





import itertools
import json
import linecache
import os
import pickle
import re
import socket
import string
from collections import Counter
from logging import getLogger
from pathlib import Path
from typing import Callable, Dict, Iterable, List

import git
import torch
from torch.utils.data import Dataset

from transformers import BartTokenizer, RagTokenizer, TaTokenizer







def     A__   (  lowerCamelCase       ,      lowerCamelCase       ,      lowerCamelCase       ,      lowerCamelCase       ,      lowerCamelCase=True       ,      lowerCamelCase="pt"  )					->		Any:
				UpperCamelCase_:							Union[str, Any]		=  {"add_prefix_space": True} if isinstance(_lowerCAmelCase       ,      _lowerCAmelCase  ) and not line.startswith(""" """  ) else {}
				UpperCamelCase_:							Dict		=  padding_side
				return tokenizer(
				    [line]       ,      max_length=_lowerCAmelCase       ,      padding="""max_length""" if pad_to_max_length else None       ,      truncation=_lowerCAmelCase       ,      return_tensors=_lowerCAmelCase       ,      add_special_tokens=_lowerCAmelCase       ,      **_lowerCAmelCase       ,      )







def     A__   (  lowerCamelCase       ,      lowerCamelCase       ,      lowerCamelCase=None       ,      )					->		str:
				UpperCamelCase_:							Optional[Any]		=  input_ids.ne(_lowerCAmelCase  ).any(dim=0  )
				if attention_mask is None:
								return input_ids[:, keep_column_mask]
				else:
								return (input_ids[:, keep_column_mask], attention_mask[:, keep_column_mask])

class     _UpperCamelCase			(   lowerCamelCase__					):






			'''simple docstring'''

			def __init__(    self	:    List[Any]  ,		snake_case_	:    List[Any]  ,		snake_case_	:    str  ,		snake_case_	:    str  ,		snake_case_	:    Dict  ,		snake_case_	:    Any="train"  ,		snake_case_	:    List[Any]=None  ,		snake_case_	:    Tuple=None  ,		snake_case_	:    int=None  ,		snake_case_	:    Any=""  ,		):
							super().__init__()
							UpperCamelCase_:							List[str]		=  Path(snake_case_ ).joinpath(type_path + """.source""" )
							UpperCamelCase_:							Any		=  Path(snake_case_ ).joinpath(type_path + """.target""" )
							UpperCamelCase_:							str		=  self.get_char_lens(self.src_file )
							UpperCamelCase_:							Tuple		=  max_source_length
							UpperCamelCase_:							int		=  max_target_length
							assert min(self.src_lens ) > 0, f'''found empty line in {self.src_file}'''
							UpperCamelCase_:							str		=  tokenizer
							UpperCamelCase_:							List[Any]		=  prefix
							if n_obs is not None:
											UpperCamelCase_:							List[str]		=  self.src_lens[:n_obs]
							UpperCamelCase_:							Any		=  src_lang
							UpperCamelCase_:							Tuple		=  tgt_lang

			def __len__(    self	:    Union[str, Any] ):
							return len(self.src_lens )

			def __getitem__(    self	:    List[str]  ,		snake_case_	:    List[Any] ):
							UpperCamelCase_:							Optional[int]		=  index + 1  # linecache starts at 1
							UpperCamelCase_:							Optional[int]		=  self.prefix + linecache.getline(str(self.src_file )  ,		snake_case_ ).rstrip("""\n""" )
							UpperCamelCase_:							Union[str, Any]		=  linecache.getline(str(self.tgt_file )  ,		snake_case_ ).rstrip("""\n""" )
							assert source_line, f'''empty source line for index {index}'''
							assert tgt_line, f'''empty tgt line for index {index}'''

							# Need to add eos token manually for T5
							if isinstance(self.tokenizer  ,		snake_case_ ):
											source_line += self.tokenizer.eos_token
											tgt_line += self.tokenizer.eos_token

							# Pad source and target to the right
							UpperCamelCase_:							Tuple		=  (
							    self.tokenizer.question_encoder if isinstance(self.tokenizer  ,		snake_case_ ) else self.tokenizer
							)
							UpperCamelCase_:							Union[str, Any]		=  self.tokenizer.generator if isinstance(self.tokenizer  ,		snake_case_ ) else self.tokenizer

							UpperCamelCase_:							int		=  encode_line(snake_case_  ,		snake_case_  ,		self.max_source_length  ,		"""right""" )
							UpperCamelCase_:							Optional[int]		=  encode_line(snake_case_  ,		snake_case_  ,		self.max_target_length  ,		"""right""" )

							UpperCamelCase_:							str		=  source_inputs["input_ids"].squeeze()
							UpperCamelCase_:							Union[str, Any]		=  target_inputs["input_ids"].squeeze()
							UpperCamelCase_:							Dict		=  source_inputs["attention_mask"].squeeze()
							return {
							    "input_ids": source_ids,
							    "attention_mask": src_mask,
							    "decoder_input_ids": target_ids,
							}

