





'''simple docstring'''

import shutil
import tempfile
import unittest

from transformers import ClapFeatureExtractor, ClapProcessor, RobertaTokenizer, RobertaTokenizerFast
from transformers.testing_utils import require_sentencepiece, require_torchaudio

from .test_feature_extraction_clap import floats_list





@require_torchaudio
@require_sentencepiece
class lowerCamelCase						(unittest.TestCase					):







  def 				UpperCAmelCase_				(		self		)		->						List[Any]:






   """simple docstring"""





   _snake_case		:	Optional[int]					     =     "laion/clap-htsat-unfused"
   _snake_case		:	List[str]					     =     tempfile.mkdtemp()







  def 				UpperCAmelCase_				(		self     ,     **lowercase__		)		->						int:






   """simple docstring"""





   return RobertaTokenizer.from_pretrained(self.checkpoint     ,     **lowercase__		)







  def 				UpperCAmelCase_				(		self     ,     **lowercase__		)		->						Optional[Any]:






   """simple docstring"""





   return ClapFeatureExtractor.from_pretrained(self.checkpoint     ,     **lowercase__		)







  def 				UpperCAmelCase_				(		self		)		->						Optional[Any]:






   """simple docstring"""





   shutil.rmtree(self.tmpdirname		)







  def 				UpperCAmelCase_				(		self		)		->						int:






   """simple docstring"""





   _snake_case		:	Optional[int]					     =     self.get_tokenizer()
   _snake_case		:	Tuple					     =     self.get_feature_extractor()

   _snake_case		:	Optional[Any]					     =     ClapProcessor(tokenizer=lowercase__     ,     feature_extractor=lowercase__		)

   processor.save_pretrained(self.tmpdirname		)
   _snake_case		:	Any					     =     ClapProcessor.from_pretrained(self.tmpdirname		)

   self.assertEqual(processor.tokenizer.get_vocab()     ,     tokenizer.get_vocab()		)
   self.assertIsInstance(processor.tokenizer     ,     lowercase__		)

   self.assertEqual(processor.feature_extractor.to_json_string()     ,     feature_extractor.to_json_string()		)
   self.assertIsInstance(processor.feature_extractor     ,     lowercase__		)







  def 				UpperCAmelCase_				(		self		)		->						Optional[int]:






   """simple docstring"""





   _snake_case		:	List[str]					     =     ClapProcessor(tokenizer=self.get_tokenizer()     ,     feature_extractor=self.get_feature_extractor()		)
   processor.save_pretrained(self.tmpdirname		)

   _snake_case		:	Union[str, Any]					     =     self.get_tokenizer(bos_token='''(BOS)'''     ,     eos_token='''(EOS)'''		)
   _snake_case		:	int					     =     self.get_feature_extractor(do_normalize=lowercase__     ,     padding_value=1.0		)

   _snake_case		:	Optional[Any]					     =     ClapProcessor.from_pretrained(
       self.tmpdirname     ,     bos_token='''(BOS)'''     ,     eos_token='''(EOS)'''     ,     do_normalize=lowercase__     ,     padding_value=1.0		)

   self.assertEqual(processor.tokenizer.get_vocab()     ,     tokenizer_add_kwargs.get_vocab()		)
   self.assertIsInstance(processor.tokenizer     ,     lowercase__		)

   self.assertEqual(processor.feature_extractor.to_json_string()     ,     feature_extractor_add_kwargs.to_json_string()		)
   self.assertIsInstance(processor.feature_extractor     ,     lowercase__		)







  def 				UpperCAmelCase_				(		self		)		->						List[Any]:






   """simple docstring"""





   _snake_case		:	int					     =     self.get_feature_extractor()
   _snake_case		:	str					     =     self.get_tokenizer()

   _snake_case		:	Any					     =     ClapProcessor(tokenizer=lowercase__     ,     feature_extractor=lowercase__		)

   _snake_case		:	List[Any]					     =     floats_list((3, 1_000)		)

