import random
def code2index(tokens, token2idx, mask_token=None):
output_tokens = []
for i, token in enumerate(tokens):
if token==mask_token:
output_tokens.append(token2idx['UNK'])
else:
output_tokens.append(token2idx.get(token, token2idx['UNK']))
return tokens, output_tokens
def random_mask(tokens, token2idx):
output_label = []
output_token = []
for i, token in enumerate(tokens):
prob = random.random()
# mask token with 15% probability
if prob < 0.15:
prob /= 0.15
# 80% randomly change token to mask token
if prob < 0.8:
output_token.append(token2idx["MASK"])
# 10% randomly change token to random token
elif prob < 0.9:
output_token.append(random.choice(list(token2idx.values())))
# -> rest 10% randomly keep current token
# append current token to output (we will predict these later
output_label.append(token2idx.get(token, token2idx['UNK']))
else:
# no masking token (will be ignored by loss function later)
output_label.append(-1)
output_token.append(token2idx.get(token, token2idx['UNK']))
return tokens, output_token, output_label
def index_seg(tokens, symbol='SEP'):
flag = 0
seg = []
for token in tokens:
if token == symbol:
seg.append(flag)
if flag == 0:
flag = 1
else:
flag = 0
else:
seg.append(flag)
return seg
def position_idx(tokens, symbol='SEP'):
pos = []
flag = 0
for token in tokens:
if token == symbol:
pos.append(flag)
flag += 1
else:
pos.append(flag)
return pos
def seq_padding(tokens, max_len, token2idx=None, symbol=None, unkown=True):
if symbol is None:
symbol = 'PAD'
seq = []
token_len = len(tokens)
for i in range(max_len):
if token2idx is None:
if i < token_len:
seq.append(tokens[i])
else:
seq.append(symbol)
else:
if i < token_len:
# 1 indicate UNK
if unkown:
seq.append(token2idx.get(tokens[i], token2idx['UNK']))
else:
seq.append(token2idx.get(tokens[i]))
else:
seq.append(token2idx.get(symbol))
return seq