


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 	_snake_case						(   _snake_case		,					unittest.TestCase							):
	SCREAMING_SNAKE_CASE__   = SpeechaTextaTokenizer
	SCREAMING_SNAKE_CASE__   = False




	def  SCREAMING_SNAKE_CASE__       (	self					):
							super().setUp()

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

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

							a		:int											= tempfile.mkdtemp()
							a		:List[str]											= os.path.join(self.tmpdirname      ,						VOCAB_FILES_NAMES['''vocab_file''']					)
							a		:Dict											= 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  SCREAMING_SNAKE_CASE__       (	self					):
							a		:Tuple											= 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  SCREAMING_SNAKE_CASE__       (	self					):
							self.assertEqual(self.get_tokenizer().vocab_size      ,						14					)




	def  SCREAMING_SNAKE_CASE__       (	self					):
							a		:Optional[Any]											= SpeechaTextaTokenizer.from_pretrained(self.tmpdirname					)

							# make sure @@ is correctly concatenated
							a		:Any											= [4, 6, 8, 7, 10]  # ["here@@", "couple", "words", "of@@", "the"]
							a		:Optional[int]											= tokenizer.decode(_lowerCamelCase					)

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




	def  SCREAMING_SNAKE_CASE__       (	self					):
							a		:str											= 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
													a		:Tuple											= SpeechaTextaTokenizer.from_pretrained(_lowerCamelCase					)

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

							self.assertIsNotNone(_lowerCamelCase					)




	def  SCREAMING_SNAKE_CASE__       (	self					):
							if not self.test_slow_tokenizer:
													return

							a		:Union[str, Any]											= inspect.signature(self.tokenizer_class.__init__					)
							a		:List[str]											= 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 TYPE_CHECKING

from ...utils import (
    OptionalDependencyNotAvailable,
    _LazyModule,
    is_torch_available,
)


snake_case       :					Dict        =  {
    '''configuration_align''': [
        '''ALIGN_PRETRAINED_CONFIG_ARCHIVE_MAP''',
        '''AlignConfig''',
        '''AlignTextConfig''',
        '''AlignVisionConfig''',
    ],
    '''processing_align''': ['''AlignProcessor'''],
}

try:
     if not is_torch_available():
          raise OptionalDependencyNotAvailable()
except OptionalDependencyNotAvailable:
     pass
else:
     snake_case       :					List[str]        =  [
         '''ALIGN_PRETRAINED_MODEL_ARCHIVE_LIST''',
         '''AlignModel''',
         '''AlignPreTrainedModel''',
         '''AlignTextModel''',
         '''AlignVisionModel''',
     ]

if TYPE_CHECKING:
     from .configuration_align import (
         ALIGN_PRETRAINED_CONFIG_ARCHIVE_MAP,
         AlignConfig,
         AlignTextConfig,
         AlignVisionConfig,
     )
     from .processing_align import AlignProcessor

     try:
          if not is_torch_available():
               raise OptionalDependencyNotAvailable()
     except OptionalDependencyNotAvailable:
          pass
     else:
          from .modeling_align import (
              ALIGN_PRETRAINED_MODEL_ARCHIVE_LIST,
              AlignModel,
              AlignPreTrainedModel,
              AlignTextModel,
              AlignVisionModel,
          )

else:
     import sys

     snake_case       :					int        =  _LazyModule(__name__, globals()['''__file__'''], _import_structure, module_spec=__spec__)





