



"""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


lowercase  							=					logging.get_logger(__name__)


lowercase  							=					{'''vocab_file''': '''vocab.json''', '''merges_file''': '''merges.txt'''}

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

lowercase  							=					{
    '''allenai/led-base-16384''': 1_63_84,
}




@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(A       )
						cs.append(2**8 + n       )
						n += 1
		_UpperCAmelCase							 =		[chr(A       ) for n in cs]
		return dict(zip(A     ,				A       )       )




def 	UpperCAmelCase     (		A	:						Union[str, Any]       ):

		'''simple docstring'''


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






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







							_UpperCAmelCase      				=					VOCAB_FILES_NAMES
							_UpperCAmelCase      				=					PRETRAINED_VOCAB_FILES_MAP
							_UpperCAmelCase      				=					PRETRAINED_POSITIONAL_EMBEDDINGS_SIZES
							_UpperCAmelCase      				=					['''input_ids''', '''attention_mask''']






							def __init__(  self	,       snake_case	,       snake_case	,       snake_case="replace"	,       snake_case="<s>"	,       snake_case="</s>"	,       snake_case="</s>"	,       snake_case="<s>"	,       snake_case="<unk>"	,       snake_case="<pad>"	,       snake_case="<mask>"	,       snake_case=False	,       **snake_case	,       )			->							int:
									_UpperCAmelCase							 =		AddedToken(snake_case	,       lstrip=snake_case	,       rstrip=snake_case						) if isinstance(snake_case	,       snake_case						) else bos_token
									_UpperCAmelCase							 =		AddedToken(snake_case	,       lstrip=snake_case	,       rstrip=snake_case						) if isinstance(snake_case	,       snake_case						) else eos_token
									_UpperCAmelCase							 =		AddedToken(snake_case	,       lstrip=snake_case	,       rstrip=snake_case						) if isinstance(snake_case	,       snake_case						) else sep_token
									_UpperCAmelCase							 =		AddedToken(snake_case	,       lstrip=snake_case	,       rstrip=snake_case						) if isinstance(snake_case	,       snake_case						) else cls_token
									_UpperCAmelCase							 =		AddedToken(snake_case	,       lstrip=snake_case	,       rstrip=snake_case						) if isinstance(snake_case	,       snake_case						) else unk_token
									_UpperCAmelCase							 =		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
									_UpperCAmelCase							 =		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:
											_UpperCAmelCase							 =		json.load(snake_case						)
									_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(snake_case	,       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(snake_case	,       range(len(snake_case						)						)						)						)
									_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        lowerCamelCase_   (  self						)			->							Any:
									return len(self.encoder						)






							def        lowerCamelCase_   (  self						)			->							Optional[int]:
									return dict(self.encoder	,       **self.added_tokens_encoder						)






							def        lowerCamelCase_   (  self	,       snake_case						)			->							List[Any]:
									if token in self.cache:
											return self.cache[token]
									_UpperCAmelCase							 =		tuple(snake_case						)
									_UpperCAmelCase							 =		get_pairs(snake_case						)

									if not pairs:
											return token

									while True:
											_UpperCAmelCase							 =		min(snake_case	,       key=lambda snake_case						: self.bpe_ranks.get(snake_case	,       float('inf'						)						)						)
											if bigram not in self.bpe_ranks:
													break
											_UpperCAmelCase ,					_UpperCAmelCase							 =		bigram
											_UpperCAmelCase							 =		[]
											_UpperCAmelCase							 =		0
											while i < len(snake_case						):
													try:
															_UpperCAmelCase							 =		word.index(snake_case	,       snake_case						)
													except ValueError:
															new_word.extend(word[i:]						)
															break
													else:
															new_word.extend(word[i:j]						)
															_UpperCAmelCase							 =		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
											_UpperCAmelCase							 =		tuple(snake_case						)
											_UpperCAmelCase							 =		new_word
											if len(snake_case						) == 1:
													break
											else:
													_UpperCAmelCase							 =		get_pairs(snake_case						)
									_UpperCAmelCase							 =		' '.join(snake_case						)
									_UpperCAmelCase							 =		word
									return word






