Skip to content

Commit e2f601b

Browse files
author
Github Actions
committed
Francisco Rivera Valverde: move to a minimization problem (#113)
1 parent 6fcbddd commit e2f601b

File tree

11 files changed

+55
-201
lines changed

11 files changed

+55
-201
lines changed

‎refactor_development/_downloads/bc82bea3a5dd7bdba60b65220891d9e5/examples_python.zip

0 Bytes
Binary file not shown.

‎refactor_development/_downloads/fb625db3c50d423b1b7881136ffdeec8/examples_jupyter.zip

0 Bytes
Binary file not shown.

‎refactor_development/_sources/examples/example_image_classification.rst.txt

Lines changed: 3 additions & 4 deletions
Original file line numberDiff line numberDiff line change
@@ -82,12 +82,11 @@ Image Classification
8282
________________________________________
8383
Configuration:
8484
image_augmenter:GaussianBlur:use_augmenter, Value: False
85-
image_augmenter:GaussianNoise:sigma_offset, Value: 0.5614286279360542
86-
image_augmenter:GaussianNoise:use_augmenter, Value: True
85+
image_augmenter:GaussianNoise:use_augmenter, Value: False
8786
image_augmenter:RandomAffine:use_augmenter, Value: False
8887
image_augmenter:RandomCutout:use_augmenter, Value: False
8988
image_augmenter:Resize:use_augmenter, Value: True
90-
image_augmenter:ZeroPadAndCrop:percent, Value: 0.2076158247310454
89+
image_augmenter:ZeroPadAndCrop:percent, Value: 0.208578408262465
9190
normalizer:__choice__, Value: 'NoNormalizer'
9291

9392
Fitting the pipeline...
@@ -167,7 +166,7 @@ Image Classification
167166
168167
.. rst-class:: sphx-glr-timing
169168

170-
**Total running time of the script:** ( 0 minutes 9.520 seconds)
169+
**Total running time of the script:** ( 0 minutes 9.911 seconds)
171170

172171

173172
.. _sphx_glr_download_examples_example_image_classification.py:

‎refactor_development/_sources/examples/example_tabular_classification.rst.txt

Lines changed: 15 additions & 55 deletions
Original file line numberDiff line numberDiff line change
@@ -36,7 +36,7 @@ with AutoPyTorch
3636

