


import json
from typing import List, Optional, Tuple

from tokenizers import pre_tokenizers, processors

from ...tokenization_utils_base import AddedToken, BatchEncoding
from ...tokenization_utils_fast import PreTrainedTokenizerFast
from ...utils import logging
from .tokenization_mvp import MvpTokenizer


UpperCAmelCase					:  Tuple			=						logging.get_logger(__name__)


UpperCAmelCase					:  List[str]			=						{'''vocab_file''': '''vocab.json''', '''merges_file''': '''merges.txt''', '''tokenizer_file''': '''tokenizer.json'''}

# See all MVP models at https://huggingface.co/models?filter=mvp
UpperCAmelCase					:  Optional[int]			=						{
    '''vocab_file''': {
        '''RUCAIBox/mvp''': '''https://huggingface.co/RUCAIBox/mvp/resolve/main/vocab.json''',
    },
    '''added_tokens.json''': {
        '''RUCAIBox/mvp''': '''https://huggingface.co/RUCAIBox/mvp/resolve/main/added_tokens.json''',
    },
    '''merges_file''': {
        '''RUCAIBox/mvp''': '''https://huggingface.co/RUCAIBox/mvp/resolve/main/merges.txt''',
    },
    '''tokenizer_file''': {
        '''RUCAIBox/mvp''': '''https://huggingface.co/RUCAIBox/mvp/resolve/main/tokenizer.json''',
    },
}

UpperCAmelCase					:  List[Any]			=						{
    '''RUCAIBox/mvp''': 10_24,
}







class     __lowercase    (				_lowerCAmelCase   ):



		"""simple docstring"""

		UpperCamelCase			: Union[str, Any]           =						VOCAB_FILES_NAMES
		UpperCamelCase			: Optional[int]           =						PRETRAINED_VOCAB_FILES_MAP
		UpperCamelCase			: Tuple           =						PRETRAINED_POSITIONAL_EMBEDDINGS_SIZES
		UpperCamelCase			: Optional[int]           =						["input_ids", "attention_mask"]
		UpperCamelCase			: Union[str, Any]           =						MvpTokenizer







		def __init__(      self						,	A=None						,	A=None						,	A=None						,	A="replace"						,	A="<s>"						,	A="</s>"						,	A="</s>"						,	A="<s>"						,	A="<unk>"						,	A="<pad>"						,	A="<mask>"						,	A=False						,	A=True						,	**A						,	)   ->      str:







					'''simple docstring'''







					super().__init__(
					    A						,	A						,	tokenizer_file=A						,	errors=A						,	bos_token=A						,	eos_token=A						,	sep_token=A						,	cls_token=A						,	unk_token=A						,	pad_token=A						,	mask_token=A						,	add_prefix_space=A						,	trim_offsets=A						,	**A						,	)

					lowerCamelCase  						=   json.loads(self.backend_tokenizer.pre_tokenizer.__getstate__()     )
					if pre_tok_state.get("""add_prefix_space"""						,	A     ) != add_prefix_space:
								lowerCamelCase  						=   getattr(A						,	pre_tok_state.pop("""type"""     )     )
								lowerCamelCase  						=   add_prefix_space
								lowerCamelCase  						=   pre_tok_class(**A     )

					lowerCamelCase  						=   add_prefix_space

					# the pre_tokenizer is already updated in the GPT2TokenizerFast `__init__`
					lowerCamelCase  						=   "post_processor"
					lowerCamelCase  						=   getattr(self.backend_tokenizer						,	A						,	A     )
					if tokenizer_component_instance:
								lowerCamelCase  						=   json.loads(tokenizer_component_instance.__getstate__()     )

								# The lists 'sep' and 'cls' must be cased in tuples for the object `post_processor_class`
								if "sep" in state:
											lowerCamelCase  						=   tuple(state["""sep"""]     )
								if "cls" in state:
											lowerCamelCase  						=   tuple(state["""cls"""]     )

								lowerCamelCase  						=   False

								if state.get("""add_prefix_space"""						,	A     ) != add_prefix_space:
											lowerCamelCase  						=   add_prefix_space
											lowerCamelCase  						=   True

								if state.get("""trim_offsets"""						,	A     ) != trim_offsets:
											lowerCamelCase  						=   trim_offsets
											lowerCamelCase  						=   True

								if changes_to_apply:
											lowerCamelCase  						=   getattr(A						,	state.pop("""type"""     )     )
											lowerCamelCase  						=   component_class(**A     )
											setattr(self.backend_tokenizer						,	A						,	A     )







		@property
		def  __A					(      self     )   ->      Optional[int]:







