





'''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        UpperCamelCase__				(		lowerCAmelCase							,     lowerCAmelCase							,     lowerCAmelCase							,     lowerCAmelCase							,     lowerCAmelCase=True							,     lowerCAmelCase="pt"  ):





      """simple docstring"""


      _lowerCAmelCase												=							{"""add_prefix_space""": True} if isinstance(lowerCAmelCase							,     lowerCAmelCase  ) and not line.startswith(""" """  ) else {}
      _lowerCAmelCase												=							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        UpperCamelCase__				(		lowerCAmelCase							,     lowerCAmelCase							,     lowerCAmelCase=None							,     ):





      """simple docstring"""


      _lowerCAmelCase												=							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					(      snake_case_       ):




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




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




      def __getitem__(      self      :			List[Any]      ,      __snake_case      :			Union[str, Any]  )    ->				Dict[str, torch.Tensor]:
            _lowerCAmelCase												=							index + 1  # linecache starts at 1
            _lowerCAmelCase												=							self.prefix + linecache.getline(str(self.src_file  )      ,      __snake_case  ).rstrip("""\n"""  )
            _lowerCAmelCase												=							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
            _lowerCAmelCase												=							(
                self.tokenizer.question_encoder if isinstance(self.tokenizer      ,      __snake_case  ) else self.tokenizer
            )
            _lowerCAmelCase												=							self.tokenizer.generator if isinstance(self.tokenizer      ,      __snake_case  ) else self.tokenizer

            _lowerCAmelCase												=							encode_line(__snake_case      ,      __snake_case      ,      self.max_source_length      ,      """right"""  )
            _lowerCAmelCase												=							encode_line(__snake_case      ,      __snake_case      ,      self.max_target_length      ,      """right"""  )

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




      @staticmethod
      def     lowercase__   (      __snake_case      :			List[str]  )    ->				Any:
            return [len(__snake_case  ) for x in Path(__snake_case  ).open().readlines()]




      def     lowercase__   (      self      :			str      ,      __snake_case      :			Any  )    ->				Dict[str, torch.Tensor]:
            _lowerCAmelCase												=							torch.stack([x["""input_ids"""] for x in batch]  )
            _lowerCAmelCase												=							torch.stack([x["""attention_mask"""] for x in batch]  )
            _lowerCAmelCase												=							torch.stack([x["""decoder_input_ids"""] for x in batch]  )
            _lowerCAmelCase												=							(
                self.tokenizer.generator.pad_token_id
                if isinstance(self.tokenizer      ,      __snake_case  )
                else self.tokenizer.pad_token_id
            )
            _lowerCAmelCase												=							(
                self.tokenizer.question_encoder.pad_token_id
                if isinstance(self.tokenizer      ,      __snake_case  )
                else self.tokenizer.pad_token_id
            )
            _lowerCAmelCase												=							trim_batch(__snake_case      ,      __snake_case  )
            _lowerCAmelCase					,							_lowerCAmelCase												=							trim_batch(__snake_case      ,      __snake_case      ,      attention_mask=__snake_case  )
            _lowerCAmelCase												=							{
                """input_ids""": source_ids,
                """attention_mask""": source_mask,
                """decoder_input_ids""": y,
            }
            return batch




A__    :       List[str]              =getLogger(__name__)
def        UpperCamelCase__				(		lowerCAmelCase  ):





      """simple docstring"""


      return list(itertools.chain.from_iterable(lowerCAmelCase  )  )
def        UpperCamelCase__				(		lowerCAmelCase  ):





      """simple docstring"""


      _lowerCAmelCase												=							get_git_info()
      save_json(lowerCAmelCase							,     os.path.join(lowerCAmelCase							,     """git_log.json"""  )  )
def        UpperCamelCase__				(		lowerCAmelCase							,     lowerCAmelCase							,     lowerCAmelCase=4							,     **lowerCAmelCase  ):





      """simple docstring"""


      with open(lowerCAmelCase							,     """w"""  ) as f:
            json.dump(lowerCAmelCase							,     lowerCAmelCase							,     indent=lowerCAmelCase							,     **lowerCAmelCase  )
def        UpperCamelCase__				(		lowerCAmelCase  ):





