
import argparse
import json
from typing import List

from ltp import LTP

from transformers.models.bert.tokenization_bert import BertTokenizer




def 							a		(				snake_case__:   Tuple   ):


				'''simple docstring'''
				# This defines a "chinese character" as anything in the CJK Unicode block:
				#   https://en.wikipedia.org/wiki/CJK_Unified_Ideographs_(Unicode_block)
				#
				# Note that the CJK Unicode block is NOT all Japanese and Korean characters,
				# despite its name. The modern Korean Hangul alphabet is a different block,
				# as is Japanese Hiragana and Katakana. Those alphabets are used to write
				# space-separated words, so they are not treated specially and handled
				# like the all of the other languages.
				if (
				    (cp >= 0X4_E00 and cp <= 0X9_FFF)
				    or (cp >= 0X3_400 and cp <= 0X4_DBF)  #
				    or (cp >= 0X20_000 and cp <= 0X2A_6DF)  #
				    or (cp >= 0X2A_700 and cp <= 0X2B_73F)  #
				    or (cp >= 0X2B_740 and cp <= 0X2B_81F)  #
				    or (cp >= 0X2B_820 and cp <= 0X2C_EAF)  #
				    or (cp >= 0XF_900 and cp <= 0XF_AFF)
				    or (cp >= 0X2F_800 and cp <= 0X2F_A1F)  #
				):  #
								return True

				return False




def 							a		(				snake_case__:   str   ):


				'''simple docstring'''
				# word like '180' or '身高' or '神'
				for char in word:
								lowercase_	    =   ord(snake_case__   )
								if not _is_chinese_char(snake_case__   ):
												return 0
				return 1




def 							a		(				snake_case__:   List[str]   ):


				'''simple docstring'''
				lowercase_	    =   set()

				for token in tokens:
								lowercase_	    =   len(snake_case__   ) > 1 and is_chinese(snake_case__   )
								if chinese_word:
												word_set.add(snake_case__   )
				lowercase_	    =   list(snake_case__   )
				return word_list




def 							a		(				snake_case__:   List[str]		,  snake_case__:   set()   ):


				'''simple docstring'''
				if not chinese_word_set:
								return bert_tokens
				lowercase_	    =   max([len(snake_case__   ) for w in chinese_word_set]   )

				lowercase_	    =   bert_tokens
				lowercase_    ,      lowercase_	    =   0, len(snake_case__   )
				while start < end:
								lowercase_	    =   True
								if is_chinese(bert_word[start]   ):
												lowercase_	    =   min(end - start		,  snake_case__   )
												for i in range(snake_case__		,  1		,  -1   ):
																lowercase_	    =   ''''''.join(bert_word[start : start + i]   )
																if whole_word in chinese_word_set:
																				for j in range(start + 1		,  start + i   ):
																								lowercase_	    =   '''##''' + bert_word[j]
																				lowercase_	    =   start + i
																				lowercase_	    =   False
																				break
								if single_word:
												start += 1
				return bert_word




def 							a		(				snake_case__:   List[str]		,  snake_case__:   LTP		,  snake_case__:   BertTokenizer   ):


				'''simple docstring'''
				lowercase_	    =   []

				for i in range(0		,  len(snake_case__   )		,  100   ):
								lowercase_	    =   ltp_tokenizer.pipeline(lines[i : i + 100]		,  tasks=['''cws''']   ).cws
								lowercase_	    =   [get_chinese_word(snake_case__   ) for r in res]
								ltp_res.extend(snake_case__   )
				assert len(snake_case__   ) == len(snake_case__   )

				lowercase_	    =   []
				for i in range(0		,  len(snake_case__   )		,  100   ):
								lowercase_	    =   bert_tokenizer(lines[i : i + 100]		,  add_special_tokens=snake_case__		,  truncation=snake_case__		,  max_length=512   )
								bert_res.extend(res['''input_ids''']   )
				assert len(snake_case__   ) == len(snake_case__   )

				lowercase_	    =   []
				for input_ids, chinese_word in zip(snake_case__		,  snake_case__   ):
								lowercase_	    =   []
								for id in input_ids:
												lowercase_	    =   bert_tokenizer._convert_id_to_token(snake_case__   )
												input_tokens.append(snake_case__   )
								lowercase_	    =   add_sub_symbol(snake_case__		,  snake_case__   )
								lowercase_	    =   []
								# We only save pos of chinese subwords start with ##, which mean is part of a whole word.
								for i, token in enumerate(snake_case__   ):
												if token[:2] == "##":
																lowercase_	    =   token[2:]
																# save chinese tokens' pos
																if len(snake_case__   ) == 1 and _is_chinese_char(ord(snake_case__   )   ):
																				ref_id.append(snake_case__   )
								ref_ids.append(snake_case__   )

				assert len(snake_case__   ) == len(snake_case__   )

				return ref_ids




def 							a		(				snake_case__:   Optional[int]   ):


