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facebookresearch · Feb 4, 2025 · 90ac07d · 90ac07d
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diff --git a/api/_modules/aepsych/benchmark/problem.html b/api/_modules/aepsych/benchmark/problem.html
@@ -25,9 +25,9 @@ <h1>Source code for aepsych.benchmark.problem</h1><div class="highlight"><pre>
 <span class="kn">from</span><span class="w"> </span><span class="nn">functools</span><span class="w"> </span><span class="kn">import</span> <span class="n">cached_property</span>
 <span class="kn">from</span><span class="w"> </span><span class="nn">typing</span><span class="w"> </span><span class="kn">import</span> <span class="n">Any</span><span class="p">,</span> <span class="n">Dict</span><span class="p">,</span> <span class="n">List</span><span class="p">,</span> <span class="n">Union</span>
 
-<span class="kn">import</span><span class="w"> </span><span class="nn">aepsych</span>
 <span class="kn">import</span><span class="w"> </span><span class="nn">numpy</span><span class="w"> </span><span class="k">as</span><span class="w"> </span><span class="nn">np</span>
 <span class="kn">import</span><span class="w"> </span><span class="nn">torch</span>
+<span class="kn">from</span><span class="w"> </span><span class="nn">aepsych.models.model_protocol</span><span class="w"> </span><span class="kn">import</span> <span class="n">ModelProtocol</span>
 <span class="kn">from</span><span class="w"> </span><span class="nn">aepsych.models.utils</span><span class="w"> </span><span class="kn">import</span> <span class="n">p_below_threshold</span>
 <span class="kn">from</span><span class="w"> </span><span class="nn">aepsych.strategy</span><span class="w"> </span><span class="kn">import</span> <span class="n">SequentialStrategy</span>
 <span class="kn">from</span><span class="w"> </span><span class="nn">aepsych.utils</span><span class="w"> </span><span class="kn">import</span> <span class="n">make_scaled_sobol</span>
@@ -96,11 +96,11 @@ <h1>Source code for aepsych.benchmark.problem</h1><div class="highlight"><pre>
 <span class="sd">        """</span>
         <span class="k">return</span> <span class="n">bernoulli</span><span class="o">.</span><span class="n">rvs</span><span class="p">(</span><span class="bp">self</span><span class="o">.</span><span class="n">p</span><span class="p">(</span><span class="n">x</span><span class="p">))</span></div>
 
-<div class="viewcode-block" id="Problem.f_hat"><a class="viewcode-back" href="../../../benchmark.html#aepsych.benchmark.problem.Problem.f_hat">[docs]</a>    <span class="k">def</span><span class="w"> </span><span class="nf">f_hat</span><span class="p">(</span><span class="bp">self</span><span class="p">,</span> <span class="n">model</span><span class="p">:</span> <span class="n">aepsych</span><span class="o">.</span><span class="n">models</span><span class="o">.</span><span class="n">base</span><span class="o">.</span><span class="n">ModelProtocol</span><span class="p">)</span> <span class="o">-&gt;</span> <span class="n">torch</span><span class="o">.</span><span class="n">Tensor</span><span class="p">:</span>
+<div class="viewcode-block" id="Problem.f_hat"><a class="viewcode-back" href="../../../benchmark.html#aepsych.benchmark.problem.Problem.f_hat">[docs]</a>    <span class="k">def</span><span class="w"> </span><span class="nf">f_hat</span><span class="p">(</span><span class="bp">self</span><span class="p">,</span> <span class="n">model</span><span class="p">:</span> <span class="n">ModelProtocol</span><span class="p">)</span> <span class="o">-&gt;</span> <span class="n">torch</span><span class="o">.</span><span class="n">Tensor</span><span class="p">:</span>
 <span class="w">        </span><span class="sd">"""Generate mean predictions from the model over the evaluation grid.</span>
 
 <span class="sd">        Args:</span>
-<span class="sd">            model (aepsych.models.base.ModelProtocol): Model to evaluate.</span>
+<span class="sd">            model (TensoModelProtocolr): Model to evaluate.</span>
 
