



'''simple docstring'''





from ...processing_utils import ProcessorMixin

class   _A   ( _lowercase	):


						'''simple docstring'''





						_snake_case			:     int      							=      """WhisperFeatureExtractor"""
						_snake_case			:     Tuple      							=      """WhisperTokenizer"""



						def __init__(	self	:							Union[str, Any]							,      lowerCamelCase	:							int							,      lowerCamelCase	:							List[str]	):






							'''simple docstring'''



							super().__init__(lowerCamelCase							,      lowerCamelCase	)
							__lowercase		       =			self.feature_extractor
							__lowercase		       =			False



						def     _snake_case	(	self	:							Union[str, Any]							,      lowerCamelCase	:							List[Any]=None							,      lowerCamelCase	:							Any=None							,      lowerCamelCase	:							Any=True	):






							'''simple docstring'''



							return self.tokenizer.get_decoder_prompt_ids(task=lowerCamelCase							,      language=lowerCamelCase							,      no_timestamps=lowerCamelCase	)



						def __call__(	self	:							str							,      *lowerCamelCase	:							Union[str, Any]							,      **lowerCamelCase	:							Optional[int]	):






							'''simple docstring'''



							if self._in_target_context_manager:
								return self.current_processor(*lowerCamelCase							,      **lowerCamelCase	)

							__lowercase		       =			kwargs.pop("audio"							,      lowerCamelCase	)
							__lowercase		       =			kwargs.pop("sampling_rate"							,      lowerCamelCase	)
							__lowercase		       =			kwargs.pop("text"							,      lowerCamelCase	)
							if len(lowerCamelCase	) > 0:
								__lowercase		       =			args[0]
								__lowercase		       =			args[1:]

							if audio is None and text is None:
								raise ValueError("You need to specify either an `audio` or `text` input to process."	)

							if audio is not None:
								__lowercase		       =			self.feature_extractor(lowerCamelCase							,      *lowerCamelCase							,      sampling_rate=lowerCamelCase							,      **lowerCamelCase	)
							if text is not None:
								__lowercase		       =			self.tokenizer(lowerCamelCase							,      **lowerCamelCase	)

							if text is None:
								return inputs

							elif audio is None:
								return encodings
							else:
								__lowercase		       =			encodings["input_ids"]
								return inputs



						def     _snake_case	(	self	:							Union[str, Any]							,      *lowerCamelCase	:							Optional[int]							,      **lowerCamelCase	:							Optional[int]	):






							'''simple docstring'''



							return self.tokenizer.batch_decode(*lowerCamelCase							,      **lowerCamelCase	)



						def     _snake_case	(	self	:							Any							,      *lowerCamelCase	:							List[str]							,      **lowerCamelCase	:							List[str]	):






							'''simple docstring'''



							return self.tokenizer.decode(*lowerCamelCase							,      **lowerCamelCase	)



						def     _snake_case	(	self	:							Union[str, Any]							,      lowerCamelCase	:							str							,      lowerCamelCase	:							List[Any]="np"	):






							'''simple docstring'''



							return self.tokenizer.get_prompt_ids(lowerCamelCase							,      return_tensors=lowerCamelCase	)








import json
import os
from functools import lru_cache
from typing import Dict, List, Optional, Tuple, Union

import regex as re

from ...tokenization_utils import AddedToken, PreTrainedTokenizer
from ...tokenization_utils_base import BatchEncoding, EncodedInput
from ...utils import PaddingStrategy, logging


snake_case__					:     List[str]    		=   logging.get_logger(__name__)


snake_case__					:     Optional[Any]    		=   {"""vocab_file""": """vocab.json""", """merges_file""": """merges.txt"""}

# See all LED models at https://huggingface.co/models?filter=LED
snake_case__					:     Optional[Any]    		=   {
    """vocab_file""": {
        """allenai/led-base-16384""": """https://huggingface.co/allenai/led-base-16384/resolve/main/vocab.json""",
    },
    """merges_file""": {
        """allenai/led-base-16384""": """https://huggingface.co/allenai/led-base-16384/resolve/main/merges.txt""",
    },
    """tokenizer_file""": {
        """allenai/led-base-16384""": """https://huggingface.co/allenai/led-base-16384/resolve/main/tokenizer.json""",
    },
}

snake_case__					:     List[str]    		=   {
    """allenai/led-base-16384""": 1_63_84,
}



