
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					   ={
    """roberta-base""": """https://huggingface.co/roberta-base/resolve/main/config.json""",
    """roberta-large""": """https://huggingface.co/roberta-large/resolve/main/config.json""",
    """roberta-large-mnli""": """https://huggingface.co/roberta-large-mnli/resolve/main/config.json""",
    """distilroberta-base""": """https://huggingface.co/distilroberta-base/resolve/main/config.json""",
    """roberta-base-openai-detector""": """https://huggingface.co/roberta-base-openai-detector/resolve/main/config.json""",
    """roberta-large-openai-detector""": """https://huggingface.co/roberta-large-openai-detector/resolve/main/config.json""",
}





class 							A__		(	__SCREAMING_SNAKE_CASE):
      _UpperCAmelCase				:    Tuple           =			"""roberta"""
      def __init__(      self    ,  __magic_name__=5_0_2_6_5    ,  __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		:	Union[str, Any]							=      vocab_size
       lowerCamelCase		:	Optional[int]							=      hidden_size
       lowerCamelCase		:	Optional[int]							=      num_hidden_layers
       lowerCamelCase		:	Tuple							=      num_attention_heads
       lowerCamelCase		:	Union[str, Any]							=      hidden_act
       lowerCamelCase		:	int							=      intermediate_size
       lowerCamelCase		:	Dict							=      hidden_dropout_prob
       lowerCamelCase		:	Optional[Any]							=      attention_probs_dropout_prob
       lowerCamelCase		:	int							=      max_position_embeddings
       lowerCamelCase		:	int							=      type_vocab_size
       lowerCamelCase		:	Union[str, Any]							=      initializer_range
       lowerCamelCase		:	int							=      layer_norm_eps
       lowerCamelCase		:	Union[str, Any]							=      position_embedding_type
       lowerCamelCase		:	Any							=      use_cache
       lowerCamelCase		:	Dict							=      classifier_dropout





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






import json
import sys





def     _a					(						lowerCamelCase,	lowerCamelCase							):
 with open(lowerCamelCase,	encoding="""utf-8"""							) as f:
  lowerCamelCase		:	List[Any]							=      json.load(lowerCamelCase							)

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

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

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

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

   lowerCamelCase		:	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__":
      _lowerCamelCase					   =sys.argv[1]
      _lowerCamelCase					   =sys.argv[2]

      format_json_to_md(input_json_file, output_md_file)




