

"""simple docstring"""


import json
from typing import List, Optional, Tuple

from tokenizers import pre_tokenizers, processors

from ...tokenization_utils_base import AddedToken, BatchEncoding
from ...tokenization_utils_fast import PreTrainedTokenizerFast
from ...utils import logging
from .tokenization_mvp import MvpTokenizer


__A						   =			logging.get_logger(__name__)


__A						   =			{"vocab_file": "vocab.json", "merges_file": "merges.txt", "tokenizer_file": "tokenizer.json"}

# See all MVP models at https://huggingface.co/models?filter=mvp
__A						   =			{
    "vocab_file": {
        "RUCAIBox/mvp": "https://huggingface.co/RUCAIBox/mvp/resolve/main/vocab.json",
    },
    "added_tokens.json": {
        "RUCAIBox/mvp": "https://huggingface.co/RUCAIBox/mvp/resolve/main/added_tokens.json",
    },
    "merges_file": {
        "RUCAIBox/mvp": "https://huggingface.co/RUCAIBox/mvp/resolve/main/merges.txt",
    },
    "tokenizer_file": {
        "RUCAIBox/mvp": "https://huggingface.co/RUCAIBox/mvp/resolve/main/tokenizer.json",
    },
}

__A						   =			{
    "RUCAIBox/mvp": 1024,
}





class     snake_case	(				__snake_case  ):
				SCREAMING_SNAKE_CASE_   :      Union[str, Any]         =  VOCAB_FILES_NAMES
				SCREAMING_SNAKE_CASE_   :      str         =  PRETRAINED_VOCAB_FILES_MAP
				SCREAMING_SNAKE_CASE_   :      int         =  PRETRAINED_POSITIONAL_EMBEDDINGS_SIZES
				SCREAMING_SNAKE_CASE_   :      Optional[int]         =  ["""input_ids""", """attention_mask"""]
				SCREAMING_SNAKE_CASE_   :      Union[str, Any]         =  MvpTokenizer

				def __init__(	self							:				Any     ,  UpperCamelCase__							:				int=None     ,  UpperCamelCase__							:				Optional[int]=None     ,  UpperCamelCase__							:				int=None     ,  UpperCamelCase__							:				Tuple="replace"     ,  UpperCamelCase__							:				List[Any]="<s>"     ,  UpperCamelCase__							:				Optional[Any]="</s>"     ,  UpperCamelCase__							:				Any="</s>"     ,  UpperCamelCase__							:				Dict="<s>"     ,  UpperCamelCase__							:				Dict="<unk>"     ,  UpperCamelCase__							:				Tuple="<pad>"     ,  UpperCamelCase__							:				Union[str, Any]="<mask>"     ,  UpperCamelCase__							:				List[str]=False     ,  UpperCamelCase__							:				Any=True     ,  **UpperCamelCase__							:				Optional[Any]     ,  )->   int:



						'''simple docstring'''


						super().__init__(
						    UpperCamelCase__     ,  UpperCamelCase__     ,  tokenizer_file=UpperCamelCase__     ,  errors=UpperCamelCase__     ,  bos_token=UpperCamelCase__     ,  eos_token=UpperCamelCase__     ,  sep_token=UpperCamelCase__     ,  cls_token=UpperCamelCase__     ,  unk_token=UpperCamelCase__     ,  pad_token=UpperCamelCase__     ,  mask_token=UpperCamelCase__     ,  add_prefix_space=UpperCamelCase__     ,  trim_offsets=UpperCamelCase__     ,  **UpperCamelCase__     ,  )

						__lowerCAmelCase:       Dict          =			json.loads(self.backend_tokenizer.pre_tokenizer.__getstate__())
						if pre_tok_state.get("add_prefix_space"     ,  UpperCamelCase__) != add_prefix_space:
								__lowerCAmelCase:       int          =			getattr(UpperCamelCase__     ,  pre_tok_state.pop("type"))
								__lowerCAmelCase:       Optional[Any]          =			add_prefix_space
								__lowerCAmelCase:       Any          =			pre_tok_class(**UpperCamelCase__)

						__lowerCAmelCase:       str          =			add_prefix_space

						# the pre_tokenizer is already updated in the GPT2TokenizerFast `__init__`
						__lowerCAmelCase:       Union[str, Any]          =			"post_processor"
						__lowerCAmelCase:       List[str]          =			getattr(self.backend_tokenizer     ,  UpperCamelCase__     ,  UpperCamelCase__)
						if tokenizer_component_instance:
								__lowerCAmelCase:       str          =			json.loads(tokenizer_component_instance.__getstate__())

