




import json
import os
from functools import lru_cache
from typing import TYPE_CHECKING, List, Optional, Tuple

import regex as re

from ...tokenization_utils import AddedToken, PreTrainedTokenizer
from ...utils import logging


if TYPE_CHECKING:
      from transformers.pipelines.conversational import Conversation

__SCREAMING_SNAKE_CASE			:      Dict      			=logging.get_logger(__name__)

__SCREAMING_SNAKE_CASE			:      Dict      			={
    """vocab_file""": """vocab.json""",
    """merges_file""": """merges.txt""",
}

__SCREAMING_SNAKE_CASE			:      str      			={
    """vocab_file""": {
        """gpt2""": """https://huggingface.co/gpt2/resolve/main/vocab.json""",
        """gpt2-medium""": """https://huggingface.co/gpt2-medium/resolve/main/vocab.json""",
        """gpt2-large""": """https://huggingface.co/gpt2-large/resolve/main/vocab.json""",
        """gpt2-xl""": """https://huggingface.co/gpt2-xl/resolve/main/vocab.json""",
        """distilgpt2""": """https://huggingface.co/distilgpt2/resolve/main/vocab.json""",
    },
    """merges_file""": {
        """gpt2""": """https://huggingface.co/gpt2/resolve/main/merges.txt""",
        """gpt2-medium""": """https://huggingface.co/gpt2-medium/resolve/main/merges.txt""",
        """gpt2-large""": """https://huggingface.co/gpt2-large/resolve/main/merges.txt""",
        """gpt2-xl""": """https://huggingface.co/gpt2-xl/resolve/main/merges.txt""",
        """distilgpt2""": """https://huggingface.co/distilgpt2/resolve/main/merges.txt""",
    },
}

__SCREAMING_SNAKE_CASE			:      str      			={
    """gpt2""": 1_024,
    """gpt2-medium""": 1_024,
    """gpt2-large""": 1_024,
    """gpt2-xl""": 1_024,
    """distilgpt2""": 1_024,
}

@lru_cache()
def 	lowerCAmelCase_	(     )    ->	Dict:


      '''simple docstring'''




      lowerCamelCase__					     = (
          list(range(ord('!'  )   , ord('~'  ) + 1  )  ) + list(range(ord('¡'  )   , ord('¬'  ) + 1  )  ) + list(range(ord('®'  )   , ord('ÿ'  ) + 1  )  )
      )
      lowerCamelCase__					     = bs[:]
      lowerCamelCase__					     = 0
      for b in range(2**8  ):
            if b not in bs:
                  bs.append(lowerCamelCase  )
                  cs.append(2**8 + n  )
                  n += 1
      lowerCamelCase__					     = [chr(lowerCamelCase  ) for n in cs]
      return dict(zip(lowerCamelCase   , lowerCamelCase  )  )

def 	lowerCAmelCase_	(     lowerCamelCase:				Optional[Any]  )    ->	int:


      '''simple docstring'''




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






class 	A	(						_lowerCAmelCase						):
     """simple docstring"""

     _snake_case:		Dict   =VOCAB_FILES_NAMES
     _snake_case:		Dict   =PRETRAINED_VOCAB_FILES_MAP
     _snake_case:		Tuple   =PRETRAINED_POSITIONAL_EMBEDDINGS_SIZES
     _snake_case:		Tuple   =["input_ids", "attention_mask"]




