'''simple docstring'''

import json
import os
from functools import lru_cache
from typing import Dict, List, Optional, Tuple, Union

import regex as re

from ...tokenization_utils import AddedToken, PreTrainedTokenizer
from ...tokenization_utils_base import BatchEncoding, EncodedInput
from ...utils import PaddingStrategy, logging


lowerCAmelCase_ : Optional[int]						  =      logging.get_logger(__name__)


lowerCAmelCase_ : Optional[Any]						  =      {"vocab_file": "vocab.json", "merges_file": "merges.txt"}

# See all LED models at https://huggingface.co/models?filter=LED
lowerCAmelCase_ : str						  =      {
    "vocab_file": {
        "allenai/led-base-16384": "https://huggingface.co/allenai/led-base-16384/resolve/main/vocab.json",
    },
    "merges_file": {
        "allenai/led-base-16384": "https://huggingface.co/allenai/led-base-16384/resolve/main/merges.txt",
    },
    "tokenizer_file": {
        "allenai/led-base-16384": "https://huggingface.co/allenai/led-base-16384/resolve/main/tokenizer.json",
    },
}

lowerCAmelCase_ : List[Any]						  =      {
    "allenai/led-base-16384": 16_384,
}


@lru_cache()
# Copied from transformers.models.bart.tokenization_bart.bytes_to_unicode
def __a (	)	->							int:
      '''simple docstring'''


      lowercase_     =      (
          list(range(ord("!"				) ,		ord("~"				) + 1				)				) + list(range(ord("¡"				) ,		ord("¬"				) + 1				)				) + list(range(ord("®"				) ,		ord("ÿ"				) + 1				)				)
      )
      lowercase_     =      bs[:]
      lowercase_     =      0
      for b in range(2**8				):
            if b not in bs:
                  bs.append(__lowerCamelCase				)
                  cs.append(2**8 + n				)
                  n += 1
      lowercase_     =      [chr(__lowerCamelCase				) for n in cs]
      return dict(zip(__lowerCamelCase ,		__lowerCamelCase				)				)


def __a (	__lowerCamelCase			:						Any				)	->							Union[str, Any]:
      '''simple docstring'''


      lowercase_     =      set()
      lowercase_     =      word[0]
      for char in word[1:]:
            pairs.add((prev_char, char)				)
            lowercase_     =      char
      return pairs






class 							lowercase						(						__lowerCamelCase ):
   lowerCamelCase_    					=VOCAB_FILES_NAMES
   lowerCamelCase_    					=PRETRAINED_VOCAB_FILES_MAP
   lowerCamelCase_    					=PRETRAINED_POSITIONAL_EMBEDDINGS_SIZES
   lowerCamelCase_    					=['input_ids', 'attention_mask']


   def __init__(   self				:	Optional[Any]   ,		__lowerCAmelCase				:	Any   ,		__lowerCAmelCase				:	List[Any]   ,		__lowerCAmelCase				:	List[Any]="replace"   ,		__lowerCAmelCase				:	Optional[Any]="<s>"   ,		__lowerCAmelCase				:	Union[str, Any]="</s>"   ,		__lowerCAmelCase				:	List[Any]="</s>"   ,		__lowerCAmelCase				:	str="<s>"   ,		__lowerCAmelCase				:	Tuple="<unk>"   ,		__lowerCAmelCase				:	int="<pad>"   ,		__lowerCAmelCase				:	Any="<mask>"   ,		__lowerCAmelCase				:	Tuple=False   ,		**__lowerCAmelCase				:	str   ,		)      ->					List[Any]:
         lowercase_     =      AddedToken(__lowerCAmelCase   ,		lstrip=__lowerCAmelCase   ,		rstrip=__lowerCAmelCase) if isinstance(__lowerCAmelCase   ,		__lowerCAmelCase) else bos_token
         lowercase_     =      AddedToken(__lowerCAmelCase   ,		lstrip=__lowerCAmelCase   ,		rstrip=__lowerCAmelCase) if isinstance(__lowerCAmelCase   ,		__lowerCAmelCase) else eos_token
         lowercase_     =      AddedToken(__lowerCAmelCase   ,		lstrip=__lowerCAmelCase   ,		rstrip=__lowerCAmelCase) if isinstance(__lowerCAmelCase   ,		__lowerCAmelCase) else sep_token
         lowercase_     =      AddedToken(__lowerCAmelCase   ,		lstrip=__lowerCAmelCase   ,		rstrip=__lowerCAmelCase) if isinstance(__lowerCAmelCase   ,		__lowerCAmelCase) else cls_token
         lowercase_     =      AddedToken(__lowerCAmelCase   ,		lstrip=__lowerCAmelCase   ,		rstrip=__lowerCAmelCase) if isinstance(__lowerCAmelCase   ,		__lowerCAmelCase) else unk_token
         lowercase_     =      AddedToken(__lowerCAmelCase   ,		lstrip=__lowerCAmelCase   ,		rstrip=__lowerCAmelCase) if isinstance(__lowerCAmelCase   ,		__lowerCAmelCase) else pad_token

