Ravin Kohli: Fix 361 (#367)

automl · Jan 24, 2022 · 536951b · 536951b
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diff --git a/development/.buildinfo b/development/.buildinfo
@@ -1,4 +1,4 @@
 # Sphinx build info version 1
 # This file hashes the configuration used when building these files. When it is not found, a full rebuild will be done.
-config: 970eb458f32b434db48854a3317b2f05
+config: d030894ca2be9e5e86b4fd97a867854b
 tags: 645f666f9bcd5a90fca523b33c5a78b7
diff --git a/development/_downloads/bc82bea3a5dd7bdba60b65220891d9e5/examples_python.zip b/development/_downloads/bc82bea3a5dd7bdba60b65220891d9e5/examples_python.zip
diff --git a/development/_downloads/fb625db3c50d423b1b7881136ffdeec8/examples_jupyter.zip b/development/_downloads/fb625db3c50d423b1b7881136ffdeec8/examples_jupyter.zip
diff --git a/development/_images/sphx_glr_example_plot_over_time_001.png b/development/_images/sphx_glr_example_plot_over_time_001.png
diff --git a/development/_images/sphx_glr_example_plot_over_time_thumb.png b/development/_images/sphx_glr_example_plot_over_time_thumb.png
diff --git a/development/_images/sphx_glr_example_visualization_001.png b/development/_images/sphx_glr_example_visualization_001.png
diff --git a/development/_images/sphx_glr_example_visualization_thumb.png b/development/_images/sphx_glr_example_visualization_thumb.png
diff --git a/development/_modules/autoPyTorch/api/tabular_classification.html b/development/_modules/autoPyTorch/api/tabular_classification.html
@@ -565,8 +565,8 @@ <h1>Source code for autoPyTorch.api.tabular_classification</h1><div class="highl
 
     </p>
     <p>
-        &copy; Copyright 2014-2021, Machine Learning Professorship Freiburg.<br/>
-      Created using <a href="http://sphinx-doc.org/">Sphinx</a> 4.3.2.<br/>
+        &copy; Copyright 2014-2022, Machine Learning Professorship Freiburg.<br/>
+      Created using <a href="http://sphinx-doc.org/">Sphinx</a> 4.4.0.<br/>
     </p>
   </div>
 </footer>

diff --git a/development/_modules/autoPyTorch/api/tabular_regression.html b/development/_modules/autoPyTorch/api/tabular_regression.html
@@ -541,8 +541,8 @@ <h1>Source code for autoPyTorch.api.tabular_regression</h1><div class="highlight
 
     </p>
     <p>
-        &copy; Copyright 2014-2021, Machine Learning Professorship Freiburg.<br/>
-      Created using <a href="http://sphinx-doc.org/">Sphinx</a> 4.3.2.<br/>
+        &copy; Copyright 2014-2022, Machine Learning Professorship Freiburg.<br/>
+      Created using <a href="http://sphinx-doc.org/">Sphinx</a> 4.4.0.<br/>
     </p>
   </div>
 </footer>

diff --git a/development/_modules/autoPyTorch/pipeline/components/base_choice.html b/development/_modules/autoPyTorch/pipeline/components/base_choice.html
@@ -433,8 +433,8 @@ <h1>Source code for autoPyTorch.pipeline.components.base_choice</h1><div class="
 
     </p>
     <p>
-        &copy; Copyright 2014-2021, Machine Learning Professorship Freiburg.<br/>
-      Created using <a href="http://sphinx-doc.org/">Sphinx</a> 4.3.2.<br/>
+        &copy; Copyright 2014-2022, Machine Learning Professorship Freiburg.<br/>
+      Created using <a href="http://sphinx-doc.org/">Sphinx</a> 4.4.0.<br/>
     </p>
   </div>
 </footer>

diff --git a/development/_modules/autoPyTorch/pipeline/components/base_component.html b/development/_modules/autoPyTorch/pipeline/components/base_component.html
@@ -441,8 +441,8 @@ <h1>Source code for autoPyTorch.pipeline.components.base_component</h1><div clas
 
