text: """ A neural chatbot using sequence to sequence model with
  attentional decoder. 
  
  This is based on Google Translate Tensorflow model 
  https://github.com/tensorflow/models/blob/master/tutorials/rnn/translate/
  
  Sequence to sequence model by Cho et al.(2014)
  
  Created by Chip Huyen as the starter code for assignment 3,
  class CS 20SI: "TensorFlow for Deep Learning Research"
  cs20si.stanford.edu
  
  This file contains the hyperparameters for the model.
  
  See readme.md for instruction on how to run the starter code.
  """
  
  # parameters for processing the dataset
  DATA_PATH = '/Users/ivanmagda/Programming/deep-learning/deep-learning-foundation/week-11/seq-to-seq/cornell-movie-dialogs-corpus'
  CONVO_FILE = 'movie_conversations.txt'
  LINE_FILE = 'movie_lines.txt'
  OUTPUT_FILE = 'output_convo.txt'
  PROCESSED_PATH = 'processed'
  CPT_PATH = 'checkpoints'
  
  THRESHOLD = 2
  
  PAD_ID = 0
  UNK_ID = 1
  START_ID = 2
  EOS_ID = 3
  
  TESTSET_SIZE = 25000
  
  # model parameters
  """ Train encoder length distribution:
  [175, 92, 11883, 8387, 10656, 13613, 13480, 12850, 11802, 10165, 
  8973, 7731, 7005, 6073, 5521, 5020, 4530, 4421, 3746, 3474, 3192, 
  2724, 2587, 2413, 2252, 2015, 1816, 1728, 1555, 1392, 1327, 1248, 
  1128, 1084, 1010, 884, 843, 755, 705, 660, 649, 594, 558, 517, 475, 
  426, 444, 388, 349, 337]
  These buckets size seem to work the best
  """
  # [19530, 17449, 17585, 23444, 22884, 16435, 17085, 18291, 18931]
  # BUCKETS = [(6, 8), (8, 10), (10, 12), (13, 15), (16, 19), (19, 22), (23, 26), (29, 32), (39, 44)]
  
  # [37049, 33519, 30223, 33513, 37371]
  # BUCKETS = [(8, 10), (12, 14), (16, 19), (23, 26), (39, 43)]
  
  BUCKETS = [(8, 10), (12, 14), (16, 19)]
  
  NUM_LAYERS = 3
  HIDDEN_SIZE = 256
  BATCH_SIZE = 64
  
  LR = 0.5
  MAX_GRAD_NORM = 5.0
  
  NUM_SAMPLES = 512
  