					'''simple docstring'''







					if self._mask_token is None:
								if self.verbose:
											logger.error("""Using mask_token, but it is not set yet."""     )
								return None
					return str(self._mask_token     )







		@mask_token.setter
		def  __A					(      self						,	A     )   ->      int:







					'''simple docstring'''







					lowerCamelCase  						=   AddedToken(A						,	lstrip=A						,	rstrip=A     ) if isinstance(A						,	A     ) else value
					lowerCamelCase  						=   value







		def  __A					(      self						,	*A						,	**A     )   ->      Tuple:







					'''simple docstring'''







					lowerCamelCase  						=   kwargs.get("""is_split_into_words"""						,	A     )

					if is_split_into_words and not self.add_prefix_space:
								raise ValueError(
								    F'You need to instantiate {self.__class__.__name__} with add_prefix_space=True '
								    """to use it with pretokenized inputs."""     )

					return super()._batch_encode_plus(*A						,	**A     )







		def  __A					(      self						,	*A						,	**A     )   ->      List[Any]:







					'''simple docstring'''







					lowerCamelCase  						=   kwargs.get("""is_split_into_words"""						,	A     )

					if is_split_into_words and not self.add_prefix_space:
								raise ValueError(
								    F'You need to instantiate {self.__class__.__name__} with add_prefix_space=True '
								    """to use it with pretokenized inputs."""     )

					return super()._encode_plus(*A						,	**A     )







		def  __A					(      self						,	A						,	A = None     )   ->      Optional[Any]:







					'''simple docstring'''







					lowerCamelCase  						=   self._tokenizer.model.save(A						,	name=A     )
					return tuple(A     )







		def  __A					(      self						,	A						,	A=None     )   ->      Any:







					'''simple docstring'''







					lowerCamelCase  						=   [self.bos_token_id] + token_ids_a + [self.eos_token_id]
					if token_ids_a is None:
								return output

					return output + [self.eos_token_id] + token_ids_a + [self.eos_token_id]







		def  __A					(      self						,	A						,	A = None     )   ->      Union[str, Any]:







					'''simple docstring'''







					lowerCamelCase  						=   [self.sep_token_id]
					lowerCamelCase  						=   [self.cls_token_id]

					if token_ids_a is None:
								return len(cls + token_ids_a + sep     ) * [0]
					return len(cls + token_ids_a + sep + sep + token_ids_a + sep     ) * [0]








'''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					:					Optional[int]	,__lowerCamelCase					:					Any	,__lowerCamelCase					:					Any	,__lowerCamelCase					:					List[str]	,__lowerCamelCase					:					Dict=True	,__lowerCamelCase					:					List[Any]="pt" ):
   lowercase_			:Dict    			= {"add_prefix_space": True} if isinstance(__lowerCamelCase	,__lowerCamelCase ) and not line.startswith(" " ) else {}
   lowercase_			:str    			= 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					:					List[str]	,__lowerCamelCase					:					Dict	,__lowerCamelCase					:					str=None	,):
   lowercase_			:Optional[int]    			= 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       a_   (				_lowerCAmelCase							):





     def __init__( self		:					Optional[int]	,      lowercase		:					Any	,      lowercase		:					Tuple	,      lowercase		:					Union[str, Any]	,      lowercase		:					Tuple	,      lowercase		:					str="train"	,      lowercase		:					Dict=None	,      lowercase		:					Tuple=None	,      lowercase		:					List[str]=None	,      lowercase		:					int=""	,      ):





        """simple docstring"""




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





     def __len__( self		:					Tuple						):





        """simple docstring"""




        return len(self.src_lens						)





     def __getitem__( self		:					str	,      lowercase		:					Dict						):





        """simple docstring"""




        lowercase_			:Tuple    			= index + 1  # linecache starts at 1
        lowercase_			:Optional[Any]    			= self.prefix + linecache.getline(str(self.src_file						)	,      lowercase						).rstrip("\n"						)
        lowercase_			:List[str]    			= 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
        lowercase_			:List[str]    			= (
            self.tokenizer.question_encoder if isinstance(self.tokenizer	,      lowercase						) else self.tokenizer
        )
        lowercase_			:int    			= self.tokenizer.generator if isinstance(self.tokenizer	,      lowercase						) else self.tokenizer

        lowercase_			:List[str]    			= encode_line(lowercase	,      lowercase	,      self.max_source_length	,      "right"						)
        lowercase_			:Any    			= encode_line(lowercase	,      lowercase	,      self.max_target_length	,      "right"						)

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





     @staticmethod
     def 							lowercase__      ( lowercase		:					Union[str, Any]						):





        """simple docstring"""




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







     def 							lowercase__      ( self		:					str	,      lowercase		:					List[Any]						):





