
'''simple docstring'''
import copy
import os
from typing import Union

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


a_											=						logging.get_logger(__name__)

a_											=						{
    "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    UpperCAmelCase_				(	snake_case__					):
 UpperCAmelCase_		    =						"""bridgetower_vision_model"""





 def __init__(    self ,       lowercase_=7_68 ,       lowercase_=12 ,       lowercase_=3 ,       lowercase_=16 ,       lowercase_=2_88 ,       lowercase_=1 ,       lowercase_=1E-05 ,       lowercase_=False ,       lowercase_=True ,       lowercase_=False ,       **lowercase_ ,       ):
     super().__init__(**lowercase_)
     snake_case_ :    str     			=						hidden_size
     snake_case_ :    int     			=						num_hidden_layers
     snake_case_ :    int     			=						num_channels
     snake_case_ :    Dict     			=						patch_size
     snake_case_ :    List[str]     			=						image_size
     snake_case_ :    Optional[int]     			=						initializer_factor
     snake_case_ :    Any     			=						layer_norm_eps
     snake_case_ :    Dict     			=						stop_gradient
     snake_case_ :    List[Any]     			=						share_layernorm
     snake_case_ :    str     			=						remove_last_layer





 @classmethod
 def        snake_case__		(    cls ,       lowercase_ ,       **lowercase_):
     snake_case_			, snake_case_ :    int     			=						cls.get_config_dict(lowercase_ ,       **lowercase_)

     if config_dict.get("model_type") == "bridgetower":
         snake_case_ :    Any     			=						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(lowercase_ ,       **lowercase_)






class    UpperCAmelCase_				(	snake_case__					):
 UpperCAmelCase_		    =						"""bridgetower_text_model"""





 def __init__(    self ,       lowercase_=5_02_65 ,       lowercase_=7_68 ,       lowercase_=12 ,       lowercase_=12 ,       lowercase_=1 ,       lowercase_=30_72 ,       lowercase_="gelu" ,       lowercase_=0.1 ,       lowercase_=0.1 ,       lowercase_=5_14 ,       lowercase_=1 ,       lowercase_=1E-05 ,       lowercase_=1 ,       lowercase_=0 ,       lowercase_=2 ,       lowercase_="absolute" ,       lowercase_=True ,       **lowercase_ ,       ):
     super().__init__(**lowercase_)

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





 @classmethod
 def        snake_case__		(    cls ,       lowercase_ ,       **lowercase_):
     snake_case_			, snake_case_ :    List[Any]     			=						cls.get_config_dict(lowercase_ ,       **lowercase_)

     if config_dict.get("model_type") == "bridgetower":
         snake_case_ :    Union[str, Any]     			=						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(lowercase_ ,       **lowercase_)






class    UpperCAmelCase_				(	snake_case__					):
 UpperCAmelCase_		    =						"""bridgetower"""





 def __init__(    self ,       lowercase_=True ,       lowercase_="gelu" ,       lowercase_=7_68 ,       lowercase_=1 ,       lowercase_=1E-05 ,       lowercase_=False ,       lowercase_="add" ,       lowercase_=12 ,       lowercase_=6 ,       lowercase_=False ,       lowercase_=False ,       lowercase_=None ,       lowercase_=None ,       **lowercase_ ,       ):
     # TODO: remove this once the Hub files are updated.
     snake_case_ :    str     			=						kwargs.pop("text_config_dict" ,       lowercase_)
     snake_case_ :    List[str]     			=						kwargs.pop("vision_config_dict" ,       lowercase_)

     super().__init__(**lowercase_)
     snake_case_ :    List[Any]     			=						share_cross_modal_transformer_layers
     snake_case_ :    List[Any]     			=						hidden_act
     snake_case_ :    Optional[Any]     			=						hidden_size
     snake_case_ :    Any     			=						initializer_factor
     snake_case_ :    str     			=						layer_norm_eps
     snake_case_ :    Optional[int]     			=						share_link_tower_layers
     snake_case_ :    str     			=						link_tower_type
     snake_case_ :    str     			=						num_attention_heads
     snake_case_ :    Optional[int]     			=						num_hidden_layers
     snake_case_ :    int     			=						tie_word_embeddings
     snake_case_ :    Any     			=						init_layernorm_from_vision_encoder

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

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

     snake_case_ :    List[str]     			=						BridgeTowerTextConfig(**lowercase_)
     snake_case_ :    Dict     			=						BridgeTowerVisionConfig(**lowercase_)





 @classmethod
 def        snake_case__		(    cls ,       lowercase_ ,       lowercase_ ,       **lowercase_):
     return cls(text_config=text_config.to_dict() ,       vision_config=vision_config.to_dict() ,       **lowercase_)





 def        snake_case__		(    self):
     snake_case_ :    Tuple     			=						copy.deepcopy(self.__dict__)
     snake_case_ :    Tuple     			=						self.text_config.to_dict()
     snake_case_ :    Optional[int]     			=						self.vision_config.to_dict()
     snake_case_ :    Dict     			=						self.__class__.model_type
     return output