     def __init__(			self     :      Any		,     A__     :      Tuple		,     A__     :      Optional[Any]		,     A__     :      int="replace"		,     A__     :      str="<|endoftext|>"		,     A__     :      Any="<|endoftext|>"		,     A__     :      Any="<|endoftext|>"		,     A__     :      Tuple=None		,     A__     :      Tuple=False		,     A__     :      Tuple=False		,     **A__     :      Tuple		,     ) ->				Dict:
           lowerCamelCase__					     = AddedToken(A__		,     lstrip=A__		,     rstrip=A__	) if isinstance(A__		,     A__	) else bos_token
           lowerCamelCase__					     = AddedToken(A__		,     lstrip=A__		,     rstrip=A__	) if isinstance(A__		,     A__	) else eos_token
           lowerCamelCase__					     = AddedToken(A__		,     lstrip=A__		,     rstrip=A__	) if isinstance(A__		,     A__	) else unk_token
           lowerCamelCase__					     = AddedToken(A__		,     lstrip=A__		,     rstrip=A__	) if isinstance(A__		,     A__	) else pad_token
           super().__init__(
               errors=A__		,     unk_token=A__		,     bos_token=A__		,     eos_token=A__		,     pad_token=A__		,     add_prefix_space=A__		,     add_bos_token=A__		,     **A__		,     )
           lowerCamelCase__					     = add_bos_token

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

           # Should have added re.IGNORECASE so BPE merges can happen for capitalized versions of contractions
           lowerCamelCase__					     = re.compile(R'\'s|\'t|\'re|\'ve|\'m|\'ll|\'d| ?\p{L}+| ?\p{N}+| ?[^\s\p{L}\p{N}]+|\s+(?!\S)|\s+'	)




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




     def        __snake_case      (			self     :      Tuple	) ->				Any:
           return dict(self.encoder		,     **self.added_tokens_encoder	)




     def        __snake_case      (			self     :      List[str]		,     A__     :      Tuple	) ->				Union[str, Any]:
           if token in self.cache:
                 return self.cache[token]
           lowerCamelCase__					     = tuple(A__	)
           lowerCamelCase__					     = get_pairs(A__	)

           if not pairs:
                 return token

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

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




     def        __snake_case      (			self     :      int		,     A__     :      Any		,     A__     :      str=None	) ->				List[Any]:
           if self.add_bos_token:
                 lowerCamelCase__					     = [self.bos_token_id]
           else:
                 lowerCamelCase__					     = []

           lowerCamelCase__					     = bos_token_ids + token_ids_a

           if token_ids_a is None:
                 return output

           return output + bos_token_ids + token_ids_a




     def        __snake_case      (			self     :      Optional[int]		,     A__     :      List[int]		,     A__     :      Optional[List[int]] = None		,     A__     :      bool = False	) ->				List[int]:
           if already_has_special_tokens:
                 return super().get_special_tokens_mask(
                     token_ids_a=A__		,     token_ids_a=A__		,     already_has_special_tokens=A__	)

           if not self.add_bos_token:
                 return super().get_special_tokens_mask(
                     token_ids_a=A__		,     token_ids_a=A__		,     already_has_special_tokens=A__	)

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




     def        __snake_case      (			self     :      List[Any]		,     A__     :      str	) ->				Tuple:
           lowerCamelCase__					     = []
           for token in re.findall(self.pat		,     A__	):
                 lowerCamelCase__					     = ''.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(A__	).split(' '	)	)
           return bpe_tokens




     def        __snake_case      (			self     :      Any		,     A__     :      str	) ->				Optional[Any]:
           return self.encoder.get(A__		,     self.encoder.get(self.unk_token	)	)




     def        __snake_case      (			self     :      str		,     A__     :      Optional[int]	) ->				Optional[Any]:
           return self.decoder.get(A__	)




     def        __snake_case      (			self     :      Tuple		,     A__     :      Optional[int]	) ->				Optional[Any]:
           lowerCamelCase__					     = ''.join(A__	)
           lowerCamelCase__					     = bytearray([self.byte_decoder[c] for c in text]	).decode('utf-8'		,     errors=self.errors	)
           return text




