



'''simple docstring'''







import random
import shutil
import tempfile
import unittest

import numpy as np

from transformers import TaTokenizer, TaTokenizerFast
from transformers.testing_utils import require_sentencepiece, require_torch
from transformers.utils.import_utils import is_speech_available, is_torch_available


if is_torch_available():
							pass

if is_speech_available():
							from transformers import EncodecFeatureExtractor, MusicgenProcessor


SCREAMING_SNAKE_CASE__     : str				=   random.Random()







def  SCREAMING_SNAKE_CASE__ (				SCREAMING_SNAKE_CASE ,		SCREAMING_SNAKE_CASE=1.0 ,		SCREAMING_SNAKE_CASE=None ,		SCREAMING_SNAKE_CASE=None     ):
		if rng is None:
				SCREAMING_SNAKE_CASE_						:List[str]										=      global_rng

		SCREAMING_SNAKE_CASE_						:Optional[int]										=      []
		for batch_idx in range(shape[0]     ):
				values.append([]     )
				for _ in range(shape[1]     ):
						values[-1].append(rng.random() * scale     )

		return values





@require_torch
@require_sentencepiece
class 				__lowerCAmelCase(							unittest.TestCase      ):






			def 				_lowercase	(   self  :							Dict	):




					"""simple docstring"""







					SCREAMING_SNAKE_CASE_						:List[Any]										=      'facebook/musicgen-small'
					SCREAMING_SNAKE_CASE_						:int										=      tempfile.mkdtemp()






			def 				_lowercase	(   self  :							Dict      ,       **SCREAMING_SNAKE_CASE  :							str	):




					"""simple docstring"""







					return TaTokenizer.from_pretrained(self.checkpoint      ,       **SCREAMING_SNAKE_CASE__	)






			def 				_lowercase	(   self  :							Optional[int]      ,       **SCREAMING_SNAKE_CASE  :							Tuple	):




					"""simple docstring"""







					return EncodecFeatureExtractor.from_pretrained(self.checkpoint      ,       **SCREAMING_SNAKE_CASE__	)






			def 				_lowercase	(   self  :							Any	):




					"""simple docstring"""







					shutil.rmtree(self.tmpdirname	)






			def 				_lowercase	(   self  :							str	):




					"""simple docstring"""







					SCREAMING_SNAKE_CASE_						:Any										=      self.get_tokenizer()
					SCREAMING_SNAKE_CASE_						:Dict										=      self.get_feature_extractor()

					SCREAMING_SNAKE_CASE_						:int										=      MusicgenProcessor(tokenizer=SCREAMING_SNAKE_CASE__      ,       feature_extractor=SCREAMING_SNAKE_CASE__	)

					processor.save_pretrained(self.tmpdirname	)
					SCREAMING_SNAKE_CASE_						:Optional[Any]										=      MusicgenProcessor.from_pretrained(self.tmpdirname	)

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

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






			def 				_lowercase	(   self  :							Any	):




					"""simple docstring"""







					SCREAMING_SNAKE_CASE_						:Tuple										=      MusicgenProcessor(tokenizer=self.get_tokenizer()      ,       feature_extractor=self.get_feature_extractor()	)
					processor.save_pretrained(self.tmpdirname	)

					SCREAMING_SNAKE_CASE_						:int										=      self.get_tokenizer(bos_token='(BOS)'      ,       eos_token='(EOS)'	)
					SCREAMING_SNAKE_CASE_						:int										=      self.get_feature_extractor(do_normalize=SCREAMING_SNAKE_CASE__      ,       padding_value=1.0	)

					SCREAMING_SNAKE_CASE_						:int										=      MusicgenProcessor.from_pretrained(
					    self.tmpdirname      ,       bos_token='(BOS)'      ,       eos_token='(EOS)'      ,       do_normalize=SCREAMING_SNAKE_CASE__      ,       padding_value=1.0	)

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

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






			def 				_lowercase	(   self  :							Union[str, Any]	):




					"""simple docstring"""







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

					SCREAMING_SNAKE_CASE_						:Union[str, Any]										=      MusicgenProcessor(tokenizer=SCREAMING_SNAKE_CASE__      ,       feature_extractor=SCREAMING_SNAKE_CASE__	)

					SCREAMING_SNAKE_CASE_						:str										=      floats_list((3, 1_000)	)

