
'''simple docstring'''


import json
from typing import List, Optional, Tuple

from tokenizers import pre_tokenizers, processors

from ...tokenization_utils_base import AddedToken, BatchEncoding
from ...tokenization_utils_fast import PreTrainedTokenizerFast
from ...utils import logging
from .tokenization_bart import BartTokenizer


snake_case_ :  Dict     =					logging.get_logger(__name__)


snake_case_ :  Any     =					{'vocab_file': 'vocab.json', 'merges_file': 'merges.txt', 'tokenizer_file': 'tokenizer.json'}

# See all BART models at https://huggingface.co/models?filter=bart
snake_case_ :  Any     =					{
    'vocab_file': {
        'facebook/bart-base': 'https://huggingface.co/facebook/bart-base/resolve/main/vocab.json',
        'facebook/bart-large': 'https://huggingface.co/facebook/bart-large/resolve/main/vocab.json',
        'facebook/bart-large-mnli': 'https://huggingface.co/facebook/bart-large-mnli/resolve/main/vocab.json',
        'facebook/bart-large-cnn': 'https://huggingface.co/facebook/bart-large-cnn/resolve/main/vocab.json',
        'facebook/bart-large-xsum': 'https://huggingface.co/facebook/bart-large-xsum/resolve/main/vocab.json',
        'yjernite/bart_eli5': 'https://huggingface.co/yjernite/bart_eli5/resolve/main/vocab.json',
    },
    'merges_file': {
        'facebook/bart-base': 'https://huggingface.co/facebook/bart-base/resolve/main/merges.txt',
        'facebook/bart-large': 'https://huggingface.co/facebook/bart-large/resolve/main/merges.txt',
        'facebook/bart-large-mnli': 'https://huggingface.co/facebook/bart-large-mnli/resolve/main/merges.txt',
        'facebook/bart-large-cnn': 'https://huggingface.co/facebook/bart-large-cnn/resolve/main/merges.txt',
        'facebook/bart-large-xsum': 'https://huggingface.co/facebook/bart-large-xsum/resolve/main/merges.txt',
        'yjernite/bart_eli5': 'https://huggingface.co/yjernite/bart_eli5/resolve/main/merges.txt',
    },
    'tokenizer_file': {
        'facebook/bart-base': 'https://huggingface.co/facebook/bart-base/resolve/main/tokenizer.json',
        'facebook/bart-large': 'https://huggingface.co/facebook/bart-large/resolve/main/tokenizer.json',
        'facebook/bart-large-mnli': 'https://huggingface.co/facebook/bart-large-mnli/resolve/main/tokenizer.json',
        'facebook/bart-large-cnn': 'https://huggingface.co/facebook/bart-large-cnn/resolve/main/tokenizer.json',
        'facebook/bart-large-xsum': 'https://huggingface.co/facebook/bart-large-xsum/resolve/main/tokenizer.json',
        'yjernite/bart_eli5': 'https://huggingface.co/yjernite/bart_eli5/resolve/main/tokenizer.json',
    },
}

snake_case_ :  int     =					{
    'facebook/bart-base': 1_024,
    'facebook/bart-large': 1_024,
    'facebook/bart-large-mnli': 1_024,
    'facebook/bart-large-cnn': 1_024,
    'facebook/bart-large-xsum': 1_024,
    'yjernite/bart_eli5': 1_024,
}


class 						lowercase__	(  _UpperCAmelCase   ):






   '''simple docstring'''







   _snake_case		   =							VOCAB_FILES_NAMES
   _snake_case		   =							PRETRAINED_VOCAB_FILES_MAP
   _snake_case		   =							PRETRAINED_POSITIONAL_EMBEDDINGS_SIZES
   _snake_case		   =							['''input_ids''', '''attention_mask''']
   _snake_case		   =							BartTokenizer







   def __init__(			self ,   lowerCamelCase__=None ,   lowerCamelCase__=None ,   lowerCamelCase__=None ,   lowerCamelCase__="replace" ,   lowerCamelCase__="<s>" ,   lowerCamelCase__="</s>" ,   lowerCamelCase__="</s>" ,   lowerCamelCase__="<s>" ,   lowerCamelCase__="<unk>" ,   lowerCamelCase__="<pad>" ,   lowerCamelCase__="<mask>" ,   lowerCamelCase__=False ,   lowerCamelCase__=True ,   **lowerCamelCase__ ,   ):

      '''simple docstring'''







      super().__init__(
          lowercase__ ,   lowercase__ ,   tokenizer_file=lowercase__ ,   errors=lowercase__ ,   bos_token=lowercase__ ,   eos_token=lowercase__ ,   sep_token=lowercase__ ,   cls_token=lowercase__ ,   unk_token=lowercase__ ,   pad_token=lowercase__ ,   mask_token=lowercase__ ,   add_prefix_space=lowercase__ ,   trim_offsets=lowercase__ ,   **lowercase__ ,   )

      UpperCamelCase       =  json.loads(self.backend_tokenizer.pre_tokenizer.__getstate__()   )
      if pre_tok_state.get('''add_prefix_space''' ,   lowercase__   ) != add_prefix_space:
         UpperCamelCase       =  getattr(lowercase__ ,   pre_tok_state.pop('''type'''   )   )
         UpperCamelCase       =  add_prefix_space
         UpperCamelCase       =  pre_tok_class(**lowercase__   )

      UpperCamelCase       =  add_prefix_space

      # the pre_tokenizer is already updated in the GPT2TokenizerFast `__init__`
      UpperCamelCase       =  "post_processor"
      UpperCamelCase       =  getattr(self.backend_tokenizer ,   lowercase__ ,   lowercase__   )
      if tokenizer_component_instance:
         UpperCamelCase       =  json.loads(tokenizer_component_instance.__getstate__()   )

         # The lists 'sep' and 'cls' must be cased in tuples for the object `post_processor_class`
         if "sep" in state:
            UpperCamelCase       =  tuple(state['''sep''']   )
         if "cls" in state:
            UpperCamelCase       =  tuple(state['''cls''']   )

         UpperCamelCase       =  False

         if state.get('''add_prefix_space''' ,   lowercase__   ) != add_prefix_space:
            UpperCamelCase       =  add_prefix_space
            UpperCamelCase       =  True

         if state.get('''trim_offsets''' ,   lowercase__   ) != trim_offsets:
            UpperCamelCase       =  trim_offsets
            UpperCamelCase       =  True

         if changes_to_apply:
            UpperCamelCase       =  getattr(lowercase__ ,   state.pop('''type'''   )   )
            UpperCamelCase       =  component_class(**lowercase__   )
            setattr(self.backend_tokenizer ,   lowercase__ ,   lowercase__   )







   @property
   def       UpperCAmelCase				(			self   ):

      '''simple docstring'''







      if self._mask_token is None:
         if self.verbose:
            logger.error('''Using mask_token, but it is not set yet.'''   )
         return None
      return str(self._mask_token   )







   @mask_token.setter
   def       UpperCAmelCase				(			self ,   lowerCamelCase__   ):

      '''simple docstring'''







      UpperCamelCase       =  AddedToken(lowercase__ ,   lstrip=lowercase__ ,   rstrip=lowercase__   ) if isinstance(lowercase__ ,   lowercase__   ) else value
      UpperCamelCase       =  value







   def       UpperCAmelCase				(			self ,   *lowerCamelCase__ ,   **lowerCamelCase__   ):

      '''simple docstring'''







      UpperCamelCase       =  kwargs.get('''is_split_into_words''' ,   lowercase__   )

      if is_split_into_words and not self.add_prefix_space:
         raise ValueError(
             f'You need to instantiate {self.__class__.__name__} with add_prefix_space=True '
             '''to use it with pretokenized inputs.'''   )

      return super()._batch_encode_plus(*lowercase__ ,   **lowercase__   )







   def       UpperCAmelCase				(			self ,   *lowerCamelCase__ ,   **lowerCamelCase__   ):

      '''simple docstring'''







      UpperCamelCase       =  kwargs.get('''is_split_into_words''' ,   lowercase__   )

      if is_split_into_words and not self.add_prefix_space:
         raise ValueError(
             f'You need to instantiate {self.__class__.__name__} with add_prefix_space=True '
             '''to use it with pretokenized inputs.'''   )

      return super()._encode_plus(*lowercase__ ,   **lowercase__   )







   def       UpperCAmelCase				(			self ,   lowerCamelCase__ ,   lowerCamelCase__ = None   ):

      '''simple docstring'''







      UpperCamelCase       =  self._tokenizer.model.save(lowercase__ ,   name=lowercase__   )
      return tuple(lowercase__   )







   def       UpperCAmelCase				(			self ,   lowerCamelCase__ ,   lowerCamelCase__=None   ):

      '''simple docstring'''







      UpperCamelCase       =  [self.bos_token_id] + token_ids_a + [self.eos_token_id]
      if token_ids_a is None:
         return output

      return output + [self.eos_token_id] + token_ids_a + [self.eos_token_id]







   def       UpperCAmelCase				(			self ,   lowerCamelCase__ ,   lowerCamelCase__ = None   ):

      '''simple docstring'''







      UpperCamelCase       =  [self.sep_token_id]
      UpperCamelCase       =  [self.cls_token_id]

      if token_ids_a is None:
         return len(cls + token_ids_a + sep   ) * [0]
      return len(cls + token_ids_a + sep + sep + token_ids_a + sep   ) * [0]







'''simple docstring'''


import math
from typing import Optional

import numpy as np

from ...configuration_utils import PretrainedConfig
from ...utils import logging


snake_case_ :  Dict     =					logging.get_logger(__name__)

snake_case_ :  Union[str, Any]     =					{
    'facebook/encodec_24khz': 'https://huggingface.co/facebook/encodec_24khz/resolve/main/config.json',
    'facebook/encodec_48khz': 'https://huggingface.co/facebook/encodec_48khz/resolve/main/config.json',
}


class 						lowercase__	(  snake_case_   ):






   '''simple docstring'''







   _snake_case		   =							'''encodec'''







   def __init__(			self ,   lowerCamelCase__=[1.5, 3.0, 6.0, 12.0, 24.0] ,   lowerCamelCase__=2_4_0_0_0 ,   lowerCamelCase__=1 ,   lowerCamelCase__=False ,   lowerCamelCase__=None ,   lowerCamelCase__=None ,   lowerCamelCase__=1_2_8 ,   lowerCamelCase__=3_2 ,   lowerCamelCase__=1 ,   lowerCamelCase__=[8, 5, 4, 2] ,   lowerCamelCase__="weight_norm" ,   lowerCamelCase__=7 ,   lowerCamelCase__=7 ,   lowerCamelCase__=3 ,   lowerCamelCase__=2 ,   lowerCamelCase__=True ,   lowerCamelCase__="reflect" ,   lowerCamelCase__=2 ,   lowerCamelCase__=2 ,   lowerCamelCase__=1.0 ,   lowerCamelCase__=1_0_2_4 ,   lowerCamelCase__=None ,   lowerCamelCase__=True ,   **lowerCamelCase__ ,   ):

      '''simple docstring'''







      UpperCamelCase       =  target_bandwidths
      UpperCamelCase       =  sampling_rate
      UpperCamelCase       =  audio_channels
      UpperCamelCase       =  normalize
      UpperCamelCase       =  chunk_length_s
      UpperCamelCase       =  overlap
      UpperCamelCase       =  hidden_size
      UpperCamelCase       =  num_filters
      UpperCamelCase       =  num_residual_layers
      UpperCamelCase       =  upsampling_ratios
      UpperCamelCase       =  norm_type
      UpperCamelCase       =  kernel_size
      UpperCamelCase       =  last_kernel_size
      UpperCamelCase       =  residual_kernel_size
      UpperCamelCase       =  dilation_growth_rate
      UpperCamelCase       =  use_causal_conv
      UpperCamelCase       =  pad_mode
      UpperCamelCase       =  compress
      UpperCamelCase       =  num_lstm_layers
      UpperCamelCase       =  trim_right_ratio
      UpperCamelCase       =  codebook_size
      UpperCamelCase       =  codebook_dim if codebook_dim is not None else hidden_size
      UpperCamelCase       =  use_conv_shortcut

      if self.norm_type not in ["weight_norm", "time_group_norm"]:
         raise ValueError(
             f'self.norm_type must be one of `"weight_norm"`, `"time_group_norm"`), got {self.norm_type}'   )

      super().__init__(**lowerCamelCase__   )







   @property
   def       UpperCAmelCase				(			self   ):

      '''simple docstring'''







      if self.chunk_length_s is None:
         return None
      else:
         return int(self.chunk_length_s * self.sampling_rate   )







   @property
   def       UpperCAmelCase				(			self   ):

      '''simple docstring'''







      if self.chunk_length_s is None or self.overlap is None:
         return None
      else:
         return max(1 ,   int((1.0 - self.overlap) * self.chunk_length   )   )







   @property
   def       UpperCAmelCase				(			self   ):

      '''simple docstring'''







      UpperCamelCase       =  np.prod(self.upsampling_ratios   )
      return math.ceil(self.sampling_rate / hop_length   )







   @property
   def       UpperCAmelCase				(			self   ):

      '''simple docstring'''







      return int(1_0_0_0 * self.target_bandwidths[-1] // (self.frame_rate * 1_0)   )





