How to use Single Mode when I am training for the same graph structure about spektral HOT 1 CLOSED

    def data_generator(X, correlation, decoder_Y, Y, batch_size=50):
        while True:
            perm = np.random.permutation(len(X))
            for i in range(0, len(X), batch_size):
                batch_X = X[perm[i:i + batch_size]]

                # Efficiently broadcasting the correlation matrix for this batch
                batch_correlation = np.repeat(correlation[np.newaxis, ...], len(batch_X), axis=0)

                batch_decoder_Y = decoder_Y[perm[i:i + batch_size]]
                batch_Y = Y[perm[i:i + batch_size]]
                yield [batch_X, batch_correlation, batch_decoder_Y], batch_Y

        # Create the training generator
        train_gen = data_generator(X_train_train, correlation_train_train, decoder_Y_train_train, Y_train_train, batch_size=50)

        # Create the validation generator
        val_gen = data_generator(X_train_valid, correlation_train_train, decoder_Y_train_valid, Y_train_valid,
                                   batch_size=50)

        # Calculate the steps per epoch for training and validation
        train_steps = len(X_train_train) // 50
        val_steps = len(X_train_valid) // 50

        # Use the generators in model.fit()
        model.fit(train_gen,
                  steps_per_epoch=train_steps,
                  validation_data=val_gen,
                  validation_steps=val_steps,
                  epochs=100,
                  callbacks=callbacks)