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Francisco Rivera Valverde: [MAINT] Drop 3.6 python support (#258)
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2 changes: 1 addition & 1 deletion development/.buildinfo
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# 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: 17fc031f04bcdcacd110ea23c1e3544e
config: eac5a5960d6840dbbd3eb7c13e8b13e2
tags: 645f666f9bcd5a90fca523b33c5a78b7
2 changes: 1 addition & 1 deletion development/_downloads/38ebc52de63d1626596d1647c695c721/example_tabular_regression.ipynb
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Expand Up @@ -80,7 +80,7 @@
},
"outputs": [],
"source": [
"api.search(\n X_train=X_train,\n y_train=y_train,\n X_test=X_test.copy(),\n y_test=y_test.copy(),\n optimize_metric='r2',\n total_walltime_limit=300,\n func_eval_time_limit_secs=50,\n enable_traditional_pipeline=False,\n)"
"api.search(\n X_train=X_train,\n y_train=y_train,\n X_test=X_test.copy(),\n y_test=y_test.copy(),\n optimize_metric='r2',\n total_walltime_limit=300,\n func_eval_time_limit_secs=50,\n)"
]
},
{
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1 change: 0 additions & 1 deletion development/_downloads/bbd6ad27117588060207b551c10df82e/example_tabular_regression.py
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Expand Up @@ -50,7 +50,6 @@
optimize_metric='r2',
total_walltime_limit=300,
func_eval_time_limit_secs=50,
enable_traditional_pipeline=False,
)

############################################################################
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396 changes: 396 additions & 0 deletions development/_modules/autoPyTorch/api/tabular_regression.html
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1 change: 1 addition & 0 deletions development/_modules/index.html
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Expand Up @@ -112,6 +112,7 @@

<h1>All modules for which code is available</h1>
<ul><li><a href="autoPyTorch/api/tabular_classification.html">autoPyTorch.api.tabular_classification</a></li>
<li><a href="autoPyTorch/api/tabular_regression.html">autoPyTorch.api.tabular_regression</a></li>
</ul>

</div>
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8 changes: 8 additions & 0 deletions development/_sources/api.rst.txt
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Expand Up @@ -16,3 +16,11 @@ Classification
.. autoclass:: autoPyTorch.api.tabular_classification.TabularClassificationTask
:members:
:inherited-members: search, refit, predict, score

~~~~~~~~~~~~~~
Regression
~~~~~~~~~~~~~~

.. autoclass:: autoPyTorch.api.tabular_regression.TabularRegressionTask
:members:
:inherited-members: search, refit, predict, score
20 changes: 6 additions & 14 deletions development/_sources/examples/20_basics/example_image_classification.rst.txt
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Expand Up @@ -53,8 +53,6 @@ Image Classification
19.9% 39.8% 59.7% 79.6% 99.5% 119.3%
Extracting ../datasets/FashionMNIST/raw/t10k-labels-idx1-ubyte.gz to ../datasets/FashionMNIST/raw

Processing...
Done!
Pipeline CS:
________________________________________
Configuration space object:
Expand Down Expand Up @@ -88,17 +86,11 @@ Image Classification
________________________________________
Configuration:
image_augmenter:GaussianBlur:use_augmenter, Value: False
image_augmenter:GaussianNoise:sigma_offset, Value: 2.2167939735095414
image_augmenter:GaussianNoise:use_augmenter, Value: True
image_augmenter:RandomAffine:rotate, Value: 32
image_augmenter:RandomAffine:scale_offset, Value: 0.21992528764167255
image_augmenter:RandomAffine:shear, Value: 10
image_augmenter:RandomAffine:translate_percent_offset, Value: 0.3741519768349007
image_augmenter:RandomAffine:use_augmenter, Value: True
image_augmenter:RandomCutout:p, Value: 0.7598328080896313
image_augmenter:RandomCutout:use_augmenter, Value: True
image_augmenter:GaussianNoise:use_augmenter, Value: False
image_augmenter:RandomAffine:use_augmenter, Value: False
image_augmenter:RandomCutout:use_augmenter, Value: False
image_augmenter:Resize:use_augmenter, Value: False
image_augmenter:ZeroPadAndCrop:percent, Value: 0.40737331917856867
image_augmenter:ZeroPadAndCrop:percent, Value: 0.20738957470432307
normalizer:__choice__, Value: 'NoNormalizer'