@lru_cache()
# Copied from transformers.models.bart.tokenization_bart.bytes_to_unicode
def    snake_case_				(    ):
	__lowercase		       =			(
	    list(range(ord("!"   )  ,	ord("~"   ) + 1   )   ) + list(range(ord("¡"   )  ,	ord("¬"   ) + 1   )   ) + list(range(ord("®"   )  ,	ord("ÿ"   ) + 1   )   )
	)
	__lowercase		       =			bs[:]
	__lowercase		       =			0
	for b in range(2**8   ):
		if b not in bs:
			bs.append(_SCREAMING_SNAKE_CASE   )
			cs.append(2**8 + n   )
			n += 1
	__lowercase		       =			[chr(_SCREAMING_SNAKE_CASE   ) for n in cs]
	return dict(zip(_SCREAMING_SNAKE_CASE  ,	_SCREAMING_SNAKE_CASE   )   )



def    snake_case_				(    _SCREAMING_SNAKE_CASE   ):
	__lowercase		       =			set()
	__lowercase		       =			word[0]
	for char in word[1:]:
		pairs.add((prev_char, char)   )
		__lowercase		       =			char
	return pairs

class   _A   ( _lowercase	):


						'''simple docstring'''





						_snake_case			:     List[str]      							=      VOCAB_FILES_NAMES
						_snake_case			:     Union[str, Any]      							=      PRETRAINED_VOCAB_FILES_MAP
						_snake_case			:     Dict      							=      PRETRAINED_POSITIONAL_EMBEDDINGS_SIZES
						_snake_case			:     Union[str, Any]      							=      ["""input_ids""", """attention_mask"""]



						def __init__(	self	:							List[str]							,      lowerCamelCase	:							Tuple							,      lowerCamelCase	:							Tuple							,      lowerCamelCase	:							Optional[int]="replace"							,      lowerCamelCase	:							Dict="<s>"							,      lowerCamelCase	:							Dict="</s>"							,      lowerCamelCase	:							Optional[Any]="</s>"							,      lowerCamelCase	:							Any="<s>"							,      lowerCamelCase	:							List[str]="<unk>"							,      lowerCamelCase	:							Union[str, Any]="<pad>"							,      lowerCamelCase	:							Any="<mask>"							,      lowerCamelCase	:							str=False							,      **lowerCamelCase	:							Optional[Any]							,      ):






							'''simple docstring'''



							__lowercase		       =			AddedToken(lowerCamelCase							,      lstrip=lowerCamelCase							,      rstrip=lowerCamelCase	) if isinstance(lowerCamelCase							,      lowerCamelCase	) else bos_token
							__lowercase		       =			AddedToken(lowerCamelCase							,      lstrip=lowerCamelCase							,      rstrip=lowerCamelCase	) if isinstance(lowerCamelCase							,      lowerCamelCase	) else eos_token
							__lowercase		       =			AddedToken(lowerCamelCase							,      lstrip=lowerCamelCase							,      rstrip=lowerCamelCase	) if isinstance(lowerCamelCase							,      lowerCamelCase	) else sep_token
							__lowercase		       =			AddedToken(lowerCamelCase							,      lstrip=lowerCamelCase							,      rstrip=lowerCamelCase	) if isinstance(lowerCamelCase							,      lowerCamelCase	) else cls_token
							__lowercase		       =			AddedToken(lowerCamelCase							,      lstrip=lowerCamelCase							,      rstrip=lowerCamelCase	) if isinstance(lowerCamelCase							,      lowerCamelCase	) else unk_token
							__lowercase		       =			AddedToken(lowerCamelCase							,      lstrip=lowerCamelCase							,      rstrip=lowerCamelCase	) if isinstance(lowerCamelCase							,      lowerCamelCase	) else pad_token

							# Mask token behave like a normal word, i.e. include the space before it
							__lowercase		       =			AddedToken(lowerCamelCase							,      lstrip=lowerCamelCase							,      rstrip=lowerCamelCase	) if isinstance(lowerCamelCase							,      lowerCamelCase	) else mask_token