				'''simple docstring'''
				# For Chinese (Ro)Bert, the best result is from : RoBERTa-wwm-ext (https://github.com/ymcui/Chinese-BERT-wwm)
				# If we want to fine-tune these model, we have to use same tokenizer : LTP (https://github.com/HIT-SCIR/ltp)
				with open(args.file_name		,  '''r'''		,  encoding='''utf-8'''   ) as f:
								lowercase_	    =   f.readlines()
				lowercase_	    =   [line.strip() for line in data if len(snake_case__   ) > 0 and not line.isspace()]  # avoid delimiter like '\u2029'
				lowercase_	    =   LTP(args.ltp   )  # faster in GPU device
				lowercase_	    =   BertTokenizer.from_pretrained(args.bert   )

				lowercase_	    =   prepare_ref(snake_case__		,  snake_case__		,  snake_case__   )

				with open(args.save_path		,  '''w'''		,  encoding='''utf-8'''   ) as f:
								lowercase_	    =   [json.dumps(snake_case__   ) + '''\n''' for ref in ref_ids]
								f.writelines(snake_case__   )


if __name__ == "__main__":
						__a         =   argparse.ArgumentParser(description='prepare_chinese_ref')
						parser.add_argument(
						    '--file_name',
						    required=False,
						    type=str,
						    default='./resources/chinese-demo.txt',
						    help='file need process, same as training data in lm',
						)
						parser.add_argument(
						    '--ltp',
						    required=False,
						    type=str,
						    default='./resources/ltp',
						    help='resources for LTP tokenizer, usually a path',
						)
						parser.add_argument(
						    '--bert',
						    required=False,
						    type=str,
						    default='./resources/robert',
						    help='resources for Bert tokenizer',
						)
						parser.add_argument(
						    '--save_path',
						    required=False,
						    type=str,
						    default='./resources/ref.txt',
						    help='path to save res',
						)

						__a         =   parser.parse_args()
						main(args)











import json
import os
from pathlib import Path

import pytest

from datasets.download.download_config import DownloadConfig
from datasets.download.download_manager import DownloadManager
from datasets.utils.file_utils import hash_url_to_filename


SCREAMING_SNAKE_CASE_   :      Union[str, Any]			=   '''http://www.mocksite.com/file1.txt'''
SCREAMING_SNAKE_CASE_   :      str			=   '''"text": ["foo", "foo"]'''
SCREAMING_SNAKE_CASE_   :      Optional[int]			=   '''6d8ce9aa78a471c7477201efbeabd3bb01ac2e7d100a6dc024ba1608361f90a8'''

class 		snake_case_   :







	'''simple docstring'''
	__UpperCamelCase   =		2_00
	__UpperCamelCase   =		{'''Content-Length''': '''100'''}
	__UpperCamelCase   =		{}




	def    UpperCAmelCase			(						self							:     str					,      **__lowerCamelCase							:     Optional[int]   )       -> str:

			'''simple docstring'''




			return [bytes(__lowerCamelCase					,      'utf-8'   )]





def  SCREAMING_SNAKE_CASE				(      *snake_case						,   **snake_case							)		->    int:
		return MockResponse()



@pytest.mark.parametrize('urls_type'						,   [str, list, dict]							)
def  SCREAMING_SNAKE_CASE				(      snake_case						,   snake_case						,   snake_case							)		->    Optional[Any]:
		import requests

		monkeypatch.setattr(snake_case						,   'request'						,   snake_case							)

		__lowercase											=     URL
		if issubclass(snake_case						,   snake_case							):
				__lowercase											=     url
		elif issubclass(snake_case						,   snake_case							):
				__lowercase											=     [url]
		elif issubclass(snake_case						,   snake_case							):
				__lowercase											=     {'train': url}
		__lowercase											=     'dummy'
		__lowercase											=     'downloads'
		__lowercase											=     tmp_path
		__lowercase											=     DownloadConfig(
		    cache_dir=os.path.join(snake_case						,   snake_case							)						,   use_etag=snake_case						,   )
		__lowercase											=     DownloadManager(dataset_name=snake_case						,   download_config=snake_case							)
		__lowercase											=     dl_manager.download(snake_case							)
		__lowercase											=     urls
		for downloaded_paths in [downloaded_paths]:
				if isinstance(snake_case						,   snake_case							):
						__lowercase											=     [downloaded_paths]
						__lowercase											=     [urls]
				elif isinstance(snake_case						,   snake_case							):
						assert "train" in downloaded_paths.keys()
						__lowercase											=     downloaded_paths.values()
						__lowercase											=     urls.values()
				assert downloaded_paths
				for downloaded_path, input_url in zip(snake_case						,   snake_case							):
						assert downloaded_path == dl_manager.downloaded_paths[input_url]
						__lowercase											=     Path(snake_case							)
						__lowercase											=     downloaded_path.parts
						assert parts[-1] == HASH
						assert parts[-2] == cache_subdir
						assert downloaded_path.exists()
						__lowercase											=     downloaded_path.read_text()
						assert content == CONTENT
						__lowercase											=     downloaded_path.with_suffix('.json'							)
						assert metadata_downloaded_path.exists()
						__lowercase											=     json.loads(metadata_downloaded_path.read_text()							)
						assert metadata_content == {"url": URL, "etag": None}



