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config.py
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config.py
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import tensorflow as tf
class Config:
vocabulary_size = 10000
bidirectional_encoder = False
encoder_cell_size = 512
decoder_cell_size = 512
num_layers = 3
use_dropout = True
dropout_keep_prob = 0.5
batch_size = 40
log_directory = 'logs/'
num_epochs = 50
validation_summary_frequency = 100
checkpoint_frequency = 5000
trace_frequency = 10000
trace_filename = "trace.json"
input_sentence_max_length = 60
max_decoder_inference_length = 60
use_word2vec = True
word_embedding_size = 200
word2vec_directory = "word2vec"
word2vec_path = word2vec_directory + "/wordembeddings_" + str(word_embedding_size) + ".word2vec"
word2vec_min_word_freq = 1
word2vec_workers_count = 4
attention_size = 512
antilm_penalization_weight = 0.15
antilm_max_penalization_len = 4
pick_multinomial_max_len = 1
scheduled_sampling_prob = 0.25
CORNELL_base_path = 'data/cornell_movie_dialogs_corpus'
CORNELL_lines_path = CORNELL_base_path + '/movie_lines.txt'
CORNELL_conversations_path = CORNELL_base_path + '/movie_conversations.txt'
CORNELL_TUPLES_PATH = CORNELL_base_path + '/Training_Cornell_Shuffled_Dataset.txt'
both_datasets_tuples_filepath = 'Training_both_datasets.txt'
use_CORNELL_for_training = True
use_CORNELL_for_word2vec = True