
'''simple docstring'''




from typing import Any







def 		lowerCAmelCase_				(   snake_case__		,				snake_case__		,				snake_case__		,				snake_case__		,				snake_case__		,				):




    '''simple docstring'''



    _validation(
        snake_case__		,				snake_case__		,				snake_case__		,				snake_case__		,				snake_case__		,				)
    # Creates data structures and fill initial step
    A       :   dict					=						{}
    A       :   dict					=						{}
    for state in states_space:
        A       :   Tuple					=						observations_space[0]
        A       :   List[Any]					=						(
            initial_probabilities[state] * emission_probabilities[state][observation]
        )
        A       :   Any					=						None

    # Fills the data structure with the probabilities of
    # different transitions and pointers to previous states
    for o in range(1		,				len(snake_case__						)						):
        A       :   Dict					=						observations_space[o]
        A       :   Any					=						observations_space[o - 1]
        for state in states_space:
            # Calculates the argmax for probability function
            A       :   List[Any]					=						''''''
            A       :   Optional[Any]					=						-1
            for k_state in states_space:
                A       :   Dict					=						(
                    probabilities[(k_state, prior_observation)]
                    * transition_probabilities[k_state][state]
                    * emission_probabilities[state][observation]
                )
                if probability > max_probability:
                    A       :   Any					=						probability
                    A       :   Union[str, Any]					=						k_state

            # Update probabilities and pointers dicts
            A       :   List[Any]					=						(
                probabilities[(arg_max, prior_observation)]
                * transition_probabilities[arg_max][state]
                * emission_probabilities[state][observation]
            )

            A       :   Tuple					=						arg_max

    # The final observation
    A       :   Union[str, Any]					=						observations_space[len(snake_case__						) - 1]

    # argmax for given final observation
    A       :   Dict					=						''''''
    A       :   int					=						-1
    for k_state in states_space:
        A       :   Tuple					=						probabilities[(k_state, final_observation)]
        if probability > max_probability:
            A       :   Optional[int]					=						probability
            A       :   List[Any]					=						k_state
    A       :   Union[str, Any]					=						arg_max

    # Process pointers backwards
    A       :   int					=						last_state
    A       :   Optional[Any]					=						[]
    for o in range(len(snake_case__						) - 1		,				-1		,				-1						):
        result.append(snake_case__						)
        A       :   Tuple					=						pointers[previous, observations_space[o]]
    result.reverse()

    return result







def 		lowerCAmelCase_				(   snake_case__		,				snake_case__		,				snake_case__		,				snake_case__		,				snake_case__		,				):




    '''simple docstring'''



    _validate_not_empty(
        snake_case__		,				snake_case__		,				snake_case__		,				snake_case__		,				snake_case__		,				)
    _validate_lists(snake_case__		,				snake_case__						)
    _validate_dicts(
        snake_case__		,				snake_case__		,				snake_case__						)







def 		lowerCAmelCase_				(   snake_case__		,				snake_case__		,				snake_case__		,				snake_case__		,				snake_case__		,				):




    '''simple docstring'''



    if not all(
        [
            observations_space,
            states_space,
            initial_probabilities,
            transition_probabilities,
            emission_probabilities,
        ]						):
        raise ValueError('''There\'s an empty parameter'''						)







def 		lowerCAmelCase_				(   snake_case__		,				snake_case__						):




    '''simple docstring'''



    _validate_list(snake_case__		,				'''observations_space'''						)
    _validate_list(snake_case__		,				'''states_space'''						)







def 		lowerCAmelCase_				(   snake_case__		,				snake_case__						):




    '''simple docstring'''



    if not isinstance(_object		,				snake_case__						):
        A       :   List[str]					=						F'{var_name} must be a list'
        raise ValueError(snake_case__						)
    else:
        for x in _object:
            if not isinstance(snake_case__		,				snake_case__						):
                A       :   Optional[int]					=						F'{var_name} must be a list of strings'
                raise ValueError(snake_case__						)







def 		lowerCAmelCase_				(   snake_case__		,				snake_case__		,				snake_case__		,				):




    '''simple docstring'''