         # Mask token behave like a normal word, i.e. include the space before it
         lowercase_     =      AddedToken(__lowerCAmelCase   ,		lstrip=__lowerCAmelCase   ,		rstrip=__lowerCAmelCase) if isinstance(__lowerCAmelCase   ,		__lowerCAmelCase) else mask_token

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

         with open(__lowerCAmelCase   ,		encoding="utf-8") as vocab_handle:
               lowercase_     =      json.load(__lowerCAmelCase)
         lowercase_     =      {v: k for k, v in self.encoder.items()}
         lowercase_     =      errors  # how to handle errors in decoding
         lowercase_     =      bytes_to_unicode()
         lowercase_     =      {v: k for k, v in self.byte_encoder.items()}
         with open(__lowerCAmelCase   ,		encoding="utf-8") as merges_handle:
               lowercase_     =      merges_handle.read().split("\n")[1:-1]
         lowercase_     =      [tuple(merge.split()) for merge in bpe_merges]
         lowercase_     =      dict(zip(__lowerCAmelCase   ,		range(len(__lowerCAmelCase))))
         lowercase_     =      {}
         lowercase_     =      add_prefix_space

         # Should have added re.IGNORECASE so BPE merges can happen for capitalized versions of contractions
         lowercase_     =      re.compile(R"'s|'t|'re|'ve|'m|'ll|'d| ?\p{L}+| ?\p{N}+| ?[^\s\p{L}\p{N}]+|\s+(?!\S)|\s+")


   @property
   # Copied from transformers.models.bart.tokenization_bart.BartTokenizer.vocab_size
   def __UpperCAmelCase       (   self				:	Optional[int])      ->					Optional[Any]:
         return len(self.encoder)


   def __UpperCAmelCase       (   self				:	Tuple)      ->					Tuple:
         return dict(self.encoder   ,		**self.added_tokens_encoder)


   def __UpperCAmelCase       (   self				:	Any   ,		__lowerCAmelCase				:	List[str])      ->					Dict:
         if token in self.cache:
               return self.cache[token]
         lowercase_     =      tuple(__lowerCAmelCase)
         lowercase_     =      get_pairs(__lowerCAmelCase)

         if not pairs:
               return token

         while True:
               lowercase_     =      min(__lowerCAmelCase   ,		key=lambda __lowerCAmelCase: self.bpe_ranks.get(__lowerCAmelCase   ,		float("inf")))
               if bigram not in self.bpe_ranks:
                     break
               lowercase_ ,							lowercase_     =      bigram
               lowercase_     =      []
               lowercase_     =      0
               while i < len(__lowerCAmelCase):
                     try:
                           lowercase_     =      word.index(__lowerCAmelCase   ,		__lowerCAmelCase)
                     except ValueError:
                           new_word.extend(word[i:])
                           break
                     else:
                           new_word.extend(word[i:j])
                           lowercase_     =      j

                     if word[i] == first and i < len(__lowerCAmelCase) - 1 and word[i + 1] == second:
                           new_word.append(first + second)
                           i += 2
                     else:
                           new_word.append(word[i])
                           i += 1
               lowercase_     =      tuple(__lowerCAmelCase)
               lowercase_     =      new_word
               if len(__lowerCAmelCase) == 1:
                     break
               else:
                     lowercase_     =      get_pairs(__lowerCAmelCase)
         lowercase_     =      " ".join(__lowerCAmelCase)
         lowercase_     =      word
         return word


