




import inspect
import json
import os
import tempfile
import unittest

from transformers.models.speech_to_text_a import SpeechaTextaTokenizer
from transformers.models.speech_to_text_a.tokenization_speech_to_text_a import VOCAB_FILES_NAMES

from ...test_tokenization_common import TokenizerTesterMixin
class       _UpperCamelCase   (					lowerCAmelCase						,							unittest.TestCase		):
      UpperCAmelCase_          =		SpeechaTextaTokenizer
      UpperCAmelCase_          =		False
      def 						UpperCAmelCase_    (      self :int   )  ->      Union[str, Any]:
       super().setUp()

       UpperCAmelCase__							=    "<s> <pad> </s> <unk> here@@ a couple of@@ words for the he@@ re@@ vocab".split(" "   )
       UpperCAmelCase__							=    ["he re</w> 123", "here a 1456"]
       UpperCAmelCase__							=    dict(zip(lowerCamelCase			,   range(len(lowerCamelCase   )   )   )   )

       UpperCAmelCase__							=    {"pad_token": "<pad>", "unk_token": "<unk>", "bos_token": "<s>", "eos_token": "</s>"}

       UpperCAmelCase__							=    tempfile.mkdtemp()
       UpperCAmelCase__							=    os.path.join(self.tmpdirname			,   VOCAB_FILES_NAMES["vocab_file"]   )
       UpperCAmelCase__							=    os.path.join(self.tmpdirname			,   VOCAB_FILES_NAMES["merges_file"]   )

       with open(self.vocab_file			,   "w"			,   encoding="utf-8"   ) as fp:
        fp.write(json.dumps(lowerCamelCase   ) + "\n"   )

       with open(self.merges_file			,   "w"   ) as fp:
        fp.write("\n".join(lowerCamelCase   )   )
      def 						UpperCAmelCase_    (      self :int   )  ->      Optional[int]:
       UpperCAmelCase__							=    list(self.get_tokenizer().get_vocab().keys()   )

       self.assertEqual(vocab_keys[0]			,   "<s>"   )
       self.assertEqual(vocab_keys[1]			,   "<pad>"   )
       self.assertEqual(vocab_keys[-1]			,   "vocab"   )
       self.assertEqual(len(lowerCamelCase   )			,   14   )
      def 						UpperCAmelCase_    (      self :str   )  ->      int:
       self.assertEqual(self.get_tokenizer().vocab_size			,   14   )
      def 						UpperCAmelCase_    (      self :Optional[Any]   )  ->      Any:
       UpperCAmelCase__							=    SpeechaTextaTokenizer.from_pretrained(self.tmpdirname   )

       # make sure @@ is correctly concatenated
       UpperCAmelCase__							=    [4, 6, 8, 7, 10]  # ["here@@", "couple", "words", "of@@", "the"]
       UpperCAmelCase__							=    tokenizer.decode(lowerCamelCase   )

       self.assertTrue(output_string == "herecouple words ofthe"   )
      def 						UpperCAmelCase_    (      self :str   )  ->      int:
       UpperCAmelCase__							=    SpeechaTextaTokenizer.from_pretrained(self.tmpdirname   )

       with tempfile.TemporaryDirectory() as tmp_dirname:
        tokenizer.save_pretrained(lowerCamelCase   )
        os.remove(os.path.join(lowerCamelCase			,   "merges.txt"   )   )

        # load tokenizer without merges file should not throw an error
        UpperCAmelCase__							=    SpeechaTextaTokenizer.from_pretrained(lowerCamelCase   )

       with tempfile.TemporaryDirectory() as tmp_dirname:
        # save tokenizer and load again
        tokenizer.save_pretrained(lowerCamelCase   )
        UpperCAmelCase__							=    SpeechaTextaTokenizer.from_pretrained(lowerCamelCase   )

       self.assertIsNotNone(lowerCamelCase   )







      def 						UpperCAmelCase_    (      self :str   )  ->      Any:
       if not self.test_slow_tokenizer:
        return

       UpperCAmelCase__							=    inspect.signature(self.tokenizer_class.__init__   )
       UpperCAmelCase__							=    self.get_tokenizer()

       for parameter_name, parameter in signature.parameters.items():
        if parameter.default != inspect.Parameter.empty and parameter_name != "merges_file":
         self.assertIn(lowerCamelCase			,   tokenizer.init_kwargs   )











from typing import Optional

from ..utils.logging import get_logger
from .audio_classificiation import AudioClassification
from .automatic_speech_recognition import AutomaticSpeechRecognition
from .base import TaskTemplate
from .image_classification import ImageClassification
from .language_modeling import LanguageModeling
from .question_answering import QuestionAnsweringExtractive
from .summarization import Summarization
from .text_classification import TextClassification


_lowerCAmelCase    : Any		= [
    "AutomaticSpeechRecognition",
    "AudioClassification",
    "ImageClassification",
    "LanguageModeling",
    "QuestionAnsweringExtractive",
    "Summarization",
    "TaskTemplate",
    "TextClassification",
]

_lowerCAmelCase    : Dict		= get_logger(__name__)


_lowerCAmelCase    : Optional[Any]		= {
    AutomaticSpeechRecognition.task: AutomaticSpeechRecognition,
    AudioClassification.task: AudioClassification,
    ImageClassification.task: ImageClassification,
    LanguageModeling.task: LanguageModeling,
    QuestionAnsweringExtractive.task: QuestionAnsweringExtractive,
    Summarization.task: Summarization,
    TextClassification.task: TextClassification,
}



def     lowerCAmelCase		(		_lowerCAmelCase				: dict						):




 """simple docstring"""







 UpperCAmelCase__							=    task_template_dict.get("task"						)
 if task_name is None:
  logger.warning(F'''Couldn\'t find template for task \'{task_name}\'. Available templates: {list(_lowerCAmelCase						)}'''						)
  return None
 UpperCAmelCase__							=    NAMEaTEMPLATE.get(_lowerCAmelCase						)
 return template.from_dict(_lowerCAmelCase						)





