span><span class="p">:</span> <span class="n">Box</span><span class="p">(</span><span class="n">low</span><span class="o">=</span><span class="mi">0</span><span class="p">,</span> <span class="n">high</span><span class="o">=</span><span class="mi">100</span><span class="p">,</span> <span class="n">shape</span><span class="o">=</span><span class="p">()),</span>
<span class="gp">... </span> <span class="p">}</span>
<span class="gp">... </span> <span class="p">),</span>
<span class="gp">... </span> <span class="p">}</span>
<span class="gp">... </span> <span class="p">),</span>
<span class="gp">... </span> <span class="p">}</span>
<span class="gp">... </span><span class="p">)</span>
</pre></div>
</div>
<p>It can be convenient to use <a class="reference internal" href="#gymnasium.spaces.Dict" title="gymnasium.spaces.Dict"><code class="xref py py-class docutils literal notranslate"><span class="pre">Dict</span></code></a> spaces if you want to make complex observations or actions more human-readable.
Usually, it will not be possible to use elements of this space directly in learning code. However, you can easily
convert <cite>Dict</cite> observations to flat arrays by using a <code class="xref py py-class docutils literal notranslate"><span class="pre">gym.wrappers.FlattenObservation</span></code> wrapper. Similar wrappers can be
implemented to deal with <a class="reference internal" href="#gymnasium.spaces.Dict" title="gymnasium.spaces.Dict"><code class="xref py py-class docutils literal notranslate"><span class="pre">Dict</span></code></a> actions.</p>
<p>Constructor of <a class="reference internal" href="#gymnasium.spaces.Dict" title="gymnasium.spaces.Dict"><code class="xref py py-class docutils literal notranslate"><span class="pre">Dict</span></code></a> space.</p>
<p>This space can be instantiated in one of two ways: Either you pass a dictionary
of spaces to <code class="xref py py-meth docutils literal notranslate"><span class="pre">__init__()</span></code> via the <code class="docutils literal notranslate"><span class="pre">spaces</span></code> argument, or you pass the spaces as separate
keyword arguments (where you will need to avoid the keys <code class="docutils literal notranslate"><span class="pre">spaces</span></code> and <code class="docutils literal notranslate"><span class="pre">seed</span></code>)</p>
<p>Example:</p>
<div class="highlight-default notranslate"><div class="highlight"><pre><span></span><span class="gp">&gt;&gt;&gt; </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">Discrete</span>
<span class="gp">&gt;&gt;&gt; </span><span class="n">Dict</span><span class="p">({</span><span class="s2">&quot;position&quot;</span><span class="p">:</span> <span class="n">Box</span><span class="p">(</span><span class="o">-</span><span class="mi">1</span><span class="p">,</span> <span class="mi">1</span><span class="p">,</span> <span class="n">shape</span><span class="o">=</span><span class="p">(</span><span class="mi">2</span><span class="p">,)),</span> <span class="s2">&quot;color&quot;</span><span class="p">:</span> <span class="n">Discrete</span><span class="p">(</span><span class="mi">3</span><span class="p">)})</span>
<span class="go">Dict(color:Discrete(3), position:Box(-1.0, 1.0, (2,), float32))</span>
<span class="gp">&gt;&gt;&gt; </span><span class="n">Dict</span><span class="p">(</span><span class="n">position</span><span class="o">=</span><span class="n">Box</span><span class="p">(</span><span class="o">-</span><span class="mi">1</span><span class="p">,</span> <span class="mi">1</span><span class="p">,</span> <span class="n">shape</span><span class="o">=</span><span class="p">(</span><span class="mi">2</span><span class="p">,)),</span> <span class="n">color</span><span class="o">=</span><span class="n">Discrete</span><span class="p">(</span><span class="mi">3</span><span class="p">))</span>
<span class="go">Dict(color:Discrete(3), position:Box(-1.0, 1.0, (2,), float32))</span>
</pre></div>
</div>
<dl class="field-list simple">
<dt class="field-odd">Parameters<span class="colon">:</span></dt>
<dd class="field-odd"><ul class="simple">
<li><p><strong>spaces</strong> – A dictionary of spaces. This specifies the structure of the <a class="reference internal" href="#gymnasium.spaces.Dict" title="gymnasium.spaces.Dict"><code class="xref py py-class docutils literal notranslate"><span class="pre">Dict</span></code></a> space</p></li>