			@staticmethod
			def  lowerCAmelCase__		(    snake_case_	:    Optional[int] ):
							return [len(snake_case_ ) for x in Path(snake_case_ ).open().readlines()]




			def  lowerCAmelCase__		(    self	:    Tuple  ,		snake_case_	:    Union[str, Any] ):
							UpperCamelCase_:							List[Any]		=  torch.stack([x["""input_ids"""] for x in batch] )
							UpperCamelCase_:							Tuple		=  torch.stack([x["""attention_mask"""] for x in batch] )
							UpperCamelCase_:							int		=  torch.stack([x["""decoder_input_ids"""] for x in batch] )
							UpperCamelCase_:							Union[str, Any]		=  (
							    self.tokenizer.generator.pad_token_id
							    if isinstance(self.tokenizer  ,		snake_case_ )
							    else self.tokenizer.pad_token_id
							)
							UpperCamelCase_:							Union[str, Any]		=  (
							    self.tokenizer.question_encoder.pad_token_id
							    if isinstance(self.tokenizer  ,		snake_case_ )
							    else self.tokenizer.pad_token_id
							)
							UpperCamelCase_:							Optional[Any]		=  trim_batch(snake_case_  ,		snake_case_ )
							UpperCamelCase_:							Optional[int]		=  trim_batch(snake_case_  ,		snake_case_  ,		attention_mask=snake_case_ )
							UpperCamelCase_:							str		=  {
							    "input_ids": source_ids,
							    "attention_mask": source_mask,
							    "decoder_input_ids": y,
							}
							return batch




lowerCamelCase_  :	Tuple 				=					getLogger(__name__)







def     A__   (  lowerCamelCase  )					->		Union[str, Any]:
				return list(itertools.chain.from_iterable(_lowerCAmelCase  )  )







def     A__   (  lowerCamelCase  )					->		None:
				UpperCamelCase_:							List[Any]		=  get_git_info()
				save_json(_lowerCAmelCase       ,      os.path.join(_lowerCAmelCase       ,      """git_log.json"""  )  )







def     A__   (  lowerCamelCase       ,      lowerCamelCase       ,      lowerCamelCase=4       ,      **lowerCamelCase  )					->		Dict:
				with open(_lowerCAmelCase       ,      """w"""  ) as f:
								json.dump(_lowerCAmelCase       ,      _lowerCAmelCase       ,      indent=_lowerCAmelCase       ,      **_lowerCAmelCase  )







def     A__   (  lowerCamelCase  )					->		List[str]:
				with open(_lowerCAmelCase  ) as f:
								return json.load(_lowerCAmelCase  )







def     A__   (  )					->		int:
				UpperCamelCase_:							Tuple		=  git.Repo(search_parent_directories=_lowerCAmelCase  )
				UpperCamelCase_:							List[str]		=  {
				    "repo_id": str(_lowerCAmelCase  ),
				    "repo_sha": str(repo.head.object.hexsha  ),
				    "repo_branch": str(repo.active_branch  ),
				    "hostname": str(socket.gethostname()  ),
				}
				return repo_infos







def     A__   (  lowerCamelCase       ,      lowerCamelCase  )					->		List:
				return list(map(_lowerCAmelCase       ,      _lowerCAmelCase  )  )







def     A__   (  lowerCamelCase       ,      lowerCamelCase  )					->		int:
				with open(_lowerCAmelCase       ,      """wb"""  ) as f:
								return pickle.dump(_lowerCAmelCase       ,      _lowerCAmelCase  )







def     A__   (  lowerCamelCase  )					->		Union[str, Any]:

				def remove_articles(lowerCamelCase  ):
								return re.sub(r"""\b(a|an|the)\b"""       ,      """ """       ,      _lowerCAmelCase  )

				def white_space_fix(lowerCamelCase  ):
								return " ".join(text.split()  )

				def remove_punc(lowerCamelCase  ):
								UpperCamelCase_:							Tuple		=  set(string.punctuation  )
								return "".join(ch for ch in text if ch not in exclude  )

				def lower(lowerCamelCase  ):
								return text.lower()

				return white_space_fix(remove_articles(remove_punc(lower(_lowerCAmelCase  )  )  )  )







def     A__   (  lowerCamelCase       ,      lowerCamelCase  )					->		int:
				UpperCamelCase_:							List[str]		=  normalize_answer(_lowerCAmelCase  ).split()
				UpperCamelCase_:							Optional[Any]		=  normalize_answer(_lowerCAmelCase  ).split()
				UpperCamelCase_:							Tuple		=  Counter(_lowerCAmelCase  ) & Counter(_lowerCAmelCase  )
				UpperCamelCase_:							List[Any]		=  sum(common.values()  )
				if num_same == 0:
								return 0
				UpperCamelCase_:							List[str]		=  1.0 * num_same / len(_lowerCAmelCase  )
				UpperCamelCase_:							Optional[int]		=  1.0 * num_same / len(_lowerCAmelCase  )
				UpperCamelCase_:							Dict		=  (2 * precision * recall) / (precision + recall)
				return fa







