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from ..utils .extmath import row_norms
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from ..utils .extmath import _incremental_mean_and_var
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from ..utils .fixes import combinations_with_replacement as combinations_w_r
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+ from ..utils .fixes import bincount
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from ..utils .sparsefuncs_fast import (inplace_csr_row_normalize_l1 ,
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inplace_csr_row_normalize_l2 )
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from ..utils .sparsefuncs import (inplace_column_scale ,
@@ -1179,7 +1180,7 @@ def powers_(self):
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combinations = self ._combinations (self .n_input_features_ , self .degree ,
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self .interaction_only ,
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self .include_bias )
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- return np .vstack (np . bincount (c , minlength = self .n_input_features_ )
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+ return np .vstack (bincount (c , minlength = self .n_input_features_ )
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for c in combinations )
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def get_feature_names (self , input_features = None ):
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