



'''simple docstring'''






import json
import sys


def  snake_case_     (					_lowerCAmelCase  :						Any   ,      _lowerCAmelCase  :						Dict  )      ->   Any:
							with open(_lowerCAmelCase   ,      encoding='''utf-8'''  ) as f:
														UpperCAmelCase :       List[Any] 							=		json.load(_lowerCAmelCase  )

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

							for benchmark_name in sorted(_lowerCAmelCase  ):
														UpperCAmelCase :       List[Any] 							=		results[benchmark_name]

														UpperCAmelCase :       Union[str, Any] 							=		benchmark_name.split('''/'''  )[-1]
														output_md.append(f"""### Benchmark: {benchmark_file_name}"""  )

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

																					UpperCAmelCase :       Dict 							=		f""" {new_val:f}""" if isinstance(_lowerCAmelCase   ,      (int, float)  ) else """None"""

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

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

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

							output_md.append('''</details>'''  )

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


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

						format_json_to_md(input_json_file, output_md_file)







from collections import OrderedDict
from typing import Mapping

from ...configuration_utils import PretrainedConfig
from ...onnx import OnnxConfig
from ...utils import logging


_lowerCamelCase					   =logging.get_logger(__name__)

_lowerCamelCase					   ={
    """camembert-base""": """https://huggingface.co/camembert-base/resolve/main/config.json""",
    """umberto-commoncrawl-cased-v1""": (
        """https://huggingface.co/Musixmatch/umberto-commoncrawl-cased-v1/resolve/main/config.json"""
    ),
    """umberto-wikipedia-uncased-v1""": (
        """https://huggingface.co/Musixmatch/umberto-wikipedia-uncased-v1/resolve/main/config.json"""
    ),
}





class 							A__		(	__SCREAMING_SNAKE_CASE):
      _UpperCAmelCase				:    Tuple           =			"""camembert"""
      def __init__(      self    ,  __magic_name__=3_0_5_2_2    ,  __magic_name__=7_6_8    ,  __magic_name__=1_2    ,  __magic_name__=1_2    ,  __magic_name__=3_0_7_2    ,  __magic_name__="gelu"    ,  __magic_name__=0.1    ,  __magic_name__=0.1    ,  __magic_name__=5_1_2    ,  __magic_name__=2    ,  __magic_name__=0.02    ,  __magic_name__=1e-12    ,  __magic_name__=1    ,  __magic_name__=0    ,  __magic_name__=2    ,  __magic_name__="absolute"    ,  __magic_name__=True    ,  __magic_name__=None    ,  **__magic_name__    ,  ):
       super().__init__(pad_token_id=__magic_name__    ,  bos_token_id=__magic_name__    ,  eos_token_id=__magic_name__    ,  **__magic_name__      )

       lowerCamelCase		:	int							=      vocab_size
       lowerCamelCase		:	int							=      hidden_size
       lowerCamelCase		:	int							=      num_hidden_layers
       lowerCamelCase		:	int							=      num_attention_heads
       lowerCamelCase		:	Optional[int]							=      hidden_act
       lowerCamelCase		:	List[Any]							=      intermediate_size
       lowerCamelCase		:	Tuple							=      hidden_dropout_prob
       lowerCamelCase		:	Optional[int]							=      attention_probs_dropout_prob
       lowerCamelCase		:	Optional[int]							=      max_position_embeddings
       lowerCamelCase		:	str							=      type_vocab_size
       lowerCamelCase		:	Optional[Any]							=      initializer_range
       lowerCamelCase		:	int							=      layer_norm_eps
       lowerCamelCase		:	Any							=      position_embedding_type
       lowerCamelCase		:	Optional[int]							=      use_cache
       lowerCamelCase		:	Union[str, Any]							=      classifier_dropout





class 							A__		(	__SCREAMING_SNAKE_CASE):
      @property
      def 						UpperCamelCase__							(      self      ):
       if self.task == "multiple-choice":
        lowerCamelCase		:	List[str]							=      {0: """batch""", 1: """choice""", 2: """sequence"""}
       else:
        lowerCamelCase		:	List[str]							=      {0: """batch""", 1: """sequence"""}
       return OrderedDict(
           [
               ("""input_ids""", dynamic_axis),
               ("""attention_mask""", dynamic_axis),
           ]      )