Fitting the pipeline...
Expand Down Expand Up @@ -178,7 +170,7 @@ Image Classification
.. rst-class:: sphx-glr-timing

**Total running time of the script:** ( 0 minutes 5.302 seconds)
**Total running time of the script:** ( 0 minutes 7.763 seconds)


.. _sphx_glr_download_examples_20_basics_example_image_classification.py:
Expand All @@ -193,7 +185,7 @@ Image Classification
.. container:: binder-badge
.. image:: images/binder_badge_logo.svg
:target: https://mybinder.org/v2/gh/automl/Auto-PyTorch/refactor_development?urlpath=lab/tree/notebooks/examples/20_basics/example_image_classification.ipynb
:target: https://mybinder.org/v2/gh/automl/Auto-PyTorch/development?urlpath=lab/tree/notebooks/examples/20_basics/example_image_classification.ipynb
:alt: Launch binder
:width: 150 px
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103 changes: 58 additions & 45 deletions development/_sources/examples/20_basics/example_tabular_classification.rst.txt
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Expand Up @@ -133,7 +133,7 @@ Search for an ensemble of machine learning algorithms
.. code-block:: none
<autoPyTorch.api.tabular_classification.TabularClassificationTask object at 0x7fc73f9a9cd0>
<autoPyTorch.api.tabular_classification.TabularClassificationTask object at 0x7f94d464afd0>
Expand Down Expand Up @@ -162,7 +162,7 @@ Print the final ensemble performance