					SCREAMING_SNAKE_CASE_						:Tuple										=      feature_extractor(SCREAMING_SNAKE_CASE__      ,       return_tensors='np'	)
					SCREAMING_SNAKE_CASE_						:int										=      processor(SCREAMING_SNAKE_CASE__      ,       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 				_lowercase	(   self  :							Dict	):




					"""simple docstring"""







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

					SCREAMING_SNAKE_CASE_						:Tuple										=      MusicgenProcessor(tokenizer=SCREAMING_SNAKE_CASE__      ,       feature_extractor=SCREAMING_SNAKE_CASE__	)

					SCREAMING_SNAKE_CASE_						:str										=      'This is a test string'

					SCREAMING_SNAKE_CASE_						:Any										=      processor(text=SCREAMING_SNAKE_CASE__	)

					SCREAMING_SNAKE_CASE_						:List[str]										=      tokenizer(SCREAMING_SNAKE_CASE__	)

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






			def 				_lowercase	(   self  :							Union[str, Any]	):




					"""simple docstring"""







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

					SCREAMING_SNAKE_CASE_						:Optional[Any]										=      MusicgenProcessor(tokenizer=SCREAMING_SNAKE_CASE__      ,       feature_extractor=SCREAMING_SNAKE_CASE__	)

					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(sequences=SCREAMING_SNAKE_CASE__	)
					SCREAMING_SNAKE_CASE_						:str										=      tokenizer.batch_decode(SCREAMING_SNAKE_CASE__	)

					self.assertListEqual(SCREAMING_SNAKE_CASE__      ,       SCREAMING_SNAKE_CASE__	)






			def 				_lowercase	(   self  :							Tuple	):




					"""simple docstring"""







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

					SCREAMING_SNAKE_CASE_						:Any										=      MusicgenProcessor(tokenizer=SCREAMING_SNAKE_CASE__      ,       feature_extractor=SCREAMING_SNAKE_CASE__	)

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






			def 				_lowercase	(   self  :							Any	):




					"""simple docstring"""







					SCREAMING_SNAKE_CASE_						:List[Any]										=      self.get_feature_extractor(padding_side='left'	)
					SCREAMING_SNAKE_CASE_						:Optional[int]										=      self.get_tokenizer()

					SCREAMING_SNAKE_CASE_						:Any										=      MusicgenProcessor(tokenizer=SCREAMING_SNAKE_CASE__      ,       feature_extractor=SCREAMING_SNAKE_CASE__	)

					SCREAMING_SNAKE_CASE_						:Union[str, Any]										=      [floats_list((1, x)	)[0] for x in range(5      ,       20      ,       5	)]
					SCREAMING_SNAKE_CASE_						:Tuple										=      processor(SCREAMING_SNAKE_CASE__	).padding_mask

					SCREAMING_SNAKE_CASE_						:List[str]										=      np.asarray(floats_list((3, 20)	)	)[:, None, :]
					SCREAMING_SNAKE_CASE_						:int										=      processor.batch_decode(SCREAMING_SNAKE_CASE__      ,       padding_mask=SCREAMING_SNAKE_CASE__	)

					self.assertIsInstance(SCREAMING_SNAKE_CASE__      ,       SCREAMING_SNAKE_CASE__	)

					for audio in decoded_audios:
							self.assertIsInstance(SCREAMING_SNAKE_CASE__      ,       np.ndarray	)

					self.assertTrue(decoded_audios[0].shape == (1, 10)	)
					self.assertTrue(decoded_audios[1].shape == (1, 15)	)
					self.assertTrue(decoded_audios[2].shape == (1, 20)	)



"""simple docstring"""




from __future__ import annotations



def 						UpperCAmelCase__ (					A__						,     A__						,     A__						,     A__ )   ->   None:




   """simple docstring"""
   lowerCamelCase__       ,							lowerCamelCase__						       =      m - 1, 0
   while i >= 0 and j < n:
      if key == mat[i][j]:
         print(f'Key {key} found at row- {i + 1} column- {j + 1}' )
         return
      if key < mat[i][j]:
         i -= 1
      else:
         j += 1
   print(f'Key {key} not found' )



def 						UpperCAmelCase__ (					)   ->   None:




   """simple docstring"""
   lowerCamelCase__						       =      [[2, 5, 7], [4, 8, 13], [9, 11, 15], [12, 17, 20]]
   lowerCamelCase__						       =      int(input("Enter the element to be searched:" ) )
   print(A__ )
   search_in_a_sorted_matrix(A__						,     len(A__ )						,     len(mat[0] )						,     A__ )


if __name__ == "__main__":
     import doctest

     doctest.testmod()
     main()