 <span class="sd">        Returns:</span>
 <span class="sd">            torch.Tensor: Posterior mean from underlying model over the evaluation grid.</span>
@@ -127,11 +127,11 @@ <h1>Source code for aepsych.benchmark.problem</h1><div class="highlight"><pre>
         <span class="n">normal_dist</span> <span class="o">=</span> <span class="n">torch</span><span class="o">.</span><span class="n">distributions</span><span class="o">.</span><span class="n">Normal</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="k">return</span> <span class="n">normal_dist</span><span class="o">.</span><span class="n">cdf</span><span class="p">(</span><span class="bp">self</span><span class="o">.</span><span class="n">f_true</span><span class="p">)</span>
 
-<div class="viewcode-block" id="Problem.p_hat"><a class="viewcode-back" href="../../../benchmark.html#aepsych.benchmark.problem.Problem.p_hat">[docs]</a>    <span class="k">def</span><span class="w"> </span><span class="nf">p_hat</span><span class="p">(</span><span class="bp">self</span><span class="p">,</span> <span class="n">model</span><span class="p">:</span> <span class="n">aepsych</span><span class="o">.</span><span class="n">models</span><span class="o">.</span><span class="n">base</span><span class="o">.</span><span class="n">ModelProtocol</span><span class="p">)</span> <span class="o">-&gt;</span> <span class="n">torch</span><span class="o">.</span><span class="n">Tensor</span><span class="p">:</span>
+<div class="viewcode-block" id="Problem.p_hat"><a class="viewcode-back" href="../../../benchmark.html#aepsych.benchmark.problem.Problem.p_hat">[docs]</a>    <span class="k">def</span><span class="w"> </span><span class="nf">p_hat</span><span class="p">(</span><span class="bp">self</span><span class="p">,</span> <span class="n">model</span><span class="p">:</span> <span class="n">ModelProtocol</span><span class="p">)</span> <span class="o">-&gt;</span> <span class="n">torch</span><span class="o">.</span><span class="n">Tensor</span><span class="p">:</span>
 <span class="w">        </span><span class="sd">"""Generate mean predictions from the model over the evaluation grid.</span>
 
 <span class="sd">        Args:</span>
-<span class="sd">            model (aepsych.models.base.ModelProtocol): Model to evaluate.</span>
+<span class="sd">            model (TensoModelProtocolr): Model to evaluate.</span>
 
 <span class="sd">        Returns:</span>
 <span class="sd">            torch.Tensor: Posterior mean from underlying model over the evaluation grid.</span>

diff --git a/api/_modules/aepsych/benchmark/problem/index.html b/api/_modules/aepsych/benchmark/problem/index.html
@@ -25,9 +25,9 @@ <h1>Source code for aepsych.benchmark.problem</h1><div class="highlight"><pre>
 <span class="kn">from</span><span class="w"> </span><span class="nn">functools</span><span class="w"> </span><span class="kn">import</span> <span class="n">cached_property</span>
 <span class="kn">from</span><span class="w"> </span><span class="nn">typing</span><span class="w"> </span><span class="kn">import</span> <span class="n">Any</span><span class="p">,</span> <span class="n">Dict</span><span class="p">,</span> <span class="n">List</span><span class="p">,</span> <span class="n">Union</span>
 
-<span class="kn">import</span><span class="w"> </span><span class="nn">aepsych</span>
 <span class="kn">import</span><span class="w"> </span><span class="nn">numpy</span><span class="w"> </span><span class="k">as</span><span class="w"> </span><span class="nn">np</span>
 <span class="kn">import</span><span class="w"> </span><span class="nn">torch</span>
+<span class="kn">from</span><span class="w"> </span><span class="nn">aepsych.models.model_protocol</span><span class="w"> </span><span class="kn">import</span> <span class="n">ModelProtocol</span>
 <span class="kn">from</span><span class="w"> </span><span class="nn">aepsych.models.utils</span><span class="w"> </span><span class="kn">import</span> <span class="n">p_below_threshold</span>
 <span class="kn">from</span><span class="w"> </span><span class="nn">aepsych.strategy</span><span class="w"> </span><span class="kn">import</span> <span class="n">SequentialStrategy</span>
 <span class="kn">from</span><span class="w"> </span><span class="nn">aepsych.utils</span><span class="w"> </span><span class="kn">import</span> <span class="n">make_scaled_sobol</span>
@@ -96,11 +96,11 @@ <h1>Source code for aepsych.benchmark.problem</h1><div class="highlight"><pre>
 <span class="sd">        """</span>
         <span class="k">return</span> <span class="n">bernoulli</span><span class="o">.</span><span class="n">rvs</span><span class="p">(</span><span class="bp">self</span><span class="o">.</span><span class="n">p</span><span class="p">(</span><span class="n">x</span><span class="p">))</span></div>
 