								# The lists 'sep' and 'cls' must be cased in tuples for the object `post_processor_class`
								if "sep" in state:
										__lowerCAmelCase:       List[str]          =			tuple(state["sep"])
								if "cls" in state:
										__lowerCAmelCase:       List[str]          =			tuple(state["cls"])

								__lowerCAmelCase:       str          =			False

								if state.get("add_prefix_space"     ,  UpperCamelCase__) != add_prefix_space:
										__lowerCAmelCase:       Optional[int]          =			add_prefix_space
										__lowerCAmelCase:       Optional[Any]          =			True

								if state.get("trim_offsets"     ,  UpperCamelCase__) != trim_offsets:
										__lowerCAmelCase:       int          =			trim_offsets
										__lowerCAmelCase:       Union[str, Any]          =			True

								if changes_to_apply:
										__lowerCAmelCase:       int          =			getattr(UpperCamelCase__     ,  state.pop("type"))
										__lowerCAmelCase:       Optional[Any]          =			component_class(**UpperCamelCase__)
										setattr(self.backend_tokenizer     ,  UpperCamelCase__     ,  UpperCamelCase__)

				@property
				def 							lowercase_     (	self							:				List[str])->   str:



						'''simple docstring'''


						if self._mask_token is None:
								if self.verbose:
										logger.error("Using mask_token, but it is not set yet.")
								return None
						return str(self._mask_token)

				@mask_token.setter
				def 							lowercase_     (	self							:				Optional[int]     ,  UpperCamelCase__							:				List[str])->   List[Any]:



						'''simple docstring'''


						__lowerCAmelCase:       Tuple          =			AddedToken(UpperCamelCase__     ,  lstrip=UpperCamelCase__     ,  rstrip=UpperCamelCase__) if isinstance(UpperCamelCase__     ,  UpperCamelCase__) else value
						__lowerCAmelCase:       int          =			value

				def 							lowercase_     (	self							:				List[Any]     ,  *UpperCamelCase__							:				int     ,  **UpperCamelCase__							:				str)->   BatchEncoding:



						'''simple docstring'''


						__lowerCAmelCase:       Tuple          =			kwargs.get("is_split_into_words"     ,  UpperCamelCase__)

						if is_split_into_words and not self.add_prefix_space:
								raise ValueError(
								    f"You need to instantiate {self.__class__.__name__} with add_prefix_space=True "
								    "to use it with pretokenized inputs.")

						return super()._batch_encode_plus(*UpperCamelCase__     ,  **UpperCamelCase__)

				def 							lowercase_     (	self							:				int     ,  *UpperCamelCase__							:				str     ,  **UpperCamelCase__							:				Any)->   BatchEncoding:



						'''simple docstring'''


						__lowerCAmelCase:       int          =			kwargs.get("is_split_into_words"     ,  UpperCamelCase__)

						if is_split_into_words and not self.add_prefix_space:
								raise ValueError(
								    f"You need to instantiate {self.__class__.__name__} with add_prefix_space=True "
								    "to use it with pretokenized inputs.")

						return super()._encode_plus(*UpperCamelCase__     ,  **UpperCamelCase__)

				def 							lowercase_     (	self							:				Optional[Any]     ,  UpperCamelCase__							:				str     ,  UpperCamelCase__							:				Optional[str] = None)->   Tuple[str]:



						'''simple docstring'''


						__lowerCAmelCase:       Dict          =			self._tokenizer.model.save(UpperCamelCase__     ,  name=UpperCamelCase__)
						return tuple(UpperCamelCase__)

				def 							lowercase_     (	self							:				int     ,  UpperCamelCase__							:				Tuple     ,  UpperCamelCase__							:				List[str]=None)->   Tuple:



						'''simple docstring'''


						__lowerCAmelCase:       Dict          =			[self.bos_token_id] + token_ids_a + [self.eos_token_id]
						if token_ids_a is None:
								return output

						return output + [self.eos_token_id] + token_ids_a + [self.eos_token_id]




				def 							lowercase_     (	self							:				Optional[Any]     ,  UpperCamelCase__							:				List[int]     ,  UpperCamelCase__							:				Optional[List[int]] = None)->   List[int]:



						'''simple docstring'''


						__lowerCAmelCase:       List[Any]          =			[self.sep_token_id]
						__lowerCAmelCase:       List[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 + sep + token_ids_a + sep) * [0]





