Feature reversing input noise

Data Science
17 
class DataSequence(tf.keras.utils.Sequence):

    def __init__(self, df, features, erasPerBatch=1, shuffle=True):
        self.df = df
        self.features = features
        self.shuffle = shuffle
        self.eras = df.era.unique()
        
        if self.shuffle == True:
            np.random.shuffle(self.eras)
            
        self.erasPerBatch = erasPerBatch
        
        self.df['target_aux'] = self.df[target]
        
  
    def __len__(self):
        return len(self.eras) // self.erasPerBatch

    def on_epoch_end(self):
        if self.shuffle == True:
            self.df = self.df.sample(frac=1).reset_index(drop=True)
            np.random.shuffle(self.eras)


    def __getitem__(self, idx):

        myEras = []
       
        for i in range(self.erasPerBatch):
            myEras.append( self.eras[idx*self.erasPerBatch+i] )
        
        #print(myEras)
                          
        X = self.df.loc[self.df.era.isin(myEras), self.features].values
        y = self.df.loc[self.df.era.isin(myEras), self.features + ['target_aux', 'target']].values
        
        X = np.split(X, X.shape[1], axis=1)
        y = np.split(y, y.shape[1], axis=1)
        
      
        return X, y
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