Как интегрировать трансформаторы HuggingFace с Torchtext BPTTIterator? - PullRequest
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Как интегрировать трансформаторы HuggingFace с Torchtext BPTTIterator?

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/ 21 октября 2019

Я пытаюсь использовать предварительно обученный токенизатор из HuggingFace Transformer-XL при обучении моей пользовательской модели трансформатора-XL на WikiText2, и у меня возникают проблемы с работой BPTTIterator из Torchtext. Ошибка возникает в самой последней строке next(iter(train_iter))

Ниже мой код: 

# Import packages 
import torch
import torch.nn as nn
import torch.nn.functional as F
from transformers import AdamW, WarmupLinearSchedule
from transformers import TransfoXLConfig, TransfoXLTokenizer, TransfoXLModel,TransfoXLLMHeadModel 
import torchtext
import torchtext.data.utils 
from torchtext.data import Field, BPTTIterator
import random
import time

# set hyperparameters for this experiment
bptt = 30
batch_size = 64
lr = 0.01 # learning rate

# load the pretrained tokenizer
tokenizer = TransfoXLTokenizer.from_pretrained('transfo-xl-wt103', do_lower_case=True)

# for huggingface - torchtext integration
tokenizer.mask_token = 'maskTok'
tokenizer.pad_token = '<pad>'
tokenizer.eos_token = '<eos>'
tokenizer.unk_token = '<unk>'
tokenizer.bos_token = '<sos>'

pad_index = tokenizer.convert_tokens_to_ids(tokenizer.pad_token)
eos_index = tokenizer.convert_tokens_to_ids(tokenizer.eos_token)
unk_index = tokenizer.convert_tokens_to_ids(tokenizer.unk_token)
mask_index = tokenizer.convert_tokens_to_ids(tokenizer.mask_token)
bos_index = tokenizer.convert_tokens_to_ids(tokenizer.bos_token)

# for huggingface - torchtext integration
tokenizer.mask_token = 'maskTok'
tokenizer.pad_token = '<pad>'
tokenizer.eos_token = '<eos>'
tokenizer.unk_token = '<unk>'
tokenizer.bos_token = '<sos>'

pad_index = tokenizer.convert_tokens_to_ids(tokenizer.pad_token)
eos_index = tokenizer.convert_tokens_to_ids(tokenizer.eos_token)
unk_index = tokenizer.convert_tokens_to_ids(tokenizer.unk_token)
mask_index = tokenizer.convert_tokens_to_ids(tokenizer.mask_token)
bos_index = tokenizer.convert_tokens_to_ids(tokenizer.bos_token)

# load WikiText-2 dataset and split it into train and test set
train_Wiki2, val_Wiki2, test_Wiki2 = torchtext.datasets.WikiText2.splits(TEXT)


# extract total number of tokens in the vocabulary
ntokens = tokenizer.vocab_size

# define transformer-XL configuration.
transfoXLconfig = TransfoXLConfig(vocab_size_or_config_json_file = ntokens,
                                  cutoffs = [20000, 40000, 200000], 
                                  d_model = 1024, 
                                  d_embed = 1024, 
                                  n_head = 16, 
                                  d_head = 64,
                                  n_layer = 5,
                                  dropout = 0.1,
                                  attn_type = 0,
                                  output_hidden_states = True,
                                  output_attentions = True)

model = TransfoXLLMHeadModel(config = transfoXLconfig)
model.resize_token_embeddings(len(tokenizer))

train_iter, test_iter = BPTTIterator.splits(
            (train_Wiki2, test_Wiki2),
            batch_size = batch_size,
            bptt_len= bptt,
            shuffle = False,
            repeat=False)

# error occurs here; the error message is:
#  File "/Users/jin-dominique/anaconda3/lib/python3.7/site-packages/torchtext/data/field.py", 
# line 359, in numericalize
# var = torch.tensor(arr, dtype=self.dtype, device=device)
# "TypeError: an integer is required (got type str)"
train = next(iter(train_iter))
test = next(iter(test_iter))

Как я могу исправить свою ошибку? Спасибо,

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