   _snake_case		:	Dict					     =     feature_extractor(lowercase__     ,     return_tensors='''np'''		)
   _snake_case		:	int					     =     processor(audios=lowercase__     ,     return_tensors='''np'''		)

   for key in input_feat_extract.keys():
    self.assertAlmostEqual(input_feat_extract[key].sum()     ,     input_processor[key].sum()     ,     delta=1E-2		)







  def 				UpperCAmelCase_				(		self		)		->						str:






   """simple docstring"""





   _snake_case		:	int					     =     self.get_feature_extractor()
   _snake_case		:	Optional[Any]					     =     self.get_tokenizer()

   _snake_case		:	Union[str, Any]					     =     ClapProcessor(tokenizer=lowercase__     ,     feature_extractor=lowercase__		)

   _snake_case		:	Any					     =     "This is a test string"

   _snake_case		:	Dict					     =     processor(text=lowercase__		)

   _snake_case		:	str					     =     tokenizer(lowercase__		)

   for key in encoded_tok.keys():
    self.assertListEqual(encoded_tok[key]     ,     encoded_processor[key]		)







  def 				UpperCAmelCase_				(		self		)		->						Union[str, Any]:






   """simple docstring"""





   _snake_case		:	Optional[int]					     =     self.get_feature_extractor()
   _snake_case		:	int					     =     self.get_tokenizer()

   _snake_case		:	List[Any]					     =     ClapProcessor(tokenizer=lowercase__     ,     feature_extractor=lowercase__		)

   _snake_case		:	List[Any]					     =     [[1, 4, 5, 8, 1, 0, 8], [3, 4, 3, 1, 1, 8, 9]]

   _snake_case		:	Union[str, Any]					     =     processor.batch_decode(lowercase__		)
   _snake_case		:	Optional[int]					     =     tokenizer.batch_decode(lowercase__		)

   self.assertListEqual(lowercase__     ,     lowercase__		)







  def 				UpperCAmelCase_				(		self		)		->						List[Any]:






   """simple docstring"""





   _snake_case		:	Dict					     =     self.get_feature_extractor()
   _snake_case		:	List[Any]					     =     self.get_tokenizer()

   _snake_case		:	Optional[Any]					     =     ClapProcessor(tokenizer=lowercase__     ,     feature_extractor=lowercase__		)

   self.assertListEqual(
       processor.model_input_names[2:]     ,     feature_extractor.model_input_names     ,     msg='''`processor` and `feature_extractor` model input names do not match'''     ,     )









'''simple docstring'''

from typing import TYPE_CHECKING

from ...utils import OptionalDependencyNotAvailable, _LazyModule, is_torch_available


UpperCAmelCase					:		int		=							{
    'configuration_pegasus_x': ['PEGASUS_X_PRETRAINED_CONFIG_ARCHIVE_MAP', 'PegasusXConfig'],
}

try:
   if not is_torch_available():
      raise OptionalDependencyNotAvailable()
except OptionalDependencyNotAvailable:
   pass
else:
   UpperCAmelCase					:		Union[str, Any]		=							[
       'PEGASUS_X_PRETRAINED_MODEL_ARCHIVE_LIST',
       'PegasusXForConditionalGeneration',
       'PegasusXModel',
       'PegasusXPreTrainedModel',
   ]


if TYPE_CHECKING:
   from .configuration_pegasus_x import PEGASUS_X_PRETRAINED_CONFIG_ARCHIVE_MAP, PegasusXConfig

   try:
      if not is_torch_available():
         raise OptionalDependencyNotAvailable()
   except OptionalDependencyNotAvailable:
      pass
   else:
      from .modeling_pegasus_x import (
          PEGASUS_X_PRETRAINED_MODEL_ARCHIVE_LIST,
          PegasusXForConditionalGeneration,
          PegasusXModel,
          PegasusXPreTrainedModel,
      )


else:
   import sys

   UpperCAmelCase					:		Dict		=							_LazyModule(__name__, globals()['__file__'], _import_structure, module_spec=__spec__)


