
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


__lowerCAmelCase									=logging.get_logger(__name__)


__lowerCAmelCase									={"vocab_file": "vocab.json", "merges_file": "merges.txt"}

# See all LED models at https://huggingface.co/models?filter=LED
__lowerCAmelCase									={
    "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",
    },
}

__lowerCAmelCase									={
    "allenai/led-base-16384": 16384,
}



@lru_cache()
# Copied from transformers.models.bart.tokenization_bart.bytes_to_unicode
def   __UpperCamelCase						(				):
					"""simple docstring"""





					UpperCAmelCase				   =  (
					    list(range(ord("!" )	,						ord("~" ) + 1 ) ) + list(range(ord("¡" )	,						ord("¬" ) + 1 ) ) + list(range(ord("®" )	,						ord("ÿ" ) + 1 ) )
					)
					UpperCAmelCase				   =  bs[:]
					UpperCAmelCase				   =  0
					for b in range(2**8 ):
										if b not in bs:
															bs.append(_lowerCAmelCase )
															cs.append(2**8 + n )
															n += 1
					UpperCAmelCase				   =  [chr(_lowerCAmelCase ) for n in cs]
					return dict(zip(_lowerCAmelCase	,						_lowerCAmelCase ) )



def   __UpperCamelCase						(				_lowerCAmelCase ):
					"""simple docstring"""





					UpperCAmelCase				   =  set()
					UpperCAmelCase				   =  word[0]
					for char in word[1:]:
										pairs.add((prev_char, char) )
										UpperCAmelCase				   =  char
					return pairs





class  __magic_name__						(     _a):
	_UpperCAmelCase	:			Optional[int]		   =     VOCAB_FILES_NAMES
	_UpperCAmelCase	:			Dict		   =     PRETRAINED_VOCAB_FILES_MAP
	_UpperCAmelCase	:			Tuple		   =     PRETRAINED_POSITIONAL_EMBEDDINGS_SIZES
	_UpperCAmelCase	:			Dict		   =     ['input_ids', 'attention_mask']





	def __init__(		self	: str    ,__SCREAMING_SNAKE_CASE	: Any    ,__SCREAMING_SNAKE_CASE	: Optional[int]    ,__SCREAMING_SNAKE_CASE	: Dict="replace"    ,__SCREAMING_SNAKE_CASE	: Optional[int]="<s>"    ,__SCREAMING_SNAKE_CASE	: List[str]="</s>"    ,__SCREAMING_SNAKE_CASE	: Any="</s>"    ,__SCREAMING_SNAKE_CASE	: Optional[int]="<s>"    ,__SCREAMING_SNAKE_CASE	: str="<unk>"    ,__SCREAMING_SNAKE_CASE	: Optional[int]="<pad>"    ,__SCREAMING_SNAKE_CASE	: Dict="<mask>"    ,__SCREAMING_SNAKE_CASE	: Optional[Any]=False    ,**__SCREAMING_SNAKE_CASE	: Optional[int]    ,):
						UpperCAmelCase				   =  AddedToken(A_    ,lstrip=A_    ,rstrip=A_       ) if isinstance(A_    ,A_       ) else bos_token
						UpperCAmelCase				   =  AddedToken(A_    ,lstrip=A_    ,rstrip=A_       ) if isinstance(A_    ,A_       ) else eos_token
						UpperCAmelCase				   =  AddedToken(A_    ,lstrip=A_    ,rstrip=A_       ) if isinstance(A_    ,A_       ) else sep_token
						UpperCAmelCase				   =  AddedToken(A_    ,lstrip=A_    ,rstrip=A_       ) if isinstance(A_    ,A_       ) else cls_token
						UpperCAmelCase				   =  AddedToken(A_    ,lstrip=A_    ,rstrip=A_       ) if isinstance(A_    ,A_       ) else unk_token
						UpperCAmelCase				   =  AddedToken(A_    ,lstrip=A_    ,rstrip=A_       ) if isinstance(A_    ,A_       ) else pad_token

