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pytorch · Aug 29, 2023 · 58b0772 · 58b0772
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diff --git a/v/latest/api/_modules/botorch/acquisition/multi_objective/multi_output_risk_measures.html b/v/latest/api/_modules/botorch/acquisition/multi_objective/multi_output_risk_measures.html
@@ -86,7 +86,6 @@ <h1>Source code for botorch.acquisition.multi_objective.multi_output_risk_measur
         <span class="bp">self</span><span class="p">,</span>
         <span class="n">n_w</span><span class="p">:</span> <span class="nb">int</span><span class="p">,</span>
         <span class="n">preprocessing_function</span><span class="p">:</span> <span class="n">Optional</span><span class="p">[</span><span class="n">Callable</span><span class="p">[[</span><span class="n">Tensor</span><span class="p">],</span> <span class="n">Tensor</span><span class="p">]]</span> <span class="o">=</span> <span class="kc">None</span><span class="p">,</span>
-        <span class="n">weights</span><span class="p">:</span> <span class="n">Optional</span><span class="p">[</span><span class="n">Union</span><span class="p">[</span><span class="n">List</span><span class="p">[</span><span class="nb">float</span><span class="p">],</span> <span class="n">Tensor</span><span class="p">]]</span> <span class="o">=</span> <span class="kc">None</span><span class="p">,</span>
     <span class="p">)</span> <span class="o">-&gt;</span> <span class="kc">None</span><span class="p">:</span>
 <span class="w">        </span><span class="sa">r</span><span class="sd">"""Transform the posterior samples to samples of a risk measure.</span>
 
@@ -98,13 +97,8 @@ <h1>Source code for botorch.acquisition.multi_objective.multi_output_risk_measur
 <span class="sd">                maximization. For constrained optimization, this should also</span>
 <span class="sd">                apply feasibility-weighting to samples. Given a `batch x m`-dim</span>
 <span class="sd">                tensor of samples, this should return a `batch x m'`-dim tensor.</span>
-<span class="sd">            weights: An optional `m`-dim tensor or list of weights for scaling</span>
-<span class="sd">                multi-output samples before calculating the risk measure.</span>
-<span class="sd">                Deprecated, use `preprocessing_function` instead.</span>
 <span class="sd">        """</span>
-        <span class="nb">super</span><span class="p">()</span><span class="o">.</span><span class="fm">__init__</span><span class="p">(</span>
-            <span class="n">n_w</span><span class="o">=</span><span class="n">n_w</span><span class="p">,</span> <span class="n">preprocessing_function</span><span class="o">=</span><span class="n">preprocessing_function</span><span class="p">,</span> <span class="n">weights</span><span class="o">=</span><span class="n">weights</span>
-        <span class="p">)</span>
+        <span class="nb">super</span><span class="p">()</span><span class="o">.</span><span class="fm">__init__</span><span class="p">(</span><span class="n">n_w</span><span class="o">=</span><span class="n">n_w</span><span class="p">,</span> <span class="n">preprocessing_function</span><span class="o">=</span><span class="n">preprocessing_function</span><span class="p">)</span>
 
     <span class="k">def</span> <span class="nf">_prepare_samples</span><span class="p">(</span><span class="bp">self</span><span class="p">,</span> <span class="n">samples</span><span class="p">:</span> <span class="n">Tensor</span><span class="p">)</span> <span class="o">-&gt;</span> <span class="n">Tensor</span><span class="p">:</span>
 <span class="w">        </span><span class="sa">r</span><span class="sd">"""Prepare samples for risk measure calculations by scaling and</span>
@@ -279,7 +273,7 @@ <h1>Source code for botorch.acquisition.multi_objective.multi_output_risk_measur
         <span class="n">alpha</span><span class="p">:</span> <span class="nb">float</span><span class="p">,</span>
         <span class="n">expectation</span><span class="p">:</span> <span class="nb">bool</span> <span class="o">=</span> <span class="kc">False</span><span class="p">,</span>
