





"""simple docstring"""




import json
import sys



def        __lowercase       (				_SCREAMING_SNAKE_CASE			,						_SCREAMING_SNAKE_CASE     )			->       Any:


      '''simple docstring'''


      with open(_SCREAMING_SNAKE_CASE			,						encoding="""utf-8"""     ) as f:
            SCREAMING_SNAKE_CASE		=						json.load(_SCREAMING_SNAKE_CASE     )

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

      for benchmark_name in sorted(_SCREAMING_SNAKE_CASE     ):
            SCREAMING_SNAKE_CASE		=						results[benchmark_name]

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

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

                  SCREAMING_SNAKE_CASE		=						F""" {new_val:f}""" if isinstance(_SCREAMING_SNAKE_CASE			,						(int, float)     ) else """None"""

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

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

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

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

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


if __name__ == "__main__":
      SCREAMING_SNAKE_CASE_						       =	sys.argv[1]
      SCREAMING_SNAKE_CASE_						       =	sys.argv[2]

      format_json_to_md(input_json_file, output_md_file)









import unittest
from dataclasses import dataclass

import pytest

from accelerate.commands.config.config_args import SageMakerConfig
from accelerate.utils import ComputeEnvironment
from accelerate.utils.launch import _convert_nargs_to_dict

@dataclass
class 		UpperCamelCase__			(				lowerCAmelCase_       ):



     '''simple docstring'''

     __snake_case   :     int		     =      ComputeEnvironment.AMAZON_SAGEMAKER
     __snake_case   :     List[Any]		     =      True
     __snake_case   :     Optional[int]		     =      "ml.p3.2xlarge"
     __snake_case   :     List[str]		     =      "accelerate_sagemaker_execution_role"
     __snake_case   :     Tuple		     =      "hf-sm"
     __snake_case   :     Any		     =      "us-east-1"
     __snake_case   :     Union[str, Any]		     =      1
     __snake_case   :     Dict		     =      "accelerate-sagemaker-1"
     __snake_case   :     Tuple		     =      "1.6"
     __snake_case   :     List[str]		     =      "4.4"
     __snake_case   :     str		     =      "train.py"
     __snake_case   :     List[str]		     =      [
         "--model_name_or_path",
         "bert",
         "--do_train",
         "False",
         "--epochs",
         "3",
         "--learning_rate",
         "5e-5",
         "--max_steps",
         "50.5",
     ]
     __snake_case   :     Optional[int]		     =      [
         "--model_name_or_path",
         "bert",
         "--do_train",
         "--do_test",
         "False",
         "--do_predict",
         "--epochs",
         "3",
         "--learning_rate",
         "5e-5",
         "--max_steps",
         "50.5",
     ]

class 		UpperCamelCase__			(				unittest.TestCase       ):



     '''simple docstring'''

     def     SCREAMING_SNAKE_CASE__  (							self						:   Union[str, Any]	)					->		int:




           '''simple docstring'''


           SCREAMING_SNAKE_CASE		=						_convert_nargs_to_dict(MockLaunchConfig.success_training_script_args	)
           assert isinstance(converted_args["""model_name_or_path"""]						,lowerCamelCase__	)
           assert isinstance(converted_args["""do_train"""]						,lowerCamelCase__	)
           assert isinstance(converted_args["""epochs"""]						,lowerCamelCase__	)
           assert isinstance(converted_args["""learning_rate"""]						,lowerCamelCase__	)
           assert isinstance(converted_args["""max_steps"""]						,lowerCamelCase__	)

           with pytest.raises(lowerCamelCase__	):
                 _convert_nargs_to_dict(MockLaunchConfig.fail_training_script_args	)


