"""simple docstring"""





import os
from shutil import copyfile
from typing import List, Optional, Tuple

import sentencepiece as spm

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


_UpperCamelCase  :		str           =       logging.get_logger(__name__)

_UpperCamelCase  :		Optional[int]           =       {"vocab_file": "sentencepiece.model"}

_UpperCamelCase  :		int           =       {
    "vocab_file": {
        "google/rembert": "https://huggingface.co/google/rembert/resolve/main/sentencepiece.model",
    },
}

_UpperCamelCase  :		Union[str, Any]           =       {
    "google/rembert": 2_56,
}


class 	UpperCAmelCase_      (       lowerCAmelCase_):
      lowerCamelCase__						:       List[str]					    =    VOCAB_FILES_NAMES
      lowerCamelCase__						:       Union[str, Any]					    =    PRETRAINED_VOCAB_FILES_MAP
      lowerCamelCase__						:       Any					    =    PRETRAINED_POSITIONAL_EMBEDDINGS_SIZES


      def __init__(  self						,     a						,     a=False						,     a=True						,     a=True						,     a="[CLS]"						,     a="[SEP]"						,     a="[UNK]"						,     a="[SEP]"						,     a="[PAD]"						,     a="[CLS]"						,     a="[MASK]"						,     **a						,     )			->   List[Any]:
             super().__init__(
                 do_lower_case=__lowerCAmelCase						,     remove_space=__lowerCAmelCase						,     keep_accents=__lowerCAmelCase						,     bos_token=__lowerCAmelCase						,     eos_token=__lowerCAmelCase						,     unk_token=__lowerCAmelCase						,     sep_token=__lowerCAmelCase						,     pad_token=__lowerCAmelCase						,     cls_token=__lowerCAmelCase						,     mask_token=__lowerCAmelCase						,     **__lowerCAmelCase						,     )

             lowercase__     :						Dict         =      do_lower_case
             lowercase__     :						Dict         =      remove_space
             lowercase__     :						int         =      keep_accents
             lowercase__     :						Union[str, Any]         =      vocab_file

             lowercase__     :						Tuple         =      spm.SentencePieceProcessor()
             self.sp_model.Load(__lowerCAmelCase				)


      @property
      def 						_UpperCAmelCase			(  self				)			->   Union[str, Any]:
             return len(self.sp_model				)


      def 						_UpperCAmelCase			(  self				)			->   int:
             lowercase__     :						str         =      {self.convert_ids_to_tokens(__lowerCAmelCase				): i for i in range(self.vocab_size				)}
             vocab.update(self.added_tokens_encoder				)
             return vocab


      def __getstate__(  self				)			->   Any:
             lowercase__     :						Optional[Any]         =      self.__dict__.copy()
             lowercase__     :						Optional[int]         =      None
             return state


      def __setstate__(  self						,     a				)			->   List[str]:
             lowercase__     :						Dict         =      d
             lowercase__     :						Tuple         =      spm.SentencePieceProcessor()
             self.sp_model.Load(self.vocab_file				)


      def 						_UpperCAmelCase			(  self						,     a						,     a=False				)			->   Dict:
             lowercase__     :						List[Any]         =      self.sp_model.EncodeAsPieces(__lowerCAmelCase				)
             return pieces


      def 						_UpperCAmelCase			(  self						,     a				)			->   List[Any]:
             return self.sp_model.PieceToId(__lowerCAmelCase				)


      def 						_UpperCAmelCase			(  self						,     a				)			->   List[str]:
             return self.sp_model.IdToPiece(__lowerCAmelCase				)


      def 						_UpperCAmelCase			(  self						,     a				)			->   int:
             lowercase__     :						Tuple         =      self.sp_model.decode_pieces(__lowerCAmelCase				)
             return out_string


      def 						_UpperCAmelCase			(  self						,     a						,     a = None				)			->   List[str]:
             lowercase__     :						List[Any]         =      [self.sep_token_id]
             lowercase__     :						Optional[int]         =      [self.cls_token_id]
             if token_ids_a is None:
                    return cls + token_ids_a + sep
             return cls + token_ids_a + sep + token_ids_a + sep


      def 						_UpperCAmelCase			(  self						,     a						,     a = None						,     a = False				)			->   Optional[int]:

             if already_has_special_tokens:
                    if token_ids_a is not None:
                           raise ValueError(
                               'You should not supply a second sequence if the provided sequence of '
                               'ids is already formatted with special tokens for the model.'				)
                    return [1 if x in [self.sep_token_id, self.cls_token_id] else 0 for x in token_ids_a]