         <span class="n">preprocessing_function</span><span class="p">:</span> <span class="n">Optional</span><span class="p">[</span><span class="n">Callable</span><span class="p">[[</span><span class="n">Tensor</span><span class="p">],</span> <span class="n">Tensor</span><span class="p">]]</span> <span class="o">=</span> <span class="kc">None</span><span class="p">,</span>
-        <span class="n">weights</span><span class="p">:</span> <span class="n">Optional</span><span class="p">[</span><span class="n">Union</span><span class="p">[</span><span class="n">List</span><span class="p">[</span><span class="nb">float</span><span class="p">],</span> <span class="n">Tensor</span><span class="p">]]</span> <span class="o">=</span> <span class="kc">None</span><span class="p">,</span>
+        <span class="o">*</span><span class="p">,</span>
         <span class="n">pad_to_n_w</span><span class="p">:</span> <span class="nb">bool</span> <span class="o">=</span> <span class="kc">False</span><span class="p">,</span>
         <span class="n">filter_dominated</span><span class="p">:</span> <span class="nb">bool</span> <span class="o">=</span> <span class="kc">True</span><span class="p">,</span>
     <span class="p">)</span> <span class="o">-&gt;</span> <span class="kc">None</span><span class="p">:</span>
@@ -298,9 +292,6 @@ <h1>Source code for botorch.acquisition.multi_objective.multi_output_risk_measur
 <span class="sd">                maximization. For constrained optimization, this should also</span>
 <span class="sd">                apply feasibility-weighting to samples. Given a `batch x m`-dim</span>
 <span class="sd">                tensor of samples, this should return a `batch x m'`-dim tensor.</span>
-<span class="sd">            weights: An optional `m`-dim tensor or list of weights for scaling</span>
-<span class="sd">                multi-output samples before calculating the risk measure.</span>
-<span class="sd">                Deprecated, use `preprocessing_function` instead.</span>
 <span class="sd">            pad_to_n_w: If True, instead of padding up to `k'`, which is the size of</span>
 <span class="sd">                the largest MVaR set across all batches, we pad the MVaR set up to</span>
 <span class="sd">                `n_w`. This produces a return tensor of known size, however, it may</span>
@@ -314,9 +305,7 @@ <h1>Source code for botorch.acquisition.multi_objective.multi_output_risk_measur
 <span class="sd">                calculating the hypervolume. Disabling this is not recommended</span>
 <span class="sd">                if `expectation=True`.</span>
 <span class="sd">        """</span>
-        <span class="nb">super</span><span class="p">()</span><span class="o">.</span><span class="fm">__init__</span><span class="p">(</span>
-            <span class="n">n_w</span><span class="o">=</span><span class="n">n_w</span><span class="p">,</span> <span class="n">preprocessing_function</span><span class="o">=</span><span class="n">preprocessing_function</span><span class="p">,</span> <span class="n">weights</span><span class="o">=</span><span class="n">weights</span>
-        <span class="p">)</span>
+        <span class="nb">super</span><span class="p">()</span><span class="o">.</span><span class="fm">__init__</span><span class="p">(</span><span class="n">n_w</span><span class="o">=</span><span class="n">n_w</span><span class="p">,</span> <span class="n">preprocessing_function</span><span class="o">=</span><span class="n">preprocessing_function</span><span class="p">)</span>
         <span class="k">if</span> <span class="ow">not</span> <span class="mi">0</span> <span class="o">&lt;</span> <span class="n">alpha</span> <span class="o">&lt;=</span> <span class="mi">1</span><span class="p">:</span>
             <span class="k">raise</span> <span class="ne">ValueError</span><span class="p">(</span><span class="s2">"`alpha` must be in (0.0, 1.0]"</span><span class="p">)</span>
