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data_iterator.py
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data_iterator.py
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import numpy as np
import shuffle
from util import load_dict
import data_utils
'''
Much of this code is based on the data_iterator.py of
nematus project (https://github.com/rsennrich/nematus)
'''
class TextIterator:
"""Simple Text iterator."""
def __init__(self, source, source_dict,
batch_size=128, maxlen=None,
n_words_source=-1,
skip_empty=False,
shuffle_each_epoch=False,
sort_by_length=False,
maxibatch_size=20,
):
if shuffle_each_epoch:
self.source_orig = source
self.source = shuffle.main([self.source_orig], temporary=True)
else:
self.source = data_utils.fopen(source, 'r')
self.source_dict = load_dict(source_dict)
self.batch_size = batch_size
self.maxlen = maxlen
self.skip_empty = skip_empty
self.n_words_source = n_words_source
if self.n_words_source > 0:
for key, idx in self.source_dict.items():
if idx >= self.n_words_source:
del self.source_dict[key]
self.shuffle = shuffle_each_epoch
self.sort_by_length = sort_by_length
self.shuffle = shuffle_each_epoch
self.sort_by_length = sort_by_length
self.source_buffer = []
self.k = batch_size * maxibatch_size
self.end_of_data = False
def __iter__(self):
return self
def __len__(self):
return sum([1 for _ in self])
def reset(self):
if self.shuffle:
self.source = shuffle.main([self.source_orig], temporary=True)
else:
self.source.seek(0)
def __next__(self):
if self.end_of_data:
self.end_of_data = False
self.reset()
raise StopIteration
source = []
# fill buffer, if it's empty
if len(self.source_buffer) == 0:
for k_ in range(self.k):
ss = self.source.readline()
if ss == "":
break
self.source_buffer.append(ss.strip().split())
# sort by buffer
if self.sort_by_length:
slen = np.array([len(s) for s in self.source_buffer])
sidx = slen.argsort()
_sbuf = [self.source_buffer[i] for i in sidx]
self.source_buffer = _sbuf
else:
self.source_buffer.reverse()
if len(self.source_buffer) == 0:
self.end_of_data = False
self.reset()
raise StopIteration
try:
# actual work here
while True:
# read from source file and map to word index
try:
ss = self.source_buffer.pop()
except IndexError:
break
ss = [self.source_dict[w] if w in self.source_dict
else data_utils.unk_token for w in ss]
if self.maxlen and len(ss) > self.maxlen:
continue
if self.skip_empty and (not ss):
continue
source.append(ss)
if len(source) >= self.batch_size:
break
except IOError:
self.end_of_data = True
# all sentence pairs in maxibatch filtered out because of length
if len(source) == 0:
source = self.__next__()
return source
class BiTextIterator:
"""Simple Bitext iterator."""
def __init__(self, source, target,
source_dict, target_dict,
batch_size=128,
maxlen=100,
n_words_source=-1,
n_words_target=-1,
skip_empty=False,
shuffle_each_epoch=False,
sort_by_length=True,
maxibatch_size=20):
if shuffle_each_epoch:
self.source_orig = source
self.target_orig = target
self.source, self.target = shuffle.main([self.source_orig, self.target_orig], temporary=True)
else:
self.source = data_utils.fopen(source, 'r')
self.target = data_utils.fopen(target, 'r')
self.source_dict = load_dict(source_dict)
self.target_dict = load_dict(target_dict)
self.batch_size = batch_size
self.maxlen = maxlen
self.skip_empty = skip_empty
self.n_words_source = n_words_source
self.n_words_target = n_words_target
if self.n_words_source > 0:
for key, idx in self.source_dict.items():
if idx >= self.n_words_source:
del self.source_dict[key]
if self.n_words_target > 0:
for key, idx in self.target_dict.items():
if idx >= self.n_words_target:
del self.target_dict[key]
self.shuffle = shuffle_each_epoch
self.sort_by_length = sort_by_length
self.source_buffer = []
self.target_buffer = []
self.k = batch_size * maxibatch_size
self.end_of_data = False
def __iter__(self):
return self
def __len__(self):
return sum([1 for _ in self])
def reset(self):
if self.shuffle:
self.source, self.target = shuffle.main([self.source_orig, self.target_orig], temporary=True)
else:
self.source.seek(0)
self.target.seek(0)
def __next__(self):
if self.end_of_data:
self.end_of_data = False
self.reset()
raise StopIteration
source = []
target = []
# fill buffer, if it's empty
assert len(self.source_buffer) == len(self.target_buffer), 'Buffer size mismatch!'
if len(self.source_buffer) == 0:
for k_ in range(self.k):
ss = self.source.readline()
if ss == "":
break
tt = self.target.readline()
if tt == "":
break
self.source_buffer.append(ss.strip().split())
self.target_buffer.append(tt.strip().split())
# sort by target buffer
if self.sort_by_length:
tlen = np.array([len(t) for t in self.target_buffer])
tidx = tlen.argsort()
_sbuf = [self.source_buffer[i] for i in tidx]
_tbuf = [self.target_buffer[i] for i in tidx]
self.source_buffer = _sbuf
self.target_buffer = _tbuf
else:
self.source_buffer.reverse()
self.target_buffer.reverse()
if len(self.source_buffer) == 0 or len(self.target_buffer) == 0:
self.end_of_data = False
self.reset()
raise StopIteration
try:
# actual work here
while True:
# read from source file and map to word index
try:
ss = self.source_buffer.pop()
except IndexError:
break
ss = [self.source_dict[w] if w in self.source_dict
else data_utils.unk_token for w in ss]
# read from source file and map to word index
tt = self.target_buffer.pop()
tt = [self.target_dict[w] if w in self.target_dict
else data_utils.unk_token for w in tt]
if self.n_words_target > 0:
tt = [w if w < self.n_words_target
else data_utils.unk_token for w in tt]
if self.maxlen:
if len(ss) > self.maxlen and len(tt) > self.maxlen:
continue
if self.skip_empty and (not ss or not tt):
continue
source.append(ss)
target.append(tt)
if len(source) >= self.batch_size or \
len(target) >= self.batch_size:
break
except IOError:
self.end_of_data = True
# all sentence pairs in maxibatch filtered out because of length
if len(source) == 0 or len(target) == 0:
source, target = self.__next__()
return source, target