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nabenabe0928: [fix] Be able to display error messages in additional info as it is (#225)
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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_visualization_001.png

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‎development/_images/sphx_glr_example_visualization_002.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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@@ -86,16 +86,16 @@ Image Classification
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________________________________________
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Configuration:
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image_augmenter:GaussianBlur:use_augmenter, Value: False
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image_augmenter:GaussianNoise:use_augmenter, Value: False
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image_augmenter:RandomAffine:rotate, Value: 234
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image_augmenter:RandomAffine:scale_offset, Value: 0.13898529256943157
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image_augmenter:RandomAffine:shear, Value: 6
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image_augmenter:RandomAffine:translate_percent_offset, Value: 0.28972636379927325
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image_augmenter:GaussianNoise:sigma_offset, Value: 0.28308981908683095
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image_augmenter:GaussianNoise:use_augmenter, Value: True
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image_augmenter:RandomAffine:rotate, Value: 91
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image_augmenter:RandomAffine:scale_offset, Value: 0.1419348290937196
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image_augmenter:RandomAffine:shear, Value: 45
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image_augmenter:RandomAffine:translate_percent_offset, Value: 0.30537089818273044
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image_augmenter:RandomAffine:use_augmenter, Value: True
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image_augmenter:RandomCutout:p, Value: 0.522348887660727
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image_augmenter:RandomCutout:use_augmenter, Value: True
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image_augmenter:RandomCutout:use_augmenter, Value: False
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image_augmenter:Resize:use_augmenter, Value: False
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image_augmenter:ZeroPadAndCrop:percent, Value: 0.4724090929806815
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image_augmenter:ZeroPadAndCrop:percent, Value: 0.26934979186928804
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normalizer:__choice__, Value: 'NoNormalizer'
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Fitting the pipeline...
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.. rst-class:: sphx-glr-timing
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**Total running time of the script:** ( 0 minutes 8.275 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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@@ -133,7 +133,7 @@ Search for an ensemble of machine learning algorithms
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.. code-block:: none
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<autoPyTorch.api.tabular_classification.TabularClassificationTask object at 0x7f04ede6f550>
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<autoPyTorch.api.tabular_classification.TabularClassificationTask object at 0x7fed3eaddd90>
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@@ -162,7 +162,7 @@ Print the final ensemble performance
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.. code-block:: none
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<smac.runhistory.runhistory.RunHistory object at 0x7f04ede6f790> [TrajEntry(train_perf=2147483648, incumbent_id=1, incumbent=Configuration:
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<smac.runhistory.runhistory.RunHistory object at 0x7fed3e8d8a30> [TrajEntry(train_perf=2147483648, incumbent_id=1, incumbent=Configuration:
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data_loader:batch_size, Value: 64
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encoder:__choice__, Value: 'OneHotEncoder'
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feature_preprocessor:__choice__, Value: 'NoFeaturePreprocessor'
@@ -194,7 +194,7 @@ Print the final ensemble performance
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scaler:__choice__, Value: 'StandardScaler'
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trainer:StandardTrainer:weighted_loss, Value: True
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trainer:__choice__, Value: 'StandardTrainer'
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, ta_runs=0, ta_time_used=0.0, wallclock_time=0.0013458728790283203, budget=0), TrajEntry(train_perf=0.18128654970760238, incumbent_id=1, incumbent=Configuration:
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, ta_runs=0, ta_time_used=0.0, wallclock_time=0.0014102458953857422, budget=0), TrajEntry(train_perf=0.18128654970760238, incumbent_id=1, incumbent=Configuration:
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data_loader:batch_size, Value: 64
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encoder:__choice__, Value: 'OneHotEncoder'
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feature_preprocessor:__choice__, Value: 'NoFeaturePreprocessor'
@@ -226,69 +226,82 @@ Print the final ensemble performance
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scaler:__choice__, Value: 'StandardScaler'
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trainer:StandardTrainer:weighted_loss, Value: True
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trainer:__choice__, Value: 'StandardTrainer'
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, ta_runs=1, ta_time_used=2.172813653945923, wallclock_time=3.204160451889038, budget=5.555555555555555), TrajEntry(train_perf=0.14035087719298245, incumbent_id=2, incumbent=Configuration:
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data_loader:batch_size, Value: 131
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encoder:__choice__, Value: 'NoEncoder'
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feature_preprocessor:KernelPCA:coef0, Value: -0.2027355777455664
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feature_preprocessor:KernelPCA:degree, Value: 2
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feature_preprocessor:KernelPCA:gamma, Value: 0.0029756156161293078
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feature_preprocessor:KernelPCA:kernel, Value: 'poly'
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feature_preprocessor:KernelPCA:n_components, Value: 4
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feature_preprocessor:__choice__, Value: 'KernelPCA'
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imputer:categorical_strategy, Value: 'constant_!missing!'