         <span class="bp">self</span><span class="o">.</span><span class="n">alpha</span> <span class="o">=</span> <span class="n">alpha</span>

diff --git a/...st/api/_modules/botorch/acquisition/multi_objective/multi_output_risk_measures/index.html b/...st/api/_modules/botorch/acquisition/multi_objective/multi_output_risk_measures/index.html
@@ -86,7 +86,6 @@ <h1>Source code for botorch.acquisition.multi_objective.multi_output_risk_measur
         <span class="bp">self</span><span class="p">,</span>
         <span class="n">n_w</span><span class="p">:</span> <span class="nb">int</span><span class="p">,</span>
         <span class="n">preprocessing_function</span><span class="p">:</span> <span class="n">Optional</span><span class="p">[</span><span class="n">Callable</span><span class="p">[[</span><span class="n">Tensor</span><span class="p">],</span> <span class="n">Tensor</span><span class="p">]]</span> <span class="o">=</span> <span class="kc">None</span><span class="p">,</span>
-        <span class="n">weights</span><span class="p">:</span> <span class="n">Optional</span><span class="p">[</span><span class="n">Union</span><span class="p">[</span><span class="n">List</span><span class="p">[</span><span class="nb">float</span><span class="p">],</span> <span class="n">Tensor</span><span class="p">]]</span> <span class="o">=</span> <span class="kc">None</span><span class="p">,</span>
     <span class="p">)</span> <span class="o">-&gt;</span> <span class="kc">None</span><span class="p">:</span>
 <span class="w">        </span><span class="sa">r</span><span class="sd">"""Transform the posterior samples to samples of a risk measure.</span>
 
@@ -98,13 +97,8 @@ <h1>Source code for botorch.acquisition.multi_objective.multi_output_risk_measur
 <span class="sd">                maximization. For constrained optimization, this should also</span>
 <span class="sd">                apply feasibility-weighting to samples. Given a `batch x m`-dim</span>
 <span class="sd">                tensor of samples, this should return a `batch x m'`-dim tensor.</span>
-<span class="sd">            weights: An optional `m`-dim tensor or list of weights for scaling</span>
-<span class="sd">                multi-output samples before calculating the risk measure.</span>
-<span class="sd">                Deprecated, use `preprocessing_function` instead.</span>
 <span class="sd">        """</span>
-        <span class="nb">super</span><span class="p">()</span><span class="o">.</span><span class="fm">__init__</span><span class="p">(</span>
-            <span class="n">n_w</span><span class="o">=</span><span class="n">n_w</span><span class="p">,</span> <span class="n">preprocessing_function</span><span class="o">=</span><span class="n">preprocessing_function</span><span class="p">,</span> <span class="n">weights</span><span class="o">=</span><span class="n">weights</span>
-        <span class="p">)</span>
+        <span class="nb">super</span><span class="p">()</span><span class="o">.</span><span class="fm">__init__</span><span class="p">(</span><span class="n">n_w</span><span class="o">=</span><span class="n">n_w</span><span class="p">,</span> <span class="n">preprocessing_function</span><span class="o">=</span><span class="n">preprocessing_function</span><span class="p">)</span>
 
     <span class="k">def</span> <span class="nf">_prepare_samples</span><span class="p">(</span><span class="bp">self</span><span class="p">,</span> <span class="n">samples</span><span class="p">:</span> <span class="n">Tensor</span><span class="p">)</span> <span class="o">-&gt;</span> <span class="n">Tensor</span><span class="p">:</span>
 <span class="w">        </span><span class="sa">r</span><span class="sd">"""Prepare samples for risk measure calculations by scaling and</span>
@@ -279,7 +273,7 @@ <h1>Source code for botorch.acquisition.multi_objective.multi_output_risk_measur
         <span class="n">alpha</span><span class="p">:</span> <span class="nb">float</span><span class="p">,</span>
         <span class="n">expectation</span><span class="p">:</span> <span class="nb">bool</span> <span class="o">=</span> <span class="kc">False</span><span class="p">,</span>
