
import json
import os
from typing import Optional

import numpy as np

from ...feature_extraction_utils import BatchFeature
from ...processing_utils import ProcessorMixin
from ...utils import logging
from ...utils.hub import get_file_from_repo
from ..auto import AutoTokenizer


lowerCamelCase__    :		Union[str, Any]          =   logging.get_logger(__name__)



class       _snake_case   (	UpperCAmelCase_							):
 __lowerCAmelCase  :     List[Any]        =			'AutoTokenizer'
 __lowerCAmelCase  :     Any        =			['tokenizer']

 __lowerCAmelCase  :     Dict        =			{
     'semantic_prompt': 1,
     'coarse_prompt': 2,
     'fine_prompt': 2,
 }


 def __init__(					self					,  SCREAMING_SNAKE_CASE_					,  SCREAMING_SNAKE_CASE_=None):


   '''simple docstring'''




   super().__init__(SCREAMING_SNAKE_CASE_)

   lowercase__  :   str    		=      speaker_embeddings


 @classmethod
 def      lowercase__     (					cls					,  SCREAMING_SNAKE_CASE_					,  SCREAMING_SNAKE_CASE_="speaker_embeddings_path.json"					,  **SCREAMING_SNAKE_CASE_):


   '''simple docstring'''




   if speaker_embeddings_dict_path is not None:
     lowercase__  :   Optional[int]    		=      get_file_from_repo(
         SCREAMING_SNAKE_CASE_					,  SCREAMING_SNAKE_CASE_					,  subfolder=kwargs.pop("""subfolder"""					,  SCREAMING_SNAKE_CASE_)					,  cache_dir=kwargs.pop("""cache_dir"""					,  SCREAMING_SNAKE_CASE_)					,  force_download=kwargs.pop("""force_download"""					,  SCREAMING_SNAKE_CASE_)					,  proxies=kwargs.pop("""proxies"""					,  SCREAMING_SNAKE_CASE_)					,  resume_download=kwargs.pop("""resume_download"""					,  SCREAMING_SNAKE_CASE_)					,  local_files_only=kwargs.pop("""local_files_only"""					,  SCREAMING_SNAKE_CASE_)					,  use_auth_token=kwargs.pop("""use_auth_token"""					,  SCREAMING_SNAKE_CASE_)					,  revision=kwargs.pop("""revision"""					,  SCREAMING_SNAKE_CASE_)					,  )
     if speaker_embeddings_path is None:
       logger.warning(
           f'`{os.path.join(SCREAMING_SNAKE_CASE_					,  SCREAMING_SNAKE_CASE_)}` does not exists\n                    , no preloaded speaker embeddings will be used - Make sure to provide a correct path to the json\n                    dictionnary if wanted, otherwise set `speaker_embeddings_dict_path=None`.')
       lowercase__  :   str    		=      None
     else:
       with open(SCREAMING_SNAKE_CASE_) as speaker_embeddings_json:
         lowercase__  :   Tuple    		=      json.load(SCREAMING_SNAKE_CASE_)
   else:
     lowercase__  :   List[Any]    		=      None

   lowercase__  :   str    		=      AutoTokenizer.from_pretrained(SCREAMING_SNAKE_CASE_					,  **SCREAMING_SNAKE_CASE_)

   return cls(tokenizer=SCREAMING_SNAKE_CASE_					,  speaker_embeddings=SCREAMING_SNAKE_CASE_)


 def      lowercase__     (					self					,  SCREAMING_SNAKE_CASE_					,  SCREAMING_SNAKE_CASE_="speaker_embeddings_path.json"					,  SCREAMING_SNAKE_CASE_="speaker_embeddings"					,  SCREAMING_SNAKE_CASE_ = False					,  **SCREAMING_SNAKE_CASE_					,  ):