     </p>
     <p>
-        &copy; Copyright 2014-2021, Machine Learning Professorship Freiburg.<br/>
-      Created using <a href="http://sphinx-doc.org/">Sphinx</a> 4.3.2.<br/>
+        &copy; Copyright 2014-2022, Machine Learning Professorship Freiburg.<br/>
+      Created using <a href="http://sphinx-doc.org/">Sphinx</a> 4.4.0.<br/>
     </p>
   </div>
 </footer>

diff --git a/development/_modules/autoPyTorch/pipeline/tabular_classification.html b/development/_modules/autoPyTorch/pipeline/tabular_classification.html
@@ -501,8 +501,8 @@ <h1>Source code for autoPyTorch.pipeline.tabular_classification</h1><div class="
 
     </p>
     <p>
-        &copy; Copyright 2014-2021, Machine Learning Professorship Freiburg.<br/>
-      Created using <a href="http://sphinx-doc.org/">Sphinx</a> 4.3.2.<br/>
+        &copy; Copyright 2014-2022, Machine Learning Professorship Freiburg.<br/>
+      Created using <a href="http://sphinx-doc.org/">Sphinx</a> 4.4.0.<br/>
     </p>
   </div>
 </footer>

diff --git a/development/_modules/autoPyTorch/pipeline/tabular_regression.html b/development/_modules/autoPyTorch/pipeline/tabular_regression.html
@@ -451,8 +451,8 @@ <h1>Source code for autoPyTorch.pipeline.tabular_regression</h1><div class="high
 
     </p>
     <p>
-        &copy; Copyright 2014-2021, Machine Learning Professorship Freiburg.<br/>
-      Created using <a href="http://sphinx-doc.org/">Sphinx</a> 4.3.2.<br/>
+        &copy; Copyright 2014-2022, Machine Learning Professorship Freiburg.<br/>
+      Created using <a href="http://sphinx-doc.org/">Sphinx</a> 4.4.0.<br/>
     </p>
   </div>
 </footer>

diff --git a/development/_modules/autoPyTorch/pipeline/traditional_tabular_classification.html b/development/_modules/autoPyTorch/pipeline/traditional_tabular_classification.html
@@ -398,8 +398,8 @@ <h1>Source code for autoPyTorch.pipeline.traditional_tabular_classification</h1>
 
     </p>
     <p>
-        &copy; Copyright 2014-2021, Machine Learning Professorship Freiburg.<br/>
-      Created using <a href="http://sphinx-doc.org/">Sphinx</a> 4.3.2.<br/>
+        &copy; Copyright 2014-2022, Machine Learning Professorship Freiburg.<br/>
+      Created using <a href="http://sphinx-doc.org/">Sphinx</a> 4.4.0.<br/>
     </p>
   </div>
 </footer>

diff --git a/development/_modules/autoPyTorch/pipeline/traditional_tabular_regression.html b/development/_modules/autoPyTorch/pipeline/traditional_tabular_regression.html
@@ -354,8 +354,8 @@ <h1>Source code for autoPyTorch.pipeline.traditional_tabular_regression</h1><div
 
     </p>
     <p>
-        &copy; Copyright 2014-2021, Machine Learning Professorship Freiburg.<br/>
-      Created using <a href="http://sphinx-doc.org/">Sphinx</a> 4.3.2.<br/>
+        &copy; Copyright 2014-2022, Machine Learning Professorship Freiburg.<br/>
+      Created using <a href="http://sphinx-doc.org/">Sphinx</a> 4.4.0.<br/>
     </p>
   </div>
 </footer>

diff --git a/development/_modules/index.html b/development/_modules/index.html
@@ -135,8 +135,8 @@ <h1>All modules for which code is available</h1>
 