         <span class="n">preprocessing_function</span><span class="p">:</span> <span class="n">Optional</span><span class="p">[</span><span class="n">Callable</span><span class="p">[[</span><span class="n">Tensor</span><span class="p">],</span> <span class="n">Tensor</span><span class="p">]]</span> <span class="o">=</span> <span class="kc">None</span><span class="p">,</span>
-        <span class="n">weights</span><span class="p">:</span> <span class="n">Optional</span><span class="p">[</span><span class="n">Union</span><span class="p">[</span><span class="n">List</span><span class="p">[</span><span class="nb">float</span><span class="p">],</span> <span class="n">Tensor</span><span class="p">]]</span> <span class="o">=</span> <span class="kc">None</span><span class="p">,</span>
+        <span class="o">*</span><span class="p">,</span>
         <span class="n">pad_to_n_w</span><span class="p">:</span> <span class="nb">bool</span> <span class="o">=</span> <span class="kc">False</span><span class="p">,</span>
         <span class="n">filter_dominated</span><span class="p">:</span> <span class="nb">bool</span> <span class="o">=</span> <span class="kc">True</span><span class="p">,</span>
     <span class="p">)</span> <span class="o">-&gt;</span> <span class="kc">None</span><span class="p">:</span>
@@ -298,9 +292,6 @@ <h1>Source code for botorch.acquisition.multi_objective.multi_output_risk_measur
 <span class="sd">                maximization. For constrained optimization, this should also</span>
 <span class="sd">                apply feasibility-weighting to samples. Given a `batch x m`-dim</span>
 <span class="sd">                tensor of samples, this should return a `batch x m'`-dim tensor.</span>
-<span class="sd">            weights: An optional `m`-dim tensor or list of weights for scaling</span>
-<span class="sd">                multi-output samples before calculating the risk measure.</span>
-<span class="sd">                Deprecated, use `preprocessing_function` instead.</span>
 <span class="sd">            pad_to_n_w: If True, instead of padding up to `k'`, which is the size of</span>
 <span class="sd">                the largest MVaR set across all batches, we pad the MVaR set up to</span>
 <span class="sd">                `n_w`. This produces a return tensor of known size, however, it may</span>
@@ -314,9 +305,7 @@ <h1>Source code for botorch.acquisition.multi_objective.multi_output_risk_measur
 <span class="sd">                calculating the hypervolume. Disabling this is not recommended</span>
 <span class="sd">                if `expectation=True`.</span>
 <span class="sd">        """</span>
-        <span class="nb">super</span><span class="p">()</span><span class="o">.</span><span class="fm">__init__</span><span class="p">(</span>
-            <span class="n">n_w</span><span class="o">=</span><span class="n">n_w</span><span class="p">,</span> <span class="n">preprocessing_function</span><span class="o">=</span><span class="n">preprocessing_function</span><span class="p">,</span> <span class="n">weights</span><span class="o">=</span><span class="n">weights</span>
-        <span class="p">)</span>
+        <span class="nb">super</span><span class="p">()</span><span class="o">.</span><span class="fm">__init__</span><span class="p">(</span><span class="n">n_w</span><span class="o">=</span><span class="n">n_w</span><span class="p">,</span> <span class="n">preprocessing_function</span><span class="o">=</span><span class="n">preprocessing_function</span><span class="p">)</span>
         <span class="k">if</span> <span class="ow">not</span> <span class="mi">0</span> <span class="o">&lt;</span> <span class="n">alpha</span> <span class="o">&lt;=</span> <span class="mi">1</span><span class="p">:</span>
             <span class="k">raise</span> <span class="ne">ValueError</span><span class="p">(</span><span class="s2">"`alpha` must be in (0.0, 1.0]"</span><span class="p">)</span>
         <span class="bp">self</span><span class="o">.</span><span class="n">alpha</span> <span class="o">=</span> <span class="n">alpha</span>