






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

import regex as re

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


__UpperCamelCase   :   str      =    logging.get_logger(__name__)


__UpperCamelCase   :   Dict      =    {
    """vocab_file""": """vocab.json""",
    """merges_file""": """merges.txt""",
    """tokenizer_config_file""": """tokenizer_config.json""",
}

__UpperCamelCase   :   Optional[int]      =    {
    """vocab_file""": {
        """facebook/blenderbot_small-90M""": """https://huggingface.co/facebook/blenderbot_small-90M/resolve/main/vocab.json"""
    },
    """merges_file""": {
        """facebook/blenderbot_small-90M""": """https://huggingface.co/facebook/blenderbot_small-90M/resolve/main/merges.txt"""
    },
    """tokenizer_config_file""": {
        """facebook/blenderbot_small-90M""": (
            """https://huggingface.co/facebook/blenderbot_small-90M/resolve/main/tokenizer_config.json"""
        )
    },
}

__UpperCamelCase   :   Dict      =    {"""facebook/blenderbot_small-90M""": 512}





def 					snake_case	(  lowerCamelCase       ):




	'''simple docstring'''







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

	__lowercase   							=	set(lowerCamelCase       )
	return pairs




class 							__UpperCamelCase     (  _lowerCAmelCase ):
	__snake_case						:List[Any] =							VOCAB_FILES_NAMES
	__snake_case						:Tuple =							PRETRAINED_VOCAB_FILES_MAP
	__snake_case						:Tuple =							PRETRAINED_POSITIONAL_EMBEDDINGS_SIZES
	__snake_case						:str =							['input_ids', 'attention_mask']







	def __init__(	self   :				Any							,					_lowerCAmelCase   :				Union[str, Any]							,					_lowerCAmelCase   :				Any							,					_lowerCAmelCase   :				str="__start__"							,					_lowerCAmelCase   :				int="__end__"							,					_lowerCAmelCase   :				Any="__unk__"							,					_lowerCAmelCase   :				List[Any]="__null__"							,					**_lowerCAmelCase   :				Tuple							,					)		->			str:
		"""simple docstring"""







		super().__init__(unk_token=_lowerCAmelCase							,					bos_token=_lowerCAmelCase							,					eos_token=_lowerCAmelCase							,					pad_token=_lowerCAmelCase							,					**_lowerCAmelCase      )

		with open(_lowerCAmelCase							,					encoding="""utf-8"""      ) as vocab_handle:
			__lowercase   							=	json.load(_lowerCAmelCase      )
		__lowercase   							=	{v: k for k, v in self.encoder.items()}
		with open(_lowerCAmelCase							,					encoding="""utf-8"""      ) as merges_handle:
			__lowercase   							=	merges_handle.read().split("""\n"""      )[1:-1]
		__lowercase   							=	[tuple(merge.split()      ) for merge in merges]
		__lowercase   							=	dict(zip(_lowerCAmelCase							,					range(len(_lowerCAmelCase      )      )      )      )
		__lowercase   							=	{}







	@property
	def 			_a (	self   :				Union[str, Any]      )		->			int:
		"""simple docstring"""







		return len(self.encoder      )







	def 			_a (	self   :				Dict      )		->			Dict:
		"""simple docstring"""







		return dict(self.encoder							,					**self.added_tokens_encoder      )







	def 			_a (	self   :				str							,					_lowerCAmelCase   :				str      )		->			str:
		"""simple docstring"""







		if token in self.cache:
			return self.cache[token]
		__lowercase   							=	re.sub("""([.,!?()])"""							,					r""" \1"""							,					_lowerCAmelCase      )
		__lowercase   							=	re.sub("""(')"""							,					r""" \1 """							,					_lowerCAmelCase      )
		__lowercase   							=	re.sub(r"""\s{2,}"""							,					""" """							,					_lowerCAmelCase      )
		if "\n" in token:
			__lowercase   							=	token.replace("""\n"""							,					""" __newln__"""      )

		__lowercase   							=	token.split(""" """      )
		__lowercase   							=	[]
		for token in tokens:
			if not len(_lowerCAmelCase      ):
				continue

			__lowercase   							=	token.lower()
			__lowercase   							=	tuple(_lowerCAmelCase      )
			__lowercase   							=	tuple(list(word[:-1]      ) + [word[-1] + """</w>"""]      )
			__lowercase   							=	get_pairs(_lowerCAmelCase      )

			if not pairs:
				words.append(_lowerCAmelCase      )
				continue

			while True:
				__lowercase   							=	min(_lowerCAmelCase							,					key=lambda _lowerCAmelCase      : self.bpe_ranks.get(_lowerCAmelCase							,					float("""inf"""      )      )      )
				if bigram not in self.bpe_ranks:
					break
				__lowercase							,    __lowercase   							=	bigram
				__lowercase   							=	[]
				__lowercase   							=	0