     </p>
     <p>
-        &copy; Copyright 2014-2021, Machine Learning Professorship Freiburg.<br/>
-      Created using <a href="http://sphinx-doc.org/">Sphinx</a> 4.3.2.<br/>
+        &copy; Copyright 2014-2022, Machine Learning Professorship Freiburg.<br/>
+      Created using <a href="http://sphinx-doc.org/">Sphinx</a> 4.4.0.<br/>
     </p>
   </div>
 </footer>

diff --git a/development/_sources/examples/20_basics/example_image_classification.rst.txt b/development/_sources/examples/20_basics/example_image_classification.rst.txt
@@ -85,25 +85,28 @@ Image Classification
     Pipeline Random Config:
      ________________________________________ 
     Configuration:
-      image_augmenter:GaussianBlur:use_augmenter, Value: False
-      image_augmenter:GaussianNoise:sigma_offset, Value: 1.1975184564563195
+      image_augmenter:GaussianBlur:sigma_min, Value: 0.7252880928545244
+      image_augmenter:GaussianBlur:sigma_offset, Value: 1.521238468454762
+      image_augmenter:GaussianBlur:use_augmenter, Value: True
+      image_augmenter:GaussianNoise:sigma_offset, Value: 1.3019933264526289
       image_augmenter:GaussianNoise:use_augmenter, Value: True
-      image_augmenter:RandomAffine:rotate, Value: 153
-      image_augmenter:RandomAffine:scale_offset, Value: 0.12364128806028525
-      image_augmenter:RandomAffine:shear, Value: 11
-      image_augmenter:RandomAffine:translate_percent_offset, Value: 0.13912161805475703
+      image_augmenter:RandomAffine:rotate, Value: 273
+      image_augmenter:RandomAffine:scale_offset, Value: 0.32933509809921574
+      image_augmenter:RandomAffine:shear, Value: 18
+      image_augmenter:RandomAffine:translate_percent_offset, Value: 0.12689372744350622
       image_augmenter:RandomAffine:use_augmenter, Value: True
-      image_augmenter:RandomCutout:use_augmenter, Value: False
+      image_augmenter:RandomCutout:p, Value: 0.2567527903290805
+      image_augmenter:RandomCutout:use_augmenter, Value: True
       image_augmenter:Resize:use_augmenter, Value: False
-      image_augmenter:ZeroPadAndCrop:percent, Value: 0.31488822578125014
-      normalizer:__choice__, Value: 'ImageNormalizer'
+      image_augmenter:ZeroPadAndCrop:percent, Value: 0.38501712446074526
+      normalizer:__choice__, Value: 'NoNormalizer'
 
     Fitting the pipeline...
     ________________________________________
             ImageClassificationPipeline
     ________________________________________
     0-) normalizer: 
-            ImageNormalizer
+            NoNormalizer
 
     1-) preprocessing: 
             EarlyPreprocessing
@@ -175,7 +178,7 @@ Image Classification
 
 .. rst-class:: sphx-glr-timing
 
-   **Total running time of the script:** ( 0 minutes  6.231 seconds)
+   **Total running time of the script:** ( 0 minutes  8.384 seconds)
 
 
 .. _sphx_glr_download_examples_20_basics_example_image_classification.py:

diff --git a/development/_sources/examples/20_basics/example_tabular_classification.rst.txt b/development/_sources/examples/20_basics/example_tabular_classification.rst.txt
@@ -134,7 +134,7 @@ Search for an ensemble of machine learning algorithms
  .. code-block:: none
 
 
-    <autoPyTorch.api.tabular_classification.TabularClassificationTask object at 0x7f19236b9430>
+    <autoPyTorch.api.tabular_classification.TabularClassificationTask object at 0x7f9622505520>
 
 
 
@@ -196,7 +196,7 @@ Print the final ensemble performance
 
 .. rst-class:: sphx-glr-timing
 
-   **Total running time of the script:** ( 5 minutes  37.241 seconds)
+   **Total running time of the script:** ( 5 minutes  46.740 seconds)
 
 
 .. _sphx_glr_download_examples_20_basics_example_tabular_classification.py:

diff --git a/development/_sources/examples/20_basics/example_tabular_regression.rst.txt b/development/_sources/examples/20_basics/example_tabular_regression.rst.txt
@@ -125,7 +125,7 @@ Search for an ensemble of machine learning algorithms
  .. code-block:: none
 
 
-    <autoPyTorch.api.tabular_regression.TabularRegressionTask object at 0x7f19c00e8dc0>
+    <autoPyTorch.api.tabular_regression.TabularRegressionTask object at 0x7f96b47a72e0>
 
 
 