   def __UpperCAmelCase       (   self				:	Optional[Any]   ,		__lowerCAmelCase				:	int)      ->					Dict:
         lowercase_     =      []
         for token in re.findall(self.pat   ,		__lowerCAmelCase):
               lowercase_     =      "".join(
                   self.byte_encoder[b] for b in token.encode("utf-8"))  # Maps all our bytes to unicode strings, avoiding control tokens of the BPE (spaces in our case)
               bpe_tokens.extend(bpe_token for bpe_token in self.bpe(__lowerCAmelCase).split(" "))
         return bpe_tokens


   def __UpperCAmelCase       (   self				:	Tuple   ,		__lowerCAmelCase				:	Any)      ->					Dict:
         return self.encoder.get(__lowerCAmelCase   ,		self.encoder.get(self.unk_token))


   def __UpperCAmelCase       (   self				:	Union[str, Any]   ,		__lowerCAmelCase				:	Optional[int])      ->					Optional[Any]:
         return self.decoder.get(__lowerCAmelCase)


   def __UpperCAmelCase       (   self				:	List[str]   ,		__lowerCAmelCase				:	Tuple)      ->					Dict:
         lowercase_     =      "".join(__lowerCAmelCase)
         lowercase_     =      bytearray([self.byte_decoder[c] for c in text]).decode("utf-8"   ,		errors=self.errors)
         return text


   def __UpperCAmelCase       (   self				:	Any   ,		__lowerCAmelCase				:	str   ,		__lowerCAmelCase				:	Optional[str] = None)      ->					Tuple[str]:
         if not os.path.isdir(__lowerCAmelCase):
               logger.error(F'Vocabulary path ({save_directory}) should be a directory')
               return
         lowercase_     =      os.path.join(
             __lowerCAmelCase   ,		(filename_prefix + "-" if filename_prefix else "") + VOCAB_FILES_NAMES["vocab_file"])
         lowercase_     =      os.path.join(
             __lowerCAmelCase   ,		(filename_prefix + "-" if filename_prefix else "") + VOCAB_FILES_NAMES["merges_file"])

         with open(__lowerCAmelCase   ,		"w"   ,		encoding="utf-8") as f:
               f.write(json.dumps(self.encoder   ,		indent=2   ,		sort_keys=__lowerCAmelCase   ,		ensure_ascii=__lowerCAmelCase) + "\n")

         lowercase_     =      0
         with open(__lowerCAmelCase   ,		"w"   ,		encoding="utf-8") as writer:
               writer.write("#version: 0.2\n")
               for bpe_tokens, token_index in sorted(self.bpe_ranks.items()   ,		key=lambda __lowerCAmelCase: kv[1]):
                     if index != token_index:
                           logger.warning(
                               F'Saving vocabulary to {merge_file}: BPE merge indices are not consecutive.'
                               " Please check that the tokenizer is not corrupted!")
                           lowercase_     =      token_index
                     writer.write(" ".join(__lowerCAmelCase) + "\n")
                     index += 1

         return vocab_file, merge_file


   def __UpperCAmelCase       (   self				:	List[Any]   ,		__lowerCAmelCase				:	List[int]   ,		__lowerCAmelCase				:	Optional[List[int]] = None)      ->					List[int]:
         if token_ids_a is None:
               return [self.cls_token_id] + token_ids_a + [self.sep_token_id]
         lowercase_     =      [self.cls_token_id]
         lowercase_     =      [self.sep_token_id]
         return cls + token_ids_a + sep + sep + token_ids_a + sep


   def __UpperCAmelCase       (   self				:	Optional[int]   ,		__lowerCAmelCase				:	List[int]   ,		__lowerCAmelCase				:	Optional[List[int]] = None   ,		__lowerCAmelCase				:	bool = False)      ->					List[int]:
         if already_has_special_tokens:
               return super().get_special_tokens_mask(
                   token_ids_a=__lowerCAmelCase   ,		token_ids_a=__lowerCAmelCase   ,		already_has_special_tokens=__lowerCAmelCase)

         if token_ids_a is None:
               return [1] + ([0] * len(__lowerCAmelCase)) + [1]
         return [1] + ([0] * len(__lowerCAmelCase)) + [1, 1] + ([0] * len(__lowerCAmelCase)) + [1]


   def __UpperCAmelCase       (   self				:	Any   ,		__lowerCAmelCase				:	List[int]   ,		__lowerCAmelCase				:	Optional[List[int]] = None)      ->					List[int]:
         lowercase_     =      [self.sep_token_id]
         lowercase_     =      [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]