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

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

           lowerCamelCase__					     = 0
           with open(A__		,     '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!'	)
                             lowerCamelCase__					     = token_index
                       writer.write(' '.join(A__	) + '\n'	)
                       index += 1

           return vocab_file, merge_file




     def        __snake_case      (			self     :      Tuple		,     A__     :      Tuple		,     A__     :      Optional[int]=False		,     **A__     :      Optional[Any]	) ->				List[Any]:
           lowerCamelCase__					     = kwargs.pop('add_prefix_space'		,     self.add_prefix_space	)
           if is_split_into_words or add_prefix_space:
                 lowerCamelCase__					     = ' ' + text
           return (text, kwargs)




     def        __snake_case      (			self     :      List[str]		,     A__     :      "Conversation"	) ->				List[int]:
           lowerCamelCase__					     = []
           for is_user, text in conversation.iter_texts():
                 input_ids.extend(self.encode(A__		,     add_special_tokens=A__	) + [self.eos_token_id]	)
           if len(A__	) > self.model_max_length:
                 lowerCamelCase__					     = input_ids[-self.model_max_length :]
           return input_ids


"""simple docstring"""




import copy

from ...configuration_utils import PretrainedConfig
from ...utils import logging


__A     :    str    =		logging.get_logger(__name__)

__A     :    Union[str, Any]    =		{
    'facebook/sam-vit-huge': 'https://huggingface.co/facebook/sam-vit-huge/resolve/main/config.json',
    'facebook/sam-vit-large': 'https://huggingface.co/facebook/sam-vit-large/resolve/main/config.json',
    'facebook/sam-vit-base': 'https://huggingface.co/facebook/sam-vit-base/resolve/main/config.json',
}





class 			__UpperCamelCase (   _A						):


		def __init__(self :		int     ,     __SCREAMING_SNAKE_CASE :		Optional[int]=2_5_6     ,     __SCREAMING_SNAKE_CASE :		List[str]=1_0_2_4     ,     __SCREAMING_SNAKE_CASE :		Optional[int]=1_6     ,     __SCREAMING_SNAKE_CASE :		Optional[int]=1_6     ,     __SCREAMING_SNAKE_CASE :		List[str]=4     ,     __SCREAMING_SNAKE_CASE :		List[Any]="gelu"     ,     __SCREAMING_SNAKE_CASE :		str=1E-6     ,     **__SCREAMING_SNAKE_CASE :		Optional[int]     ,     ):
							super().__init__(**__SCREAMING_SNAKE_CASE)
							A			=					hidden_size
							A			=					image_size
							A			=					patch_size
							A			=					image_size // patch_size
							A			=					mask_input_channels
							A			=					num_point_embeddings
							A			=					hidden_act
							A			=					layer_norm_eps





class 			__UpperCamelCase (   _A						):


		def __init__(self :		List[Any]     ,     __SCREAMING_SNAKE_CASE :		Tuple=2_5_6     ,     __SCREAMING_SNAKE_CASE :		str="relu"     ,     __SCREAMING_SNAKE_CASE :		List[Any]=2_0_4_8     ,     __SCREAMING_SNAKE_CASE :		Tuple=2     ,     __SCREAMING_SNAKE_CASE :		Any=8     ,     __SCREAMING_SNAKE_CASE :		Union[str, Any]=2     ,     __SCREAMING_SNAKE_CASE :		Optional[int]=3     ,     __SCREAMING_SNAKE_CASE :		List[Any]=3     ,     __SCREAMING_SNAKE_CASE :		Tuple=2_5_6     ,     __SCREAMING_SNAKE_CASE :		int=1E-6     ,     **__SCREAMING_SNAKE_CASE :		int     ,     ):
							super().__init__(**__SCREAMING_SNAKE_CASE)
							A			=					hidden_size
							A			=					hidden_act
							A			=					mlp_dim
							A			=					num_hidden_layers
							A			=					num_attention_heads
							A			=					attention_downsample_rate
							A			=					num_multimask_outputs
							A			=					iou_head_depth
							A			=					iou_head_hidden_dim
							A			=					layer_norm_eps





class 			__UpperCamelCase (   _A						):