@@ -167,13 +167,13 @@ Print the final ensemble performance
     |  2 | None                                                              | LGBMLearner                                                     |     0.08 |
     |  3 | SimpleImputer,OneHotEncoder,StandardScaler,NoFeaturePreprocessing | no embedding,ShapedMLPBackbone,FullyConnectedHead,nn.Sequential |     0.06 |
     autoPyTorch results:
-            Dataset name: d92e165b-6274-11ec-8842-fd2c828ae65b
+            Dataset name: 8c995636-7d0f-11ec-8762-c7716973b762
             Optimisation Metric: r2
             Best validation score: 0.8644967965917701
-            Number of target algorithm runs: 22
+            Number of target algorithm runs: 23
             Number of successful target algorithm runs: 20
             Number of crashed target algorithm runs: 1
-            Number of target algorithms that exceeded the time limit: 1
+            Number of target algorithms that exceeded the time limit: 2
             Number of target algorithms that exceeded the memory limit: 0
 
 
@@ -183,7 +183,7 @@ Print the final ensemble performance
 
 .. rst-class:: sphx-glr-timing
 
-   **Total running time of the script:** ( 5 minutes  33.522 seconds)
+   **Total running time of the script:** ( 5 minutes  49.941 seconds)
 
 
 .. _sphx_glr_download_examples_20_basics_example_tabular_regression.py:

diff --git a/development/_sources/examples/20_basics/sg_execution_times.rst.txt b/development/_sources/examples/20_basics/sg_execution_times.rst.txt
@@ -5,12 +5,12 @@
 
 Computation times
 =================
-**11:16.994** total execution time for **examples_20_basics** files:
+**11:45.065** total execution time for **examples_20_basics** files:
 
 +--------------------------------------------------------------------------------------------------------------+-----------+--------+
-| :ref:`sphx_glr_examples_20_basics_example_tabular_classification.py` (``example_tabular_classification.py``) | 05:37.241 | 0.0 MB |
+| :ref:`sphx_glr_examples_20_basics_example_tabular_regression.py` (``example_tabular_regression.py``)         | 05:49.941 | 0.0 MB |
 +--------------------------------------------------------------------------------------------------------------+-----------+--------+
-| :ref:`sphx_glr_examples_20_basics_example_tabular_regression.py` (``example_tabular_regression.py``)         | 05:33.522 | 0.0 MB |
+| :ref:`sphx_glr_examples_20_basics_example_tabular_classification.py` (``example_tabular_classification.py``) | 05:46.740 | 0.0 MB |
 +--------------------------------------------------------------------------------------------------------------+-----------+--------+
-| :ref:`sphx_glr_examples_20_basics_example_image_classification.py` (``example_image_classification.py``)     | 00:06.231 | 0.0 MB |
+| :ref:`sphx_glr_examples_20_basics_example_image_classification.py` (``example_image_classification.py``)     | 00:08.384 | 0.0 MB |
 +--------------------------------------------------------------------------------------------------------------+-----------+--------+
diff --git a/...opment/_sources/examples/40_advanced/example_custom_configuration_space.rst.txt b/...opment/_sources/examples/40_advanced/example_custom_configuration_space.rst.txt
@@ -163,7 +163,7 @@ Search for an ensemble of machine learning algorithms
  .. code-block:: none
 
 
-    <autoPyTorch.api.tabular_classification.TabularClassificationTask object at 0x7f19230192e0>
+    <autoPyTorch.api.tabular_classification.TabularClassificationTask object at 0x7f961c24b190>
 
 
 