        """simple docstring"""




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







lowerCAmelCase					:     List[str]												=getLogger(__name__)
def 							UpperCAmelCase_  (						__lowerCamelCase					:					List[List] ):
   return list(itertools.chain.from_iterable(__lowerCamelCase ) )
def 							UpperCAmelCase_  (						__lowerCamelCase					:					str ):
   lowercase_			:List[str]    			= get_git_info()
   save_json(__lowerCamelCase	,os.path.join(__lowerCamelCase	,"git_log.json" ) )
def 							UpperCAmelCase_  (						__lowerCamelCase					:					Any	,__lowerCamelCase					:					Any	,__lowerCamelCase					:					List[Any]=4	,**__lowerCamelCase					:					List[str] ):
   with open(__lowerCamelCase	,"w" ) as f:
      json.dump(__lowerCamelCase	,__lowerCamelCase	,indent=__lowerCamelCase	,**__lowerCamelCase )
def 							UpperCAmelCase_  (						__lowerCamelCase					:					Tuple ):
   with open(__lowerCamelCase ) as f:
      return json.load(__lowerCamelCase )
def 							UpperCAmelCase_  (						):
   lowercase_			:Dict    			= git.Repo(search_parent_directories=__lowerCamelCase )
   lowercase_			: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 							UpperCAmelCase_  (						__lowerCamelCase					:					Callable	,__lowerCamelCase					:					Iterable ):
   return list(map(__lowerCamelCase	,__lowerCamelCase ) )
def 							UpperCAmelCase_  (						__lowerCamelCase					:					Union[str, Any]	,__lowerCamelCase					:					List[str] ):
   with open(__lowerCamelCase	,"wb" ) as f:
      return pickle.dump(__lowerCamelCase	,__lowerCamelCase )
def 							UpperCAmelCase_  (						__lowerCamelCase					:					str ):

   def remove_articles(__lowerCamelCase					:					Optional[int] ):
      return re.sub(r"\b(a|an|the)\b"	," "	,__lowerCamelCase )

   def white_space_fix(__lowerCamelCase					:					Dict ):
      return " ".join(text.split() )

   def remove_punc(__lowerCamelCase					:					Optional[Any] ):
      lowercase_			:Any    			= set(string.punctuation )
      return "".join(ch for ch in text if ch not in exclude )

   def lower(__lowerCamelCase					:					List[Any] ):
      return text.lower()

   return white_space_fix(remove_articles(remove_punc(lower(__lowerCamelCase ) ) ) )
def 							UpperCAmelCase_  (						__lowerCamelCase					:					Optional[int]	,__lowerCamelCase					:					Optional[int] ):
   lowercase_			:Tuple    			= normalize_answer(__lowerCamelCase ).split()
   lowercase_			:Dict    			= normalize_answer(__lowerCamelCase ).split()
   lowercase_			:Tuple    			= Counter(__lowerCamelCase ) & Counter(__lowerCamelCase )
   lowercase_			:Tuple    			= sum(common.values() )
   if num_same == 0:
      return 0
   lowercase_			:Union[str, Any]    			= 1.0 * num_same / len(__lowerCamelCase )
   lowercase_			:List[Any]    			= 1.0 * num_same / len(__lowerCamelCase )
   lowercase_			:Tuple    			= (2 * precision * recall) / (precision + recall)
   return fa
def 							UpperCAmelCase_  (						__lowerCamelCase					:					int	,__lowerCamelCase					:					Union[str, Any] ):
   return normalize_answer(__lowerCamelCase ) == normalize_answer(__lowerCamelCase )
def 							UpperCAmelCase_  (						__lowerCamelCase					:					List[str]	,__lowerCamelCase					:					List[str] ):
   assert len(__lowerCamelCase ) == len(__lowerCamelCase )
   lowercase_			: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 							UpperCAmelCase_  (						__lowerCamelCase					:					str ):
   return model_prefix.startswith("rag" )


def 							UpperCAmelCase_  (						__lowerCamelCase					:					List[str]	,__lowerCamelCase					:					List[Any]	,__lowerCamelCase					:					int ):
   lowercase_			:Dict    			= {p: p for p in extra_params}
   # T5 models don't have `dropout` param, they have `dropout_rate` instead
   lowercase_			:List[str]    			= "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
         lowercase_			:List[Any]    			= p if hasattr(__lowerCamelCase	,__lowerCamelCase ) else equivalent_param[p]
         setattr(__lowerCamelCase	,__lowerCamelCase	,getattr(__lowerCamelCase	,__lowerCamelCase ) )
         delattr(__lowerCamelCase	,__lowerCamelCase )
   return hparams, config


