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dengdifan: fix dist twine check for github (automl#439)
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‎development/_downloads/bc82bea3a5dd7bdba60b65220891d9e5/examples_python.zip‎

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‎development/_downloads/fb625db3c50d423b1b7881136ffdeec8/examples_jupyter.zip‎

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‎development/_images/sphx_glr_example_plot_over_time_001.png‎

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‎development/_images/sphx_glr_example_plot_over_time_thumb.png‎

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‎development/_images/sphx_glr_example_visualization_001.png‎

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‎development/_images/sphx_glr_example_visualization_thumb.png‎

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‎development/_sources/examples/20_basics/example_image_classification.rst.txt‎

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@@ -85,17 +85,15 @@ Image Classification
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Pipeline Random Config:
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________________________________________
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Configuration(values={
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'image_augmenter:GaussianBlur:use_augmenter': False,
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'image_augmenter:GaussianBlur:sigma_min': 1.321282449895124,
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'image_augmenter:GaussianBlur:sigma_offset': 1.170627862969532,
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'image_augmenter:GaussianBlur:use_augmenter': True,
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'image_augmenter:GaussianNoise:use_augmenter': False,
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'image_augmenter:RandomAffine:rotate': 25,
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'image_augmenter:RandomAffine:scale_offset': 0.17911084673615535,
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'image_augmenter:RandomAffine:shear': 29,
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'image_augmenter:RandomAffine:translate_percent_offset': 0.2595162834252603,
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'image_augmenter:RandomAffine:use_augmenter': True,
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'image_augmenter:RandomCutout:p': 0.41657143992832846,
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'image_augmenter:RandomAffine:use_augmenter': False,
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'image_augmenter:RandomCutout:p': 0.924326689627855,
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'image_augmenter:RandomCutout:use_augmenter': True,
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'image_augmenter:Resize:use_augmenter': False,
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'image_augmenter:ZeroPadAndCrop:percent': 0.2504071930090588,
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'image_augmenter:ZeroPadAndCrop:percent': 0.2936727016383677,
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'normalizer:__choice__': 'NoNormalizer',
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})
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.. rst-class:: sphx-glr-timing
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**Total running time of the script:** ( 0 minutes 5.591 seconds)
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**Total running time of the script:** ( 0 minutes 5.420 seconds)
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.. _sphx_glr_download_examples_20_basics_example_image_classification.py:

‎development/_sources/examples/20_basics/example_tabular_classification.rst.txt‎

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.. code-block:: none
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<autoPyTorch.api.tabular_classification.TabularClassificationTask object at 0x7fdc1b398100>
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<autoPyTorch.api.tabular_classification.TabularClassificationTask object at 0x7f41d91834f0>
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@@ -165,23 +165,25 @@ Print the final ensemble performance
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.. code-block:: none
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{'accuracy': 0.8670520231213873}
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{'accuracy': 0.861271676300578}
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| | Preprocessing | Estimator | Weight |
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|---:|:-------------------------------------------------------------------------------------------------|:----------------------------------------------------------------|---------:|
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| 0 | None | CBLearner | 0.32 |
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| 1 | SimpleImputer,Variance Threshold,MinorityCoalescer,OneHotEncoder,QuantileTransformer,KitchenSink | no embedding,ShapedMLPBackbone,FullyConnectedHead,nn.Sequential | 0.2 |
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| 2 | SimpleImputer,Variance Threshold,NoCoalescer,OneHotEncoder,StandardScaler,SRC | embedding,MLPBackbone,FullyConnectedHead,nn.Sequential | 0.2 |
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| 3 | SimpleImputer,Variance Threshold,MinorityCoalescer,OneHotEncoder,NoScaler,KitchenSink | embedding,ResNetBackbone,FullyConnectedHead,nn.Sequential | 0.12 |
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| 4 | SimpleImputer,Variance Threshold,MinorityCoalescer,OneHotEncoder,QuantileTransformer,KitchenSink | no embedding,ShapedMLPBackbone,FullyConnectedHead,nn.Sequential | 0.08 |
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| 5 | SimpleImputer,Variance Threshold,MinorityCoalescer,OneHotEncoder,QuantileTransformer,KitchenSink | no embedding,ShapedMLPBackbone,FullyConnectedHead,nn.Sequential | 0.08 |
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| 0 | SimpleImputer,Variance Threshold,NoCoalescer,OneHotEncoder,StandardScaler,SRC | embedding,MLPBackbone,FullyConnectedHead,nn.Sequential | 0.38 |
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| 1 | SimpleImputer,Variance Threshold,MinorityCoalescer,OneHotEncoder,NoScaler,KitchenSink | embedding,ResNetBackbone,FullyConnectedHead,nn.Sequential | 0.18 |
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| 2 | SimpleImputer,Variance Threshold,MinorityCoalescer,OneHotEncoder,QuantileTransformer,KitchenSink | no embedding,ShapedMLPBackbone,FullyConnectedHead,nn.Sequential | 0.16 |
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| 3 | SimpleImputer,Variance Threshold,NoCoalescer,OneHotEncoder,StandardScaler,NoFeaturePreprocessing | no embedding,ShapedMLPBackbone,FullyConnectedHead,nn.Sequential | 0.1 |
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| 4 | SimpleImputer,Variance Threshold,MinorityCoalescer,OneHotEncoder,NoScaler,KitchenSink | embedding,ResNetBackbone,FullyConnectedHead,nn.Sequential | 0.08 |
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| 5 | None | SVMLearner | 0.04 |
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| 6 | SimpleImputer,Variance Threshold,MinorityCoalescer,OneHotEncoder,NoScaler,KitchenSink | embedding,ResNetBackbone,FullyConnectedHead,nn.Sequential | 0.04 |
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| 7 | None | CBLearner | 0.02 |
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autoPyTorch results:
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Dataset name: Australian
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Optimisation Metric: accuracy
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Best validation score: 0.8713450292397661
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Number of target algorithm runs: 21
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Number of target algorithm runs: 22
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Number of successful target algorithm runs: 19
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Number of crashed target algorithm runs: 0
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Number of target algorithms that exceeded the time limit: 2
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Number of target algorithms that exceeded the time limit: 3
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Number of target algorithms that exceeded the memory limit: 0
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.. rst-class:: sphx-glr-timing
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**Total running time of the script:** ( 5 minutes 20.003 seconds)
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**Total running time of the script:** ( 5 minutes 29.291 seconds)
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.. _sphx_glr_download_examples_20_basics_example_tabular_classification.py:

‎development/_sources/examples/20_basics/example_tabular_regression.rst.txt‎

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.. code-block:: none
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<autoPyTorch.api.tabular_regression.TabularRegressionTask object at 0x7fdca57c8b50>
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<autoPyTorch.api.tabular_regression.TabularRegressionTask object at 0x7f426a157cd0>
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| 2 | SimpleImputer,Variance Threshold,NoCoalescer,OneHotEncoder,StandardScaler,NoFeaturePreprocessing | no embedding,ShapedMLPBackbone,FullyConnectedHead,nn.Sequential | 0.1 |
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| 3 | None | LGBMLearner | 0.04 |
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autoPyTorch results:
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Dataset name: 7a5ffe66-f075-11ec-8806-a30cbc8a0bb8
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Dataset name: 3828ee5f-f23e-11ec-87fd-dbbaad031c38
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Optimisation Metric: r2
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Best validation score: 0.8670098636440993
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Number of target algorithm runs: 24
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.. rst-class:: sphx-glr-timing
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**Total running time of the script:** ( 5 minutes 35.570 seconds)
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**Total running time of the script:** ( 5 minutes 32.769 seconds)
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.. _sphx_glr_download_examples_20_basics_example_tabular_regression.py:

‎development/_sources/examples/20_basics/sg_execution_times.rst.txt‎

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Computation times
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=================
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**11:01.164** total execution time for **examples_20_basics** files:
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**11:07.480** total execution time for **examples_20_basics** files:
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+--------------------------------------------------------------------------------------------------------------+-----------+--------+
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| :ref:`sphx_glr_examples_20_basics_example_tabular_regression.py` (``example_tabular_regression.py``) | 05:35.570 | 0.0 MB |
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| :ref:`sphx_glr_examples_20_basics_example_tabular_regression.py` (``example_tabular_regression.py``) | 05:32.769 | 0.0 MB |
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+--------------------------------------------------------------------------------------------------------------+-----------+--------+
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| :ref:`sphx_glr_examples_20_basics_example_tabular_classification.py` (``example_tabular_classification.py``) | 05:20.003 | 0.0 MB |
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| :ref:`sphx_glr_examples_20_basics_example_tabular_classification.py` (``example_tabular_classification.py``) | 05:29.291 | 0.0 MB |
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+--------------------------------------------------------------------------------------------------------------+-----------+--------+
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| :ref:`sphx_glr_examples_20_basics_example_image_classification.py` (``example_image_classification.py``) | 00:05.591 | 0.0 MB |
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| :ref:`sphx_glr_examples_20_basics_example_image_classification.py` (``example_image_classification.py``) | 00:05.420 | 0.0 MB |
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+--------------------------------------------------------------------------------------------------------------+-----------+--------+

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