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

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

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

						# Should have added re.IGNORECASE so BPE merges can happen for capitalized versions of contractions
						UpperCAmelCase				   =  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 	_UpperCAmelCase						(		self	: Any       ):
						return len(self.encoder       )





	def 	_UpperCAmelCase						(		self	: Any       ):
						return dict(self.encoder    ,**self.added_tokens_encoder       )





	def 	_UpperCAmelCase						(		self	: str    ,__SCREAMING_SNAKE_CASE	: Tuple       ):
						if token in self.cache:
											return self.cache[token]
						UpperCAmelCase				   =  tuple(A_       )
						UpperCAmelCase				   =  get_pairs(A_       )

						if not pairs:
											return token

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

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





	def 	_UpperCAmelCase						(		self	: Optional[int]    ,__SCREAMING_SNAKE_CASE	: str       ):
						UpperCAmelCase				   =  []
						for token in re.findall(self.pat    ,A_       ):
											UpperCAmelCase				   =  "".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(A_       ).split(" "       )       )
						return bpe_tokens





	def 	_UpperCAmelCase						(		self	: List[str]    ,__SCREAMING_SNAKE_CASE	: Dict       ):
						return self.encoder.get(A_    ,self.encoder.get(self.unk_token       )       )





	def 	_UpperCAmelCase						(		self	: List[Any]    ,__SCREAMING_SNAKE_CASE	: Any       ):
						return self.decoder.get(A_       )





	def 	_UpperCAmelCase						(		self	: str    ,__SCREAMING_SNAKE_CASE	: List[Any]       ):
						UpperCAmelCase				   =  "".join(A_       )
						UpperCAmelCase				   =  bytearray([self.byte_decoder[c] for c in text]       ).decode("utf-8"    ,errors=self.errors       )
						return text





	def 	_UpperCAmelCase						(		self	: List[str]    ,__SCREAMING_SNAKE_CASE	: Dict    ,__SCREAMING_SNAKE_CASE	: Dict = None       ):
						if not os.path.isdir(A_       ):
											logger.error(f'''Vocabulary path ({save_directory}) should be a directory'''       )
											return
						UpperCAmelCase				   =  os.path.join(
						    A_    ,(filename_prefix + "-" if filename_prefix else "") + VOCAB_FILES_NAMES["vocab_file"]       )
						UpperCAmelCase				   =  os.path.join(
						    A_    ,(filename_prefix + "-" if filename_prefix else "") + VOCAB_FILES_NAMES["merges_file"]       )

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

						UpperCAmelCase				   =  0
						with open(A_    ,"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 __SCREAMING_SNAKE_CASE       : 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!"       )
																					UpperCAmelCase				   =  token_index
																writer.write(" ".join(A_       ) + "\n"       )
																index += 1

						return vocab_file, merge_file





	def 	_UpperCAmelCase						(		self	: Optional[int]    ,__SCREAMING_SNAKE_CASE	: int    ,__SCREAMING_SNAKE_CASE	: List[Any] = None       ):
						if token_ids_a is None:
											return [self.cls_token_id] + token_ids_a + [self.sep_token_id]
						UpperCAmelCase				   =  [self.cls_token_id]
						UpperCAmelCase				   =  [self.sep_token_id]
						return cls + token_ids_a + sep + sep + token_ids_a + sep





	def 	_UpperCAmelCase						(		self	: int    ,__SCREAMING_SNAKE_CASE	: List[str]    ,__SCREAMING_SNAKE_CASE	: str = None    ,__SCREAMING_SNAKE_CASE	: List[str] = False       ):
						if already_has_special_tokens:
											return super().get_special_tokens_mask(
											    token_ids_a=A_    ,token_ids_a=A_    ,already_has_special_tokens=A_       )

						if token_ids_a is None:
											return [1] + ([0] * len(A_       )) + [1]
						return [1] + ([0] * len(A_       )) + [1, 1] + ([0] * len(A_       )) + [1]





	def 	_UpperCAmelCase						(		self	: int    ,__SCREAMING_SNAKE_CASE	: Union[str, Any]    ,__SCREAMING_SNAKE_CASE	: Any = None       ):
						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]