.. code-block:: none
<smac.runhistory.runhistory.RunHistory object at 0x7fc73f9a9ee0> [TrajEntry(train_perf=2147483648, incumbent_id=1, incumbent=Configuration:
<smac.runhistory.runhistory.RunHistory object at 0x7f94d464ac10> [TrajEntry(train_perf=2147483648, incumbent_id=1, incumbent=Configuration:
data_loader:batch_size, Value: 64
encoder:__choice__, Value: 'OneHotEncoder'
feature_preprocessor:__choice__, Value: 'NoFeaturePreprocessor'
Expand Down Expand Up @@ -194,7 +194,7 @@ Print the final ensemble performance
scaler:__choice__, Value: 'StandardScaler'
trainer:StandardTrainer:weighted_loss, Value: True
trainer:__choice__, Value: 'StandardTrainer'
, ta_runs=0, ta_time_used=0.0, wallclock_time=0.0012178421020507812, budget=0), TrajEntry(train_perf=0.17543859649122806, incumbent_id=1, incumbent=Configuration:
, ta_runs=0, ta_time_used=0.0, wallclock_time=0.0011582374572753906, budget=0), TrajEntry(train_perf=0.16374269005847952, incumbent_id=1, incumbent=Configuration:
data_loader:batch_size, Value: 64
encoder:__choice__, Value: 'OneHotEncoder'
feature_preprocessor:__choice__, Value: 'NoFeaturePreprocessor'
Expand Down Expand Up @@ -226,59 +226,72 @@ Print the final ensemble performance
scaler:__choice__, Value: 'StandardScaler'
trainer:StandardTrainer:weighted_loss, Value: True
trainer:__choice__, Value: 'StandardTrainer'
, ta_runs=1, ta_time_used=1.8383204936981201, wallclock_time=2.867694139480591, budget=5.555555555555555), TrajEntry(train_perf=0.14619883040935677, incumbent_id=2, incumbent=Configuration:
data_loader:batch_size, Value: 54
encoder:__choice__, Value: 'OneHotEncoder'
feature_preprocessor:__choice__, Value: 'NoFeaturePreprocessor'
, ta_runs=1, ta_time_used=1.9798626899719238, wallclock_time=3.0097038745880127, budget=5.555555555555555), TrajEntry(train_perf=0.13450292397660824, incumbent_id=2, incumbent=Configuration:
data_loader:batch_size, Value: 131
encoder:__choice__, Value: 'NoEncoder'
feature_preprocessor:KernelPCA:coef0, Value: -0.2027355777455664
feature_preprocessor:KernelPCA:degree, Value: 2
feature_preprocessor:KernelPCA:gamma, Value: 0.0029756156161293078
feature_preprocessor:KernelPCA:kernel, Value: 'poly'
feature_preprocessor:KernelPCA:n_components, Value: 4
feature_preprocessor:__choice__, Value: 'KernelPCA'
imputer:categorical_strategy, Value: 'constant_!missing!'
imputer:numerical_strategy, Value: 'mean'
lr_scheduler:CosineAnnealingLR:T_max, Value: 307
lr_scheduler:__choice__, Value: 'CosineAnnealingLR'
network_backbone:ShapedMLPBackbone:activation, Value: 'relu'
network_backbone:ShapedMLPBackbone:max_dropout, Value: 0.543030049110043
network_backbone:ShapedMLPBackbone:max_units, Value: 35
network_backbone:ShapedMLPBackbone:mlp_shape, Value: 'hexagon'
network_backbone:ShapedMLPBackbone:num_groups, Value: 3
network_backbone:ShapedMLPBackbone:output_dim, Value: 18
network_backbone:ShapedMLPBackbone:use_dropout, Value: True
network_backbone:__choice__, Value: 'ShapedMLPBackbone'
lr_scheduler:CosineAnnealingWarmRestarts:T_0, Value: 20
lr_scheduler:CosineAnnealingWarmRestarts:T_mult, Value: 1.2502829975237466
lr_scheduler:__choice__, Value: 'CosineAnnealingWarmRestarts'
network_backbone:ShapedResNetBackbone:activation, Value: 'sigmoid'
network_backbone:ShapedResNetBackbone:blocks_per_group, Value: 2
network_backbone:ShapedResNetBackbone:max_units, Value: 21
network_backbone:ShapedResNetBackbone:num_groups, Value: 11
network_backbone:ShapedResNetBackbone:output_dim, Value: 128
network_backbone:ShapedResNetBackbone:resnet_shape, Value: 'stairs'
network_backbone:ShapedResNetBackbone:use_dropout, Value: False
network_backbone:ShapedResNetBackbone:use_shake_drop, Value: False
network_backbone:ShapedResNetBackbone:use_shake_shake, Value: False
network_backbone:__choice__, Value: 'ShapedResNetBackbone'
network_embedding:__choice__, Value: 'NoEmbedding'
network_head:__choice__, Value: 'fully_connected'
network_head:fully_connected:activation, Value: 'relu'
network_head:fully_connected:num_layers, Value: 3
network_head:fully_connected:units_layer_1, Value: 316
network_head:fully_connected:units_layer_2, Value: 503
network_init:SparseInit:bias_strategy, Value: 'Normal'
network_init:__choice__, Value: 'SparseInit'
optimizer:AdamWOptimizer:beta1, Value: 0.9489565046389004
optimizer:AdamWOptimizer:beta2, Value: 0.9647522172509646
