
"""simple docstring"""





import json
import sys



def 				lowerCamelCase__		(      __snake_case,					__snake_case     )							->		Union[str, Any]:


					"""simple docstring"""





					with open(__snake_case,					encoding='''utf-8'''     ) as f:
										_UpperCamelCase										=  json.load(__snake_case     )

					_UpperCamelCase										=  ['''<details>''', '''<summary>Show updated benchmarks!</summary>''', ''' ''']

					for benchmark_name in sorted(__snake_case     ):
										_UpperCamelCase										=  results[benchmark_name]

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

										_UpperCamelCase										=  '''| metric |'''
										_UpperCamelCase										=  '''|--------|'''
										_UpperCamelCase										=  '''| new / old (diff) |'''
										for metric_name in sorted(__snake_case     ):
															_UpperCamelCase										=  benchmark_res[metric_name]
															_UpperCamelCase										=  metric_vals['''new''']
															_UpperCamelCase										=  metric_vals.get('''old''',					__snake_case     )
															_UpperCamelCase										=  metric_vals.get('''diff''',					__snake_case     )

															_UpperCamelCase										=  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														=		sys.argv[1]
				_a														=		sys.argv[2]

				format_json_to_md(input_json_file, output_md_file)








"""simple docstring"""





from collections import OrderedDict
from typing import Mapping

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


_a														=		logging.get_logger(__name__)

_a														=		{
    """facebook/xlm-roberta-xl""": """https://huggingface.co/facebook/xlm-roberta-xl/resolve/main/config.json""",
    """facebook/xlm-roberta-xxl""": """https://huggingface.co/facebook/xlm-roberta-xxl/resolve/main/config.json""",
    # See all XLM-RoBERTa-XL models at https://huggingface.co/models?filter=xlm-roberta-xl
}






class    _UpperCAmelCase(   lowerCamelCase     ):
		lowercase__      =				'xlm-roberta-xl'



		def __init__( self    ,		__a=25_08_80    ,		__a=25_60    ,		__a=36    ,		__a=32    ,		__a=1_02_40    ,		__a="gelu"    ,		__a=0.1    ,		__a=0.1    ,		__a=5_14    ,		__a=1    ,		__a=0.02    ,		__a=1e-05    ,		__a=1    ,		__a=0    ,		__a=2    ,		__a="absolute"    ,		__a=True    ,		__a=None    ,		**__a    ,		)	->	Tuple:






							'''simple docstring'''
							super().__init__(pad_token_id=__a    ,		bos_token_id=__a    ,		eos_token_id=__a    ,		**__a)
							_UpperCamelCase										=  vocab_size
							_UpperCamelCase										=  hidden_size
							_UpperCamelCase										=  num_hidden_layers
							_UpperCamelCase										=  num_attention_heads
							_UpperCamelCase										=  hidden_act
							_UpperCamelCase										=  intermediate_size
							_UpperCamelCase										=  hidden_dropout_prob
							_UpperCamelCase										=  attention_probs_dropout_prob
							_UpperCamelCase										=  max_position_embeddings
							_UpperCamelCase										=  type_vocab_size
							_UpperCamelCase										=  initializer_range
							_UpperCamelCase										=  layer_norm_eps
							_UpperCamelCase										=  position_embedding_type
							_UpperCamelCase										=  use_cache
							_UpperCamelCase										=  classifier_dropout






class    _UpperCAmelCase(   lowerCamelCase     ):



		@property
		def 						UpperCAmelCase							( self)	->	Mapping[str, Mapping[int, str]]:






							'''simple docstring'''
							if self.task == "multiple-choice":
												_UpperCamelCase										=  {0: '''batch''', 1: '''choice''', 2: '''sequence'''}
							else:
												_UpperCamelCase										=  {0: '''batch''', 1: '''sequence'''}
							return OrderedDict(
							    [
							        ('''input_ids''', dynamic_axis),
							        ('''attention_mask''', dynamic_axis),
							    ])