@@ -194,22 +194,23 @@ Print the final ensemble performance
 
  .. code-block:: none
 
-    {'accuracy': 0.8728323699421965}
+    {'accuracy': 0.8670520231213873}
     |    | Preprocessing                                                     | Estimator                                                 |   Weight |
     |---:|:------------------------------------------------------------------|:----------------------------------------------------------|---------:|
-    |  0 | None                                                              | RFLearner                                                 |     0.42 |
-    |  1 | None                                                              | ETLearner                                                 |     0.24 |
-    |  2 | None                                                              | LGBMLearner                                               |     0.14 |
+    |  0 | None                                                              | RFLearner                                                 |     0.44 |
+    |  1 | None                                                              | ETLearner                                                 |     0.26 |
+    |  2 | None                                                              | LGBMLearner                                               |     0.1  |
     |  3 | None                                                              | SVMLearner                                                |     0.08 |
     |  4 | None                                                              | KNNLearner                                                |     0.08 |
-    |  5 | SimpleImputer,OneHotEncoder,StandardScaler,NoFeaturePreprocessing | no embedding,MLPBackbone,FullyConnectedHead,nn.Sequential |     0.04 |
+    |  5 | SimpleImputer,OneHotEncoder,StandardScaler,NoFeaturePreprocessing | no embedding,MLPBackbone,FullyConnectedHead,nn.Sequential |     0.02 |
+    |  6 | SimpleImputer,OneHotEncoder,StandardScaler,NoFeaturePreprocessing | no embedding,MLPBackbone,FullyConnectedHead,nn.Sequential |     0.02 |
     autoPyTorch results:
-            Dataset name: 91ea9c50-6278-11ec-8842-fd2c828ae65b
+            Dataset name: 3b91f6a7-7d13-11ec-8762-c7716973b762
             Optimisation Metric: accuracy
             Best validation score: 0.8596491228070176
-            Number of target algorithm runs: 15
+            Number of target algorithm runs: 17
             Number of successful target algorithm runs: 13
-            Number of crashed target algorithm runs: 1
+            Number of crashed target algorithm runs: 3
             Number of target algorithms that exceeded the time limit: 1
             Number of target algorithms that exceeded the memory limit: 0
 
@@ -269,7 +270,7 @@ Search for an ensemble of machine learning algorithms
  .. code-block:: none
 
 
-    <autoPyTorch.api.tabular_classification.TabularClassificationTask object at 0x7f1922b0be50>
+    <autoPyTorch.api.tabular_classification.TabularClassificationTask object at 0x7f96220f03a0>
 
 
 
@@ -306,15 +307,16 @@ Print the final ensemble performance
     |  1 | None                                                          | ETLearner                                                       |     0.26 |
     |  2 | None                                                          | LGBMLearner                                                     |     0.2  |
     |  3 | None                                                          | KNNLearner                                                      |     0.08 |
-    |  4 | None                                                          | SVMLearner                                                      |     0.06 |
-    |  5 | SimpleImputer,NoEncoder,StandardScaler,NoFeaturePreprocessing | no embedding,ShapedMLPBackbone,FullyConnectedHead,nn.Sequential |     0.06 |
+    |  4 | SimpleImputer,NoEncoder,StandardScaler,NoFeaturePreprocessing | no embedding,ShapedMLPBackbone,FullyConnectedHead,nn.Sequential |     0.06 |
+    |  5 | None                                                          | SVMLearner                                                      |     0.04 |
+    |  6 | SimpleImputer,NoEncoder,StandardScaler,NoFeaturePreprocessing | no embedding,ShapedMLPBackbone,FullyConnectedHead,nn.Sequential |     0.02 |
     autoPyTorch results:
-            Dataset name: fc8643fb-6278-11ec-8842-fd2c828ae65b
+            Dataset name: a3b948ad-7d13-11ec-8762-c7716973b762
             Optimisation Metric: accuracy
             Best validation score: 0.8596491228070176
             Number of target algorithm runs: 17
-            Number of successful target algorithm runs: 16
-            Number of crashed target algorithm runs: 0
+            Number of successful target algorithm runs: 13
+            Number of crashed target algorithm runs: 3
             Number of target algorithms that exceeded the time limit: 1
             Number of target algorithms that exceeded the memory limit: 0
 
@@ -325,7 +327,7 @@ Print the final ensemble performance
 
 .. rst-class:: sphx-glr-timing
 
-   **Total running time of the script:** ( 5 minutes  49.334 seconds)
+   **Total running time of the script:** ( 5 minutes  55.495 seconds)
 
 
 .. _sphx_glr_download_examples_40_advanced_example_custom_configuration_space.py:

diff --git a/development/_sources/examples/40_advanced/example_parallel_n_jobs.rst.txt b/development/_sources/examples/40_advanced/example_parallel_n_jobs.rst.txt
@@ -36,14 +36,14 @@ with AutoPyTorch
 
