import copy
import os
from typing import Union

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


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

__lowerCamelCase			: List[str]							   =		{
    '''BridgeTower/bridgetower-base''': '''https://huggingface.co/BridgeTower/bridgetower-base/blob/main/config.json''',
    '''BridgeTower/bridgetower-base-itm-mlm''': (
        '''https://huggingface.co/BridgeTower/bridgetower-base-itm-mlm/blob/main/config.json'''
    ),
}







class __snake_case				(						__UpperCAmelCase		):
   lowerCAmelCase_														=							"bridgetower_vision_model"




   def __init__(    self			:				Optional[Any]       ,	_lowercase			:				Optional[int]=7_68       ,	_lowercase			:				List[Any]=12       ,	_lowercase			:				List[str]=3       ,	_lowercase			:				List[Any]=16       ,	_lowercase			:				List[str]=2_88       ,	_lowercase			:				Tuple=1       ,	_lowercase			:				str=1E-05       ,	_lowercase			:				Optional[int]=False       ,	_lowercase			:				Dict=True       ,	_lowercase			:				Tuple=False       ,	**_lowercase			:				List[Any]       ,	):



     """simple docstring"""






     super().__init__(**UpperCamelCase__      )
     SCREAMING_SNAKE_CASE__										=      hidden_size
     SCREAMING_SNAKE_CASE__										=      num_hidden_layers
     SCREAMING_SNAKE_CASE__										=      num_channels
     SCREAMING_SNAKE_CASE__										=      patch_size
     SCREAMING_SNAKE_CASE__										=      image_size
     SCREAMING_SNAKE_CASE__										=      initializer_factor
     SCREAMING_SNAKE_CASE__										=      layer_norm_eps
     SCREAMING_SNAKE_CASE__										=      stop_gradient
     SCREAMING_SNAKE_CASE__										=      share_layernorm
     SCREAMING_SNAKE_CASE__										=      remove_last_layer




   @classmethod
   def 	__a						(    cls			:				Any       ,	_lowercase			:				Optional[int]       ,	**_lowercase			:				Union[str, Any]      ):



     """simple docstring"""






     SCREAMING_SNAKE_CASE__							,     SCREAMING_SNAKE_CASE__										=      cls.get_config_dict(UpperCamelCase__       ,	**UpperCamelCase__      )

     if config_dict.get("""model_type"""      ) == "bridgetower":
       SCREAMING_SNAKE_CASE__										=      config_dict["""text_config"""]

     if "model_type" in config_dict and hasattr(cls       ,	"""model_type"""      ) and config_dict["model_type"] != cls.model_type:
       logger.warning(
           f"""You are using a model of type {config_dict['model_type']} to instantiate a model of type """
           f"""{cls.model_type}. This is not supported for all configurations of models and can yield errors."""      )

     return cls.from_dict(UpperCamelCase__       ,	**UpperCamelCase__      )







class __snake_case				(						__UpperCAmelCase		):
   lowerCAmelCase_														=							"bridgetower_text_model"




   def __init__(    self			:				Dict       ,	_lowercase			:				Dict=5_02_65       ,	_lowercase			:				Dict=7_68       ,	_lowercase			:				str=12       ,	_lowercase			:				Optional[Any]=12       ,	_lowercase			:				List[str]=1       ,	_lowercase			:				Optional[Any]=30_72       ,	_lowercase			:				int="gelu"       ,	_lowercase			:				List[str]=0.1       ,	_lowercase			:				List[str]=0.1       ,	_lowercase			:				List[Any]=5_14       ,	_lowercase			:				Any=1       ,	_lowercase			:				Dict=1E-05       ,	_lowercase			:				Tuple=1       ,	_lowercase			:				Tuple=0       ,	_lowercase			:				Any=2       ,	_lowercase			:				Dict="absolute"       ,	_lowercase			:				Any=True       ,	**_lowercase			:				int       ,	):



     """simple docstring"""






     super().__init__(**UpperCamelCase__      )

