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<section id="deepmind-control-examples">
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<h1>DeepMind Control Examples<a class="headerlink" href="#deepmind-control-examples" title="Permalink to this heading"></a></h1>
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<div class="highlight-python notranslate"><div class="highlight"><pre><span></span><span class="linenos"> 1</span><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="linenos"> 2</span><span class="kn">import</span> <span class="nn">fancy_gym</span>
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<span class="linenos"> 3</span>
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<span class="linenos"> 4</span>
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<span class="linenos"> 5</span><span class="k">def</span> <span class="nf">example_dmc</span><span class="p">(</span><span class="n">env_id</span><span class="o">=</span><span class="s2">"dm_control/fish-swim"</span><span class="p">,</span> <span class="n">seed</span><span class="o">=</span><span class="mi">1</span><span class="p">,</span> <span class="n">iterations</span><span class="o">=</span><span class="mi">1000</span><span class="p">,</span> <span class="n">render</span><span class="o">=</span><span class="kc">True</span><span class="p">):</span>
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<span class="linenos"> 6</span><span class="w"> </span><span class="sd">"""</span>
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<span class="linenos"> 7</span><span class="sd"> Example for running a DMC based env in the step based setting.</span>
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<span class="linenos"> 8</span><span class="sd"> The env_id has to be specified as `domain_name:task_name` or</span>
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<span class="linenos"> 9</span><span class="sd"> for manipulation tasks as `domain_name:manipulation-environment_name`</span>
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<span class="linenos"> 10</span>
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<span class="linenos"> 11</span><span class="sd"> Args:</span>
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<span class="linenos"> 12</span><span class="sd"> env_id: Either `domain_name-task_name` or `manipulation-environment_name`</span>
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<span class="linenos"> 13</span><span class="sd"> seed: seed for deterministic behaviour</span>
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<span class="linenos"> 14</span><span class="sd"> iterations: Number of rollout steps to run</span>
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<span class="linenos"> 15</span><span class="sd"> render: Render the episode</span>
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<span class="linenos"> 16</span>
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<span class="linenos"> 17</span><span class="sd"> Returns:</span>
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<span class="linenos"> 18</span>
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<span class="linenos"> 19</span><span class="sd"> """</span>
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<span class="linenos"> 20</span> <span class="n">env</span> <span class="o">=</span> <span class="n">gym</span><span class="o">.</span><span class="n">make</span><span class="p">(</span><span class="n">env_id</span><span class="p">)</span>
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<span class="linenos"> 21</span> <span class="n">rewards</span> <span class="o">=</span> <span class="mi">0</span>
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<span class="linenos"> 22</span> <span class="n">obs</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>
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<span class="linenos"> 23</span> <span class="nb">print</span><span class="p">(</span><span class="s2">"observation shape:"</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">shape</span><span class="p">)</span>
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<span class="linenos"> 24</span> <span class="nb">print</span><span class="p">(</span><span class="s2">"action shape:"</span><span class="p">,</span> <span class="n">env</span><span class="o">.</span><span class="n">action_space</span><span class="o">.</span><span class="n">shape</span><span class="p">)</span>
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<span class="linenos"> 25</span>
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<span class="linenos"> 26</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="n">iterations</span><span class="p">):</span>
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<span class="linenos"> 27</span> <span class="n">ac</span> <span class="o">=</span> <span class="n">env</span><span class="o">.</span><span class="n">action_space</span><span class="o">.</span><span class="n">sample</span><span class="p">()</span>
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<span class="linenos"> 28</span> <span class="k">if</span> <span class="n">render</span><span class="p">:</span>
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<span class="linenos"> 29</span> <span class="n">env</span><span class="o">.</span><span class="n">render</span><span class="p">(</span><span class="n">mode</span><span class="o">=</span><span class="s2">"human"</span><span class="p">)</span>
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<span class="linenos"> 30</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="n">env</span><span class="o">.</span><span class="n">step</span><span class="p">(</span><span class="n">ac</span><span class="p">)</span>
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<span class="linenos"> 31</span> <span class="n">rewards</span> <span class="o">+=</span> <span class="n">reward</span>
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<span class="linenos"> 32</span>
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<span class="linenos"> 33</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>
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<span class="linenos"> 34</span> <span class="nb">print</span><span class="p">(</span><span class="n">env_id</span><span class="p">,</span> <span class="n">rewards</span><span class="p">)</span>