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


      def 						_UpperCAmelCase			(  self						,     a						,     a = None				)			->   str:
             lowercase__     :						Dict         =      [self.sep_token_id]
             lowercase__     :						int         =      [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				) * [0] + len(token_ids_a + sep				) * [1]


      def 						_UpperCAmelCase			(  self						,     a						,     a = None				)			->   Any:
             if not os.path.isdir(__lowerCAmelCase				):
                    logger.error('Vocabulary path ({}) should be a directory'.format(__lowerCAmelCase				)				)
                    return
             lowercase__     :						int         =      os.path.join(
                 __lowerCAmelCase						,     (filename_prefix + '-' if filename_prefix else '') + VOCAB_FILES_NAMES['vocab_file']				)

             if os.path.abspath(self.vocab_file				) != os.path.abspath(__lowerCAmelCase				):
                    copyfile(self.vocab_file						,     __lowerCAmelCase				)

             return (out_vocab_file,)


"""simple docstring"""


from collections import OrderedDict
from typing import List, Mapping

from packaging import version

from ...configuration_utils import PretrainedConfig
from ...onnx import OnnxConfig
from ...utils import logging


UpperCAmelCase__			=    logging.get_logger(__name__)

UpperCAmelCase__			=    {
    """google/efficientnet-b7""": """https://huggingface.co/google/efficientnet-b7/resolve/main/config.json""",
}


class 							a					(		lowerCAmelCase_ ):
    _snake_case  :	Tuple  				=				'efficientnet'


    def __init__(       self						:	int ,					__lowerCAmelCase						:	int = 3 ,					__lowerCAmelCase						:	int = 600 ,					__lowerCAmelCase						:	float = 2.0 ,					__lowerCAmelCase						:	float = 3.1 ,					__lowerCAmelCase						:	int = 8 ,					__lowerCAmelCase						:	List[int] = [3, 3, 5, 3, 5, 5, 3] ,					__lowerCAmelCase						:	List[int] = [32, 16, 24, 40, 80, 112, 192] ,					__lowerCAmelCase						:	List[int] = [16, 24, 40, 80, 112, 192, 320] ,					__lowerCAmelCase						:	List[int] = [] ,					__lowerCAmelCase						:	List[int] = [1, 2, 2, 2, 1, 2, 1] ,					__lowerCAmelCase						:	List[int] = [1, 2, 2, 3, 3, 4, 1] ,					__lowerCAmelCase						:	List[int] = [1, 6, 6, 6, 6, 6, 6] ,					__lowerCAmelCase						:	float = 0.25 ,					__lowerCAmelCase						:	str = "swish" ,					__lowerCAmelCase						:	int = 2560 ,					__lowerCAmelCase						:	str = "mean" ,					__lowerCAmelCase						:	float = 0.02 ,					__lowerCAmelCase						:	float = 0.001 ,					__lowerCAmelCase						:	float = 0.99 ,					__lowerCAmelCase						:	float = 0.5 ,					__lowerCAmelCase						:	float = 0.2 ,					**__lowerCAmelCase						:	Optional[Any] ,					):
      super().__init__(**__lowerCAmelCase       )

      _UpperCAmelCase    			=   num_channels
      _UpperCAmelCase    			=   image_size
      _UpperCAmelCase    			=   width_coefficient
      _UpperCAmelCase    			=   depth_coefficient
      _UpperCAmelCase    			=   depth_divisor
      _UpperCAmelCase    			=   kernel_sizes
      _UpperCAmelCase    			=   in_channels
      _UpperCAmelCase    			=   out_channels
      _UpperCAmelCase    			=   depthwise_padding
      _UpperCAmelCase    			=   strides
      _UpperCAmelCase    			=   num_block_repeats
      _UpperCAmelCase    			=   expand_ratios
      _UpperCAmelCase    			=   squeeze_expansion_ratio
      _UpperCAmelCase    			=   hidden_act
      _UpperCAmelCase    			=   hidden_dim
      _UpperCAmelCase    			=   pooling_type
      _UpperCAmelCase    			=   initializer_range
      _UpperCAmelCase    			=   batch_norm_eps
      _UpperCAmelCase    			=   batch_norm_momentum
      _UpperCAmelCase    			=   dropout_rate
      _UpperCAmelCase    			=   drop_connect_rate
      _UpperCAmelCase    			=   sum(__lowerCAmelCase       ) * 4



class 							a					(		lowerCAmelCase_ ):
    _snake_case  :	Union[str, Any]  				=				version.parse('1.11' )


    @property
    def   lowerCAmelCase_	(       self						:	Any       ):
      return OrderedDict(
          [
              ("""pixel_values""", {0: """batch""", 1: """num_channels""", 2: """height""", 3: """width"""}),
          ]       )


    @property
    def   lowerCAmelCase_	(       self						:	List[Any]       ):
      return 1e-5