				while i < len(_lowerCAmelCase      ):
					try:
						__lowercase   							=	word.index(_lowerCAmelCase							,					_lowerCAmelCase      )
						new_word.extend(word[i:j]      )
						__lowercase   							=	j
					except ValueError:
						new_word.extend(word[i:]      )
						break

					if word[i] == first and i < len(_lowerCAmelCase      ) - 1 and word[i + 1] == second:
						new_word.append(first + second      )
						i += 2
					else:
						new_word.append(word[i]      )
						i += 1
				__lowercase   							=	tuple(_lowerCAmelCase      )
				__lowercase   							=	new_word
				if len(_lowerCAmelCase      ) == 1:
					break
				else:
					__lowercase   							=	get_pairs(_lowerCAmelCase      )
			__lowercase   							=	"""@@ """.join(_lowerCAmelCase      )
			__lowercase   							=	word[:-4]

			__lowercase   							=	word
			words.append(_lowerCAmelCase      )
		return " ".join(_lowerCAmelCase      )







	def 			_a (	self   :				Optional[Any]							,					_lowerCAmelCase   :				str      )		->			List[str]:
		"""simple docstring"""







		__lowercase   							=	[]

		__lowercase   							=	re.findall(r"""\S+\n?"""							,					_lowerCAmelCase      )

		for token in words:
			split_tokens.extend(list(self.bpe(_lowerCAmelCase      ).split(""" """      )      )      )
		return split_tokens







	def 			_a (	self   :				Tuple							,					_lowerCAmelCase   :				str      )		->			int:
		"""simple docstring"""







		__lowercase   							=	token.lower()
		return self.encoder.get(_lowerCAmelCase							,					self.encoder.get(self.unk_token      )      )







	def 			_a (	self   :				Tuple							,					_lowerCAmelCase   :				int      )		->			str:
		"""simple docstring"""







		return self.decoder.get(_lowerCAmelCase							,					self.unk_token      )







	def 			_a (	self   :				Dict							,					_lowerCAmelCase   :				List[str]      )		->			str:
		"""simple docstring"""







		__lowercase   							=	""" """.join(_lowerCAmelCase      ).replace("""@@ """							,					""""""      ).strip()
		return out_string







	def 			_a (	self   :				List[str]							,					_lowerCAmelCase   :				str							,					_lowerCAmelCase   :				Optional[str] = None      )		->			Tuple[str]:
		"""simple docstring"""







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

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

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

		return vocab_file, merge_file






'''simple docstring'''





import copy

from ...configuration_utils import PretrainedConfig
from ...utils import logging
from ..auto.configuration_auto import CONFIG_MAPPING


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



class  snake_case__						(    SCREAMING_SNAKE_CASE_				):
 A__				= '''upernet'''
 def __init__(   self						:							Optional[int]      ,     __a						:							Dict=None      ,     __a						:							List[str]=512      ,     __a						:							int=0.0_2      ,     __a						:							Optional[Any]=[1, 2, 3, 6]      ,     __a						:							Union[str, Any]=True      ,     __a						:							Any=0.4      ,     __a						:							int=384      ,     __a						:							int=256      ,     __a						:							str=1      ,     __a						:							List[Any]=False      ,     __a						:							Dict=255      ,     **__a						:							Dict      ,     )      ->   Optional[int]:







       '''simple docstring'''
       super().__init__(**__a  )

       if backbone_config is None:
             logger.info('`backbone_config` is `None`. Initializing the config with the default `ResNet` backbone.'  )
             __snake_case :   Optional[int]													=    CONFIG_MAPPING['resnet'](out_features=['stage1', 'stage2', 'stage3', 'stage4']  )
       elif isinstance(__a      ,     __a  ):
             __snake_case :   List[Any]													=    backbone_config.get('model_type'  )
             __snake_case :   List[str]													=    CONFIG_MAPPING[backbone_model_type]
             __snake_case :   int													=    config_class.from_dict(__a  )

       __snake_case :   Any													=    backbone_config
       __snake_case :   Tuple													=    hidden_size
       __snake_case :   str													=    initializer_range
       __snake_case :   Dict													=    pool_scales
       __snake_case :   Optional[Any]													=    use_auxiliary_head
       __snake_case :   Optional[Any]													=    auxiliary_loss_weight
       __snake_case :   Optional[int]													=    auxiliary_in_channels
       __snake_case :   Dict													=    auxiliary_channels
       __snake_case :   Any													=    auxiliary_num_convs
       __snake_case :   Optional[Any]													=    auxiliary_concat_input
       __snake_case :   List[str]													=    loss_ignore_index





 def A_   (   self						:							List[Any]  )      ->   Union[str, Any]:







       '''simple docstring'''
       __snake_case :   Union[str, Any]													=    copy.deepcopy(self.__dict__  )
       __snake_case :   str													=    self.backbone_config.to_dict()
       __snake_case :   Optional[int]													=    self.__class__.model_type
       return output