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<span class="linenos"> 35</span> <span class="n">rewards</span> <span class="o">=</span> <span class="mi">0</span>
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<span class="linenos"> 36</span> <span class="n">obs</span> <span class="o">=</span> <span class="n">env</span><span class="o">.</span><span class="n">reset</span><span class="p">()</span>
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<span class="linenos"> 37</span>
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<span class="linenos"> 38</span> <span class="n">env</span><span class="o">.</span><span class="n">close</span><span class="p">()</span>
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<span class="linenos"> 39</span> <span class="k">del</span> <span class="n">env</span>
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<span class="linenos"> 40</span>
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<span class="linenos"> 41</span>
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<span class="linenos"> 42</span><span class="k">def</span> <span class="nf">example_custom_dmc_and_mp</span><span class="p">(</span><span class="n">seed</span><span class="o">=</span><span class="mi">1</span><span class="p">,</span> <span class="n">iterations</span><span class="o">=</span><span class="mi">1</span><span class="p">,</span> <span class="n">render</span><span class="o">=</span><span class="kc">True</span><span class="p">):</span>
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<span class="linenos"> 43</span><span class="w"> </span><span class="sd">"""</span>
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<span class="linenos"> 44</span><span class="sd"> Example for running a custom movement primitive based environments.</span>
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<span class="linenos"> 45</span><span class="sd"> Our already registered environments follow the same structure.</span>
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<span class="linenos"> 46</span><span class="sd"> Hence, this also allows to adjust hyperparameters of the movement primitives.</span>
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<span class="linenos"> 47</span><span class="sd"> Yet, we recommend the method above if you are just interested in chaining those parameters for existing tasks.</span>
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<span class="linenos"> 48</span><span class="sd"> We appreciate PRs for custom environments (especially MP wrappers of existing tasks)</span>
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<span class="linenos"> 49</span><span class="sd"> for our repo: https://github.com/ALRhub/fancy_gym/</span>
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<span class="linenos"> 50</span><span class="sd"> Args:</span>
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<span class="linenos"> 51</span><span class="sd"> seed: seed for deterministic behaviour</span>
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<span class="linenos"> 52</span><span class="sd"> iterations: Number of rollout steps to run</span>
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<span class="linenos"> 53</span><span class="sd"> render: Render the episode</span>
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<span class="linenos"> 54</span>
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<span class="linenos"> 55</span><span class="sd"> Returns:</span>
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<span class="linenos"> 56</span>
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<span class="linenos"> 57</span><span class="sd"> """</span>
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<span class="linenos"> 58</span>
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<span class="linenos"> 59</span> <span class="c1"># Base DMC name, according to structure of above example</span>
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<span class="linenos"> 60</span> <span class="n">base_env_id</span> <span class="o">=</span> <span class="s2">"dm_control/ball_in_cup-catch"</span>
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<span class="linenos"> 61</span>
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<span class="linenos"> 62</span> <span class="c1"># Replace this wrapper with the custom wrapper for your environment by inheriting from the RawInterfaceWrapper.</span>
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<span class="linenos"> 63</span> <span class="c1"># You can also add other gym.Wrappers in case they are needed.</span>
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<span class="linenos"> 64</span> <span class="n">wrappers</span> <span class="o">=</span> <span class="p">[</span><span class="n">fancy_gym</span><span class="o">.</span><span class="n">dmc</span><span class="o">.</span><span class="n">suite</span><span class="o">.</span><span class="n">ball_in_cup</span><span class="o">.</span><span class="n">MPWrapper</span><span class="p">]</span>
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<span class="linenos"> 65</span> <span class="c1"># # For a ProMP</span>
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<span class="linenos"> 66</span> <span class="n">trajectory_generator_kwargs</span> <span class="o">=</span> <span class="p">{</span><span class="s1">'trajectory_generator_type'</span><span class="p">:</span> <span class="s1">'promp'</span><span class="p">}</span>
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<span class="linenos"> 67</span> <span class="n">phase_generator_kwargs</span> <span class="o">=</span> <span class="p">{</span><span class="s1">'phase_generator_type'</span><span class="p">:</span> <span class="s1">'linear'</span><span class="p">}</span>
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<span class="linenos"> 68</span> <span class="n">controller_kwargs</span> <span class="o">=</span> <span class="p">{</span><span class="s1">'controller_type'</span><span class="p">:</span> <span class="s1">'motor'</span><span class="p">,</span>
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<span class="linenos"> 69</span> <span class="s2">"p_gains"</span><span class="p">:</span> <span class="mf">1.0</span><span class="p">,</span>
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<span class="linenos"> 70</span> <span class="s2">"d_gains"</span><span class="p">:</span> <span class="mf">0.1</span><span class="p">,</span> <span class="p">}</span>
