


"""simple docstring"""


import numpy as np  # noqa: E402

from ...configuration_utils import ConfigMixin, register_to_config
from ...schedulers.scheduling_utils import SchedulerMixin


try:
		import librosa  # noqa: E402

		a_											=			True
		a_											=			""
except Exception as e:
		a_											=			False
		a_											=			(
		    f'''Cannot import librosa because {e}. Make sure to correctly install librosa to be able to install it.'''
		)


from PIL import Image  # noqa: E402
class snake_case					(     _UpperCamelCase   , _UpperCamelCase):
		__UpperCamelCase							=	'mel_config.json'







		@register_to_config
		def __init__(    self					:				int			,      a__					:				int = 2_56			,      a__					:				int = 2_56			,      a__					:				int = 2_20_50			,      a__					:				int = 20_48			,      a__					:				int = 5_12			,      a__					:				int = 80			,      a__					:				int = 32			,      )				->  Tuple:





						'''simple docstring'''







						_A         =	hop_length
						_A         =	sample_rate
						_A         =	n_fft
						_A         =	top_db
						_A         =	n_iter
						self.set_resolution(a__			,      a__						)
						_A         =	None

						if not _librosa_can_be_imported:
										raise ValueError(_import_error						)







		def        a_       (    self					:				List[str]			,      a__					:				int			,      a__					:				int						)				->  List[str]:





						'''simple docstring'''







						_A         =	x_res
						_A         =	y_res
						_A         =	self.y_res
						_A         =	self.x_res * self.hop_length - 1







		def        a_       (    self					:				str			,      a__					:				str = None			,      a__					:				np.ndarray = None						)				->  List[Any]:





						'''simple docstring'''







						if audio_file is not None:
										_A     ,						_A         =	librosa.load(a__			,      mono=a__			,      sr=self.sr						)
						else:
										_A         =	raw_audio

						# Pad with silence if necessary.
						if len(self.audio						) < self.x_res * self.hop_length:
										_A         =	np.concatenate([self.audio, np.zeros((self.x_res * self.hop_length - len(self.audio						),)						)]						)







		def        a_       (    self					:				List[str]						)				->  int:





						'''simple docstring'''







						return len(self.audio						) // self.slice_size







		def        a_       (    self					:				Tuple			,      a__					:				int = 0						)				->  np.ndarray:





						'''simple docstring'''







						return self.audio[self.slice_size * slice : self.slice_size * (slice + 1)]







		def        a_       (    self					:				Tuple						)				->  int:





						'''simple docstring'''







						return self.sr







		def        a_       (    self					:				Tuple			,      a__					:				int						)				->  Image.Image:





						'''simple docstring'''







						_A         =	librosa.feature.melspectrogram(
						    y=self.get_audio_slice(a__						)			,      sr=self.sr			,      n_fft=self.n_fft			,      hop_length=self.hop_length			,      n_mels=self.n_mels						)
						_A         =	librosa.power_to_db(a__			,      ref=np.max			,      top_db=self.top_db						)
						_A         =	(((log_S + self.top_db) * 2_55 / self.top_db).clip(0			,      2_55						) + 0.5).astype(np.uinta						)
						_A         =	Image.fromarray(a__						)
						return image







		def        a_       (    self					:				Optional[Any]			,      a__					:				Image.Image						)				->  np.ndarray:





						'''simple docstring'''







						_A         =	np.frombuffer(image.tobytes()			,      dtype="uint8"						).reshape((image.height, image.width)						)
						_A         =	bytedata.astype("float"						) * self.top_db / 2_55 - self.top_db
						_A         =	librosa.db_to_power(a__						)
						_A         =	librosa.feature.inverse.mel_to_audio(
						    a__			,      sr=self.sr			,      n_fft=self.n_fft			,      hop_length=self.hop_length			,      n_iter=self.n_iter						)
						return audio

