


'''simple docstring'''




import logging
import os
from typing import List, TextIO, Union

from conllu import parse_incr
from utils_ner import InputExample, Split, TokenClassificationTask


_a   :   str												=   logging.getLogger(__name__)




class 			_lowercase (	__lowercase							):
   def __init__(						self       :      int       ,   SCREAMING_SNAKE_CASE_       :      Optional[int]=-1      ) ->							List[Any]:
        # in NER datasets, the last column is usually reserved for NER label
        __snake_case           =						label_idx
   def a  (						self       :      Any       ,   SCREAMING_SNAKE_CASE_       :      Dict       ,   SCREAMING_SNAKE_CASE_       :      Union[Split, str]      ) ->							List[InputExample]:
        if isinstance(SCREAMING_SNAKE_CASE_       ,   SCREAMING_SNAKE_CASE_      ):
             __snake_case           =						mode.value
        __snake_case           =						os.path.join(SCREAMING_SNAKE_CASE_       ,   f'{mode}.txt'      )
        __snake_case           =						1
        __snake_case           =						[]
        with open(SCREAMING_SNAKE_CASE_       ,   encoding='utf-8'      ) as f:
             __snake_case           =						[]
             __snake_case           =						[]
             for line in f:
                  if line.startswith('-DOCSTART-'      ) or line == "" or line == "\n":
                       if words:
                            examples.append(InputExample(guid=f'{mode}-{guid_index}'       ,   words=SCREAMING_SNAKE_CASE_       ,   labels=SCREAMING_SNAKE_CASE_      )      )
                            guid_index += 1
                            __snake_case           =						[]
                            __snake_case           =						[]
                  else:
                       __snake_case           =						line.split(' '      )
                       words.append(splits[0]      )
                       if len(SCREAMING_SNAKE_CASE_      ) > 1:
                            labels.append(splits[self.label_idx].replace('\n'       ,   ''      )      )
                       else:
                            # Examples could have no label for mode = "test"
                            labels.append('O'      )
             if words:
                  examples.append(InputExample(guid=f'{mode}-{guid_index}'       ,   words=SCREAMING_SNAKE_CASE_       ,   labels=SCREAMING_SNAKE_CASE_      )      )
        return examples
   def a  (						self       :      Optional[Any]       ,   SCREAMING_SNAKE_CASE_       :      TextIO       ,   SCREAMING_SNAKE_CASE_       :      TextIO       ,   SCREAMING_SNAKE_CASE_       :      List      ) ->							List[Any]:
        __snake_case           =						0
        for line in test_input_reader:
             if line.startswith('-DOCSTART-'      ) or line == "" or line == "\n":
                  writer.write(SCREAMING_SNAKE_CASE_      )
                  if not preds_list[example_id]:
                       example_id += 1
             elif preds_list[example_id]:
                  __snake_case           =						line.split()[0] + ' ' + preds_list[example_id].pop(0      ) + '\n'
                  writer.write(SCREAMING_SNAKE_CASE_      )
             else:
                  logger.warning('Maximum sequence length exceeded: No prediction for \'%s\'.'       ,   line.split()[0]      )





   def a  (						self       :      int       ,   SCREAMING_SNAKE_CASE_       :      str      ) ->							List[str]:
        if path:
             with open(SCREAMING_SNAKE_CASE_       ,   'r'      ) as f:
                  __snake_case           =						f.read().splitlines()
             if "O" not in labels:
                  __snake_case           =						['O'] + labels
             return labels
        else:
             return ["O", "B-MISC", "I-MISC", "B-PER", "I-PER", "B-ORG", "I-ORG", "B-LOC", "I-LOC"]




class 			_lowercase (	__lowercase							):
   def __init__(						self       :      int      ) ->							List[str]:
        # in CONLL2003 dataset chunk column is second-to-last
        super().__init__(label_idx=-2      )