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imputer:numerical_strategy, Value: 'mean'
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lr_scheduler:CosineAnnealingWarmRestarts:T_0, Value: 20
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lr_scheduler:CosineAnnealingWarmRestarts:T_mult, Value: 1.2502829975237466
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, ta_runs=1, ta_time_used=2.9105358123779297, wallclock_time=3.9437384605407715, budget=5.555555555555555), TrajEntry(train_perf=0.13450292397660824, incumbent_id=2, incumbent=Configuration:
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data_loader:batch_size, Value: 149
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encoder:__choice__, Value: 'OneHotEncoder'
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feature_preprocessor:Nystroem:gamma, Value: 0.0011818439394745584
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feature_preprocessor:Nystroem:kernel, Value: 'rbf'
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feature_preprocessor:Nystroem:n_components, Value: 3
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feature_preprocessor:__choice__, Value: 'Nystroem'
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imputer:categorical_strategy, Value: 'most_frequent'
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imputer:numerical_strategy, Value: 'constant_zero'
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lr_scheduler:CosineAnnealingWarmRestarts:T_0, Value: 13
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lr_scheduler:CosineAnnealingWarmRestarts:T_mult, Value: 1.524242262025724
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lr_scheduler:__choice__, Value: 'CosineAnnealingWarmRestarts'
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network_backbone:ShapedResNetBackbone:activation, Value: 'sigmoid'
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network_backbone:ShapedResNetBackbone:blocks_per_group, Value: 2
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network_backbone:ShapedResNetBackbone:max_units, Value: 21
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network_backbone:ShapedResNetBackbone:num_groups, Value: 11
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network_backbone:ShapedResNetBackbone:output_dim, Value: 128
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network_backbone:ShapedResNetBackbone:resnet_shape, Value: 'stairs'
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network_backbone:ShapedResNetBackbone:use_dropout, Value: False
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network_backbone:ShapedResNetBackbone:use_shake_drop, Value: False
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network_backbone:ShapedResNetBackbone:use_shake_shake, Value: False
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network_backbone:__choice__, Value: 'ShapedResNetBackbone'
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network_backbone:ResNetBackbone:activation, Value: 'tanh'
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network_backbone:ResNetBackbone:blocks_per_group_0, Value: 1
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network_backbone:ResNetBackbone:blocks_per_group_1, Value: 1
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network_backbone:ResNetBackbone:blocks_per_group_2, Value: 4
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network_backbone:ResNetBackbone:blocks_per_group_3, Value: 2
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network_backbone:ResNetBackbone:blocks_per_group_4, Value: 2
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network_backbone:ResNetBackbone:blocks_per_group_5, Value: 2
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network_backbone:ResNetBackbone:dropout_0, Value: 0.26612716792811836
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network_backbone:ResNetBackbone:dropout_1, Value: 0.4042968315566448
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network_backbone:ResNetBackbone:dropout_2, Value: 0.10216930761786128
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network_backbone:ResNetBackbone:dropout_3, Value: 0.6859286849839384
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network_backbone:ResNetBackbone:dropout_4, Value: 0.56482307358881
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network_backbone:ResNetBackbone:dropout_5, Value: 0.03114494377280881
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network_backbone:ResNetBackbone:max_shake_drop_probability, Value: 0.06411335288267506
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network_backbone:ResNetBackbone:num_groups, Value: 5
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network_backbone:ResNetBackbone:num_units_0, Value: 142
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network_backbone:ResNetBackbone:num_units_1, Value: 425
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network_backbone:ResNetBackbone:num_units_2, Value: 826
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network_backbone:ResNetBackbone:num_units_3, Value: 27
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network_backbone:ResNetBackbone:num_units_4, Value: 309
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network_backbone:ResNetBackbone:num_units_5, Value: 345
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network_backbone:ResNetBackbone:use_dropout, Value: True
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network_backbone:ResNetBackbone:use_shake_drop, Value: True
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network_backbone:ResNetBackbone:use_shake_shake, Value: False
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network_backbone:__choice__, Value: 'ResNetBackbone'
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network_embedding:__choice__, Value: 'NoEmbedding'
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network_head:__choice__, Value: 'fully_connected'
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network_head:fully_connected:activation, Value: 'tanh'
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network_head:fully_connected:num_layers, Value: 4
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network_head:fully_connected:units_layer_1, Value: 415
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network_head:fully_connected:units_layer_2, Value: 290
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network_head:fully_connected:units_layer_3, Value: 313
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network_init:KaimingInit:bias_strategy, Value: 'Normal'
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network_init:__choice__, Value: 'KaimingInit'
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optimizer:AdamOptimizer:beta1, Value: 0.9981587455677909
