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Francisco Rivera Valverde: Missing params in signature (#1084)
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42 changes: 29 additions & 13 deletions development/_modules/autosklearn/experimental/askl2.html
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Expand Up @@ -137,15 +137,16 @@ <h1>Source code for autosklearn.experimental.askl2</h1><div class="highlight"><p
<span class="n">m</span> <span class="o">=</span> <span class="n">hashlib</span><span class="o">.</span><span class="n">md5</span><span class="p">()</span>
<span class="n">m</span><span class="o">.</span><span class="n">update</span><span class="p">(</span><span class="n">fh</span><span class="o">.</span><span class="n">read</span><span class="p">()</span><span class="o">.</span><span class="n">encode</span><span class="p">(</span><span class="s1">&#39;utf8&#39;</span><span class="p">))</span>
<span class="n">training_data_hash</span> <span class="o">=</span> <span class="n">m</span><span class="o">.</span><span class="n">hexdigest</span><span class="p">()[:</span><span class="mi">10</span><span class="p">]</span>
<span class="n">sklearn_version</span> <span class="o">=</span> <span class="n">sklearn</span><span class="o">.</span><span class="n">__version__</span>
<span class="n">autosklearn_version</span> <span class="o">=</span> <span class="n">autosklearn</span><span class="o">.</span><span class="n">__version__</span>
<span class="n">selector_file</span> <span class="o">=</span> <span class="n">pathlib</span><span class="o">.</span><span class="n">Path</span><span class="p">(</span>
<span class="n">os</span><span class="o">.</span><span class="n">environ</span><span class="o">.</span><span class="n">get</span><span class="p">(</span>
<span class="s1">&#39;XDG_CACHE_HOME&#39;</span><span class="p">,</span>
<span class="s1">&#39;~/.cache/auto-sklearn/askl2_selector_</span><span class="si">%s</span><span class="s1">_</span><span class="si">%s</span><span class="s1">_</span><span class="si">%s</span><span class="s1">.pkl&#39;</span>
<span class="o">%</span> <span class="p">(</span><span class="n">autosklearn_version</span><span class="p">,</span> <span class="n">sklearn_version</span><span class="p">,</span> <span class="n">training_data_hash</span><span class="p">),</span>
<span class="p">)</span>
<span class="p">)</span><span class="o">.</span><span class="n">expanduser</span><span class="p">()</span>
<span class="n">selector_filename</span> <span class="o">=</span> <span class="s2">&quot;askl2_selector_</span><span class="si">%s</span><span class="s2">_</span><span class="si">%s</span><span class="s2">_</span><span class="si">%s</span><span class="s2">.pkl&quot;</span> <span class="o">%</span> <span class="p">(</span>
<span class="n">autosklearn</span><span class="o">.</span><span class="n">__version__</span><span class="p">,</span>
<span class="n">sklearn</span><span class="o">.</span><span class="n">__version__</span><span class="p">,</span>
<span class="n">training_data_hash</span>
<span class="p">)</span>
<span class="n">selector_directory</span> <span class="o">=</span> <span class="n">os</span><span class="o">.</span><span class="n">environ</span><span class="o">.</span><span class="n">get</span><span class="p">(</span><span class="s1">&#39;XDG_CACHE_HOME&#39;</span><span class="p">)</span>
<span class="k">if</span> <span class="n">selector_directory</span> <span class="ow">is</span> <span class="kc">None</span><span class="p">:</span>
<span class="n">selector_directory</span> <span class="o">=</span> <span class="n">pathlib</span><span class="o">.</span><span class="n">Path</span><span class="o">.</span><span class="n">home</span><span class="p">()</span>
<span class="n">selector_directory</span> <span class="o">=</span> <span class="n">pathlib</span><span class="o">.</span><span class="n">Path</span><span class="p">(</span><span class="n">selector_directory</span><span class="p">)</span><span class="o">.</span><span class="n">joinpath</span><span class="p">(</span><span class="s1">&#39;auto-sklearn&#39;</span><span class="p">)</span><span class="o">.</span><span class="n">expanduser</span><span class="p">()</span>
<span class="n">selector_file</span> <span class="o">=</span> <span class="n">selector_directory</span> <span class="o">/</span> <span class="n">selector_filename</span>
<span class="n">metafeatures</span> <span class="o">=</span> <span class="n">pd</span><span class="o">.</span><span class="n">DataFrame</span><span class="p">(</span><span class="n">training_data</span><span class="p">[</span><span class="s1">&#39;metafeatures&#39;</span><span class="p">])</span>
<span class="n">y_values</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="n">training_data</span><span class="p">[</span><span class="s1">&#39;y_values&#39;</span><span class="p">])</span>
<span class="n">strategies</span> <span class="o">=</span> <span class="n">training_data</span><span class="p">[</span><span class="s1">&#39;strategies&#39;</span><span class="p">]</span>
Expand All @@ -165,8 +166,14 @@ <h1>Source code for autosklearn.experimental.askl2</h1><div class="highlight"><p
<span class="n">maxima</span><span class="o">=</span><span class="n">maxima_for_methods</span><span class="p">,</span>
<span class="p">)</span>
<span class="n">selector_file</span><span class="o">.</span><span class="n">parent</span><span class="o">.</span><span class="n">mkdir</span><span class="p">(</span><span class="n">exist_ok</span><span class="o">=</span><span class="kc">True</span><span class="p">,</span> <span class="n">parents</span><span class="o">=</span><span class="kc">True</span><span class="p">)</span>
<span class="k">with</span> <span class="nb">open</span><span class="p">(</span><span class="n">selector_file</span><span class="p">,</span> <span class="s1">&#39;wb&#39;</span><span class="p">)</span> <span class="k">as</span> <span class="n">fh</span><span class="p">:</span>
<span class="n">pickle</span><span class="o">.</span><span class="n">dump</span><span class="p">(</span><span class="n">selector</span><span class="p">,</span> <span class="n">fh</span><span class="p">)</span>
<span class="k">try</span><span class="p">:</span>
<span class="k">with</span> <span class="nb">open</span><span class="p">(</span><span class="n">selector_file</span><span class="p">,</span> <span class="s1">&#39;wb&#39;</span><span class="p">)</span> <span class="k">as</span> <span class="n">fh</span><span class="p">:</span>
<span class="n">pickle</span><span class="o">.</span><span class="n">dump</span><span class="p">(</span><span class="n">selector</span><span class="p">,</span> <span class="n">fh</span><span class="p">)</span>
<span class="k">except</span> <span class="ne">Exception</span> <span class="k">as</span> <span class="n">e</span><span class="p">:</span>
<span class="nb">print</span><span class="p">(</span><span class="s2">&quot;AutoSklearn2Classifier needs to create a selector file under &quot;</span>
<span class="s2">&quot;the user&#39;s home directory or XDG_CACHE_HOME. Nevertheless &quot;</span>
<span class="s2">&quot;the path </span><span class="si">{}</span><span class="s2"> is not writable.&quot;</span><span class="o">.</span><span class="n">format</span><span class="p">(</span><span class="n">selector_file</span><span class="p">))</span>
<span class="k">raise</span> <span class="n">e</span>