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<span class="linenos"> 71</span> <span class="n">basis_generator_kwargs</span> <span class="o">=</span> <span class="p">{</span><span class="s1">'basis_generator_type'</span><span class="p">:</span> <span class="s1">'zero_rbf'</span><span class="p">,</span>
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<span class="linenos"> 72</span> <span class="s1">'num_basis'</span><span class="p">:</span> <span class="mi">5</span><span class="p">,</span>
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<span class="linenos"> 73</span> <span class="s1">'num_basis_zero_start'</span><span class="p">:</span> <span class="mi">1</span>
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<span class="linenos"> 74</span> <span class="p">}</span>
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<span class="linenos"> 75</span>
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<span class="linenos"> 76</span> <span class="c1"># For a DMP</span>
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<span class="linenos"> 77</span> <span class="c1"># trajectory_generator_kwargs = {'trajectory_generator_type': 'dmp'}</span>
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<span class="linenos"> 78</span> <span class="c1"># phase_generator_kwargs = {'phase_generator_type': 'exp',</span>
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<span class="linenos"> 79</span> <span class="c1"># 'alpha_phase': 2}</span>
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<span class="linenos"> 80</span> <span class="c1"># controller_kwargs = {'controller_type': 'motor',</span>
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<span class="linenos"> 81</span> <span class="c1"># "p_gains": 1.0,</span>
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<span class="linenos"> 82</span> <span class="c1"># "d_gains": 0.1,</span>
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<span class="linenos"> 83</span> <span class="c1"># }</span>
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<span class="linenos"> 84</span> <span class="c1"># basis_generator_kwargs = {'basis_generator_type': 'rbf',</span>
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<span class="linenos"> 85</span> <span class="c1"># 'num_basis': 5</span>
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<span class="linenos"> 86</span> <span class="c1"># }</span>
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<span class="linenos"> 87</span> <span class="n">env</span> <span class="o">=</span> <span class="n">fancy_gym</span><span class="o">.</span><span class="n">make_bb</span><span class="p">(</span><span class="n">env_id</span><span class="o">=</span><span class="n">base_env_id</span><span class="p">,</span> <span class="n">wrappers</span><span class="o">=</span><span class="n">wrappers</span><span class="p">,</span> <span class="n">black_box_kwargs</span><span class="o">=</span><span class="p">{},</span>
|
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<span class="linenos"> 88</span> <span class="n">traj_gen_kwargs</span><span class="o">=</span><span class="n">trajectory_generator_kwargs</span><span class="p">,</span> <span class="n">controller_kwargs</span><span class="o">=</span><span class="n">controller_kwargs</span><span class="p">,</span>
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<span class="linenos"> 89</span> <span class="n">phase_kwargs</span><span class="o">=</span><span class="n">phase_generator_kwargs</span><span class="p">,</span> <span class="n">basis_kwargs</span><span class="o">=</span><span class="n">basis_generator_kwargs</span><span class="p">,</span>
|
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<span class="linenos"> 90</span> <span class="n">seed</span><span class="o">=</span><span class="n">seed</span><span class="p">)</span>
|
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<span class="linenos"> 91</span>
|
||
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<span class="linenos"> 92</span> <span class="c1"># This renders the full MP trajectory</span>
|
||
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<span class="linenos"> 93</span> <span class="c1"># It is only required to call render() once in the beginning, which renders every consecutive trajectory.</span>
|
||
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<span class="linenos"> 94</span> <span class="c1"># Resetting to no rendering, can be achieved by render(mode=None).</span>
|
||
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<span class="linenos"> 95</span> <span class="c1"># It is also possible to change them mode multiple times when</span>
|
||
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<span class="linenos"> 96</span> <span class="c1"># e.g. only every nth trajectory should be displayed.</span>
|
||
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<span class="linenos"> 97</span> <span class="k">if</span> <span class="n">render</span><span class="p">:</span>
|
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<span class="linenos"> 98</span> <span class="n">env</span><span class="o">.</span><span class="n">render</span><span class="p">(</span><span class="n">mode</span><span class="o">=</span><span class="s2">"human"</span><span class="p">)</span>
|
||
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<span class="linenos"> 99</span>
|
||
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<span class="linenos">100</span> <span class="n">rewards</span> <span class="o">=</span> <span class="mi">0</span>
|
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<span class="linenos">101</span> <span class="n">obs</span> <span class="o">=</span> <span class="n">env</span><span class="o">.</span><span class="n">reset</span><span class="p">()</span>
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||
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<span class="linenos">102</span>
|
||
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<span class="linenos">103</span> <span class="c1"># number of samples/full trajectories (multiple environment steps)</span>
|
||
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|
<span class="linenos">104</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="n">iterations</span><span class="p">):</span>
|
||
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|