'''simple docstring'''
from __future__ import annotations

from collections.abc import Callable
from typing import Generic, TypeVar

a_											=						TypeVar("T")
a_											=						TypeVar("U")






class    UpperCAmelCase_				(	Generic[T, U]					):





 def __init__(    self ,       lowercase_ ,       lowercase_):
     snake_case_ :    Any     			=						key
     snake_case_ :    List[Any]     			=						val
     snake_case_ :    DoubleLinkedListNode[T, U] | None     			=						None
     snake_case_ :    DoubleLinkedListNode[T, U] | None     			=						None





 def __repr__(    self):
     return (
         F'Node: key: {self.key}, val: {self.val}, '
         F'has next: {bool(self.next)}, has prev: {bool(self.prev)}'
     )






class    UpperCAmelCase_				(	Generic[T, U]					):





 def __init__(    self):
     snake_case_ :    DoubleLinkedListNode[T, U]     			=						DoubleLinkedListNode(lowercase_ ,       lowercase_)
     snake_case_ :    DoubleLinkedListNode[T, U]     			=						DoubleLinkedListNode(lowercase_ ,       lowercase_)
     snake_case_			, snake_case_ :    Union[str, Any]     			=						self.rear, self.head





 def __repr__(    self):
     snake_case_ :    Dict     			=						["DoubleLinkedList"]
     snake_case_ :    Dict     			=						self.head
     while node.next is not None:
         rep.append(str(lowercase_))
         snake_case_ :    List[str]     			=						node.next
     rep.append(str(self.rear))
     return ",\n    ".join(lowercase_)





 def        snake_case__		(    self ,       lowercase_):
     snake_case_ :    List[str]     			=						self.rear.prev

     # All nodes other than self.head are guaranteed to have non-None previous
     assert previous is not None

     snake_case_ :    Tuple     			=						node
     snake_case_ :    str     			=						previous
     snake_case_ :    Optional[Any]     			=						node
     snake_case_ :    Any     			=						self.rear





 def        snake_case__		(    self ,       lowercase_):

     if node.prev is None or node.next is None:
         return None

     snake_case_ :    Union[str, Any]     			=						node.next
     snake_case_ :    Optional[int]     			=						node.prev
     snake_case_ :    str     			=						None
     snake_case_ :    int     			=						None
     return node






class    UpperCAmelCase_				(	Generic[T, U]					):
 UpperCAmelCase_		    =						{}





 def __init__(    self ,       lowercase_):
     snake_case_ :    DoubleLinkedList[T, U]     			=						DoubleLinkedList()
     snake_case_ :    List[str]     			=						capacity
     snake_case_ :    Any     			=						0
     snake_case_ :    Dict     			=						0
     snake_case_ :    Union[str, Any]     			=						0
     snake_case_ :    dict[T, DoubleLinkedListNode[T, U]]     			=						{}





 def __repr__(    self):
     return (
         F'CacheInfo(hits={self.hits}, misses={self.miss}, '
         F'capacity={self.capacity}, current size={self.num_keys})'
     )





 def __contains__(    self ,       lowercase_):
     return key in self.cache





 def        snake_case__		(    self ,       lowercase_):
     # Note: pythonic interface would throw KeyError rather than return None

     if key in self.cache:
         self.hits += 1
         snake_case_ :    DoubleLinkedListNode[T, U]     			=						self.cache[key]
         snake_case_ :    Optional[Any]     			=						self.list.remove(self.cache[key])
         assert node == value_node

         # node is guaranteed not None because it is in self.cache
         assert node is not None
         self.list.add(lowercase_)
         return node.val
     self.miss += 1
     return None





 def        snake_case__		(    self ,       lowercase_ ,       lowercase_):

     if key not in self.cache:
         if self.num_keys >= self.capacity:
             # delete first node (oldest) when over capacity
             snake_case_ :    Optional[Any]     			=						self.list.head.next

             # guaranteed to have a non-None first node when num_keys > 0
             # explain to type checker via assertions
             assert first_node is not None
             assert first_node.key is not None
             assert (
                 self.list.remove(lowercase_) is not None
             )  # node guaranteed to be in list assert node.key is not None

             del self.cache[first_node.key]
             self.num_keys -= 1
         snake_case_ :    Dict     			=						DoubleLinkedListNode(lowercase_ ,       lowercase_)
         self.list.add(self.cache[key])
         self.num_keys += 1

     else:
         # bump node to the end of the list, update value
         snake_case_ :    List[Any]     			=						self.list.remove(self.cache[key])
         assert node is not None  # node guaranteed to be in list
         snake_case_ :    Optional[Any]     			=						value
         self.list.add(lowercase_)





 @classmethod
 def        snake_case__		(    cls ,       lowercase_ = 1_28):

     def cache_decorator_inner(lowercase_) -> Callable[..., U]:
         def cache_decorator_wrapper(*lowercase_) -> U:
             if func not in cls.decorator_function_to_instance_map:
                 snake_case_ :    List[str]     			=						LRUCache(lowercase_)

             snake_case_ :    Optional[Any]     			=						cls.decorator_function_to_instance_map[func].get(args[0])
             if result is None:
                 snake_case_ :    Any     			=						func(*lowercase_)
                 cls.decorator_function_to_instance_map[func].put(args[0] ,       lowercase_)
             return result

         def cache_info() -> LRUCache[T, U]:
             return cls.decorator_function_to_instance_map[func]

         setattr(lowercase_ ,       "cache_info" ,       lowercase_)  # noqa: B010

         return cache_decorator_wrapper

     return cache_decorator_inner


if __name__ == "__main__":
  import doctest

  doctest.testmod()