"""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


__A						   =			logging.get_logger(__name__)

__A						   =			{
    "microsoft/beit-base-patch16-224-pt22k": (
        "https://huggingface.co/microsoft/beit-base-patch16-224-pt22k/resolve/main/config.json"
    ),
    # See all BEiT models at https://huggingface.co/models?filter=beit
}





class     snake_case	(				__snake_case  ):
				SCREAMING_SNAKE_CASE_   :      Tuple         =  """beit"""

				def __init__(	self							:				List[Any]     ,  UpperCamelCase__							:				List[str]=8_1_9_2     ,  UpperCamelCase__							:				Dict=7_6_8     ,  UpperCamelCase__							:				List[str]=1_2     ,  UpperCamelCase__							:				Union[str, Any]=1_2     ,  UpperCamelCase__							:				Dict=3_0_7_2     ,  UpperCamelCase__							:				Optional[int]="gelu"     ,  UpperCamelCase__							:				Tuple=0.0     ,  UpperCamelCase__							:				Tuple=0.0     ,  UpperCamelCase__							:				Union[str, Any]=0.02     ,  UpperCamelCase__							:				Optional[Any]=1e-12     ,  UpperCamelCase__							:				str=2_2_4     ,  UpperCamelCase__							:				str=1_6     ,  UpperCamelCase__							:				Union[str, Any]=3     ,  UpperCamelCase__							:				Optional[int]=False     ,  UpperCamelCase__							:				int=False     ,  UpperCamelCase__							:				Optional[Any]=False     ,  UpperCamelCase__							:				Optional[Any]=False     ,  UpperCamelCase__							:				Dict=0.1     ,  UpperCamelCase__							:				List[Any]=0.1     ,  UpperCamelCase__							:				Any=True     ,  UpperCamelCase__							:				Optional[Any]=[3, 5, 7, 1_1]     ,  UpperCamelCase__							:				Optional[Any]=[1, 2, 3, 6]     ,  UpperCamelCase__							:				Optional[Any]=True     ,  UpperCamelCase__							:				Tuple=0.4     ,  UpperCamelCase__							:				Optional[Any]=2_5_6     ,  UpperCamelCase__							:				Optional[int]=1     ,  UpperCamelCase__							:				Optional[int]=False     ,  UpperCamelCase__							:				Optional[Any]=2_5_5     ,  **UpperCamelCase__							:				Optional[int]     ,  )->   int:



						'''simple docstring'''


						super().__init__(**UpperCamelCase__)

						__lowerCAmelCase:       str          =			vocab_size
						__lowerCAmelCase:       List[Any]          =			hidden_size
						__lowerCAmelCase:       str          =			num_hidden_layers
						__lowerCAmelCase:       Tuple          =			num_attention_heads
						__lowerCAmelCase:       Union[str, Any]          =			intermediate_size
						__lowerCAmelCase:       List[Any]          =			hidden_act
						__lowerCAmelCase:       Optional[Any]          =			hidden_dropout_prob
						__lowerCAmelCase:       List[Any]          =			attention_probs_dropout_prob
						__lowerCAmelCase:       str          =			initializer_range
						__lowerCAmelCase:       Optional[Any]          =			layer_norm_eps

						__lowerCAmelCase:       Any          =			image_size
						__lowerCAmelCase:       Any          =			patch_size
						__lowerCAmelCase:       Union[str, Any]          =			num_channels
						__lowerCAmelCase:       Tuple          =			use_mask_token
						__lowerCAmelCase:       Optional[Any]          =			use_absolute_position_embeddings
						__lowerCAmelCase:       List[Any]          =			use_relative_position_bias
						__lowerCAmelCase:       Optional[Any]          =			use_shared_relative_position_bias
						__lowerCAmelCase:       List[str]          =			layer_scale_init_value
						__lowerCAmelCase:       str          =			drop_path_rate
						__lowerCAmelCase:       str          =			use_mean_pooling
						# decode head attributes (semantic segmentation)
						__lowerCAmelCase:       Optional[Any]          =			out_indices
						__lowerCAmelCase:       Union[str, Any]          =			pool_scales
						# auxiliary head attributes (semantic segmentation)
						__lowerCAmelCase:       List[str]          =			use_auxiliary_head
						__lowerCAmelCase:       Union[str, Any]          =			auxiliary_loss_weight
						__lowerCAmelCase:       Optional[int]          =			auxiliary_channels
						__lowerCAmelCase:       Dict          =			auxiliary_num_convs
						__lowerCAmelCase:       List[Any]          =			auxiliary_concat_input
						__lowerCAmelCase:       str          =			semantic_loss_ignore_index





class     snake_case	(				__snake_case  ):
				SCREAMING_SNAKE_CASE_   :      Optional[Any]         =  version.parse("""1.11"""  )

				@property
				def 							lowercase_     (	self							:				str)->   Mapping[str, Mapping[int, str]]:



						'''simple docstring'''


						return OrderedDict(
						    [
						        ("pixel_values", {0: "batch", 1: "num_channels", 2: "height", 3: "width"}),
						    ])




				@property
				def 							lowercase_     (	self							:				Any)->   float:



						'''simple docstring'''


						return 1e-4