<span class="k">class</span> <span class="nc">SmacObjectCallback</span><span class="p">:</span>
Expand Down Expand Up @@ -268,6 +275,7 @@ <h1>Source code for autosklearn.experimental.askl2</h1><div class="highlight"><p
<span class="k">def</span> <span class="fm">__init__</span><span class="p">(</span>
<span class="bp">self</span><span class="p">,</span>
<span class="n">time_left_for_this_task</span><span class="p">:</span> <span class="nb">int</span> <span class="o">=</span> <span class="mi">3600</span><span class="p">,</span>
<span class="n">per_run_time_limit</span><span class="o">=</span><span class="kc">None</span><span class="p">,</span>
<span class="n">ensemble_size</span><span class="p">:</span> <span class="nb">int</span> <span class="o">=</span> <span class="mi">50</span><span class="p">,</span>
<span class="n">ensemble_nbest</span><span class="p">:</span> <span class="n">Union</span><span class="p">[</span><span class="nb">float</span><span class="p">,</span> <span class="nb">int</span><span class="p">]</span> <span class="o">=</span> <span class="mi">50</span><span class="p">,</span>
<span class="n">max_models_on_disc</span><span class="p">:</span> <span class="nb">int</span> <span class="o">=</span> <span class="mi">50</span><span class="p">,</span>
Expand Down Expand Up @@ -295,6 +303,13 @@ <h1>Source code for autosklearn.experimental.askl2</h1><div class="highlight"><p
<span class="sd"> models. By increasing this value, *auto-sklearn* has a higher</span>
<span class="sd"> chance of finding better models.</span>

