



"""simple docstring"""





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 	__lowerCAmelCase						(		__UpperCamelCase      :			Tuple					, __UpperCamelCase      :			Any					, __UpperCamelCase      :			List[Any]					, __UpperCamelCase      :			Any					, __UpperCamelCase      :			int=True					, __UpperCamelCase      :			Union[str, Any]="pt"    ):


      '''simple docstring'''






      snake_case_   : Union[str, Any]						=			{"""add_prefix_space""": True} if isinstance(__UpperCamelCase					, __UpperCamelCase    ) and not line.startswith(""" """    ) else {}
      snake_case_   : Any						=			padding_side
      return tokenizer(
          [line]					, max_length=__UpperCamelCase					, padding="""max_length""" if pad_to_max_length else None					, truncation=__UpperCamelCase					, return_tensors=__UpperCamelCase					, add_special_tokens=__UpperCamelCase					, **__UpperCamelCase					, )
def 	__lowerCAmelCase						(		__UpperCamelCase      :			str					, __UpperCamelCase      :			Any					, __UpperCamelCase      :			Optional[int]=None					, ):


      '''simple docstring'''






      snake_case_   : List[Any]						=			input_ids.ne(__UpperCamelCase    ).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    _lowerCAmelCase    (				SCREAMING_SNAKE_CASE__		):





  """simple docstring"""






  def __init__(					self							,    _lowercase							,    _lowercase							,    _lowercase							,    _lowercase							,    _lowercase="train"							,    _lowercase=None							,    _lowercase=None							,    _lowercase=None							,    _lowercase=""							,    ) ->						Dict:







        '''simple docstring'''

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





  def __len__(					self   ) ->						Any:







        '''simple docstring'''

        return len(self.src_lens   )





  def __getitem__(					self							,    _lowercase   ) ->						Dict[str, torch.Tensor]:







        '''simple docstring'''

        snake_case_   : Optional[Any]						=			index + 1  # linecache starts at 1
        snake_case_   : Optional[int]						=			self.prefix + linecache.getline(str(self.src_file   )							,    _lowercase   ).rstrip("""\n"""   )
        snake_case_   : Union[str, Any]						=			linecache.getline(str(self.tgt_file   )							,    _lowercase   ).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							,    _lowercase   ):
              source_line += self.tokenizer.eos_token
              tgt_line += self.tokenizer.eos_token

        # Pad source and target to the right
        snake_case_   : Optional[Any]						=			(
            self.tokenizer.question_encoder if isinstance(self.tokenizer							,    _lowercase   ) else self.tokenizer
        )
        snake_case_   : Dict						=			self.tokenizer.generator if isinstance(self.tokenizer							,    _lowercase   ) else self.tokenizer

        snake_case_   : str						=			encode_line(_lowercase							,    _lowercase							,    self.max_source_length							,    """right"""   )
        snake_case_   : Dict						=			encode_line(_lowercase							,    _lowercase							,    self.max_target_length							,    """right"""   )

        snake_case_   : Optional[int]						=			source_inputs["""input_ids"""].squeeze()
        snake_case_   : Optional[Any]						=			target_inputs["""input_ids"""].squeeze()
        snake_case_   : Optional[int]						=			source_inputs["""attention_mask"""].squeeze()
        return {
            "input_ids": source_ids,
            "attention_mask": src_mask,
            "decoder_input_ids": target_ids,
        }





  @staticmethod
  def    UpperCAmelCase__							(					_lowercase   ) ->						List[str]:







        '''simple docstring'''

        return [len(_lowercase   ) for x in Path(_lowercase   ).open().readlines()]





  def    UpperCAmelCase__							(					self							,    _lowercase   ) ->						Dict[str, torch.Tensor]:







        '''simple docstring'''

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




__lowerCAmelCase       :					List[Any]      					=					getLogger(__name__)
def 	__lowerCAmelCase						(		__UpperCamelCase      :			List[List]    ):


      '''simple docstring'''






      return list(itertools.chain.from_iterable(__UpperCamelCase    )    )
def 	__lowerCAmelCase						(		__UpperCamelCase      :			str    ):


