






"""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 ):






      '''simple docstring'''

      def _SCREAMING_SNAKE_CASE (						self     :  Optional[Any]):




          '''simple docstring'''


          SCREAMING_SNAKE_CASE_      :  int    						=		"""laion/clap-htsat-unfused"""
          SCREAMING_SNAKE_CASE_      :  int    						=		tempfile.mkdtemp()
      def _SCREAMING_SNAKE_CASE (						self     :  Dict						,	**lowercase_     :  int):




          '''simple docstring'''


          return RobertaTokenizer.from_pretrained(self.checkpoint						,	**__a)
      def _SCREAMING_SNAKE_CASE (						self     :  List[Any]						,	**lowercase_     :  Optional[int]):




          '''simple docstring'''


          return ClapFeatureExtractor.from_pretrained(self.checkpoint						,	**__a)
      def _SCREAMING_SNAKE_CASE (						self     :  Tuple):




          '''simple docstring'''


          shutil.rmtree(self.tmpdirname)
      def _SCREAMING_SNAKE_CASE (						self     :  Optional[int]):




          '''simple docstring'''


          SCREAMING_SNAKE_CASE_      :  Optional[Any]    						=		self.get_tokenizer()
          SCREAMING_SNAKE_CASE_      :  str    						=		self.get_feature_extractor()

          SCREAMING_SNAKE_CASE_      :  List[Any]    						=		ClapProcessor(tokenizer=__a						,	feature_extractor=__a)

          processor.save_pretrained(self.tmpdirname)
          SCREAMING_SNAKE_CASE_      :  Union[str, Any]    						=		ClapProcessor.from_pretrained(self.tmpdirname)

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

          self.assertEqual(processor.feature_extractor.to_json_string()						,	feature_extractor.to_json_string())
          self.assertIsInstance(processor.feature_extractor						,	__a)
      def _SCREAMING_SNAKE_CASE (						self     :  Union[str, Any]):




          '''simple docstring'''


          SCREAMING_SNAKE_CASE_      :  Optional[Any]    						=		ClapProcessor(tokenizer=self.get_tokenizer()						,	feature_extractor=self.get_feature_extractor())
          processor.save_pretrained(self.tmpdirname)

          SCREAMING_SNAKE_CASE_      :  str    						=		self.get_tokenizer(bos_token='''(BOS)'''						,	eos_token='''(EOS)''')
          SCREAMING_SNAKE_CASE_      :  List[Any]    						=		self.get_feature_extractor(do_normalize=__a						,	padding_value=1.0)

          SCREAMING_SNAKE_CASE_      :  List[str]    						=		ClapProcessor.from_pretrained(
              self.tmpdirname						,	bos_token='''(BOS)'''						,	eos_token='''(EOS)'''						,	do_normalize=__a						,	padding_value=1.0)

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

          self.assertEqual(processor.feature_extractor.to_json_string()						,	feature_extractor_add_kwargs.to_json_string())
          self.assertIsInstance(processor.feature_extractor						,	__a)
      def _SCREAMING_SNAKE_CASE (						self     :  Any):




          '''simple docstring'''


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

          SCREAMING_SNAKE_CASE_      :  Union[str, Any]    						=		ClapProcessor(tokenizer=__a						,	feature_extractor=__a)

          SCREAMING_SNAKE_CASE_      :  Optional[Any]    						=		floats_list((3, 1000))

          SCREAMING_SNAKE_CASE_      :  Any    						=		feature_extractor(__a						,	return_tensors='''np''')
          SCREAMING_SNAKE_CASE_      :  List[Any]    						=		processor(audios=__a						,	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 _SCREAMING_SNAKE_CASE (						self     :  Union[str, Any]):




          '''simple docstring'''


          SCREAMING_SNAKE_CASE_      :  str    						=		self.get_feature_extractor()
          SCREAMING_SNAKE_CASE_      :  Tuple    						=		self.get_tokenizer()

          SCREAMING_SNAKE_CASE_      :  Union[str, Any]    						=		ClapProcessor(tokenizer=__a						,	feature_extractor=__a)

          SCREAMING_SNAKE_CASE_      :  Dict    						=		"""This is a test string"""

          SCREAMING_SNAKE_CASE_      :  Union[str, Any]    						=		processor(text=__a)

          SCREAMING_SNAKE_CASE_      :  List[Any]    						=		tokenizer(__a)

          for key in encoded_tok.keys():
              self.assertListEqual(encoded_tok[key]						,	encoded_processor[key])
      def _SCREAMING_SNAKE_CASE (						self     :  Optional[Any]):




          '''simple docstring'''


          SCREAMING_SNAKE_CASE_      :  Tuple    						=		self.get_feature_extractor()
          SCREAMING_SNAKE_CASE_      :  Tuple    						=		self.get_tokenizer()

          SCREAMING_SNAKE_CASE_      :  Union[str, Any]    						=		ClapProcessor(tokenizer=__a						,	feature_extractor=__a)

          SCREAMING_SNAKE_CASE_      :  Union[str, Any]    						=		[[1, 4, 5, 8, 1, 0, 8], [3, 4, 3, 1, 1, 8, 9]]

          SCREAMING_SNAKE_CASE_      :  Optional[Any]    						=		processor.batch_decode(__a)
          SCREAMING_SNAKE_CASE_      :  str    						=		tokenizer.batch_decode(__a)

          self.assertListEqual(__a						,	__a)



      def _SCREAMING_SNAKE_CASE (						self     :  Optional[int]):




          '''simple docstring'''


          SCREAMING_SNAKE_CASE_      :  List[str]    						=		self.get_feature_extractor()
          SCREAMING_SNAKE_CASE_      :  Optional[int]    						=		self.get_tokenizer()

          SCREAMING_SNAKE_CASE_      :  Tuple    						=		ClapProcessor(tokenizer=__a						,	feature_extractor=__a)

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










from __future__ import annotations
def 					snake_case_						(   lowerCAmelCase_				:  int				,				lowerCAmelCase_				:  int					):
							if partitions <= 0:
														raise ValueError("""partitions must be a positive number!"""					)
							if partitions > number_of_bytes:
														raise ValueError("""partitions can not > number_of_bytes!"""					)
							__lowercase					:							Dict			=   number_of_bytes // partitions
							__lowercase					:							Union[str, Any]			=   []
							for i in range(lowerCAmelCase_					):
														__lowercase					:							str			=   i * bytes_per_partition + 1
														__lowercase					:							List[Any]			=   (
														    number_of_bytes if i == partitions - 1 else (i + 1) * bytes_per_partition
														)
														allocation_list.append(F"{start_bytes}-{end_bytes}"					)
							return allocation_list


if __name__ == "__main__":
	import doctest

	doctest.testmod()