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optimizer:AdamOptimizer:beta2, Value: 0.9934737249657393
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optimizer:AdamOptimizer:lr, Value: 0.0015351906927605823
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optimizer:AdamOptimizer:weight_decay, Value: 0.06126849297256112
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optimizer:__choice__, Value: 'AdamOptimizer'
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scaler:__choice__, Value: 'MinMaxScaler'
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trainer:StandardTrainer:weighted_loss, Value: False
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network_head:fully_connected:activation, Value: 'sigmoid'
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network_head:fully_connected:num_layers, Value: 2
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network_head:fully_connected:units_layer_1, Value: 356
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network_init:OrthogonalInit:bias_strategy, Value: 'Normal'
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network_init:__choice__, Value: 'OrthogonalInit'
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optimizer:AdamWOptimizer:beta1, Value: 0.9376381409135858
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optimizer:AdamWOptimizer:beta2, Value: 0.9559640621179888
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optimizer:AdamWOptimizer:lr, Value: 3.153418844144074e-05
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optimizer:AdamWOptimizer:weight_decay, Value: 0.04398417011111847
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optimizer:__choice__, Value: 'AdamWOptimizer'
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scaler:__choice__, Value: 'StandardScaler'
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trainer:StandardTrainer:weighted_loss, Value: True
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trainer:__choice__, Value: 'StandardTrainer'
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, ta_runs=20, ta_time_used=119.23157835006714, wallclock_time=186.0883228778839, budget=50.0)]
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{'accuracy': 0.861271676300578}
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| | Preprocessing | Estimator | Weight |
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|---:|:------------------------------------------------------------------|:-------------------------------------------------------------------|---------:|
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| 0 | None | RFLearner | 0.2 |
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| 1 | SimpleImputer,NoEncoder,MinMaxScaler,KernelPCA | no embedding,ShapedResNetBackbone,FullyConnectedHead,nn.Sequential | 0.14 |
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| 2 | SimpleImputer,NoEncoder,Normalizer,NoFeaturePreprocessing | no embedding,ShapedResNetBackbone,FullyConnectedHead,nn.Sequential | 0.14 |
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| 3 | None | CBLearner | 0.12 |
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| 4 | None | SVMLearner | 0.1 |
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| 5 | None | KNNLearner | 0.1 |
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| 6 | SimpleImputer,NoEncoder,Normalizer,NoFeaturePreprocessing | no embedding,ShapedResNetBackbone,FullyConnectedHead,nn.Sequential | 0.06 |
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| 7 | None | ETLearner | 0.06 |
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| 8 | SimpleImputer,OneHotEncoder,StandardScaler,NoFeaturePreprocessing | no embedding,ShapedMLPBackbone,FullyConnectedHead,nn.Sequential | 0.06 |
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| 9 | SimpleImputer,OneHotEncoder,StandardScaler,NoFeaturePreprocessing | no embedding,ShapedMLPBackbone,FullyConnectedHead,nn.Sequential | 0.02 |
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, ta_runs=20, ta_time_used=165.19103455543518, wallclock_time=239.00682401657104, budget=50.0)]
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{'accuracy': 0.8497109826589595}
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| | Preprocessing | Estimator | Weight |
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|---:|:------------------------------------------------------------------|:----------------------------------------------------------------|---------:|
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| 0 | SimpleImputer,OneHotEncoder,MinMaxScaler,KitchenSink | no embedding,ShapedMLPBackbone,FullyConnectedHead,nn.Sequential | 0.26 |
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| 1 | SimpleImputer,NoEncoder,StandardScaler,Nystroem | no embedding,ShapedMLPBackbone,FullyConnectedHead,nn.Sequential | 0.18 |
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| 2 | SimpleImputer,OneHotEncoder,MinMaxScaler,KitchenSink | no embedding,ShapedMLPBackbone,FullyConnectedHead,nn.Sequential | 0.16 |
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| 3 | SimpleImputer,NoEncoder,StandardScaler,Nystroem | no embedding,ShapedMLPBackbone,FullyConnectedHead,nn.Sequential | 0.1 |
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| 4 | SimpleImputer,OneHotEncoder,StandardScaler,Nystroem | no embedding,ResNetBackbone,FullyConnectedHead,nn.Sequential | 0.06 |
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| 5 | None | KNNLearner | 0.06 |
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| 6 | None | CBLearner | 0.04 |
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| 7 | None | SVMLearner | 0.04 |
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| 8 | SimpleImputer,OneHotEncoder,StandardScaler,NoFeaturePreprocessing | no embedding,ShapedMLPBackbone,FullyConnectedHead,nn.Sequential | 0.04 |
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| 9 | None | RFLearner | 0.02 |
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| 10 | SimpleImputer,OneHotEncoder,StandardScaler,NoFeaturePreprocessing | no embedding,ShapedMLPBackbone,FullyConnectedHead,nn.Sequential | 0.02 |
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| 11 | SimpleImputer,OneHotEncoder,StandardScaler,NoFeaturePreprocessing | no embedding,ShapedMLPBackbone,FullyConnectedHead,nn.Sequential | 0.02 |
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.. rst-class:: sphx-glr-timing
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**Total running time of the script:** ( 5 minutes 30.259 seconds)
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**Total running time of the script:** ( 5 minutes 25.335 seconds)
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.. _sphx_glr_download_examples_20_basics_example_tabular_classification.py:

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