



"""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 						snake_case_ (					self					:     Any						):
           _UpperCAmelCase      :     str        =   "ylacombe/bark-small"
           _UpperCAmelCase      :     Optional[int]        =   tempfile.mkdtemp()
           _UpperCAmelCase      :     Union[str, Any]        =   "en_speaker_1"
           _UpperCAmelCase      :     str        =   "This is a test string"
           _UpperCAmelCase      :     Tuple        =   "speaker_embeddings_path.json"
           _UpperCAmelCase      :     Dict        =   "speaker_embeddings"



      def 						snake_case_ (					self					:     Any					,     **A					:     List[str]						):
           return AutoTokenizer.from_pretrained(self.checkpoint					,     **A						)



      def 						snake_case_ (					self					:     List[Any]						):
           shutil.rmtree(self.tmpdirname						)



      def 						snake_case_ (					self					:     Tuple						):
           _UpperCAmelCase      :     Tuple        =   self.get_tokenizer()

           _UpperCAmelCase      :     Union[str, Any]        =   BarkProcessor(tokenizer=A						)

           processor.save_pretrained(self.tmpdirname						)
           _UpperCAmelCase      :     Optional[Any]        =   BarkProcessor.from_pretrained(self.tmpdirname						)

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



      @slow
      def 						snake_case_ (					self					:     Dict						):
           _UpperCAmelCase      :     Dict        =   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					,     )

           _UpperCAmelCase      :     Any        =   self.get_tokenizer(bos_token="(BOS)"					,     eos_token="(EOS)"						)

           _UpperCAmelCase      :     Union[str, Any]        =   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 						snake_case_ (					self					:     int						):
           _UpperCAmelCase      :     Any        =   BarkProcessor.from_pretrained(
               pretrained_processor_name_or_path=self.checkpoint					,     speaker_embeddings_dict_path=self.speaker_embeddings_dict_path					,     )

           _UpperCAmelCase      :     List[str]        =   3_5
           _UpperCAmelCase      :     Dict        =   2
           _UpperCAmelCase      :     Dict        =   8

           _UpperCAmelCase      :     Any        =   {
               "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
           _UpperCAmelCase      :     Optional[Any]        =   processor(text=self.input_string					,     voice_preset=A						)

           _UpperCAmelCase      :     Optional[int]        =   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
           _UpperCAmelCase      :     List[Any]        =   os.path.join(self.tmpdirname					,     "file.npz"						)
           np.savez(A					,     **A						)
           _UpperCAmelCase      :     Any        =   processor(text=self.input_string					,     voice_preset=A						)
           _UpperCAmelCase      :     str        =   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
           _UpperCAmelCase      :     Optional[int]        =   processor(text=self.input_string					,     voice_preset=self.voice_preset						)



      def 						snake_case_ (					self					:     List[Any]						):
           _UpperCAmelCase      :     int        =   self.get_tokenizer()

           _UpperCAmelCase      :     Optional[Any]        =   BarkProcessor(tokenizer=A						)

           _UpperCAmelCase      :     Tuple        =   processor(text=self.input_string						)

           _UpperCAmelCase      :     int        =   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"""




from collections.abc import Callable






class      UpperCAmelCase_  :



      def __init__(					self					:     Dict					,     A					:     Callable | None = None						):
           # Stores actual heap items.
           _UpperCAmelCase      :     list        =   []
           # Stores indexes of each item for supporting updates and deletion.
           _UpperCAmelCase      :     dict        =   {}
           # Stores current size of heap.
           _UpperCAmelCase      :     Tuple        =   0
           # Stores function used to evaluate the score of an item on which basis ordering
           # will be done.
           _UpperCAmelCase      :     Any        =   key or (lambda A						: x)



      def 						snake_case_ (					self					:     List[Any]					,     A					:     int						):
           return int((i - 1) / 2						) if i > 0 else None



      def 						snake_case_ (					self					:     List[Any]					,     A					:     int						):
           _UpperCAmelCase      :     Tuple        =   int(2 * i + 1						)
           return left if 0 < left < self.size else None



