'''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       _a    (		unittest.TestCase      ):


  """simple docstring"""

  def 		lowerCamelCase__  (		self      :       Dict      ):







    '''simple docstring'''


    lowercase_     =       """ylacombe/bark-small"""
    lowercase_     =       tempfile.mkdtemp()
    lowercase_     =       """en_speaker_1"""
    lowercase_     =       """This is a test string"""
    lowercase_     =       """speaker_embeddings_path.json"""
    lowercase_     =       """speaker_embeddings"""




  def 		lowerCamelCase__  (		self      :       Any   ,				**lowercase_      :       Optional[int]      ):







    '''simple docstring'''


    return AutoTokenizer.from_pretrained(self.checkpoint   ,				**lowercase_      )




  def 		lowerCamelCase__  (		self      :       int      ):







    '''simple docstring'''


    shutil.rmtree(self.tmpdirname      )




  def 		lowerCamelCase__  (		self      :       Tuple      ):







    '''simple docstring'''


    lowercase_     =       self.get_tokenizer()

    lowercase_     =       BarkProcessor(tokenizer=lowercase_      )

    processor.save_pretrained(self.tmpdirname      )
    lowercase_     =       BarkProcessor.from_pretrained(self.tmpdirname      )

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




  @slow
  def 		lowerCamelCase__  (		self      :       Any      ):







    '''simple docstring'''


    lowercase_     =       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_     =       self.get_tokenizer(bos_token="""(BOS)"""   ,				eos_token="""(EOS)"""      )

    lowercase_     =       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 		lowerCamelCase__  (		self      :       Dict      ):







    '''simple docstring'''


    lowercase_     =       BarkProcessor.from_pretrained(
        pretrained_processor_name_or_path=self.checkpoint   ,				speaker_embeddings_dict_path=self.speaker_embeddings_dict_path   ,				)

    lowercase_     =       35
    lowercase_     =       2
    lowercase_     =       8

    lowercase_     =       {
        """semantic_prompt""": np.ones(lowercase_      ),
        """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_     =       processor(text=self.input_string   ,				voice_preset=lowercase_      )

    lowercase_     =       inputs["""history_prompt"""]
    for key in voice_preset:
      self.assertListEqual(voice_preset[key].tolist()   ,				processed_voice_preset.get(lowercase_   ,				np.array([]      )      ).tolist()      )

    # test loading voice preset from npz file
    lowercase_     =       os.path.join(self.tmpdirname   ,				"""file.npz"""      )
    np.savez(lowercase_   ,				**lowercase_      )
    lowercase_     =       processor(text=self.input_string   ,				voice_preset=lowercase_      )
    lowercase_     =       inputs["""history_prompt"""]

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

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





  def 		lowerCamelCase__  (		self      :       Dict      ):







    '''simple docstring'''


    lowercase_     =       self.get_tokenizer()

    lowercase_     =       BarkProcessor(tokenizer=lowercase_      )

    lowercase_     =       processor(text=self.input_string      )

    lowercase_     =       tokenizer(
        self.input_string   ,				padding="""max_length"""   ,				max_length=256   ,				add_special_tokens=lowercase_   ,				return_attention_mask=lowercase_   ,				return_token_type_ids=lowercase_   ,				)

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


'''simple docstring'''


def   A_      (       SCREAMING_SNAKE_CASE_						)			->bool:
  if number < 0:
    raise ValueError("""number must not be negative"""						)
  return number & (number - 1) == 0


if __name__ == "__main__":
       import doctest

       doctest.testmod()

