






import copy
import os
from typing import Union

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


SCREAMING_SNAKE_CASE__      :			Tuple							=		logging.get_logger(__name__)

SCREAMING_SNAKE_CASE__      :			int							=		{
    """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 						lowerCamelCase_				(      lowerCamelCase ):
				a__					       =  '''bridgetower_vision_model'''







				def __init__(						self       ,					__lowerCAmelCase=7_6_8       ,					__lowerCAmelCase=1_2       ,					__lowerCAmelCase=3       ,					__lowerCAmelCase=1_6       ,					__lowerCAmelCase=2_8_8       ,					__lowerCAmelCase=1       ,					__lowerCAmelCase=1E-05       ,					__lowerCAmelCase=False       ,					__lowerCAmelCase=True       ,					__lowerCAmelCase=False       ,					**__lowerCAmelCase       ,					):
								"""simple docstring"""
								super().__init__(**__lowerCAmelCase     )
								__magic_name__		:Optional[int]        =      hidden_size
								__magic_name__		:Dict        =      num_hidden_layers
								__magic_name__		:Optional[Any]        =      num_channels
								__magic_name__		:List[Any]        =      patch_size
								__magic_name__		:str        =      image_size
								__magic_name__		:Optional[int]        =      initializer_factor
								__magic_name__		:Optional[Any]        =      layer_norm_eps
								__magic_name__		:Optional[Any]        =      stop_gradient
								__magic_name__		:List[str]        =      share_layernorm
								__magic_name__		:Tuple        =      remove_last_layer







				@classmethod
				def 			A	(						cls       ,					__lowerCAmelCase       ,					**__lowerCAmelCase     ):
								"""simple docstring"""
								__magic_name__     ,				__magic_name__		:Tuple        =      cls.get_config_dict(__lowerCAmelCase       ,					**__lowerCAmelCase     )

								if config_dict.get('''model_type'''     ) == "bridgetower":
												__magic_name__		:List[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(__lowerCAmelCase       ,					**__lowerCAmelCase     )







class 						lowerCamelCase_				(      lowerCamelCase ):
				a__					       =  '''bridgetower_text_model'''







				def __init__(						self       ,					__lowerCAmelCase=5_0_2_6_5       ,					__lowerCAmelCase=7_6_8       ,					__lowerCAmelCase=1_2       ,					__lowerCAmelCase=1_2       ,					__lowerCAmelCase=1       ,					__lowerCAmelCase=3_0_7_2       ,					__lowerCAmelCase="gelu"       ,					__lowerCAmelCase=0.1       ,					__lowerCAmelCase=0.1       ,					__lowerCAmelCase=5_1_4       ,					__lowerCAmelCase=1       ,					__lowerCAmelCase=1E-05       ,					__lowerCAmelCase=1       ,					__lowerCAmelCase=0       ,					__lowerCAmelCase=2       ,					__lowerCAmelCase="absolute"       ,					__lowerCAmelCase=True       ,					**__lowerCAmelCase       ,					):
								"""simple docstring"""
								super().__init__(**__lowerCAmelCase     )

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







				@classmethod
				def 			A	(						cls       ,					__lowerCAmelCase       ,					**__lowerCAmelCase     ):
								"""simple docstring"""
								__magic_name__     ,				__magic_name__		:Any        =      cls.get_config_dict(__lowerCAmelCase       ,					**__lowerCAmelCase     )

								if config_dict.get('''model_type'''     ) == "bridgetower":
												__magic_name__		:Dict        =      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(__lowerCAmelCase       ,					**__lowerCAmelCase     )







class 						lowerCamelCase_				(      lowerCamelCase ):
				a__					       =  '''bridgetower'''







				def __init__(						self       ,					__lowerCAmelCase=True       ,					__lowerCAmelCase="gelu"       ,					__lowerCAmelCase=7_6_8       ,					__lowerCAmelCase=1       ,					__lowerCAmelCase=1E-05       ,					__lowerCAmelCase=False       ,					__lowerCAmelCase="add"       ,					__lowerCAmelCase=1_2       ,					__lowerCAmelCase=6       ,					__lowerCAmelCase=False       ,					__lowerCAmelCase=False       ,					__lowerCAmelCase=None       ,					__lowerCAmelCase=None       ,					**__lowerCAmelCase       ,					):
								"""simple docstring"""
								# TODO: remove this once the Hub files are updated.
								__magic_name__		:Optional[int]        =      kwargs.pop('''text_config_dict'''       ,					__lowerCAmelCase     )
								__magic_name__		:Any        =      kwargs.pop('''vision_config_dict'''       ,					__lowerCAmelCase     )

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

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

								if vision_config is None:
												__magic_name__		:Optional[Any]        =      {}
												logger.info('''`vision_config` is `None`. Initializing the `BridgeTowerVisionConfig` with default values.'''     )

								__magic_name__		:Any        =      BridgeTowerTextConfig(**__lowerCAmelCase     )
								__magic_name__		:List[Any]        =      BridgeTowerVisionConfig(**__lowerCAmelCase     )







				@classmethod
				def 			A	(						cls       ,					__lowerCAmelCase       ,					__lowerCAmelCase       ,					**__lowerCAmelCase     ):
								"""simple docstring"""
								return cls(text_config=text_config.to_dict()       ,					vision_config=vision_config.to_dict()       ,					**__lowerCAmelCase     )







				def 			A	(						self     ):
								"""simple docstring"""
								__magic_name__		:Optional[Any]        =      copy.deepcopy(self.__dict__     )
								__magic_name__		:List[str]        =      self.text_config.to_dict()
								__magic_name__		:Optional[int]        =      self.vision_config.to_dict()
								__magic_name__		:Optional[int]        =      self.__class__.model_type
								return output














from urllib.parse import quote

import pytest

from datasets.utils.hub import hf_hub_url

@pytest.mark.parametrize('''repo_id''',  ['''canonical_dataset_name''', '''org-name/dataset-name'''] )
@pytest.mark.parametrize('''path''',  ['''filename.csv''', '''filename with blanks.csv'''] )
@pytest.mark.parametrize('''revision''',  [None, '''v2'''] )
def      __lowercase					( snake_case,  snake_case,  snake_case ):







				"""simple docstring"""






				__magic_name__		:Tuple        =      hf_hub_url(repo_id=snake_case,  path=snake_case,  revision=snake_case )
				assert url == f'''https://huggingface.co/datasets/{repo_id}/resolve/{revision or "main"}/{quote(snake_case )}'''