<li><p><strong>seed</strong> – Optionally, you can use this argument to seed the RNGs of the spaces that make up the <a class="reference internal" href="#gymnasium.spaces.Dict" title="gymnasium.spaces.Dict"><code class="xref py py-class docutils literal notranslate"><span class="pre">Dict</span></code></a> space.</p></li>
<li><p><strong>**spaces_kwargs</strong> – If <code class="docutils literal notranslate"><span class="pre">spaces</span></code> is <code class="docutils literal notranslate"><span class="pre">None</span></code>, you need to pass the constituent spaces as keyword arguments, as described above.</p></li>
</ul>
</dd>
</dl>
<dl class="py method">
<dt class="sig sig-object py" id="gymnasium.spaces.Dict.sample">
<span class="sig-name descname"><span class="pre">sample</span></span><span class="sig-paren">(</span><em class="sig-param"><span class="n"><span class="pre">mask</span></span><span class="p"><span class="pre">:</span></span><span class="w"> </span><span class="n"><span class="pre">Optional</span><span class="p"><span class="pre">[</span></span><span class="pre">Dict</span><span class="p"><span class="pre">[</span></span><span class="pre">str</span><span class="p"><span class="pre">,</span></span><span class="w"> </span><span class="pre">Any</span><span class="p"><span class="pre">]</span></span><span class="p"><span class="pre">]</span></span></span><span class="w"> </span><span class="o"><span class="pre">=</span></span><span class="w"> </span><span class="default_value"><span class="pre">None</span></span></em><span class="sig-paren">)</span> <span class="sig-return"><span class="sig-return-icon">&#x2192;</span> <span class="sig-return-typehint"><span class="pre">dict</span></span></span><a class="headerlink" href="#gymnasium.spaces.Dict.sample" title="Permalink to this definition">#</a></dt>
<dd><p>Generates a single random sample from this space.</p>
<p>The sample is an ordered dictionary of independent samples from the constituent spaces.</p>
<dl class="field-list simple">
<dt class="field-odd">Parameters<span class="colon">:</span></dt>
<dd class="field-odd"><p><strong>mask</strong> – An optional mask for each of the subspaces, expects the same keys as the space</p>
</dd>
<dt class="field-even">Returns<span class="colon">:</span></dt>
<dd class="field-even"><p><strong>A dictionary with the same key and sampled values from :attr:`self.spaces`</strong></p>
</dd>
</dl>
</dd></dl>
</dd></dl>
</section>
<section id="graph">
<h3>Graph<a class="headerlink" href="#graph" title="Permalink to this heading">#</a></h3>
<dl class="py class">
<dt class="sig sig-object py" id="gymnasium.spaces.Graph">
<em class="property"><span class="pre">class</span><span class="w"> </span></em><span class="sig-prename descclassname"><span class="pre">gymnasium.spaces.</span></span><span class="sig-name descname"><span class="pre">Graph</span></span><span class="sig-paren">(</span><em class="sig-param"><span class="n"><span class="pre">node_space</span></span><span class="p"><span class="pre">:</span></span><span class="w"> </span><span class="n"><span class="pre">Union</span><span class="p"><span class="pre">[</span></span><a class="reference internal" href="#gymnasium.spaces.Box" title="gymnasium.spaces.box.Box"><span class="pre">Box</span></a><span class="p"><span class="pre">,</span></span><span class="w"> </span><a class="reference internal" href="#gymnasium.spaces.Discrete" title="gymnasium.spaces.discrete.Discrete"><span class="pre">Discrete</span></a><span class="p"><span class="pre">]</span></span></span></em>, <em class="sig-param"><span class="n"><span class="pre">edge_space</span></span><span class="p"><span class="pre">:</span></span><span class="w"> </span><span class="n"><span class="pre">Union</span><span class="p"><span class="pre">[</span></span><span class="pre">None</span><span class="p"><span class="pre">,</span></span><span class="w"> </span><a class="reference internal" href="#gymnasium.spaces.Box" title="gymnasium.spaces.box.Box"><span class="pre">Box</span></a><span class="p"><span class="pre">,</span></span><span class="w"> </span><a class="reference internal" href="#gymnasium.spaces.Discrete" title="gymnasium.spaces.discrete.Discrete"><span class="pre">Discrete</span></a><span class="p"><span class="pre">]</span></span></span></em>, <em class="sig-param"><span class="n"><span class="pre">seed</span></span><span