




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__ :   Optional[Any]						=     random.Random()

def   A   (   _SCREAMING_SNAKE_CASE				,_SCREAMING_SNAKE_CASE=1.0				,_SCREAMING_SNAKE_CASE=None				,_SCREAMING_SNAKE_CASE=None					)			->				List[str]:
       if rng is None:
              lowerCamelCase     :   Any    				=      global_rng

       lowerCamelCase     :   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 	UpperCamelCase__			(unittest.TestCase  ):

    '''simple docstring'''



    def 					_lowercase  (					self  )  ->   Union[str, Any]:
           lowerCamelCase     :   str    				=      "facebook/musicgen-small"
           lowerCamelCase     :   str    				=      tempfile.mkdtemp()







    def 					_lowercase  (					self  ,						**UpperCamelCase__  )  ->   int:
           return TaTokenizer.from_pretrained(self.checkpoint  ,						**UpperCamelCase__  )







    def 					_lowercase  (					self  ,						**UpperCamelCase__  )  ->   List[Any]:
           return EncodecFeatureExtractor.from_pretrained(self.checkpoint  ,						**UpperCamelCase__  )







    def 					_lowercase  (					self  )  ->   Any:
           shutil.rmtree(self.tmpdirname  )







    def 					_lowercase  (					self  )  ->   str:
           lowerCamelCase     :   Optional[int]    				=      self.get_tokenizer()
           lowerCamelCase     :   int    				=      self.get_feature_extractor()

           lowerCamelCase     :   List[Any]    				=      MusicgenProcessor(tokenizer=UpperCamelCase__  ,						feature_extractor=UpperCamelCase__  )

           processor.save_pretrained(self.tmpdirname  )
           lowerCamelCase     :   Any    				=      MusicgenProcessor.from_pretrained(self.tmpdirname  )

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

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







    def 					_lowercase  (					self  )  ->   Union[str, Any]:
           lowerCamelCase     :   int    				=      MusicgenProcessor(tokenizer=self.get_tokenizer()  ,						feature_extractor=self.get_feature_extractor()  )
           processor.save_pretrained(self.tmpdirname  )

           lowerCamelCase     :   Any    				=      self.get_tokenizer(bos_token="(BOS)"  ,						eos_token="(EOS)"  )
           lowerCamelCase     :   Tuple    				=      self.get_feature_extractor(do_normalize=UpperCamelCase__  ,						padding_value=1.0  )

           lowerCamelCase     :   int    				=      MusicgenProcessor.from_pretrained(
               self.tmpdirname  ,						bos_token="(BOS)"  ,						eos_token="(EOS)"  ,						do_normalize=UpperCamelCase__  ,						padding_value=1.0  )

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

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







    def 					_lowercase  (					self  )  ->   List[str]:
           lowerCamelCase     :   str    				=      self.get_feature_extractor()
           lowerCamelCase     :   Optional[Any]    				=      self.get_tokenizer()

           lowerCamelCase     :   List[str]    				=      MusicgenProcessor(tokenizer=UpperCamelCase__  ,						feature_extractor=UpperCamelCase__  )

           lowerCamelCase     :   str    				=      floats_list((3, 1000)  )

           lowerCamelCase     :   List[Any]    				=      feature_extractor(UpperCamelCase__  ,						return_tensors="np"  )
           lowerCamelCase     :   Union[str, Any]    				=      processor(UpperCamelCase__  ,						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  )  ->   int:
           lowerCamelCase     :   Any    				=      self.get_feature_extractor()
           lowerCamelCase     :   List[str]    				=      self.get_tokenizer()

           lowerCamelCase     :   int    				=      MusicgenProcessor(tokenizer=UpperCamelCase__  ,						feature_extractor=UpperCamelCase__  )

           lowerCamelCase     :   Optional[int]    				=      "This is a test string"

           lowerCamelCase     :   List[Any]    				=      processor(text=UpperCamelCase__  )

           lowerCamelCase     :   Tuple    				=      tokenizer(UpperCamelCase__  )