      '''simple docstring'''






      snake_case_   : Any						=			get_git_info()
      save_json(__UpperCamelCase					, os.path.join(__UpperCamelCase					, """git_log.json"""    )    )
def 	__lowerCAmelCase						(		__UpperCamelCase      :			List[Any]					, __UpperCamelCase      :			int					, __UpperCamelCase      :			List[Any]=4					, **__UpperCamelCase      :			Optional[Any]    ):


      '''simple docstring'''






      with open(__UpperCamelCase					, """w"""    ) as f:
            json.dump(__UpperCamelCase					, __UpperCamelCase					, indent=__UpperCamelCase					, **__UpperCamelCase    )
def 	__lowerCAmelCase						(		__UpperCamelCase      :			Union[str, Any]    ):


      '''simple docstring'''






      with open(__UpperCamelCase    ) as f:
            return json.load(__UpperCamelCase    )
def 	__lowerCAmelCase						(		):


      '''simple docstring'''






      snake_case_   : Any						=			git.Repo(search_parent_directories=__UpperCamelCase    )
      snake_case_   : Dict						=			{
          """repo_id""": str(__UpperCamelCase    ),
          """repo_sha""": str(repo.head.object.hexsha    ),
          """repo_branch""": str(repo.active_branch    ),
          """hostname""": str(socket.gethostname()    ),
      }
      return repo_infos
def 	__lowerCAmelCase						(		__UpperCamelCase      :			Callable					, __UpperCamelCase      :			Iterable    ):


      '''simple docstring'''






      return list(map(__UpperCamelCase					, __UpperCamelCase    )    )
def 	__lowerCAmelCase						(		__UpperCamelCase      :			List[str]					, __UpperCamelCase      :			Optional[int]    ):


      '''simple docstring'''






      with open(__UpperCamelCase					, """wb"""    ) as f:
            return pickle.dump(__UpperCamelCase					, __UpperCamelCase    )
def 	__lowerCAmelCase						(		__UpperCamelCase      :			List[Any]    ):


      '''simple docstring'''






      def remove_articles(__UpperCamelCase      :			List[str]    ):
            return re.sub(r"""\b(a|an|the)\b"""					, """ """					, __UpperCamelCase    )

      def white_space_fix(__UpperCamelCase      :			Union[str, Any]    ):
            return " ".join(text.split()    )

      def remove_punc(__UpperCamelCase      :			Optional[int]    ):
            snake_case_   : List[str]						=			set(string.punctuation    )
            return "".join(ch for ch in text if ch not in exclude    )

      def lower(__UpperCamelCase      :			Optional[int]    ):
            return text.lower()

      return white_space_fix(remove_articles(remove_punc(lower(__UpperCamelCase    )    )    )    )
def 	__lowerCAmelCase						(		__UpperCamelCase      :			Dict					, __UpperCamelCase      :			Any    ):


      '''simple docstring'''






      snake_case_   : Optional[int]						=			normalize_answer(__UpperCamelCase    ).split()
      snake_case_   : Optional[int]						=			normalize_answer(__UpperCamelCase    ).split()
      snake_case_   : int						=			Counter(__UpperCamelCase    ) & Counter(__UpperCamelCase    )
      snake_case_   : str						=			sum(common.values()    )
      if num_same == 0:
            return 0
      snake_case_   : Optional[Any]						=			1.0 * num_same / len(__UpperCamelCase    )
      snake_case_   : Tuple						=			1.0 * num_same / len(__UpperCamelCase    )
      snake_case_   : Tuple						=			(2 * precision * recall) / (precision + recall)
      return fa
def 	__lowerCAmelCase						(		__UpperCamelCase      :			Optional[int]					, __UpperCamelCase      :			Optional[Any]    ):


      '''simple docstring'''






      return normalize_answer(__UpperCamelCase    ) == normalize_answer(__UpperCamelCase    )
def 	__lowerCAmelCase						(		__UpperCamelCase      :			List[str]					, __UpperCamelCase      :			List[str]    ):