     SCREAMING_SNAKE_CASE__										=      vocab_size
     SCREAMING_SNAKE_CASE__										=      hidden_size
     SCREAMING_SNAKE_CASE__										=      num_hidden_layers
     SCREAMING_SNAKE_CASE__										=      num_attention_heads
     SCREAMING_SNAKE_CASE__										=      hidden_act
     SCREAMING_SNAKE_CASE__										=      initializer_factor
     SCREAMING_SNAKE_CASE__										=      intermediate_size
     SCREAMING_SNAKE_CASE__										=      hidden_dropout_prob
     SCREAMING_SNAKE_CASE__										=      attention_probs_dropout_prob
     SCREAMING_SNAKE_CASE__										=      max_position_embeddings
     SCREAMING_SNAKE_CASE__										=      type_vocab_size
     SCREAMING_SNAKE_CASE__										=      layer_norm_eps
     SCREAMING_SNAKE_CASE__										=      position_embedding_type
     SCREAMING_SNAKE_CASE__										=      use_cache
     SCREAMING_SNAKE_CASE__										=      pad_token_id
     SCREAMING_SNAKE_CASE__										=      bos_token_id
     SCREAMING_SNAKE_CASE__										=      eos_token_id




   @classmethod
   def 	__a						(    cls			:				Union[str, Any]       ,	_lowercase			:				Optional[int]       ,	**_lowercase			:				List[str]      ):



     """simple docstring"""






     SCREAMING_SNAKE_CASE__							,     SCREAMING_SNAKE_CASE__										=      cls.get_config_dict(UpperCamelCase__       ,	**UpperCamelCase__      )

     if config_dict.get("""model_type"""      ) == "bridgetower":
       SCREAMING_SNAKE_CASE__										=      config_dict["""text_config"""]

     if "model_type" in config_dict and hasattr(cls       ,	"""model_type"""      ) and config_dict["model_type"] != cls.model_type:
       logger.warning(
           f"""You are using a model of type {config_dict['model_type']} to instantiate a model of type """
           f"""{cls.model_type}. This is not supported for all configurations of models and can yield errors."""      )

     return cls.from_dict(UpperCamelCase__       ,	**UpperCamelCase__      )







class __snake_case				(						__UpperCAmelCase		):
   lowerCAmelCase_														=							"bridgetower"




   def __init__(    self			:				int       ,	_lowercase			:				List[Any]=True       ,	_lowercase			:				str="gelu"       ,	_lowercase			:				Tuple=7_68       ,	_lowercase			:				Dict=1       ,	_lowercase			:				Any=1E-05       ,	_lowercase			:				Tuple=False       ,	_lowercase			:				Optional[int]="add"       ,	_lowercase			:				str=12       ,	_lowercase			:				List[str]=6       ,	_lowercase			:				Tuple=False       ,	_lowercase			:				str=False       ,	_lowercase			:				Dict=None       ,	_lowercase			:				List[Any]=None       ,	**_lowercase			:				str       ,	):



     """simple docstring"""






     SCREAMING_SNAKE_CASE__										=      kwargs.pop("""text_config_dict"""       ,	UpperCamelCase__      )
     SCREAMING_SNAKE_CASE__										=      kwargs.pop("""vision_config_dict"""       ,	UpperCamelCase__      )

     super().__init__(**UpperCamelCase__      )
     SCREAMING_SNAKE_CASE__										=      share_cross_modal_transformer_layers
     SCREAMING_SNAKE_CASE__										=      hidden_act
     SCREAMING_SNAKE_CASE__										=      hidden_size
     SCREAMING_SNAKE_CASE__										=      initializer_factor
     SCREAMING_SNAKE_CASE__										=      layer_norm_eps
     SCREAMING_SNAKE_CASE__										=      share_link_tower_layers
     SCREAMING_SNAKE_CASE__										=      link_tower_type
     SCREAMING_SNAKE_CASE__										=      num_attention_heads
     SCREAMING_SNAKE_CASE__										=      num_hidden_layers
     SCREAMING_SNAKE_CASE__										=      tie_word_embeddings
     SCREAMING_SNAKE_CASE__										=      init_layernorm_from_vision_encoder

     if text_config is None:
       SCREAMING_SNAKE_CASE__										=      {}
       logger.info("""`text_config` is `None`. Initializing the `BridgeTowerTextConfig` with default values."""      )

     if vision_config is None:
       SCREAMING_SNAKE_CASE__										=      {}
       logger.info("""`vision_config` is `None`. Initializing the `BridgeTowerVisionConfig` with default values."""      )