class="p"><span class="pre">:</span></span><span class="w"> </span><span class="n"><span class="pre">Optional</span><span class="p"><span class="pre">[</span></span><span class="pre">Union</span><span class="p"><span class="pre">[</span></span><span class="pre">int</span><span class="p"><span class="pre">,</span></span><span class="w"> </span><span class="pre">Generator</span><span class="p"><span class="pre">]</span></span><span class="p"><span class="pre">]</span></span></span><span class="w"> </span><span class="o"><span class="pre">=</span></span><span class="w"> </span><span class="default_value"><span class="pre">None</span></span></em><span class="sig-paren">)</span><a class="headerlink" href="#gymnasium.spaces.Graph" title="Permalink to this definition">#</a></dt>
<dd><p>A space representing graph information as a series of <cite>nodes</cite> connected with <cite>edges</cite> according to an adjacency matrix represented as a series of <cite>edge_links</cite>.</p>
<p>Example usage:</p>
<div class="highlight-default notranslate"><div class="highlight"><pre><span></span><span class="bp">self</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="n">Graph</span><span class="p">(</span><span class="n">node_space</span><span class="o">=</span><span class="n">space</span><span class="o">.</span><span class="n">Box</span><span class="p">(</span><span class="n">low</span><span class="o">=-</span><span class="mi">100</span><span class="p">,</span> <span class="n">high</span><span class="o">=</span><span class="mi">100</span><span class="p">,</span> <span class="n">shape</span><span class="o">=</span><span class="p">(</span><span class="mi">3</span><span class="p">,)),</span> <span class="n">edge_space</span><span class="o">=</span><span class="n">spaces</span><span class="o">.</span><span class="n">Discrete</span><span class="p">(</span><span class="mi">3</span><span class="p">))</span>
</pre></div>
</div>
<p>Constructor of <a class="reference internal" href="#gymnasium.spaces.Graph" title="gymnasium.spaces.Graph"><code class="xref py py-class docutils literal notranslate"><span class="pre">Graph</span></code></a>.</p>
<p>The argument <code class="docutils literal notranslate"><span class="pre">node_space</span></code> specifies the base space that each node feature will use.
This argument must be either a Box or Discrete instance.</p>
<p>The argument <code class="docutils literal notranslate"><span class="pre">edge_space</span></code> specifies the base space that each edge feature will use.
This argument must be either a None, Box or Discrete instance.</p>
<dl class="field-list simple">
<dt class="field-odd">Parameters<span class="colon">:</span></dt>
<dd class="field-odd"><ul class="simple">
<li><p><strong>node_space</strong> (<em>Union</em><em>[</em><a class="reference internal" href="#gymnasium.spaces.Box" title="gymnasium.spaces.Box"><em>Box</em></a><em>, </em><a class="reference internal" href="#gymnasium.spaces.Discrete" title="gymnasium.spaces.Discrete"><em>Discrete</em></a><em>]</em>) – space of the node features.</p></li>
<li><p><strong>edge_space</strong> (<em>Union</em><em>[</em><em>None</em><em>, </em><a class="reference internal" href="#gymnasium.spaces.Box" title="gymnasium.spaces.Box"><em>Box</em></a><em>, </em><a class="reference internal" href="#gymnasium.spaces.Discrete" title="gymnasium.spaces.Discrete"><em>Discrete</em></a><em>]</em>) – space of the node features.</p></li>
<li><p><strong>seed</strong> – Optionally, you can use this argument to seed the RNG that is used to sample from the space.</p></li>
</ul>
</dd>
</dl>
<dl class="py method">
<dt class="sig sig-object py" id="gymnasium.spaces.Graph.sample">
<span class="sig-name descname"><span class="pre">sample</span></span><span class="sig-paren">(</span><em class="sig-param"><span class="n"><span class="pre">mask</span></span><span class="p"><span class="pre">:</span></span><span class="w"> </span><span class="n"><span class="pre">Optional</span><span class="p"><span class="pre">[</span></span><span class="pre">Tuple</span><span class="p"><span class="pre">[</span></span><span class="pre">Optional</span><span class="p"><span class="pre">[</span></span><span class="pre">Union</span><span class="p"><span class="pre">[</span></span><span class="pre">ndarray</span><span class="p"><span class="pre">,</span></span><span class="w"> </span><span class="pre">tuple</span><span