   '''simple docstring'''




   if self.speaker_embeddings is not None:
     os.makedirs(os.path.join(SCREAMING_SNAKE_CASE_					,  SCREAMING_SNAKE_CASE_					,  """v2""")					,  exist_ok=SCREAMING_SNAKE_CASE_)

     lowercase__  :   Tuple    		=      {}

     lowercase__  :   int    		=      save_directory

     for prompt_key in self.speaker_embeddings:
       if prompt_key != "repo_or_path":
         lowercase__  :   List[Any]    		=      self._load_voice_preset(SCREAMING_SNAKE_CASE_)

         lowercase__  :   List[str]    		=      {}
         for key in self.speaker_embeddings[prompt_key]:
           np.save(
               os.path.join(
                   embeddings_dict["""repo_or_path"""]					,  SCREAMING_SNAKE_CASE_					,  f'{prompt_key}_{key}')					,  voice_preset[key]					,  allow_pickle=SCREAMING_SNAKE_CASE_					,  )
           lowercase__  :   str    		=      os.path.join(SCREAMING_SNAKE_CASE_					,  f'{prompt_key}_{key}.npy')

         lowercase__  :   Optional[int]    		=      tmp_dict

     with open(os.path.join(SCREAMING_SNAKE_CASE_					,  SCREAMING_SNAKE_CASE_)					,  """w""") as fp:
       json.dump(SCREAMING_SNAKE_CASE_					,  SCREAMING_SNAKE_CASE_)

   super().save_pretrained(SCREAMING_SNAKE_CASE_					,  SCREAMING_SNAKE_CASE_					,  **SCREAMING_SNAKE_CASE_)


 def      lowercase__     (					self					,  SCREAMING_SNAKE_CASE_ = None					,  **SCREAMING_SNAKE_CASE_):


   '''simple docstring'''




   lowercase__  :   Optional[int]    		=      self.speaker_embeddings[voice_preset]

   lowercase__  :   List[str]    		=      {}
   for key in ["semantic_prompt", "coarse_prompt", "fine_prompt"]:
     if key not in voice_preset_paths:
       raise ValueError(
           f'Voice preset unrecognized, missing {key} as a key in self.speaker_embeddings[{voice_preset}].')

     lowercase__  :   List[Any]    		=      get_file_from_repo(
         self.speaker_embeddings.get("""repo_or_path"""					,  """/""")					,  voice_preset_paths[key]					,  subfolder=kwargs.pop("""subfolder"""					,  SCREAMING_SNAKE_CASE_)					,  cache_dir=kwargs.pop("""cache_dir"""					,  SCREAMING_SNAKE_CASE_)					,  force_download=kwargs.pop("""force_download"""					,  SCREAMING_SNAKE_CASE_)					,  proxies=kwargs.pop("""proxies"""					,  SCREAMING_SNAKE_CASE_)					,  resume_download=kwargs.pop("""resume_download"""					,  SCREAMING_SNAKE_CASE_)					,  local_files_only=kwargs.pop("""local_files_only"""					,  SCREAMING_SNAKE_CASE_)					,  use_auth_token=kwargs.pop("""use_auth_token"""					,  SCREAMING_SNAKE_CASE_)					,  revision=kwargs.pop("""revision"""					,  SCREAMING_SNAKE_CASE_)					,  )
     if path is None:
       raise ValueError(
           f'`{os.path.join(self.speaker_embeddings.get("repo_or_path"					,  "/")					,  voice_preset_paths[key])}` does not exists\n                    , no preloaded voice preset will be used - Make sure to provide correct paths to the {voice_preset}\n                    embeddings.')

     lowercase__  :   List[str]    		=      np.load(SCREAMING_SNAKE_CASE_)

   return voice_preset_dict


 def      lowercase__     (					self					,  SCREAMING_SNAKE_CASE_ = None):


   '''simple docstring'''




   for key in ["semantic_prompt", "coarse_prompt", "fine_prompt"]:
     if key not in voice_preset:
       raise ValueError(f'Voice preset unrecognized, missing {key} as a key.')

     if not isinstance(voice_preset[key]					,  np.ndarray):
       raise ValueError(f'{key} voice preset must be a {str(self.preset_shape[key])}D ndarray.')