-<div class="viewcode-block" id="Problem.f_hat"><a class="viewcode-back" href="../../../benchmark.html#aepsych.benchmark.problem.Problem.f_hat">[docs]</a>    <span class="k">def</span><span class="w"> </span><span class="nf">f_hat</span><span class="p">(</span><span class="bp">self</span><span class="p">,</span> <span class="n">model</span><span class="p">:</span> <span class="n">aepsych</span><span class="o">.</span><span class="n">models</span><span class="o">.</span><span class="n">base</span><span class="o">.</span><span class="n">ModelProtocol</span><span class="p">)</span> <span class="o">-&gt;</span> <span class="n">torch</span><span class="o">.</span><span class="n">Tensor</span><span class="p">:</span>
+<div class="viewcode-block" id="Problem.f_hat"><a class="viewcode-back" href="../../../benchmark.html#aepsych.benchmark.problem.Problem.f_hat">[docs]</a>    <span class="k">def</span><span class="w"> </span><span class="nf">f_hat</span><span class="p">(</span><span class="bp">self</span><span class="p">,</span> <span class="n">model</span><span class="p">:</span> <span class="n">ModelProtocol</span><span class="p">)</span> <span class="o">-&gt;</span> <span class="n">torch</span><span class="o">.</span><span class="n">Tensor</span><span class="p">:</span>
 <span class="w">        </span><span class="sd">"""Generate mean predictions from the model over the evaluation grid.</span>
 
 <span class="sd">        Args:</span>
-<span class="sd">            model (aepsych.models.base.ModelProtocol): Model to evaluate.</span>
+<span class="sd">            model (TensoModelProtocolr): Model to evaluate.</span>
 
 <span class="sd">        Returns:</span>
 <span class="sd">            torch.Tensor: Posterior mean from underlying model over the evaluation grid.</span>
@@ -127,11 +127,11 @@ <h1>Source code for aepsych.benchmark.problem</h1><div class="highlight"><pre>
         <span class="n">normal_dist</span> <span class="o">=</span> <span class="n">torch</span><span class="o">.</span><span class="n">distributions</span><span class="o">.</span><span class="n">Normal</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="k">return</span> <span class="n">normal_dist</span><span class="o">.</span><span class="n">cdf</span><span class="p">(</span><span class="bp">self</span><span class="o">.</span><span class="n">f_true</span><span class="p">)</span>
 
-<div class="viewcode-block" id="Problem.p_hat"><a class="viewcode-back" href="../../../benchmark.html#aepsych.benchmark.problem.Problem.p_hat">[docs]</a>    <span class="k">def</span><span class="w"> </span><span class="nf">p_hat</span><span class="p">(</span><span class="bp">self</span><span class="p">,</span> <span class="n">model</span><span class="p">:</span> <span class="n">aepsych</span><span class="o">.</span><span class="n">models</span><span class="o">.</span><span class="n">base</span><span class="o">.</span><span class="n">ModelProtocol</span><span class="p">)</span> <span class="o">-&gt;</span> <span class="n">torch</span><span class="o">.</span><span class="n">Tensor</span><span class="p">:</span>
+<div class="viewcode-block" id="Problem.p_hat"><a class="viewcode-back" href="../../../benchmark.html#aepsych.benchmark.problem.Problem.p_hat">[docs]</a>    <span class="k">def</span><span class="w"> </span><span class="nf">p_hat</span><span class="p">(</span><span class="bp">self</span><span class="p">,</span> <span class="n">model</span><span class="p">:</span> <span class="n">ModelProtocol</span><span class="p">)</span> <span class="o">-&gt;</span> <span class="n">torch</span><span class="o">.</span><span class="n">Tensor</span><span class="p">:</span>
 <span class="w">        </span><span class="sd">"""Generate mean predictions from the model over the evaluation grid.</span>
 