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

							with open(lowerCamelCase							,      encoding="utf-8"	) as vocab_handle:
								__lowercase		       =			json.load(lowerCamelCase	)
							__lowercase		       =			{v: k for k, v in self.encoder.items()}
							__lowercase		       =			errors  # how to handle errors in decoding
							__lowercase		       =			bytes_to_unicode()
							__lowercase		       =			{v: k for k, v in self.byte_encoder.items()}
							with open(lowerCamelCase							,      encoding="utf-8"	) as merges_handle:
								__lowercase		       =			merges_handle.read().split("\n"	)[1:-1]
							__lowercase		       =			[tuple(merge.split()	) for merge in bpe_merges]
							__lowercase		       =			dict(zip(lowerCamelCase							,      range(len(lowerCamelCase	)	)	)	)
							__lowercase		       =			{}
							__lowercase		       =			add_prefix_space

							# Should have added re.IGNORECASE so BPE merges can happen for capitalized versions of contractions
							__lowercase		       =			re.compile(R"'s|'t|'re|'ve|'m|'ll|'d| ?\p{L}+| ?\p{N}+| ?[^\s\p{L}\p{N}]+|\s+(?!\S)|\s+"	)



						@property
						# Copied from transformers.models.bart.tokenization_bart.BartTokenizer.vocab_size
						def     _snake_case	(	self	:							Optional[int]	):






							'''simple docstring'''



							return len(self.encoder	)



						def     _snake_case	(	self	:							Optional[int]	):






							'''simple docstring'''



							return dict(self.encoder							,      **self.added_tokens_encoder	)



						def     _snake_case	(	self	:							List[Any]							,      lowerCamelCase	:							str	):






							'''simple docstring'''



							if token in self.cache:
								return self.cache[token]
							__lowercase		       =			tuple(lowerCamelCase	)
							__lowercase		       =			get_pairs(lowerCamelCase	)

							if not pairs:
								return token

							while True:
								__lowercase		       =			min(lowerCamelCase							,      key=lambda lowerCamelCase	: self.bpe_ranks.get(lowerCamelCase							,      float("inf"	)	)	)
								if bigram not in self.bpe_ranks:
									break
								__lowercase       ,    __lowercase		       =			bigram
								__lowercase		       =			[]
								__lowercase		       =			0
								while i < len(lowerCamelCase	):
									try:
										__lowercase		       =			word.index(lowerCamelCase							,      lowerCamelCase	)
									except ValueError:
										new_word.extend(word[i:]	)
										break
									else:
										new_word.extend(word[i:j]	)
										__lowercase		       =			j

									if word[i] == first and i < len(lowerCamelCase	) - 1 and word[i + 1] == second:
										new_word.append(first + second	)
										i += 2
									else:
										new_word.append(word[i]	)
										i += 1
								__lowercase		       =			tuple(lowerCamelCase	)
								__lowercase		       =			new_word
								if len(lowerCamelCase	) == 1:
									break
								else:
									__lowercase		       =			get_pairs(lowerCamelCase	)
							__lowercase		       =			" ".join(lowerCamelCase	)
							__lowercase		       =			word
							return word



						def     _snake_case	(	self	:							List[Any]							,      lowerCamelCase	:							Tuple	):






							'''simple docstring'''



							__lowercase		       =			[]
							for token in re.findall(self.pat							,      lowerCamelCase	):
								__lowercase		       =			"".join(
								    self.byte_encoder[b] for b in token.encode("utf-8"	)	)  # Maps all our bytes to unicode strings, avoiding control tokens of the BPE (spaces in our case)
								bpe_tokens.extend(bpe_token for bpe_token in self.bpe(lowerCamelCase	).split(" "	)	)
							return bpe_tokens



						def     _snake_case	(	self	:							Dict							,      lowerCamelCase	:							Optional[int]	):






							'''simple docstring'''



							return self.encoder.get(lowerCamelCase							,      self.encoder.get(self.unk_token	)	)



						def     _snake_case	(	self	:							str							,      lowerCamelCase	:							Optional[Any]	):






							'''simple docstring'''



							return self.decoder.get(lowerCamelCase	)



						def     _snake_case	(	self	:							Union[str, Any]							,      lowerCamelCase	:							int	):






							'''simple docstring'''



							__lowercase		       =			"".join(lowerCamelCase	)
							__lowercase		       =			bytearray([self.byte_decoder[c] for c in text]	).decode("utf-8"							,      errors=self.errors	)
							return text



						def     _snake_case	(	self	:							Optional[Any]							,      lowerCamelCase	:							str							,      lowerCamelCase	:							Optional[str] = None	):