   def a  (						self       :      List[Any]       ,   SCREAMING_SNAKE_CASE_       :      str      ) ->							List[str]:
        if path:
             with open(SCREAMING_SNAKE_CASE_       ,   'r'      ) as f:
                  __snake_case           =						f.read().splitlines()
             if "O" not in labels:
                  __snake_case           =						['O'] + labels
             return labels
        else:
             return [
                 "O",
                 "B-ADVP",
                 "B-INTJ",
                 "B-LST",
                 "B-PRT",
                 "B-NP",
                 "B-SBAR",
                 "B-VP",
                 "B-ADJP",
                 "B-CONJP",
                 "B-PP",
                 "I-ADVP",
                 "I-INTJ",
                 "I-LST",
                 "I-PRT",
                 "I-NP",
                 "I-SBAR",
                 "I-VP",
                 "I-ADJP",
                 "I-CONJP",
                 "I-PP",
             ]




class 			_lowercase (	__lowercase							):
   def a  (						self       :      Optional[Any]       ,   SCREAMING_SNAKE_CASE_       :      Any       ,   SCREAMING_SNAKE_CASE_       :      Union[Split, str]      ) ->							List[InputExample]:
        if isinstance(SCREAMING_SNAKE_CASE_       ,   SCREAMING_SNAKE_CASE_      ):
             __snake_case           =						mode.value
        __snake_case           =						os.path.join(SCREAMING_SNAKE_CASE_       ,   f'{mode}.txt'      )
        __snake_case           =						1
        __snake_case           =						[]

        with open(SCREAMING_SNAKE_CASE_       ,   encoding='utf-8'      ) as f:
             for sentence in parse_incr(SCREAMING_SNAKE_CASE_      ):
                  __snake_case           =						[]
                  __snake_case           =						[]
                  for token in sentence:
                       words.append(token['form']      )
                       labels.append(token['upos']      )
                  assert len(SCREAMING_SNAKE_CASE_      ) == len(SCREAMING_SNAKE_CASE_      )
                  if words:
                       examples.append(InputExample(guid=f'{mode}-{guid_index}'       ,   words=SCREAMING_SNAKE_CASE_       ,   labels=SCREAMING_SNAKE_CASE_      )      )
                       guid_index += 1
        return examples
   def a  (						self       :      Tuple       ,   SCREAMING_SNAKE_CASE_       :      TextIO       ,   SCREAMING_SNAKE_CASE_       :      TextIO       ,   SCREAMING_SNAKE_CASE_       :      List      ) ->							List[Any]:
        __snake_case           =						0
        for sentence in parse_incr(SCREAMING_SNAKE_CASE_      ):
             __snake_case           =						preds_list[example_id]
             __snake_case           =						''
             for token in sentence:
                  out += f'{token["form"]} ({token["upos"]}|{s_p.pop(0      )}) '
             out += "\n"
             writer.write(SCREAMING_SNAKE_CASE_      )
             example_id += 1





   def a  (						self       :      Union[str, Any]       ,   SCREAMING_SNAKE_CASE_       :      str      ) ->							List[str]:
        if path:
             with open(SCREAMING_SNAKE_CASE_       ,   'r'      ) as f:
                  return f.read().splitlines()
        else:
             return [
                 "ADJ",
                 "ADP",
                 "ADV",
                 "AUX",
                 "CCONJ",
                 "DET",
                 "INTJ",
                 "NOUN",
                 "NUM",
                 "PART",
                 "PRON",
                 "PROPN",
                 "PUNCT",
                 "SCONJ",
                 "SYM",
                 "VERB",
                 "X",
             ]












import json
import os
from typing import Dict, List, Optional, Tuple

import regex as re

from ...tokenization_utils import PreTrainedTokenizer
from ...utils import logging


__a:     Any   					=					logging.get_logger(__name__)


__a:     Dict   					=					{
    '''vocab_file''': '''vocab.json''',
    '''merges_file''': '''merges.txt''',
    '''tokenizer_config_file''': '''tokenizer_config.json''',
}