   def __UpperCAmelCase       (   self				:	Union[str, Any]   ,		__lowerCAmelCase				:	str   ,		__lowerCAmelCase				:	str=False   ,		**__lowerCAmelCase				:	Dict)      ->					Optional[int]:
         lowercase_     =      kwargs.pop("add_prefix_space"   ,		self.add_prefix_space)
         if (is_split_into_words or add_prefix_space) and (len(__lowerCAmelCase) > 0 and not text[0].isspace()):
               lowercase_     =      " " + text
         return (text, kwargs)


   def __UpperCAmelCase       (   self				:	int   ,		__lowerCAmelCase				:	Union[Dict[str, EncodedInput], BatchEncoding]   ,		__lowerCAmelCase				:	Optional[int] = None   ,		__lowerCAmelCase				:	PaddingStrategy = PaddingStrategy.DO_NOT_PAD   ,		__lowerCAmelCase				:	Optional[int] = None   ,		__lowerCAmelCase				:	Optional[bool] = None   ,		)      ->					dict:
         lowercase_     =      super()._pad(
             encoded_inputs=__lowerCAmelCase   ,		max_length=__lowerCAmelCase   ,		padding_strategy=__lowerCAmelCase   ,		pad_to_multiple_of=__lowerCAmelCase   ,		return_attention_mask=__lowerCAmelCase   ,		)

         # Load from model defaults
         if return_attention_mask is None:
               lowercase_     =      "attention_mask" in self.model_input_names

         if return_attention_mask and "global_attention_mask" in encoded_inputs:
               lowercase_     =      encoded_inputs[self.model_input_names[0]]
               # `global_attention_mask` need to have the same length as other (sequential) inputs.
               lowercase_     =      len(encoded_inputs["global_attention_mask"]) != len(__lowerCAmelCase)

               if needs_to_be_padded:
                     lowercase_     =      len(__lowerCAmelCase) - len(encoded_inputs["global_attention_mask"])

                     if self.padding_side == "right":
                           # Use `-1` since `0` in `global_attention_mask` means `local attention` instead of `not to attend`
                           lowercase_     =      (
                               encoded_inputs["global_attention_mask"] + [-1] * difference
                           )
                     elif self.padding_side == "left":
                           lowercase_     =      [-1] * difference + encoded_inputs[
                               "global_attention_mask"
                           ]
                     else:
                           raise ValueError("Invalid padding strategy:" + str(self.padding_side))

         return encoded_inputs







'''simple docstring'''

import logging
from dataclasses import dataclass, field
from pathlib import Path
from typing import Optional, Union

from .generation.configuration_utils import GenerationConfig
from .training_args import TrainingArguments
from .utils import add_start_docstrings


lowerCAmelCase_ : Dict						  =      logging.getLogger(__name__)





@dataclass
@add_start_docstrings(TrainingArguments.__doc__ )
class 							lowercase						(						__lowerCamelCase ):
   lowerCamelCase_    					=field(default=__lowerCamelCase ,				metadata={'help': 'Whether to use SortishSampler or not.'} )
   lowerCamelCase_    					=field(
       default=__lowerCamelCase ,				metadata={'help': 'Whether to use generate to calculate generative metrics (ROUGE, BLEU).'} )
   lowerCamelCase_    					=field(
       default=__lowerCamelCase ,				metadata={
           'help': (
               'The `max_length` to use on each evaluation loop when `predict_with_generate=True`. Will default '
               'to the `max_length` value of the model configuration.'
           )
       } ,				)
   lowerCamelCase_    					=field(
       default=__lowerCamelCase ,				metadata={
           'help': (
               'The `num_beams` to use on each evaluation loop when `predict_with_generate=True`. Will default '
               'to the `num_beams` value of the model configuration.'
           )
       } ,				)
   lowerCamelCase_    					=field(
       default=__lowerCamelCase ,				metadata={
           'help': 'Model id, file path or url pointing to a GenerationConfig json file, to use during prediction.'
       } ,				)


   def __UpperCAmelCase       (   self				:	Tuple)      ->					Optional[int]:
         lowercase_     =      super().to_dict()
         for k, v in d.items():
               if isinstance(__lowerCAmelCase   ,		__lowerCAmelCase):
                     lowercase_     =      v.to_dict()
         return d