<span class="sd"> per_run_time_limit : int, optional (default=1/10 of time_left_for_this_task)</span>
<span class="sd"> Time limit for a single call to the machine learning model.</span>
<span class="sd"> Model fitting will be terminated if the machine learning</span>
<span class="sd"> algorithm runs over the time limit. Set this value high enough so</span>
<span class="sd"> that typical machine learning algorithms can be fit on the</span>
<span class="sd"> training data.</span>

<span class="sd"> ensemble_size : int, optional (default=50)</span>
<span class="sd"> Number of models added to the ensemble built by *Ensemble</span>
<span class="sd"> selection from libraries of models*. Models are drawn with</span>
Expand Down Expand Up @@ -367,7 +382,7 @@ <h1>Source code for autosklearn.experimental.askl2</h1><div class="highlight"><p

<span class="sd"> smac_scenario_args : dict, optional (None)</span>
<span class="sd"> Additional arguments inserted into the scenario of SMAC. See the</span>
<span class="sd"> `SMAC documentation </span>
<span class="sd"> `SMAC documentation</span>
<span class="sd"> &lt;https://automl.github.io/SMAC3/master/options.html?highlight=scenario</span>
<span class="sd"> #scenario&gt;`_</span>
<span class="sd"> for a list of available arguments.</span>
Expand All @@ -384,7 +399,7 @@ <h1>Source code for autosklearn.experimental.askl2</h1><div class="highlight"><p
<span class="sd"> If None is provided, a default metric is selected depending on the task.</span>

<span class="sd"> scoring_functions : List[Scorer], optional (None)</span>
<span class="sd"> List of scorers which will be calculated for each pipeline and results will be </span>
<span class="sd"> List of scorers which will be calculated for each pipeline and results will be</span>
<span class="sd"> available via ``cv_results``</span>

<span class="sd"> load_models : bool, optional (True)</span>
Expand All @@ -407,6 +422,7 @@ <h1>Source code for autosklearn.experimental.askl2</h1><div class="highlight"><p
<span class="n">include_preprocessors</span> <span class="o">=</span> <span class="p">[</span><span class="s2">&quot;no_preprocessing&quot;</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">time_left_for_this_task</span><span class="o">=</span><span class="n">time_left_for_this_task</span><span class="p">,</span>
<span class="n">per_run_time_limit</span><span class="o">=</span><span class="n">per_run_time_limit</span><span class="p">,</span>
<span class="n">initial_configurations_via_metalearning</span><span class="o">=</span><span class="mi">0</span><span class="p">,</span>
<span class="n">ensemble_size</span><span class="o">=</span><span class="n">ensemble_size</span><span class="p">,</span>
<span class="n">ensemble_nbest</span><span class="o">=</span><span class="n">ensemble_nbest</span><span class="p">,</span>
Expand Down
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