__a:     int   					=					{
    '''vocab_file''': {
        '''facebook/blenderbot_small-90M''': '''https://huggingface.co/facebook/blenderbot_small-90M/resolve/main/vocab.json'''
    },
    '''merges_file''': {
        '''facebook/blenderbot_small-90M''': '''https://huggingface.co/facebook/blenderbot_small-90M/resolve/main/merges.txt'''
    },
    '''tokenizer_config_file''': {
        '''facebook/blenderbot_small-90M''': (
            '''https://huggingface.co/facebook/blenderbot_small-90M/resolve/main/tokenizer_config.json'''
        )
    },
}

__a:     str   					=					{'''facebook/blenderbot_small-90M''': 512}




def       _SCREAMING_SNAKE_CASE (							__snake_case )				->						List[str]:
       _UpperCAmelCase							=    set()
       _UpperCAmelCase							=    word[0]
       for char in word[1:]:
              pairs.add((prev_char, char) )
              _UpperCAmelCase							=    char

       _UpperCAmelCase							=    set(__snake_case )
       return pairs





class 		SCREAMING_SNAKE_CASE__	(  UpperCAmelCase     ):

  '''simple docstring'''







  _lowerCamelCase    =  VOCAB_FILES_NAMES
  _lowerCamelCase    =  PRETRAINED_VOCAB_FILES_MAP
  _lowerCamelCase    =  PRETRAINED_POSITIONAL_EMBEDDINGS_SIZES
  _lowerCamelCase    =  ['''input_ids''', '''attention_mask''']


  def __init__(      self		:			List[Any]       ,				lowerCamelCase		:			Optional[int]       ,				lowerCamelCase		:			Dict       ,				lowerCamelCase		:			List[str]="__start__"       ,				lowerCamelCase		:			List[Any]="__end__"       ,				lowerCamelCase		:			Any="__unk__"       ,				lowerCamelCase		:			Optional[Any]="__null__"       ,				**lowerCamelCase		:			Optional[Any]       ,				)						->	Tuple:


         """simple docstring"""
         super().__init__(unk_token=lowerCamelCase       ,				bos_token=lowerCamelCase       ,				eos_token=lowerCamelCase       ,				pad_token=lowerCamelCase       ,				**lowerCamelCase							)

         with open(lowerCamelCase       ,				encoding="""utf-8"""							) as vocab_handle:
                _UpperCAmelCase							=    json.load(lowerCamelCase							)
         _UpperCAmelCase							=    {v: k for k, v in self.encoder.items()}
         with open(lowerCamelCase       ,				encoding="""utf-8"""							) as merges_handle:
                _UpperCAmelCase							=    merges_handle.read().split("""\n"""							)[1:-1]
         _UpperCAmelCase							=    [tuple(merge.split()							) for merge in merges]
         _UpperCAmelCase							=    dict(zip(lowerCamelCase       ,				range(len(lowerCamelCase							)							)							)							)
         _UpperCAmelCase							=    {}


  @property
  def  lowerCamelCase       (      self		:			str							)						->	int:


         """simple docstring"""
         return len(self.encoder							)


  def  lowerCamelCase       (      self		:			List[Any]							)						->	Dict:


         """simple docstring"""
         return dict(self.encoder       ,				**self.added_tokens_encoder							)


  def  lowerCamelCase       (      self		:			Optional[Any]       ,				lowerCamelCase		:			str							)						->	str:


         """simple docstring"""
         if token in self.cache:
                return self.cache[token]
         _UpperCAmelCase							=    re.sub("""([.,!?()])"""       ,				r""" \1"""       ,				lowerCamelCase							)
         _UpperCAmelCase							=    re.sub("""(')"""       ,				r""" \1 """       ,				lowerCamelCase							)
         _UpperCAmelCase							=    re.sub(r"""\s{2,}"""       ,				""" """       ,				lowerCamelCase							)
         if "\n" in token:
                _UpperCAmelCase							=    token.replace("""\n"""       ,				""" __newln__"""							)