      def 						snake_case_ (					self					:     List[Any]					,     A					:     int						):
           _UpperCAmelCase      :     Tuple        =   int(2 * i + 2						)
           return right if 0 < right < self.size else None



      def 						snake_case_ (					self					:     Optional[int]					,     A					:     int					,     A					:     int						):
           _UpperCAmelCase    ,	_UpperCAmelCase      :     int        =   (
               self.pos_map[self.arr[j][0]],
               self.pos_map[self.arr[i][0]],
           )
           # Then swap the items in the list.
           _UpperCAmelCase    ,	_UpperCAmelCase      :     Any        =   self.arr[j], self.arr[i]



      def 						snake_case_ (					self					:     List[str]					,     A					:     int					,     A					:     int						):
           return self.arr[i][1] < self.arr[j][1]



      def 						snake_case_ (					self					:     Dict					,     A					:     int						):
           _UpperCAmelCase      :     str        =   self._left(A						)
           _UpperCAmelCase      :     str        =   self._right(A						)
           _UpperCAmelCase      :     List[Any]        =   i

           if left is not None and not self._cmp(A					,     A						):
                _UpperCAmelCase      :     Optional[int]        =   left
           if right is not None and not self._cmp(A					,     A						):
                _UpperCAmelCase      :     Any        =   right

           return valid_parent



      def 						snake_case_ (					self					:     Tuple					,     A					:     int						):
           _UpperCAmelCase      :     Tuple        =   self._parent(A						)
           while parent is not None and not self._cmp(A					,     A						):
                self._swap(A					,     A						)
                _UpperCAmelCase    ,	_UpperCAmelCase      :     Dict        =   parent, self._parent(A						)



      def 						snake_case_ (					self					:     Optional[int]					,     A					:     int						):
           _UpperCAmelCase      :     Tuple        =   self._get_valid_parent(A						)
           while valid_parent != index:
                self._swap(A					,     A						)
                _UpperCAmelCase    ,	_UpperCAmelCase      :     Optional[Any]        =   valid_parent, self._get_valid_parent(A						)



      def 						snake_case_ (					self					:     Dict					,     A					:     int					,     A					:     int						):
           if item not in self.pos_map:
                return
           _UpperCAmelCase      :     Any        =   self.pos_map[item]
           _UpperCAmelCase      :     Optional[int]        =   [item, self.key(A						)]
           # Make sure heap is right in both up and down direction.
           # Ideally only one of them will make any change.
           self._heapify_up(A						)
           self._heapify_down(A						)



      def 						snake_case_ (					self					:     List[str]					,     A					:     int						):
           if item not in self.pos_map:
                return
           _UpperCAmelCase      :     str        =   self.pos_map[item]
           del self.pos_map[item]
           _UpperCAmelCase      :     Tuple        =   self.arr[self.size - 1]
           _UpperCAmelCase      :     List[Any]        =   index
           self.size -= 1
           # Make sure heap is right in both up and down direction. Ideally only one
           # of them will make any change- so no performance loss in calling both.
           if self.size > index:
                self._heapify_up(A						)
                self._heapify_down(A						)



      def 						snake_case_ (					self					:     Any					,     A					:     int					,     A					:     int						):
           _UpperCAmelCase      :     Any        =   len(self.arr						)
           if arr_len == self.size:
                self.arr.append([item, self.key(A						)]						)
           else:
                _UpperCAmelCase      :     Any        =   [item, self.key(A						)]
           _UpperCAmelCase      :     List[Any]        =   self.size
           self.size += 1
           self._heapify_up(self.size - 1						)



      def 						snake_case_ (					self					:     Tuple						):
           return self.arr[0] if self.size else None



      def 						snake_case_ (					self					:     Any						):
           _UpperCAmelCase      :     Dict        =   self.get_top()
           if top_item_tuple:
                self.delete_item(top_item_tuple[0]						)
           return top_item_tuple







def 						__snake_case						(				)  ->       None:





     '''simple docstring'''



if __name__ == "__main__":
 import doctest

 doctest.testmod()
