text: -- This SQL code was generated by sklearn2sql (development version).
  -- Copyright 2018
  
  -- Model : KerasClassifier_GRU
  -- Dataset : FourClass_100
  -- Database : sqlite
  
  
  -- This SQL code can contain one or more statements, to be executed in the order they appear in this file.
  
  
  
  -- Model deployment code
  
  WITH RECURSIVE keras_input AS 
  (SELECT "ADS"."KEY" AS "KEY", "ADS"."Feature_0" AS "Feature_0", "ADS"."Feature_1" AS "Feature_1", "ADS"."Feature_2" AS "Feature_2", "ADS"."Feature_3" AS "Feature_3", "ADS"."Feature_4" AS "Feature_4", "ADS"."Feature_5" AS "Feature_5", "ADS"."Feature_6" AS "Feature_6", "ADS"."Feature_7" AS "Feature_7", "ADS"."Feature_8" AS "Feature_8", "ADS"."Feature_9" AS "Feature_9", "ADS"."Feature_10" AS "Feature_10", "ADS"."Feature_11" AS "Feature_11", "ADS"."Feature_12" AS "Feature_12", "ADS"."Feature_13" AS "Feature_13", "ADS"."Feature_14" AS "Feature_14", "ADS"."Feature_15" AS "Feature_15", "ADS"."Feature_16" AS "Feature_16", "ADS"."Feature_17" AS "Feature_17", "ADS"."Feature_18" AS "Feature_18", "ADS"."Feature_19" AS "Feature_19", "ADS"."Feature_20" AS "Feature_20", "ADS"."Feature_21" AS "Feature_21", "ADS"."Feature_22" AS "Feature_22", "ADS"."Feature_23" AS "Feature_23", "ADS"."Feature_24" AS "Feature_24", "ADS"."Feature_25" AS "Feature_25", "ADS"."Feature_26" AS "Feature_26", "ADS"."Feature_27" AS "Feature_27", "ADS"."Feature_28" AS "Feature_28", "ADS"."Feature_29" AS "Feature_29", "ADS"."Feature_30" AS "Feature_30", "ADS"."Feature_31" AS "Feature_31", "ADS"."Feature_32" AS "Feature_32", "ADS"."Feature_33" AS "Feature_33", "ADS"."Feature_34" AS "Feature_34", "ADS"."Feature_35" AS "Feature_35", "ADS"."Feature_36" AS "Feature_36", "ADS"."Feature_37" AS "Feature_37", "ADS"."Feature_38" AS "Feature_38", "ADS"."Feature_39" AS "Feature_39", "ADS"."Feature_40" AS "Feature_40", "ADS"."Feature_41" AS "Feature_41", "ADS"."Feature_42" AS "Feature_42", "ADS"."Feature_43" AS "Feature_43", "ADS"."Feature_44" AS "Feature_44", "ADS"."Feature_45" AS "Feature_45", "ADS"."Feature_46" AS "Feature_46", "ADS"."Feature_47" AS "Feature_47", "ADS"."Feature_48" AS "Feature_48", "ADS"."Feature_49" AS "Feature_49", "ADS"."Feature_50" AS "Feature_50", "ADS"."Feature_51" AS "Feature_51", "ADS"."Feature_52" AS "Feature_52", "ADS"."Feature_53" AS "Feature_53", "ADS"."Feature_54" AS "Feature_54", "ADS"."Feature_55" AS "Feature_55", "ADS"."Feature_56" AS "Feature_56", "ADS"."Feature_57" AS "Feature_57", "ADS"."Feature_58" AS "Feature_58", "ADS"."Feature_59" AS "Feature_59", "ADS"."Feature_60" AS "Feature_60", "ADS"."Feature_61" AS "Feature_61", "ADS"."Feature_62" AS "Feature_62", "ADS"."Feature_63" AS "Feature_63", "ADS"."Feature_64" AS "Feature_64", "ADS"."Feature_65" AS "Feature_65", "ADS"."Feature_66" AS "Feature_66", "ADS"."Feature_67" AS "Feature_67", "ADS"."Feature_68" AS "Feature_68", "ADS"."Feature_69" AS "Feature_69", "ADS"."Feature_70" AS "Feature_70", "ADS"."Feature_71" AS "Feature_71", "ADS"."Feature_72" AS "Feature_72", "ADS"."Feature_73" AS "Feature_73", "ADS"."Feature_74" AS "Feature_74", "ADS"."Feature_75" AS "Feature_75", "ADS"."Feature_76" AS "Feature_76", "ADS"."Feature_77" AS "Feature_77", "ADS"."Feature_78" AS "Feature_78", "ADS"."Feature_79" AS "Feature_79", "ADS"."Feature_80" AS "Feature_80", "ADS"."Feature_81" AS "Feature_81", "ADS"."Feature_82" AS "Feature_82", "ADS"."Feature_83" AS "Feature_83", "ADS"."Feature_84" AS "Feature_84", "ADS"."Feature_85" AS "Feature_85", "ADS"."Feature_86" AS "Feature_86", "ADS"."Feature_87" AS "Feature_87", "ADS"."Feature_88" AS "Feature_88", "ADS"."Feature_89" AS "Feature_89", "ADS"."Feature_90" AS "Feature_90", "ADS"."Feature_91" AS "Feature_91", "ADS"."Feature_92" AS "Feature_92", "ADS"."Feature_93" AS "Feature_93", "ADS"."Feature_94" AS "Feature_94", "ADS"."Feature_95" AS "Feature_95", "ADS"."Feature_96" AS "Feature_96", "ADS"."Feature_97" AS "Feature_97", "ADS"."Feature_98" AS "Feature_98", "ADS"."Feature_99" AS "Feature_99" 
  FROM "FourClass_100" AS "ADS"), 
  keras_input_1 AS 
  (SELECT keras_input."KEY" AS "KEY", keras_input."Feature_0" AS "Feature_0", keras_input."Feature_1" AS "Feature_1", keras_input."Feature_2" AS "Feature_2", keras_input."Feature_3" AS "Feature_3", keras_input."Feature_4" AS "Feature_4", keras_input."Feature_5" AS "Feature_5", keras_input."Feature_6" AS "Feature_6", keras_input."Feature_7" AS "Feature_7", keras_input."Feature_8" AS "Feature_8", keras_input."Feature_9" AS "Feature_9", keras_input."Feature_10" AS "Feature_10", keras_input."Feature_11" AS "Feature_11", keras_input."Feature_12" AS "Feature_12", keras_input."Feature_13" AS "Feature_13", keras_input."Feature_14" AS "Feature_14", keras_input."Feature_15" AS "Feature_15", keras_input."Feature_16" AS "Feature_16", keras_input."Feature_17" AS "Feature_17", keras_input."Feature_18" AS "Feature_18", keras_input."Feature_19" AS "Feature_19", keras_input."Feature_20" AS "Feature_20", keras_input."Feature_21" AS "Feature_21", keras_input."Feature_22" AS "Feature_22", keras_input."Feature_23" AS "Feature_23", keras_input."Feature_24" AS "Feature_24", keras_input."Feature_25" AS "Feature_25", keras_input."Feature_26" AS "Feature_26", keras_input."Feature_27" AS "Feature_27", keras_input."Feature_28" AS "Feature_28", keras_input."Feature_29" AS "Feature_29", keras_input."Feature_30" AS "Feature_30", keras_input."Feature_31" AS "Feature_31", keras_input."Feature_32" AS "Feature_32", keras_input."Feature_33" AS "Feature_33", keras_input."Feature_34" AS "Feature_34", keras_input."Feature_35" AS "Feature_35", keras_input."Feature_36" AS "Feature_36", keras_input."Feature_37" AS "Feature_37", keras_input."Feature_38" AS "Feature_38", keras_input."Feature_39" AS "Feature_39", keras_input."Feature_40" AS "Feature_40", keras_input."Feature_41" AS "Feature_41", keras_input."Feature_42" AS "Feature_42", keras_input."Feature_43" AS "Feature_43", keras_input."Feature_44" AS "Feature_44", keras_input."Feature_45" AS "Feature_45", keras_input."Feature_46" AS "Feature_46", keras_input."Feature_47" AS "Feature_47", keras_input."Feature_48" AS "Feature_48", keras_input."Feature_49" AS "Feature_49", keras_input."Feature_50" AS "Feature_50", keras_input."Feature_51" AS "Feature_51", keras_input."Feature_52" AS "Feature_52", keras_input."Feature_53" AS "Feature_53", keras_input."Feature_54" AS "Feature_54", keras_input."Feature_55" AS "Feature_55", keras_input."Feature_56" AS "Feature_56", keras_input."Feature_57" AS "Feature_57", keras_input."Feature_58" AS "Feature_58", keras_input."Feature_59" AS "Feature_59", keras_input."Feature_60" AS "Feature_60", keras_input."Feature_61" AS "Feature_61", keras_input."Feature_62" AS "Feature_62", keras_input."Feature_63" AS "Feature_63", keras_input."Feature_64" AS "Feature_64", keras_input."Feature_65" AS "Feature_65", keras_input."Feature_66" AS "Feature_66", keras_input."Feature_67" AS "Feature_67", keras_input."Feature_68" AS "Feature_68", keras_input."Feature_69" AS "Feature_69", keras_input."Feature_70" AS "Feature_70", keras_input."Feature_71" AS "Feature_71", keras_input."Feature_72" AS "Feature_72", keras_input."Feature_73" AS "Feature_73", keras_input."Feature_74" AS "Feature_74", keras_input."Feature_75" AS "Feature_75", keras_input."Feature_76" AS "Feature_76", keras_input."Feature_77" AS "Feature_77", keras_input."Feature_78" AS "Feature_78", keras_input."Feature_79" AS "Feature_79", keras_input."Feature_80" AS "Feature_80", keras_input."Feature_81" AS "Feature_81", keras_input."Feature_82" AS "Feature_82", keras_input."Feature_83" AS "Feature_83", keras_input."Feature_84" AS "Feature_84", keras_input."Feature_85" AS "Feature_85", keras_input."Feature_86" AS "Feature_86", keras_input."Feature_87" AS "Feature_87", keras_input."Feature_88" AS "Feature_88", keras_input."Feature_89" AS "Feature_89", keras_input."Feature_90" AS "Feature_90", keras_input."Feature_91" AS "Feature_91", keras_input."Feature_92" AS "Feature_92", keras_input."Feature_93" AS "Feature_93", keras_input."Feature_94" AS "Feature_94", keras_input."Feature_95" AS "Feature_95", keras_input."Feature_96" AS "Feature_96", keras_input."Feature_97" AS "Feature_97", keras_input."Feature_98" AS "Feature_98", keras_input."Feature_99" AS "Feature_99" 
  FROM keras_input), 
  keras_input_1_rn AS 
  (SELECT (SELECT count(t."KEY") AS count_1 
  FROM (SELECT keras_input_1."KEY" AS "KEY" 
  FROM keras_input_1) AS t 
  WHERE t."KEY" <= keras_input_1."KEY") AS rn, keras_input_1."KEY" AS "KEY", keras_input_1."Feature_0" AS "Feature_0", keras_input_1."Feature_1" AS "Feature_1", keras_input_1."Feature_2" AS "Feature_2", keras_input_1."Feature_3" AS "Feature_3", keras_input_1."Feature_4" AS "Feature_4", keras_input_1."Feature_5" AS "Feature_5", keras_input_1."Feature_6" AS "Feature_6", keras_input_1."Feature_7" AS "Feature_7", keras_input_1."Feature_8" AS "Feature_8", keras_input_1."Feature_9" AS "Feature_9", keras_input_1."Feature_10" AS "Feature_10", keras_input_1."Feature_11" AS "Feature_11", keras_input_1."Feature_12" AS "Feature_12", keras_input_1."Feature_13" AS "Feature_13", keras_input_1."Feature_14" AS "Feature_14", keras_input_1."Feature_15" AS "Feature_15", keras_input_1."Feature_16" AS "Feature_16", keras_input_1."Feature_17" AS "Feature_17", keras_input_1."Feature_18" AS "Feature_18", keras_input_1."Feature_19" AS "Feature_19", keras_input_1."Feature_20" AS "Feature_20", keras_input_1."Feature_21" AS "Feature_21", keras_input_1."Feature_22" AS "Feature_22", keras_input_1."Feature_23" AS "Feature_23", keras_input_1."Feature_24" AS "Feature_24", keras_input_1."Feature_25" AS "Feature_25", keras_input_1."Feature_26" AS "Feature_26", keras_input_1."Feature_27" AS "Feature_27", keras_input_1."Feature_28" AS "Feature_28", keras_input_1."Feature_29" AS "Feature_29", keras_input_1."Feature_30" AS "Feature_30", keras_input_1."Feature_31" AS "Feature_31", keras_input_1."Feature_32" AS "Feature_32", keras_input_1."Feature_33" AS "Feature_33", keras_input_1."Feature_34" AS "Feature_34", keras_input_1."Feature_35" AS "Feature_35", keras_input_1."Feature_36" AS "Feature_36", keras_input_1."Feature_37" AS "Feature_37", keras_input_1."Feature_38" AS "Feature_38", keras_input_1."Feature_39" AS "Feature_39", keras_input_1."Feature_40" AS "Feature_40", keras_input_1."Feature_41" AS "Feature_41", keras_input_1."Feature_42" AS "Feature_42", keras_input_1."Feature_43" AS "Feature_43", keras_input_1."Feature_44" AS "Feature_44", keras_input_1."Feature_45" AS "Feature_45", keras_input_1."Feature_46" AS "Feature_46", keras_input_1."Feature_47" AS "Feature_47", keras_input_1."Feature_48" AS "Feature_48", keras_input_1."Feature_49" AS "Feature_49", keras_input_1."Feature_50" AS "Feature_50", keras_input_1."Feature_51" AS "Feature_51", keras_input_1."Feature_52" AS "Feature_52", keras_input_1."Feature_53" AS "Feature_53", keras_input_1."Feature_54" AS "Feature_54", keras_input_1."Feature_55" AS "Feature_55", keras_input_1."Feature_56" AS "Feature_56", keras_input_1."Feature_57" AS "Feature_57", keras_input_1."Feature_58" AS "Feature_58", keras_input_1."Feature_59" AS "Feature_59", keras_input_1."Feature_60" AS "Feature_60", keras_input_1."Feature_61" AS "Feature_61", keras_input_1."Feature_62" AS "Feature_62", keras_input_1."Feature_63" AS "Feature_63", keras_input_1."Feature_64" AS "Feature_64", keras_input_1."Feature_65" AS "Feature_65", keras_input_1."Feature_66" AS "Feature_66", keras_input_1."Feature_67" AS "Feature_67", keras_input_1."Feature_68" AS "Feature_68", keras_input_1."Feature_69" AS "Feature_69", keras_input_1."Feature_70" AS "Feature_70", keras_input_1."Feature_71" AS "Feature_71", keras_input_1."Feature_72" AS "Feature_72", keras_input_1."Feature_73" AS "Feature_73", keras_input_1."Feature_74" AS "Feature_74", keras_input_1."Feature_75" AS "Feature_75", keras_input_1."Feature_76" AS "Feature_76", keras_input_1."Feature_77" AS "Feature_77", keras_input_1."Feature_78" AS "Feature_78", keras_input_1."Feature_79" AS "Feature_79", keras_input_1."Feature_80" AS "Feature_80", keras_input_1."Feature_81" AS "Feature_81", keras_input_1."Feature_82" AS "Feature_82", keras_input_1."Feature_83" AS "Feature_83", keras_input_1."Feature_84" AS "Feature_84", keras_input_1."Feature_85" AS "Feature_85", keras_input_1."Feature_86" AS "Feature_86", keras_input_1."Feature_87" AS "Feature_87", keras_input_1."Feature_88" AS "Feature_88", keras_input_1."Feature_89" AS "Feature_89", keras_input_1."Feature_90" AS "Feature_90", keras_input_1."Feature_91" AS "Feature_91", keras_input_1."Feature_92" AS "Feature_92", keras_input_1."Feature_93" AS "Feature_93", keras_input_1."Feature_94" AS "Feature_94", keras_input_1."Feature_95" AS "Feature_95", keras_input_1."Feature_96" AS "Feature_96", keras_input_1."Feature_97" AS "Feature_97", keras_input_1."Feature_98" AS "Feature_98", keras_input_1."Feature_99" AS "Feature_99" 
  FROM keras_input_1), 
  gru_input_kernel_bias AS 
  (SELECT keras_input_1_rn.rn AS rn, keras_input_1_rn."KEY" AS "KEY", keras_input_1_rn."Feature_0" AS "Feature_0", keras_input_1_rn."Feature_1" AS "Feature_1", keras_input_1_rn."Feature_2" AS "Feature_2", keras_input_1_rn."Feature_3" AS "Feature_3", keras_input_1_rn."Feature_4" AS "Feature_4", keras_input_1_rn."Feature_5" AS "Feature_5", keras_input_1_rn."Feature_6" AS "Feature_6", keras_input_1_rn."Feature_7" AS "Feature_7", keras_input_1_rn."Feature_8" AS "Feature_8", keras_input_1_rn."Feature_9" AS "Feature_9", keras_input_1_rn."Feature_10" AS "Feature_10", keras_input_1_rn."Feature_11" AS "Feature_11", keras_input_1_rn."Feature_12" AS "Feature_12", keras_input_1_rn."Feature_13" AS "Feature_13", keras_input_1_rn."Feature_14" AS "Feature_14", keras_input_1_rn."Feature_15" AS "Feature_15", keras_input_1_rn."Feature_16" AS "Feature_16", keras_input_1_rn."Feature_17" AS "Feature_17", keras_input_1_rn."Feature_18" AS "Feature_18", keras_input_1_rn."Feature_19" AS "Feature_19", keras_input_1_rn."Feature_20" AS "Feature_20", keras_input_1_rn."Feature_21" AS "Feature_21", keras_input_1_rn."Feature_22" AS "Feature_22", keras_input_1_rn."Feature_23" AS "Feature_23", keras_input_1_rn."Feature_24" AS "Feature_24", keras_input_1_rn."Feature_25" AS "Feature_25", keras_input_1_rn."Feature_26" AS "Feature_26", keras_input_1_rn."Feature_27" AS "Feature_27", keras_input_1_rn."Feature_28" AS "Feature_28", keras_input_1_rn."Feature_29" AS "Feature_29", keras_input_1_rn."Feature_30" AS "Feature_30", keras_input_1_rn."Feature_31" AS "Feature_31", keras_input_1_rn."Feature_32" AS "Feature_32", keras_input_1_rn."Feature_33" AS "Feature_33", keras_input_1_rn."Feature_34" AS "Feature_34", keras_input_1_rn."Feature_35" AS "Feature_35", keras_input_1_rn."Feature_36" AS "Feature_36", keras_input_1_rn."Feature_37" AS "Feature_37", keras_input_1_rn."Feature_38" AS "Feature_38", keras_input_1_rn."Feature_39" AS "Feature_39", keras_input_1_rn."Feature_40" AS "Feature_40", keras_input_1_rn."Feature_41" AS "Feature_41", keras_input_1_rn."Feature_42" AS "Feature_42", keras_input_1_rn."Feature_43" AS "Feature_43", keras_input_1_rn."Feature_44" AS "Feature_44", keras_input_1_rn."Feature_45" AS "Feature_45", keras_input_1_rn."Feature_46" AS "Feature_46", keras_input_1_rn."Feature_47" AS "Feature_47", keras_input_1_rn."Feature_48" AS "Feature_48", keras_input_1_rn."Feature_49" AS "Feature_49", keras_input_1_rn."Feature_50" AS "Feature_50", keras_input_1_rn."Feature_51" AS "Feature_51", keras_input_1_rn."Feature_52" AS "Feature_52", keras_input_1_rn."Feature_53" AS "Feature_53", keras_input_1_rn."Feature_54" AS "Feature_54", keras_input_1_rn."Feature_55" AS "Feature_55", keras_input_1_rn."Feature_56" AS "Feature_56", keras_input_1_rn."Feature_57" AS "Feature_57", keras_input_1_rn."Feature_58" AS "Feature_58", keras_input_1_rn."Feature_59" AS "Feature_59", keras_input_1_rn."Feature_60" AS "Feature_60", keras_input_1_rn."Feature_61" AS "Feature_61", keras_input_1_rn."Feature_62" AS "Feature_62", keras_input_1_rn."Feature_63" AS "Feature_63", keras_input_1_rn."Feature_64" AS "Feature_64", keras_input_1_rn."Feature_65" AS "Feature_65", keras_input_1_rn."Feature_66" AS "Feature_66", keras_input_1_rn."Feature_67" AS "Feature_67", keras_input_1_rn."Feature_68" AS "Feature_68", keras_input_1_rn."Feature_69" AS "Feature_69", keras_input_1_rn."Feature_70" AS "Feature_70", keras_input_1_rn."Feature_71" AS "Feature_71", keras_input_1_rn."Feature_72" AS "Feature_72", keras_input_1_rn."Feature_73" AS "Feature_73", keras_input_1_rn."Feature_74" AS "Feature_74", keras_input_1_rn."Feature_75" AS "Feature_75", keras_input_1_rn."Feature_76" AS "Feature_76", keras_input_1_rn."Feature_77" AS "Feature_77", keras_input_1_rn."Feature_78" AS "Feature_78", keras_input_1_rn."Feature_79" AS "Feature_79", keras_input_1_rn."Feature_80" AS "Feature_80", keras_input_1_rn."Feature_81" AS "Feature_81", keras_input_1_rn."Feature_82" AS "Feature_82", keras_input_1_rn."Feature_83" AS "Feature_83", keras_input_1_rn."Feature_84" AS "Feature_84", keras_input_1_rn."Feature_85" AS "Feature_85", keras_input_1_rn."Feature_86" AS "Feature_86", keras_input_1_rn."Feature_87" AS "Feature_87", keras_input_1_rn."Feature_88" AS "Feature_88", keras_input_1_rn."Feature_89" AS "Feature_89", keras_input_1_rn."Feature_90" AS "Feature_90", keras_input_1_rn."Feature_91" AS "Feature_91", keras_input_1_rn."Feature_92" AS "Feature_92", keras_input_1_rn."Feature_93" AS "Feature_93", keras_input_1_rn."Feature_94" AS "Feature_94", keras_input_1_rn."Feature_95" AS "Feature_95", keras_input_1_rn."Feature_96" AS "Feature_96", keras_input_1_rn."Feature_97" AS "Feature_97", keras_input_1_rn."Feature_98" AS "Feature_98", keras_input_1_rn."Feature_99" AS "Feature_99", 0.02641161712828919 + -0.027108022717210023 * keras_input_1_rn."Feature_0" + 0.02931641698182654 * keras_input_1_rn."Feature_1" + 0.03239199479855417 * keras_input_1_rn."Feature_2" + -0.0763546165234123 * keras_input_1_rn."Feature_3" + 0.04903499107558589 * keras_input_1_rn."Feature_4" + 0.12601806616796524 * keras_input_1_rn."Feature_5" + -0.1011031266732298 * keras_input_1_rn."Feature_6" + 0.07475839276637736 * keras_input_1_rn."Feature_7" + 0.13225338926682548 * keras_input_1_rn."Feature_8" + -0.06033593431438634 * keras_input_1_rn."Feature_9" + -0.2786668336564693 * keras_input_1_rn."Feature_10" + -0.05169021934693588 * keras_input_1_rn."Feature_11" + -0.1327450295717865 * keras_input_1_rn."Feature_12" + -0.06547098664381244 * keras_input_1_rn."Feature_13" + 0.11054345918478761 * keras_input_1_rn."Feature_14" + -0.003942704572355762 * keras_input_1_rn."Feature_15" + 0.021640659562507457 * keras_input_1_rn."Feature_16" + -0.006330337530789962 * keras_input_1_rn."Feature_17" + 0.09610354815147025 * keras_input_1_rn."Feature_18" + 0.26097627311519983 * keras_input_1_rn."Feature_19" + 0.10159495234958196 * keras_input_1_rn."Feature_20" + -0.055907523910115844 * 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keras_input_1_rn."Feature_46" + -0.18328737508991172 * keras_input_1_rn."Feature_47" + 0.10569890816792593 * keras_input_1_rn."Feature_48" + -0.0366858725792506 * keras_input_1_rn."Feature_49" + 0.051039123635226225 * keras_input_1_rn."Feature_50" + 0.13507158351194254 * keras_input_1_rn."Feature_51" + -0.23090813050645537 * keras_input_1_rn."Feature_52" + 0.07494513563045851 * keras_input_1_rn."Feature_53" + -0.0317482072692839 * keras_input_1_rn."Feature_54" + -0.23215000026422394 * keras_input_1_rn."Feature_55" + 0.18612864849625727 * keras_input_1_rn."Feature_56" + -0.2111500413921007 * keras_input_1_rn."Feature_57" + -0.1386522042894877 * keras_input_1_rn."Feature_58" + 0.056358621109458606 * keras_input_1_rn."Feature_59" + 0.04574701255537611 * keras_input_1_rn."Feature_60" + 0.21233503781269708 * keras_input_1_rn."Feature_61" + -0.08793320185639195 * keras_input_1_rn."Feature_62" + 0.18087271295728286 * keras_input_1_rn."Feature_63" + 0.03598740836283626 * keras_input_1_rn."Feature_64" + 0.1730745582948795 * keras_input_1_rn."Feature_65" + -0.17464681060441467 * keras_input_1_rn."Feature_66" + 0.09698435614607026 * keras_input_1_rn."Feature_67" + 0.02481922033690398 * keras_input_1_rn."Feature_68" + 0.07780682246915405 * keras_input_1_rn."Feature_69" + 0.09495956995440435 * keras_input_1_rn."Feature_70" + -0.2203053918624035 * keras_input_1_rn."Feature_71" + -0.061913265034715004 * keras_input_1_rn."Feature_72" + -0.2036786865573968 * keras_input_1_rn."Feature_73" + -0.10447599973630711 * keras_input_1_rn."Feature_74" + 0.031578990376853355 * keras_input_1_rn."Feature_75" + 0.0672700047121525 * keras_input_1_rn."Feature_76" + -0.17983482645808885 * keras_input_1_rn."Feature_77" + -0.15218303256756205 * keras_input_1_rn."Feature_78" + 0.2360469637384438 * keras_input_1_rn."Feature_79" + 0.13223451291526012 * keras_input_1_rn."Feature_80" + -0.1930124548936734 * keras_input_1_rn."Feature_81" + -0.14925512746275887 * keras_input_1_rn."Feature_82" + 0.013378467987228804 * keras_input_1_rn."Feature_83" + 0.11295835310140018 * keras_input_1_rn."Feature_84" + 0.06739467886852918 * keras_input_1_rn."Feature_85" + 0.09323417895551478 * keras_input_1_rn."Feature_86" + -0.11172764563491022 * keras_input_1_rn."Feature_87" + 0.10468732350310922 * keras_input_1_rn."Feature_88" + 0.04684004984530482 * keras_input_1_rn."Feature_89" + 0.12010431484398792 * keras_input_1_rn."Feature_90" + 0.03562432457347653 * keras_input_1_rn."Feature_91" + -0.13134877883624926 * keras_input_1_rn."Feature_92" + -0.03451915906455616 * keras_input_1_rn."Feature_93" + 0.02620761059915916 * keras_input_1_rn."Feature_94" + 0.18033312267078383 * keras_input_1_rn."Feature_95" + -0.02950451367636614 * keras_input_1_rn."Feature_96" + -0.2049316114904521 * keras_input_1_rn."Feature_97" + -0.1473094951013431 * keras_input_1_rn."Feature_98" + 0.11480076651589305 * keras_input_1_rn."Feature_99" AS dot_prod_r_2, -0.014208675539662907 + -0.18162956965330251 * keras_input_1_rn."Feature_0" + -0.26271625815573474 * keras_input_1_rn."Feature_1" + -0.007101394530210774 * keras_input_1_rn."Feature_2" + 0.12742804653709827 * keras_input_1_rn."Feature_3" + -0.18838789282434756 * keras_input_1_rn."Feature_4" + -0.14848438321171514 * keras_input_1_rn."Feature_5" + -0.13629329771800705 * keras_input_1_rn."Feature_6" + -0.18248969284809594 * keras_input_1_rn."Feature_7" + -0.2226608611010809 * keras_input_1_rn."Feature_8" + 0.05529517569075047 * keras_input_1_rn."Feature_9" + 0.23227268864125888 * keras_input_1_rn."Feature_10" + -0.13076151915278855 * keras_input_1_rn."Feature_11" + -0.10670954845986182 * keras_input_1_rn."Feature_12" + 0.14848575709462805 * keras_input_1_rn."Feature_13" + -0.16531601816202068 * keras_input_1_rn."Feature_14" + -0.17991448102800764 * keras_input_1_rn."Feature_15" + -0.013575709190487447 * keras_input_1_rn."Feature_16" + -0.09929384314184857 * keras_input_1_rn."Feature_17" + -0.0788832946128298 * keras_input_1_rn."Feature_18" + 0.13788457461746437 * keras_input_1_rn."Feature_19" + -0.0869533419005275 * keras_input_1_rn."Feature_20" + 0.17820246570866538 * keras_input_1_rn."Feature_21" + 0.12278395677805574 * keras_input_1_rn."Feature_22" + -0.1794266130877541 * keras_input_1_rn."Feature_23" + 0.13585452887600152 * keras_input_1_rn."Feature_24" + -0.03278275439679978 * keras_input_1_rn."Feature_25" + 0.12402750242314783 * keras_input_1_rn."Feature_26" + -0.0950116795962926 * keras_input_1_rn."Feature_27" + -0.00024180598875335238 * keras_input_1_rn."Feature_28" + -0.31364480543805806 * keras_input_1_rn."Feature_29" + 0.2315677076719474 * keras_input_1_rn."Feature_30" + 0.08367491733138874 * keras_input_1_rn."Feature_31" + 0.09643511356706876 * keras_input_1_rn."Feature_32" + -0.17243232822990506 * keras_input_1_rn."Feature_33" + -0.3039358531471057 * keras_input_1_rn."Feature_34" + 0.10594798739435955 * keras_input_1_rn."Feature_35" + 0.0491790843112241 * keras_input_1_rn."Feature_36" + 0.12166963842539012 * keras_input_1_rn."Feature_37" + -0.301173518563102 * keras_input_1_rn."Feature_38" + 0.22534203250264323 * keras_input_1_rn."Feature_39" + -0.10600624597227812 * keras_input_1_rn."Feature_40" + 0.04752429898706617 * keras_input_1_rn."Feature_41" + 0.21150835869747864 * keras_input_1_rn."Feature_42" + -0.028400326661553725 * keras_input_1_rn."Feature_43" + 0.14153926860428348 * keras_input_1_rn."Feature_44" + 0.10519922638995097 * keras_input_1_rn."Feature_45" + -0.0550509916581791 * keras_input_1_rn."Feature_46" + 0.036420643299645304 * keras_input_1_rn."Feature_47" + 0.24072164770606505 * keras_input_1_rn."Feature_48" + 0.08125198673854209 * keras_input_1_rn."Feature_49" + 0.06853541670375274 * keras_input_1_rn."Feature_50" + -0.007236034761366842 * keras_input_1_rn."Feature_51" + -0.10019669479125555 * keras_input_1_rn."Feature_52" + -0.1334672014989182 * keras_input_1_rn."Feature_53" + 0.09055506727130401 * keras_input_1_rn."Feature_54" + -0.03256620110654389 * keras_input_1_rn."Feature_55" + -0.10236155888153212 * keras_input_1_rn."Feature_56" + -0.03670884648228794 * keras_input_1_rn."Feature_57" + 0.1310510088083423 * keras_input_1_rn."Feature_58" + 0.1749437517004325 * keras_input_1_rn."Feature_59" + -0.11726606426857347 * keras_input_1_rn."Feature_60" + 0.08224324153997105 * keras_input_1_rn."Feature_61" + 0.2169432863889108 * keras_input_1_rn."Feature_62" + -0.09254336547122176 * keras_input_1_rn."Feature_63" + -0.0801601673606541 * keras_input_1_rn."Feature_64" + 0.2537590375887137 * keras_input_1_rn."Feature_65" + -0.15811797962304647 * keras_input_1_rn."Feature_66" + -0.023989409223636748 * keras_input_1_rn."Feature_67" + 0.38260241840940784 * keras_input_1_rn."Feature_68" + 0.03697976154590925 * keras_input_1_rn."Feature_69" + 0.18470798462488142 * keras_input_1_rn."Feature_70" + -0.0037728035739380008 * keras_input_1_rn."Feature_71" + 0.2743452449284065 * keras_input_1_rn."Feature_72" + -0.02690472628583696 * keras_input_1_rn."Feature_73" + 0.012616472997774441 * keras_input_1_rn."Feature_74" + 0.0924053572322324 * keras_input_1_rn."Feature_75" + -0.07441951425387172 * keras_input_1_rn."Feature_76" + 0.20820743188068475 * keras_input_1_rn."Feature_77" + 0.0888367277352608 * keras_input_1_rn."Feature_78" + 0.056462177695530254 * keras_input_1_rn."Feature_79" + -0.08695087082179483 * keras_input_1_rn."Feature_80" + -0.19533935828174995 * keras_input_1_rn."Feature_81" + -0.13164221676411028 * keras_input_1_rn."Feature_82" + 0.09979169851083033 * keras_input_1_rn."Feature_83" + 0.03184198899645282 * keras_input_1_rn."Feature_84" + 0.041758032899692106 * keras_input_1_rn."Feature_85" + 0.09762114938225505 * keras_input_1_rn."Feature_86" + 0.09883133470461745 * keras_input_1_rn."Feature_87" + 0.19987543459199544 * keras_input_1_rn."Feature_88" + -0.12515209540988742 * keras_input_1_rn."Feature_89" + -0.07295102177413555 * keras_input_1_rn."Feature_90" + 0.031506766962862386 * keras_input_1_rn."Feature_91" + 0.08814398720373344 * keras_input_1_rn."Feature_92" + 0.18714585934040076 * keras_input_1_rn."Feature_93" + -0.0338516327615542 * keras_input_1_rn."Feature_94" + 0.25450993497407254 * keras_input_1_rn."Feature_95" + 0.020523650809515112 * keras_input_1_rn."Feature_96" + 0.04027881156711539 * keras_input_1_rn."Feature_97" + 0.08474663620196848 * keras_input_1_rn."Feature_98" + 0.07796864124815374 * keras_input_1_rn."Feature_99" AS dot_prod_h_1, -0.026201045057769715 + 0.04309332081106651 * keras_input_1_rn."Feature_0" + -0.09258358334538175 * keras_input_1_rn."Feature_1" + 0.11356051663169751 * keras_input_1_rn."Feature_2" + -0.05988326212386732 * keras_input_1_rn."Feature_3" + 0.17088464677679643 * keras_input_1_rn."Feature_4" + -0.004406370021734433 * keras_input_1_rn."Feature_5" + 0.2511319837666578 * keras_input_1_rn."Feature_6" + 0.32343882953089287 * keras_input_1_rn."Feature_7" + 0.0035821593938702655 * keras_input_1_rn."Feature_8" + 0.06996598592896247 * keras_input_1_rn."Feature_9" + 0.1904487005756491 * keras_input_1_rn."Feature_10" + -0.2809080467772244 * keras_input_1_rn."Feature_11" + -0.13579370586534376 * keras_input_1_rn."Feature_12" + -0.18747362302335488 * keras_input_1_rn."Feature_13" + 0.1558519396607859 * keras_input_1_rn."Feature_14" + 0.11644913815076037 * keras_input_1_rn."Feature_15" + 0.05379278926302833 * keras_input_1_rn."Feature_16" + 0.14651611530956601 * keras_input_1_rn."Feature_17" + -0.02529309605364245 * keras_input_1_rn."Feature_18" + -0.030525627526860187 * keras_input_1_rn."Feature_19" + -0.2173660270454008 * keras_input_1_rn."Feature_20" + 0.2652578141299312 * keras_input_1_rn."Feature_21" + 0.237917881365106 * keras_input_1_rn."Feature_22" + 0.06321263649560277 * keras_input_1_rn."Feature_23" + -0.07373944389824127 * keras_input_1_rn."Feature_24" + 0.1769475012727916 * keras_input_1_rn."Feature_25" + 0.12317217801557122 * keras_input_1_rn."Feature_26" + -0.02791671163790815 * keras_input_1_rn."Feature_27" + -0.005924962351755816 * keras_input_1_rn."Feature_28" + -0.028238333981497134 * keras_input_1_rn."Feature_29" + 0.05541492209108586 * keras_input_1_rn."Feature_30" + -0.23948848289152813 * keras_input_1_rn."Feature_31" + 0.09482683973383263 * keras_input_1_rn."Feature_32" + 0.022996897062222438 * keras_input_1_rn."Feature_33" + 0.028194282584946898 * keras_input_1_rn."Feature_34" + -0.11213766275969485 * keras_input_1_rn."Feature_35" + -0.253646558984866 * keras_input_1_rn."Feature_36" + -0.1548454250385761 * keras_input_1_rn."Feature_37" + -0.3106535017760415 * keras_input_1_rn."Feature_38" + -0.08729672193121267 * keras_input_1_rn."Feature_39" + 0.15893521244065725 * keras_input_1_rn."Feature_40" + -0.008268755613674059 * keras_input_1_rn."Feature_41" + 0.16725469210010385 * keras_input_1_rn."Feature_42" + -0.05296179057871682 * keras_input_1_rn."Feature_43" + 0.024736492851266643 * keras_input_1_rn."Feature_44" + 0.046182425754399556 * keras_input_1_rn."Feature_45" + -0.17391739585483942 * keras_input_1_rn."Feature_46" + -0.005828747551858941 * keras_input_1_rn."Feature_47" + -0.10948027844468998 * keras_input_1_rn."Feature_48" + 0.06972065104154108 * keras_input_1_rn."Feature_49" + 0.1326343896418144 * keras_input_1_rn."Feature_50" + -0.07591824921940647 * keras_input_1_rn."Feature_51" + 0.10277307699407608 * keras_input_1_rn."Feature_52" + -0.15415759077838803 * keras_input_1_rn."Feature_53" + 0.07957367240856347 * keras_input_1_rn."Feature_54" + 0.14557358279073573 * keras_input_1_rn."Feature_55" + 0.25299678135261533 * keras_input_1_rn."Feature_56" + -0.06367490020214939 * keras_input_1_rn."Feature_57" + 0.013570385608297594 * keras_input_1_rn."Feature_58" + 0.10564236502026705 * keras_input_1_rn."Feature_59" + -0.25087974800773405 * keras_input_1_rn."Feature_60" + 0.18728845042104458 * keras_input_1_rn."Feature_61" + -0.08383818558913124 * keras_input_1_rn."Feature_62" + -0.02718435027959801 * keras_input_1_rn."Feature_63" + 0.08695236345672551 * keras_input_1_rn."Feature_64" + 0.01127010937560834 * keras_input_1_rn."Feature_65" + 0.15833115747916407 * keras_input_1_rn."Feature_66" + 0.28067779218485045 * keras_input_1_rn."Feature_67" + 0.05302343746889758 * keras_input_1_rn."Feature_68" + 0.04571334965785818 * keras_input_1_rn."Feature_69" + -0.30815491587772725 * keras_input_1_rn."Feature_70" + -0.13201405569683294 * keras_input_1_rn."Feature_71" + 0.007487568941096786 * keras_input_1_rn."Feature_72" + 0.04557163529336143 * keras_input_1_rn."Feature_73" + -0.18001814524463255 * keras_input_1_rn."Feature_74" + 0.20941813232522785 * keras_input_1_rn."Feature_75" + 0.01118981873784512 * keras_input_1_rn."Feature_76" + 0.20261811098527752 * keras_input_1_rn."Feature_77" + 0.4228656692300836 * keras_input_1_rn."Feature_78" + 0.08346411462612705 * keras_input_1_rn."Feature_79" + -0.022696115994838086 * keras_input_1_rn."Feature_80" + 0.11424393820522104 * keras_input_1_rn."Feature_81" + -0.15646350982012008 * keras_input_1_rn."Feature_82" + 0.13589279890348524 * keras_input_1_rn."Feature_83" + 0.04491074011079169 * keras_input_1_rn."Feature_84" + -0.18690556168341885 * keras_input_1_rn."Feature_85" + -0.04353554807219847 * keras_input_1_rn."Feature_86" + 0.0041118431412787634 * keras_input_1_rn."Feature_87" + 0.06496376304875627 * keras_input_1_rn."Feature_88" + -0.09895641461466848 * keras_input_1_rn."Feature_89" + -0.1081654509863002 * keras_input_1_rn."Feature_90" + 0.03119533768304921 * keras_input_1_rn."Feature_91" + -0.08069792793140823 * keras_input_1_rn."Feature_92" + 0.21482295330643134 * keras_input_1_rn."Feature_93" + -0.0584401918935944 * keras_input_1_rn."Feature_94" + -0.0024736389224118385 * keras_input_1_rn."Feature_95" + -0.18457220737169372 * keras_input_1_rn."Feature_96" + -0.1672240164479457 * keras_input_1_rn."Feature_97" + -0.2669860156639161 * keras_input_1_rn."Feature_98" + 0.3435296287750693 * keras_input_1_rn."Feature_99" AS dot_prod_h_2 
  FROM keras_input_1_rn), 
  rnn_cte_gru_1(rn_1, "KEY", "PreviousState_1", "PreviousState_2", "State_1", "State_2") AS 