@pytest.mark.parametrize('paths_type'						,   [str, list, dict]							)
def  SCREAMING_SNAKE_CASE				(      snake_case						,   snake_case						,   snake_case							)		->    Union[str, Any]:
		__lowercase											=     str(snake_case							)
		if issubclass(snake_case						,   snake_case							):
				__lowercase											=     filename
		elif issubclass(snake_case						,   snake_case							):
				__lowercase											=     [filename]
		elif issubclass(snake_case						,   snake_case							):
				__lowercase											=     {'train': filename}
		__lowercase											=     'dummy'
		__lowercase											=     xz_file.parent
		__lowercase											=     'extracted'
		__lowercase											=     DownloadConfig(
		    cache_dir=snake_case						,   use_etag=snake_case						,   )
		__lowercase											=     DownloadManager(dataset_name=snake_case						,   download_config=snake_case							)
		__lowercase											=     dl_manager.extract(snake_case							)
		__lowercase											=     paths
		for extracted_paths in [extracted_paths]:
				if isinstance(snake_case						,   snake_case							):
						__lowercase											=     [extracted_paths]
						__lowercase											=     [paths]
				elif isinstance(snake_case						,   snake_case							):
						assert "train" in extracted_paths.keys()
						__lowercase											=     extracted_paths.values()
						__lowercase											=     paths.values()
				assert extracted_paths
				for extracted_path, input_path in zip(snake_case						,   snake_case							):
						assert extracted_path == dl_manager.extracted_paths[input_path]
						__lowercase											=     Path(snake_case							)
						__lowercase											=     extracted_path.parts
						assert parts[-1] == hash_url_to_filename(snake_case						,   etag=snake_case							)
						assert parts[-2] == extracted_subdir
						assert extracted_path.exists()
						__lowercase											=     extracted_path.read_text()
						__lowercase											=     text_file.read_text()
						assert extracted_file_content == expected_file_content



def  SCREAMING_SNAKE_CASE				(      snake_case						,   snake_case							)		->    int:
		assert path.endswith('.jsonl'							)
		for num_items, line in enumerate(snake_case						,   start=1							):
				__lowercase											=     json.loads(line.decode('utf-8'							)							)
				assert item.keys() == {"col_1", "col_2", "col_3"}
		assert num_items == 4



@pytest.mark.parametrize('archive_jsonl'						,   ['tar_jsonl_path', 'zip_jsonl_path']							)
def  SCREAMING_SNAKE_CASE				(      snake_case						,   snake_case							)		->    int:
		__lowercase											=     request.getfixturevalue(snake_case							)
		__lowercase											=     DownloadManager()
		for num_jsonl, (path, file) in enumerate(dl_manager.iter_archive(snake_case							)						,   start=1							):
				_test_jsonl(snake_case						,   snake_case							)
		assert num_jsonl == 2



@pytest.mark.parametrize('archive_nested_jsonl'						,   ['tar_nested_jsonl_path', 'zip_nested_jsonl_path']							)
def  SCREAMING_SNAKE_CASE				(      snake_case						,   snake_case							)		->    Any:
		__lowercase											=     request.getfixturevalue(snake_case							)
		__lowercase											=     DownloadManager()
		for num_tar, (path, file) in enumerate(dl_manager.iter_archive(snake_case							)						,   start=1							):
				for num_jsonl, (subpath, subfile) in enumerate(dl_manager.iter_archive(snake_case							)						,   start=1							):
						_test_jsonl(snake_case						,   snake_case							)
		assert num_tar == 1
		assert num_jsonl == 2



def  SCREAMING_SNAKE_CASE				(      snake_case							)		->    Dict:
		__lowercase											=     DownloadManager()
		for num_file, file in enumerate(dl_manager.iter_files(snake_case							)						,   start=1							):
				assert os.path.basename(snake_case							) == ("test.txt" if num_file == 1 else "train.txt")
		assert num_file == 2




