def tokenizer_from_json(json_string):
"""Parses a JSON tokenizer configuration file and returns a
tokenizer instance.
# Arguments
json_string: JSON string encoding a tokenizer configuration.
# Returns
A Keras Tokenizer instance
"""
tokenizer_config = json.loads(json_string)
config = tokenizer_config.get('config')
word_counts = json.loads(config.pop('word_counts'))
word_docs = json.loads(config.pop('word_docs'))
index_docs = json.loads(config.pop('index_docs'))
# Integer indexing gets converted to strings with json.dumps()
index_docs = {int(k): v for k, v in index_docs.items()}
index_word = json.loads(config.pop('index_word'))
index_word = {int(k): v for k, v in index_word.items()}
word_index = json.loads(config.pop('word_index'))
tokenizer = Tokenizer(**config)
tokenizer.word_counts = word_counts
tokenizer.word_docs = word_docs
tokenizer.index_docs = index_docs
tokenizer.word_index = word_index
tokenizer.index_word = index_word
return tokenizer
def loadTokenzier(self, directory):
with open(directory, encoding='UTF-8-sig') as fh:
data = json.load(fh)
tk = Tokenizer()
key = list(data.keys())
for i in key:
setattr(tk, i, data[i])
VOCAB_SIZE = len(tk.word_index) + 1
self.START_TOKEN, self.END_TOKEN = [VOCAB_SIZE], [VOCAB_SIZE + 1]
self.VOCAB_SIZE = VOCAB_SIZE + 2
# 토크나이저 로드하면 모든 key,value가 string으로 들어감 나중에 토큰을 텍스트로
# 복원할 때 정상적으로 구동하기 위해서 index_word는 key를 int로 바꿔줌
tk.index_word = {int(k): v for k, v in tk.index_word.items()}
return tk
def tokenizer_from_json(json_string):
tokenizer_config = json.loads(json_string)
config = tokenizer_config.get('config')
word_counts = json.loads(config.pop('word_counts'))
word_docs = json.loads(config.pop('word_docs'))
index_docs = json.loads(config.pop('index_docs'))
# Integer indexing gets converted to strings with json.dumps()
index_docs = {int(k): v for k, v in index_docs.items()}
index_word = json.loads(config.pop('index_word'))
index_word = {int(k): v for k, v in index_word.items()}
word_index = json.loads(config.pop('word_index'))
tokenizer = Tokenizer(**config)
tokenizer.word_counts = word_counts
tokenizer.word_docs = word_docs
tokenizer.index_docs = index_docs
tokenizer.word_index = word_index
tokenizer.index_word = index_word
return tokenizer
word_counts = json.loads(config.pop('word_counts'))
word_docs = json.loads(config.pop('word_docs'))
index_docs = json.loads(config.pop('index_docs'))
# Integer indexing gets converted to strings with json.dumps()
index_docs = {int(k): v for k, v in index_docs.items()}
index_word = json.loads(config.pop('index_word'))
index_word = {int(k): v for k, v in index_word.items()}
word_index = json.loads(config.pop('word_index'))
tokenizer = Tokenizer(**config)
tokenizer.word_counts = word_counts
tokenizer.word_docs = word_docs
tokenizer.index_docs = index_docs
tokenizer.word_index = word_index
tokenizer.index_word = index_word
return tokenizer
def create_tf_example_row(input_row):
# convert to string
password = str(input_row[0])
# create tf example
tf_example = tf.train.Example(features=tf.train.Features(feature={