'''simple docstring'''

import copy
import os
from typing import Union

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


lowercase_     		= logging.get_logger(__name__)

lowercase_     		= {
    '''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   SCREAMING_SNAKE_CASE			(						__lowercase):







		"""simple docstring"""
		lowercase   :      List[Any]       =							'bridgetower_vision_model'






		def __init__(   self		,						__A=768		,						__A=12		,						__A=3		,						__A=16		,						__A=288		,						__A=1		,						__A=1E-05		,						__A=False		,						__A=True		,						__A=False		,						**__A		,						) ->     Optional[int]:
								super().__init__(**__A				)
								_lowerCAmelCase										=hidden_size
								_lowerCAmelCase										=num_hidden_layers
								_lowerCAmelCase										=num_channels
								_lowerCAmelCase										=patch_size
								_lowerCAmelCase										=image_size
								_lowerCAmelCase										=initializer_factor
								_lowerCAmelCase										=layer_norm_eps
								_lowerCAmelCase										=stop_gradient
								_lowerCAmelCase										=share_layernorm
								_lowerCAmelCase										=remove_last_layer






		@classmethod
		def 		UpperCamelCase__       (   cls		,						__A		,						**__A				) ->     "PretrainedConfig":
								_lowerCAmelCase						,				_lowerCAmelCase										=cls.get_config_dict(__A		,						**__A				)

								if config_dict.get('model_type'				) == "bridgetower":
														_lowerCAmelCase										=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(__A		,						**__A				)

class   SCREAMING_SNAKE_CASE			(						__lowercase):







		"""simple docstring"""
		lowercase   :      Optional[int]       =							'bridgetower_text_model'






		def __init__(   self		,						__A=5_0265		,						__A=768		,						__A=12		,						__A=12		,						__A=1		,						__A=3072		,						__A="gelu"		,						__A=0.1		,						__A=0.1		,						__A=514		,						__A=1		,						__A=1E-05		,						__A=1		,						__A=0		,						__A=2		,						__A="absolute"		,						__A=True		,						**__A		,						) ->     Dict:
								super().__init__(**__A				)

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






		@classmethod
		def 		UpperCamelCase__       (   cls		,						__A		,						**__A				) ->     "PretrainedConfig":
								_lowerCAmelCase						,				_lowerCAmelCase										=cls.get_config_dict(__A		,						**__A				)

								if config_dict.get('model_type'				) == "bridgetower":
														_lowerCAmelCase										=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(__A		,						**__A				)

class   SCREAMING_SNAKE_CASE			(						__lowercase):







		"""simple docstring"""
		lowercase   :      Dict       =							'bridgetower'






		def __init__(   self		,						__A=True		,						__A="gelu"		,						__A=768		,						__A=1		,						__A=1E-05		,						__A=False		,						__A="add"		,						__A=12		,						__A=6		,						__A=False		,						__A=False		,						__A=None		,						__A=None		,						**__A		,						) ->     Any:
								# TODO: remove this once the Hub files are updated.
								_lowerCAmelCase										=kwargs.pop('text_config_dict'		,						__A				)
								_lowerCAmelCase										=kwargs.pop('vision_config_dict'		,						__A				)

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

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

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

								_lowerCAmelCase										=BridgeTowerTextConfig(**__A				)
								_lowerCAmelCase										=BridgeTowerVisionConfig(**__A				)






		@classmethod
		def 		UpperCamelCase__       (   cls		,						__A		,						__A		,						**__A				) ->     List[Any]:
								return cls(text_config=text_config.to_dict()		,						vision_config=vision_config.to_dict()		,						**__A				)






		def 		UpperCamelCase__       (   self				) ->     Optional[Any]:
								_lowerCAmelCase										=copy.deepcopy(self.__dict__				)
								_lowerCAmelCase										=self.text_config.to_dict()
								_lowerCAmelCase										=self.vision_config.to_dict()
								_lowerCAmelCase										=self.__class__.model_type
								return output






'''simple docstring'''

from __future__ import annotations

lowercase_     		= 10



def 							UpperCamelCase__			(			a__      ):


						'''simple docstring'''






						_lowerCAmelCase										=1
						_lowerCAmelCase										=max(a__      )
						while placement <= max_digit:
												# declare and initialize empty buckets
												_lowerCAmelCase										=[[] for _ in range(a__      )]
												# split list_of_ints between the buckets
												for i in list_of_ints:
																		_lowerCAmelCase										=int((i / placement) % RADIX      )
																		buckets[tmp].append(a__      )
												# put each buckets' contents into list_of_ints
												_lowerCAmelCase										=0
												for b in range(a__      ):
																		for i in buckets[b]:
																								_lowerCAmelCase										=i
																								a += 1
        # move to next
												placement *= RADIX
						return list_of_ints


if __name__ == "__main__":
							import doctest

							doctest.testmod()





