"""simple docstring"""





import os
import shutil
import tempfile
import unittest

import numpy as np

from transformers import AutoTokenizer, BarkProcessor
from transformers.testing_utils import require_torch, slow


@require_torch
class   UpperCAmelCase_			(					unittest.TestCase):


      def 	_UpperCAmelCase (     self							) ->      List[str]:
             lowercase__    :	Optional[Any]     					=			'ylacombe/bark-small'
             lowercase__    :	Optional[int]     					=			tempfile.mkdtemp()
             lowercase__    :	int     					=			'en_speaker_1'
             lowercase__    :	Union[str, Any]     					=			'This is a test string'
             lowercase__    :	Any     					=			'speaker_embeddings_path.json'
             lowercase__    :	str     					=			'speaker_embeddings'


      def 	_UpperCAmelCase (     self	,    **a							) ->      List[Any]:
             return AutoTokenizer.from_pretrained(self.checkpoint	,    **a							)


      def 	_UpperCAmelCase (     self							) ->      Optional[Any]:
             shutil.rmtree(self.tmpdirname							)


      def 	_UpperCAmelCase (     self							) ->      str:
             lowercase__    :	List[str]     					=			self.get_tokenizer()

             lowercase__    :	Dict     					=			BarkProcessor(tokenizer=a							)

             processor.save_pretrained(self.tmpdirname							)
             lowercase__    :	List[Any]     					=			BarkProcessor.from_pretrained(self.tmpdirname							)

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


      @slow
      def 	_UpperCAmelCase (     self							) ->      Dict:
             lowercase__    :	str     					=			BarkProcessor.from_pretrained(
                 pretrained_processor_name_or_path=self.checkpoint	,    speaker_embeddings_dict_path=self.speaker_embeddings_dict_path	,    )
             processor.save_pretrained(
                 self.tmpdirname	,    speaker_embeddings_dict_path=self.speaker_embeddings_dict_path	,    speaker_embeddings_directory=self.speaker_embeddings_directory	,    )

             lowercase__    :	Dict     					=			self.get_tokenizer(bos_token='(BOS)'	,    eos_token='(EOS)'							)

             lowercase__    :	int     					=			BarkProcessor.from_pretrained(
                 self.tmpdirname	,    self.speaker_embeddings_dict_path	,    bos_token='(BOS)'	,    eos_token='(EOS)'	,    )

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


      def 	_UpperCAmelCase (     self							) ->      Any:
             lowercase__    :	List[Any]     					=			BarkProcessor.from_pretrained(
                 pretrained_processor_name_or_path=self.checkpoint	,    speaker_embeddings_dict_path=self.speaker_embeddings_dict_path	,    )

             lowercase__    :	List[Any]     					=			3_5
             lowercase__    :	Tuple     					=			2
             lowercase__    :	Dict     					=			8

             lowercase__    :	Dict     					=			{
                 'semantic_prompt': np.ones(a							),
                 'coarse_prompt': np.ones((nb_codebooks_coarse, seq_len)							),
                 'fine_prompt': np.ones((nb_codebooks_total, seq_len)							),
             }

             # test providing already loaded voice_preset
             lowercase__    :	int     					=			processor(text=self.input_string	,    voice_preset=a							)

             lowercase__    :	Any     					=			inputs['history_prompt']
             for key in voice_preset:
                    self.assertListEqual(voice_preset[key].tolist()	,    processed_voice_preset.get(a	,    np.array([]							)							).tolist()							)

             # test loading voice preset from npz file
             lowercase__    :	Dict     					=			os.path.join(self.tmpdirname	,    'file.npz'							)
             np.savez(a	,    **a							)
             lowercase__    :	Any     					=			processor(text=self.input_string	,    voice_preset=a							)
             lowercase__    :	Optional[Any]     					=			inputs['history_prompt']

             for key in voice_preset:
                    self.assertListEqual(voice_preset[key].tolist()	,    processed_voice_preset.get(a	,    np.array([]							)							).tolist()							)

             # test loading voice preset from the hub
             lowercase__    :	Tuple     					=			processor(text=self.input_string	,    voice_preset=self.voice_preset							)


      def 	_UpperCAmelCase (     self							) ->      int:
             lowercase__    :	int     					=			self.get_tokenizer()

             lowercase__    :	Union[str, Any]     					=			BarkProcessor(tokenizer=a							)

             lowercase__    :	Any     					=			processor(text=self.input_string							)

             lowercase__    :	Union[str, Any]     					=			tokenizer(
                 self.input_string	,    padding='max_length'	,    max_length=2_5_6	,    add_special_tokens=a	,    return_attention_mask=a	,    return_token_type_ids=a	,    )

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


"""simple docstring"""





import math





def        a_  (   _lowerCAmelCase						:				int = 100  ):





       '''simple docstring'''

       lowercase__    :	Union[str, Any]     					=			sum(i * i for i in range(1     ,				n + 1  )  )
       lowercase__    :	str     					=			int(math.pow(sum(range(1     ,				n + 1  )  )     ,				2  )  )
       return square_of_sum - sum_of_squares


if __name__ == "__main__":
       print(f'''{solution() = }''')

