


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

from transformers.utils import is_jieba_available, requires_backends


if is_jieba_available():
   import jieba

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


UpperCAmelCase_      : Any  					=       logging.get_logger(__name__)

UpperCAmelCase_      : Dict  					=       {'vocab_file': 'vocab.txt'}

UpperCAmelCase_      : Optional[int]  					=       {
    'vocab_file': {
        'openbmb/cpm-ant-10b': 'https://huggingface.co/openbmb/cpm-ant-10b/blob/main/vocab.txt',
    },
}

UpperCAmelCase_      : Tuple  					=       {
    'openbmb/cpm-ant-10b': 1024,
}







def        SCREAMING_SNAKE_CASE_						(			__A :			Tuple				)	->		Tuple:

       """simple docstring"""

       a_					:		Union[str, Any]							=  collections.OrderedDict()
       with open(__A  ,    'r'  ,    encoding='utf-8'				) as reader:
              a_					:		int							=  reader.readlines()
       for index, token in enumerate(__A				):
              a_					:		Union[str, Any]							=  token.rstrip('\n'				)
              a_					:		Union[str, Any]							=  index
       return vocab
class  SCREAMING_SNAKE_CASE__  (				lowercase__			):
      def __init__(       self				:       int     ,							SCREAMING_SNAKE_CASE__				:       int     ,							SCREAMING_SNAKE_CASE__				:       List[str]="<unk>"     ,							SCREAMING_SNAKE_CASE__				:       Optional[Any]=2_0_0     )		->			List[str]:
             a_					:		List[Any]							=  vocab
             a_					:		Tuple							=  unk_token
             a_					:		Tuple							=  max_input_chars_per_word

      def        SCREAMING_SNAKE_CASE							(       self				:       List[Any]     ,							SCREAMING_SNAKE_CASE__				:       Union[str, Any]     )		->			Dict:
             a_					:		Any							=  list(SCREAMING_SNAKE_CASE__     )
             if len(SCREAMING_SNAKE_CASE__     ) > self.max_input_chars_per_word:
                    return [self.unk_token]

             a_					:		Tuple							=  0
             a_					:		Union[str, Any]							=  []
             while start < len(SCREAMING_SNAKE_CASE__     ):
                    a_					:		List[Any]							=  len(SCREAMING_SNAKE_CASE__     )
                    a_					:		List[Any]							=  None
                    while start < end:
                           a_					:		Dict							=  ''.join(chars[start:end]     )
                           if substr in self.vocab:
                                  a_					:		int							=  substr
                                  break
                           end -= 1
                    if cur_substr is None:
                           sub_tokens.append(self.unk_token     )
                           start += 1
                    else:
                           sub_tokens.append(SCREAMING_SNAKE_CASE__     )
                           a_					:		Union[str, Any]							=  end

             return sub_tokens
class  SCREAMING_SNAKE_CASE__  (				lowercase__			):
      snake_case__				:     Optional[int]        =						VOCAB_FILES_NAMES
      snake_case__				:     Dict        =						PRETRAINED_VOCAB_FILES_MAP
      snake_case__				:     List[Any]        =						PRETRAINED_POSITIONAL_EMBEDDINGS_SIZES
      snake_case__				:     str        =						['''input_ids''', '''attention_mask''']
      snake_case__				:     Union[str, Any]        =						False
      def __init__(       self				:       Tuple     ,							SCREAMING_SNAKE_CASE__				:       Tuple     ,							SCREAMING_SNAKE_CASE__				:       Dict="<d>"     ,							SCREAMING_SNAKE_CASE__				:       Union[str, Any]="</d>"     ,							SCREAMING_SNAKE_CASE__				:       List[Any]="<s>"     ,							SCREAMING_SNAKE_CASE__				:       Optional[int]="</s>"     ,							SCREAMING_SNAKE_CASE__				:       Tuple="<pad>"     ,							SCREAMING_SNAKE_CASE__				:       str="<unk>"     ,							SCREAMING_SNAKE_CASE__				:       str="</n>"     ,							SCREAMING_SNAKE_CASE__				:       Any="</_>"     ,							SCREAMING_SNAKE_CASE__				:       Tuple="left"     ,							**SCREAMING_SNAKE_CASE__				:       Dict     ,							)		->			Union[str, Any]:
             requires_backends(self     ,							['jieba']     )
             super().__init__(
                 bod_token=SCREAMING_SNAKE_CASE__     ,							eod_token=SCREAMING_SNAKE_CASE__     ,							bos_token=SCREAMING_SNAKE_CASE__     ,							eos_token=SCREAMING_SNAKE_CASE__     ,							pad_token=SCREAMING_SNAKE_CASE__     ,							unk_token=SCREAMING_SNAKE_CASE__     ,							line_token=SCREAMING_SNAKE_CASE__     ,							space_token=SCREAMING_SNAKE_CASE__     ,							padding_side=SCREAMING_SNAKE_CASE__     ,							**SCREAMING_SNAKE_CASE__     ,							)
             a_					:		Tuple							=  bod_token
             a_					:		str							=  eod_token
             a_					:		Optional[int]							=  load_vocab(SCREAMING_SNAKE_CASE__     )
             a_					:		Tuple							=  self.encoder[space_token]
             a_					:		Any							=  self.encoder[line_token]

