text: from tensorflow.keras.losses import categorical_crossentropy
  from tensorflow.keras.preprocessing.text import Tokenizer
  from tensorflow.keras.optimizers import Adam
  import utils
  
  LOSS = categorical_crossentropy
  OPTIMIZER = Adam(lr=0.01)
  
  EPOCHS = 50
  
  MODEL_PATH = "../saved_model/Model.h5"
  TOKENIZER_PATH = "../saved_model/tokenizer.pickle"
  DATA_PATH = "../data/poem_dataset.csv"
  
  EMBEDDING_DIM = 300
  
  TOKENIZER = Tokenizer()
  
  PADDING = "pre"
  NEXT_WORDS = 20
  
  MAX_LEN, TOTAL_WORDS = None, None
  
  
  def set_value(max_len, total_words):
  
      global MAX_LEN
      global TOTAL_WORDS
  
      MAX_LEN = max_len
      TOTAL_WORDS = total_words
  
      file = {"max_len": MAX_LEN, "total_words": TOTAL_WORDS}
      utils.save_file(file)
  
  
  FILE_NAME = "../saved_model/file.pickel"
  