src/data_loader/data_generator.py
def __shuffle_all_data(self):
        """Private function.
        Shuffles the whole training set to avoid patterns recognition by the model(I liked that course:D).
        shuffle function is used instead of sklearn shuffle function in order reduce usage of
        external dependencies.

        Returns:
        """
        indices_list = [i for i in range(self.x_train.shape[0])]
        shuffle(indices_list)
        # Next two lines may cause memory error if no sufficient ram.
        self.x_train = self.x_train[indices_list]
        self.y_train = self.y_train[indices_list]

        indices_list = [i for i in range(self.x_val.shape[0])]
        shuffle(indices_list)
        # Next two lines may cause memory error if no sufficient ram.
        self.x_val = self.x_val[indices_list]
        self.y_val = self.y_val[indices_list]
Private function.
        Shuffles the whole training set to avoid patterns recognition by the model(I liked that course:D).
        shuffle function is used instead of sklearn shuffle function in order reduce usage of
        external dependencies.

        Returns:
        
Private function.
Shuffles the whole training set to avoid patterns recognition by the model(I liked that course:D).
shuffle function is used instead of sklearn shuffle function in order reduce usage of
external dependencies.
Private function . Shuffles the whole training set to avoid patterns recognition by the model ( I liked that course : D ) . shuffle function is used instead of sklearn shuffle function in order reduce usage of external dependencies .
def __shuffle_all_data(self):
        indices_list = [i for i in range(self.x_train.shape[0])]
        shuffle(indices_list)
        self.x_train = self.x_train[indices_list]
        self.y_train = self.y_train[indices_list]
        indices_list = [i for i in range(self.x_val.shape[0])]
        shuffle(indices_list)
        self.x_val = self.x_val[indices_list]
        self.y_val = self.y_val[indices_list]
def __shuffle_all_data ( self ) : indices_list = [ i for i in range ( self . x_train . shape [ 0 ] ) ] shuffle ( indices_list ) self . x_train = self . x_train [ indices_list ] self . y_train = self . y_train [ indices_list ] indices_list = [ i for i in range ( self . x_val . shape [ 0 ] ) ] shuffle ( indices_list ) self . x_val = self . x_val [ indices_list ] self . y_val = self . y_val [ indices_list ]
Private function.
Private function .
"""Private function.
        Shuffles the whole training set to avoid patterns recognition by the model(I liked that course:D).
        shuffle function is used instead of sklearn shuffle function in order reduce usage of
        external dependencies.

        Returns:
        """ # Next two lines may cause memory error if no sufficient ram. # Next two lines may cause memory error if no sufficient ram.
None
self