     SCREAMING_SNAKE_CASE__										=      BridgeTowerTextConfig(**UpperCamelCase__      )
     SCREAMING_SNAKE_CASE__										=      BridgeTowerVisionConfig(**UpperCamelCase__      )




   @classmethod
   def 	__a						(    cls			:				Dict       ,	_lowercase			:				Union[str, Any]       ,	_lowercase			:				List[str]       ,	**_lowercase			:				List[str]      ):



     """simple docstring"""






     return cls(text_config=text_config.to_dict()       ,	vision_config=vision_config.to_dict()       ,	**UpperCamelCase__      )




   def 	__a						(    self			:				int      ):



     """simple docstring"""






     SCREAMING_SNAKE_CASE__										=      copy.deepcopy(self.__dict__      )
     SCREAMING_SNAKE_CASE__										=      self.text_config.to_dict()
     SCREAMING_SNAKE_CASE__										=      self.vision_config.to_dict()
     SCREAMING_SNAKE_CASE__										=      self.__class__.model_type
     return output






from typing import Dict, List, Optional

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


_A     =			logging.get_logger(__name__)


_A     =			{
    '''nielsr/canine-s''': 2_048,
}

# Unicode defines 1,114,112 total “codepoints”
_A     =			1_114_112

# Below: Constants defining canonical codepoints for special, pseudo-characters.
# Copied from https://github.com/google-research/language/blob/master/language/canine/special_codepoints.py
_A     =			0

_A     =			0xe0_00
_A     =			0xe0_01
_A     =			0xe0_02
_A     =			0xe0_03
_A     =			0xe0_04

# Maps special codepoints to human-readable names.
_A     =			{
    # Special symbols are represented using codepoints values that are valid,
    # but designated as "Private Use", meaning that they will never be assigned
    # characters by the Unicode Consortium, and are thus safe for use here.
    #
    # NOTE: Do *NOT* add any sort of [UNK_CHAR] here. They are explicitly
    # excluded and should fail with a hard error.
    CLS: "[CLS]",
    SEP: "[SEP]",
    BOS: "[BOS]",
    MASK: "[MASK]",
    PAD: "[PAD]",
    RESERVED: "[RESERVED]",
}

# Maps special codepoint human-readable names to their codepoint values.
_A     =			{name: codepoint for codepoint, name in SPECIAL_CODEPOINTS.items()}


class  A		(  __UpperCAmelCase     ):
		__snake_case									=   PRETRAINED_POSITIONAL_EMBEDDINGS_SIZES



		def __init__(     self,	UpperCamelCase__=chr(UpperCamelCase__   ),	UpperCamelCase__=chr(UpperCamelCase__   ),	UpperCamelCase__=chr(UpperCamelCase__   ),	UpperCamelCase__=chr(UpperCamelCase__   ),	UpperCamelCase__=chr(UpperCamelCase__   ),	UpperCamelCase__=chr(UpperCamelCase__   ),	UpperCamelCase__=False,	UpperCamelCase__=2048,	**UpperCamelCase__,	):







								"""simple docstring"""



								lowerCAmelCase_      			=  AddedToken(UpperCamelCase__,	lstrip=UpperCamelCase__,	rstrip=UpperCamelCase__   ) if isinstance(UpperCamelCase__,	UpperCamelCase__   ) else bos_token
								lowerCAmelCase_      			=  AddedToken(UpperCamelCase__,	lstrip=UpperCamelCase__,	rstrip=UpperCamelCase__   ) if isinstance(UpperCamelCase__,	UpperCamelCase__   ) else eos_token
								lowerCAmelCase_      			=  AddedToken(UpperCamelCase__,	lstrip=UpperCamelCase__,	rstrip=UpperCamelCase__   ) if isinstance(UpperCamelCase__,	UpperCamelCase__   ) else sep_token
								lowerCAmelCase_      			=  AddedToken(UpperCamelCase__,	lstrip=UpperCamelCase__,	rstrip=UpperCamelCase__   ) if isinstance(UpperCamelCase__,	UpperCamelCase__   ) else cls_token
								lowerCAmelCase_      			=  AddedToken(UpperCamelCase__,	lstrip=UpperCamelCase__,	rstrip=UpperCamelCase__   ) if isinstance(UpperCamelCase__,	UpperCamelCase__   ) else pad_token

