






"""simple docstring"""



import json
import sys

def 					_snake_case							(	lowerCamelCase__      :       Tuple							,		lowerCamelCase__      :       List[Any]    )							->      Optional[int]:
							with open(__snake_case							,		encoding="utf-8"    ) as f:
														lowerCamelCase_			:				Optional[int]										=json.load(__snake_case    )

							lowerCamelCase_			:				Any										=["<details>", "<summary>Show updated benchmarks!</summary>", " "]

							for benchmark_name in sorted(__snake_case    ):
														lowerCamelCase_			:				List[Any]										=results[benchmark_name]

														lowerCamelCase_			:				Any										=benchmark_name.split("/"    )[-1]
														output_md.append(F"""### Benchmark: {benchmark_file_name}"""    )

														lowerCamelCase_			:				List[Any]										="| metric |"
														lowerCamelCase_			:				str										="|--------|"
														lowerCamelCase_			:				Any										="| new / old (diff) |"
														for metric_name in sorted(__snake_case    ):
																					lowerCamelCase_			:				List[Any]										=benchmark_res[metric_name]
																					lowerCamelCase_			:				Optional[Any]										=metric_vals["new"]
																					lowerCamelCase_			:				Optional[int]										=metric_vals.get("old"							,		__snake_case    )
																					lowerCamelCase_			:				Tuple										=metric_vals.get("diff"							,		__snake_case    )

																					lowerCamelCase_			:				Tuple										=F""" {new_val:f}""" if isinstance(__snake_case							,		(int, float)    ) else "None"

																					if old_val is not None:
																												val_str += F""" / {old_val:f}""" if isinstance(__snake_case							,		(int, float)    ) else "None"
																					if dif_val is not None:
																												val_str += F""" ({dif_val:f})""" if isinstance(__snake_case							,		(int, float)    ) else "None"

																					title += " " + metric_name + " |"
																					lines += "---|"
																					value += val_str + " |"

														output_md += [title, lines, value, " "]

							output_md.append("</details>"    )

							with open(__snake_case							,		"w"							,		encoding="utf-8"    ) as f:
														f.writelines("\n".join(__snake_case    )    )


if __name__ == "__main__":
						A__			:							Tuple					   =   sys.argv[1]
						A__			:							str					   =   sys.argv[2]

						format_json_to_md(input_json_file, output_md_file)








"""simple docstring"""






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


__snake_case				:  Dict =       logging.get_logger(__name__)

__snake_case				:  int =       {
    '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      A__  (    __SCREAMING_SNAKE_CASE				):




	'''simple docstring'''





	SCREAMING_SNAKE_CASE        =      'visual_bert'

	def __init__(	self:						int			,     _SCREAMING_SNAKE_CASE:						Dict=3_0522			,     _SCREAMING_SNAKE_CASE:						Union[str, Any]=768			,     _SCREAMING_SNAKE_CASE:						List[str]=512			,     _SCREAMING_SNAKE_CASE:						Optional[int]=12			,     _SCREAMING_SNAKE_CASE:						List[str]=12			,     _SCREAMING_SNAKE_CASE:						Tuple=3072			,     _SCREAMING_SNAKE_CASE:						Union[str, Any]="gelu"			,     _SCREAMING_SNAKE_CASE:						Tuple=0.1			,     _SCREAMING_SNAKE_CASE:						str=0.1			,     _SCREAMING_SNAKE_CASE:						List[Any]=512			,     _SCREAMING_SNAKE_CASE:						Any=2			,     _SCREAMING_SNAKE_CASE:						Optional[int]=0.02			,     _SCREAMING_SNAKE_CASE:						Union[str, Any]=1e-12			,     _SCREAMING_SNAKE_CASE:						List[str]=False			,     _SCREAMING_SNAKE_CASE:						int=True			,     _SCREAMING_SNAKE_CASE:						str=1			,     _SCREAMING_SNAKE_CASE:						Tuple=0			,     _SCREAMING_SNAKE_CASE:						Any=2			,     **_SCREAMING_SNAKE_CASE:						List[str]			,     )							->			str:

				"""simple docstring"""

				super().__init__(pad_token_id=_SCREAMING_SNAKE_CASE			,     bos_token_id=_SCREAMING_SNAKE_CASE			,     eos_token_id=_SCREAMING_SNAKE_CASE			,     **_SCREAMING_SNAKE_CASE)

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