/
build_vocab.py
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build_vocab.py
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import json
import collections
# train_input_file_path = 'data/preprocess_input/train-webnlg-all-delex.triple'
# train_output_file_path = 'data/preprocess_input/train-webnlg-all-delex.lex'
train_input_file_path = 'data/GKBdataset/train.triple'
train_output_file_path = 'data/GKBdataset/train.lex'
def get_words(data):
words_box=[]
for line in data:
words_box.extend(line.replace(' < TSP > ',' ').replace(' | ', ' ').lower().split())
return collections.Counter(words_box)
def main():
with open(train_input_file_path,'r') as f:
train_inputs = f.readlines()
with open(train_output_file_path,'r') as f:
train_outputs = f.readlines()
input_vocab = get_words(train_inputs)
# input_vocab = [key for key, _ in input_vocab.most_common()]
output_vocab = get_words(train_outputs)
# output_vocab = [key for key, _ in output_vocab.most_common()]
all_vocab = input_vocab+output_vocab
all_vocab = [key for key, _ in all_vocab.most_common()]
# all_vocab = ['<pad>','<start>','<end>','<unk>']+all_vocab
all_vocab = ['<pad>','<start>','<end>','<unk>','A0','A1','NE']+all_vocab
print(len(all_vocab))
word2id = {}
# id2word = {}
for idx, line in enumerate(all_vocab):
word2id[line] = idx
# id2word[idx] = line
# vocab_file_path1 = 'data/preprocess_input/vocab_word2id'
# vocab_file_path2 = 'data/preprocess_input/vocab_id2word'
vocab_file_path1 = 'data/GKBdataset/vocab_word2id'
vocab_file_path2 = 'data/GKBdataset/vocab_id2word'
with open(vocab_file_path1,'w+') as f:
json.dump(word2id,f)
with open(vocab_file_path2,'w+') as f:
json.dump(all_vocab,f)
return word2id
def main_gkb():
train_input0 = open('data/preprocess_input/train-webnlg-all-delex.triple').readlines()
train_output0 = open('data/preprocess_input/train-webnlg-all-delex.lex').readlines()
train_input = open('data/GKBdataset/train.triple').readlines()
train_output = open('data/GKBdataset/train.lex').readlines()
train_inputs = train_input0 + train_input
train_outputs = train_output0 + train_output
input_vocab = get_words(train_inputs)
# input_vocab = [key for key, _ in input_vocab.most_common()]
output_vocab = get_words(train_outputs)
# output_vocab = [key for key, _ in output_vocab.most_common()]
all_vocab = input_vocab+output_vocab
all_vocab = [key for key, _ in all_vocab.most_common()]
# all_vocab = ['<pad>','<start>','<end>','<unk>']+all_vocab
all_vocab = ['<pad>','<start>','<end>','<unk>','A0','A1','NE']+all_vocab
print(len(all_vocab))
word2id = {}
# id2word = {}
for idx, line in enumerate(all_vocab):
word2id[line] = idx
# id2word[idx] = line
# vocab_file_path1 = 'data/preprocess_input/vocab_word2id'
# vocab_file_path2 = 'data/preprocess_input/vocab_id2word'
vocab_file_path1 = 'data/GKBdataset/vocab_word2id'
vocab_file_path2 = 'data/GKBdataset/vocab_id2word'
with open(vocab_file_path1,'w+') as f:
json.dump(word2id,f)
with open(vocab_file_path2,'w+') as f:
json.dump(all_vocab,f)
return word2id
def main_pq():
train_inputs = open('data/PQdataset/both_masked/train.triple').readlines()
train_outputs = open('data/PQdataset/both_masked/train.lex').readlines()
input_vocab = get_words(train_inputs)
# input_vocab = [key for key, _ in input_vocab.most_common()]
output_vocab = get_words(train_outputs)
# output_vocab = [key for key, _ in output_vocab.most_common()]
all_vocab = input_vocab+output_vocab
all_vocab = [key for key, _ in all_vocab.most_common()]
# all_vocab = ['<pad>','<start>','<end>','<unk>']+all_vocab
all_vocab = ['<pad>','<start>','<end>','<unk>','A0','A1','NE']+all_vocab
print(len(all_vocab))
word2id = {}
# id2word = {}
for idx, line in enumerate(all_vocab):
word2id[line] = idx
# id2word[idx] = line
# vocab_file_path1 = 'data/preprocess_input/vocab_word2id'
# vocab_file_path2 = 'data/preprocess_input/vocab_id2word'
vocab_file_path1 = 'data/PQdataset/both_masked/vocab_word2id'
vocab_file_path2 = 'data/PQdataset/both_masked/vocab_id2word'
with open(vocab_file_path1,'w+') as f:
json.dump(word2id,f)
with open(vocab_file_path2,'w+') as f:
json.dump(all_vocab,f)
return word2id
# main()
# main_gkb()
main_pq()