Further fixes

Author: franchuterivera

autoPyTorch/configs/greedy_portfolio.json

@@ -1,5 +1,6 @@
 [{"data_loader:batch_size": 60,
  "encoder:__choice__": "OneHotEncoder",
+ "coalescer:__choice__": "NoCoalescer",
  "feature_preprocessor:__choice__": "NoFeaturePreprocessor",
  "imputer:categorical_strategy": "most_frequent",
  "imputer:numerical_strategy": "mean",
@@ -506,4 +507,4 @@
  "network_backbone:ShapedResNetBackbone:max_shake_drop_probability": 0.034431265307095615,
  "network_head:fully_connected:activation": "relu",
  "network_head:fully_connected:units_layer_1": 128,
- "network_backbone:ShapedResNetBackbone:max_dropout": 0.6296079567189131}]
+ "network_backbone:ShapedResNetBackbone:max_dropout": 0.6296079567189131}]

autoPyTorch/pipeline/components/preprocessing/tabular_preprocessing/coalescer/__init__.py

@@ -112,8 +112,10 @@ def get_hyperparameter_search_space(self,
         # add only child hyperparameters of early_preprocessor choices
         for name in preprocessor.choices:
             updates = self._get_search_space_updates(prefix=name)
+            # Call arg is ignored on mypy as the search space dynamically
+            # provides different args
             preprocessor_configuration_space = available_preprocessors[name].\
-                get_hyperparameter_search_space(dataset_properties,
+                get_hyperparameter_search_space(dataset_properties,  # type:ignore[call-arg]
                                                 **updates)
             parent_hyperparameter = {'parent': preprocessor, 'value': name}
             cs.add_configuration_space(name, preprocessor_configuration_space,

test/test_api/.tmp_api/runhistory.json

@@ -705,6 +705,7 @@
     "1": {
       "data_loader:batch_size": 64,
       "encoder:__choice__": "NoEncoder",
+      "coalescer:__choice__": "NoCoalescer",
       "feature_preprocessor:__choice__": "NoFeaturePreprocessor",
       "imputer:numerical_strategy": "mean",
       "lr_scheduler:__choice__": "ReduceLROnPlateau",
@@ -737,6 +738,7 @@
     "2": {
       "data_loader:batch_size": 101,
       "encoder:__choice__": "NoEncoder",
+      "coalescer:__choice__": "NoCoalescer",
       "feature_preprocessor:__choice__": "PowerTransformer",
       "imputer:numerical_strategy": "most_frequent",
       "lr_scheduler:__choice__": "CyclicLR",
@@ -801,6 +803,7 @@
     "3": {
       "data_loader:batch_size": 242,
       "encoder:__choice__": "NoEncoder",
+      "coalescer:__choice__": "NoCoalescer",
       "feature_preprocessor:__choice__": "RandomKitchenSinks",
       "imputer:numerical_strategy": "median",
       "lr_scheduler:__choice__": "NoScheduler",
@@ -831,6 +834,7 @@
     "4": {
       "data_loader:batch_size": 115,
       "encoder:__choice__": "NoEncoder",
+      "coalescer:__choice__": "NoCoalescer",
       "feature_preprocessor:__choice__": "Nystroem",
       "imputer:numerical_strategy": "median",
       "lr_scheduler:__choice__": "CosineAnnealingLR",
@@ -864,6 +868,7 @@
     "5": {
       "data_loader:batch_size": 185,
       "encoder:__choice__": "NoEncoder",
+      "coalescer:__choice__": "NoCoalescer",
       "feature_preprocessor:__choice__": "RandomKitchenSinks",
       "imputer:numerical_strategy": "median",
       "lr_scheduler:__choice__": "ReduceLROnPlateau",
@@ -904,6 +909,7 @@
     "6": {
       "data_loader:batch_size": 95,
       "encoder:__choice__": "NoEncoder",
+      "coalescer:__choice__": "NoCoalescer",
       "feature_preprocessor:__choice__": "RandomKitchenSinks",
       "imputer:numerical_strategy": "most_frequent",
       "lr_scheduler:__choice__": "ExponentialLR",
@@ -937,6 +943,7 @@
     "7": {
       "data_loader:batch_size": 119,
       "encoder:__choice__": "NoEncoder",
+      "coalescer:__choice__": "NoCoalescer",
       "feature_preprocessor:__choice__": "Nystroem",
       "imputer:numerical_strategy": "mean",
       "lr_scheduler:__choice__": "StepLR",
@@ -979,6 +986,7 @@
     "8": {
       "data_loader:batch_size": 130,
       "encoder:__choice__": "NoEncoder",
+      "coalescer:__choice__": "NoCoalescer",
       "feature_preprocessor:__choice__": "PolynomialFeatures",
       "imputer:numerical_strategy": "median",
       "lr_scheduler:__choice__": "CyclicLR",
@@ -1032,6 +1040,7 @@
     "9": {
       "data_loader:batch_size": 137,
       "encoder:__choice__": "NoEncoder",
+      "coalescer:__choice__": "NoCoalescer",
       "feature_preprocessor:__choice__": "Nystroem",
       "imputer:numerical_strategy": "mean",
       "lr_scheduler:__choice__": "CosineAnnealingLR",
@@ -1077,4 +1086,4 @@
       "network_head:fully_connected:units_layer_1": 294
     }
   }
-}
+}