text: # -*- coding: utf-8 -*-
  # @File    : image_caption_with_attention_r9.1/configuration.py
  # @Info    : @ TSMC-SIGGRAPH, 2018/9/6
  # @Desc    :
  # -.-.. - ... -- -.-. .-.. .- -... .---.   -.-- ..- .-.. --- -. --.   ..-. .- -. 
  
  
  class ModelConfig(object):
      def __init__(self):
          self.batch_size = 32
          self.epoch = 5
          self.buffer_size = 1000
  
          self.embedding_dim = 256  # input img/sequence embedding dimension
          self.units = 512        # hidden units
          self.vocab_size = None  # the size of the caption's vocabulary
  
          # shape of the vector extracted from InceptionV3 is (64, 2048)
          # these two variables represent that
          self.attention_features_shape = 64
          self.features_shape = 2048
  
          # (Inference) The maximum caption length before stopping the search.
          self.max_caption_length = 20
  
          # limit the size of the training set for faster training, selecting the first 3w captions from the shuffled set
          self.limit_num_examples = 30000
  
          # choosing the top k words from the vocabulary
          self.top_k = 5000
  