							'''simple docstring'''



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

							with open(lowerCamelCase							,      "w"							,      encoding="utf-8"	) as f:
								f.write(json.dumps(self.encoder							,      indent=2							,      sort_keys=lowerCamelCase							,      ensure_ascii=lowerCamelCase	) + "\n"	)

							__lowercase		       =			0
							with open(lowerCamelCase							,      "w"							,      encoding="utf-8"	) as writer:
								writer.write("#version: 0.2\n"	)
								for bpe_tokens, token_index in sorted(self.bpe_ranks.items()							,      key=lambda lowerCamelCase	: kv[1]	):
									if index != token_index:
										logger.warning(
										    f"""Saving vocabulary to {merge_file}: BPE merge indices are not consecutive."""
										    " Please check that the tokenizer is not corrupted!"	)
										__lowercase		       =			token_index
									writer.write(" ".join(lowerCamelCase	) + "\n"	)
									index += 1

							return vocab_file, merge_file



						def     _snake_case	(	self	:							Tuple							,      lowerCamelCase	:							List[int]							,      lowerCamelCase	:							Optional[List[int]] = None	):






							'''simple docstring'''



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



						def     _snake_case	(	self	:							str							,      lowerCamelCase	:							List[int]							,      lowerCamelCase	:							Optional[List[int]] = None							,      lowerCamelCase	:							bool = False	):






							'''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 None:
								return [1] + ([0] * len(lowerCamelCase	)) + [1]
							return [1] + ([0] * len(lowerCamelCase	)) + [1, 1] + ([0] * len(lowerCamelCase	)) + [1]



						def     _snake_case	(	self	:							int							,      lowerCamelCase	:							List[int]							,      lowerCamelCase	:							Optional[List[int]] = None	):






							'''simple docstring'''



							__lowercase		       =			[self.sep_token_id]
							__lowercase		       =			[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]



						def     _snake_case	(	self	:							Dict							,      lowerCamelCase	:							Any							,      lowerCamelCase	:							Tuple=False							,      **lowerCamelCase	:							Any	):






							'''simple docstring'''



							__lowercase		       =			kwargs.pop("add_prefix_space"							,      self.add_prefix_space	)
							if (is_split_into_words or add_prefix_space) and (len(lowerCamelCase	) > 0 and not text[0].isspace()):
								__lowercase		       =			" " + text
							return (text, kwargs)



						def     _snake_case	(	self	:							List[Any]							,      lowerCamelCase	:							Union[Dict[str, EncodedInput], BatchEncoding]							,      lowerCamelCase	:							Optional[int] = None							,      lowerCamelCase	:							PaddingStrategy = PaddingStrategy.DO_NOT_PAD							,      lowerCamelCase	:							Optional[int] = None							,      lowerCamelCase	:							Optional[bool] = None							,      ):






							'''simple docstring'''



							__lowercase		       =			super()._pad(
							    encoded_inputs=lowerCamelCase							,      max_length=lowerCamelCase							,      padding_strategy=lowerCamelCase							,      pad_to_multiple_of=lowerCamelCase							,      return_attention_mask=lowerCamelCase							,      )

							# Load from model defaults
							if return_attention_mask is None:
								__lowercase		       =			"attention_mask" in self.model_input_names

							if return_attention_mask and "global_attention_mask" in encoded_inputs:
								__lowercase		       =			encoded_inputs[self.model_input_names[0]]
								# `global_attention_mask` need to have the same length as other (sequential) inputs.
								__lowercase		       =			len(encoded_inputs["global_attention_mask"]	) != len(lowerCamelCase	)

								if needs_to_be_padded:
									__lowercase		       =			len(lowerCamelCase	) - len(encoded_inputs["global_attention_mask"]	)

									if self.padding_side == "right":
										# Use `-1` since `0` in `global_attention_mask` means `local attention` instead of `not to attend`
										__lowercase		       =			(
										    encoded_inputs["global_attention_mask"] + [-1] * difference
										)
									elif self.padding_side == "left":
										__lowercase		       =			[-1] * difference + encoded_inputs[
										    "global_attention_mask"
										]
									else:
										raise ValueError("Invalid padding strategy:" + str(self.padding_side	)	)

							return encoded_inputs