  .. code-block:: none
 
-    {'accuracy': 0.8554913294797688}
+    {'accuracy': 0.8497109826589595}
     autoPyTorch results:
-            Dataset name: 942e38d5-6277-11ec-8842-fd2c828ae65b
+            Dataset name: 419ef270-7d12-11ec-8762-c7716973b762
             Optimisation Metric: accuracy
             Best validation score: 0.8713450292397661
-            Number of target algorithm runs: 43
-            Number of successful target algorithm runs: 35
-            Number of crashed target algorithm runs: 7
+            Number of target algorithm runs: 46
+            Number of successful target algorithm runs: 37
+            Number of crashed target algorithm runs: 8
             Number of target algorithms that exceeded the time limit: 1
             Number of target algorithms that exceeded the memory limit: 0
 
@@ -121,7 +121,7 @@ with AutoPyTorch
 
 .. rst-class:: sphx-glr-timing
 
-   **Total running time of the script:** ( 5 minutes  40.376 seconds)
+   **Total running time of the script:** ( 5 minutes  32.350 seconds)
 
 
 .. _sphx_glr_download_examples_40_advanced_example_parallel_n_jobs.py:

diff --git a/development/_sources/examples/40_advanced/example_plot_over_time.rst.txt b/development/_sources/examples/40_advanced/example_plot_over_time.rst.txt
@@ -89,9 +89,9 @@ Task Definition
 
  .. code-block:: none
 
-    [1 1 1 1 0 1 1 0 0 1 0 1 0 0 0 1 0 1 0 1 1 1 0 0 1 0 1 0 1 1 1 1 0 1 0 1 1
-     0 1 0 0 1 0 0 1 1 0 0 1 0 0 1 1 0 0 0 1 0 0 1 0 1 1 1 0 0 0 0 1 0 1 0 0 1
-     0 1 1 0 1 0 0 1 1 1 0 0 1 0 0 1 0 1 1 1 0 1 0 0 1 0]
+    [1 0 1 1 1 1 0 0 0 0 0 1 1 0 1 1 1 0 0 0 0 0 1 1 0 0 1 1 0 0 1 0 0 0 0 1 0
+     1 0 0 0 1 0 0 0 0 1 1 0 0 1 0 0 0 0 0 1 0 0 0 1 0 1 1 0 1 1 1 1 0 0 1 1 1
+     0 1 1 0 0 1 0 0 0 0 1 1 0 0 1 0 0 1 1 1 0 1 1 1 1 1]
 
 
 
@@ -120,12 +120,8 @@ API Instantiation and Searching
 
  .. code-block:: none
 
-    [WARNING] [2021-12-21 16:02:50,128:smac.runhistory.runhistory2epm.RunHistory2EPM4LogCost] Got cost of smaller/equal to 0. Replace by 0.000010 since we use log cost.
-    [WARNING] [2021-12-21 16:03:04,067:smac.runhistory.runhistory2epm.RunHistory2EPM4LogCost] Got cost of smaller/equal to 0. Replace by 0.000010 since we use log cost.
-    [WARNING] [2021-12-21 16:03:16,713:smac.runhistory.runhistory2epm.RunHistory2EPM4LogCost] Got cost of smaller/equal to 0. Replace by 0.000010 since we use log cost.
-    [WARNING] [2021-12-21 16:03:30,101:smac.runhistory.runhistory2epm.RunHistory2EPM4LogCost] Got cost of smaller/equal to 0. Replace by 0.000010 since we use log cost.
 
-    <autoPyTorch.api.tabular_classification.TabularClassificationTask object at 0x7f1922c1d9a0>
+    <autoPyTorch.api.tabular_classification.TabularClassificationTask object at 0x7f9621cc8190>
 
 
 
@@ -190,7 +186,7 @@ _, ax = plt.subplots()  <=== You can feed it to post-process the figure.
 
 .. rst-class:: sphx-glr-timing
 
-   **Total running time of the script:** ( 2 minutes  35.045 seconds)
+   **Total running time of the script:** ( 2 minutes  20.749 seconds)
 
 
 .. _sphx_glr_download_examples_40_advanced_example_plot_over_time.py: