
"""simple docstring"""






import os
import unicodedata
from shutil import copyfile
from typing import Any, Dict, List, Optional, Tuple

import sentencepiece as spm

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


lowerCamelCase__ :       str						     =			logging.get_logger(__name__)

lowerCamelCase__ :       List[str]						     =			{"vocab_file": "spiece.model"}

lowerCamelCase__ :       Tuple						     =			{
    "vocab_file": {
        "TsinghuaAI/CPM-Generate": "https://huggingface.co/TsinghuaAI/CPM-Generate/resolve/main/spiece.model",
    }
}




class 				lowercase__(				_UpperCAmelCase   ):
	'''simple docstring'''

	def __init__(						self    :Optional[int]		, lowerCamelCase_    :str		, lowerCamelCase_    :Union[str, Any]=False		, lowerCamelCase_    :Optional[int]=True		, lowerCamelCase_    :Any=False		, lowerCamelCase_    :Optional[int]="<s>"		, lowerCamelCase_    :int="</s>"		, lowerCamelCase_    :Dict="<unk>"		, lowerCamelCase_    :Tuple="<sep>"		, lowerCamelCase_    :Union[str, Any]="<pad>"		, lowerCamelCase_    :str="<cls>"		, lowerCamelCase_    :Union[str, Any]="<mask>"		, lowerCamelCase_    :List[Any]=["<eop>", "<eod>"]		, lowerCamelCase_    :Optional[Dict[str, Any]] = None		, **lowerCamelCase_    :int		, )							->			None:







			'''simple docstring'''




			SCREAMING_SNAKE_CASE       :     Optional[int]				= AddedToken(lowerCamelCase_		, lstrip=lowerCamelCase_		, rstrip=lowerCamelCase_					) if isinstance(lowerCamelCase_		, lowerCamelCase_					) else mask_token

			SCREAMING_SNAKE_CASE       :     Union[str, Any]				= {} if sp_model_kwargs is None else sp_model_kwargs

			super().__init__(
			    do_lower_case=lowerCamelCase_		, remove_space=lowerCamelCase_		, keep_accents=lowerCamelCase_		, bos_token=lowerCamelCase_		, eos_token=lowerCamelCase_		, unk_token=lowerCamelCase_		, sep_token=lowerCamelCase_		, pad_token=lowerCamelCase_		, cls_token=lowerCamelCase_		, mask_token=lowerCamelCase_		, additional_special_tokens=lowerCamelCase_		, sp_model_kwargs=self.sp_model_kwargs		, **lowerCamelCase_		, )

			SCREAMING_SNAKE_CASE       :     Union[str, Any]				= 3

			SCREAMING_SNAKE_CASE       :     List[str]				= do_lower_case
			SCREAMING_SNAKE_CASE       :     int				= remove_space
			SCREAMING_SNAKE_CASE       :     Tuple				= keep_accents
			SCREAMING_SNAKE_CASE       :     Tuple				= vocab_file

			SCREAMING_SNAKE_CASE       :     List[str]				= spm.SentencePieceProcessor(**self.sp_model_kwargs					)
			self.sp_model.Load(lowerCamelCase_					)

			try:
					import jieba
			except ModuleNotFoundError as error:
					raise error.__class__(
					    '''You need to install jieba to use CpmTokenizer or CpmTokenizerFast. '''
					    '''See https://pypi.org/project/jieba/ for installation.'''					)
			SCREAMING_SNAKE_CASE       :     List[str]				= jieba
			SCREAMING_SNAKE_CASE       :     Any				= str.maketrans(''' \n'''		, '''\u2582\u2583'''					)





	@property
	# Copied from transformers.models.xlnet.tokenization_xlnet.XLNetTokenizer.vocab_size
	def   __lowerCAmelCase (						self    :Dict					)							->			Union[str, Any]:







			'''simple docstring'''




			return len(self.sp_model					)





	def   __lowerCAmelCase (						self    :str					)							->			Optional[Any]:







			'''simple docstring'''




			SCREAMING_SNAKE_CASE       :     List[Any]				= {self.convert_ids_to_tokens(lowerCamelCase_					): i for i in range(self.vocab_size					)}
			vocab.update(self.added_tokens_encoder					)
			return vocab





	def __getstate__(						self    :Dict					)							->			List[Any]:







			'''simple docstring'''




			SCREAMING_SNAKE_CASE       :     str				= self.__dict__.copy()
			SCREAMING_SNAKE_CASE       :     Optional[Any]				= None
			return state





	def __setstate__(						self    :Any		, lowerCamelCase_    :Dict					)							->			Optional[Any]:







			'''simple docstring'''




			SCREAMING_SNAKE_CASE       :     List[Any]				= d

			# for backward compatibility
			if not hasattr(self		, '''sp_model_kwargs'''					):
					SCREAMING_SNAKE_CASE       :     str				= {}

			SCREAMING_SNAKE_CASE       :     str				= spm.SentencePieceProcessor(**self.sp_model_kwargs					)
			self.sp_model.Load(self.vocab_file					)





	def   __lowerCAmelCase (						self    :Dict		, lowerCamelCase_    :Dict					)							->			Optional[int]:







			'''simple docstring'''




			if self.remove_space:
					SCREAMING_SNAKE_CASE       :     Optional[int]				= ''' '''.join(inputs.strip().split()					)
			else:
					SCREAMING_SNAKE_CASE       :     List[str]				= inputs
			SCREAMING_SNAKE_CASE       :     List[str]				= outputs.replace('''``'''		, '''"'''					).replace('''\'\''''		, '''"'''					)

			if not self.keep_accents:
					SCREAMING_SNAKE_CASE       :     Union[str, Any]				= unicodedata.normalize('''NFKD'''		, lowerCamelCase_					)
					SCREAMING_SNAKE_CASE       :     Dict				= ''''''.join([c for c in outputs if not unicodedata.combining(lowerCamelCase_					)]					)
			if self.do_lower_case:
					SCREAMING_SNAKE_CASE       :     List[str]				= outputs.lower()

			return outputs





	def   __lowerCAmelCase (						self    :Tuple		, lowerCamelCase_    :str					)							->			List[str]:







			'''simple docstring'''




			SCREAMING_SNAKE_CASE       :     Optional[int]				= self.preprocess_text(lowerCamelCase_					)
			SCREAMING_SNAKE_CASE       :     Optional[Any]				= self.sp_model.encode(lowerCamelCase_		, out_type=lowerCamelCase_					)
			SCREAMING_SNAKE_CASE       :     str				= []
			for piece in pieces:
					if len(lowerCamelCase_					) > 1 and piece[-1] == str(''','''					) and piece[-2].isdigit():
							SCREAMING_SNAKE_CASE       :     int				= self.sp_model.EncodeAsPieces(piece[:-1].replace(lowerCamelCase_		, ''''''					)					)
							if piece[0] != SPIECE_UNDERLINE and cur_pieces[0][0] == SPIECE_UNDERLINE:
									if len(cur_pieces[0]					) == 1:
											SCREAMING_SNAKE_CASE       :     List[str]				= cur_pieces[1:]
									else:
											SCREAMING_SNAKE_CASE       :     int				= cur_pieces[0][1:]
							cur_pieces.append(piece[-1]					)
							new_pieces.extend(lowerCamelCase_					)
					else:
							new_pieces.append(lowerCamelCase_					)

			return new_pieces





	def   __lowerCAmelCase (						self    :Optional[int]		, lowerCamelCase_    :Optional[Any]					)							->			List[Any]:







			'''simple docstring'''




			return self.sp_model.PieceToId(lowerCamelCase_					)





	def   __lowerCAmelCase (						self    :Tuple		, lowerCamelCase_    :str					)							->			Optional[Any]:







			'''simple docstring'''




			return self.sp_model.IdToPiece(lowerCamelCase_					)





	def   __lowerCAmelCase (						self    :Any		, lowerCamelCase_    :Union[str, Any]					)							->			Optional[int]:







			'''simple docstring'''




			SCREAMING_SNAKE_CASE       :     str				= ''''''.join(lowerCamelCase_					).replace(lowerCamelCase_		, ''' '''					).strip()
			return out_string





	def   __lowerCAmelCase (						self    :List[str]		, lowerCamelCase_    :List[int]		, lowerCamelCase_    :Optional[List[int]] = None					)							->			List[int]:







			'''simple docstring'''




			SCREAMING_SNAKE_CASE       :     Any				= [self.sep_token_id]
			SCREAMING_SNAKE_CASE       :     Tuple				= [self.cls_token_id]
			if token_ids_a is None:
					return token_ids_a + sep + cls
			return token_ids_a + sep + token_ids_a + sep + cls





	def   __lowerCAmelCase (						self    :Optional[Any]		, lowerCamelCase_    :List[int]		, lowerCamelCase_    :Optional[List[int]] = None		, lowerCamelCase_    :bool = False					)							->			List[int]:







			'''simple docstring'''




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

			if token_ids_a is not None:
					return ([0] * len(lowerCamelCase_					)) + [1] + ([0] * len(lowerCamelCase_					)) + [1, 1]
			return ([0] * len(lowerCamelCase_					)) + [1, 1]





	def   __lowerCAmelCase (						self    :Union[str, Any]		, lowerCamelCase_    :List[int]		, lowerCamelCase_    :Optional[List[int]] = None					)							->			List[int]:







			'''simple docstring'''




			SCREAMING_SNAKE_CASE       :     str				= [self.sep_token_id]
			SCREAMING_SNAKE_CASE       :     Union[str, Any]				= [2]

			if token_ids_a is None:
					return len(token_ids_a + sep					) * [0] + cls_segment_id
			return len(token_ids_a + sep					) * [0] + len(token_ids_a + sep					) * [1] + cls_segment_id





	def   __lowerCAmelCase (						self    :Union[str, Any]		, lowerCamelCase_    :str		, lowerCamelCase_    :Optional[str] = None					)							->			Tuple[str]:







			'''simple docstring'''




			if not os.path.isdir(lowerCamelCase_					):
					logger.error(f"Vocabulary path ({save_directory}) should be a directory"					)
					return
			SCREAMING_SNAKE_CASE       :     Dict				= os.path.join(
			    lowerCamelCase_		, (filename_prefix + '''-''' if filename_prefix else '''''') + VOCAB_FILES_NAMES['''vocab_file''']					)

			if os.path.abspath(self.vocab_file					) != os.path.abspath(lowerCamelCase_					) and os.path.isfile(self.vocab_file					):
					copyfile(self.vocab_file		, lowerCamelCase_					)
			elif not os.path.isfile(self.vocab_file					):
					with open(lowerCamelCase_		, '''wb'''					) as fi:
							SCREAMING_SNAKE_CASE       :     Union[str, Any]				= self.sp_model.serialized_model_proto()
							fi.write(lowerCamelCase_					)

			return (out_vocab_file,)







	def   __lowerCAmelCase (						self    :Optional[int]		, *lowerCamelCase_    :str		, **lowerCamelCase_    :Dict					)							->			List[str]:







			'''simple docstring'''




			SCREAMING_SNAKE_CASE       :     Dict				= super()._decode(*lowerCamelCase_		, **lowerCamelCase_					)
			SCREAMING_SNAKE_CASE       :     List[Any]				= text.replace(''' '''		, ''''''					).replace('''\u2582'''		, ''' '''					).replace('''\u2583'''		, '''\n'''					)
			return text







"""simple docstring"""






import math
from typing import Optional

import numpy as np

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


lowerCamelCase__ :       Tuple						     =			logging.get_logger(__name__)

lowerCamelCase__ :       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__(				_UpperCAmelCase   ):
	'''simple docstring'''

	UpperCamelCase				=  """encodec"""





	def __init__(						self    :List[str]		, lowerCamelCase_    :Tuple=[1.5, 3.0, 6.0, 1_2.0, 2_4.0]		, lowerCamelCase_    :str=2_40_00		, lowerCamelCase_    :Any=1		, lowerCamelCase_    :List[Any]=False		, lowerCamelCase_    :Optional[int]=None		, lowerCamelCase_    :Optional[Any]=None		, lowerCamelCase_    :str=1_28		, lowerCamelCase_    :Any=32		, lowerCamelCase_    :int=1		, lowerCamelCase_    :Dict=[8, 5, 4, 2]		, lowerCamelCase_    :List[Any]="weight_norm"		, lowerCamelCase_    :Optional[int]=7		, lowerCamelCase_    :Tuple=7		, lowerCamelCase_    :Optional[Any]=3		, lowerCamelCase_    :int=2		, lowerCamelCase_    :Dict=True		, lowerCamelCase_    :Optional[int]="reflect"		, lowerCamelCase_    :Optional[int]=2		, lowerCamelCase_    :Union[str, Any]=2		, lowerCamelCase_    :Dict=1.0		, lowerCamelCase_    :Any=10_24		, lowerCamelCase_    :str=None		, lowerCamelCase_    :Union[str, Any]=True		, **lowerCamelCase_    :Optional[int]		, )							->			Dict:







			'''simple docstring'''




			SCREAMING_SNAKE_CASE       :     Optional[Any]				= target_bandwidths
			SCREAMING_SNAKE_CASE       :     List[str]				= sampling_rate
			SCREAMING_SNAKE_CASE       :     Tuple				= audio_channels
			SCREAMING_SNAKE_CASE       :     Tuple				= normalize
			SCREAMING_SNAKE_CASE       :     str				= chunk_length_s
			SCREAMING_SNAKE_CASE       :     List[str]				= overlap
			SCREAMING_SNAKE_CASE       :     int				= hidden_size
			SCREAMING_SNAKE_CASE       :     Optional[int]				= num_filters
			SCREAMING_SNAKE_CASE       :     Tuple				= num_residual_layers
			SCREAMING_SNAKE_CASE       :     List[Any]				= upsampling_ratios
			SCREAMING_SNAKE_CASE       :     Optional[int]				= norm_type
			SCREAMING_SNAKE_CASE       :     Any				= kernel_size
			SCREAMING_SNAKE_CASE       :     Union[str, Any]				= last_kernel_size
			SCREAMING_SNAKE_CASE       :     Tuple				= residual_kernel_size
			SCREAMING_SNAKE_CASE       :     Any				= dilation_growth_rate
			SCREAMING_SNAKE_CASE       :     Optional[int]				= use_causal_conv
			SCREAMING_SNAKE_CASE       :     str				= pad_mode
			SCREAMING_SNAKE_CASE       :     List[Any]				= compress
			SCREAMING_SNAKE_CASE       :     Optional[Any]				= num_lstm_layers
			SCREAMING_SNAKE_CASE       :     Dict				= trim_right_ratio
			SCREAMING_SNAKE_CASE       :     List[Any]				= codebook_size
			SCREAMING_SNAKE_CASE       :     Union[str, Any]				= codebook_dim if codebook_dim is not None else hidden_size
			SCREAMING_SNAKE_CASE       :     Union[str, Any]				= 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   __lowerCAmelCase (						self    :Optional[Any]					)							->			Optional[int]:







			'''simple docstring'''




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





	@property
	def   __lowerCAmelCase (						self    :List[str]					)							->			Optional[int]:







			'''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   __lowerCAmelCase (						self    :Dict					)							->			int:







			'''simple docstring'''




			SCREAMING_SNAKE_CASE       :     Tuple				= np.prod(self.upsampling_ratios					)
			return math.ceil(self.sampling_rate / hop_length					)







	@property
	def   __lowerCAmelCase (						self    :Dict					)							->			int:







			'''simple docstring'''




			return int(10_00 * self.target_bandwidths[-1] // (self.frame_rate * 10)					)





