for i in range(int(len(all_text_chars)/SEQUENCE_LENGTH)):

    #Get next sequence of length 57 as input.
    X_sequence = all_text_chars[i*SEQUENCE_LENGTH:(i+1)*SEQUENCE_LENGTH]

    # Convert the above sequence to the integer mapping using our mapping dictionary.
    X_sequence_ix = [char_to_ix[value] for value in X_sequence]

    # Create a skeleton for the input sequence:
    # we create a 2d numpy matrix which has a feature array of 94
    # long for each of the 57 characters in sequence.
    # This way we basically one hot encode our sequences.
    input_sequence = np.zeros((SEQUENCE_LENGTH, NUMBER_FEATURES))

    # The one hot encoding process: we replace a zero with a one
    # on a position in the input sequence which corresponds with the index
    # of a character in our converted array!
    for j in range(SEQUENCE_LENGTH):
        input_sequence[j][X_sequence_ix[j]] = 1.

    # For each spot in X (which stands for each sequence) we
    # fill in our one hot encoded array!
    X[i] = input_sequence

    #Same for y!
    y_sequence = all_text_chars[i*SEQUENCE_LENGTH+1:(i+1)*SEQUENCE_LENGTH+1]

    y_sequence_ix = [char_to_ix[value] for value in y_sequence]

    target_sequence = np.zeros((SEQUENCE_LENGTH, NUMBER_FEATURES))

    for j in range(SEQUENCE_LENGTH):
        target_sequence[j][y_sequence_ix[j]] = 1.

    y[i] = target_sequence