"""simple docstring"""




import os
from shutil import copyfile
from typing import List, Optional, Tuple

from ...tokenization_utils_fast import AddedToken, PreTrainedTokenizerFast
from ...utils import logging


snake_case    =		logging.get_logger(__name__)

snake_case    =		{'vocab_file': 'spiece.model', 'tokenizer_file': 'tokenizer.json'}

snake_case    =		{
    'vocab_file': {
        'TsinghuaAI/CPM-Generate': 'https://huggingface.co/TsinghuaAI/CPM-Generate/resolve/main/spiece.model',
    },
    'tokenizer_file': {
        'TsinghuaAI/CPM-Generate': 'https://huggingface.co/TsinghuaAI/CPM-Generate/resolve/main/tokenizer.json',
    },
}




class      UpperCamelCase	(       __magic_name__      ):

				"""simple docstring"""



				def __init__(				self		,	lowercase__=None		,	lowercase__=None		,	lowercase__=False		,	lowercase__=True		,	lowercase__=False		,	lowercase__="<s>"		,	lowercase__="</s>"		,	lowercase__="<unk>"		,	lowercase__="<sep>"		,	lowercase__="<pad>"		,	lowercase__="<cls>"		,	lowercase__="<mask>"		,	lowercase__=["<eop>", "<eod>"]		,	**lowercase__		,	)    ->    int:
									"""simple docstring"""







									SCREAMING_SNAKE_CASE				=	AddedToken(lowercase__		,	lstrip=lowercase__		,	rstrip=lowercase__			) if isinstance(lowercase__		,	lowercase__			) else mask_token

									super().__init__(
									    vocab_file=lowercase__		,	tokenizer_file=lowercase__		,	do_lower_case=lowercase__		,	remove_space=lowercase__		,	keep_accents=lowercase__		,	bos_token=lowercase__		,	eos_token=lowercase__		,	unk_token=lowercase__		,	sep_token=lowercase__		,	pad_token=lowercase__		,	cls_token=lowercase__		,	mask_token=lowercase__		,	additional_special_tokens=lowercase__		,	**lowercase__		,	)

									SCREAMING_SNAKE_CASE				=	3
									SCREAMING_SNAKE_CASE				=	do_lower_case
									SCREAMING_SNAKE_CASE				=	remove_space
									SCREAMING_SNAKE_CASE				=	keep_accents
									SCREAMING_SNAKE_CASE				=	vocab_file
									SCREAMING_SNAKE_CASE				=	False if not self.vocab_file else True

									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				=	jieba
									SCREAMING_SNAKE_CASE				=	str.maketrans(' \n'		,	'\u2582\u2583'			)


				def 							A					(				self		,	lowercase__		,	lowercase__ = None			)    ->    List[int]:
									"""simple docstring"""







									SCREAMING_SNAKE_CASE				=	[self.sep_token_id]
									SCREAMING_SNAKE_CASE				=	[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 							A					(				self		,	lowercase__		,	lowercase__ = None			)    ->    List[int]:
									"""simple docstring"""







									SCREAMING_SNAKE_CASE				=	[self.sep_token_id]
									SCREAMING_SNAKE_CASE				=	[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 							A					(				self		,	lowercase__		,	lowercase__ = None			)    ->    Tuple[str]:
									"""simple docstring"""







									if not self.can_save_slow_tokenizer:
														raise ValueError(
														    'Your fast tokenizer does not have the necessary information to save the vocabulary for a slow '
														    'tokenizer.'			)

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

									if os.path.abspath(self.vocab_file			) != os.path.abspath(lowercase__			):
														copyfile(self.vocab_file		,	lowercase__			)

									return (out_vocab_file,)


				def 							A					(				self		,	lowercase__		,	*lowercase__		,	**lowercase__			)    ->    Any:
									"""simple docstring"""







									SCREAMING_SNAKE_CASE				=	[
									    ' '.join([x.translate(self.translator			) for x in self.jieba.cut(lowercase__		,	cut_all=lowercase__			)]			)
									    for text in batch_text_or_text_pairs
									]
									return super()._batch_encode_plus(lowercase__		,	*lowercase__		,	**lowercase__			)




				def 							A					(				self		,	*lowercase__		,	**lowercase__			)    ->    Optional[int]:
									"""simple docstring"""







									SCREAMING_SNAKE_CASE				=	super()._decode(*lowercase__		,	**lowercase__			)
									SCREAMING_SNAKE_CASE				=	text.replace(' '		,	''			).replace('\u2582'		,	' '			).replace('\u2583'		,	'\n'			)
									return text