 <span class="sd">        Args:</span>
-<span class="sd">            model (aepsych.models.base.ModelProtocol): Model to evaluate.</span>
+<span class="sd">            model (TensoModelProtocolr): Model to evaluate.</span>
 
 <span class="sd">        Returns:</span>
 <span class="sd">            torch.Tensor: Posterior mean from underlying model over the evaluation grid.</span>

diff --git a/api/_modules/aepsych/generators/acqf_grid_search_generator.html b/api/_modules/aepsych/generators/acqf_grid_search_generator.html
@@ -28,7 +28,7 @@ <h1>Source code for aepsych.generators.acqf_grid_search_generator</h1><div class
 
 <span class="kn">import</span><span class="w"> </span><span class="nn">numpy</span><span class="w"> </span><span class="k">as</span><span class="w"> </span><span class="nn">np</span>
 <span class="kn">import</span><span class="w"> </span><span class="nn">torch</span>
-<span class="kn">from</span><span class="w"> </span><span class="nn">aepsych.models.base</span><span class="w"> </span><span class="kn">import</span> <span class="n">ModelProtocol</span>
+<span class="kn">from</span><span class="w"> </span><span class="nn">aepsych.models.model_protocol</span><span class="w"> </span><span class="kn">import</span> <span class="n">ModelProtocol</span>
 <span class="kn">from</span><span class="w"> </span><span class="nn">aepsych.utils_logging</span><span class="w"> </span><span class="kn">import</span> <span class="n">getLogger</span>
 <span class="kn">from</span><span class="w"> </span><span class="nn">numpy.random</span><span class="w"> </span><span class="kn">import</span> <span class="n">choice</span>
 

diff --git a/api/_modules/aepsych/generators/acqf_grid_search_generator/index.html b/api/_modules/aepsych/generators/acqf_grid_search_generator/index.html
@@ -28,7 +28,7 @@ <h1>Source code for aepsych.generators.acqf_grid_search_generator</h1><div class
 
 <span class="kn">import</span><span class="w"> </span><span class="nn">numpy</span><span class="w"> </span><span class="k">as</span><span class="w"> </span><span class="nn">np</span>
 <span class="kn">import</span><span class="w"> </span><span class="nn">torch</span>
-<span class="kn">from</span><span class="w"> </span><span class="nn">aepsych.models.base</span><span class="w"> </span><span class="kn">import</span> <span class="n">ModelProtocol</span>
+<span class="kn">from</span><span class="w"> </span><span class="nn">aepsych.models.model_protocol</span><span class="w"> </span><span class="kn">import</span> <span class="n">ModelProtocol</span>
 <span class="kn">from</span><span class="w"> </span><span class="nn">aepsych.utils_logging</span><span class="w"> </span><span class="kn">import</span> <span class="n">getLogger</span>
 <span class="kn">from</span><span class="w"> </span><span class="nn">numpy.random</span><span class="w"> </span><span class="kn">import</span> <span class="n">choice</span>
 

diff --git a/api/_modules/aepsych/generators/acqf_thompson_sampler_generator.html b/api/_modules/aepsych/generators/acqf_thompson_sampler_generator.html
@@ -28,7 +28,7 @@ <h1>Source code for aepsych.generators.acqf_thompson_sampler_generator</h1><div
 