             del self.encoder[space_token]
             del self.encoder[line_token]

             a_					:		str							=  collections.OrderedDict(sorted(self.encoder.items()     ,							key=lambda SCREAMING_SNAKE_CASE__     : x[1]     )     )
             a_					:		List[Any]							=  {v: k for k, v in self.encoder.items()}

             a_					:		str							=  WordpieceTokenizer(vocab=self.encoder     ,							unk_token=self.unk_token     )
      @property
      def        SCREAMING_SNAKE_CASE							(       self				:       Dict     )		->			int:
             return self.encoder[self.bod_token]
      @property
      def        SCREAMING_SNAKE_CASE							(       self				:       List[Any]     )		->			Optional[Any]:
             return self.encoder[self.eod_token]
      @property
      def        SCREAMING_SNAKE_CASE							(       self				:       Optional[int]     )		->			List[Any]:
             return self.encoder["\n"]
      @property
      def        SCREAMING_SNAKE_CASE							(       self				:       List[str]     )		->			int:
             return len(self.encoder     )
      def        SCREAMING_SNAKE_CASE							(       self				:       str     )		->			Union[str, Any]:
             return dict(self.encoder     ,							**self.added_tokens_encoder     )
      def        SCREAMING_SNAKE_CASE							(       self				:       Optional[int]     ,							SCREAMING_SNAKE_CASE__				:       Optional[Any]     )		->			Dict:
             a_					:		Union[str, Any]							=  []
             for x in jieba.cut(SCREAMING_SNAKE_CASE__     ,							cut_all=SCREAMING_SNAKE_CASE__     ):
                    output_tokens.extend(self.wordpiece_tokenizer.tokenize(SCREAMING_SNAKE_CASE__     )     )
             return output_tokens
      def        SCREAMING_SNAKE_CASE							(       self				:       str     ,							SCREAMING_SNAKE_CASE__				:       List[str]     ,							**SCREAMING_SNAKE_CASE__				:       str     )		->			List[Any]:
             a_					:		Optional[Any]							=  [i for i in token_ids if i >= 0]
             a_					:		int							=  [
                 x for x in token_ids if x != self.pad_token_id and x != self.eos_token_id and x != self.bos_token_id
             ]
             return super()._decode(SCREAMING_SNAKE_CASE__     ,							**SCREAMING_SNAKE_CASE__     )
      def        SCREAMING_SNAKE_CASE							(       self				:       Tuple     ,							SCREAMING_SNAKE_CASE__				:       List[Any]     )		->			int:
             return token in self.encoder
      def        SCREAMING_SNAKE_CASE							(       self				:       Optional[int]     ,							SCREAMING_SNAKE_CASE__				:       List[str]     )		->			str:
             return "".join(SCREAMING_SNAKE_CASE__     )
      def        SCREAMING_SNAKE_CASE							(       self				:       str     ,							SCREAMING_SNAKE_CASE__				:       Dict     )		->			Union[str, Any]:
             return self.encoder.get(SCREAMING_SNAKE_CASE__     ,							self.encoder.get(self.unk_token     )     )
      def        SCREAMING_SNAKE_CASE							(       self				:       Optional[int]     ,							SCREAMING_SNAKE_CASE__				:       List[str]     )		->			Dict:
             return self.decoder.get(SCREAMING_SNAKE_CASE__     ,							self.unk_token     )
      def        SCREAMING_SNAKE_CASE							(       self				:       int     ,							SCREAMING_SNAKE_CASE__				:       str     ,							SCREAMING_SNAKE_CASE__				:       Optional[str] = None     )		->			Tuple[str]:
             if os.path.isdir(SCREAMING_SNAKE_CASE__     ):
                    a_					:		str							=  os.path.join(
                        SCREAMING_SNAKE_CASE__     ,							(filename_prefix + '-' if filename_prefix else '') + VOCAB_FILES_NAMES['vocab_file']     )
             else:
                    a_					:		str							=  (filename_prefix + '-' if filename_prefix else '') + save_directory
             a_					:		int							=  0
             if " " in self.encoder:
                    a_					:		List[str]							=  self.encoder[' ']
                    del self.encoder[" "]
             if "\n" in self.encoder:
                    a_					:		Union[str, Any]							=  self.encoder['\n']
                    del self.encoder["\n"]
             a_					:		List[Any]							=  collections.OrderedDict(sorted(self.encoder.items()     ,							key=lambda SCREAMING_SNAKE_CASE__     : x[1]     )     )
             with open(SCREAMING_SNAKE_CASE__     ,							'w'     ,							encoding='utf-8'     ) as writer:
                    for token, token_index in self.encoder.items():
                           if index != token_index:
                                  logger.warning(
                                      F"""Saving vocabulary to {vocab_file}: vocabulary indices are not consecutive."""
                                      ' Please check that the vocabulary is not corrupted!'     )
                                  a_					:		Optional[Any]							=  token_index
                           writer.write(token + '\n'     )
                           index += 1
             return (vocab_file,)
      def        SCREAMING_SNAKE_CASE							(       self				:       Tuple     ,							SCREAMING_SNAKE_CASE__				:       List[int]     ,							SCREAMING_SNAKE_CASE__				:       List[int] = None     )		->			List[int]:
             if token_ids_a is None:
                    return [self.bos_token_id] + token_ids_a
             return [self.bos_token_id] + token_ids_a + [self.bos_token_id] + token_ids_a

