




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

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


_lowerCamelCase     :		Optional[Any]								=       logging.get_logger(__name__)


_lowerCamelCase     :		Tuple								=       {
    """vocab_file""": """vocab.json""",
    """tokenizer_config_file""": """tokenizer_config.json""",
    """merges_file""": """merges.txt""",
}

_lowerCamelCase     :		Union[str, Any]								=       {
    """vocab_file""": {
        """facebook/s2t-wav2vec2-large-en-de""": (
            """https://huggingface.co/facebook/s2t-wav2vec2-large-en-de/resolve/main/vocab.json"""
        ),
    },
    """tokenizer_config_file""": {
        """facebook/s2t-wav2vec2-large-en-de""": (
            """https://huggingface.co/facebook/s2t-wav2vec2-large-en-de/resolve/main/tokenizer_config.json"""
        ),
    },
    """merges_file""": {
        """facebook/s2t-wav2vec2-large-en-de""": (
            """https://huggingface.co/facebook/s2t-wav2vec2-large-en-de/resolve/main/merges.txt"""
        ),
    },
}

_lowerCamelCase     :		Union[str, Any]								=       """</w>"""
_lowerCamelCase     :		Any								=       """@@ """







def SCREAMING_SNAKE_CASE    (	lowercase_						)       ->	Optional[int]:



       """simple docstring"""

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


# Speech2Text2 has no max input length
_lowerCamelCase     :		List[str]								=       {"""facebook/s2t-wav2vec2-large-en-de""": 1024}


class     UpperCamelCase_   (			UpperCAmelCase__					):

    '''simple docstring'''






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


    def __init__(      self				:     str ,			UpperCAmelCase__				:     Dict ,			UpperCAmelCase__				:     Union[str, Any]="<s>" ,			UpperCAmelCase__				:     int="<pad>" ,			UpperCAmelCase__				:     Union[str, Any]="</s>" ,			UpperCAmelCase__				:     Tuple="<unk>" ,			UpperCAmelCase__				:     Optional[int]=False ,			UpperCAmelCase__				:     Union[str, Any]=None ,			**UpperCAmelCase__				:     int ,			)						->Union[str, Any]:





           '''simple docstring'''

           super().__init__(
               unk_token=UpperCAmelCase__ ,			bos_token=UpperCAmelCase__ ,			eos_token=UpperCAmelCase__ ,			pad_token=UpperCAmelCase__ ,			do_lower_case=UpperCAmelCase__ ,			**UpperCAmelCase__ ,			)

           A__							=   do_lower_case

           with open(UpperCAmelCase__ ,			encoding='''utf-8''') as vocab_handle:
                  A__							=   json.load(UpperCAmelCase__)
           A__							=   {v: k for k, v in self.encoder.items()}

           if merges_file is None:
                  logger.info(f"""No merges files provided. {self.__class__.__name__} can only be used for decoding.""")

                  A__							=   None
                  A__							=   None
           else:
                  with open(UpperCAmelCase__ ,			encoding='''utf-8''') as merges_handle:
                         A__							=   merges_handle.read().split('''\n''')[:-1]

                  A__							=   [tuple(merge.split()[:2]) for merge in merges]
                  A__							=   dict(zip(UpperCAmelCase__ ,			range(len(UpperCAmelCase__))))
                  A__							=   {}


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





           '''simple docstring'''

           return len(self.decoder)


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





           '''simple docstring'''

           return dict(self.encoder ,			**self.added_tokens_encoder)


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





           '''simple docstring'''

           A__							=   tuple(token[:-1]) + (token[-1] + BPE_TOKEN_MERGES,)
           if token in self.cache:
                  return self.cache[token]
           A__							=   get_pairs(UpperCAmelCase__)

           if not pairs:
                  return token

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

                         if word[i] == first and i < len(UpperCAmelCase__) - 1 and word[i + 1] == second:
                                new_word.append(first + second)
                                i += 2
                         else:
                                new_word.append(word[i])
                                i += 1
                  A__							=   tuple(UpperCAmelCase__)
                  A__							=   new_word
                  if len(UpperCAmelCase__) == 1:
                         break
                  else:
                         A__							=   get_pairs(UpperCAmelCase__)
           A__							=   ''' '''.join(UpperCAmelCase__)
           if word == "\n  " + BPE_TOKEN_MERGES:
                  A__							=   '''\n''' + BPE_TOKEN_MERGES

           if word.endswith(UpperCAmelCase__):
                  A__							=   word.replace(UpperCAmelCase__ ,			'''''')

           A__							=   word.replace(''' ''' ,			UpperCAmelCase__)
           A__							=   word
           return word


    def 	SCREAMING_SNAKE_CASE							(      self				:     List[Any] ,			UpperCAmelCase__				:     Tuple)						->Tuple:





           '''simple docstring'''

           if self.bpe_ranks is None:
                  raise ValueError(
                      '''This tokenizer was instantiated without a `merges.txt` file, so'''
                      ''' that it can only be used for decoding, not for encoding.'''
                      '''Make sure to provide `merges.txt` file at instantiation to enable '''
                      '''encoding.''')

           if self.do_lower_case:
                  A__							=   text.lower()

