

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


a__												=						logging.get_logger(__name__)

a__												=						{
    '''uclanlp/visualbert-vqa''': '''https://huggingface.co/uclanlp/visualbert-vqa/resolve/main/config.json''',
    '''uclanlp/visualbert-vqa-pre''': '''https://huggingface.co/uclanlp/visualbert-vqa-pre/resolve/main/config.json''',
    '''uclanlp/visualbert-vqa-coco-pre''': (
        '''https://huggingface.co/uclanlp/visualbert-vqa-coco-pre/resolve/main/config.json'''
    ),
    '''uclanlp/visualbert-vcr''': '''https://huggingface.co/uclanlp/visualbert-vcr/resolve/main/config.json''',
    '''uclanlp/visualbert-vcr-pre''': '''https://huggingface.co/uclanlp/visualbert-vcr-pre/resolve/main/config.json''',
    '''uclanlp/visualbert-vcr-coco-pre''': (
        '''https://huggingface.co/uclanlp/visualbert-vcr-coco-pre/resolve/main/config.json'''
    ),
    '''uclanlp/visualbert-nlvr2''': '''https://huggingface.co/uclanlp/visualbert-nlvr2/resolve/main/config.json''',
    '''uclanlp/visualbert-nlvr2-pre''': '''https://huggingface.co/uclanlp/visualbert-nlvr2-pre/resolve/main/config.json''',
    '''uclanlp/visualbert-nlvr2-coco-pre''': (
        '''https://huggingface.co/uclanlp/visualbert-nlvr2-coco-pre/resolve/main/config.json'''
    )
    # See all VisualBERT models at https://huggingface.co/models?filter=visual_bert
}

class 							UpperCAmelCase_						(     __lowercase  ):
							"""simple docstring"""







							UpperCAmelCase__			:		List[Any]             =       "visual_bert"


							def __init__(     self			,				_a=3_0_5_2_2			,				_a=7_6_8			,				_a=5_1_2			,				_a=1_2			,				_a=1_2			,				_a=3_0_7_2			,				_a="gelu"			,				_a=0.1			,				_a=0.1			,				_a=5_1_2			,				_a=2			,				_a=0.02			,				_a=1e-1_2			,				_a=False			,				_a=True			,				_a=1			,				_a=0			,				_a=2			,				**_a			,				)       ->       str:
												super().__init__(pad_token_id=_a			,				bos_token_id=_a			,				eos_token_id=_a			,				**_a			)

												_a      :       Any   =						vocab_size
												_a      :       List[str]   =						max_position_embeddings
												_a      :       Dict   =						hidden_size
												_a      :       Union[str, Any]   =						visual_embedding_dim
												_a      :       Tuple   =						num_hidden_layers
												_a      :       int   =						num_attention_heads
												_a      :       Union[str, Any]   =						intermediate_size
												_a      :       List[Any]   =						hidden_act
												_a      :       Union[str, Any]   =						hidden_dropout_prob
												_a      :       List[Any]   =						attention_probs_dropout_prob
												_a      :       Optional[Any]   =						initializer_range
												_a      :       Tuple   =						type_vocab_size
												_a      :       List[str]   =						layer_norm_eps
												_a      :       int   =						bypass_transformer
												_a      :       Optional[int]   =						special_visual_initialize






from __future__ import annotations

from dataclasses import dataclass

@dataclass
class 							UpperCAmelCase_						:
							"""simple docstring"""







							UpperCAmelCase__			:		float
							UpperCAmelCase__			:		TreeNode | None             =       None
							UpperCAmelCase__			:		TreeNode | None             =       None



def   __UpperCAmelCase					(      __a :     TreeNode | None      )     ->	bool:

					"""simple docstring"""

					def is_valid_tree(__a :     TreeNode | None      ) -> bool:
										if node is None:
															return True

										if not isinstance(__a						,__a      ):
															return False

										try:
															float(node.data      )
										except (TypeError, ValueError):
															return False

										return is_valid_tree(node.left      ) and is_valid_tree(node.right      )

					if not is_valid_tree(__a      ):
										raise ValueError(
										    '''Each node should be type of TreeNode and data should be float.'''      )

					def is_binary_search_tree_recursive_check(
					    __a :     TreeNode | None						,__a :     float						,__a :     float      ) -> bool:

										if node is None:
															return True

										return (
										    left_bound < node.data < right_bound
										    and is_binary_search_tree_recursive_check(node.left						,__a						,node.data      )
										    and is_binary_search_tree_recursive_check(
										        node.right						,node.data						,__a      )
										)

					return is_binary_search_tree_recursive_check(__a						,-float('''inf'''      )						,float('''inf'''      )      )


if __name__ == "__main__":
			import doctest

			doctest.testmod()