class="p"><span class="pre">]</span></span><span class="p"><span class="pre">]</span></span><span class="p"><span class="pre">,</span></span><span class="w"> </span><span class="pre">Optional</span><span class="p"><span class="pre">[</span></span><span class="pre">Union</span><span class="p"><span class="pre">[</span></span><span class="pre">ndarray</span><span class="p"><span class="pre">,</span></span><span class="w"> </span><span class="pre">tuple</span><span class="p"><span class="pre">]</span></span><span class="p"><span class="pre">]</span></span><span class="p"><span class="pre">]</span></span><span class="p"><span class="pre">]</span></span></span><span class="w"> </span><span class="o"><span class="pre">=</span></span><span class="w"> </span><span class="default_value"><span class="pre">None</span></span></em>, <em class="sig-param"><span class="n"><span class="pre">num_nodes</span></span><span class="p"><span class="pre">:</span></span><span class="w"> </span><span class="n"><span class="pre">int</span></span><span class="w"> </span><span class="o"><span class="pre">=</span></span><span class="w"> </span><span class="default_value"><span class="pre">10</span></span></em>, <em class="sig-param"><span class="n"><span class="pre">num_edges</span></span><span class="p"><span class="pre">:</span></span><span class="w"> </span><span class="n"><span class="pre">Optional</span><span class="p"><span class="pre">[</span></span><span class="pre">int</span><span class="p"><span class="pre">]</span></span></span><span class="w"> </span><span class="o"><span class="pre">=</span></span><span class="w"> </span><span class="default_value"><span class="pre">None</span></span></em><span class="sig-paren">)</span> <span class="sig-return"><span class="sig-return-icon">&#x2192;</span> <span class="sig-return-typehint"><span class="pre">GraphInstance</span></span></span><a class="headerlink" href="#gymnasium.spaces.Graph.sample" title="Permalink to this definition">#</a></dt>
<dd><p>Generates a single sample graph with num_nodes between 1 and 10 sampled from the Graph.</p>
<dl class="field-list simple">
<dt class="field-odd">Parameters<span class="colon">:</span></dt>
<dd class="field-odd"><ul class="simple">
<li><p><strong>mask</strong> – An optional tuple of optional node and edge mask that is only possible with Discrete spaces
(Box spaces don’t support sample masks).
If no <cite>num_edges</cite> is provided then the <cite>edge_mask</cite> is multiplied by the number of edges</p></li>
<li><p><strong>num_nodes</strong> – The number of nodes that will be sampled, the default is 10 nodes</p></li>
<li><p><strong>num_edges</strong> – An optional number of edges, otherwise, a random number between 0 and <a href="#id1"><span class="problematic" id="id2">`</span></a>num_nodes`^2</p></li>
</ul>
</dd>
<dt class="field-even">Returns<span class="colon">:</span></dt>
<dd class="field-even"><p><strong>A NamedTuple representing a graph with attributes .nodes, .edges, and .edge_links.</strong></p>
</dd>
</dl>
</dd></dl>
</dd></dl>
</section>
<section id="sequence">
<h3>Sequence<a class="headerlink" href="#sequence" title="Permalink to this heading">#</a></h3>
<dl class="py class">
<dt class="sig sig-object py" id="gymnasium.spaces.Sequence">
<em class="property"><span class="pre">class</span><span class="w"> </span></em><span class="sig-prename descclassname"><span class="pre">gymnasium.spaces.</span></span><span class="sig-name descname"><span class="pre">Sequence</span></span><span class="sig-paren">(</span><em class="sig-param"><span class="n"><span class="pre">space</span></span><span class="p"><span class="pre">:</span></span><span class="w"> </span><span class="n"><a class="reference internal" href="#gymnasium.spaces.Space" title="gymnasium.spaces.space.Space"><span class="pre">Space</span></a></span></em>, <em class="sig-param"><span class="n"><span class="pre">seed</span></span><span class="p"><span class="pre">:</span></span><span class="w"> </span><span class="n"><span class="pre">Optional</span><span class="p"><span class="pre">[</span></span><span class="pre">Union</span><span class="p"><span class="pre">[</span></span><span class="pre">int</span><span class="p"><span class="pre">,</span></span><span class="w"> </span><span class="pre">Generator</span><span class="p"><span class="pre">]</span></span><span class="p"><span class="pre">]</span></span></span><span class="w"> </span><span class="o"><span class="pre">=</span></span><span class="w"> </span><span class="default_value"><span class="pre">None</span></span></em><span class="sig-paren">)</span><a class="headerlink" href="#gymnasium.spaces.Sequence" title="Permalink to this definition">#</a></dt>
