






import json
import os
from typing import List, Optional, Tuple

from ...tokenization_utils import PreTrainedTokenizer
from ...utils import logging


snake_case_   :	Union[str, Any]							      =logging.get_logger(__name__)

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

snake_case_   :	Optional[Any]							      ={
    '''vocab_file''': {
        '''microsoft/biogpt''': '''https://huggingface.co/microsoft/biogpt/resolve/main/vocab.json''',
    },
    '''merges_file''': {'''microsoft/biogpt''': '''https://huggingface.co/microsoft/biogpt/resolve/main/merges.txt'''},
}

snake_case_   :	List[str]							      ={
    '''microsoft/biogpt''': 1024,
}



def      UpperCAmelCase						( lowerCAmelCase__	):


		'''simple docstring'''

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





class        a__      (	lowerCAmelCase__		):
		UpperCAmelCase_							:       List[Any] 					= VOCAB_FILES_NAMES
		UpperCAmelCase_							:       List[Any] 					= PRETRAINED_VOCAB_FILES_MAP
		UpperCAmelCase_							:       Optional[Any] 					= PRETRAINED_POSITIONAL_EMBEDDINGS_SIZES
		UpperCAmelCase_							:       Optional[Any] 					= ['input_ids', 'attention_mask']






		def __init__(      self							, lowercase__							, lowercase__							, lowercase__="<unk>"							, lowercase__="<s>"							, lowercase__="</s>"							, lowercase__="</s>"							, lowercase__="<pad>"							, **lowercase__							, )				->				Optional[Any]:
				super().__init__(
				    bos_token=lowercase__							, eos_token=lowercase__							, sep_token=lowercase__							, unk_token=lowercase__							, pad_token=lowercase__							, **lowercase__							, )

				try:
						import sacremoses
				except ImportError:
						raise ImportError(
						    "You need to install sacremoses to use BioGptTokenizer. "
						    "See https://pypi.org/project/sacremoses/ for installation."						)

				__A    =							"en"
				__A    =							sacremoses
				# cache of sm.MosesTokenizer instance
				__A    =							{}
				__A    =							{}
				with open(lowercase__							, encoding="utf-8"						) as vocab_handle:
						__A    =							json.load(lowercase__						)
				__A    =							{v: k for k, v in self.encoder.items()}
				with open(lowercase__							, encoding="utf-8"						) as merges_handle:
						__A    =							merges_handle.read().split("\n"						)[:-1]
				__A    =							[tuple(merge.split()[:2]						) for merge in merges]
				__A    =							dict(zip(lowercase__							, range(len(lowercase__						)						)						)						)
				__A    =							{}






		@property
		def 					_lowerCamelCase					(      self						)				->				List[Any]:
				return len(self.encoder						)






		def 					_lowerCamelCase					(      self						)				->				Union[str, Any]:
				return dict(self.encoder							, **self.added_tokens_encoder						)






		def 					_lowerCamelCase					(      self							, lowercase__							, lowercase__						)				->				Any:
				if lang not in self.cache_moses_tokenizer:
						__A    =							self.sm.MosesTokenizer(lang=lowercase__						)
						__A    =							moses_tokenizer
				return self.cache_moses_tokenizer[lang].tokenize(
				    lowercase__							, aggressive_dash_splits=lowercase__							, return_str=lowercase__							, escape=lowercase__						)






		def 					_lowerCamelCase					(      self							, lowercase__							, lowercase__						)				->				Tuple:
				if lang not in self.cache_moses_detokenizer:
						__A    =							self.sm.MosesDetokenizer(lang=lowercase__						)
						__A    =							moses_detokenizer
				return self.cache_moses_detokenizer[lang].detokenize(lowercase__						)






		def 					_lowerCamelCase					(      self							, lowercase__						)				->				Optional[Any]:
				__A    =							tuple(token[:-1]						) + (token[-1] + "</w>",)
				if token in self.cache:
						return self.cache[token]
				__A    =							get_pairs(lowercase__						)

				if not pairs:
						return token + "</w>"

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

								if word[i] == first and i < len(lowercase__						) - 1 and word[i + 1] == second:
										new_word.append(first + second						)
										i += 2
								else:
										new_word.append(word[i]						)
										i += 1
						__A    =							tuple(lowercase__						)
						__A    =							new_word
						if len(lowercase__						) == 1:
								break
						else:
								__A    =							get_pairs(lowercase__						)
				__A    =							" ".join(lowercase__						)
				if word == "\n  </w>":
						__A    =							"\n</w>"
				__A    =							word
				return word






		def 					_lowerCamelCase					(      self							, lowercase__							, lowercase__=False						)				->				Optional[int]:
				if bypass_tokenizer:
						__A    =							text.split()
				else:
						__A    =							self.moses_tokenize(lowercase__							, self.lang						)