								# Mask token behave like a normal word, i.e. include the space before it
								lowerCAmelCase_      			=  AddedToken(UpperCamelCase__,	lstrip=UpperCamelCase__,	rstrip=UpperCamelCase__   ) if isinstance(UpperCamelCase__,	UpperCamelCase__   ) else mask_token

								super().__init__(
								    bos_token=UpperCamelCase__,	eos_token=UpperCamelCase__,	sep_token=UpperCamelCase__,	cls_token=UpperCamelCase__,	pad_token=UpperCamelCase__,	mask_token=UpperCamelCase__,	add_prefix_space=UpperCamelCase__,	model_max_length=UpperCamelCase__,	**UpperCamelCase__,	)

								# Creates a mapping for looking up the IDs of special symbols.
								lowerCAmelCase_      			=  {}
								for codepoint, name in SPECIAL_CODEPOINTS.items():
														lowerCAmelCase_      			=  codepoint

								# Creates a mapping for looking up the string forms of special symbol IDs.
								lowerCAmelCase_      			=  {
								    codepoint: name for name, codepoint in self._special_codepoints.items()
								}

								lowerCAmelCase_      			=  UNICODE_VOCAB_SIZE
								lowerCAmelCase_      			=  len(self._special_codepoints   )



		@property
		def        SCREAMING_SNAKE_CASE__			(     self   ):







								"""simple docstring"""



								return self._unicode_vocab_size



		def        SCREAMING_SNAKE_CASE__			(     self,	UpperCamelCase__   ):







								"""simple docstring"""



								return list(UpperCamelCase__   )



		def        SCREAMING_SNAKE_CASE__			(     self,	UpperCamelCase__   ):







								"""simple docstring"""



								try:
														return ord(UpperCamelCase__   )
								except TypeError:
														raise ValueError(f"invalid token: '{token}'"   )



		def        SCREAMING_SNAKE_CASE__			(     self,	UpperCamelCase__   ):







								"""simple docstring"""



								try:
														if index in SPECIAL_CODEPOINTS:
																				return SPECIAL_CODEPOINTS[index]
														return chr(UpperCamelCase__   )
								except TypeError:
														raise ValueError(f"invalid id: {index}"   )



		def        SCREAMING_SNAKE_CASE__			(     self,	UpperCamelCase__   ):







								"""simple docstring"""



								return "".join(UpperCamelCase__   )



		def        SCREAMING_SNAKE_CASE__			(     self,	UpperCamelCase__,	UpperCamelCase__ = None   ):







								"""simple docstring"""



								lowerCAmelCase_      			=  [self.sep_token_id]
								lowerCAmelCase_      			=  [self.cls_token_id]

								lowerCAmelCase_      			=  cls + token_ids_a + sep
								if token_ids_a is not None:
														result += token_ids_a + sep
								return result



		def        SCREAMING_SNAKE_CASE__			(     self,	UpperCamelCase__,	UpperCamelCase__ = None,	UpperCamelCase__ = False   ):







								"""simple docstring"""



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

								lowerCAmelCase_      			=  [1] + ([0] * len(UpperCamelCase__   )) + [1]
								if token_ids_a is not None:
														result += ([0] * len(UpperCamelCase__   )) + [1]
								return result



		def        SCREAMING_SNAKE_CASE__			(     self,	UpperCamelCase__,	UpperCamelCase__ = None   ):







								"""simple docstring"""



								lowerCAmelCase_      			=  [self.sep_token_id]
								lowerCAmelCase_      			=  [self.cls_token_id]

								lowerCAmelCase_      			=  len(cls + token_ids_a + sep   ) * [0]
								if token_ids_a is not None:
														result += len(token_ids_a + sep   ) * [1]
								return result







		def        SCREAMING_SNAKE_CASE__			(     self,	UpperCamelCase__,	UpperCamelCase__ = None   ):







								"""simple docstring"""



								return ()




