




'''simple docstring'''







import warnings
from typing import Dict, List, Optional, Tuple

from ...tokenization_utils import AddedToken, PreTrainedTokenizer
from ...utils import logging


A									=logging.get_logger(__name__)


class     _a						(			_UpperCamelCase				):
       __a       :  Dict            =      ["""input_ids""", """attention_mask"""]
       def __init__(			self		:			List[str]     ,       lowercase		:			Dict="</s>"     ,       lowercase		:			List[Any]="<unk>"     ,       lowercase		:			Tuple="<pad>"     ,       lowercase		:			Any=125     ,       lowercase		:			Union[str, Any]=None     ,       **lowercase		:			Any     ,       ):



           '''simple docstring'''

           if extra_ids > 0 and additional_special_tokens is None:
               UpperCAmelCase     =	[f"<extra_id_{i}>" for i in range(_UpperCAmelCase       )]
           elif extra_ids > 0 and additional_special_tokens is not None:
               # Check that we have the right number of extra_id special tokens
               UpperCAmelCase     =	len(set(filter(lambda lowercase       : bool('''extra_id''' in str(_UpperCAmelCase       )       )     ,       _UpperCAmelCase       )       )       )
               if extra_tokens != extra_ids:
                   raise ValueError(
                       f"Both extra_ids ({extra_ids}) and additional_special_tokens ({additional_special_tokens}) are"
                       ''' provided to ByT5Tokenizer. In this case the additional_special_tokens must include the'''
                       ''' extra_ids tokens'''       )

           UpperCAmelCase     =	AddedToken(_UpperCAmelCase     ,       lstrip=_UpperCAmelCase     ,       rstrip=_UpperCAmelCase       ) if isinstance(_UpperCAmelCase     ,       _UpperCAmelCase       ) else pad_token
           UpperCAmelCase     =	AddedToken(_UpperCAmelCase     ,       lstrip=_UpperCAmelCase     ,       rstrip=_UpperCAmelCase       ) if isinstance(_UpperCAmelCase     ,       _UpperCAmelCase       ) else eos_token
           UpperCAmelCase     =	AddedToken(_UpperCAmelCase     ,       lstrip=_UpperCAmelCase     ,       rstrip=_UpperCAmelCase       ) if isinstance(_UpperCAmelCase     ,       _UpperCAmelCase       ) else unk_token

           super().__init__(
               eos_token=_UpperCAmelCase     ,       unk_token=_UpperCAmelCase     ,       pad_token=_UpperCAmelCase     ,       extra_ids=_UpperCAmelCase     ,       additional_special_tokens=_UpperCAmelCase     ,       **_UpperCAmelCase     ,       )

           UpperCAmelCase     =	extra_ids

           UpperCAmelCase     =	2**8  # utf is 8 bits

           # define special tokens dict
           UpperCAmelCase     =	{
               self.pad_token: 0,
               self.eos_token: 1,
               self.unk_token: 2,
           }
           UpperCAmelCase     =	len(self.special_tokens_encoder       )
           UpperCAmelCase     =	len(_UpperCAmelCase       )
           for i, token in enumerate(_UpperCAmelCase       ):
               UpperCAmelCase     =	self.vocab_size + i - n
           UpperCAmelCase     =	{v: k for k, v in self.special_tokens_encoder.items()}
       @property
       def 					A   (			self		:			str       ):



           '''simple docstring'''

           return self._utf_vocab_size + self._num_special_tokens + self._extra_ids
       def 					A   (			self		:			Any     ,       lowercase		:			List[str]     ,       lowercase		:			List[str] = None     ,       lowercase		:			Any = False       ):



           '''simple docstring'''

           if already_has_special_tokens:
               return super().get_special_tokens_mask(
                   token_ids_a=_UpperCAmelCase     ,       token_ids_a=_UpperCAmelCase     ,       already_has_special_tokens=_UpperCAmelCase       )

           # normal case: some special tokens
           if token_ids_a is None:
               return ([0] * len(_UpperCAmelCase       )) + [1]
           return ([0] * len(_UpperCAmelCase       )) + [1] + ([0] * len(_UpperCAmelCase       )) + [1]
       def 					A   (			self		:			int     ,       lowercase		:			Any       ):



           '''simple docstring'''

           if len(_UpperCAmelCase       ) > 0 and token_ids[-1] == self.eos_token_id:
               warnings.warn(
                   f"This sequence already has {self.eos_token}. In future versions this behavior may lead to duplicated"
                   ''' eos tokens being added.'''       )
               return token_ids
           else:
               return token_ids + [self.eos_token_id]
       def 					A   (			self		:			Union[str, Any]     ,       lowercase		:			Optional[Any]     ,       lowercase		:			Optional[int] = None       ):



           '''simple docstring'''

           UpperCAmelCase     =	[self.eos_token_id]

           if token_ids_a is None:
               return len(token_ids_a + eos       ) * [0]
           return len(token_ids_a + eos + token_ids_a + eos       ) * [0]
       def 					A   (			self		:			List[Any]     ,       lowercase		:			Union[str, Any]     ,       lowercase		:			str = None       ):



           '''simple docstring'''

           UpperCAmelCase     =	self._add_eos_if_not_present(_UpperCAmelCase       )
           if token_ids_a is None:
               return token_ids_a
           else:
               UpperCAmelCase     =	self._add_eos_if_not_present(_UpperCAmelCase       )
               return token_ids_a + token_ids_a
       def 					A   (			self		:			Tuple     ,       lowercase		:			Tuple       ):



           '''simple docstring'''

           UpperCAmelCase     =	[chr(_UpperCAmelCase       ) for i in text.encode('''utf-8'''       )]
           return tokens
       def 					A   (			self		:			Optional[Any]     ,       lowercase		:			List[Any]       ):



           '''simple docstring'''

           if token in self.special_tokens_encoder:
               UpperCAmelCase     =	self.special_tokens_encoder[token]
           elif token in self.added_tokens_encoder:
               UpperCAmelCase     =	self.added_tokens_encoder[token]
           elif len(_UpperCAmelCase       ) != 1:
               UpperCAmelCase     =	self.unk_token_id
           else:
               UpperCAmelCase     =	ord(_UpperCAmelCase       ) + self._num_special_tokens
           return token_id
       def 					A   (			self		:			Optional[Any]     ,       lowercase		:			Dict       ):



           '''simple docstring'''

           if index in self.special_tokens_decoder:
               UpperCAmelCase     =	self.special_tokens_decoder[index]
           else:
               UpperCAmelCase     =	chr(index - self._num_special_tokens       )
           return token
       def 					A   (			self		:			List[Any]     ,       lowercase		:			Tuple       ):



           '''simple docstring'''

           UpperCAmelCase     =	b''''''
           for token in tokens:
               if token in self.special_tokens_decoder:
                   UpperCAmelCase     =	self.special_tokens_decoder[token].encode('''utf-8'''       )
               elif token in self.added_tokens_decoder:
                   UpperCAmelCase     =	self.special_tokens_decoder[token].encode('''utf-8'''       )
               elif token in self.special_tokens_encoder:
                   UpperCAmelCase     =	token.encode('''utf-8'''       )
               elif token in self.added_tokens_encoder:
                   UpperCAmelCase     =	token.encode('''utf-8'''       )
               else:
                   UpperCAmelCase     =	bytes([ord(_UpperCAmelCase       )]       )
               bstring += tok_string
           UpperCAmelCase     =	bstring.decode('''utf-8'''     ,       errors='''ignore'''       )
           return string







       def 					A   (			self		:			Union[str, Any]     ,       lowercase		:			Tuple     ,       lowercase		:			List[Any] = None       ):



           '''simple docstring'''

           return ()










'''simple docstring'''







import math
from typing import Optional

import numpy as np

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


A									=logging.get_logger(__name__)

A									={
    '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     _a						(			__a				):
       __a       :  Union[str, Any]            =      """encodec"""
       def __init__(			self		:			Optional[int]     ,       lowercase		:			Union[str, Any]=[1.5, 3.0, 6.0, 12.0, 24.0]     ,       lowercase		:			str=24_000     ,       lowercase		:			int=1     ,       lowercase		:			int=False     ,       lowercase		:			List[str]=None     ,       lowercase		:			Tuple=None     ,       lowercase		:			int=128     ,       lowercase		:			List[Any]=32     ,       lowercase		:			Optional[int]=1     ,       lowercase		:			Optional[int]=[8, 5, 4, 2]     ,       lowercase		:			Union[str, Any]="weight_norm"     ,       lowercase		:			Optional[int]=7     ,       lowercase		:			Tuple=7     ,       lowercase		:			Tuple=3     ,       lowercase		:			Union[str, Any]=2     ,       lowercase		:			Optional[Any]=True     ,       lowercase		:			Tuple="reflect"     ,       lowercase		:			Any=2     ,       lowercase		:			List[str]=2     ,       lowercase		:			str=1.0     ,       lowercase		:			List[str]=1_024     ,       lowercase		:			Optional[Any]=None     ,       lowercase		:			Any=True     ,       **lowercase		:			Optional[Any]     ,       ):



           '''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__(**lowercase       )
       @property
       def 					A   (			self		:			List[str]       ):



           '''simple docstring'''

           if self.chunk_length_s is None:
               return None
           else:
               return int(self.chunk_length_s * self.sampling_rate       )
       @property
       def 					A   (			self		:			Optional[Any]       ):



           '''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 					A   (			self		:			Union[str, Any]       ):



           '''simple docstring'''

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







       @property
       def 					A   (			self		:			Optional[int]       ):



           '''simple docstring'''

           return int(1_000 * self.target_bandwidths[-1] // (self.frame_rate * 10)       )