3737
.. code-block:: none
3838
39-
<smac.runhistory.runhistory.RunHistory object at 0x7ff7fbf2b190> [TrajEntry(train_perf=2147483648, incumbent_id=1, incumbent=Configuration:
39+
<smac.runhistory.runhistory.RunHistory object at 0x7f983433d160> [TrajEntry(train_perf=2147483648, incumbent_id=1, incumbent=Configuration:
4040
data_loader:batch_size, Value: 32
4141
encoder:__choice__, Value: 'OneHotEncoder'
4242
feature_preprocessor:__choice__, Value: 'NoFeaturePreprocessor'
@@ -77,7 +77,7 @@ with AutoPyTorch
7777
scaler:__choice__, Value: 'StandardScaler'
7878
trainer:StandardTrainer:weighted_loss, Value: True
7979
trainer:__choice__, Value: 'StandardTrainer'
80-
, ta_runs=0, ta_time_used=0.0, wallclock_time=0.0019752979278564453, budget=0), TrajEntry(train_perf=0.216374269005848, incumbent_id=1, incumbent=Configuration:
80+
, ta_runs=0, ta_time_used=0.0, wallclock_time=0.00208282470703125, budget=0), TrajEntry(train_perf=0.16959064327485385, incumbent_id=1, incumbent=Configuration:
8181
data_loader:batch_size, Value: 32
8282
encoder:__choice__, Value: 'OneHotEncoder'
8383
feature_preprocessor:__choice__, Value: 'NoFeaturePreprocessor'
@@ -118,40 +118,7 @@ with AutoPyTorch
118118
scaler:__choice__, Value: 'StandardScaler'
119119
trainer:StandardTrainer:weighted_loss, Value: True
120120
trainer:__choice__, Value: 'StandardTrainer'
121-
, ta_runs=1, ta_time_used=5.269052505493164, wallclock_time=6.652451276779175, budget=5.555555555555555), TrajEntry(train_perf=0.21052631578947367, incumbent_id=2, incumbent=Configuration:
122-
data_loader:batch_size, Value: 472
123-
encoder:__choice__, Value: 'NoEncoder'
124-
feature_preprocessor:Nystroem:gamma, Value: 0.07411722362589628
125-
feature_preprocessor:Nystroem:kernel, Value: 'rbf'
126-
feature_preprocessor:Nystroem:n_components, Value: 5
127-
feature_preprocessor:__choice__, Value: 'Nystroem'
128-
imputer:categorical_strategy, Value: 'constant_!missing!'
129-
imputer:numerical_strategy, Value: 'constant_zero'
130-
lr_scheduler:__choice__, Value: 'NoScheduler'
131-
network_backbone:ShapedMLPBackbone:activation, Value: 'tanh'
132-
network_backbone:ShapedMLPBackbone:max_units, Value: 766
133-
network_backbone:ShapedMLPBackbone:mlp_shape, Value: 'diamond'
134-
network_backbone:ShapedMLPBackbone:num_groups, Value: 9
135-
network_backbone:ShapedMLPBackbone:output_dim, Value: 243
136-
network_backbone:ShapedMLPBackbone:use_dropout, Value: False
137-
network_backbone:__choice__, Value: 'ShapedMLPBackbone'
138-
network_embedding:__choice__, Value: 'NoEmbedding'
139-
network_head:__choice__, Value: 'fully_connected'
140-
network_head:fully_connected:activation, Value: 'tanh'
141-
network_head:fully_connected:num_layers, Value: 3
142-
network_head:fully_connected:units_layer_1, Value: 323
143-
network_head:fully_connected:units_layer_2, Value: 332
144-
network_init:KaimingInit:bias_strategy, Value: 'Normal'
145-
network_init:__choice__, Value: 'KaimingInit'
146-
optimizer:SGDOptimizer:lr, Value: 0.0024087824203718427
147-
optimizer:SGDOptimizer:momentum, Value: 0.418322885741585
148-
optimizer:SGDOptimizer:weight_decay, Value: 0.015250671878609713
149-
optimizer:__choice__, Value: 'SGDOptimizer'
150-
scaler:__choice__, Value: 'NoScaler'
151-
trainer:MixUpTrainer:alpha, Value: 0.4043218849947128
152-
trainer:MixUpTrainer:weighted_loss, Value: True
153-
trainer:__choice__, Value: 'MixUpTrainer'
154-
, ta_runs=3, ta_time_used=40.172093629837036, wallclock_time=46.57782244682312, budget=5.555555555555555), TrajEntry(train_perf=0.17543859649122806, incumbent_id=3, incumbent=Configuration:
121+
, ta_runs=1, ta_time_used=4.665428161621094, wallclock_time=6.140820026397705, budget=5.555555555555555), TrajEntry(train_perf=0.14619883040935677, incumbent_id=2, incumbent=Configuration:
155122
data_loader:batch_size, Value: 224
156123
encoder:__choice__, Value: 'OneHotEncoder'
157124
feature_preprocessor:KernelPCA:gamma, Value: 0.6217858094449208
@@ -184,26 +151,19 @@ with AutoPyTorch
184151
trainer:MixUpTrainer:alpha, Value: 0.7490557199071863
185152
trainer:MixUpTrainer:weighted_loss, Value: False
186153
trainer:__choice__, Value: 'MixUpTrainer'
187-
, ta_runs=4, ta_time_used=48.74088931083679, wallclock_time=56.56371068954468, budget=5.555555555555555)]
188-
{'accuracy': 0.861271676300578}
154+
, ta_runs=12, ta_time_used=105.31449437141418, wallclock_time=135.89934992790222, budget=16.666666666666664)]
155+
{'accuracy': 0.884393063583815}
189156
| | Preprocessing | Estimator | Weight |
190157
|---:|:------------------------------------------------------------------|:-------------------------------------------------------------------|---------:|
191-
| 0 | SimpleImputer,OneHotEncoder,StandardScaler,KernelPCA | no embedding,ShapedMLPBackbone,FullyConnectedHead,nn.Sequential | 0.14 |
192-
| 1 | None | ExtraTreesClassifier | 0.12 |
193-
| 2 | None | KNNClassifier | 0.12 |
194-
| 3 | SimpleImputer,OneHotEncoder,Normalizer,NoFeaturePreprocessing | no embedding,ShapedMLPBackbone,FullyConnectedHead,nn.Sequential | 0.1 |
195-
| 4 | SimpleImputer,OneHotEncoder,StandardScaler,KernelPCA | no embedding,ShapedMLPBackbone,FullyConnectedHead,nn.Sequential | 0.08 |
196-
| 5 | SimpleImputer,OneHotEncoder,Normalizer,KitchenSink | no embedding,ShapedResNetBackbone,FullyConnectedHead,nn.Sequential | 0.08 |
197-
| 6 | SimpleImputer,OneHotEncoder,NoScaler,TruncSVD | no embedding,ShapedResNetBackbone,FullyConnectedHead,nn.Sequential | 0.08 |
198-
| 7 | SimpleImputer,NoEncoder,NoScaler,Nystroem | no embedding,ShapedMLPBackbone,FullyConnectedHead,nn.Sequential | 0.06 |
199-
| 8 | SimpleImputer,OneHotEncoder,MinMaxScaler,PolynomialFeatures | embedding,ResNetBackbone,FullyConnectedHead,nn.Sequential | 0.06 |
200-
| 9 | SimpleImputer,OneHotEncoder,StandardScaler,KernelPCA | no embedding,ShapedMLPBackbone,FullyConnectedHead,nn.Sequential | 0.04 |
201-
| 10 | SimpleImputer,NoEncoder,NoScaler,Nystroem | no embedding,ShapedMLPBackbone,FullyConnectedHead,nn.Sequential | 0.02 |
202-
| 11 | None | LGBMClassifier | 0.02 |
203-
| 12 | None | RFClassifier | 0.02 |
204-
| 13 | None | SVC | 0.02 |
205-
| 14 | SimpleImputer,OneHotEncoder,StandardScaler,NoFeaturePreprocessing | embedding,ShapedMLPBackbone,FullyConnectedHead,nn.Sequential | 0.02 |
206-
| 15 | SimpleImputer,OneHotEncoder,StandardScaler,NoFeaturePreprocessing | embedding,ShapedMLPBackbone,FullyConnectedHead,nn.Sequential | 0.02 |
158+
| 0 | SimpleImputer,OneHotEncoder,Normalizer,KitchenSink | no embedding,ShapedResNetBackbone,FullyConnectedHead,nn.Sequential | 0.42 |
159+
| 1 | SimpleImputer,OneHotEncoder,StandardScaler,KernelPCA | no embedding,ShapedMLPBackbone,FullyConnectedHead,nn.Sequential | 0.14 |
160+
| 2 | SimpleImputer,OneHotEncoder,StandardScaler,KernelPCA | no embedding,ShapedMLPBackbone,FullyConnectedHead,nn.Sequential | 0.14 |
161+
| 3 | None | KNNClassifier | 0.1 |
162+
| 4 | None | RFClassifier | 0.08 |
163+
| 5 | SimpleImputer,OneHotEncoder,Normalizer,NoFeaturePreprocessing | no embedding,ShapedMLPBackbone,FullyConnectedHead,nn.Sequential | 0.04 |
164+
| 6 | None | ExtraTreesClassifier | 0.04 |
165+
| 7 | SimpleImputer,OneHotEncoder,StandardScaler,KernelPCA | no embedding,ShapedMLPBackbone,FullyConnectedHead,nn.Sequential | 0.02 |
166+
| 8 | SimpleImputer,OneHotEncoder,StandardScaler,NoFeaturePreprocessing | embedding,ShapedMLPBackbone,FullyConnectedHead,nn.Sequential | 0.02 |
207167
208168
209169
@@ -295,7 +255,7 @@ with AutoPyTorch
295255
296256
.. rst-class:: sphx-glr-timing
297257