optimizer:AdamWOptimizer:lr, Value: 0.0030477242366055836
optimizer:AdamWOptimizer:weight_decay, Value: 0.061913730296919815
optimizer:__choice__, Value: 'AdamWOptimizer'
network_head:fully_connected:activation, Value: 'tanh'
network_head:fully_connected:num_layers, Value: 4
network_head:fully_connected:units_layer_1, Value: 415
network_head:fully_connected:units_layer_2, Value: 290
network_head:fully_connected:units_layer_3, Value: 313
network_init:KaimingInit:bias_strategy, Value: 'Normal'
network_init:__choice__, Value: 'KaimingInit'
optimizer:AdamOptimizer:beta1, Value: 0.9981587455677909
optimizer:AdamOptimizer:beta2, Value: 0.9934737249657393
optimizer:AdamOptimizer:lr, Value: 0.0015351906927605823
optimizer:AdamOptimizer:weight_decay, Value: 0.06126849297256112
optimizer:__choice__, Value: 'AdamOptimizer'
scaler:__choice__, Value: 'MinMaxScaler'
trainer:MixUpTrainer:alpha, Value: 0.8559230573827334
trainer:MixUpTrainer:weighted_loss, Value: True
trainer:__choice__, Value: 'MixUpTrainer'
, ta_runs=18, ta_time_used=198.87974619865417, wallclock_time=247.5048122406006, budget=50.0)]
{'accuracy': 0.861271676300578}
| | Preprocessing | Estimator | Weight |
|---:|:------------------------------------------------------------------|:----------------------------------------------------------------|---------:|
| 0 | SimpleImputer,NoEncoder,Normalizer,Nystroem | no embedding,ShapedMLPBackbone,FullyConnectedHead,nn.Sequential | 0.2 |
| 1 | SimpleImputer,OneHotEncoder,StandardScaler,NoFeaturePreprocessing | no embedding,ShapedMLPBackbone,FullyConnectedHead,nn.Sequential | 0.2 |
| 2 | None | CatBoostClassifier | 0.18 |
| 3 | None | SVC | 0.18 |
| 4 | None | RFClassifier | 0.08 |
| 5 | None | ExtraTreesClassifier | 0.06 |
| 6 | None | KNNClassifier | 0.06 |
| 7 | SimpleImputer,OneHotEncoder,MinMaxScaler,NoFeaturePreprocessing | no embedding,ShapedMLPBackbone,FullyConnectedHead,nn.Sequential | 0.04 |
trainer:StandardTrainer:weighted_loss, Value: False
trainer:__choice__, Value: 'StandardTrainer'
, ta_runs=20, ta_time_used=86.29950213432312, wallclock_time=148.91276454925537, budget=50.0)]
{'accuracy': 0.884393063583815}
| | Preprocessing | Estimator | Weight |
|---:|:------------------------------------------------------------------|:-------------------------------------------------------------------|---------:|
| 0 | None | CBLearner | 0.24 |
| 1 | SimpleImputer,OneHotEncoder,MinMaxScaler,KitchenSink | no embedding,ShapedMLPBackbone,FullyConnectedHead,nn.Sequential | 0.14 |
| 2 | SimpleImputer,OneHotEncoder,StandardScaler,NoFeaturePreprocessing | no embedding,ShapedMLPBackbone,FullyConnectedHead,nn.Sequential | 0.12 |
| 3 | SimpleImputer,OneHotEncoder,MinMaxScaler,KitchenSink | no embedding,ShapedMLPBackbone,FullyConnectedHead,nn.Sequential | 0.1 |
| 4 | SimpleImputer,NoEncoder,MinMaxScaler,KernelPCA | no embedding,ShapedResNetBackbone,FullyConnectedHead,nn.Sequential | 0.08 |
| 5 | None | RFLearner | 0.06 |
| 6 | None | SVMLearner | 0.06 |
| 7 | SimpleImputer,OneHotEncoder,StandardScaler,NoFeaturePreprocessing | no embedding,ShapedMLPBackbone,FullyConnectedHead,nn.Sequential | 0.06 |
| 8 | SimpleImputer,NoEncoder,NoScaler,Nystroem | no embedding,ShapedResNetBackbone,FullyConnectedHead,nn.Sequential | 0.04 |
| 9 | SimpleImputer,NoEncoder,NoScaler,Nystroem | no embedding,ShapedResNetBackbone,FullyConnectedHead,nn.Sequential | 0.04 |
| 10 | None | ETLearner | 0.02 |
| 11 | None | KNNLearner | 0.02 |
| 12 | SimpleImputer,OneHotEncoder,StandardScaler,NoFeaturePreprocessing | no embedding,ShapedMLPBackbone,FullyConnectedHead,nn.Sequential | 0.02 |
.. rst-class:: sphx-glr-timing

**Total running time of the script:** ( 5 minutes 26.583 seconds)
**Total running time of the script:** ( 5 minutes 26.276 seconds)


.. _sphx_glr_download_examples_20_basics_example_tabular_classification.py:
Expand All @@ -293,7 +306,7 @@ Print the final ensemble performance
.. container:: binder-badge
.. image:: images/binder_badge_logo.svg
:target: https://mybinder.org/v2/gh/automl/Auto-PyTorch/refactor_development?urlpath=lab/tree/notebooks/examples/20_basics/example_tabular_classification.ipynb
:target: https://mybinder.org/v2/gh/automl/Auto-PyTorch/development?urlpath=lab/tree/notebooks/examples/20_basics/example_tabular_classification.ipynb
:alt: Launch binder
:width: 150 px
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