  (SELECT gru_input_kernel_bias.rn AS rn_1, gru_input_kernel_bias."KEY" AS "KEY", CAST(0.0 AS FLOAT) AS "PreviousState_1", CAST(0.0 AS FLOAT) AS "PreviousState_2", (1.0 - max(0.0, min(1.0, 0.2 * (0.0 + gru_input_kernel_bias.dot_prod_z_1) + 0.5))) * tanh(0.0 + gru_input_kernel_bias.dot_prod_h_1) AS "State_1", (1.0 - max(0.0, min(1.0, 0.2 * (0.0 + gru_input_kernel_bias.dot_prod_z_2) + 0.5))) * tanh(0.0 + gru_input_kernel_bias.dot_prod_h_2) AS "State_2" 
  FROM gru_input_kernel_bias 
  WHERE gru_input_kernel_bias.rn = 1 UNION ALL SELECT gru_input_kernel_bias.rn AS rn, gru_input_kernel_bias."KEY" AS "KEY", CAST(0.0 AS FLOAT) AS "PreviousState_1", CAST(0.0 AS FLOAT) AS "PreviousState_2", max(0.0, min(1.0, 0.2 * (0.07889305402131672 * CAST(0.0 AS FLOAT) + -0.12001338771399168 * CAST(0.0 AS FLOAT) + gru_input_kernel_bias.dot_prod_z_1) + 0.5)) * CAST(0.0 AS FLOAT) + (1.0 - max(0.0, min(1.0, 0.2 * (0.07889305402131672 * CAST(0.0 AS FLOAT) + -0.12001338771399168 * CAST(0.0 AS FLOAT) + gru_input_kernel_bias.dot_prod_z_1) + 0.5))) * tanh(0.19308494093258327 * max(0.0, min(1.0, 0.2 * (-0.1888178280225422 * CAST(0.0 AS FLOAT) + -0.24466095906319685 * CAST(0.0 AS FLOAT) + gru_input_kernel_bias.dot_prod_r_1) + 0.5)) * CAST(0.0 AS FLOAT) + 0.7665848473643189 * max(0.0, min(1.0, 0.2 * (-0.5245068706087566 * CAST(0.0 AS FLOAT) + -0.3341770861035541 * CAST(0.0 AS FLOAT) + gru_input_kernel_bias.dot_prod_r_2) + 0.5)) * CAST(0.0 AS FLOAT) + gru_input_kernel_bias.dot_prod_h_1) AS "State_1", max(0.0, min(1.0, 0.2 * (-0.034960511057912716 * CAST(0.0 AS FLOAT) + -0.14062053889322335 * CAST(0.0 AS FLOAT) + gru_input_kernel_bias.dot_prod_z_2) + 0.5)) * CAST(0.0 AS FLOAT) + (1.0 - max(0.0, min(1.0, 0.2 * (-0.034960511057912716 * CAST(0.0 AS FLOAT) + -0.14062053889322335 * CAST(0.0 AS FLOAT) + gru_input_kernel_bias.dot_prod_z_2) + 0.5))) * tanh(0.8028151871906004 * max(0.0, min(1.0, 0.2 * (-0.1888178280225422 * CAST(0.0 AS FLOAT) + -0.24466095906319685 * CAST(0.0 AS FLOAT) + gru_input_kernel_bias.dot_prod_r_1) + 0.5)) * CAST(0.0 AS FLOAT) + -0.4545734405306024 * max(0.0, min(1.0, 0.2 * (-0.5245068706087566 * CAST(0.0 AS FLOAT) + -0.3341770861035541 * CAST(0.0 AS FLOAT) + gru_input_kernel_bias.dot_prod_r_2) + 0.5)) * CAST(0.0 AS FLOAT) + gru_input_kernel_bias.dot_prod_h_2) AS "State_2" 
  FROM gru_input_kernel_bias, rnn_cte_gru_1 
  WHERE gru_input_kernel_bias.rn = rnn_cte_gru_1.rn_1 + 1), 
  gru_1 AS 
  (SELECT rnn_cte_gru_1."KEY" AS "KEY", CAST(rnn_cte_gru_1."State_1" AS FLOAT) AS output_1, CAST(rnn_cte_gru_1."State_2" AS FLOAT) AS output_2 
  FROM rnn_cte_gru_1), 
  gru_1_1 AS 
  (SELECT gru_1."KEY" AS "KEY", gru_1.output_1 AS output_1, gru_1.output_2 AS output_2 
  FROM gru_1), 
  layer_dense_1 AS 
  (SELECT gru_1_1."KEY" AS "KEY", 0.0591918941918908 + 0.2464015504655088 * gru_1_1.output_1 + 0.19525921142409763 * gru_1_1.output_2 AS output_1, 0.020821727236258147 + 1.0381651536913779 * gru_1_1.output_1 + -0.8114133652631286 * gru_1_1.output_2 AS output_2, -0.07859073964615634 + -0.7400756392115873 * gru_1_1.output_1 + -1.2373296310864894 * gru_1_1.output_2 AS output_3, -0.013264106086631767 + -0.3873204911496532 * gru_1_1.output_1 + -1.0983883294617462 * gru_1_1.output_2 AS output_4 
  FROM gru_1_1), 
  layer_dense_1_1 AS 
  (SELECT layer_dense_1."KEY" AS "KEY", layer_dense_1.output_1 AS output_1, layer_dense_1.output_2 AS output_2, layer_dense_1.output_3 AS output_3, layer_dense_1.output_4 AS output_4 
  FROM layer_dense_1), 
  score_soft_max_step1 AS 
  (SELECT layer_dense_1_1."KEY" AS "KEY", layer_dense_1_1.output_1 AS "Score_0", exp(min(100.0, max(-100.0, layer_dense_1_1.output_1))) AS "exp_Score_0", layer_dense_1_1.output_2 AS "Score_1", exp(min(100.0, max(-100.0, layer_dense_1_1.output_2))) AS "exp_Score_1", layer_dense_1_1.output_3 AS "Score_2", exp(min(100.0, max(-100.0, layer_dense_1_1.output_3))) AS "exp_Score_2", layer_dense_1_1.output_4 AS "Score_3", exp(min(100.0, max(-100.0, layer_dense_1_1.output_4))) AS "exp_Score_3" 
  FROM layer_dense_1_1), 
  score_class_union_soft AS 
  (SELECT soft_scu."KEY" AS "KEY", soft_scu.class AS class, soft_scu."exp_Score" AS "exp_Score" 
  FROM (SELECT score_soft_max_step1."KEY" AS "KEY", 0 AS class, score_soft_max_step1."exp_Score_0" AS "exp_Score" 
  FROM score_soft_max_step1 UNION ALL SELECT score_soft_max_step1."KEY" AS "KEY", 1 AS class, score_soft_max_step1."exp_Score_1" AS "exp_Score" 
  FROM score_soft_max_step1 UNION ALL SELECT score_soft_max_step1."KEY" AS "KEY", 2 AS class, score_soft_max_step1."exp_Score_2" AS "exp_Score" 
  FROM score_soft_max_step1 UNION ALL SELECT score_soft_max_step1."KEY" AS "KEY", 3 AS class, score_soft_max_step1."exp_Score_3" AS "exp_Score" 
  FROM score_soft_max_step1) AS soft_scu), 
  score_soft_max AS 
  (SELECT score_soft_max_step1."KEY" AS "KEY", score_soft_max_step1."Score_0" AS "Score_0", score_soft_max_step1."exp_Score_0" AS "exp_Score_0", score_soft_max_step1."Score_1" AS "Score_1", score_soft_max_step1."exp_Score_1" AS "exp_Score_1", score_soft_max_step1."Score_2" AS "Score_2", score_soft_max_step1."exp_Score_2" AS "exp_Score_2", score_soft_max_step1."Score_3" AS "Score_3", score_soft_max_step1."exp_Score_3" AS "exp_Score_3", sum_exp_t."KEY_sum" AS "KEY_sum", sum_exp_t."sum_ExpScore" AS "sum_ExpScore" 
  FROM score_soft_max_step1 LEFT OUTER JOIN (SELECT score_class_union_soft."KEY" AS "KEY_sum", sum(score_class_union_soft."exp_Score") AS "sum_ExpScore" 
  FROM score_class_union_soft GROUP BY score_class_union_soft."KEY") AS sum_exp_t ON score_soft_max_step1."KEY" = sum_exp_t."KEY_sum"), 
  layer_softmax AS 
