





import unittest

from transformers import RoFormerTokenizer, RoFormerTokenizerFast
from transformers.testing_utils import require_rjieba, require_tokenizers

from ...test_tokenization_common import TokenizerTesterMixin

@require_rjieba
@require_tokenizers
class       __A     (						a    ,					unittest.TestCase    ):
				__A      =				RoFormerTokenizer
				__A      =				RoFormerTokenizerFast
				__A      =				True
				__A      =				True


				def _snake_case       (		self							):
								super().setUp()


				def _snake_case       (		self   , **UpperCAmelCase_							):
								return self.tokenizer_class.from_pretrained("""junnyu/roformer_chinese_base"""   , **__UpperCamelCase							)


				def _snake_case       (		self   , **UpperCAmelCase_							):
								return self.rust_tokenizer_class.from_pretrained("""junnyu/roformer_chinese_base"""   , **__UpperCamelCase							)


				def _snake_case       (		self							):
								lowerCamelCase	 ="""永和服装饰品有限公司,今天天气非常好"""
								lowerCamelCase	 ="""永和 服装 饰品 有限公司 , 今 天 天 气 非常 好"""
								return input_text, output_text


				def _snake_case       (		self							):
								lowerCamelCase	 =self.get_tokenizer()
								lowerCamelCase ,  lowerCamelCase	 =self.get_chinese_input_output_texts()
								lowerCamelCase	 =tokenizer.tokenize(__UpperCamelCase							)

								self.assertListEqual(__UpperCamelCase   , output_text.split()							)

								lowerCamelCase	 =tokens + [tokenizer.unk_token]
								lowerCamelCase	 =[22943, 21332, 34431, 45904, 117, 306, 1231, 1231, 2653, 33994, 1266, 100]
								self.assertListEqual(tokenizer.convert_tokens_to_ids(__UpperCamelCase							)   , __UpperCamelCase							)


				def _snake_case       (		self							):
								lowerCamelCase	 =self.get_rust_tokenizer()
								lowerCamelCase ,  lowerCamelCase	 =self.get_chinese_input_output_texts()
								lowerCamelCase	 =tokenizer.tokenize(__UpperCamelCase							)
								self.assertListEqual(__UpperCamelCase   , output_text.split()							)
								lowerCamelCase	 =tokens + [tokenizer.unk_token]
								lowerCamelCase	 =[22943, 21332, 34431, 45904, 117, 306, 1231, 1231, 2653, 33994, 1266, 100]
								self.assertListEqual(tokenizer.convert_tokens_to_ids(__UpperCamelCase							)   , __UpperCamelCase							)


				def _snake_case       (		self							):
								pass


				def _snake_case       (		self							):
								pass


				def _snake_case       (		self							):
								pass












import fire
from torch.utils.data import DataLoader
from tqdm import tqdm

from transformers import AutoTokenizer
from utils import SeqaSeqDataset, pickle_save





def      _lowercase					(						_UpperCAmelCase			,      _UpperCAmelCase			,      _UpperCAmelCase=10_24			,      _UpperCAmelCase=10_24			,      _UpperCAmelCase=False			,      **_UpperCAmelCase				)						->  Optional[Any]:
				lowerCamelCase	 =AutoTokenizer.from_pretrained(_UpperCAmelCase				)
				lowerCamelCase	 =SeqaSeqDataset(_UpperCAmelCase			,      _UpperCAmelCase			,      _UpperCAmelCase			,      _UpperCAmelCase			,      type_path="""train"""			,      **_UpperCAmelCase				)
				lowerCamelCase	 =tok.pad_token_id

				def get_lens(_UpperCAmelCase				):
								lowerCamelCase	 =tqdm(
								    DataLoader(_UpperCAmelCase			,      batch_size=5_12			,      num_workers=8			,      shuffle=_UpperCAmelCase			,      collate_fn=ds.collate_fn				)			,      desc=str(ds.len_file				)			,      )
								lowerCamelCase	 =[]
								for batch in dl:
												lowerCamelCase	 =batch["""input_ids"""].ne(_UpperCAmelCase				).sum(1				).tolist()
												lowerCamelCase	 =batch["""labels"""].ne(_UpperCAmelCase				).sum(1				).tolist()
												if consider_target:
																for src, tgt in zip(_UpperCAmelCase			,      _UpperCAmelCase				):
																				max_lens.append(max(_UpperCAmelCase			,      _UpperCAmelCase				)				)
												else:
																max_lens.extend(_UpperCAmelCase				)
								return max_lens

				lowerCamelCase	 =get_lens(_UpperCAmelCase				)
				lowerCamelCase	 =SeqaSeqDataset(_UpperCAmelCase			,      _UpperCAmelCase			,      _UpperCAmelCase			,      _UpperCAmelCase			,      type_path="""val"""			,      **_UpperCAmelCase				)
				lowerCamelCase	 =get_lens(_UpperCAmelCase				)
				pickle_save(_UpperCAmelCase			,      train_ds.len_file				)
				pickle_save(_UpperCAmelCase			,      val_ds.len_file				)


if __name__ == "__main__":
							fire.Fire(save_len_file)