         _UpperCAmelCase							=    token.split(""" """							)
         _UpperCAmelCase							=    []
         for token in tokens:
                if not len(lowerCamelCase							):
                       continue

                _UpperCAmelCase							=    token.lower()
                _UpperCAmelCase							=    tuple(lowerCamelCase							)
                _UpperCAmelCase							=    tuple(list(word[:-1]							) + [word[-1] + """</w>"""]							)
                _UpperCAmelCase							=    get_pairs(lowerCamelCase							)

                if not pairs:
                       words.append(lowerCamelCase							)
                       continue

                while True:
                       _UpperCAmelCase							=    min(lowerCamelCase       ,				key=lambda lowerCamelCase							: self.bpe_ranks.get(lowerCamelCase       ,				float("""inf"""							)							)							)
                       if bigram not in self.bpe_ranks:
                              break
                       _UpperCAmelCase	,			_UpperCAmelCase							=    bigram
                       _UpperCAmelCase							=    []
                       _UpperCAmelCase							=    0

                       while i < len(lowerCamelCase							):
                              try:
                                     _UpperCAmelCase							=    word.index(lowerCamelCase       ,				lowerCamelCase							)
                                     new_word.extend(word[i:j]							)
                                     _UpperCAmelCase							=    j
                              except ValueError:
                                     new_word.extend(word[i:]							)
                                     break

                              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
                       _UpperCAmelCase							=    tuple(lowerCamelCase							)
                       _UpperCAmelCase							=    new_word
                       if len(lowerCamelCase							) == 1:
                              break
                       else:
                              _UpperCAmelCase							=    get_pairs(lowerCamelCase							)
                _UpperCAmelCase							=    """@@ """.join(lowerCamelCase							)
                _UpperCAmelCase							=    word[:-4]

                _UpperCAmelCase							=    word
                words.append(lowerCamelCase							)
         return " ".join(lowerCamelCase							)


  def  lowerCamelCase       (      self		:			Any       ,				lowerCamelCase		:			str							)						->	List[str]:


         """simple docstring"""
         _UpperCAmelCase							=    []

         _UpperCAmelCase							=    re.findall(r"""\S+\n?"""       ,				lowerCamelCase							)

         for token in words:
                split_tokens.extend(list(self.bpe(lowerCamelCase							).split(""" """							)							)							)
         return split_tokens


  def  lowerCamelCase       (      self		:			Tuple       ,				lowerCamelCase		:			str							)						->	int:


         """simple docstring"""
         _UpperCAmelCase							=    token.lower()
         return self.encoder.get(lowerCamelCase       ,				self.encoder.get(self.unk_token							)							)


  def  lowerCamelCase       (      self		:			List[str]       ,				lowerCamelCase		:			int							)						->	str:


         """simple docstring"""
         return self.decoder.get(lowerCamelCase       ,				self.unk_token							)


  def  lowerCamelCase       (      self		:			Dict       ,				lowerCamelCase		:			List[str]							)						->	str:


         """simple docstring"""
         _UpperCAmelCase							=    """ """.join(lowerCamelCase							).replace("""@@ """       ,				""""""							).strip()
         return out_string





  def  lowerCamelCase       (      self		:			List[Any]       ,				lowerCamelCase		:			str       ,				lowerCamelCase		:			Optional[str] = None							)						->	Tuple[str]:


         """simple docstring"""
         if not os.path.isdir(lowerCamelCase							):
                logger.error(f"""Vocabulary path ({save_directory}) should be a directory"""							)
                return
         _UpperCAmelCase							=    os.path.join(
             lowerCamelCase       ,				(filename_prefix + """-""" if filename_prefix else """""") + VOCAB_FILES_NAMES["""vocab_file"""]							)
         _UpperCAmelCase							=    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"""							)

         _UpperCAmelCase							=    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!"""							)
                              _UpperCAmelCase							=    token_index
                       writer.write(""" """.join(lowerCamelCase							) + """\n"""							)
                       index += 1

         return vocab_file, merge_file