  (SELECT score_soft_max."KEY" AS "KEY", score_soft_max."exp_Score_0" / score_soft_max."sum_ExpScore" AS output_1, score_soft_max."exp_Score_1" / score_soft_max."sum_ExpScore" AS output_2, score_soft_max."exp_Score_2" / score_soft_max."sum_ExpScore" AS output_3, score_soft_max."exp_Score_3" / score_soft_max."sum_ExpScore" AS output_4 
  FROM score_soft_max), 
  orig_cte AS 
  (SELECT layer_softmax."KEY" AS "KEY", CAST(NULL AS FLOAT) AS "Score_0", CAST(NULL AS FLOAT) AS "Score_1", CAST(NULL AS FLOAT) AS "Score_2", CAST(NULL AS FLOAT) AS "Score_3", layer_softmax.output_1 AS "Proba_0", layer_softmax.output_2 AS "Proba_1", layer_softmax.output_3 AS "Proba_2", layer_softmax.output_4 AS "Proba_3", CAST(NULL AS FLOAT) AS "LogProba_0", CAST(NULL AS FLOAT) AS "LogProba_1", CAST(NULL AS FLOAT) AS "LogProba_2", CAST(NULL AS FLOAT) AS "LogProba_3", CAST(NULL AS BIGINT) AS "Decision", CAST(NULL AS FLOAT) AS "DecisionProba" 
  FROM layer_softmax), 
  score_class_union AS 
  (SELECT scu."KEY_u" AS "KEY_u", scu.class AS class, scu."LogProba" AS "LogProba", scu."Proba" AS "Proba", scu."Score" AS "Score" 
  FROM (SELECT orig_cte."KEY" AS "KEY_u", 0 AS class, orig_cte."LogProba_0" AS "LogProba", orig_cte."Proba_0" AS "Proba", orig_cte."Score_0" AS "Score" 
  FROM orig_cte UNION ALL SELECT orig_cte."KEY" AS "KEY_u", 1 AS class, orig_cte."LogProba_1" AS "LogProba", orig_cte."Proba_1" AS "Proba", orig_cte."Score_1" AS "Score" 
  FROM orig_cte UNION ALL SELECT orig_cte."KEY" AS "KEY_u", 2 AS class, orig_cte."LogProba_2" AS "LogProba", orig_cte."Proba_2" AS "Proba", orig_cte."Score_2" AS "Score" 
  FROM orig_cte UNION ALL SELECT orig_cte."KEY" AS "KEY_u", 3 AS class, orig_cte."LogProba_3" AS "LogProba", orig_cte."Proba_3" AS "Proba", orig_cte."Score_3" AS "Score" 
  FROM orig_cte) AS scu), 
  score_max AS 
  (SELECT orig_cte."KEY" AS "KEY", orig_cte."Score_0" AS "Score_0", orig_cte."Score_1" AS "Score_1", orig_cte."Score_2" AS "Score_2", orig_cte."Score_3" AS "Score_3", orig_cte."Proba_0" AS "Proba_0", orig_cte."Proba_1" AS "Proba_1", orig_cte."Proba_2" AS "Proba_2", orig_cte."Proba_3" AS "Proba_3", orig_cte."LogProba_0" AS "LogProba_0", orig_cte."LogProba_1" AS "LogProba_1", orig_cte."LogProba_2" AS "LogProba_2", orig_cte."LogProba_3" AS "LogProba_3", orig_cte."Decision" AS "Decision", orig_cte."DecisionProba" AS "DecisionProba", max_select."KEY_m" AS "KEY_m", max_select."max_Proba" AS "max_Proba" 
  FROM orig_cte LEFT OUTER JOIN (SELECT score_class_union."KEY_u" AS "KEY_m", max(score_class_union."Proba") AS "max_Proba" 
  FROM score_class_union GROUP BY score_class_union."KEY_u") AS max_select ON orig_cte."KEY" = max_select."KEY_m"), 
  union_with_max AS 
  (SELECT score_class_union."KEY_u" AS "KEY_u", score_class_union.class AS class, score_class_union."LogProba" AS "LogProba", score_class_union."Proba" AS "Proba", score_class_union."Score" AS "Score", score_max."KEY" AS "KEY", score_max."Score_0" AS "Score_0", score_max."Score_1" AS "Score_1", score_max."Score_2" AS "Score_2", score_max."Score_3" AS "Score_3", score_max."Proba_0" AS "Proba_0", score_max."Proba_1" AS "Proba_1", score_max."Proba_2" AS "Proba_2", score_max."Proba_3" AS "Proba_3", score_max."LogProba_0" AS "LogProba_0", score_max."LogProba_1" AS "LogProba_1", score_max."LogProba_2" AS "LogProba_2", score_max."LogProba_3" AS "LogProba_3", score_max."Decision" AS "Decision", score_max."DecisionProba" AS "DecisionProba", score_max."KEY_m" AS "KEY_m", score_max."max_Proba" AS "max_Proba" 
  FROM score_class_union LEFT OUTER JOIN score_max ON score_class_union."KEY_u" = score_max."KEY"), 
  arg_max_cte AS 
  (SELECT score_max."KEY" AS "KEY", score_max."Score_0" AS "Score_0", score_max."Score_1" AS "Score_1", score_max."Score_2" AS "Score_2", score_max."Score_3" AS "Score_3", score_max."Proba_0" AS "Proba_0", score_max."Proba_1" AS "Proba_1", score_max."Proba_2" AS "Proba_2", score_max."Proba_3" AS "Proba_3", score_max."LogProba_0" AS "LogProba_0", score_max."LogProba_1" AS "LogProba_1", score_max."LogProba_2" AS "LogProba_2", score_max."LogProba_3" AS "LogProba_3", score_max."Decision" AS "Decision", score_max."DecisionProba" AS "DecisionProba", score_max."KEY_m" AS "KEY_m", score_max."max_Proba" AS "max_Proba", "arg_max_t_Proba"."KEY_Proba" AS "KEY_Proba", "arg_max_t_Proba"."arg_max_Proba" AS "arg_max_Proba" 
  FROM score_max LEFT OUTER JOIN (SELECT union_with_max."KEY" AS "KEY_Proba", max(union_with_max.class) AS "arg_max_Proba" 
  FROM union_with_max 
  WHERE union_with_max."max_Proba" <= union_with_max."Proba" GROUP BY union_with_max."KEY") AS "arg_max_t_Proba" ON score_max."KEY" = "arg_max_t_Proba"."KEY_Proba")
   SELECT arg_max_cte."KEY" AS "KEY", arg_max_cte."Score_0" AS "Score_0", arg_max_cte."Score_1" AS "Score_1", arg_max_cte."Score_2" AS "Score_2", arg_max_cte."Score_3" AS "Score_3", arg_max_cte."Proba_0" AS "Proba_0", arg_max_cte."Proba_1" AS "Proba_1", arg_max_cte."Proba_2" AS "Proba_2", arg_max_cte."Proba_3" AS "Proba_3", CASE WHEN (arg_max_cte."Proba_0" IS NULL OR arg_max_cte."Proba_0" > 0.0) THEN ln(arg_max_cte."Proba_0") ELSE -1.79769313486231e+308 END AS "LogProba_0", CASE WHEN (arg_max_cte."Proba_1" IS NULL OR arg_max_cte."Proba_1" > 0.0) THEN ln(arg_max_cte."Proba_1") ELSE -1.79769313486231e+308 END AS "LogProba_1", CASE WHEN (arg_max_cte."Proba_2" IS NULL OR arg_max_cte."Proba_2" > 0.0) THEN ln(arg_max_cte."Proba_2") ELSE -1.79769313486231e+308 END AS "LogProba_2", CASE WHEN (arg_max_cte."Proba_3" IS NULL OR arg_max_cte."Proba_3" > 0.0) THEN ln(arg_max_cte."Proba_3") ELSE -1.79769313486231e+308 END AS "LogProba_3", arg_max_cte."arg_max_Proba" AS "Decision", arg_max_cte."max_Proba" AS "DecisionProba" 
  FROM arg_max_cte