      """simple docstring"""


      with open(lowerCAmelCase  ) as f:
            return json.load(lowerCAmelCase  )
def        UpperCamelCase__				(		):





      """simple docstring"""


      _lowerCAmelCase												=							git.Repo(search_parent_directories=lowerCAmelCase  )
      _lowerCAmelCase												=							{
          """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        UpperCamelCase__				(		lowerCAmelCase							,     lowerCAmelCase  ):





      """simple docstring"""


      return list(map(lowerCAmelCase							,     lowerCAmelCase  )  )
def        UpperCamelCase__				(		lowerCAmelCase							,     lowerCAmelCase  ):





      """simple docstring"""


      with open(lowerCAmelCase							,     """wb"""  ) as f:
            return pickle.dump(lowerCAmelCase							,     lowerCAmelCase  )
def        UpperCamelCase__				(		lowerCAmelCase  ):





      """simple docstring"""


      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  ):
            _lowerCAmelCase												=							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        UpperCamelCase__				(		lowerCAmelCase							,     lowerCAmelCase  ):





      """simple docstring"""


      _lowerCAmelCase												=							normalize_answer(lowerCAmelCase  ).split()
      _lowerCAmelCase												=							normalize_answer(lowerCAmelCase  ).split()
      _lowerCAmelCase												=							Counter(lowerCAmelCase  ) & Counter(lowerCAmelCase  )
      _lowerCAmelCase												=							sum(common.values()  )
      if num_same == 0:
            return 0
      _lowerCAmelCase												=							1.0 * num_same / len(lowerCAmelCase  )
      _lowerCAmelCase												=							1.0 * num_same / len(lowerCAmelCase  )
      _lowerCAmelCase												=							(2 * precision * recall) / (precision + recall)
      return fa
def        UpperCamelCase__				(		lowerCAmelCase							,     lowerCAmelCase  ):





      """simple docstring"""


      return normalize_answer(lowerCAmelCase  ) == normalize_answer(lowerCAmelCase  )
def        UpperCamelCase__				(		lowerCAmelCase							,     lowerCAmelCase  ):





      """simple docstring"""


      assert len(lowerCAmelCase  ) == len(lowerCAmelCase  )
      _lowerCAmelCase												=							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        UpperCamelCase__				(		lowerCAmelCase  ):





      """simple docstring"""


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





def        UpperCamelCase__				(		lowerCAmelCase							,     lowerCAmelCase							,     lowerCAmelCase  ):





      """simple docstring"""


      _lowerCAmelCase												=							{p: p for p in extra_params}
      # T5 models don't have `dropout` param, they have `dropout_rate` instead
      _lowerCAmelCase												=							"""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
                  _lowerCAmelCase												=							p if hasattr(lowerCAmelCase							,     lowerCAmelCase  ) else equivalent_param[p]
                  setattr(lowerCAmelCase							,     lowerCAmelCase							,     getattr(lowerCAmelCase							,     lowerCAmelCase  )  )
                  delattr(lowerCAmelCase							,     lowerCAmelCase  )
      return hparams, config













'''simple docstring'''






from typing import TYPE_CHECKING

from ...utils import OptionalDependencyNotAvailable, _LazyModule, is_tokenizers_available


A__    :       int              ={'''tokenization_herbert''': ['''HerbertTokenizer''']}

try:
      if not is_tokenizers_available():
            raise OptionalDependencyNotAvailable()
except OptionalDependencyNotAvailable:
      pass
else:
      A__    :       Dict              =['''HerbertTokenizerFast''']


if TYPE_CHECKING:
      from .tokenization_herbert import HerbertTokenizer

      try:
            if not is_tokenizers_available():
                  raise OptionalDependencyNotAvailable()
      except OptionalDependencyNotAvailable:
            pass
      else:
            from .tokenization_herbert_fast import HerbertTokenizerFast

else:
      import sys

      A__    :       List[Any]              =_LazyModule(__name__, globals()['''__file__'''], _import_structure, module_spec=__spec__)