     if len(voice_preset[key].shape) != self.preset_shape[key]:
       raise ValueError(f'{key} voice preset must be a {str(self.preset_shape[key])}D ndarray.')



 def __call__(					self					,  SCREAMING_SNAKE_CASE_=None					,  SCREAMING_SNAKE_CASE_=None					,  SCREAMING_SNAKE_CASE_="pt"					,  SCREAMING_SNAKE_CASE_=2_56					,  SCREAMING_SNAKE_CASE_=False					,  SCREAMING_SNAKE_CASE_=True					,  SCREAMING_SNAKE_CASE_=False					,  **SCREAMING_SNAKE_CASE_					,  ):


   '''simple docstring'''




   if voice_preset is not None and not isinstance(SCREAMING_SNAKE_CASE_					,  SCREAMING_SNAKE_CASE_):
     if (
         isinstance(SCREAMING_SNAKE_CASE_					,  SCREAMING_SNAKE_CASE_)
         and self.speaker_embeddings is not None
         and voice_preset in self.speaker_embeddings
     ):
       lowercase__  :   List[str]    		=      self._load_voice_preset(SCREAMING_SNAKE_CASE_)

     else:
       if isinstance(SCREAMING_SNAKE_CASE_					,  SCREAMING_SNAKE_CASE_) and not voice_preset.endswith(""".npz"""):
         lowercase__  :   Optional[int]    		=      voice_preset + """.npz"""

       lowercase__  :   Tuple    		=      np.load(SCREAMING_SNAKE_CASE_)

   if voice_preset is not None:
     self._validate_voice_preset_dict(SCREAMING_SNAKE_CASE_					,  **SCREAMING_SNAKE_CASE_)
     lowercase__  :   Tuple    		=      BatchFeature(data=SCREAMING_SNAKE_CASE_					,  tensor_type=SCREAMING_SNAKE_CASE_)

   lowercase__  :   Optional[int]    		=      self.tokenizer(
       SCREAMING_SNAKE_CASE_					,  return_tensors=SCREAMING_SNAKE_CASE_					,  padding="""max_length"""					,  max_length=SCREAMING_SNAKE_CASE_					,  return_attention_mask=SCREAMING_SNAKE_CASE_					,  return_token_type_ids=SCREAMING_SNAKE_CASE_					,  add_special_tokens=SCREAMING_SNAKE_CASE_					,  **SCREAMING_SNAKE_CASE_					,  )

   if voice_preset is not None:
     lowercase__  :   Any    		=      voice_preset

   return encoded_text








from __future__ import annotations

from collections.abc import Iterator
from typing import Any



class       _snake_case   :


 def __init__(					self					,  SCREAMING_SNAKE_CASE_):


   '''simple docstring'''




   lowercase__  :   Any    		=      data
   lowercase__  :   Node | None    		=      None



class       _snake_case   :


 def __init__(					self):


   '''simple docstring'''




   lowercase__  :   List[Any]    		=      None
   lowercase__  :   int    		=      None


 def __iter__(					self):


   '''simple docstring'''




   lowercase__  :   List[str]    		=      self.head
   while self.head:
     yield node.data
     lowercase__  :   str    		=      node.next
     if node == self.head:
       break


 def __len__(					self):


   '''simple docstring'''




   return sum(1 for _ in self)


 def __repr__(					self):


   '''simple docstring'''




   return "->".join(str(SCREAMING_SNAKE_CASE_) for item in iter(self))


 def      lowercase__     (					self					,  SCREAMING_SNAKE_CASE_):


   '''simple docstring'''




   self.insert_nth(len(self)					,  SCREAMING_SNAKE_CASE_)


 def      lowercase__     (					self					,  SCREAMING_SNAKE_CASE_):


   '''simple docstring'''




   self.insert_nth(0					,  SCREAMING_SNAKE_CASE_)


 def      lowercase__     (					self					,  SCREAMING_SNAKE_CASE_					,  SCREAMING_SNAKE_CASE_):