      def        SCREAMING_SNAKE_CASE							(       self				:       List[Any]     ,							SCREAMING_SNAKE_CASE__				:       List[int]     ,							SCREAMING_SNAKE_CASE__				:       Optional[List[int]] = None     ,							SCREAMING_SNAKE_CASE__				:       bool = False     )		->			List[int]:

             if already_has_special_tokens:
                    return super().get_special_tokens_mask(
                        token_ids_a=SCREAMING_SNAKE_CASE__     ,							token_ids_a=SCREAMING_SNAKE_CASE__     ,							already_has_special_tokens=SCREAMING_SNAKE_CASE__     )

             if token_ids_a is not None:
                    return [1] + ([0] * len(SCREAMING_SNAKE_CASE__     )) + [1] + ([0] * len(SCREAMING_SNAKE_CASE__     ))
             return [1] + ([0] * len(SCREAMING_SNAKE_CASE__     ))





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


lowerCAmelCase_       	=	logging.get_logger(__name__)

lowerCAmelCase_       	=	{
    '''sayakpaul/vit-msn-base''': '''https://huggingface.co/sayakpaul/vit-msn-base/resolve/main/config.json''',
    # See all ViT MSN models at https://huggingface.co/models?filter=vit_msn
}





class 	snake_case_   (		__A					):







			'''simple docstring'''

			SCREAMING_SNAKE_CASE     :   List[Any]									=				"vit_msn"







			def __init__(     self :				Dict							,   _UpperCamelCase :				Optional[int]=7_6_8							,   _UpperCamelCase :				Optional[Any]=1_2							,   _UpperCamelCase :				Union[str, Any]=1_2							,   _UpperCamelCase :				str=3_0_7_2							,   _UpperCamelCase :				Tuple="gelu"							,   _UpperCamelCase :				Dict=0.0							,   _UpperCamelCase :				Dict=0.0							,   _UpperCamelCase :				List[str]=0.02							,   _UpperCamelCase :				List[Any]=1e-06							,   _UpperCamelCase :				Any=2_2_4							,   _UpperCamelCase :				Optional[Any]=1_6							,   _UpperCamelCase :				Any=3							,   _UpperCamelCase :				str=True							,   **_UpperCamelCase :				Any							,   )      ->int:
									super().__init__(**_UpperCamelCase							)

									snake_case_   =	hidden_size
									snake_case_   =	num_hidden_layers
									snake_case_   =	num_attention_heads
									snake_case_   =	intermediate_size
									snake_case_   =	hidden_act
									snake_case_   =	hidden_dropout_prob
									snake_case_   =	attention_probs_dropout_prob
									snake_case_   =	initializer_range
									snake_case_   =	layer_norm_eps
									snake_case_   =	image_size
									snake_case_   =	patch_size
									snake_case_   =	num_channels
									snake_case_   =	qkv_bias