	def 	_UpperCAmelCase						(		self	: Optional[Any]    ,__SCREAMING_SNAKE_CASE	: Tuple    ,__SCREAMING_SNAKE_CASE	: Dict=False    ,**__SCREAMING_SNAKE_CASE	: List[Any]       ):
						UpperCAmelCase				   =  kwargs.pop("add_prefix_space"    ,self.add_prefix_space       )
						if (is_split_into_words or add_prefix_space) and (len(A_       ) > 0 and not text[0].isspace()):
											UpperCAmelCase				   =  " " + text
						return (text, kwargs)





	def 	_UpperCAmelCase						(		self	: Tuple    ,__SCREAMING_SNAKE_CASE	: str    ,__SCREAMING_SNAKE_CASE	: Dict = None    ,__SCREAMING_SNAKE_CASE	: Optional[int] = PaddingStrategy.DO_NOT_PAD    ,__SCREAMING_SNAKE_CASE	: Dict = None    ,__SCREAMING_SNAKE_CASE	: List[Any] = None    ,):
						UpperCAmelCase				   =  super()._pad(
						    encoded_inputs=A_    ,max_length=A_    ,padding_strategy=A_    ,pad_to_multiple_of=A_    ,return_attention_mask=A_    ,)

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

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

											if needs_to_be_padded:
																UpperCAmelCase				   =  len(A_       ) - 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`
																					UpperCAmelCase				   =  (
																					    encoded_inputs["global_attention_mask"] + [-1] * difference
																					)
																elif self.padding_side == "left":
																					UpperCAmelCase				   =  [-1] * difference + encoded_inputs[
																					    "global_attention_mask"
																					]
																else:
																					raise ValueError("Invalid padding strategy:" + str(self.padding_side       )       )

						return encoded_inputs









from typing import TYPE_CHECKING

from ...utils import (
    OptionalDependencyNotAvailable,
    _LazyModule,
    is_flax_available,
    is_tf_available,
    is_tokenizers_available,
    is_torch_available,
    is_vision_available,
)


UpperCamelCase_												=	{
    'configuration_owlvit': [
        'OWLVIT_PRETRAINED_CONFIG_ARCHIVE_MAP',
        'OwlViTConfig',
        'OwlViTOnnxConfig',
        'OwlViTTextConfig',
        'OwlViTVisionConfig',
    ],
    'processing_owlvit': ['OwlViTProcessor'],
}


try:
    if not is_vision_available():
        raise OptionalDependencyNotAvailable()
except OptionalDependencyNotAvailable:
    pass
else:
    UpperCamelCase_												=	['OwlViTFeatureExtractor']
    UpperCamelCase_												=	['OwlViTImageProcessor']

try:
    if not is_torch_available():
        raise OptionalDependencyNotAvailable()
except OptionalDependencyNotAvailable:
    pass
else:
    UpperCamelCase_												=	[
        'OWLVIT_PRETRAINED_MODEL_ARCHIVE_LIST',
        'OwlViTModel',
        'OwlViTPreTrainedModel',
        'OwlViTTextModel',
        'OwlViTVisionModel',
        'OwlViTForObjectDetection',
    ]

if TYPE_CHECKING:
    from .configuration_owlvit import (
        OWLVIT_PRETRAINED_CONFIG_ARCHIVE_MAP,
        OwlViTConfig,
        OwlViTOnnxConfig,
        OwlViTTextConfig,
        OwlViTVisionConfig,
    )
    from .processing_owlvit import OwlViTProcessor

    try:
        if not is_vision_available():
            raise OptionalDependencyNotAvailable()
    except OptionalDependencyNotAvailable:
        pass
    else:
        from .feature_extraction_owlvit import OwlViTFeatureExtractor
        from .image_processing_owlvit import OwlViTImageProcessor

    try:
        if not is_torch_available():
            raise OptionalDependencyNotAvailable()
    except OptionalDependencyNotAvailable:
        pass
    else:
        from .modeling_owlvit import (
            OWLVIT_PRETRAINED_MODEL_ARCHIVE_LIST,
            OwlViTForObjectDetection,
            OwlViTModel,
            OwlViTPreTrainedModel,
            OwlViTTextModel,
            OwlViTVisionModel,
        )

else:
    import sys

    UpperCamelCase_												=	_LazyModule(__name__, globals()['__file__'], _import_structure, module_spec=__spec__)