298-
**Total running time of the script:** ( 9 minutes 22.257 seconds)
258+
**Total running time of the script:** ( 9 minutes 10.157 seconds)
299259

300260

301261
.. _sphx_glr_download_examples_example_tabular_classification.py:

‎refactor_development/_sources/examples/example_tabular_regression.rst.txt

Lines changed: 5 additions & 37 deletions
Original file line numberDiff line numberDiff line change
@@ -36,7 +36,7 @@ with AutoPyTorch
3636

3737
.. code-block:: none
3838
39-
<smac.runhistory.runhistory.RunHistory object at 0x7ff7fa161700> [TrajEntry(train_perf=2147483648, incumbent_id=1, incumbent=Configuration:
39+
<smac.runhistory.runhistory.RunHistory object at 0x7f9827376ee0> [TrajEntry(train_perf=2147483648, incumbent_id=1, incumbent=Configuration:
4040
data_loader:batch_size, Value: 32
4141
encoder:__choice__, Value: 'NoEncoder'
4242
imputer:numerical_strategy, Value: 'mean'
@@ -65,7 +65,7 @@ with AutoPyTorch
6565
optimizer:__choice__, Value: 'AdamOptimizer'
6666
scaler:__choice__, Value: 'StandardScaler'
6767
trainer:__choice__, Value: 'StandardTrainer'
68-
, ta_runs=0, ta_time_used=0.0, wallclock_time=0.001894235610961914, budget=0), TrajEntry(train_perf=0.0033956446141917285, incumbent_id=1, incumbent=Configuration:
68+
, ta_runs=0, ta_time_used=0.0, wallclock_time=0.0018258094787597656, budget=0), TrajEntry(train_perf=0.022066190658357243, incumbent_id=1, incumbent=Configuration:
6969
data_loader:batch_size, Value: 32
7070
encoder:__choice__, Value: 'NoEncoder'
7171
imputer:numerical_strategy, Value: 'mean'
@@ -94,40 +94,8 @@ with AutoPyTorch
9494
optimizer:__choice__, Value: 'AdamOptimizer'
9595
scaler:__choice__, Value: 'StandardScaler'
9696
trainer:__choice__, Value: 'StandardTrainer'
97-
, ta_runs=1, ta_time_used=8.826370239257812, wallclock_time=12.347334861755371, budget=5.555555555555555), TrajEntry(train_perf=0.16943683190326564, incumbent_id=2, incumbent=Configuration:
98-
data_loader:batch_size, Value: 324
99-
encoder:__choice__, Value: 'NoEncoder'
100-
imputer:numerical_strategy, Value: 'median'
101-
lr_scheduler:CosineAnnealingLR:T_max, Value: 58
102-
lr_scheduler:__choice__, Value: 'CosineAnnealingLR'
103-
network_backbone:ShapedMLPBackbone:activation, Value: 'relu'
104-
network_backbone:ShapedMLPBackbone:max_dropout, Value: 0.08110946585949352
105-
network_backbone:ShapedMLPBackbone:max_units, Value: 77
106-
network_backbone:ShapedMLPBackbone:mlp_shape, Value: 'diamond'
107-
network_backbone:ShapedMLPBackbone:num_groups, Value: 12
108-
network_backbone:ShapedMLPBackbone:output_dim, Value: 383
109-
network_backbone:ShapedMLPBackbone:use_dropout, Value: True
110-
network_backbone:__choice__, Value: 'ShapedMLPBackbone'
111-
network_embedding:__choice__, Value: 'NoEmbedding'
112-
network_head:__choice__, Value: 'fully_connected'
113-
network_head:fully_connected:activation, Value: 'relu'
114-
network_head:fully_connected:num_layers, Value: 4
115-
network_head:fully_connected:units_layer_1, Value: 376
116-
network_head:fully_connected:units_layer_2, Value: 67
117-
network_head:fully_connected:units_layer_3, Value: 333
118-
network_init:KaimingInit:bias_strategy, Value: 'Zero'
119-
network_init:__choice__, Value: 'KaimingInit'
120-
optimizer:RMSpropOptimizer:alpha, Value: 0.3647734535713807
121-
optimizer:RMSpropOptimizer:lr, Value: 0.00037624565303773076
122-
optimizer:RMSpropOptimizer:momentum, Value: 0.9118730100154911
123-
optimizer:RMSpropOptimizer:weight_decay, Value: 0.039774901898577665
124-
optimizer:__choice__, Value: 'RMSpropOptimizer'
125-
scaler:Normalizer:norm, Value: 'mean_abs'
126-
scaler:__choice__, Value: 'Normalizer'
127-
trainer:MixUpTrainer:alpha, Value: 0.6330663830411708
128-
trainer:__choice__, Value: 'MixUpTrainer'
129-
, ta_runs=17, ta_time_used=394.7455403804779, wallclock_time=445.0417649745941, budget=50.0)]
130-
{'r2': 0.9992392159989721}
97+
, ta_runs=1, ta_time_used=7.395039081573486, wallclock_time=10.92704463005066, budget=5.555555555555555)]
98+
{'r2': 0.9995185033602313}
13199
132100
133101
@@ -250,7 +218,7 @@ with AutoPyTorch
250218
251219
.. rst-class:: sphx-glr-timing
252220

