

"""simple docstring"""




import json
import sys



def 	UpperCAmelCase__   (				A__	,    A__   )      ->      Optional[int]:




   """simple docstring"""
   with open(A__	,    encoding="utf-8"   ) as f:
      lowerCamelCase__						=			json.load(A__   )

   lowerCamelCase__						=			["<details>", "<summary>Show updated benchmarks!</summary>", " "]

   for benchmark_name in sorted(A__   ):
      lowerCamelCase__						=			results[benchmark_name]

      lowerCamelCase__						=			benchmark_name.split("/"   )[-1]
      output_md.append(f'### Benchmark: {benchmark_file_name}'   )

      lowerCamelCase__						=			"| metric |"
      lowerCamelCase__						=			"|--------|"
      lowerCamelCase__						=			"| new / old (diff) |"
      for metric_name in sorted(A__   ):
         lowerCamelCase__						=			benchmark_res[metric_name]
         lowerCamelCase__						=			metric_vals["new"]
         lowerCamelCase__						=			metric_vals.get("old"	,    A__   )
         lowerCamelCase__						=			metric_vals.get("diff"	,    A__   )

         lowerCamelCase__						=			f' {new_val:f}' if isinstance(A__	,    (int, float)   ) else "None"

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

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

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

   output_md.append("</details>"   )

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


if __name__ == "__main__":
     SCREAMING_SNAKE_CASE_     :			List[str]	  =			sys.argv[1]
     SCREAMING_SNAKE_CASE_     :			Optional[Any]	  =			sys.argv[2]

     format_json_to_md(input_json_file, output_md_file)







"""simple docstring"""




import copy

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


SCREAMING_SNAKE_CASE_     :			Dict	  =			logging.get_logger(__name__)


class 		_A       (			__a					):
      __a								=	'encoder-decoder'
      __a								=	True





      def __init__(  self    ,						**SCREAMING_SNAKE_CASE__		)   ->					Optional[int]:
         super().__init__(**SCREAMING_SNAKE_CASE__		)
         assert (
             "encoder" in kwargs and "decoder" in kwargs
         ), "Config has to be initialized with encoder and decoder config"
         lowerCamelCase__						=			kwargs.pop("encoder"		)
         lowerCamelCase__						=			encoder_config.pop("model_type"		)
         lowerCamelCase__						=			kwargs.pop("decoder"		)
         lowerCamelCase__						=			decoder_config.pop("model_type"		)

         from ..auto.configuration_auto import AutoConfig

         lowerCamelCase__						=			AutoConfig.for_model(SCREAMING_SNAKE_CASE__    ,						**SCREAMING_SNAKE_CASE__		)
         lowerCamelCase__						=			AutoConfig.for_model(SCREAMING_SNAKE_CASE__    ,						**SCREAMING_SNAKE_CASE__		)
         lowerCamelCase__						=			True





      @classmethod
      def 					_lowerCamelCase  (  cls    ,						SCREAMING_SNAKE_CASE__    ,						SCREAMING_SNAKE_CASE__    ,						**SCREAMING_SNAKE_CASE__		)   ->					PretrainedConfig:
         logger.info("Set `config.is_decoder=True` and `config.add_cross_attention=True` for decoder_config"		)
         lowerCamelCase__						=			True
         lowerCamelCase__						=			True

         return cls(encoder=encoder_config.to_dict()    ,						decoder=decoder_config.to_dict()    ,						**SCREAMING_SNAKE_CASE__		)





      def 					_lowerCamelCase  (  self		)   ->					int:
         lowerCamelCase__						=			copy.deepcopy(self.__dict__		)
         lowerCamelCase__						=			self.encoder.to_dict()
         lowerCamelCase__						=			self.decoder.to_dict()
         lowerCamelCase__						=			self.__class__.model_type
         return output