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







    def 					_lowercase  (					self  )  ->   Union[str, Any]:
           lowerCamelCase     :   List[str]    				=      self.get_feature_extractor()
           lowerCamelCase     :   Optional[int]    				=      self.get_tokenizer()

           lowerCamelCase     :   Union[str, Any]    				=      MusicgenProcessor(tokenizer=UpperCamelCase__  ,						feature_extractor=UpperCamelCase__  )

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

           lowerCamelCase     :   Tuple    				=      processor.batch_decode(sequences=UpperCamelCase__  )
           lowerCamelCase     :   List[str]    				=      tokenizer.batch_decode(UpperCamelCase__  )

           self.assertListEqual(UpperCamelCase__  ,						UpperCamelCase__  )







    def 					_lowercase  (					self  )  ->   Tuple:
           lowerCamelCase     :   Tuple    				=      self.get_feature_extractor()
           lowerCamelCase     :   List[Any]    				=      self.get_tokenizer()

           lowerCamelCase     :   Tuple    				=      MusicgenProcessor(tokenizer=UpperCamelCase__  ,						feature_extractor=UpperCamelCase__  )

           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  )  ->   Union[str, Any]:
           lowerCamelCase     :   Optional[int]    				=      self.get_feature_extractor(padding_side="left"  )
           lowerCamelCase     :   Optional[Any]    				=      self.get_tokenizer()

           lowerCamelCase     :   Any    				=      MusicgenProcessor(tokenizer=UpperCamelCase__  ,						feature_extractor=UpperCamelCase__  )

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

           lowerCamelCase     :   List[Any]    				=      np.asarray(floats_list((3, 20)  )  )[:, None, :]
           lowerCamelCase     :   str    				=      processor.batch_decode(UpperCamelCase__  ,						padding_mask=UpperCamelCase__  )

           self.assertIsInstance(UpperCamelCase__  ,						UpperCamelCase__  )

           for audio in decoded_audios:
                  self.assertIsInstance(UpperCamelCase__  ,						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)  )












from __future__ import annotations

def   A   (   _SCREAMING_SNAKE_CASE				,_SCREAMING_SNAKE_CASE					)			->				list:
       lowerCamelCase     :   int    				=      [None] * (len(_SCREAMING_SNAKE_CASE					) + len(_SCREAMING_SNAKE_CASE					))

       lowerCamelCase     :   Any    				=      0  # pointer to current index for left Half
       lowerCamelCase     :   int    				=      0  # pointer to current index for the right Half
       lowerCamelCase     :   Optional[int]    				=      0  # pointer to current index for the sorted array Half

       while pointera < len(_SCREAMING_SNAKE_CASE					) and pointera < len(_SCREAMING_SNAKE_CASE					):
              if left_half[pointera] < right_half[pointera]:
                     lowerCamelCase     :   Any    				=      left_half[pointera]
                     pointera += 1
                     index += 1
              else:
                     lowerCamelCase     :   Any    				=      right_half[pointera]
                     pointera += 1
                     index += 1
       while pointera < len(_SCREAMING_SNAKE_CASE					):
              lowerCamelCase     :   Optional[Any]    				=      left_half[pointera]
              pointera += 1
              index += 1

       while pointera < len(_SCREAMING_SNAKE_CASE					):
              lowerCamelCase     :   str    				=      right_half[pointera]
              pointera += 1
              index += 1

       return sorted_array

def   A   (   _SCREAMING_SNAKE_CASE					)			->				list:
       if len(_SCREAMING_SNAKE_CASE					) <= 1:
              return array
       # the actual formula to calculate the middle element = left + (right - left) // 2
       # this avoids integer overflow in case of large N
       lowerCamelCase     :   int    				=      0 + (len(_SCREAMING_SNAKE_CASE					) - 0) // 2

       # Split the array into halves till the array length becomes equal to One
       # merge the arrays of single length returned by mergeSort function and
       # pass them into the merge arrays function which merges the array
       lowerCamelCase     :   Optional[Any]    				=      array[:middle]
       lowerCamelCase     :   Optional[Any]    				=      array[middle:]

       return merge(merge_sort(_SCREAMING_SNAKE_CASE					)				,merge_sort(_SCREAMING_SNAKE_CASE					)					)


if __name__ == "__main__":
       import doctest

       doctest.testmod()






