

'''simple docstring'''

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


SCREAMING_SNAKE_CASE							:				Optional[int]     	=			logging.get_logger(__name__)


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

# See all LED models at https://huggingface.co/models?filter=LED
SCREAMING_SNAKE_CASE							:				List[str]     	=			{
    """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""",
    },
}

SCREAMING_SNAKE_CASE							:				Optional[int]     	=			{
    """allenai/led-base-16384""": 16384,
}




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




def 							_UpperCamelCase				(   lowerCAmelCase__:					List[str]   )      -> List[str]:
							SCREAMING_SNAKE_CASE_				=				set()
							SCREAMING_SNAKE_CASE_				=				word[0]
							for char in word[1:]:
														pairs.add((prev_char, char)   )
														SCREAMING_SNAKE_CASE_				=				char
							return pairs






class    snake_case     (      SCREAMING_SNAKE_CASE_		):






				"""simple docstring"""
				_a    	=     VOCAB_FILES_NAMES
				_a    	=     PRETRAINED_VOCAB_FILES_MAP
				_a    	=     PRETRAINED_POSITIONAL_EMBEDDINGS_SIZES
				_a    	=     ["""input_ids""", """attention_mask"""]



				def __init__(    self,     _lowercase,     _lowercase,     _lowercase="replace",     _lowercase="<s>",     _lowercase="</s>",     _lowercase="</s>",     _lowercase="<s>",     _lowercase="<unk>",     _lowercase="<pad>",     _lowercase="<mask>",     _lowercase=False,     **_lowercase,     )     ->							Any:
											SCREAMING_SNAKE_CASE_				=				AddedToken(snake_case__,     lstrip=snake_case__,     rstrip=snake_case__       ) if isinstance(snake_case__,     snake_case__       ) else bos_token
											SCREAMING_SNAKE_CASE_				=				AddedToken(snake_case__,     lstrip=snake_case__,     rstrip=snake_case__       ) if isinstance(snake_case__,     snake_case__       ) else eos_token
											SCREAMING_SNAKE_CASE_				=				AddedToken(snake_case__,     lstrip=snake_case__,     rstrip=snake_case__       ) if isinstance(snake_case__,     snake_case__       ) else sep_token
											SCREAMING_SNAKE_CASE_				=				AddedToken(snake_case__,     lstrip=snake_case__,     rstrip=snake_case__       ) if isinstance(snake_case__,     snake_case__       ) else cls_token
											SCREAMING_SNAKE_CASE_				=				AddedToken(snake_case__,     lstrip=snake_case__,     rstrip=snake_case__       ) if isinstance(snake_case__,     snake_case__       ) else unk_token
											SCREAMING_SNAKE_CASE_				=				AddedToken(snake_case__,     lstrip=snake_case__,     rstrip=snake_case__       ) if isinstance(snake_case__,     snake_case__       ) else pad_token

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

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

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

											# Should have added re.IGNORECASE so BPE merges can happen for capitalized versions of contractions
											SCREAMING_SNAKE_CASE_				=				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   a__					(    self       )     ->							List[str]:
											return len(self.encoder       )



				def   a__					(    self       )     ->							List[str]:
											return dict(self.encoder,     **self.added_tokens_encoder       )



				def   a__					(    self,     _lowercase       )     ->							Any:

											if token in self.cache:
																		return self.cache[token]
											SCREAMING_SNAKE_CASE_				=				tuple(snake_case__       )
											SCREAMING_SNAKE_CASE_				=				get_pairs(snake_case__       )

											if not pairs:
																		return token

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

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



				def   a__					(    self,     _lowercase       )     ->							str:
											SCREAMING_SNAKE_CASE_				=				[]
											for token in re.findall(self.pat,     snake_case__       ):
																		SCREAMING_SNAKE_CASE_				=				''.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(snake_case__       ).split(' '       )       )
											return bpe_tokens



				def   a__					(    self,     _lowercase       )     ->							List[str]:
											return self.encoder.get(snake_case__,     self.encoder.get(self.unk_token       )       )



				def   a__					(    self,     _lowercase       )     ->							Optional[Any]:
											return self.decoder.get(snake_case__       )



				def   a__					(    self,     _lowercase       )     ->							Tuple:
											SCREAMING_SNAKE_CASE_				=				''.join(snake_case__       )
											SCREAMING_SNAKE_CASE_				=				bytearray([self.byte_decoder[c] for c in text]       ).decode('utf-8',     errors=self.errors       )
											return text



				def   a__					(    self,     _lowercase,     _lowercase = None       )     ->							int:

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

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

											SCREAMING_SNAKE_CASE_				=				0
											with open(snake_case__,     '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 _lowercase       : 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!'       )
																																SCREAMING_SNAKE_CASE_				=				token_index
																									writer.write(' '.join(snake_case__       ) + '\n'       )
																									index += 1

											return vocab_file, merge_file



				def   a__					(    self,     _lowercase,     _lowercase = None       )     ->							List[Any]:

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



				def   a__					(    self,     _lowercase,     _lowercase = None,     _lowercase = False       )     ->							List[Any]:

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

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



				def   a__					(    self,     _lowercase,     _lowercase = None       )     ->							Tuple:
											SCREAMING_SNAKE_CASE_				=				[self.sep_token_id]
											SCREAMING_SNAKE_CASE_				=				[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   a__					(    self,     _lowercase,     _lowercase=False,     **_lowercase       )     ->							List[Any]:
											SCREAMING_SNAKE_CASE_				=				kwargs.pop('add_prefix_space',     self.add_prefix_space       )
											if (is_split_into_words or add_prefix_space) and (len(snake_case__       ) > 0 and not text[0].isspace()):
																		SCREAMING_SNAKE_CASE_				=				' ' + text
											return (text, kwargs)





				def   a__					(    self,     _lowercase,     _lowercase = None,     _lowercase = PaddingStrategy.DO_NOT_PAD,     _lowercase = None,     _lowercase = None,     )     ->							Dict:
											SCREAMING_SNAKE_CASE_				=				super()._pad(
											    encoded_inputs=snake_case__,     max_length=snake_case__,     padding_strategy=snake_case__,     pad_to_multiple_of=snake_case__,     return_attention_mask=snake_case__,     )

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

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

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

											return encoded_inputs









'''simple docstring'''







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,
)


lowerCAmelCase     :  int											=    {
    """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:
       lowerCAmelCase     :  Dict											=    ["""OwlViTFeatureExtractor"""]
       lowerCAmelCase     :  int											=    ["""OwlViTImageProcessor"""]

try:
       if not is_torch_available():
              raise OptionalDependencyNotAvailable()
except OptionalDependencyNotAvailable:
       pass
else:
       lowerCAmelCase     :  Optional[Any]											=    [
           """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

       lowerCAmelCase     :  Union[str, Any]											=    _LazyModule(__name__, globals()["""__file__"""], _import_structure, module_spec=__spec__)