				__A    =							[]
				for token in text:
						if token:
								split_tokens.extend(list(self.bpe(lowercase__						).split(" "						)						)						)

				return split_tokens






		def 					_lowerCamelCase					(      self							, lowercase__						)				->				List[Any]:
				return self.encoder.get(lowercase__							, self.encoder.get(self.unk_token						)						)






		def 					_lowerCamelCase					(      self							, lowercase__						)				->				Optional[Any]:
				return self.decoder.get(lowercase__							, self.unk_token						)






		def 					_lowerCamelCase					(      self							, lowercase__						)				->				Dict:
				__A    =							[t.replace(" "							, ""						).replace("</w>"							, " "						) for t in tokens]
				__A    =							"".join(lowercase__						).split()
				# detokenize
				__A    =							self.moses_detokenize(lowercase__							, self.lang						)
				return text






		def 					_lowerCamelCase					(      self							, lowercase__							, lowercase__ = None						)				->				List[int]:
				if token_ids_a is None:
						return [self.sep_token_id] + token_ids_a
				__A    =							[self.sep_token_id]
				return sep + token_ids_a + sep + token_ids_a






		def 					_lowerCamelCase					(      self							, lowercase__							, lowercase__ = None							, lowercase__ = False						)				->				List[int]:
				if already_has_special_tokens:
						return super().get_special_tokens_mask(
						    token_ids_a=lowercase__							, token_ids_a=lowercase__							, already_has_special_tokens=lowercase__						)
				# no bos used in fairseq
				if token_ids_a is not None:
						return [1] + ([0] * len(lowercase__						)) + [1] + ([0] * len(lowercase__						))
				return [1] + ([0] * len(lowercase__						))






		def 					_lowerCamelCase					(      self							, lowercase__							, lowercase__ = None						)				->				List[int]:
				__A    =							[self.sep_token_id]

				# no bos used in fairseq
				if token_ids_a is None:
						return len(token_ids_a + sep						) * [0]
				return len(token_ids_a + sep						) * [0] + len(token_ids_a + sep						) * [1]






		def 					_lowerCamelCase					(      self							, lowercase__							, lowercase__ = None						)				->				Tuple[str]:
				if not os.path.isdir(lowercase__						):
						logger.error(F"""Vocabulary path ({save_directory}) should be a directory"""						)
						return
				__A    =							os.path.join(
				    lowercase__							, (filename_prefix + "-" if filename_prefix else "") + VOCAB_FILES_NAMES["vocab_file"]						)
				__A    =							os.path.join(
				    lowercase__							, (filename_prefix + "-" if filename_prefix else "") + VOCAB_FILES_NAMES["merges_file"]						)

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

				__A    =							0
				with open(lowercase__							, "w"							, encoding="utf-8"						) as writer:
						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!"						)
										__A    =							token_index
								writer.write(" ".join(lowercase__						) + "\n"						)
								index += 1

				return vocab_file, merge_file






		def __getstate__(      self						)				->				List[Any]:
				__A    =							self.__dict__.copy()
				__A    =							None
				return state






		def __setstate__(      self							, lowercase__						)				->				Any:
				__A    =							d

				try:
						import sacremoses
				except ImportError:
						raise ImportError(
						    "You need to install sacremoses to use XLMTokenizer. "
						    "See https://pypi.org/project/sacremoses/ for installation."						)

				__A    =							sacremoses



"""simple docstring"""


from typing import TYPE_CHECKING

from ...utils import OptionalDependencyNotAvailable, _LazyModule, is_torch_available, is_vision_available


__A					=			{
    'configuration_donut_swin': ['DONUT_SWIN_PRETRAINED_CONFIG_ARCHIVE_MAP', 'DonutSwinConfig'],
    'processing_donut': ['DonutProcessor'],
}

try:
			if not is_torch_available():
						raise OptionalDependencyNotAvailable()
except OptionalDependencyNotAvailable:
			pass
else:
			__A					=			[
			    'DONUT_SWIN_PRETRAINED_MODEL_ARCHIVE_LIST',
			    'DonutSwinModel',
			    'DonutSwinPreTrainedModel',
			]

try:
			if not is_vision_available():
						raise OptionalDependencyNotAvailable()
except OptionalDependencyNotAvailable:
			pass
else:
			__A					=			['DonutFeatureExtractor']
			__A					=			['DonutImageProcessor']


if TYPE_CHECKING:
			from .configuration_donut_swin import DONUT_SWIN_PRETRAINED_CONFIG_ARCHIVE_MAP, DonutSwinConfig
			from .processing_donut import DonutProcessor

			try:
						if not is_torch_available():
									raise OptionalDependencyNotAvailable()
			except OptionalDependencyNotAvailable:
						pass
			else:
						from .modeling_donut_swin import (
						    DONUT_SWIN_PRETRAINED_MODEL_ARCHIVE_LIST,
						    DonutSwinModel,
						    DonutSwinPreTrainedModel,
						)

			try:
						if not is_vision_available():
									raise OptionalDependencyNotAvailable()
			except OptionalDependencyNotAvailable:
						pass
			else:
						from .feature_extraction_donut import DonutFeatureExtractor
						from .image_processing_donut import DonutImageProcessor

else:
			import sys

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