    _validate_dict(snake_case__		,				'''initial_probabilities'''		,				snake_case__						)
    _validate_nested_dict(snake_case__		,				'''transition_probabilities'''						)
    _validate_nested_dict(snake_case__		,				'''emission_probabilities'''						)







def 		lowerCAmelCase_				(   snake_case__		,				snake_case__						):




    '''simple docstring'''



    _validate_dict(_object		,				snake_case__		,				snake_case__						)
    for x in _object.values():
        _validate_dict(snake_case__		,				snake_case__		,				snake_case__		,				snake_case__						)







def 		lowerCAmelCase_				(   snake_case__		,				snake_case__		,				snake_case__		,				snake_case__ = False						):




    '''simple docstring'''



    if not isinstance(_object		,				snake_case__						):
        A       :   Union[str, Any]					=						F'{var_name} must be a dict'
        raise ValueError(snake_case__						)
    if not all(isinstance(snake_case__		,				snake_case__						) for x in _object						):
        A       :   Union[str, Any]					=						F'{var_name} all keys must be strings'
        raise ValueError(snake_case__						)
    if not all(isinstance(snake_case__		,				snake_case__						) for x in _object.values()						):
        A       :   str					=						'''nested dictionary ''' if nested else ''''''
        A       :   List[str]					=						F'{var_name} {nested_text}all values must be {value_type.__name__}'
        raise ValueError(snake_case__						)


if __name__ == "__main__":
      from doctest import testmod

      testmod()






import copy
import os
from typing import Union

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


_lowerCamelCase					   =logging.get_logger(__name__)

_lowerCamelCase					   ={
    """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 							A__		(	__SCREAMING_SNAKE_CASE):
      _UpperCAmelCase				:    Dict           =			"""bridgetower_vision_model"""
      def __init__(      self    ,  __magic_name__=7_6_8    ,  __magic_name__=1_2    ,  __magic_name__=3    ,  __magic_name__=1_6    ,  __magic_name__=2_8_8    ,  __magic_name__=1    ,  __magic_name__=1e-05    ,  __magic_name__=False    ,  __magic_name__=True    ,  __magic_name__=False    ,  **__magic_name__    ,  ):
       super().__init__(**__magic_name__      )
       lowerCamelCase		:	Dict							=      hidden_size
       lowerCamelCase		:	str							=      num_hidden_layers
       lowerCamelCase		:	Optional[int]							=      num_channels
       lowerCamelCase		:	List[str]							=      patch_size
       lowerCamelCase		:	Tuple							=      image_size
       lowerCamelCase		:	Any							=      initializer_factor
       lowerCamelCase		:	Tuple							=      layer_norm_eps
       lowerCamelCase		:	Tuple							=      stop_gradient
       lowerCamelCase		:	Optional[int]							=      share_layernorm
       lowerCamelCase		:	str							=      remove_last_layer






      @classmethod
      def 						UpperCamelCase__							(      cls    ,  __magic_name__    ,  **__magic_name__      ):
       lowerCamelCase			,    lowerCamelCase		:	int							=      cls.get_config_dict(__magic_name__    ,  **__magic_name__      )

       if config_dict.get("""model_type"""      ) == "bridgetower":
        lowerCamelCase		:	str							=      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(__magic_name__    ,  **__magic_name__      )





class 							A__		(	__SCREAMING_SNAKE_CASE):
      _UpperCAmelCase				:    Union[str, Any]           =			"""bridgetower_text_model"""
      def __init__(      self    ,  __magic_name__=5_0_2_6_5    ,  __magic_name__=7_6_8    ,  __magic_name__=1_2    ,  __magic_name__=1_2    ,  __magic_name__=1    ,  __magic_name__=3_0_7_2    ,  __magic_name__="gelu"    ,  __magic_name__=0.1    ,  __magic_name__=0.1    ,  __magic_name__=5_1_4    ,  __magic_name__=1    ,  __magic_name__=1e-05    ,  __magic_name__=1    ,  __magic_name__=0    ,  __magic_name__=2    ,  __magic_name__="absolute"    ,  __magic_name__=True    ,  **__magic_name__    ,  ):
       super().__init__(**__magic_name__      )

