


"""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__				:Optional[int]			   =	logging.get_logger(__name__)

UpperCamelCase__				:List[str]			   =	{"""vocab_file""": """sentencepiece.model"""}

UpperCamelCase__				:List[str]			   =	{
    """vocab_file""": {
        """google/rembert""": """https://huggingface.co/google/rembert/resolve/main/sentencepiece.model""",
    },
}

UpperCamelCase__				:str			   =	{
    """google/rembert""": 256,
}






class      A(  lowerCamelCase__		):

		"""simple docstring"""





		A    =							VOCAB_FILES_NAMES
		A    =							PRETRAINED_VOCAB_FILES_MAP
		A    =							PRETRAINED_POSITIONAL_EMBEDDINGS_SIZES
		def __init__( self					,				SCREAMING_SNAKE_CASE__					,				SCREAMING_SNAKE_CASE__=False					,				SCREAMING_SNAKE_CASE__=True					,				SCREAMING_SNAKE_CASE__=True					,				SCREAMING_SNAKE_CASE__="[CLS]"					,				SCREAMING_SNAKE_CASE__="[SEP]"					,				SCREAMING_SNAKE_CASE__="[UNK]"					,				SCREAMING_SNAKE_CASE__="[SEP]"					,				SCREAMING_SNAKE_CASE__="[PAD]"					,				SCREAMING_SNAKE_CASE__="[CLS]"					,				SCREAMING_SNAKE_CASE__="[MASK]"					,				**SCREAMING_SNAKE_CASE__					,				)      ->	str:

					"""simple docstring"""



					super().__init__(
					    do_lower_case=SCREAMING_SNAKE_CASE__					,				remove_space=SCREAMING_SNAKE_CASE__					,				keep_accents=SCREAMING_SNAKE_CASE__					,				bos_token=SCREAMING_SNAKE_CASE__					,				eos_token=SCREAMING_SNAKE_CASE__					,				unk_token=SCREAMING_SNAKE_CASE__					,				sep_token=SCREAMING_SNAKE_CASE__					,				pad_token=SCREAMING_SNAKE_CASE__					,				cls_token=SCREAMING_SNAKE_CASE__					,				mask_token=SCREAMING_SNAKE_CASE__					,				**SCREAMING_SNAKE_CASE__					,				)

					_UpperCamelCase					:Optional[int]					     =	do_lower_case
					_UpperCamelCase					:int					     =	remove_space
					_UpperCamelCase					:str					     =	keep_accents
					_UpperCamelCase					:List[Any]					     =	vocab_file

					_UpperCamelCase					:Optional[int]					     =	spm.SentencePieceProcessor()
					self.sp_model.Load(SCREAMING_SNAKE_CASE__   )
		@property
		def   _UpperCamelCase( self   )      ->	Optional[int]:

					"""simple docstring"""



					return len(self.sp_model   )
		def   _UpperCamelCase( self   )      ->	Dict:

					"""simple docstring"""



					_UpperCamelCase					:Optional[int]					     =	{self.convert_ids_to_tokens(SCREAMING_SNAKE_CASE__   ): i for i in range(self.vocab_size   )}
					vocab.update(self.added_tokens_encoder   )
					return vocab
		def __getstate__( self   )      ->	Optional[Any]:

					"""simple docstring"""



					_UpperCamelCase					:str					     =	self.__dict__.copy()
					_UpperCamelCase					:List[Any]					     =	None
					return state
		def __setstate__( self					,				SCREAMING_SNAKE_CASE__   )      ->	List[Any]:

					"""simple docstring"""



					_UpperCamelCase					:Any					     =	d
					_UpperCamelCase					:int					     =	spm.SentencePieceProcessor()
					self.sp_model.Load(self.vocab_file   )
		def   _UpperCamelCase( self					,				SCREAMING_SNAKE_CASE__					,				SCREAMING_SNAKE_CASE__=False   )      ->	List[Any]:

					"""simple docstring"""



					_UpperCamelCase					:Tuple					     =	self.sp_model.EncodeAsPieces(SCREAMING_SNAKE_CASE__   )
					return pieces
		def   _UpperCamelCase( self					,				SCREAMING_SNAKE_CASE__   )      ->	str:

					"""simple docstring"""



					return self.sp_model.PieceToId(SCREAMING_SNAKE_CASE__   )
		def   _UpperCamelCase( self					,				SCREAMING_SNAKE_CASE__   )      ->	Optional[Any]:

					"""simple docstring"""



					return self.sp_model.IdToPiece(SCREAMING_SNAKE_CASE__   )
		def   _UpperCamelCase( self					,				SCREAMING_SNAKE_CASE__   )      ->	Dict:

					"""simple docstring"""



					_UpperCamelCase					:int					     =	self.sp_model.decode_pieces(SCREAMING_SNAKE_CASE__   )
					return out_string
		def   _UpperCamelCase( self					,				SCREAMING_SNAKE_CASE__					,				SCREAMING_SNAKE_CASE__ = None   )      ->	List[int]:

					"""simple docstring"""



					_UpperCamelCase					:Optional[Any]					     =	[self.sep_token_id]
					_UpperCamelCase					:Dict					     =	[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					,				SCREAMING_SNAKE_CASE__					,				SCREAMING_SNAKE_CASE__ = None					,				SCREAMING_SNAKE_CASE__ = False   )      ->	List[int]:

					"""simple docstring"""



					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(SCREAMING_SNAKE_CASE__   )) + [1] + ([0] * len(SCREAMING_SNAKE_CASE__   )) + [1]
					return [1] + ([0] * len(SCREAMING_SNAKE_CASE__   )) + [1]
		def   _UpperCamelCase( self					,				SCREAMING_SNAKE_CASE__					,				SCREAMING_SNAKE_CASE__ = None   )      ->	List[int]:

					"""simple docstring"""



					_UpperCamelCase					:Union[str, Any]					     =	[self.sep_token_id]
					_UpperCamelCase					:Union[str, Any]					     =	[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					,				SCREAMING_SNAKE_CASE__					,				SCREAMING_SNAKE_CASE__ = None   )      ->	Tuple[str]:

					"""simple docstring"""



					if not os.path.isdir(SCREAMING_SNAKE_CASE__   ):
								logger.error('''Vocabulary path ({}) should be a directory'''.format(SCREAMING_SNAKE_CASE__   )   )
								return
					_UpperCamelCase					:int					     =	os.path.join(
					    SCREAMING_SNAKE_CASE__					,				(filename_prefix + '''-''' if filename_prefix else '''''') + VOCAB_FILES_NAMES['''vocab_file''']   )

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

					return (out_vocab_file,)





"""simple docstring"""






from collections import OrderedDict
from typing import Mapping

from packaging import version

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


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

UpperCamelCase__				:Union[str, Any]			   =	{
    """google/mobilenet_v2_1.4_224""": """https://huggingface.co/google/mobilenet_v2_1.4_224/resolve/main/config.json""",
    """google/mobilenet_v2_1.0_224""": """https://huggingface.co/google/mobilenet_v2_1.0_224/resolve/main/config.json""",
    """google/mobilenet_v2_0.75_160""": """https://huggingface.co/google/mobilenet_v2_0.75_160/resolve/main/config.json""",
    """google/mobilenet_v2_0.35_96""": """https://huggingface.co/google/mobilenet_v2_0.35_96/resolve/main/config.json""",
    # See all MobileNetV2 models at https://huggingface.co/models?filter=mobilenet_v2
}






class      A(  lowerCamelCase__		):

		"""simple docstring"""





		A    =							"mobilenet_v2"
		def __init__( self					,				SCREAMING_SNAKE_CASE__=3					,				SCREAMING_SNAKE_CASE__=2_24					,				SCREAMING_SNAKE_CASE__=1.0					,				SCREAMING_SNAKE_CASE__=8					,				SCREAMING_SNAKE_CASE__=8					,				SCREAMING_SNAKE_CASE__=6					,				SCREAMING_SNAKE_CASE__=32					,				SCREAMING_SNAKE_CASE__=True					,				SCREAMING_SNAKE_CASE__=True					,				SCREAMING_SNAKE_CASE__="relu6"					,				SCREAMING_SNAKE_CASE__=True					,				SCREAMING_SNAKE_CASE__=0.8					,				SCREAMING_SNAKE_CASE__=0.0_2					,				SCREAMING_SNAKE_CASE__=0.0_0_1					,				SCREAMING_SNAKE_CASE__=2_55					,				**SCREAMING_SNAKE_CASE__					,				)      ->	int:

					"""simple docstring"""



					super().__init__(**SCREAMING_SNAKE_CASE__   )

					if depth_multiplier <= 0:
								raise ValueError('''depth_multiplier must be greater than zero.'''   )

					_UpperCamelCase					:Optional[int]					     =	num_channels
					_UpperCamelCase					:Tuple					     =	image_size
					_UpperCamelCase					:Union[str, Any]					     =	depth_multiplier
					_UpperCamelCase					:Any					     =	depth_divisible_by
					_UpperCamelCase					:Optional[int]					     =	min_depth
					_UpperCamelCase					:Union[str, Any]					     =	expand_ratio
					_UpperCamelCase					:str					     =	output_stride
					_UpperCamelCase					:Tuple					     =	first_layer_is_expansion
					_UpperCamelCase					:Any					     =	finegrained_output
					_UpperCamelCase					:Union[str, Any]					     =	hidden_act
					_UpperCamelCase					:Any					     =	tf_padding
					_UpperCamelCase					:str					     =	classifier_dropout_prob
					_UpperCamelCase					:Optional[Any]					     =	initializer_range
					_UpperCamelCase					:int					     =	layer_norm_eps
					_UpperCamelCase					:Union[str, Any]					     =	semantic_loss_ignore_index






class      A(  lowerCamelCase__		):

		"""simple docstring"""





		A    =							version.parse("1.11"		)
		@property
		def   _UpperCamelCase( self   )      ->	Mapping[str, Mapping[int, str]]:

					"""simple docstring"""



					return OrderedDict([('''pixel_values''', {0: '''batch'''})]   )
		@property
		def   _UpperCamelCase( self   )      ->	Mapping[str, Mapping[int, str]]:

					"""simple docstring"""



					if self.task == "image-classification":
								return OrderedDict([('''logits''', {0: '''batch'''})]   )
					else:
								return OrderedDict([('''last_hidden_state''', {0: '''batch'''}), ('''pooler_output''', {0: '''batch'''})]   )





		@property
		def   _UpperCamelCase( self   )      ->	float:

					"""simple docstring"""



					return 1E-4