def     A__   (  lowerCamelCase       ,      lowerCamelCase  )					->		Optional[Any]:
				return normalize_answer(_lowerCAmelCase  ) == normalize_answer(_lowerCAmelCase  )







def     A__   (  lowerCamelCase       ,      lowerCamelCase  )					->		Dict:
				assert len(_lowerCAmelCase  ) == len(_lowerCAmelCase  )
				UpperCamelCase_:							List[Any]		=  0
				for hypo, pred in zip(_lowerCAmelCase       ,      _lowerCAmelCase  ):
								em += exact_match_score(_lowerCAmelCase       ,      _lowerCAmelCase  )
				if len(_lowerCAmelCase  ) > 0:
								em /= len(_lowerCAmelCase  )
				return {"em": em}







def     A__   (  lowerCamelCase  )					->		str:
				return model_prefix.startswith("""rag"""  )







def     A__   (  lowerCamelCase       ,      lowerCamelCase       ,      lowerCamelCase  )					->		Optional[Any]:
				UpperCamelCase_:							Tuple		=  {p: p for p in extra_params}
				# T5 models don't have `dropout` param, they have `dropout_rate` instead
				UpperCamelCase_:							int		=  "dropout_rate"
				for p in extra_params:
								if getattr(_lowerCAmelCase       ,      _lowerCAmelCase       ,      _lowerCAmelCase  ):
												if not hasattr(_lowerCAmelCase       ,      _lowerCAmelCase  ) and not hasattr(_lowerCAmelCase       ,      equivalent_param[p]  ):
																logger.info("""config doesn't have a `{}` attribute""".format(_lowerCAmelCase  )  )
																delattr(_lowerCAmelCase       ,      _lowerCAmelCase  )
																continue
												UpperCamelCase_:							Union[str, Any]		=  p if hasattr(_lowerCAmelCase       ,      _lowerCAmelCase  ) else equivalent_param[p]
												setattr(_lowerCAmelCase       ,      _lowerCAmelCase       ,      getattr(_lowerCAmelCase       ,      _lowerCAmelCase  )  )
												delattr(_lowerCAmelCase       ,      _lowerCAmelCase  )
				return hparams, config








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     _UpperCamelCase			(   _A       ,    unittest.TestCase					):






			'''simple docstring'''

			__UpperCamelCase :  Union[str, Any]    =	RoFormerTokenizer
			__UpperCamelCase :  Union[str, Any]    =	RoFormerTokenizerFast
			__UpperCamelCase :  Optional[Any]    =	True
			__UpperCamelCase :  Tuple    =	True

			def  lowerCAmelCase__		(    self	:    Optional[Any] ):
							super().setUp()

			def  lowerCAmelCase__		(    self	:    List[str]  ,		**snake_case_	:    Union[str, Any] ):
							return self.tokenizer_class.from_pretrained("""junnyu/roformer_chinese_base"""  ,		**snake_case_ )

			def  lowerCAmelCase__		(    self	:    Dict  ,		**snake_case_	:    Union[str, Any] ):
							return self.rust_tokenizer_class.from_pretrained("""junnyu/roformer_chinese_base"""  ,		**snake_case_ )

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

			def  lowerCAmelCase__		(    self	:    Dict ):
							UpperCamelCase_:							Dict		=  self.get_tokenizer()
							UpperCamelCase_,				UpperCamelCase_:							Optional[int]		=  self.get_chinese_input_output_texts()
							UpperCamelCase_:							Optional[int]		=  tokenizer.tokenize(snake_case_ )

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

							UpperCamelCase_:							Dict		=  tokens + [tokenizer.unk_token]
							UpperCamelCase_:							int		=  [2_2943, 2_1332, 3_4431, 4_5904, 117, 306, 1231, 1231, 2653, 3_3994, 1266, 100]
							self.assertListEqual(tokenizer.convert_tokens_to_ids(snake_case_ )  ,		snake_case_ )

			def  lowerCAmelCase__		(    self	:    Dict ):
							UpperCamelCase_:							Optional[int]		=  self.get_rust_tokenizer()
							UpperCamelCase_,				UpperCamelCase_:							Any		=  self.get_chinese_input_output_texts()
							UpperCamelCase_:							int		=  tokenizer.tokenize(snake_case_ )
							self.assertListEqual(snake_case_  ,		output_text.split() )
							UpperCamelCase_:							Union[str, Any]		=  tokens + [tokenizer.unk_token]
							UpperCamelCase_:							Optional[Any]		=  [2_2943, 2_1332, 3_4431, 4_5904, 117, 306, 1231, 1231, 2653, 3_3994, 1266, 100]
							self.assertListEqual(tokenizer.convert_tokens_to_ids(snake_case_ )  ,		snake_case_ )

			def  lowerCAmelCase__		(    self	:    Dict ):
							pass

			def  lowerCAmelCase__		(    self	:    Tuple ):
							pass




			def  lowerCAmelCase__		(    self	:    Union[str, Any] ):
							pass






