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# Copyright (c) 2023, NVIDIA CORPORATION. All rights reserved.
import os
import torch
import types
from megatron import get_retro_args
from megatron.tokenizer.tokenizer import (
_BertWordPieceTokenizer,
_GPT2BPETokenizer,
_GPTSentencePieceTokenizer,
)
def get_args_path(workdir):
'''Argument copy stored within retro workdir.'''
return os.path.join(workdir, "args.json")
def get_num_chunks_per_sample():
'''Compute seq_length // chunk_length.'''
args = get_retro_args()
sample_length = args.retro_gpt_seq_length
chunk_length = args.retro_gpt_chunk_length
assert sample_length % chunk_length == 0
return sample_length // chunk_length
def get_gpt_tokenizer():
'''GPT (BPE) tokenizer.'''
args = get_retro_args()
tokenizer_type = args.retro_gpt_tokenizer_type
if tokenizer_type == "GPT2BPETokenizer":
assert args.retro_gpt_vocab_file and args.retro_gpt_merge_file
return _GPT2BPETokenizer(
vocab_file=args.retro_gpt_vocab_file,
merge_file=args.retro_gpt_merge_file,
)
elif tokenizer_type == 'GPTSentencePieceTokenizer':
assert args.retro_gpt_tokenizer_model is not None
return _GPTSentencePieceTokenizer(args.retro_gpt_tokenizer_model)
else:
raise Exception("unrecognized gpt tokenizer, '%s'." % tokenizer_type)
def get_bert_tokenizer():
'''Bert (Wordpiece) tokenizer.'''
args = get_retro_args()
lower_case = {
"BertWordPieceLowerCase" : True,
"BertWordPieceCase" : False,
}[args.retro_bert_tokenizer_type]
return _BertWordPieceTokenizer(
vocab_file=args.retro_bert_vocab_file,
lower_case=lower_case,
)
class GPTToTextDataset(torch.utils.data.Dataset):
'''Dataset to convert GPT tokens to text.'''
def __init__(self, gpt_dataset):
super().__init__()
self.gpt_dataset = gpt_dataset
self.gpt_tokenizer = get_gpt_tokenizer()
def __len__(self):
return len(self.gpt_dataset)
def __getitem__(self, idx):
gpt_token_ids = self.gpt_dataset[idx]["text"].tolist()
text = self.gpt_tokenizer.detokenize(gpt_token_ids)
return {"text": text}
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