		def __init__(self :		List[str]     ,     __SCREAMING_SNAKE_CASE :		List[Any]=7_6_8     ,     __SCREAMING_SNAKE_CASE :		int=2_5_6     ,     __SCREAMING_SNAKE_CASE :		Tuple=1_2     ,     __SCREAMING_SNAKE_CASE :		str=1_2     ,     __SCREAMING_SNAKE_CASE :		Any=3     ,     __SCREAMING_SNAKE_CASE :		Dict=1_0_2_4     ,     __SCREAMING_SNAKE_CASE :		str=1_6     ,     __SCREAMING_SNAKE_CASE :		Tuple="gelu"     ,     __SCREAMING_SNAKE_CASE :		int=1E-06     ,     __SCREAMING_SNAKE_CASE :		Dict=0.0     ,     __SCREAMING_SNAKE_CASE :		str=1E-10     ,     __SCREAMING_SNAKE_CASE :		List[str]=True     ,     __SCREAMING_SNAKE_CASE :		Union[str, Any]=4.0     ,     __SCREAMING_SNAKE_CASE :		str=True     ,     __SCREAMING_SNAKE_CASE :		Any=True     ,     __SCREAMING_SNAKE_CASE :		Optional[int]=1_4     ,     __SCREAMING_SNAKE_CASE :		Tuple=[2, 5, 8, 1_1]     ,     __SCREAMING_SNAKE_CASE :		str=1_2_8     ,     __SCREAMING_SNAKE_CASE :		Optional[int]=None     ,     **__SCREAMING_SNAKE_CASE :		Optional[Any]     ,     ):
							super().__init__(**__SCREAMING_SNAKE_CASE)

							A			=					hidden_size
							A			=					output_channels
							A			=					num_hidden_layers
							A			=					num_attention_heads
							A			=					num_channels
							A			=					image_size
							A			=					patch_size
							A			=					hidden_act
							A			=					layer_norm_eps
							A			=					attention_dropout
							A			=					initializer_range
							A			=					qkv_bias
							A			=					mlp_ratio
							A			=					use_abs_pos
							A			=					use_rel_pos
							A			=					window_size
							A			=					global_attn_indexes
							A			=					num_pos_feats
							A			=					int(hidden_size * mlp_ratio) if mlp_dim is None else mlp_dim





class 			__UpperCamelCase (   _A						):
		SCREAMING_SNAKE_CASE								=    "sam"
		SCREAMING_SNAKE_CASE								=    True


		def __init__(self :		Optional[int]     ,     __SCREAMING_SNAKE_CASE :		Dict=None     ,     __SCREAMING_SNAKE_CASE :		Union[str, Any]=None     ,     __SCREAMING_SNAKE_CASE :		Optional[int]=None     ,     __SCREAMING_SNAKE_CASE :		List[Any]=0.0_2     ,     **__SCREAMING_SNAKE_CASE :		Optional[Any]     ,     ):
							super().__init__(**__SCREAMING_SNAKE_CASE)
							A			=					vision_config if vision_config is not None else {}
							A			=					prompt_encoder_config if prompt_encoder_config is not None else {}
							A			=					mask_decoder_config if mask_decoder_config is not None else {}

							if isinstance(__SCREAMING_SNAKE_CASE     ,     __SCREAMING_SNAKE_CASE):
												A			=					vision_config.to_dict()
							if isinstance(__SCREAMING_SNAKE_CASE     ,     __SCREAMING_SNAKE_CASE):
												A			=					prompt_encoder_config.to_dict()
							if isinstance(__SCREAMING_SNAKE_CASE     ,     __SCREAMING_SNAKE_CASE):
												A			=					mask_decoder_config.to_dict()

							A			=					SamVisionConfig(**__SCREAMING_SNAKE_CASE)
							A			=					SamPromptEncoderConfig(**__SCREAMING_SNAKE_CASE)
							A			=					SamMaskDecoderConfig(**__SCREAMING_SNAKE_CASE)
							A			=					initializer_range


		def 					SCREAMING_SNAKE_CASE__   (self :		List[str]):
							A			=					copy.deepcopy(self.__dict__)
							A			=					self.vision_config.to_dict()
							A			=					self.prompt_encoder_config.to_dict()
							A			=					self.mask_decoder_config.to_dict()
							A			=					self.__class__.model_type
							return output





