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from autoPyTorch .data .tabular_validator import TabularInputValidator
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from autoPyTorch .datasets .base_dataset import BaseDatasetPropertiesType
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from autoPyTorch .datasets .resampling_strategy import (
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- CrossValTypes ,
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HoldoutValTypes ,
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ResamplingStrategies ,
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)
Original file line number Diff line number Diff line change 13
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from autoPyTorch .data .tabular_validator import TabularInputValidator
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from autoPyTorch .datasets .base_dataset import BaseDatasetPropertiesType
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from autoPyTorch .datasets .resampling_strategy import (
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- CrossValTypes ,
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HoldoutValTypes ,
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ResamplingStrategies ,
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)
Original file line number Diff line number Diff line change @@ -277,7 +277,7 @@ def transform(
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if len (self .categorical_columns ) > 0 :
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if self .column_transformer is None :
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raise AttributeError ("Expect column transformer to be built"
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- "if there are categorical columns" )
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+ "if there are categorical columns" )
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categorical_columns = self .column_transformer .transformers_ [0 ][- 1 ]
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for column in categorical_columns :
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if X [column ].isna ().all ():
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