 <span class="kn">import</span><span class="w"> </span><span class="nn">numpy</span><span class="w"> </span><span class="k">as</span><span class="w"> </span><span class="nn">np</span>
 <span class="kn">import</span><span class="w"> </span><span class="nn">torch</span>
-<span class="kn">from</span><span class="w"> </span><span class="nn">aepsych.models.base</span><span class="w"> </span><span class="kn">import</span> <span class="n">ModelProtocol</span>
+<span class="kn">from</span><span class="w"> </span><span class="nn">aepsych.models.model_protocol</span><span class="w"> </span><span class="kn">import</span> <span class="n">ModelProtocol</span>
 <span class="kn">from</span><span class="w"> </span><span class="nn">aepsych.utils_logging</span><span class="w"> </span><span class="kn">import</span> <span class="n">getLogger</span>
 <span class="kn">from</span><span class="w"> </span><span class="nn">numpy.random</span><span class="w"> </span><span class="kn">import</span> <span class="n">choice</span>
 

diff --git a/api/_modules/aepsych/generators/acqf_thompson_sampler_generator/index.html b/api/_modules/aepsych/generators/acqf_thompson_sampler_generator/index.html
@@ -28,7 +28,7 @@ <h1>Source code for aepsych.generators.acqf_thompson_sampler_generator</h1><div
 
 <span class="kn">import</span><span class="w"> </span><span class="nn">numpy</span><span class="w"> </span><span class="k">as</span><span class="w"> </span><span class="nn">np</span>
 <span class="kn">import</span><span class="w"> </span><span class="nn">torch</span>
-<span class="kn">from</span><span class="w"> </span><span class="nn">aepsych.models.base</span><span class="w"> </span><span class="kn">import</span> <span class="n">ModelProtocol</span>
+<span class="kn">from</span><span class="w"> </span><span class="nn">aepsych.models.model_protocol</span><span class="w"> </span><span class="kn">import</span> <span class="n">ModelProtocol</span>
 <span class="kn">from</span><span class="w"> </span><span class="nn">aepsych.utils_logging</span><span class="w"> </span><span class="kn">import</span> <span class="n">getLogger</span>
 <span class="kn">from</span><span class="w"> </span><span class="nn">numpy.random</span><span class="w"> </span><span class="kn">import</span> <span class="n">choice</span>
 

diff --git a/api/_modules/aepsych/generators/base.html b/api/_modules/aepsych/generators/base.html
@@ -39,7 +39,7 @@ <h1>Source code for aepsych.generators.base</h1><div class="highlight"><pre>
 <span class="p">)</span>
 <span class="kn">from</span><span class="w"> </span><span class="nn">botorch.acquisition.preference</span><span class="w"> </span><span class="kn">import</span> <span class="n">AnalyticExpectedUtilityOfBestOption</span>
 
-<span class="kn">from</span><span class="w"> </span><span class="nn">..models.base</span><span class="w"> </span><span class="kn">import</span> <span class="n">ModelProtocol</span>
+<span class="kn">from</span><span class="w"> </span><span class="nn">..models.model_protocol</span><span class="w"> </span><span class="kn">import</span> <span class="n">ModelProtocol</span>
 
 <span class="n">AEPsychModelType</span> <span class="o">=</span> <span class="n">TypeVar</span><span class="p">(</span><span class="s2">"AEPsychModelType"</span><span class="p">,</span> <span class="n">bound</span><span class="o">=</span><span class="n">AEPsychMixin</span><span class="p">)</span>
 

diff --git a/api/_modules/aepsych/generators/base/index.html b/api/_modules/aepsych/generators/base/index.html
@@ -39,7 +39,7 @@ <h1>Source code for aepsych.generators.base</h1><div class="highlight"><pre>
 <span class="p">)</span>
 <span class="kn">from</span><span class="w"> </span><span class="nn">botorch.acquisition.preference</span><span class="w"> </span><span class="kn">import</span> <span class="n">AnalyticExpectedUtilityOfBestOption</span>
 
-<span class="kn">from</span><span class="w"> </span><span class="nn">..models.base</span><span class="w"> </span><span class="kn">import</span> <span class="n">ModelProtocol</span>
+<span class="kn">from</span><span class="w"> </span><span class="nn">..models.model_protocol</span><span class="w"> </span><span class="kn">import</span> <span class="n">ModelProtocol</span>
 
 <span class="n">AEPsychModelType</span> <span class="o">=</span> <span class="n">TypeVar</span><span class="p">(</span><span class="s2">"AEPsychModelType"</span><span class="p">,</span> <span class="n">bound</span><span class="o">=</span><span class="n">AEPsychMixin</span><span class="p">)</span>