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Update dataloader.py and dataset.py #305

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Update dataloader.py and dataset.py #305

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4aca8cb
Update dataloader.py
liujiachi1997 May 1, 2022
93df5d4
Update dataset.py
liujiachi1997 May 1, 2022
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45 changes: 29 additions & 16 deletions uer/utils/dataloader.py
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Original file line number Diff line number Diff line change
Expand Up @@ -72,23 +72,27 @@ def __iter__(self):
masked_words_num = 0

for ins in instances:
src_single, pad_num = ins[0]
for _ in range(pad_num):
src_single.append(self.vocab.get(PAD_TOKEN))

if len(ins) == 4:
src.append(ins[0])
src.append(src_single)
masked_words_num += len(ins[1])
tgt_mlm.append([0] * len(ins[0]))
tgt_mlm.append([0] * len(src_single))
for mask in ins[1]:
tgt_mlm[-1][mask[0]] = mask[1]
is_next.append(ins[2])
seg.append([1] * ins[3][0] + [2] * (ins[3][1] - ins[3][0]) + [0] * (len(ins[0]) - ins[3][1]))
seg.append([1] * ins[3][0] + [2] * (ins[3][1] - ins[3][0]) + [0] * (pad_num))
else:
src_single, tgt_mlm_single = mask_seq(ins[0], self.tokenizer, self.whole_word_masking, self.span_masking, self.span_geo_prob, self.span_max_length)
tgt_mlm.append([0] * len(src_single))
src_single, tgt_mlm_single = mask_seq(src_single, self.tokenizer, self.whole_word_masking, self.span_masking, self.span_geo_prob, self.span_max_length)
masked_words_num += len(tgt_mlm_single)
src.append(src_single)
tgt_mlm.append([0] * len(ins[0]))
for mask in tgt_mlm_single:
tgt_mlm[-1][mask[0]] = mask[1]
is_next.append(ins[1])
seg.append([1] * ins[2][0] + [2] * (ins[2][1] - ins[2][0]) + [0] * (len(ins[0]) - ins[2][1]))
seg.append([1] * ins[2][0] + [2] * (ins[2][1] - ins[2][0]) + [0] * (pad_num))

if masked_words_num == 0:
continue
Expand Down Expand Up @@ -118,21 +122,25 @@ def __iter__(self):
masked_words_num = 0

for ins in instances:
src_single, pad_num = ins[0]
for _ in range(pad_num):
src_single.append(self.vocab.get(PAD_TOKEN))

if len(ins) == 3:
src.append(ins[0])
src.append(src_single)
masked_words_num += len(ins[1])
tgt.append([0] * len(ins[0]))
tgt.append([0] * len(src_single))
for mask in ins[1]:
tgt[-1][mask[0]] = mask[1]
seg.append([1] * ins[2][0] + [0] * (len(ins[0]) - ins[2][0]))
seg.append([1] * ins[2][0] + [0] * (pad_num))
else:
src_single, tgt_single = mask_seq(ins[0], self.tokenizer, self.whole_word_masking, self.span_masking, self.span_geo_prob, self.span_max_length)
tgt.append([0] * len(src_single))
src_single, tgt_single = mask_seq(src_single, self.tokenizer, self.whole_word_masking, self.span_masking, self.span_geo_prob, self.span_max_length)
masked_words_num += len(tgt_single)
src.append(src_single)
tgt.append([0] * len(ins[0]))
for mask in tgt_single:
tgt[-1][mask[0]] = mask[1]
seg.append([1] * ins[1][0] + [0] * (len(ins[0]) - ins[1][0]))
seg.append([1] * ins[1][0] + [0] * (pad_num))

if masked_words_num == 0:
continue
Expand All @@ -142,6 +150,7 @@ def __iter__(self):
torch.LongTensor(seg)



class AlbertDataloader(BertDataloader):
'''
AlbertDataloader can reuse the code of BertDataloader.
Expand All @@ -166,12 +175,16 @@ def __iter__(self):
seg = []

for ins in instances:
src.append(ins[0][:-1])
tgt.append(ins[0][1:])
if ins[1] == len(ins[0]):
src_single, pad_num = ins[0]
if ins[1] == len(src_single):
seg.append([1] * (ins[1] - 1))
else:
seg.append([1] * ins[1] + [0] * (len(ins[0]) - 1 - ins[1]))
for _ in range(pad_num):
src_single.append(self.vocab.get(PAD_TOKEN))
seg.append([1] * ins[1] + [0] * (pad_num - 1))

src.append(src_single[:-1])
tgt.append(src_single[1:])

yield torch.LongTensor(src), \
torch.LongTensor(tgt), \
Expand Down
22 changes: 15 additions & 7 deletions uer/utils/dataset.py
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Original file line number Diff line number Diff line change
Expand Up @@ -205,13 +205,16 @@ def create_ins_from_doc(self, all_documents, document_index):
src.append(self.vocab.get(SEP_TOKEN))
seg_pos.append(len(src))

while len(src) != self.seq_length:
src.append(self.vocab.get(PAD_TOKEN))

pad_num = 0
if len(src) != self.seq_length:
pad_num = self.seq_length - len(src)

if not self.dynamic_masking:
src, tgt_mlm = mask_seq(src, self.tokenizer, self.whole_word_masking, self.span_masking, self.span_geo_prob, self.span_max_length)
src = (src, pad_num)
instance = (src, tgt_mlm, is_random_next, seg_pos)
else:
src = (src, pad_num)
instance = (src, is_random_next, seg_pos)

instances.append(instance)
Expand Down Expand Up @@ -290,22 +293,26 @@ def build_instances(self, all_documents):

if not self.dynamic_masking:
src, tgt = mask_seq(src, self.tokenizer, self.whole_word_masking, self.span_masking, self.span_geo_prob, self.span_max_length)
src = (src, 0)
instance = (src, tgt, seg_pos)
else:
src = (src, 0)
instance = (src, seg_pos)

instances.append(instance)

src = all_documents[instances_num * self.seq_length:]
seg_pos = [len(src)]

while len(src) != self.seq_length:
src.append(self.vocab.get(PAD_TOKEN))
if len(src) != self.seq_length:
pad_num = self.seq_length - len(src)

if not self.dynamic_masking:
src, tgt = mask_seq(src, self.tokenizer, self.whole_word_masking, self.span_masking, self.span_geo_prob, self.span_max_length)
src = (src, pad_num)
instance = (src, tgt, seg_pos)
else:
src = (src, pad_num)
instance = (src, seg_pos)

instances.append(instance)
Expand Down Expand Up @@ -442,13 +449,14 @@ def worker(self, proc_id, start, end):
for i in range(instances_num):
src = document[i * (self.seq_length + 1): (i + 1) * (self.seq_length + 1)]
seg_pos = self.seq_length
src = (src, 0)
pickle.dump((src, seg_pos), dataset_writer)

src = document[instances_num * (self.seq_length + 1):]
if len(src) > 0:
seg_pos = len(src)
while len(src) != self.seq_length + 1:
src.append(self.vocab.get(PAD_TOKEN))
pad_num = self.seq_length - len(src) + 1
src = (src, pad_num)
pickle.dump((src, seg_pos), dataset_writer)

if pos >= end:
Expand Down