


"""simple docstring"""

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

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


UpperCAmelCase__					=logging.get_logger(__name__)


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

UpperCAmelCase__					={
    "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"
        ),
    },
}

UpperCAmelCase__					="</w>"
UpperCAmelCase__					="@@ "


def lowerCAmelCase_   (					UpperCamelCase__						:			Optional[Any]			):






 """simple docstring"""







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


# Speech2Text2 has no max input length
UpperCAmelCase__					={"facebook/s2t-wav2vec2-large-en-de": 1024}





class  lowerCamelCase__    (		_a     ):
      a			:  List[Any]           =		VOCAB_FILES_NAMES
      a			:  Optional[int]           =		PRETRAINED_VOCAB_FILES_MAP
      a			:  str           =		PRETRAINED_POSITIONAL_EMBEDDINGS_SIZES
      a			:  str           =		["""input_ids""", """attention_mask"""]
      def __init__(		self						:						Optional[Any]   ,							A_						:						Tuple   ,							A_						:						str="<s>"   ,							A_						:						Optional[Any]="<pad>"   ,							A_						:						Dict="</s>"   ,							A_						:						List[str]="<unk>"   ,							A_						:						List[str]=False   ,							A_						:						Dict=None   ,							**A_						:						List[Any]   ,							):






       '''simple docstring'''


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

       __lowercase						=						do_lower_case

       with open(A_   ,							encoding="""utf-8"""				) as vocab_handle:
        __lowercase						=						json.load(A_				)
       __lowercase						=						{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.'''				)

        __lowercase						=						None
        __lowercase						=						None
       else:
        with open(A_   ,							encoding="""utf-8"""				) as merges_handle:
         __lowercase						=						merges_handle.read().split("""\n"""				)[:-1]

        __lowercase						=						[tuple(merge.split()[:2]				) for merge in merges]
        __lowercase						=						dict(zip(A_   ,							range(len(A_				)				)				)				)
        __lowercase						=						{}
      @property
      def SCREAMING_SNAKE_CASE_						(		self						:						Optional[Any]				):






       '''simple docstring'''


       return len(self.decoder				)
      def SCREAMING_SNAKE_CASE_						(		self						:						Tuple				):






       '''simple docstring'''


       return dict(self.encoder   ,							**self.added_tokens_encoder				)
      def SCREAMING_SNAKE_CASE_						(		self						:						Optional[Any]   ,							A_						:						List[str]				):






       '''simple docstring'''


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

       if not pairs:
        return token

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

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

       if word.endswith(A_				):
        __lowercase						=						word.replace(A_   ,							""""""				)

       __lowercase						=						word.replace(""" """   ,							A_				)
       __lowercase						=						word
       return word
      def SCREAMING_SNAKE_CASE_						(		self						:						str   ,							A_						:						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:
        __lowercase						=						text.lower()

       __lowercase						=						text.split()

       __lowercase						=						[]
       for token in text:
        if token:
         split_tokens.extend(list(self.bpe(A_				).split(""" """				)				)				)

       return split_tokens
      def SCREAMING_SNAKE_CASE_						(		self						:						Any   ,							A_						:						str				):






       '''simple docstring'''


       return self.encoder.get(A_   ,							self.encoder.get(self.unk_token				)				)
      def SCREAMING_SNAKE_CASE_						(		self						:						Optional[int]   ,							A_						:						int				):






       '''simple docstring'''


       __lowercase						=						self.decoder.get(A_   ,							self.unk_token				)
       return result
      def SCREAMING_SNAKE_CASE_						(		self						:						Dict   ,							A_						:						List[str]				):






       '''simple docstring'''


       __lowercase						=						""" """.join(A_				)

       # make sure @@ tokens are concatenated
       __lowercase						=						"""""".join(string.split(A_				)				)

       return string






      def SCREAMING_SNAKE_CASE_						(		self						:						List[str]   ,							A_						:						str   ,							A_						:						Optional[str] = None				):






       '''simple docstring'''


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

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

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

       with open(A_   ,							"""w"""   ,							encoding="""utf-8"""				) as writer:
        for bpe_tokens, token_index in sorted(self.bpe_ranks.items()   ,							key=lambda A_				: 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!"""				)
          __lowercase						=						token_index
         writer.write(""" """.join(A_				) + """\n"""				)
         index += 1

       return (vocab_file, merges_file)




"""simple docstring"""

import pytest
import requests

from datasets.utils.file_utils import http_head

from .utils import OfflineSimulationMode, RequestWouldHangIndefinitelyError, offline


@pytest.mark.integration
def lowerCAmelCase_   (					):






 """simple docstring"""







 with offline(OfflineSimulationMode.CONNECTION_TIMES_OUT			):
  with pytest.raises(UpperCamelCase__			):
   requests.request("""GET"""					, """https://huggingface.co"""			)
  with pytest.raises(requests.exceptions.ConnectTimeout			):
   requests.request("""GET"""					, """https://huggingface.co"""					, timeout=1.0			)


@pytest.mark.integration
def lowerCAmelCase_   (					):






 """simple docstring"""







 with offline(OfflineSimulationMode.CONNECTION_FAILS			):
  with pytest.raises(requests.exceptions.ConnectionError			):
   requests.request("""GET"""					, """https://huggingface.co"""			)


def lowerCAmelCase_   (					):






 """simple docstring"""







 with offline(OfflineSimulationMode.HF_DATASETS_OFFLINE_SET_TO_1			):
  with pytest.raises(UpperCamelCase__			):
   http_head("""https://huggingface.co"""			)