<span class="linenos">105</span> <span class="n">ac</span> <span class="o">=</span> <span class="n">env</span><span class="o">.</span><span class="n">action_space</span><span class="o">.</span><span class="n">sample</span><span class="p">()</span>
|
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|
<span class="linenos">106</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="n">env</span><span class="o">.</span><span class="n">step</span><span class="p">(</span><span class="n">ac</span><span class="p">)</span>
|
||
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|
<span class="linenos">107</span> <span class="n">rewards</span> <span class="o">+=</span> <span class="n">reward</span>
|
||
|
|
<span class="linenos">108</span>
|
||
|
|
<span class="linenos">109</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>
|
||
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|
<span class="linenos">110</span> <span class="nb">print</span><span class="p">(</span><span class="n">base_env_id</span><span class="p">,</span> <span class="n">rewards</span><span class="p">)</span>
|
||
|
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<span class="linenos">111</span> <span class="n">rewards</span> <span class="o">=</span> <span class="mi">0</span>
|
||
|
|
<span class="linenos">112</span> <span class="n">obs</span> <span class="o">=</span> <span class="n">env</span><span class="o">.</span><span class="n">reset</span><span class="p">()</span>
|
||
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<span class="linenos">113</span>
|
||
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|
<span class="linenos">114</span> <span class="n">env</span><span class="o">.</span><span class="n">close</span><span class="p">()</span>
|
||
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<span class="linenos">115</span> <span class="k">del</span> <span class="n">env</span>
|
||
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|
<span class="linenos">116</span>
|
||
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<span class="linenos">117</span>
|
||
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<span class="linenos">118</span><span class="k">if</span> <span class="vm">__name__</span> <span class="o">==</span> <span class="s1">'__main__'</span><span class="p">:</span>
|
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<span class="linenos">119</span> <span class="c1"># Disclaimer: DMC environments require the seed to be specified in the beginning.</span>
|
||
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|
<span class="linenos">120</span> <span class="c1"># Adjusting it afterwards with env.seed() is not recommended as it does not affect the underlying physics.</span>
|
||
|
|
<span class="linenos">121</span>
|
||
|
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<span class="linenos">122</span> <span class="c1"># For rendering DMC</span>
|
||
|
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<span class="linenos">123</span> <span class="c1"># export MUJOCO_GL="osmesa"</span>
|
||
|
|
<span class="linenos">124</span> <span class="n">render</span> <span class="o">=</span> <span class="kc">True</span>
|
||
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|
<span class="linenos">125</span>
|
||
|
|
<span class="linenos">126</span> <span class="c1"># # Standard DMC Suite tasks</span>
|
||
|
|
<span class="linenos">127</span> <span class="n">example_dmc</span><span class="p">(</span><span class="s2">"dm_control/fish-swim"</span><span class="p">,</span> <span class="n">seed</span><span class="o">=</span><span class="mi">10</span><span class="p">,</span> <span class="n">iterations</span><span class="o">=</span><span class="mi">1000</span><span class="p">,</span> <span class="n">render</span><span class="o">=</span><span class="n">render</span><span class="p">)</span>
|
||
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<span class="linenos">128</span> <span class="c1">#</span>
|
||
|
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<span class="linenos">129</span> <span class="c1"># # Manipulation tasks</span>
|
||
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<span class="linenos">130</span> <span class="c1"># # Disclaimer: The vision versions are currently not integrated and yield an error</span>
|
||
|
|
<span class="linenos">131</span> <span class="n">example_dmc</span><span class="p">(</span><span class="s2">"dm_control/manipulation-reach_site_features"</span><span class="p">,</span> <span class="n">seed</span><span class="o">=</span><span class="mi">10</span><span class="p">,</span> <span class="n">iterations</span><span class="o">=</span><span class="mi">250</span><span class="p">,</span> <span class="n">render</span><span class="o">=</span><span class="n">render</span><span class="p">)</span>
|
||
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<span class="linenos">132</span> <span class="c1">#</span>
|
||
|
|
<span class="linenos">133</span> <span class="c1"># # Gym + DMC hybrid task provided in the MP framework</span>
|
||
|
|
<span class="linenos">134</span> <span class="n">example_dmc</span><span class="p">(</span><span class="s2">"dm_control_ProMP/ball_in_cup-catch-v0"</span><span class="p">,</span> <span class="n">seed</span><span class="o">=</span><span class="mi">10</span><span class="p">,</span> <span class="n">iterations</span><span class="o">=</span><span class="mi">1</span><span class="p">,</span> <span class="n">render</span><span class="o">=</span><span class="n">render</span><span class="p">)</span>
|
||
|
|
<span class="linenos">135</span>
|
||
|
|
<span class="linenos">136</span> <span class="c1"># Custom DMC task # Different seed, because the episode is longer for this example and the name+seed combo is</span>
|
||
|
|
<span class="linenos">137</span> <span class="c1"># already registered above</span>
|
||
|
|
<span class="linenos">138</span> <span class="n">example_custom_dmc_and_mp</span><span class="p">(</span><span class="n">seed</span><span class="o">=</span><span class="mi">11</span><span class="p">,</span> <span class="n">iterations</span><span class="o">=</span><span class="mi">1</span><span class="p">,</span> <span class="n">render</span><span class="o">=</span><span class="n">render</span><span class="p">)</span>
|
||
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</pre></div>
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