<dd><p>This space represent sets of finite-length sequences.</p>
<p>This space represents the set of tuples of the form <span class="math notranslate nohighlight">\((a_0, \dots, a_n)\)</span> where the <span class="math notranslate nohighlight">\(a_i\)</span> belong
to some space that is specified during initialization and the integer <span class="math notranslate nohighlight">\(n\)</span> is not fixed</p>
<dl>
<dt>Example::</dt><dd><div class="doctest highlight-default notranslate"><div class="highlight"><pre><span></span><span class="gp">&gt;&gt;&gt; </span><span class="n">space</span> <span class="o">=</span> <span class="n">Sequence</span><span class="p">(</span><span class="n">Box</span><span class="p">(</span><span class="mi">0</span><span class="p">,</span> <span class="mi">1</span><span class="p">))</span>
<span class="gp">&gt;&gt;&gt; </span><span class="n">space</span><span class="o">.</span><span class="n">sample</span><span class="p">()</span>
<span class="go">(array([0.0259352], dtype=float32),)</span>
<span class="gp">&gt;&gt;&gt; </span><span class="n">space</span><span class="o">.</span><span class="n">sample</span><span class="p">()</span>
<span class="go">(array([0.80977976], dtype=float32), array([0.80066574], dtype=float32), array([0.77165383], dtype=float32))</span>
</pre></div>
</div>
</dd>
</dl>
<p>Constructor of the <a class="reference internal" href="#gymnasium.spaces.Sequence" title="gymnasium.spaces.Sequence"><code class="xref py py-class docutils literal notranslate"><span class="pre">Sequence</span></code></a> space.</p>
<dl class="field-list simple">
<dt class="field-odd">Parameters<span class="colon">:</span></dt>
<dd class="field-odd"><ul class="simple">
<li><p><strong>space</strong> – Elements in the sequences this space represent must belong to this space.</p></li>
<li><p><strong>seed</strong> – Optionally, you can use this argument to seed the RNG that is used to sample from the space.</p></li>
</ul>
</dd>
</dl>
<dl class="py method">
<dt class="sig sig-object py" id="gymnasium.spaces.Sequence.sample">
<span class="sig-name descname"><span class="pre">sample</span></span><span class="sig-paren">(</span><em class="sig-param"><span class="n"><span class="pre">mask</span></span><span class="p"><span class="pre">:</span></span><span class="w"> </span><span class="n"><span class="pre">Optional</span><span class="p"><span class="pre">[</span></span><span class="pre">Tuple</span><span class="p"><span class="pre">[</span></span><span class="pre">Optional</span><span class="p"><span class="pre">[</span></span><span class="pre">Union</span><span class="p"><span class="pre">[</span></span><span class="pre">ndarray</span><span class="p"><span class="pre">,</span></span><span class="w"> </span><span class="pre">int</span><span class="p"><span class="pre">]</span></span><span class="p"><span class="pre">]</span></span><span class="p"><span class="pre">,</span></span><span class="w"> </span><span class="pre">Optional</span><span class="p"><span class="pre">[</span></span><span class="pre">Any</span><span class="p"><span class="pre">]</span></span><span class="p"><span class="pre">]</span></span><span class="p"><span class="pre">]</span></span></span><span class="w"> </span><span class="o"><span class="pre">=</span></span><span class="w"> </span><span class="default_value"><span class="pre">None</span></span></em><span class="sig-paren">)</span> <span class="sig-return"><span class="sig-return-icon">&#x2192;</span> <span class="sig-return-typehint"><span class="pre">Tuple</span><span class="p"><span class="pre">[</span></span><span class="pre">Any</span><span class="p"><span class="pre">]</span></span></span></span><a class="headerlink" href="#gymnasium.spaces.Sequence.sample" title="Permalink to this definition">#</a></dt>
<dd><p>Generates a single random sample from this space.</p>
<dl class="field-list simple">
<dt class="field-odd">Parameters<span class="colon">:</span></dt>
<dd class="field-odd"><p><strong>mask</strong> – An optional mask for (optionally) the length of the sequence and (optionally) the values in the sequence.