   '''simple docstring'''




   if index < 0 or index > len(self):
     raise IndexError("""list index out of range.""")
   lowercase__  :   Optional[int]    		=      Node(SCREAMING_SNAKE_CASE_)
   if self.head is None:
     lowercase__  :   Union[str, Any]    		=      new_node  # first node points itself
     lowercase__  :   Dict    		=      new_node
   elif index == 0:  # insert at head
     lowercase__  :   int    		=      self.head
     lowercase__  :   int    		=      new_node
   else:
     lowercase__  :   List[str]    		=      self.head
     for _ in range(index - 1):
       lowercase__  :   Union[str, Any]    		=      temp.next
     lowercase__  :   int    		=      temp.next
     lowercase__  :   Optional[Any]    		=      new_node
     if index == len(self) - 1:  # insert at tail
       lowercase__  :   Union[str, Any]    		=      new_node


 def      lowercase__     (					self):


   '''simple docstring'''




   return self.delete_nth(0)


 def      lowercase__     (					self):


   '''simple docstring'''




   return self.delete_nth(len(self) - 1)


 def      lowercase__     (					self					,  SCREAMING_SNAKE_CASE_ = 0):


   '''simple docstring'''




   if not 0 <= index < len(self):
     raise IndexError("""list index out of range.""")
   lowercase__  :   str    		=      self.head
   if self.head == self.tail:  # just one node
     lowercase__  :   List[Any]    		=      None
   elif index == 0:  # delete head node
     lowercase__  :   str    		=      self.tail.next.next
     lowercase__  :   List[Any]    		=      self.head.next
   else:
     lowercase__  :   Optional[int]    		=      self.head
     for _ in range(index - 1):
       lowercase__  :   List[Any]    		=      temp.next
     lowercase__  :   Optional[Any]    		=      temp.next
     lowercase__  :   Dict    		=      temp.next.next
     if index == len(self) - 1:  # delete at tail
       lowercase__  :   Tuple    		=      temp
   return delete_node.data



 def      lowercase__     (					self):


   '''simple docstring'''




   return len(self) == 0

def 		UpperCamelCase	(      )		->	None:


  '''simple docstring'''






  lowercase__  :   int    		=      CircularLinkedList()
  assert len(lowercase_   ) == 0
  assert circular_linked_list.is_empty() is True
  assert str(lowercase_   ) == ""

  try:
    circular_linked_list.delete_front()
    raise AssertionError  # This should not happen
  except IndexError:
    assert True  # This should happen

  try:
    circular_linked_list.delete_tail()
    raise AssertionError  # This should not happen
  except IndexError:
    assert True  # This should happen

  try:
    circular_linked_list.delete_nth(-1   )
    raise AssertionError
  except IndexError:
    assert True

  try:
    circular_linked_list.delete_nth(0   )
    raise AssertionError
  except IndexError:
    assert True

  assert circular_linked_list.is_empty() is True
  for i in range(5   ):
    assert len(lowercase_   ) == i
    circular_linked_list.insert_nth(lowercase_ , i + 1   )
  assert str(lowercase_   ) == "->".join(str(lowercase_   ) for i in range(1 , 6   )   )

  circular_linked_list.insert_tail(6   )
  assert str(lowercase_   ) == "->".join(str(lowercase_   ) for i in range(1 , 7   )   )
  circular_linked_list.insert_head(0   )
  assert str(lowercase_   ) == "->".join(str(lowercase_   ) for i in range(0 , 7   )   )

  assert circular_linked_list.delete_front() == 0
  assert circular_linked_list.delete_tail() == 6
  assert str(lowercase_   ) == "->".join(str(lowercase_   ) for i in range(1 , 6   )   )
  assert circular_linked_list.delete_nth(2   ) == 3

  circular_linked_list.insert_nth(2 , 3   )
  assert str(lowercase_   ) == "->".join(str(lowercase_   ) for i in range(1 , 6   )   )

  assert circular_linked_list.is_empty() is False


if __name__ == "__main__":
     import doctest

     doctest.testmod()






