





'''simple docstring'''


# this script builds a small sample spm file tests/fixtures/test_sentencepiece_no_bos.model, with features needed by pegasus

# 1. pip install sentencepiece
#
# 2. wget https://raw.githubusercontent.com/google/sentencepiece/master/data/botchan.txt

# 3. build
import sentencepiece as spm

# pegasus:
# 1. no bos
# 2. eos_id is 1
# 3. unk_id is 2
# build a sample spm file accordingly
spm.SentencePieceTrainer.train(
    '--input=botchan.txt --model_prefix=test_sentencepiece_no_bos --bos_id=-1 --unk_id=2  --eos_id=1  --vocab_size=1000'
)

# 4. now update the fixture
# mv test_sentencepiece_no_bos.model ../../tests/fixtures/








'''simple docstring'''


import sys

from transformers import AutoTokenizer


_lowerCamelCase					:						Any					     =							sys.argv[1]
_lowerCamelCase					:						Union[str, Any]					     =							sys.argv[2]
_lowerCamelCase					:						Optional[Any]					     =							int(sys.argv[3])

_lowerCamelCase					:						Union[str, Any]					     =							0

_lowerCamelCase					:						Tuple					     =							AutoTokenizer.from_pretrained(model_name_or_path)
max_len -= tokenizer.num_special_tokens_to_add()

with open(dataset, 'rt') as f_p:
				for line in f_p:
								_lowerCamelCase					:						Optional[int]					     =							line.rstrip()

								if not line:
												print(line)
												_lowerCamelCase					:						Optional[int]					     =							0
												continue

								_lowerCamelCase					:						int					     =							line.split()[0]

								_lowerCamelCase					:						Union[str, Any]					     =							len(tokenizer.tokenize(token))

								# Token contains strange control characters like \x96 or \x95
								# Just filter out the complete line
								if current_subwords_len == 0:
												continue

								if (subword_len_counter + current_subwords_len) > max_len:
												print('')
												print(line)
												_lowerCamelCase					:						Optional[int]					     =							current_subwords_len
												continue

								subword_len_counter += current_subwords_len

								print(line)