If you specify <cite>mask</cite>, it is expected to be a tuple of the form <cite>(length_mask, sample_mask)</cite> where <cite>length_mask</cite>
is
- <cite>None</cite> The length will be randomly drawn from a geometric distribution
- <cite>np.ndarray</cite> of integers, in which case the length of the sampled sequence is randomly drawn from this array.
- <cite>int</cite> for a fixed length sample
The second element of the mask tuple <cite>sample</cite> mask specifies a mask that is applied when
sampling elements from the base space. The mask is applied for each feature space sample.</p>
</dd>
<dt class="field-even">Returns<span class="colon">:</span></dt>
<dd class="field-even"><p><strong>A tuple of random length with random samples of elements from the :attr:`feature_space`.</strong></p>
</dd>
</dl>
</dd></dl>
</dd></dl>
</section>
<section id="tuple">
<h3>Tuple<a class="headerlink" href="#tuple" title="Permalink to this heading">#</a></h3>
<dl class="py class">
<dt class="sig sig-object py" id="gymnasium.spaces.Tuple">
<em class="property"><span class="pre">class</span><span class="w"> </span></em><span class="sig-prename descclassname"><span class="pre">gymnasium.spaces.</span></span><span class="sig-name descname"><span class="pre">Tuple</span></span><span class="sig-paren">(</span><em class="sig-param"><span class="n"><span class="pre">spaces</span></span><span class="p"><span class="pre">:</span></span><span class="w"> </span><span class="n"><span class="pre">Iterable</span><span class="p"><span class="pre">[</span></span><a class="reference internal" href="#gymnasium.spaces.Space" title="gymnasium.spaces.space.Space"><span class="pre">Space</span></a><span class="p"><span class="pre">]</span></span></span></em>, <em class="sig-param"><span class="n"><span class="pre">seed</span></span><span class="p"><span class="pre">:</span></span><span class="w"> </span><span class="n"><span class="pre">Optional</span><span class="p"><span class="pre">[</span></span><span class="pre">Union</span><span class="p"><span class="pre">[</span></span><span class="pre">int</span><span class="p"><span class="pre">,</span></span><span class="w"> </span><span class="pre">Sequence</span><span class="p"><span class="pre">[</span></span><span class="pre">int</span><span class="p"><span class="pre">]</span></span><span class="p"><span class="pre">,</span></span><span class="w"> </span><span class="pre">Generator</span><span class="p"><span class="pre">]</span></span><span class="p"><span class="pre">]</span></span></span><span class="w"> </span><span class="o"><span class="pre">=</span></span><span class="w"> </span><span class="default_value"><span class="pre">None</span></span></em><span class="sig-paren">)</span><a class="headerlink" href="#gymnasium.spaces.Tuple" title="Permalink to this definition">#</a></dt>
<dd><p>A tuple (more precisely: the cartesian product) of <a class="reference internal" href="#gymnasium.spaces.Space" title="gymnasium.spaces.Space"><code class="xref py py-class docutils literal notranslate"><span class="pre">Space</span></code></a> instances.</p>
<p>Elements of this space are tuples of elements of the constituent spaces.</p>
<p>Example usage:</p>
<div class="highlight-default notranslate"><div class="highlight"><pre><span></span><span class="gp">&gt;&gt;&gt; </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">Discrete</span>
<span class="gp">&gt;&gt;&gt; </span><span class="n">observation_space</span> <span class="o">=</span> <span class="n">Tuple</span><span class="p">((</span><span class="n">Discrete</span><span class="p">(</span><span class="mi">2</span><span class="p">),</span> <span class="n">Box</span><span class="p">(</span><span class="o">-</span><span class="mi">1</span><span class="p">,</span> <span class="mi">1</span><span class="p">,</span> <span class="n">shape</span><span class="o">=</span><span class="p">(</span><span class="mi">2</span><span class="p">,))))</span>
<span class="gp">&gt;&gt;&gt; </span><span class="n">observation_space</span><span class="o">.</span><span class="n">sample</span><span class="p">()</span>