       lowerCamelCase		:	int							=      vocab_size
       lowerCamelCase		:	int							=      hidden_size
       lowerCamelCase		:	Any							=      num_hidden_layers
       lowerCamelCase		:	Union[str, Any]							=      num_attention_heads
       lowerCamelCase		:	Tuple							=      hidden_act
       lowerCamelCase		:	Optional[int]							=      initializer_factor
       lowerCamelCase		:	Any							=      intermediate_size
       lowerCamelCase		:	List[str]							=      hidden_dropout_prob
       lowerCamelCase		:	Dict							=      attention_probs_dropout_prob
       lowerCamelCase		:	str							=      max_position_embeddings
       lowerCamelCase		:	Union[str, Any]							=      type_vocab_size
       lowerCamelCase		:	Optional[int]							=      layer_norm_eps
       lowerCamelCase		:	Optional[int]							=      position_embedding_type
       lowerCamelCase		:	List[str]							=      use_cache
       lowerCamelCase		:	List[str]							=      pad_token_id
       lowerCamelCase		:	List[str]							=      bos_token_id
       lowerCamelCase		:	Optional[int]							=      eos_token_id






      @classmethod
      def 						UpperCamelCase__							(      cls    ,  __magic_name__    ,  **__magic_name__      ):
       lowerCamelCase			,    lowerCamelCase		:	int							=      cls.get_config_dict(__magic_name__    ,  **__magic_name__      )

       if config_dict.get("""model_type"""      ) == "bridgetower":
        lowerCamelCase		:	Optional[int]							=      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(__magic_name__    ,  **__magic_name__      )





class 							A__		(	__SCREAMING_SNAKE_CASE):
      _UpperCAmelCase				:    Dict           =			"""bridgetower"""
      def __init__(      self    ,  __magic_name__=True    ,  __magic_name__="gelu"    ,  __magic_name__=7_6_8    ,  __magic_name__=1    ,  __magic_name__=1e-05    ,  __magic_name__=False    ,  __magic_name__="add"    ,  __magic_name__=1_2    ,  __magic_name__=6    ,  __magic_name__=False    ,  __magic_name__=False    ,  __magic_name__=None    ,  __magic_name__=None    ,  **__magic_name__    ,  ):
       # TODO: remove this once the Hub files are updated.
       lowerCamelCase		:	int							=      kwargs.pop("""text_config_dict"""    ,  __magic_name__      )
       lowerCamelCase		:	str							=      kwargs.pop("""vision_config_dict"""    ,  __magic_name__      )

       super().__init__(**__magic_name__      )
       lowerCamelCase		:	str							=      share_cross_modal_transformer_layers
       lowerCamelCase		:	Union[str, Any]							=      hidden_act
       lowerCamelCase		:	str							=      hidden_size
       lowerCamelCase		:	Tuple							=      initializer_factor
       lowerCamelCase		:	List[str]							=      layer_norm_eps
       lowerCamelCase		:	int							=      share_link_tower_layers
       lowerCamelCase		:	List[Any]							=      link_tower_type
       lowerCamelCase		:	Tuple							=      num_attention_heads
       lowerCamelCase		:	int							=      num_hidden_layers
       lowerCamelCase		:	Union[str, Any]							=      tie_word_embeddings
       lowerCamelCase		:	Tuple							=      init_layernorm_from_vision_encoder

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

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

       lowerCamelCase		:	Any							=      BridgeTowerTextConfig(**__magic_name__      )
       lowerCamelCase		:	Optional[Any]							=      BridgeTowerVisionConfig(**__magic_name__      )
      @classmethod
      def 						UpperCamelCase__							(      cls    ,  __magic_name__    ,  __magic_name__    ,  **__magic_name__      ):
       return cls(text_config=text_config.to_dict()    ,  vision_config=vision_config.to_dict()    ,  **__magic_name__      )






      def 						UpperCamelCase__							(      self      ):
       lowerCamelCase		:	str							=      copy.deepcopy(self.__dict__      )
       lowerCamelCase		:	int							=      self.text_config.to_dict()
       lowerCamelCase		:	Dict							=      self.vision_config.to_dict()
       lowerCamelCase		:	List[str]							=      self.__class__.model_type
       return output