      '''simple docstring'''






      assert len(__UpperCamelCase    ) == len(__UpperCamelCase    )
      snake_case_   : Optional[Any]						=			0
      for hypo, pred in zip(__UpperCamelCase					, __UpperCamelCase    ):
            em += exact_match_score(__UpperCamelCase					, __UpperCamelCase    )
      if len(__UpperCamelCase    ) > 0:
            em /= len(__UpperCamelCase    )
      return {"em": em}
def 	__lowerCAmelCase						(		__UpperCamelCase      :			Tuple    ):


      '''simple docstring'''






      return model_prefix.startswith("""rag"""    )






def 	__lowerCAmelCase						(		__UpperCamelCase      :			List[Any]					, __UpperCamelCase      :			Union[str, Any]					, __UpperCamelCase      :			Dict    ):


      '''simple docstring'''






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






"""simple docstring"""





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    _lowerCAmelCase    (				SCREAMING_SNAKE_CASE__  ,				unittest.TestCase		):





		"""simple docstring"""






		_lowerCamelCase			  =       RoFormerTokenizer
		_lowerCamelCase			  =       RoFormerTokenizerFast
		_lowerCamelCase			  =       True
		_lowerCamelCase			  =       True





		def    UpperCAmelCase__							(					self   ) ->						Any:







								'''simple docstring'''

								super().setUp()





		def    UpperCAmelCase__							(					self							,    **_lowercase   ) ->						str:







								'''simple docstring'''

								return self.tokenizer_class.from_pretrained("""junnyu/roformer_chinese_base"""							,    **_lowercase   )





		def    UpperCAmelCase__							(					self							,    **_lowercase   ) ->						Union[str, Any]:







								'''simple docstring'''

								return self.rust_tokenizer_class.from_pretrained("""junnyu/roformer_chinese_base"""							,    **_lowercase   )





		def    UpperCAmelCase__							(					self   ) ->						Dict:







								'''simple docstring'''

								snake_case_   : Tuple						=			"""永和服装饰品有限公司,今天天气非常好"""
								snake_case_   : int						=			"""永和 服装 饰品 有限公司 , 今 天 天 气 非常 好"""
								return input_text, output_text





		def    UpperCAmelCase__							(					self   ) ->						str:







								'''simple docstring'''

								snake_case_   : List[str]						=			self.get_tokenizer()
								snake_case_			,		snake_case_   : Optional[Any]						=			self.get_chinese_input_output_texts()
								snake_case_   : List[str]						=			tokenizer.tokenize(_lowercase   )

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

								snake_case_   : str						=			tokens + [tokenizer.unk_token]
								snake_case_   : Tuple						=			[2_2_9_4_3, 2_1_3_3_2, 3_4_4_3_1, 4_5_9_0_4, 1_1_7, 3_0_6, 1_2_3_1, 1_2_3_1, 2_6_5_3, 3_3_9_9_4, 1_2_6_6, 1_0_0]
								self.assertListEqual(tokenizer.convert_tokens_to_ids(_lowercase   )							,    _lowercase   )





		def    UpperCAmelCase__							(					self   ) ->						Any:







								'''simple docstring'''

								snake_case_   : int						=			self.get_rust_tokenizer()
								snake_case_			,		snake_case_   : List[Any]						=			self.get_chinese_input_output_texts()
								snake_case_   : Union[str, Any]						=			tokenizer.tokenize(_lowercase   )
								self.assertListEqual(_lowercase							,    output_text.split()   )
								snake_case_   : Optional[int]						=			tokens + [tokenizer.unk_token]
								snake_case_   : Union[str, Any]						=			[2_2_9_4_3, 2_1_3_3_2, 3_4_4_3_1, 4_5_9_0_4, 1_1_7, 3_0_6, 1_2_3_1, 1_2_3_1, 2_6_5_3, 3_3_9_9_4, 1_2_6_6, 1_0_0]
								self.assertListEqual(tokenizer.convert_tokens_to_ids(_lowercase   )							,    _lowercase   )





		def    UpperCAmelCase__							(					self   ) ->						Tuple:







								'''simple docstring'''

								pass





		def    UpperCAmelCase__							(					self   ) ->						Optional[Any]:







								'''simple docstring'''

								pass





		def    UpperCAmelCase__							(					self   ) ->						Optional[int]:







								'''simple docstring'''

								pass