           A__							=   text.split()

           A__							=   []
           for token in text:
                  if token:
                         split_tokens.extend(list(self.bpe(UpperCAmelCase__).split(''' ''')))

           return split_tokens


    def 	SCREAMING_SNAKE_CASE							(      self				:     Optional[Any] ,			UpperCAmelCase__				:     str)						->int:





           '''simple docstring'''

           return self.encoder.get(UpperCAmelCase__ ,			self.encoder.get(self.unk_token))


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





           '''simple docstring'''

           A__							=   self.decoder.get(UpperCAmelCase__ ,			self.unk_token)
           return result


    def 	SCREAMING_SNAKE_CASE							(      self				:     str ,			UpperCAmelCase__				:     List[str])						->str:





           '''simple docstring'''

           A__							=   ''' '''.join(UpperCAmelCase__)

           # make sure @@ tokens are concatenated
           A__							=   ''''''.join(string.split(UpperCAmelCase__))

           return string





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





           '''simple docstring'''

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

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

           A__							=   0
           if self.bpe_ranks is None:
                  return (vocab_file,)

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

           return (vocab_file, merges_file)











import unittest

from transformers import is_torch_available
from transformers.testing_utils import require_torch


if is_torch_available():
  import torch

  from transformers.generation import DisjunctiveConstraint


@require_torch
class     UpperCamelCase_   (			unittest.TestCase					):

    '''simple docstring'''






    def 	SCREAMING_SNAKE_CASE							(      self				:     Dict)						->Tuple:





           '''simple docstring'''

           A__							=   [[1, 2, 4], [1, 2, 3, 4]]
           A__							=   DisjunctiveConstraint(UpperCAmelCase__)
           self.assertTrue(isinstance(dc.token_ids ,			UpperCAmelCase__))

           with self.assertRaises(UpperCAmelCase__):
                  DisjunctiveConstraint(torch.LongTensor([[1, 2, 4], [1, 2, 3]]))

           with self.assertRaises(UpperCAmelCase__):
                  DisjunctiveConstraint([torch.LongTensor([1, 2, 4]), torch.LongTensor([1, 2, 3, 4, 5])])


    def 	SCREAMING_SNAKE_CASE							(      self				:     int)						->str:





           '''simple docstring'''

           A__							=   [[1, 2], [1, 2, 3, 4]]

           with self.assertRaises(UpperCAmelCase__):
                  DisjunctiveConstraint(UpperCAmelCase__)  # fails here


    def 	SCREAMING_SNAKE_CASE							(      self				:     Any)						->str:





           '''simple docstring'''

           A__							=   [[1, 2, 3], [1, 2, 4]]

           A__							=   DisjunctiveConstraint(UpperCAmelCase__)

           A__			,							A__			,							A__							=   dc.update(1)
           A__							=   stepped is True and completed is False and reset is False
           self.assertTrue(UpperCAmelCase__)
           self.assertTrue(not dc.completed)
           self.assertTrue(dc.current_seq == [1])

           A__			,							A__			,							A__							=   dc.update(2)
           A__							=   stepped is True and completed is False and reset is False
           self.assertTrue(UpperCAmelCase__)
           self.assertTrue(not dc.completed)
           self.assertTrue(dc.current_seq == [1, 2])

           A__			,							A__			,							A__							=   dc.update(3)
           A__							=   stepped is True and completed is True and reset is False
           self.assertTrue(UpperCAmelCase__)
           self.assertTrue(dc.completed)  # Completed!
           self.assertTrue(dc.current_seq == [1, 2, 3])





    def 	SCREAMING_SNAKE_CASE							(      self				:     Optional[Any])						->Tuple:





           '''simple docstring'''

           A__							=   [[1, 2, 3], [1, 2, 4, 5], [1, 2, 5]]

           A__							=   DisjunctiveConstraint(UpperCAmelCase__)

           A__			,							A__			,							A__							=   dc.update(1)
           self.assertTrue(not dc.completed)
           self.assertTrue(dc.current_seq == [1])

           A__			,							A__			,							A__							=   dc.update(2)
           self.assertTrue(not dc.completed)
           self.assertTrue(dc.current_seq == [1, 2])

           A__			,							A__			,							A__							=   dc.update(4)
           self.assertTrue(not dc.completed)
           self.assertTrue(dc.current_seq == [1, 2, 4])

           A__			,							A__			,							A__							=   dc.update(5)
           self.assertTrue(dc.completed)  # Completed!
           self.assertTrue(dc.current_seq == [1, 2, 4, 5])

           dc.reset()

           A__			,							A__			,							A__							=   dc.update(1)
           self.assertTrue(not dc.completed)
           self.assertTrue(dc.remaining() == 3)
           self.assertTrue(dc.current_seq == [1])

           A__			,							A__			,							A__							=   dc.update(2)
           self.assertTrue(not dc.completed)
           self.assertTrue(dc.remaining() == 2)
           self.assertTrue(dc.current_seq == [1, 2])

           A__			,							A__			,							A__							=   dc.update(5)
           self.assertTrue(dc.completed)  # Completed!
           self.assertTrue(dc.remaining() == 0)
           self.assertTrue(dc.current_seq == [1, 2, 5])


