





"""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


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''': 16_384,
}


@lru_cache()
# Copied from transformers.models.bart.tokenization_bart.bytes_to_unicode
def       a__					(					):




		"""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       a__					(					_SCREAMING_SNAKE_CASE    ):




		"""simple docstring"""


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






class        _lowerCamelCase      (       __A ):
						UpperCAmelCase_ =			VOCAB_FILES_NAMES
						UpperCAmelCase_ =			PRETRAINED_VOCAB_FILES_MAP
						UpperCAmelCase_ =			PRETRAINED_POSITIONAL_EMBEDDINGS_SIZES
						UpperCAmelCase_ =			["""input_ids""", """attention_mask"""]


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

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

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

								with open(UpperCamelCase__   ,							encoding="utf-8"		) as vocab_handle:
										UpperCamelCase   =	json.load(UpperCamelCase__		)
								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(UpperCamelCase__   ,							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(UpperCamelCase__   ,							range(len(UpperCamelCase__		)		)		)		)
								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     snake_case_   (self		) ->   Optional[Any]:
								return len(self.encoder		)


						def     snake_case_   (self		) ->   Dict:
								return dict(self.encoder   ,							**self.added_tokens_encoder		)


						def     snake_case_   (self   ,							__a		) ->   Dict:
								if token in self.cache:
										return self.cache[token]
								UpperCamelCase   =	tuple(UpperCamelCase__		)
								UpperCamelCase   =	get_pairs(UpperCamelCase__		)

								if not pairs:
										return token

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

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


						def     snake_case_   (self   ,							__a		) ->   List[str]:
								UpperCamelCase   =	[]
								for token in re.findall(self.pat   ,							UpperCamelCase__		):
										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(UpperCamelCase__		).split(" "		)		)
								return bpe_tokens


						def     snake_case_   (self   ,							__a		) ->   Optional[Any]:
								return self.encoder.get(UpperCamelCase__   ,							self.encoder.get(self.unk_token		)		)


						def     snake_case_   (self   ,							__a		) ->   Tuple:
								return self.decoder.get(UpperCamelCase__		)


						def     snake_case_   (self   ,							__a		) ->   Optional[int]:
								UpperCamelCase   =	''.join(UpperCamelCase__		)
								UpperCamelCase   =	bytearray([self.byte_decoder[c] for c in text]		).decode("utf-8"   ,							errors=self.errors		)
								return text


						def     snake_case_   (self   ,							__a   ,							__a = None		) ->   Any:
								if not os.path.isdir(UpperCamelCase__		):
										logger.error(F"Vocabulary path ({save_directory}) should be a directory"		)
										return
								UpperCamelCase   =	os.path.join(
								    UpperCamelCase__   ,							(filename_prefix + "-" if filename_prefix else "") + VOCAB_FILES_NAMES["vocab_file"]		)
								UpperCamelCase   =	os.path.join(
								    UpperCamelCase__   ,							(filename_prefix + "-" if filename_prefix else "") + VOCAB_FILES_NAMES["merges_file"]		)

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

								UpperCamelCase   =	0
								with open(UpperCamelCase__   ,							"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 __a		: 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(UpperCamelCase__		) + "\n"		)
												index += 1

								return vocab_file, merge_file


						def     snake_case_   (self   ,							__a   ,							__a = None		) ->   List[str]:
								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     snake_case_   (self   ,							__a   ,							__a = None   ,							__a = False		) ->   Tuple:
								if already_has_special_tokens:
										return super().get_special_tokens_mask(
										    token_ids_a=UpperCamelCase__   ,							token_ids_a=UpperCamelCase__   ,							already_has_special_tokens=UpperCamelCase__		)

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


						def     snake_case_   (self   ,							__a   ,							__a = None		) ->   Dict:
								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     snake_case_   (self   ,							__a   ,							__a=False   ,							**__a		) ->   Any:
								UpperCamelCase   =	kwargs.pop("add_prefix_space"   ,							self.add_prefix_space		)
								if (is_split_into_words or add_prefix_space) and (len(UpperCamelCase__		) > 0 and not text[0].isspace()):
										UpperCamelCase   =	' ' + text
								return (text, kwargs)




						def     snake_case_   (self   ,							__a   ,							__a = None   ,							__a = PaddingStrategy.DO_NOT_PAD   ,							__a = None   ,							__a = None   ,							) ->   Tuple:
								UpperCamelCase   =	super()._pad(
								    encoded_inputs=UpperCamelCase__   ,							max_length=UpperCamelCase__   ,							padding_strategy=UpperCamelCase__   ,							pad_to_multiple_of=UpperCamelCase__   ,							return_attention_mask=UpperCamelCase__   ,							)

								# 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(UpperCamelCase__		)

										if needs_to_be_padded:
												UpperCamelCase   =	len(UpperCamelCase__		) - 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 ...configuration_utils import PretrainedConfig
from ...utils import logging


lowerCAmelCase__     			=			logging.get_logger(__name__)

lowerCAmelCase__     			=			{
    '''microsoft/swinv2-tiny-patch4-window8-256''': (
        '''https://huggingface.co/microsoft/swinv2-tiny-patch4-window8-256/resolve/main/config.json'''
    ),
}





class        _lowerCamelCase      (       _lowercase ):
						UpperCAmelCase_ =			"swinv2"

						UpperCAmelCase_ =			{
						    "num_attention_heads": "num_heads",
						    "num_hidden_layers": "num_layers",
						}


						def __init__(self   ,							__a=2_24   ,							__a=4   ,							__a=3   ,							__a=96   ,							__a=[2, 2, 6, 2]   ,							__a=[3, 6, 12, 24]   ,							__a=7   ,							__a=4.0   ,							__a=True   ,							__a=0.0   ,							__a=0.0   ,							__a=0.1   ,							__a="gelu"   ,							__a=False   ,							__a=0.02   ,							__a=1e-5   ,							__a=32   ,							**__a   ,							) ->   Optional[Any]:
								super().__init__(**__a		)

								UpperCamelCase   =	image_size
								UpperCamelCase   =	patch_size
								UpperCamelCase   =	num_channels
								UpperCamelCase   =	embed_dim
								UpperCamelCase   =	depths
								UpperCamelCase   =	len(__a		)
								UpperCamelCase   =	num_heads
								UpperCamelCase   =	window_size
								UpperCamelCase   =	mlp_ratio
								UpperCamelCase   =	qkv_bias
								UpperCamelCase   =	hidden_dropout_prob
								UpperCamelCase   =	attention_probs_dropout_prob
								UpperCamelCase   =	drop_path_rate
								UpperCamelCase   =	hidden_act
								UpperCamelCase   =	use_absolute_embeddings
								UpperCamelCase   =	layer_norm_eps
								UpperCamelCase   =	initializer_range
								UpperCamelCase   =	encoder_stride
								# we set the hidden_size attribute in order to make Swinv2 work with VisionEncoderDecoderModel
								# this indicates the channel dimension after the last stage of the model
								UpperCamelCase   =	int(embed_dim * 2 ** (len(__a		) - 1)		)
								UpperCamelCase   =	(0, 0, 0, 0)