<span class="go">(0, array([0.03633198, 0.42370757], dtype=float32))</span>
</pre></div>
</div>
<p>Constructor of <a class="reference internal" href="#gymnasium.spaces.Tuple" title="gymnasium.spaces.Tuple"><code class="xref py py-class docutils literal notranslate"><span class="pre">Tuple</span></code></a> space.</p>
<p>The generated instance will represent the cartesian product <span class="math notranslate nohighlight">\(\text{spaces}[0] \times ... \times \text{spaces}[-1]\)</span>.</p>
<dl class="field-list simple">
<dt class="field-odd">Parameters<span class="colon">:</span></dt>
<dd class="field-odd"><ul class="simple">
<li><p><strong>spaces</strong> (<em>Iterable</em><em>[</em><a class="reference internal" href="#gymnasium.spaces.Space" title="gymnasium.spaces.Space"><em>Space</em></a><em>]</em>) – The spaces that are involved in the cartesian product.</p></li>
<li><p><strong>seed</strong> – Optionally, you can use this argument to seed the RNGs of the <code class="docutils literal notranslate"><span class="pre">spaces</span></code> to ensure reproducible sampling.</p></li>
</ul>
</dd>
</dl>
<dl class="py method">
<dt class="sig sig-object py" id="gymnasium.spaces.Tuple.sample">
<span class="sig-name descname"><span class="pre">sample</span></span><span class="sig-paren">(</span><em class="sig-param"><span class="n"><span class="pre">mask</span></span><span class="p"><span class="pre">:</span></span><span class="w"> </span><span class="n"><span class="pre">Optional</span><span class="p"><span class="pre">[</span></span><span class="pre">Tuple</span><span class="p"><span class="pre">[</span></span><span class="pre">Optional</span><span class="p"><span class="pre">[</span></span><span class="pre">ndarray</span><span class="p"><span class="pre">]</span></span><span class="p"><span class="pre">,</span></span><span class="w"> </span><span class="p"><span class="pre">...</span></span><span class="p"><span class="pre">]</span></span><span class="p"><span class="pre">]</span></span></span><span class="w"> </span><span class="o"><span class="pre">=</span></span><span class="w"> </span><span class="default_value"><span class="pre">None</span></span></em><span class="sig-paren">)</span> <span class="sig-return"><span class="sig-return-icon">&#x2192;</span> <span class="sig-return-typehint"><span class="pre">tuple</span></span></span><a class="headerlink" href="#gymnasium.spaces.Tuple.sample" title="Permalink to this definition">#</a></dt>
<dd><p>Generates a single random sample inside this space.</p>
<p>This method draws independent samples from the subspaces.</p>
<dl class="field-list simple">
<dt class="field-odd">Parameters<span class="colon">:</span></dt>
<dd class="field-odd"><p><strong>mask</strong> – An optional tuple of optional masks for each of the subspace’s samples,
expects the same number of masks as spaces</p>
</dd>
<dt class="field-even">Returns<span class="colon">:</span></dt>
<dd class="field-even"><p><strong>Tuple of the subspace’s samples</strong></p>
</dd>
</dl>
</dd></dl>
</dd></dl>
</section>
</section>
</section>
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<ul>
<li><a class="reference internal" href="#">Spaces</a><ul>
<li><a class="reference internal" href="#general-functions">General Functions</a></li>
<li><a class="reference internal" href="#fundamental-spaces">Fundamental Spaces</a><ul>
<li><a class="reference internal" href="#box">Box</a></li>
<li><a class="reference internal" href="#discrete">Discrete</a></li>
<li><a class="reference internal" href="#multibinary">MultiBinary</a></li>
<li><a class="reference internal" href="#multidiscrete">MultiDiscrete</a></li>
<li><a class="reference internal" href="#text">Text</a></li>
</ul>
</li>
<li><a class="reference internal" href="#composite-spaces">Composite Spaces</a><ul>
<li><a class="reference internal" href="#dict">Dict</a></li>
<li><a class="reference internal" href="#graph">Graph</a></li>
<li><a class="reference internal" href="#sequence">Sequence</a></li>
<li><a class="reference internal" href="#tuple">Tuple</a></li>
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