							def        lowerCamelCase_   (  self	,       snake_case						)			->							int:
									_UpperCAmelCase							 =		[]
									for token in re.findall(self.pat	,       snake_case						):
											_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(snake_case						).split(' '						)						)
									return bpe_tokens






							def        lowerCamelCase_   (  self	,       snake_case						)			->							Tuple:
									return self.encoder.get(snake_case	,       self.encoder.get(self.unk_token						)						)






							def        lowerCamelCase_   (  self	,       snake_case						)			->							Dict:
									return self.decoder.get(snake_case						)






							def        lowerCamelCase_   (  self	,       snake_case						)			->							Optional[int]:
									_UpperCAmelCase							 =		''.join(snake_case						)
									_UpperCAmelCase							 =		bytearray([self.byte_decoder[c] for c in text]						).decode('utf-8'	,       errors=self.errors						)
									return text






							def        lowerCamelCase_   (  self	,       snake_case	,       snake_case = None						)			->							Tuple[str]:
									if not os.path.isdir(snake_case						):
											logger.error(f'Vocabulary path ({save_directory}) should be a directory'						)
											return
									_UpperCAmelCase							 =		os.path.join(
									    snake_case	,       (filename_prefix + '-' if filename_prefix else '') + VOCAB_FILES_NAMES['vocab_file']						)
									_UpperCAmelCase							 =		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'						)

									_UpperCAmelCase							 =		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 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(snake_case						) + '\n'						)
													index += 1

									return vocab_file, merge_file






							def        lowerCamelCase_   (  self	,       snake_case	,       snake_case = None						)			->							List[int]:
									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        lowerCamelCase_   (  self	,       snake_case	,       snake_case = None	,       snake_case = False						)			->							List[int]:
									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        lowerCamelCase_   (  self	,       snake_case	,       snake_case = None						)			->							List[int]:
									_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        lowerCamelCase_   (  self	,       snake_case	,       snake_case=False	,       **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(snake_case						) > 0 and not text[0].isspace()):
											_UpperCAmelCase							 =		' ' + text
									return (text, kwargs)






							def        lowerCamelCase_   (  self	,       snake_case	,       snake_case = None	,       snake_case = PaddingStrategy.DO_NOT_PAD	,       snake_case = None	,       snake_case = None	,       )			->							dict:
									_UpperCAmelCase							 =		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:
											_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(snake_case						)

											if needs_to_be_padded:
													_UpperCAmelCase							 =		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`
															_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







"""simple docstring"""





from typing import TYPE_CHECKING

from ...utils import OptionalDependencyNotAvailable, _LazyModule, is_torch_available


lowercase  							=					{
    '''configuration_clipseg''': [
        '''CLIPSEG_PRETRAINED_CONFIG_ARCHIVE_MAP''',
        '''CLIPSegConfig''',
        '''CLIPSegTextConfig''',
        '''CLIPSegVisionConfig''',
    ],
    '''processing_clipseg''': ['''CLIPSegProcessor'''],
}

try:
					if not is_torch_available():
										raise OptionalDependencyNotAvailable()
except OptionalDependencyNotAvailable:
					pass
else:
					lowercase  							=					[
					    '''CLIPSEG_PRETRAINED_MODEL_ARCHIVE_LIST''',
					    '''CLIPSegModel''',
					    '''CLIPSegPreTrainedModel''',
					    '''CLIPSegTextModel''',
					    '''CLIPSegVisionModel''',
					    '''CLIPSegForImageSegmentation''',
					]

if TYPE_CHECKING:
					from .configuration_clipseg import (
					    CLIPSEG_PRETRAINED_CONFIG_ARCHIVE_MAP,
					    CLIPSegConfig,
					    CLIPSegTextConfig,
					    CLIPSegVisionConfig,
					)
					from .processing_clipseg import CLIPSegProcessor

					try:
										if not is_torch_available():
															raise OptionalDependencyNotAvailable()
					except OptionalDependencyNotAvailable:
										pass
					else:
										from .modeling_clipseg import (
										    CLIPSEG_PRETRAINED_MODEL_ARCHIVE_LIST,
										    CLIPSegForImageSegmentation,
										    CLIPSegModel,
										    CLIPSegPreTrainedModel,
										    CLIPSegTextModel,
										    CLIPSegVisionModel,
										)

else:
					import sys

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