253-
**Total running time of the script:** ( 8 minutes 37.201 seconds)
221+
**Total running time of the script:** ( 8 minutes 34.410 seconds)
254222

255223

256224
.. _sphx_glr_download_examples_example_tabular_regression.py:

‎refactor_development/_sources/examples/sg_execution_times.rst.txt

Lines changed: 4 additions & 4 deletions
Original file line numberDiff line numberDiff line change
@@ -5,12 +5,12 @@
55

66
Computation times
77
=================
8-
**18:08.978** total execution time for **examples** files:
8+
**17:54.478** total execution time for **examples** files:
99

1010
+----------------------------------------------------------------------------------------------------+-----------+--------+
11-
| :ref:`sphx_glr_examples_example_tabular_classification.py` (``example_tabular_classification.py``) | 09:22.257 | 0.0 MB |
11+
| :ref:`sphx_glr_examples_example_tabular_classification.py` (``example_tabular_classification.py``) | 09:10.157 | 0.0 MB |
1212
+----------------------------------------------------------------------------------------------------+-----------+--------+
13-
| :ref:`sphx_glr_examples_example_tabular_regression.py` (``example_tabular_regression.py``) | 08:37.201 | 0.0 MB |
13+
| :ref:`sphx_glr_examples_example_tabular_regression.py` (``example_tabular_regression.py``) | 08:34.410 | 0.0 MB |
1414
+----------------------------------------------------------------------------------------------------+-----------+--------+
15-
| :ref:`sphx_glr_examples_example_image_classification.py` (``example_image_classification.py``) | 00:09.520 | 0.0 MB |
15+
| :ref:`sphx_glr_examples_example_image_classification.py` (``example_image_classification.py``) | 00:09.911 | 0.0 MB |
1616
+----------------------------------------------------------------------------------------------------+-----------+--------+

‎refactor_development/examples/example_image_classification.html

Lines changed: 3 additions & 4 deletions
Original file line numberDiff line numberDiff line change
@@ -30326,12 +30326,11 @@
3032630326
________________________________________
3032730327
Configuration:
3032830328
image_augmenter:GaussianBlur:use_augmenter, Value: False
30329-
image_augmenter:GaussianNoise:sigma_offset, Value: 0.5614286279360542
30330-
image_augmenter:GaussianNoise:use_augmenter, Value: True
30329+
image_augmenter:GaussianNoise:use_augmenter, Value: False
3033130330
image_augmenter:RandomAffine:use_augmenter, Value: False
3033230331
image_augmenter:RandomCutout:use_augmenter, Value: False
3033330332
image_augmenter:Resize:use_augmenter, Value: True
30334-
image_augmenter:ZeroPadAndCrop:percent, Value: 0.2076158247310454
30333+
image_augmenter:ZeroPadAndCrop:percent, Value: 0.208578408262465
3033530334
normalizer:__choice__, Value: &#39;NoNormalizer&#39;
3033630335

3033730336
Fitting the pipeline...
@@ -30404,7 +30403,7 @@
3040430403
<span class="nb">print</span><span class="p">(</span><span class="n">pipeline</span><span class="p">)</span>
3040530404
</pre></div>
3040630405
</div>
30407-
<p class="sphx-glr-timing"><strong>Total running time of the script:</strong> ( 0 minutes 9.520 seconds)</p>
30406+
<p class="sphx-glr-timing"><strong>Total running time of the script:</strong> ( 0 minutes 9.911 seconds)</p>
3040830407
<div class="sphx-glr-footer class sphx-glr-footer-example docutils container" id="sphx-glr-download-examples-example-image-classification-py">
3040930408
<div class="binder-badge docutils container">
3041030409
<a class="reference external image-reference" href="https://mybinder.org/v2/gh/automl/Auto-PyTorch/refactor_development?urlpath=lab/tree/notebooks/examples/example_image_classification.ipynb"><img alt="Launch binder" src="../_images/binder_badge_logo.svg" width="150px" /></a>

0 commit comments

Comments
 (0)