

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 							A_			(		snake_case__							,     unittest.TestCase ):
     _lowercase      :					Union[str, Any]       =     SpeechaTextaTokenizer
     _lowercase      :					List[str]       =     False


     def   UpperCAmelCase  (							self      :		List[str] )							->     Union[str, Any]:
      super().setUp()

      __lowerCAmelCase:       List[Any]            =				'<s> <pad> </s> <unk> here@@ a couple of@@ words for the he@@ re@@ vocab'.split(' ' )
      __lowerCAmelCase:       int            =				['he re</w> 123', 'here a 1456']
      __lowerCAmelCase:       Tuple            =				dict(zip(UpperCAmelCase      ,  range(len(UpperCAmelCase ) ) ) )

      __lowerCAmelCase:       List[Any]            =				{'pad_token': '<pad>', 'unk_token': '<unk>', 'bos_token': '<s>', 'eos_token': '</s>'}

      __lowerCAmelCase:       int            =				tempfile.mkdtemp()
      __lowerCAmelCase:       List[str]            =				os.path.join(self.tmpdirname      ,  VOCAB_FILES_NAMES['vocab_file'] )
      __lowerCAmelCase:       Union[str, Any]            =				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(UpperCAmelCase ) + '\n' )

      with open(self.merges_file      ,  'w' ) as fp:
       fp.write('\n'.join(UpperCAmelCase ) )


     def   UpperCAmelCase  (							self      :		str )							->     List[str]:
      __lowerCAmelCase:       str            =				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(UpperCAmelCase )      ,  1_4 )


     def   UpperCAmelCase  (							self      :		Tuple )							->     str:
      self.assertEqual(self.get_tokenizer().vocab_size      ,  1_4 )


     def   UpperCAmelCase  (							self      :		List[str] )							->     Dict:
      __lowerCAmelCase:       List[Any]            =				SpeechaTextaTokenizer.from_pretrained(self.tmpdirname )

      # make sure @@ is correctly concatenated
      __lowerCAmelCase:       Optional[int]            =				[4, 6, 8, 7, 1_0]  # ["here@@", "couple", "words", "of@@", "the"]
      __lowerCAmelCase:       Optional[Any]            =				tokenizer.decode(UpperCAmelCase )

      self.assertTrue(output_string == 'herecouple words ofthe' )


     def   UpperCAmelCase  (							self      :		List[str] )							->     List[str]:
      __lowerCAmelCase:       Dict            =				SpeechaTextaTokenizer.from_pretrained(self.tmpdirname )

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

       # load tokenizer without merges file should not throw an error
       __lowerCAmelCase:       int            =				SpeechaTextaTokenizer.from_pretrained(UpperCAmelCase )

      with tempfile.TemporaryDirectory() as tmp_dirname:
       # save tokenizer and load again
       tokenizer.save_pretrained(UpperCAmelCase )
       __lowerCAmelCase:       Dict            =				SpeechaTextaTokenizer.from_pretrained(UpperCAmelCase )

      self.assertIsNotNone(UpperCAmelCase )


     def   UpperCAmelCase  (							self      :		Dict )							->     Any:
      if not self.test_slow_tokenizer:
       return

      __lowerCAmelCase:       List[str]            =				inspect.signature(self.tokenizer_class.__init__ )
      __lowerCAmelCase:       List[Any]            =				self.get_tokenizer()

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








import torch

from transformers import PreTrainedModel

from .custom_configuration import CustomConfig, NoSuperInitConfig






class 							A_			(		snake_case__ ):
     _lowercase      :					Any       =     CustomConfig


     def __init__(							self      :		List[Any]      ,  UpperCAmelCase      :		Optional[Any] )							->     int:
      super().__init__(UpperCAmelCase )
      __lowerCAmelCase:       Tuple            =				torch.nn.Linear(config.hidden_size      ,  config.hidden_size )


     def   UpperCAmelCase  (							self      :		Optional[int]      ,  UpperCAmelCase      :		Tuple )							->     Union[str, Any]:
      return self.linear(UpperCAmelCase )


     def   UpperCAmelCase  (							self      :		str      ,  UpperCAmelCase      :		str )							->     Optional[int]:
      pass







class 							A_			(		snake_case__ ):
     _lowercase      :					str       =     NoSuperInitConfig


     def __init__(							self      :		List[Any]      ,  UpperCAmelCase      :		Union[str, Any] )							->     int:
      super().__init__(UpperCAmelCase )
      __lowerCAmelCase:       int            =				torch.nn.Linear(config.attribute      ,  config.attribute )


     def   UpperCAmelCase  (							self      :		Tuple      ,  UpperCAmelCase      :		Tuple )							->     Tuple:
      return self.linear(UpperCAmelCase )


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





